research paper on water logging

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Front Plant Sci

Mechanisms of Waterlogging Tolerance in Plants: Research Progress and Prospects

1 School of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China

2 Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China

Rahat Sharif

Xuehao chen.

Waterlogging is one of the main abiotic stresses suffered by plants. Inhibition of aerobic respiration during waterlogging limits energy metabolism and restricts growth and a wide range of developmental processes, from seed germination to vegetative growth and further reproductive growth. Plants respond to waterlogging stress by regulating their morphological structure, energy metabolism, endogenous hormone biosynthesis, and signaling processes. In this updated review, we systematically summarize the changes in morphological structure, photosynthesis, respiration, reactive oxygen species damage, plant hormone synthesis, and signaling cascades after plants were subjected to waterlogging stress. Finally, we propose future challenges and research directions in this field.

Introduction

Plants achieve normal growth through the coordination of water absorption by the roots with transpiration from the leaves. Sufficient water is a prerequisite for normal growth of plants, but saturation of the soil water-holding capacity, or even super-saturation, easily leads to waterlogging stress. The inhibition of root respiration and accumulation of toxic substances during waterlogging stress have adverse effects not only on vegetative growth, but also on reproductive growth, eventually leading to yield loss or even complete harvest failure ( Hirabayashi et al., 2013 ; Xu et al., 2014 ; Herzog et al., 2016 ; Tian et al., 2019 ; Ding et al., 2020 ; Zhou et al., 2020 ). Therefore, in the context of global warming, with predictions of more frequent and/or heavy rainfall and frequent flood disasters, there is a pressing need to study plant waterlogging tolerance and its mechanisms in order to maintain successful agriculture and promote effective adaptations to the changing climate ( Bailey-Serres et al., 2012 ; Nishiuchi et al., 2012 ; Mondal et al., 2020 ).

During waterlogging, leaf stomata close, whereas chlorophyll degradation, leaf senescence, and yellowing reduce the ability of leaves to capture light and ultimately lead to a decline in photosynthetic rate ( Kuai et al., 2014 ; Yan et al., 2018 ). Waterlogging removes air from soil pores, resulting in blocked gas exchange between soil and atmosphere; at the same time, the oxygen diffusion rate in water is only 1/10,000 of that in air. Consequently, oxygen availability in waterlogged soil is greatly restricted, resulting in suppressed roots respiration, decreased root activity, and energy shortage ( van Veen et al., 2014 ). Plants can temporarily maintain energy production to some extent during hypoxia caused by waterlogging, via glycolysis and ethanol fermentation. However, prolonged duration of waterlogging and anaerobic respiration ultimately leads to the accumulation of toxic metabolites such as lactic acid, ethanol, and aldehydes, combined with an increases in reactive oxygen species (ROS), notably hydrogen peroxide, thus eventually leading to cell death and plant senescence ( Xu et al., 2014 ; Zhang P. et al., 2017 ). Hindered gaseous exchange can also lead to rapid accumulation or degradation of plant hormones and further affect plant waterlogging tolerance ( Hattori et al., 2009 ; Kuroha et al., 2018 ). Although most plants perform poorly when waterlogged, they can adapt to the damage caused by such environmental stress through various strategies ( Fukao et al., 2006 ; Xu et al., 2016 ; Doupis et al., 2017 ; Yin et al., 2019 ).

The flooding stress, which further causes the submergence; hypoxia; and waterlogging stress are the main limiting factors of crop productivity. Flooding imposes submergence and ultimately raises the ground water table, which creates a hypoxic condition in the rhizosphere. The hypoxic condition in the rhizosphere restricts the oxygen uptake by causing an anaerobic environment, which further leads to plant death ( Fukao et al., 2019 ), Therefore, the flooding, submergence, and waterlogging stress are interconnected and affect the plant in nearly similar fashion ( Fukao et al., 2019 ).

In this updated review, we summarize the progress of research on plant adaptations to waterlogging stress with a focus on six aspects: morphological and anatomical adaptations, photosynthesis, respiration, ROS injury, plant hormone biosynthesis and signaling cascades, and genetic engineering in enhancing tolerance of plant against waterlogging stress ( Figure 1 ). Finally, the future challenges and research direction in this field are discussed, aiming to provide a source of reference and recommendations for further research on plant waterlogging resistance.

Schematic representation of plant response to waterlogging stress and hormonal effects resistance in plants.

Morphological and Anatomical Adaptation

Most plants are sensitive to waterlogging, as the diffusion rates of O 2 and CO 2 in roots and stems of plants decrease significantly during waterlogging, and photosynthesis and respiration are significantly inhibited. However, various morphological changes occur in some plants and can relieve root respiratory depression and damage caused by disrupted energy metabolism under waterlogging. Morphological changes are mainly manifested as the formation of adventitious roots (ARs) or other aeration tissues, rapid elongation of apical meristematic tissue, barriers to radial oxygen loss (ROL), and the formation of air films in the upper cuticle ( Hattori et al., 2009 ; Pedersen et al., 2009 ; Yamauchi et al., 2017 ; Qi et al., 2019 ).

Formation of ARs is a typical adaptive change in morphology ( Steffens and Rasmussen, 2016 ). During extended waterlogging, ARs develop in the internodes on the hypocotyl or at the base of the stem, where they promote the exchange of gases and the absorption of water and nutrients. To a certain extent, AR formation can replace the primary roots that die because of hypoxia stress, maintaining metabolic cycles, and enabling normal growth and development ( Xu et al., 2016 ; Eysholdt−Derzsó and Sauter, 2019 ). The newly formed ARs contain more aerenchyma than the primary roots, which augment both O 2 uptake and diffusion ability ( Visser and Voesenek, 2005 ).

Programmed cell death and degradation occur in cortical cells of plant root under hypoxia, producing tissue cavities and leading to aerenchyma formation. Aerenchyma not only can transport O 2 from non-waterlogged tissue to the root system, but also discharge CO 2 and toxic volatile substances from waterlogged tissue. Therefore, aerenchyma provides the possibility of gas exchange within plants and is vital for maintaining the normal physiological metabolism in the cells of waterlogged roots ( Drew et al., 2000 ; Evans, 2004 ; Yamauchi et al., 2013 ).

Radial oxygen loss refers to the fact that O 2 can be consumed by respiration during the longitudinal transport of O 2 along the aerenchyma to the root tip and can also be lost by lateral leakage into the intercellular spaces of the rhizosphere ( Yamauchi et al., 2018 ). Plants are able to produce a barrier to ROL, thereby reducing the loss of O 2 to the intercellular spaces of the rhizosphere and O 2 diversion between and around the root tip ( Pedersen et al., 2020 ). Abiko and Miyasaka (2020) used methylene blue to stain the ARs of taro [ Colocasia esculenta (L.) Schott] after 8 days of waterlogging and found that the root tips turned blue, whereas no blue areas appeared in the middle sections of the roots. This indicated that O 2 leakage was detected only near the root tip along the intercellular spaces of the rhizosphere, as the ROL barrier was formed in the middle of the root and prevented lateral losses ( Shiono et al., 2011 ). The formation of the ROL barrier inhibited the release of O 2 in the primordia of aerenchyma in rice ( Oryza sativa ) after 12 h of waterlogging ( Shiono et al., 2011 ). Moreover, deepwater rice cultivars form a tighter ROL barrier under low oxygen conditions than upland rice ( Colmer, 2002 ).

The rapid elongation of plant apical meristems is another adaptation of plants to waterlogging. The rapid elongation of tender stems and internodes facilitates escape from the anoxic environment and contact with the air as soon as possible, thereby enabling normal respiration ( Kuroha et al., 2018 ). This response is known as low oxygen escape syndrome (LOES). Internodes of deepwater rice cultivars elongate rapidly: waterlogging induces accumulation of ethylene (ET) and promotes synthesis of gibberellins (GAs) (largely GA 4 ), thus promoting internode elongation ( Kuroha et al., 2018 ) (see also Waterlogging stress mediated by plant hormones).

As an adaptation to waterlogging, some plants maintain a gas film on the leaf surface when submerged ( Winkel et al., 2016 ; Kurokawa et al., 2018 ). The gas film promotes the entry of O 2 in darkness and CO 2 when in light, thus contributing to the maintenance of aerobic respiration and photosynthesis. After artificial removal of the gas film in waterlogged rice, the underwater net photosynthetic rate was found to be only 20% of that with the gas film in place ( Pedersen et al., 2009 ).

Photosynthetic Adaptation

During waterlogging, stomatal conductance of leaves decreases, stomatal resistance increases, stomatal closure increases, and absorption of CO 2 is reduced ( Li et al., 2010 ). However, plants need CO 2 and light for photosynthesis to maintain growth and development. Under prolonged waterlogging condition, the enzyme activities related to photosynthesis were inhibited; the chlorophyll synthesis ability of leaves decreased, leading to leaf senescence, yellowing, and peeling; the formation of new leaves was blocked, and then the photosynthetic rate decreased, finally leading to death of the plants ( Voesenek et al., 2006 ; Wu and Yang, 2016 ).

Photosynthetic pigments are the material basis of plant photosynthesis, and the change of pigment content and composition directly affects the photosynthetic rate. Anee et al. (2019) conducted waterlogging experiments on sesame ( Sesamum indicum L.) seeds for 2, 4, 6, and 8 days to explore the changes in physiological and biochemical characteristics with time under waterlogging. The content of the photosynthetic pigments, chlorophyll A, B chlorophyll A + B, and carotenoids, was significantly lower in waterlogged seeds than in the unwaterlogged control; as the content of photosynthetic pigments decreased, the photosynthetic capacity also decreased.

The enzyme rubisco catalyzes the first step of both the photosynthetic carbon cycle and photorespiration and plays a key role in regulating the photosynthetic rate. After 24 h upon waterlogging stress, the expression of rubisco and rubisco activase genes in cotton ( Gossypium hirsutum L.) leaves was down-regulated; a reduction in net photosynthetic rate of cotton was mainly caused by lower rubisco activity. Sucrose and starch are the main products of photosynthesis in most plants. Sucrose is the main transport carbohydrate from source to sink, a process that is very sensitive to waterlogging. The decreased photosynthetic rate, sucrose conversion rate, and initial rubisco activity directly reduced the boll weight of waterlogged cotton. The enzyme sucrose synthase is central to the metabolic breakdown of sucrose required for cellulose biosynthesis; increased gene expression and enzyme activity of sucrose synthase during waterlogging were associated with prolonging the period of rapid accumulation of seed fiber weight, tending to reduce the phenomenon of boll weight decline caused by waterlogging ( Kuai et al., 2014 ).

Respiratory Adaptation

The generation of energy is crucial for plant growth and development. The lack of energy caused by hypoxia and consequent inhibition of root respiration are some of the most serious problems faced by plants under waterlogging ( Loreti et al., 2016 ). In cultivated soil, the concentration of dissolved oxygen in water is generally approximately 0.23 mol/m 3 , whereas in waterlogged conditions, the concentration of dissolved oxygen in water is less than 0.05 mmol/m 3 . The diffusion rate of O 2 in waterlogged soil is only 1/10,000 of that in the air. O 2 is the electron acceptor at the end of the mitochondrial electron transport chain. Decreased O 2 availability rapidly inhibits the production of adenosine triphosphate (ATP) by interfering with the electron transport chain, leading to inhibition of mitochondrial respiration ( Bailey-Serres and Voesenek, 2008 ; Limami et al., 2014 ). Plants need to obtain the necessary energy supply through glycolysis and ethanol fermentation so as to cope with the energy shortage caused by waterlogging stress ( Baxter-Burrell et al., 2002 ). However, 1 mol glucose can produce 36 to 38 mol ATP through the tricarboxylic acid cycle, whereas only 2 mol ATP can be obtained through glycolysis and ethanol fermentation. Therefore, plants need to accelerate glycolysis and ethanol fermentation in order to obtain the necessary amounts of ATP needed to sustain life.

Pyruvate accumulated from glycolysis can be used for anaerobic fermentation. Pyruvate fermentation produces energy in two different ways, producing lactic acid either via lactate dehydrogenase (LDH) or via pyruvate decarboxylase (PDC) turning pyruvate into acetaldehyde, which is then reduced to ethanol by alcohol dehydrogenase (ADH) ( Zabalza et al., 2009 ; Caruso et al., 2012 ; Borella et al., 2019 ). ADH and PDC play key roles in the ethanol fermentation pathway, and their activity is usually considered as one of the important indexes reflecting the tolerance of plants to waterlogging. Waterlogging-tolerant plants can improve the ethanol fermentation rate by regulating the expression of ADH , PDC , and other related enzyme genes, which can temporarily provide energy for the growth of plants under waterlogging ( Zhang P. et al., 2017 ). Therefore, fermentation is a necessary process of energy metabolism under waterlogging, as shown by the up-regulated expression of anaerobic metabolism genes such as PDCs and ADHs in cucumber, cotton, and soybean ( Komatsu et al., 2011 ; Xu et al., 2014 ; Zhang et al., 2015 ). The seed germination ability of GmADH2 -transgenic soybeans was enhanced under waterlogging, and the GmADH2 gene was induced during glycolysis and ethanol fermentation ( Tougou et al., 2012 ). The overexpression of kiwifruit PDC1 gene in transgenic Arabidopsis enhanced waterlogging tolerance ( Zhang J.Y. et al., 2016 ). These results indicate that PDC and ADH genes play key roles in plant waterlogging tolerance.

Lactate dehydrogenase also participates in the waterlogging stress response, alongside PDC and ADH. Overexpression of LDH significantly enhanced the PDC activity and hypoxia resistance of Arabidopsis , whereas LDH loss of function mutant ldh showed the opposite phenotype ( Dolferus et al., 2008 ). Therefore, lactic acid fermentation is an important pathway in response to waterlogging stress in some plants. The transcript abundances of the ethanol dehydrogenase genes ADH1-1 , ADH1-2 , ADH1-3 , and PDC genes PDC1 and PDC2 were down-regulated in Petunia plants in which an ET-responsive element–binding factor PhERF2 was silenced, whereas they were up-regulated in PhERF2- overexpressing plants. In contrast, the expression of LDH gene LDH was up-regulated in PhERF2- silenced lines and down-regulated in PhERF2- overexpressing lines. This result suggests that the main pathway for NAD + regeneration in PhERF- overexpressing plants is ethanol fermentation, whereas PhERF2- silenced plants might rely on lactic acid fermentation in response to waterlogging stress ( Yin et al., 2019 ).

Although the energy generated via glycolysis and ethanol fermentation can temporarily alleviate the energy deficiency caused by the inhibition of respiration in roots, the accumulation of toxic substances such as lactic acid, alcohols, aldehydes, and other anaerobic metabolites eventually leads to plant death as the time of waterlogging is prolonged ( Tamang et al., 2014 ).

Damage by Reactive Oxygen Species

Reactive oxygen species are a normal product of plant cell metabolism. Insufficient O 2 will also lead to increases in intracellular ROS under waterlogging stress ( Bailey-Serres and Chang, 2005 ; Pucciariello et al., 2012 ). For example, superoxide radicals (⋅O 2 ), hydroxyl radicals (⋅OH), and hydrogen peroxide (H 2 O 2 ) have strong oxidizing activity that can lead to lipid peroxidation and delipidation of leaf membranes, oxidative damage to proteins, oxidative damage to DNA, and severe damage to cell membranes and organelles ( Sharma et al., 2012 ; Baxter et al., 2014 ).

Although excessive ROS are harmful to plant cells, ROS can also act as signaling molecules in plant cells under stress. Plant NADPH oxidase is a key enzyme in the production of ROS and plays a vital role in ROS-mediated signal transduction. The expression of NADPH oxidase–related gene Atrboh D , a gene associated with ROS production, is induced by waterlogging and positively regulates the production of H 2 O 2 and the increase of ADH1 gene expression in Arabidopsis . Therefore, this signal improves the capacity for ethanol fermentation and increases the survival rate of plants under waterlogging ( Sun et al., 2018 ). Analysis of the atrboh d mutant by Yang and Hong (2015) showed that AtRboh D is involved in the primary hypoxia signaling pathway and can regulate the transcription of ET synthesis gene ACC synthetase7/8 (ACS7/8 ), as well as the regulation of hypoxia-induced downstream genes such as ERF73/HRE 1 and ADH1 and the expression of genes encoding peroxidase and cytoplasmic P450. Subsequently, Liu et al. (2017) analyzed the single mutant atrboh d and atrboh f and the double-mutant atrbohd/f. Both Atrboh D and Atrboh F play a role in hypoxia signal through the production of ROS, promoting the increase of Ca 2+ and mediating hypoxia-induced expression of downstream genes, such as ADH1 , PDC1 , ERF73 , MYB2 , LDH , SUS1 , SUS4 , HsfA2 , and HSP18.2 , thus improving the tolerance of Arabidopsis to hypoxia stress. These findings provide new insights into the adaptation mechanism of Rboh gene regulation under waterlogging stress in plants.

H 2 O 2 is an essential signaling molecule involved in ET-induced epidermal cell death. The formation of aerenchyma in rice stems is controlled by H 2 O 2 , indicating that ROS play a key role in regulating various cell death processes in rice ( Steffens et al., 2011 ). H 2 O 2 plays a role in primary hypoxia signaling by regulating ET signal transduction and modulating the transcription of downstream hypoxia-induced genes such as ERF73/HRE1 and ADH1 in Arabidopsis ( Yang, 2014 ). This signal promoted the capacity for ethanol fermentation, temporarily alleviated the energy shortage, and improved the adaptability of the plants to waterlogging.

Under waterlogging stress, plants can rely on antioxidant enzyme systems and other active antioxidants to maintain the dynamic balance of ROS, thus reducing the extent of oxidative damage ( Zhang et al., 2007 ; Bin et al., 2010 ; Doupis et al., 2017 ; Hasanuzzaman et al., 2020 ). Waterlogging treatment resulted in increased activities of catalase (CAT), ascorbate peroxidase (APX), and superoxide dismutase (SOD), as well as polyphenol oxidase. Furthermore, the enzyme activity of waterlogging-resistant lines was significantly higher than that of waterlogging-sensitive lines ( Bansal and Srivastava, 2012 ). Li (2007) took two cucumber varieties with significantly different waterlogging tolerance as test materials and found that the activities of SOD, POD, and CAT, as well as chlorophyll content, soluble sugar content, and CAT content of waterlogging-sensitive lines, decreased rapidly; there was no significant difference between waterlogging-resistant lines in the early stress (1–3 days) treatment and the control. After 3 days, they all decreased rapidly, but the extent of the decrease was smaller than that of waterlogging-sensitive lines. Several genotypes of maize were subjected to waterlogging stress. Genotypes withstanding the waterlogging stress displayed higher SOD, POD, and CAT activities ( Li et al., 2018 ). Similarly, induced SOD and CAT activities were observed in the Sorghum bicolor waterlogging-resistant lines JN01 and JZ31 ( Zhang R. et al., 2019 ). Waterlogging stress was given to barley-tolerant and -sensitive genotypes for 21 days to evaluate the antioxidant response ( Luan et al., 2018 ). The study revealed that SOD, POD, and CAT activities were increased in both the tolerant and sensitive genotypes ( Luan et al., 2018 ). It could be presumed that enhanced antioxidant activities under waterlogging stress can increase the tolerance of plant for a certain amount of time. However, extended waterlogging stress leads to the dysfunctioning of mitochondria, which is the key regulator of antioxidant enzyme activities ( Sharif et al., 2018 ).

The activity of APX in eggplant roots under waterlogging was higher than that of other antioxidant enzymes, and the activity of APX was higher than that of tomato. Consequently, eggplant had higher adaptation ability to waterlogging ( Lin et al., 2004 ). Lee et al. (2014) conducted waterlogging experiments on rapeseed seedlings and found that a CAT-encoding gene was down-regulated, whereas SOD and POD genes were up-regulated. CAT might be involved in controlling H 2 O 2 content by converting H 2 O 2 into O 2 . The down-regulation of this gene would then increase the content of H 2 O 2 in the leaves of rape seedlings and eventually damage the photosynthetic organs, leading to premature aging.

The application of exogenous regulatory substances is one of the main ways to improve the antioxidant capacity of waterlogged crops ( An et al., 2016 ). For example, application of γ-aminobutyric acid can increase the photosynthetic rate and chlorophyll content by triggering the activity of antioxidant enzymes (SOD, POD, CAT, GR, APX), suppress the malondialdehyde (MDA) contents and H 2 O 2 , and thus improve the waterlogging tolerance of maize ( Zea mays L.) ( Salah et al., 2019 ). The H 2 O 2 application at low concentrations can also induce plant tolerance to stress ( Hossain et al., 2015 ). In line with that, Andrade et al. (2018) pretreated soybean seeds with 70 mM H 2 O 2 solution for 24 h and then subjected the seedlings to waterlogging for 32 days. The obtained results revealed that H 2 O 2 pretreatment promoted the antioxidant system activity and net photosynthetic rate under waterlogging and at the same time reduced the production of ROS and the degree of cell membrane damage, conferring enhanced waterlogging tolerance of soybean. The above results indicate that the ROS-scavenging ability of plants can be enhanced by increasing in active antioxidant substances, and the waterlogging-resistant lines maintained high antioxidant enzyme activities that enabled them to resist oxidative damage caused by waterlogging.

Waterlogging Stress Mediated by Plant Hormones

Endogenous plant hormones are closely involved in the regulation of the entire life process of plants, and the balance of various hormones is the basis to ensure normal physiological metabolism, growth, and development of plants ( Bartoli et al., 2013 ; Miransari and Smith, 2014 ; Wang X. et al., 2020 ). The plant changes the balance of synthesis and transport of plant hormones and regulates the response to waterlogging via complex signaling. Plant hormones, as important endogenous signals, play a central role in the mechanism of waterlogging tolerance ( Benschop et al., 2006 ; Wu et al., 2019 ; Yamauchi et al., 2020 ). Some selected recent studies on phytohormones and plant growth regulator–mediated waterlogging tolerance in plants are presented in Table 1 . A model drawing together the interactions of the various signals, growth regulators, genes, and processes involved in the response of plants to waterlogging is summarized in Figure 2 .

Recent studies on phytohormones and plant growth regulator mediated waterlogging tolerance in plants.

Model of waterlogging response mechanism in plants. Arrows indicate positive stimuli; lines with blocked ends denote inhibitory effects. Waterlogging-tolerant plants can improve the rate of ethanol and lactic fermentation by enhancing the expression of ADHs , PDCs , and LDHs , whose gene products temporarily provide ATP for the growth of plants under waterlogging. OsEIL1a (an ethylene-responsive transcription factor) promotes SK1/2 transcription and also directly binds the promoter of GA biosynthesis gene SD1 , thereby increasing the synthesis of GA, which stimulates shoot elongation. Increased ethylene levels (ET) inhibit ABA biosynthesis, which leads to increased GA content and induces shoot elongation in deepwater rice cultivars. However, in non-deepwater cultivars, Sub1A negatively regulates the GA response by limiting the degradation of the GA signal inhibitor protein SLR1/SLRL1, which inhibits shoot elongation. An increased BR level in Sub1A rice genotype induces the expression of GA catabolism gene GA2ox7 , which represses GA signaling, so then shoot elongation is inhibited. In addition, the expression of ACS and ACO5 is induced in rice root aerenchyma under waterlogging, thereby promoting ethylene synthesis. Ethylene accumulation enhances auxin biosynthesis and transport, and vice versa . Ethylene enhances the expression of RBOH (NADPH oxidase, respiratory burst oxidase homolog) and induces ROS signals, which finally lead to the formation of ARs and aerenchyma. Furthermore, SA triggers a programmed cell death response, which leads to the development of aerenchyma cells. At the same time, the accumulation of SA stimulates the formation of AR primordia. JA inhibits AR growth and inhibits the action of SA under waterlogging. The application of MT enhanced tolerance to waterlogging stress by triggering the generation of PA biosynthesis, suppression of excessive ROS, and then improved photosynthetic machinery and aerobic respiration. Interestingly, the MT-treated plants under waterlogging stress exhibited decrease expression pattern of ethylene biosynthesis and signaling gene.

Ethylene is a gaseous hormone in plants, and its diffusion rate is extremely low in water. The rapid accumulation of ET is an important way in which plants respond to waterlogging ( Alpuerto et al., 2016 ; Hartman et al., 2019a,b ).

1-Aminocyclopropane-1-carboxylic acid (ACC), the direct precursor in the biosynthesis of ET, is produced in large quantities under the catalysis of ACC synthase (ACS), and the process can occur under hypoxic conditions. ACC is converted to ET under the catalysis of ACC oxidase (ACO), but the process needs the participation of O 2 ; thus, ACC needs to be continuously transferred from the hypoxic environment of the root system to the lower region of the plant’s aerobic part where the oxidation reaction can take place, finally producing ET. Rauf et al. (2013) found that waterlogging directly or indirectly activates the expression of ACO5 and ACS genes in Arabidopsis and increases ET biosynthesis.

ET synthesis and perception are necessary for AR formation. Waterlogging treatment was carried out on 4-week-old tomato ( Solanum lycopersicum ) seedlings, and 500 μM aminoethoxyvinylglycine (AVG), which inhibits ET biosynthesis, was sprayed on the above-ground parts daily. After 72 h of waterlogging, AR primordia became visible in the stem base of waterlogged plants that had not been treated with AVG, and these primordia elongated and generated a large number of ARs within 7 days. The number of ARs in tomato plants treated with the inhibitor AVG was significantly lower than in untreated plants ( Vidoz et al., 2010 ). Qi et al. (2019) found that treating cucumber seedlings with 1 mg/L 1-methylcyclopropene (1-MCP, an ET receptor inhibitor) before waterlogging inhibited the formation of ARs, whereas exogenous 10 μM ACC promoted the formation of ARs under waterlogging. Kim et al. (2018) not only significantly induced the occurrence of ARs on soybean plants but also increased the root surface area by exogenous application of 50, 100, or 200 μM ethephon, a synthetic plant growth regulator that produces ET when metabolized.

The production of endogenous ET is closely related to the development of aerenchyma cells ( Kreuzwieser and Rennenberg, 2014 ; Mignolli et al., 2020 ). The expression of ACS1 and ACO5 is induced in rice root aerenchyma under hypoxia and promotes ET synthesis. At the same time, ET induces cortical cell death, mediated by ROS, leading to aerenchyma formation ( Yamauchi et al., 2017 ). ET accumulates in roots under waterlogging as its biosynthesis continues and the diffusion rate in water is low. ET stimulates programmed cell death that occurs during the formation of lysogenic aerenchyma ( Sasidharan and Voesenek, 2015 ). The accumulation of ET triggers the formation of lysosomal aerenchyma in maize ( Yamauchi et al., 2016 ), rice ( Yamauchi et al., 2017 ), and wheat ( Yamauchi et al., 2014 ).

ET response factor ( ERF ) is an important transcription factor involved in plant responses to several different biotic and abiotic stresses. The ERF family genes specifically induce genes containing AGCCGCC elements and DRE/CRT cis -elements, activating or inhibiting the expression of downstream functional genes, and thereby mediating plant tolerance to various stresses ( Yin et al., 2019 ). ERF transcription factors are regulated by ET, and exogenous ET significantly promotes ERF transcription in Arabidopsis and soybean ( Hess et al., 2011 ; Tamang et al., 2014 ). ET regulates the response of Arabidopsis to hypoxia stress through ERF73/HRE1 ( Hess et al., 2011 ).

Group VII ET-response factors ( ERF -VIIs) play an important role in ET signal transduction and plant responses to waterlogging ( Gasch et al., 2016 ; Giuntoli and Perata, 2018 ). The gene ZmEREB180 , a member of the ERF -VII family in maize, positively regulates the growth and development of ARs and the level of ROS: overexpression of ZmEREB180 in maize also improves the survival rate after long-term waterlogging stress ( Yu et al., 2019 ). The PhERF2 protein binds directly with the promoter of ADH-related gene ADH1-2. PhERF2 -RNAi lines had a mortality rate of 96% after flooding. Almost all PhERF2- overexpressing lines survived and showed faster and stronger recovery than WT plants ( Yin et al., 2019 ).

The rice Sub1A ( Submergence1A ) gene is another member of the ET-response factor ERF -VII family. Overexpression of Sub1A enhanced the transcription of ADH1 in transgenic rice and at the same time led to the enhanced ability to withstand waterlogging stress. Therefore, Sub1A gene could be the main determinant of submergence tolerance ( Xu et al., 2006 ). Interestingly, the other two ERF -VII gene family members in rice, SK1/2 ( SNORKEL1/2 ), can also regulate the waterlogging tolerance of rice. Overexpression of SK1/2 led to internode elongation and significantly improved the waterlogging tolerance of deepwater rice cultivars ( Hattori et al., 2009 ).

However, Sub1A and SK1/2 have opposite functions in regulating rice growth in response to waterlogging. Sub1A negatively regulates the GA response by limiting the degradation of the DELLA family protein SLR1 (Slender Rice-1), which are GA signal inhibitors, and thereby inhibits the elongation of rice ( Fukao and Bailey-Serres, 2008 ; Hattori et al., 2009 ). Plants temporarily inhibit energy metabolism until water recedes, an effective long-term submergence strategy that occurs in rice mainly in non-deepwater cultivars ( Xu et al., 2006 ; Bailey-Serres and Voesenek, 2008 ). In contrast, SK1/2 stimulates GA synthesis, which promotes rapid growth of rice stems and internode petioles, a structural change that allows rice leaves to respire normally once they have extended away from the water. The reason was found to be that submersion induced ET accumulation in rice and positively regulated the stability of OsEIL1a , an ET-responsive transcription factor ( Kuroha et al., 2018 ). OsEIL1a protein promotes SK1/2 transcription by directly binding to the SK1/2 promoter, and then SK1/2 mediates the expression of downstream genes to initiate shoot elongation ( Kuroha et al., 2018 ). OsEIL1a also directly binds and transcribes the promoter of GA biosynthesis gene SEMIDWARF1 ( SD1 ), and SD1 protein promotes the synthesis of GA, mainly GA 4 , thus promoting shoot elongation ( Kuroha et al., 2018 ). This evidence indicates that the OsEIL1a–SD1–SK1/2 cascade is closely related to waterlogging tolerance in deepwater rice cultivars.

Abscisic Acid

Abscisic acid (ABA) has a main role in regulating stomata by adjusting the size of guard cells, thereby regulating the water potential in plants. Because of this, ABA is considered to be a key hormone in water stress responses ( Zhu, 2016 ; He et al., 2018 ).

Abscisic acid is involved in the development of root aerenchyma under waterlogging. The ABA concentration in soybean hypocotyls decreased rapidly under waterlogging, falling by 50% within 24 h compared with plants without waterlogging. In addition, secondary aeration tissues appeared after 72 h. Exogenous 1 μM ABA treatment inhibited the cell development of aerenchyma, suggesting that the formation of secondary aerenchyma required a reduction in the concentration of the negative regulatory factor ABA ( Shimamura et al., 2014 ).

During waterlogging stress of Solanum dulcamara , following the rapid down-regulation of ABA biosynthesis and up-regulation of ABA decomposition, the ABA concentration in the stem and AR primordia decreased sharply ( Dawood et al., 2016 ). Waterlogging resulted in ET accumulation in the lower stem and subsequently reduced ABA concentrations in the stem and AR primordia. 1 mM ABA treatment significantly inhibited the formation of ARs induced by waterlogging, whereas 100 μM ABA inhibitor (Fluridone) induced AR production ( Dawood et al., 2016 ). These results showed that ABA, in contrast to ET, negatively regulated the formation of ARs under waterlogging. Kim et al. (2015) determined the plant hormone content in soybeans after waterlogging for 5 and 10 days and found that the ABA content significantly decreased. The ABA content in waterlogging-resistant lines was significantly lower than that in sensitive lines, indicating that ABA might be negatively correlated with waterlogging tolerance. Waterlogging increased shoot elongation in deepwater rice cultivars partly by reducing the endogenous ABA content and thereby increasing the GA concentration ( Yang and Choi, 2006 ). Similarly, ET and its precursor ACC rapidly induced the expression of OsABA8ox1 . In addition, ET receptor inhibitor 1-MCP pretreatment partially inhibited the expression of OsABA8ox1 . These results indicated that the rapid decline of ABA in deepwater rice cultivars under waterlogging was partly controlled by ET-induced OsABA8ox1 expression ( Saika et al., 2007 ).

The relative expression of the kiwifruit ( Actinidia deliciosa ) gene AdPDC1 encoding pyruvate decarboxylase was significantly up-regulated under waterlogging, suggesting that the gene played an important role in the waterlogging response. ABA down-regulated the expression of AdPDC1 under waterlogging, whereas the overexpression of AdPDC1 in Arabidopsis inhibited seed germination and root elongation under ABA treatment, indicating that ABA might negatively regulate AdPDC1 under waterlogging ( Zhang J.Y. et al., 2016 ).

However, other studies have shown that accumulation of ABA accelerated in the above-ground parts of the plant under waterlogging. ABA increased the accumulation of H 2 O 2 and promoted stomatal closure, thus reducing the water loss from transpiration and improving the resistance of plants to waterlogging and related adverse environmental conditions. Overexpression of AP2/ERF family gene RAP2.6L in Arabidopsis promoted the expression of ABA biosynthesis genes, thus increasing ABA concentration. The increased ABA in RAP2.6L -overexpressing plants led to initiation of the antioxidant defense system and stomatal closure and finally resulted in reduced oxidative damage, delayed senescence, and significantly improved waterlogging tolerance ( Liu et al., 2012 ). A significant increase in ABA content induced by waterlogging has been reported in cotton ( Zhang Y. et al., 2016 ), wheat ( Nan et al., 2002 ), and other crops. Komatsu et al. (2013) found that addition of 5, 10, and 50 μM ABA during waterlogging significantly improved soybean survival compared with waterlogging treatment alone. Similarly, pretreatment with 10 μM ABA had recorded affirmative responses in rice net assimilation rate, relative growth rate, and chlorophyll content under submergence ( Saha et al., 2021 ).

Auxin (IAA) plays an important role in plant growth and development ( Kazan and Manners, 2009 ; Lv et al., 2019 ). ET production, as an early response to waterlogging, can promote the transport of auxin, and conversely, the accumulation of auxin can prompt ET biosynthesis, further stimulating auxin transport to flooded parts of the plant, where the accumulation of auxin can induce ARs by initiating cell division. Exogenous application of the auxin transport inhibitor 1-naphthylphthalamic acid (NPA) to tomato ( Vidoz et al., 2010 ), cucumber ( Qi et al., 2019 ), and tobacco ( McDonald and Visser, 2003 ) led to inhibition of AR growth after flooding.

The dynamic transport of auxin in plants is mediated by the auxin polar transport carrier protein PIN (PIN-FORMED), and treatment of rice with the transport inhibitor NPA decreased the expression of OsPIN2 , suggesting that NPA might inhibit the production of ARs through an effect on PIN ( Lin and Sauter, 2019 ). Similarly, when auxin polar transport was blocked in PIN expression–deficient mutants of S. dulcamara , the formation of ARs was inhibited, which further confirmed that AR production required auxin transport ( Dawood et al., 2016 ).

However, some studies found that waterlogging reduced the content of IAA in soybean plants. Shimamura et al. (2016) found that the hypocotyl could form ARs and aerenchyma after 72 h of waterlogging, but physiological tests showed no significant difference within 72 h in the endogenous IAA concentration in the hypocotyl between the waterlogged and the control groups. This result showed that the accumulation of IAA was not a necessary condition for the formation of secondary aerenchyma in soybean hypocotyls under waterlogging.

Waterlogging can cause a large amount of carbohydrate consumption in plants, leading to energy shortage. Qi et al. (2020) first proposed a model for the interaction of sugars with auxin-induced AR initiation and elongation in waterlogged cucumber. Under waterlogging stress and in light conditions, photosynthesis supported the biosynthesis of sugars, whose accumulation induced auxin transport and subsequent signal transduction, and finally induced the formation of ARs in the hypocotyl.

Gibberellin

GAs are one of the essential plant hormones regulating growth and development. GAs regulate multiple processes in plant growth and development, mainly by controlling the size and number of cells ( Nelissen et al., 2012 ).

Studies on different genotypes of soybean found that GA content in waterlogging-tolerant lines significantly increased under waterlogging, and GA content in waterlogging-resistant lines was significantly higher than that in waterlogging-sensitive lines ( Kim et al., 2015 ). Huang et al. (2018) determined physiological indexes of peanuts ( Arachis hypogaea ) under waterlogging and found that spraying GA on the leaf surface could promote the growth of upper and underground parts of peanut plants and significantly increase the yield. Wang et al. (2016) showed that exogenous GA could effectively reduce the MDA content in the leaves and roots of rape under waterlogged conditions, thus improving the tolerance of plants to waterlogging.

Treatment with inhibitors of GA biosynthesis significantly reduced internode elongation in rice under waterlogging ( Hattori et al., 2009 ; Ayano et al., 2014 ). Mutations in GA biosynthesis ( Os1 , OsCPS2 , OsKS2 , OsKS5 , OsKO2 , OsKAO , Os13ox , OsGA20ox1 , OsGA20ox2 , OsGA20ox3 , OsGA3ox1 , OsGA3ox2 ) and signal transduction genes ( OsGID1 , OsGID2 , OsSPY , OsSEC , OsGAMYB ) also inhibited internode elongation ( Ayano et al., 2014 ). Waterlogged rice plants treated with exogenous GA were able to restore internode elongation, enabling the leaves to respire normally once away from the flood water. GA has been shown to be a key hormone in improving rice tolerance under waterlogged conditions. Under waterlogging, GA participates in the SK1/2 gene-mediated response pathway, and the GA content is up-regulated, leading to internode elongation. This structural change causes rice to extend above the water surface and reestablish gas exchange between plant tissue and the air ( Hattori et al., 2009 ; Ayano et al., 2014 ). GA biosynthesis gene SD1 was shown to be the cause of internode elongation under waterlogging. When submerged, the SD1 gene was activated by OsEIL1a , an ET-responsive transcription factor, and SD1 protein promoted the synthesis of GA, mainly GA 4 , which promoted the rapid growth of leaf stalk internodes in rice ( Kuroha et al., 2018 ). The results indicated that GA is centrally involved in promoting internode elongation in rice under waterlogged conditions.

Salicylic Acid

Salicylic acid (SA) is a common phenolic compound in plants, which regulates the antioxidant mechanism of cells by inducing the expression of stress-related genes, thus enhancing the adaptability of plants to adverse conditions ( Zhou et al., 2009 ; Hayat et al., 2010 ; Arif et al., 2020 ).

Salicylic acid, as a signal substance, can induce changes in physiological characteristics of waterlogged plants. Peach trees ( Prunus persica L.) were subjected to waterlogging stress. Spraying exogenous SA on day 1 of waterlogging can significantly increase the activities of ethanol dehydrogenase, protective enzymes such as POD and CAT, and the content of proline in leaves and roots, thereby protecting leaves and root membranes from damage and stabilizing photosynthetic capacity of leaves as well as root activity. Together, these protective effects are conducive to the alleviation of waterlogging-induced stress ( Wang et al., 2015 ).

An increase of SA content might be an important factor in tolerance of waterlogging stress. Studies have shown that SA regulates two different physiological responses. First, an increase in intracellular SA triggers a programmed cell death response, leading to an increase in lipid peroxidation in the root cell walls, which in turn leads to the development of aerenchyma cells within the root. Aerenchyma cells can increase oxygen transfer into the root tissues and alleviate waterlogging stress. Second, the accumulation of SA stimulates the formation of AR primordia and further enhances waterlogging tolerance by inducing the development of a large number of ARs ( Kim et al., 2015 ).

Kim et al. (2015) measured SA content in soybean after 5 and 10 days of waterlogging and found that the content of SA in waterlogging-tolerant soybean PI408105A was significantly higher than that in the unstressed control, whereas the content of SA in waterlogging-sensitive soybean S99-2281 was not significantly different from that in the control. Elevated SA would stimulate the formation of ARs, promote gas exchange, and ultimately enhance waterlogging tolerance. Bai et al. (2009) found that spraying exogenous SA alleviated oxidative stress damage caused by hypoxia stress on plants, and enhanced the hypoxia tolerance of Begonia occidentalis . The above results indicate that appropriate SA level can promote the formation of ARs and aerenchyma, which is positively correlated with the waterlogging tolerance of plants.

Jasmonic Acid

Jasmonic acid (JA) is a basic plant growth regulator that is known to be involved in the defense response produced by abiotic stress, but there are few studies on the relationship between JA and waterlogging tolerance ( Per et al., 2018 ; Farhangi-Abriz and Ghassemi-Golezani, 2019 ; Raza et al., 2020 ; Wang J. et al., 2020 ).

Xu et al. (2016) found that the JA content in hypocotyl of Pepino, a waterlogging-sensitive cucumber line, was about twice that of the unstressed control after 2 days of waterlogging. However, JA content in the hypocotyl of the waterlogging-resistant line Zaoer-N decreased significantly during waterlogging to only 0.33 that of the control. The result suggested that JA is negatively correlated with the waterlogging tolerance of plants. However, other research showed that JA treatment inhibited root growth and the action of SA under waterlogging. Compared with the control, 649 different proteins were found in waterlogged soybeans treated with JA, which were mainly related to the stress response metabolite pathway, glycolysis, ethanol fermentation, and cell wall and cell tissue metabolism. The application of JA significantly reduced the damage to soybean plants under waterlogging and promoted plant growth by changing the proteomic profile ( Kamal and Komatsu, 2016 ). There can be significant differences in JA content in different tissues of the same plant under waterlogging conditions. Under waterlogging stress, the JA content in citrus leaves increased significantly compared with the unstressed control, but the JA concentration in the root system decreased sharply. This might be caused by inhibition of the key lipoxygenase of the JA synthesis pathway under hypoxic conditions ( Arbona and Gómez-Cadenas, 2008 ).

The interaction between JA and ET plays an important role in the formation and development of the root system and aerenchyma under waterlogging stress. Spraying methyl jasmonate on the leaves increased the content of ET ( Hudgins and Franceschi, 2004 ). Thus, exogenous JA can increase the content of ET, which is beneficial in relieving waterlogging stress.

Brassinosteroid

Brassinosteroid (BR) is a naturally occurring steroid in plants. BR can induce resistance to a variety of biological and abiotic stresses, thus promoting plant growth and development ( Bajguz and Hayat, 2009 ; Huang et al., 2020 ; Nazir et al., 2021 ).

Exogenous 24-epi-brassinolide (EBR) promotes the transfer of carbohydrates from leaves to roots of cucumber seedlings under hypoxic stress, enhances the activity of glycolytic enzymes in the roots, and triggers the antioxidant enzymes activity and reduced ROS production, thus improving the resistance of the seedlings to hypoxic stress ( Kang et al., 2009 ). EBR also improved enzyme activity related to cell wall degradation by promoting ET production in cucumber seedlings. It further promoted the expansion and loosening of cucumber hypocotyl and formation of ARs, thus improving the oxygen supply status of the plant and enhancing the tolerance of the plant to hypoxic stress ( Ma and Guo, 2014 ).

The Sub1A gene, an ET-response factor ERF-VII family member, has different regulatory effects on brassinolide biosynthetic gene expression and rice shoot elongation under waterlogging, compared with exogenous BR. Exogenous BR pretreatment can activate the tolerance mechanism in waterlogging-tolerant rice genotypes and inhibit shoot elongation under waterlogging. Compared to the LOES, higher expression of BR biosynthesis genes was observed in the Sub1A rice genotype, which triggered the endogenous BR level. The enhanced BR level induced the transcription of GA catabolism gene GA2ox7 resulting in reduced GA contents. At the same time, GA-mediated responses can be negatively regulated under submerged conditions by a DELLA family member, the GA-signal inhibitory factor SLR1 protein, so that the elongation of rice plants is inhibited ( Schmitz et al., 2013 ). Therefore, BR limited shoot elongation by inhibiting GA biosynthesis and decreasing the action of GA in the rice Sub1A genotype.

Some selected recent studies on Phytohormones and plant growth regulator mediated waterlogging tolerance in plants are presented in Table 1 .

Melatonin (MT) is a phytohormone and an excellent antioxidant molecule that augments plant growth under adverse conditions ( Sharif et al., 2018 ). The MT has been previously reported for its mitigatory role of numerous abiotic stresses ( Sharif et al., 2018 ). Owing to that, research related to MT and its involvement in improving waterlogging stress tolerance is relatively less, and only few research articles are available ( Moustafa-Farag et al., 2020 ).

The very first report over MT in response to waterlogging stress unraveled that it can mend plant tolerance by inducing the activity of antioxidant enzymes, suppression of harmful ROS, and maintained proper growth to ensure good yield ( Chen et al., 2015 ). Following that, the young apple seedlings subjected to waterlogging stress were treated with MT ( Zheng et al., 2017 ). The study showed that seedling treated with MT presented enhanced tolerance to waterlogging stress by triggering the generation of antioxidant enzymes activities, improved aerobic respiration, and photosynthetic machinery ( Zheng et al., 2017 ). On the other hand, the application of MT significantly inhibited the deleterious effects of anaerobic respiration and MDA- and ROS-induced chlorosis ( Zheng et al., 2017 ). The induced expression level of MT biosynthesis genes such as MbT5H1 , MbAANAT3 , and MbASMT9 increased the production of endogenous MT in the seedlings treated with MT ( Zheng et al., 2017 ). Therefore, it can be assumed that MT plays a key role in regulating the response of plants to waterlogging stress. The growth of the alfalfa plant has been hampered by the waterlogging stress by dysfunctioning the photosynthetic ability and boosted the generation of electrolyte leakage and MDA contents ( Zhang Q. et al., 2019 ). The up-regulated expression level of PA biosynthesis genes also highlighted their involvement in regulating the alfalfa response to waterlogging stress ( Zhang Q. et al., 2019 ). The application of MT at the rate of 100 μM over 6-week-old alfalfa seedlings displayed tolerance to waterlogging stress ( Zhang Q. et al., 2019 ). The enhanced tolerance post–MT application was associated with the further induction in the expression of PAs biosynthesis genes ( SPDS , SPMS , and ADC ). Also, the exogenous MT treatment not only increased the endogenous MT level but also stabilized the normal functioning of other biochemical and physiological parameters ( Zhang Q. et al., 2019 ). Further, the MT-treated plants under waterlogging stress exhibited decreased expression pattern of ET biosynthesis and signaling genes ( ACS , ACO , and ERF ) ( Zhang Q. et al., 2019 ). This means that MT and ET possess an antagonistic relationship under waterlogging stress. However, no report is available to confirm the antagonistic crosstalk between MT and ET. P. persica is considered one of the most hypoxia-intolerant stone fruits. However, waterlogging, which causes hypoxia, occurs frequently in southern China, where peaches are commercially important ( Gu et al., 2020 ). The application of MT at the rate of 200 μM substantially augmented the antioxidant activities, suppressed the lipid peroxidation, and H 2 O 2 , positively regulated the size of aerenchyma for better anaerobic respiration activities and induced mRNA level of Ca 2+ signaling and hypoxia-related ERF VII transcription factor genes ( Gu et al., 2020 ). Therefore, it can be suggested that the application of MT positively regulates the ET homeostasis, which is an important and crucial factor in inducing waterlogging stress tolerance.

Inducing Waterlogging Tolerance via Genetic Engineering

The manipulation of targeted plant genes to increase the production capacity or tolerance against a certain stress is becoming the need of the day ( Lemay and Moineau, 2020 ). As the climate threat looms over the safe production of agronomic and horticultural crops, genome editing techniques can play a significant role in decreasing the adverse environmental effects ( Lemay and Moineau, 2020 ). Previous studies have shown that the deleterious effects of the waterlogging stress can be mimicked by utilizing the genome editing tools. For example, the overexpression of AtACO5 gene in Arabidopsis triggered the ET production, and cell expansion activities resulted in enhanced tolerance against waterlogging stress ( Rauf et al., 2013 ). The overexpression of CsARN6.1 gene in cucumber facilitates the formation of ARs independent of hormonal generations. However, the increased number of ARs in the overexpressed CsARN6.1 lines was associated with the intense cellular activities and hydrolysis of the ATP energy packets ( Xu et al., 2018 ). The ERF transcription factors are directly involved in the regulation of waterlogging stress. A member of ERF transcription factor family PhERF2 was characterized in petunia ( Yin et al., 2019 ). Up-regulation in the transcript abundance of PhERF2 was observed under waterlogging stress. To further highlight the role, the PhERF2 overexpressed lines were generated, which displayed enhanced tolerance to waterlogging stress. On the contrary, the RNAi line of PhERF2 showed sensitivity to waterlogging ( Yin et al., 2019 ). The genes influence the alcoholic fermentation process such as ADH1-1 , ADH1-2 , ADH1-3 , PDC1 , and PDC2 induced and suppressed in overexpressed and silenced plants, respectively ( Yin et al., 2019 ). Similarly, the induced expression levels of NtPDC , NtADH , NtHB1 , NtHB2 , NtPCO1 , and NtPCO2 genes in AdRAP2.3 overexpressed tobacco plants presented its association with the enhanced waterlogging stress tolerance ( Pan et al., 2019 ). In wheat, waterlogging stress can significantly hinder the physiological activities particularly photosynthesis, which ultimately reduce the grain yield and affect overall yield. The constitutive expression of TaERFVII.1 gene in wheat alleviated the negative effects of waterlogging stress by boosting the immunity resulting in increased grain weight per plant, improved survival rate, and better chlorophyll content of leaves ( Wei et al., 2019 ). On the other hand, the compromised expression of TaERFVII.1 in silenced plants also decreased the transcript of several waterlogging−responsive genes ( Wei et al., 2019 ). Interestingly, the constitutive expression of TaERFVII.1 did not negatively impact both plant development and grain yield under standard conditions by suppressing the TaSAB18.1 gene ( Wei et al., 2019 ). The barley HvERF2.11 when overexpressed in Arabidopsis triggered the expression level of antioxidant enzyme biosynthesis genes ( AtSOD1 , AtPOD1 ) and ET biosynthesis gene ( AtACO1 ), conferring resistance to waterlogging stress ( Luan et al., 2020 ). The HD-ZIP I subfamily gene HaHB11 was overexpressed in the Arabidopsis and exposed to waterlogging stress ( Cabello et al., 2016 ). The transgenic Arabidopsis plants carrying gain-of-function HaHB11 gene not only induced the tolerance to waterlogging stress but also increased the biomass and yielded more seeds than control by inducing the glucose and sucrose level ( Cabello et al., 2016 ). In addition, the HaHB11 were notably involved in the increment of expression of genes involved in the alcohol fermentation ( Cabello et al., 2016 ). Multiple studies highlighting the importance of genetic engineering in augmenting the immunity of plants to waterlogging stress are presented in Table 2 .

Listed studies related to improved waterlogging tolerance via genetic engineering.

Conclusion and Outlook

The regulation of plant growth and development processes under waterlogging stress is very complex, with different crops, different varieties of the same crop, and different growth periods of the same crop often showing great differences, while different plant species evolved different adaptation strategies. At present, research on crop waterlogging tolerance is mainly carried out from the perspective of morphological, structural, physiological, biochemical, and metabolic gene signal regulation. The most effective ways to enhance plant waterlogging tolerance will be (1) improving cultivation management to reduce the direct damage to crops caused by waterlogging and (2) using modern molecular biology technology to discover the key genes regulating waterlogging tolerance and verify their functions.

Building on existing research results and aiming to address identified problems, the following aspects should receive increased attention in future research on plant waterlogging tolerance:

• (1) Current studies focus mainly on the vegetative growth stage of plants under waterlogging stress. However, the molecular responses during seed germination, early seedling morphogenesis, and late reproductive growth under waterlogging stress are neglected topics that warrant further study.
• (2) Although a large number of related genes regulating plant waterlogging tolerance have been obtained by transcriptomics, proteomics, and other methods. However, most of them are preliminary study and required functional characterization.
• (3) There is a need to exploit additional genetic resources for waterlogging tolerance, using both isolated populations and natural populations to identify waterlogging tolerance–related genes.
• (4) The hormonal-induced waterlogging resistance has been studied extensively. Majority of the available studies mainly reported the effects of growth hormones on vegetative stages under waterlogging stress. Although studies are missing to investigate the role of these phytohormones when waterlogging stress happens at reproductive stages of the plant. Hormonal crosstalk under waterlogging stress in the early developmental stages of plant has been investigated and is presented in Figure 2 . However, it could be interesting to examine the complex hormonal crosstalk under waterlogging stress during reproductive stages, such as how these hormones ensure plant productivity under prolonged waterlogging stress. Additionally, is there an unknown genetic factor(s) controlling phytohormone-mediated cascades under waterlogging condition? Therefore, it is of great importance to elucidate these mechanisms to develop waterlogging resilience plants to increase crop productivity particularly in the areas that have poor soil drainage properties, those affected by frequent heavy rainfall, and areas with duplex soil.

Author Contributions

JP wrote the manuscript. RS, XX, and XC revised and finally approved the manuscript for publication. All the authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank Dr. Qi Xioahua (College of Horticulture and Plant Protection, Yangzhou University) for critically revising the manuscript.

Funding. This research was supported by the National Natural Science Foundation of China (grant nos. 32030093 and 31801883) and Natural Science Foundation of Jiangsu Province (BK20180913).

• Abiko T., Miyasaka S. C. (2020). Aerenchyma and barrier to radial oxygen loss are formed in roots of Taro (Colocasia esculenta) propagules under flooded conditions. J. Plant Res. 133 49–56. 10.1007/s10265-019-01150-6 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Alpuerto J. B., Hussain R. M. F., Fukao T. (2016). The key regulator of submergence tolerance, SUB1A, promotes photosynthetic and metabolic recovery from submergence damage in rice leaves. Plant Cell Environ. 39 672–684. 10.1111/pce.12661 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• An Y., Qi L., Wang L. (2016). ALA pretreatment improves waterlogging tolerance of fig plants. PLoS One 11 : e0147202 . 10.1371/journal.pone.0147202 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Andrade C. A., de Souza K. R. D., de Oliveira Santos M., da Silva D. M., Alves J. D. (2018). Hydrogen peroxide promotes the tolerance of soybeans to waterlogging. Sci. Horticult. 232 40–45. 10.1016/j.scienta.2017.12.048 [ CrossRef ] [ Google Scholar ]
• Anee T. I., Nahar K., Rahman A., Mahmud J. A., Bhuiyan T. F., Alam M. U., et al. (2019). Oxidative damage and antioxidant defense in Sesamum indicum after different waterlogging durations. Plants 8 : 196 . 10.3390/plants8070196 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Arbona V., Gómez-Cadenas A. (2008). Hormonal modulation of citrus responses to flooding. J. Plant Growth Regulat. 27 : 241 10.1007/s00344-008-9051-x [ CrossRef ] [ Google Scholar ]
• Arif Y., Sami F., Siddiqui H., Bajguz A., Hayat S. (2020). Salicylic acid in relation to other phytohormones in plant: a study towards physiology and signal transduction under challenging environment. Environ. Exp. Bot. 175 : 104040 10.1016/j.envexpbot.2020.104040 [ CrossRef ] [ Google Scholar ]
• Ayano M., Kani T., Kojima M., Sakakibara H., Kitaoka T., Kuroha T., et al. (2014). Gibberellin biosynthesis and signal transduction is essential for internode elongation in deepwater rice. Plant Cell Environ. 37 2313–2324. 10.1111/pce.12377 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bai T., Li C., Ma F., Shu H., Han M. (2009). Exogenous salicylic acid alleviates growth inhibition and oxidative stress induced by hypoxia stress in Malus robusta Rehd. J. Plant Growth Regulat. 28 358–366. 10.1007/s00344-009-9104-9 [ CrossRef ] [ Google Scholar ]
• Bailey-Serres J., Chang R. (2005). Sensing and signalling in response to oxygen deprivation in plants and other organisms. Ann. Bot. 96 507–518. 10.1093/aob/mci206 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bailey-Serres J., Voesenek L. (2008). Flooding stress: acclimations and genetic diversity. Annu. Rev. Plant Biol. 59 313–339. 10.1146/annurev.arplant.59.032607.092752 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bailey-Serres J., Fukao T., Gibbs D. J., Holdsworth M. J., Lee S. C., Licausi F., et al. (2012). Making sense of low oxygen sensing. Trends Plant Sci. 17 129–138. [ PubMed ] [ Google Scholar ]
• Bajguz A., Hayat S. (2009). Effects of brassinosteroids on the plant responses to environmental stresses. Plant Physiol. Biochem. 47 1–8. 10.1016/j.plaphy.2008.10.002 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bansal R., Srivastava J. P. (2012). Antioxidative defense system in pigeonpea roots under waterlogging stress. Acta Physiol. Plant. 34 515–522. 10.1007/s11738-011-0848-z [ CrossRef ] [ Google Scholar ]
• Bartoli C. G., Casalongué C. A., Simontacchi M., Marquez-Garcia B., Foyer C. H. (2013). Interactions between hormone and redox signalling pathways in the control of growth and cross tolerance to stress. Environ. Exp. Bot. 94 73–88. 10.1016/j.envexpbot.2012.05.003 [ CrossRef ] [ Google Scholar ]
• Baxter A., Mittler R., Suzuki N. (2014). ROS as key players in plant stress signalling. J. Exp. Bot. 65 1229–1240. 10.1093/jxb/ert375 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Baxter-Burrell A., Yang Z., Springer P. S., Bailey-Serres J. (2002). RopGAP4-dependent Rop GTPase rheostat control of Arabidopsis oxygen deprivation tolerance. Science 296 2026–2028. 10.1126/science.1071505 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Benschop J. J., Bou J., Peeters A. J., Wagemaker N., Gühl K., Ward D., et al. (2006). Long-term submergence-induced elongation in Rumex palustris requires abscisic acid-dependent biosynthesis of gibberellin1. Plant Physiol. 141 1644–1652. 10.1104/pp.106.082636 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bin T., Xu S.-Z., Zou X.-L., Zheng Y.-L., Qiu F.-Z. (2010). Changes of antioxidative enzymes and lipid peroxidation in leaves and roots of waterlogging-tolerant and waterlogging-sensitive maize genotypes at seedling stage. Agricult. Sci. China 9 651–661. 10.1016/s1671-2927(09)60140-1 [ CrossRef ] [ Google Scholar ]
• Borella J., Becker R., Lima M. C., Oliveira D. D. S. C. D., Braga E. J. B., Oliveira A. C. B. D., et al. (2019). Nitrogen source influences the antioxidative system of soybean plants under hypoxia and re-oxygenation. Sci. Agricol. 76 51–62. 10.1590/1678-992x-2017-0195 [ CrossRef ] [ Google Scholar ]
• Cabello J. V., Giacomelli J. I., Piattoni C. V., Iglesias A. A., Chan R. L. (2016). The sunflower transcription factor HaHB11 improves yield, biomass and tolerance to flooding in transgenic Arabidopsis plants. J. Biotechnol. 222 73–83. 10.1016/j.jbiotec.2016.02.015 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Caruso P., Baldoni E., Mattana M., Paolo D. P., Genga A., Coraggio I., et al. (2012). Ectopic expression of a rice transcription factor, Mybleu, enhances tolerance of transgenic plants of Carrizo citrange to low oxygen stress. Plant Cell Tissue Organ Cult. (PCTOC) 109 327–339. 10.1007/s11240-011-0098-1 [ CrossRef ] [ Google Scholar ]
• Chen H., Feng C., Kong J., Wang L., Wang N., Zheng X., et al. (2015). Use of product containing melatonin as effective component for improving waterlogging stress resistance in plants. Google Patent No. A01N-043/38 201612. [ Google Scholar ]
• Colmer T. (2002). Aerenchyma and an inducible barrier to radial oxygen loss facilitate root aeration in upland, paddy and deep−water rice ( Oryza sativa L.). Ann. Bot. 91 301–309. 10.1093/aob/mcf114 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dawood T., Yang X., Visser E. J., Te Beek T. A., Kensche P. R., Cristescu S. M., et al. (2016). A co-opted hormonal cascade activates dormant adventitious root primordia upon flooding in Solanum dulcamara. Plant Physiol. 170 2351–2364. 10.1104/pp.15.00773 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ding J., Liang P., Wu P., Zhu M., Li C., Zhu X., et al. (2020). Effects of waterlogging on grain yield and associated traits of historic wheat cultivars in the middle and lower reaches of the Yangtze River, China. Field Crops Res. 246 : 107695 10.1016/j.fcr.2019.107695 [ CrossRef ] [ Google Scholar ]
• Dolferus R., Wolansky M., Carroll R., Miyashita Y., Ismond K., Good A. (2008). Functional analysis of lactate dehydrogenase during hypoxic stress in Arabidopsis . Funct. Plant Biol. 35 131–140. 10.1071/fp07228 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Doupis G., Kavroulakis N., Psarras G., Papadakis I. (2017). Growth, photosynthetic performance and antioxidative response of ‘Hass’ and ‘Fuerte’avocado (Persea americana Mill.) plants grown under high soil moisture. Photosynthetica 55 655–663. 10.1007/s11099-016-0679-7 [ CrossRef ] [ Google Scholar ]
• Drew M. C., He C.-J., Morgan P. W. (2000). Programmed cell death and aerenchyma formation in roots. Trends Plant Sci. 5 123–127. 10.1016/s1360-1385(00)01570-3 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Evans D. E. (2004). Aerenchyma formation. New Phytol. 161 35–49. 10.1046/j.1469-8137.2003.00907.x [ CrossRef ] [ Google Scholar ]
• Eysholdt−Derzsó E., Sauter M. (2019). Hypoxia and the group VII ethylene response transcription factor HRE2 promote adventitious root elongation in Arabidopsis . Plant Biol. 21 103–108. 10.1111/plb.12873 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Farhangi-Abriz S., Ghassemi-Golezani K. (2019). Jasmonates: mechanisms and functions in abiotic stress tolerance of plants. Biocatalys. Agricult. Biotechnol. 20 : 101210 10.1016/j.bcab.2019.101210 [ CrossRef ] [ Google Scholar ]
• Fukao T., Bailey-Serres J. (2008). Submergence tolerance conferred by Sub1A is mediated by SLR1 and SLRL1 restriction of gibberellin responses in rice. Proc. Natl. Acad. Sci. U.S.A. 105 16814–16819. 10.1073/pnas.0807821105 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fukao T., Barrera-Figueroa B. E., Juntawong P., Peña-Castro J. M. (2019). Submergence and waterlogging stress in plants: a review highlighting research opportunities and understudied aspects. Front. Plant Sci. 10 : 340 . 10.3389/fpls.2019.00340 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fukao T., Xu K., Ronald P. C., Bailey-Serres J. (2006). A variable cluster of ethylene response factor–like genes regulates metabolic and developmental acclimation responses to submergence in rice. Plant Cell 18 2021–2034. 10.1105/tpc.106.043000 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gasch P., Fundinger M., Müller J. T., Lee T., Bailey-Serres J., Mustroph A. (2016). Redundant ERF-VII transcription factors bind to an evolutionarily conserved cis-motif to regulate hypoxia-responsive gene expression in Arabidopsis . Plant Cell 28 160–180. 10.1105/tpc.15.00866 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Giuntoli B., Perata P. (2018). Group VII ethylene response factors in Arabidopsis : regulation and physiological roles. Plant Physiol. 176 1143–1155. 10.1104/pp.17.01225 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gu X., Xue L., Lu L., Xiao J., Song G., Xie M., et al. (2020). Melatonin Enhances the waterlogging tolerance of prunus persica by modulating antioxidant metabolism and anaerobic respiration. J. Plant Growth Regulat. 1–13. 10.9734/ijbcrr/2016/32087 [ CrossRef ] [ Google Scholar ]
• Hartman S., Liu Z., Van Veen H., Vicente J., Reinen E., Martopawiro S., et al. (2019a). Ethylene-mediated nitric oxide depletion pre-adapts plants to hypoxia stress. Nat. Commun. 10 1–9. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hartman S., Sasidharan R., Voesenek L. A. (2019b). The role of ethylene in metabolic acclimations to low oxygen. New Phytol. 229 64–70. 10.1111/nph.16378 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hasanuzzaman M., Bhuyan M., Zulfiqar F., Raza A., Mohsin S. M., Mahmud J. A., et al. (2020). Reactive oxygen species and antioxidant defense in plants under abiotic stress: revisiting the crucial role of a universal defense regulator. Antioxidants 9 : 681 . 10.3390/antiox9080681 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hattori Y., Nagai K., Furukawa S., Song X.-J., Kawano R., Sakakibara H., et al. (2009). The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water. Nature 460 1026–1030. 10.1038/nature08258 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hayat Q., Hayat S., Irfan M., Ahmad A. (2010). Effect of exogenous salicylic acid under changing environment: a review. Environ. Exp. Bot. 68 14–25. 10.1016/j.envexpbot.2009.08.005 [ CrossRef ] [ Google Scholar ]
• He F., Wang H.-L., Li H.-G., Su Y., Li S., Yang Y., et al. (2018). PeCHYR 1, a ubiquitin E3 ligase from Populus euphratica, enhances drought tolerance via ABA−induced stomatal closure by ROS production in Populus. Plant Biotechnol. J. 16 1514–1528. 10.1111/pbi.12893 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Herzog M., Striker G. G., Colmer T. D., Pedersen O. (2016). Mechanisms of waterlogging tolerance in wheat–a review of root and shoot physiology. Plant Cell Environ. 39 1068–1086. 10.1111/pce.12676 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hess N., Klode M., Anders M., Sauter M. (2011). The hypoxia responsive transcription factor genes ERF71/HRE2 and ERF73/HRE1 of Arabidopsis are differentially regulated by ethylene. Physiol. Plant. 143 41–49. 10.1111/j.1399-3054.2011.01486.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hirabayashi Y., Mahendran R., Koirala S., Konoshima L., Yamazaki D., Watanabe S., et al. (2013). Global flood risk under climate change. Nat. Clim. Change 3 816–821. 10.1038/nclimate1911 [ CrossRef ] [ Google Scholar ]
• Hossain M. A., Bhattacharjee S., Armin S.-M., Qian P., Xin W., Li H.-Y., et al. (2015). Hydrogen peroxide priming modulates abiotic oxidative stress tolerance: insights from ROS detoxification and scavenging. Front. Plant Sci. 6 : 420 . 10.3389/fpls.2015.00420 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Huang H., Liu D., Li L., Wu J., Wang S., Li X. (2018). Effects of spraying plant growth regulators on peanut growth and yield & quality under waterlogging stress. J. Hum. Agric. Univ. 44 129 . (in Chinese), [ Google Scholar ]
• Huang L., Zhang L., Zeng R., Wang X., Zhang H., Wang L., et al. (2020). Brassinosteroid priming improves peanut drought tolerance via eliminating inhibition on genes in photosynthesis and hormone signaling. Genes 11 919 10.3390/genes11080919 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hudgins J., Franceschi V. R. (2004). Methyl jasmonate-induced ethylene production is responsible for conifer phloem defense responses and reprogramming of stem cambial zone for traumatic resin duct formation. Plant Physiol. 135 2134–2149. 10.1104/pp.103.037929 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kamal A. H. M., Komatsu S. (2016). Jasmonic acid induced protein response to biophoton emissions and flooding stress in soybean. J. Proteom. 133 33–47. 10.1016/j.jprot.2015.12.004 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kang Y.-Y., Guo S.-R., Li J., Duan J.-J. (2009). Effect of root applied 24-epibrassinolide on carbohydrate status and fermentative enzyme activities in cucumber ( Cucumis sativus L.) seedlings under hypoxia. Plant Growth Regul. 57 259–269. 10.1007/s10725-008-9344-x [ CrossRef ] [ Google Scholar ]
• Kazan K., Manners J. M. (2009). Linking development to defense: auxin in plant–pathogen interactions. Trends Plant Sci. 14 373–382. 10.1016/j.tplants.2009.04.005 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kim Y., Seo C.-W., Khan A. L., Mun B.-G., Shahzad R., Ko J.-W., et al. (2018). Exo-ethylene application mitigates waterlogging stress in soybean ( Glycine max L.). BMC Plant Biol. 18 : 254 . 10.1186/s12870-018-1457-4 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kim Y.-H., Hwang S.-J., Waqas M., Khan A. L., Lee J.-H., Lee J.-D., et al. (2015). Comparative analysis of endogenous hormones level in two soybean ( Glycine max L.) lines differing in waterlogging tolerance. Front. Plant Sci. 6 : 714 . 10.3389/fpls.2015.00714 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Komatsu S., Han C., Nanjo Y., Altaf-Un-Nahar M., Wang K., He D., et al. (2013). Label-free quantitative proteomic analysis of abscisic acid effect in early-stage soybean under flooding. J. Proteome Res. 12 4769–4784. 10.1021/pr4001898 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Komatsu S., Thibaut D., Hiraga S., Kato M., Chiba M., Hashiguchi A., et al. (2011). Characterization of a novel flooding stress-responsive alcohol dehydrogenase expressed in soybean roots. Plant Mol. Biol. 77 309–322. 10.1007/s11103-011-9812-y [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kreuzwieser J., Rennenberg H. (2014). Molecular and physiological responses of trees to waterlogging stress. Plant Cell Environ. 37 2245–2259. [ PubMed ] [ Google Scholar ]
• Kuai J., Liu Z., Wang Y., Meng Y., Chen B., Zhao W., et al. (2014). Waterlogging during flowering and boll forming stages affects sucrose metabolism in the leaves subtending the cotton boll and its relationship with boll weight. Plant Sci. 223 79–98. 10.1016/j.plantsci.2014.03.010 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kuroha T., Nagai K., Gamuyao R., Wang D. R., Furuta T., Nakamori M., et al. (2018). Ethylene-gibberellin signaling underlies adaptation of rice to periodic flooding. Science 361 181–186. 10.1126/science.aat1577 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kurokawa Y., Nagai K., Huan P. D., Shimazaki K., Qu H., Mori Y., et al. (2018). Rice leaf hydrophobicity and gas films are conferred by a wax synthesis gene (LGF 1) and contribute to flood tolerance. New Phytol. 218 1558–1569. 10.1111/nph.15070 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lee Y.-H., Kim K.-S., Jang Y.-S., Hwang J.-H., Lee D.-H., Choi I.-H. (2014). Global gene expression responses to waterlogging in leaves of rape seedlings. Plant Cell Rep. 33 289–299. 10.1007/s00299-013-1529-8 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lemay M.-L., Moineau S. (2020). “ How are genes modified? Crossbreeding, mutagenesis, and CRISPR-Cas9 ,” in Genetically Modified and Irradiated Food , ed. Andersen V. (Cambridge, MA: Academic Press; ), 39–54. 10.1016/b978-0-12-817240-7.00003-6 [ CrossRef ] [ Google Scholar ]
• Li C.-X., Wei H., Geng Y.-H., Schneider R. (2010). Effects of submergence on photosynthesis and growth of Pterocarya stenoptera (Chinese wingnut) seedlings in the recently-created Three Gorges Reservoir region of China. Wetl. Ecol. Manag. 18 485–494. 10.1007/s11273-010-9181-3 [ CrossRef ] [ Google Scholar ]
• Li T. (2007). Preliminary Studies of Waterlogging in Physiology of Cucumber at the Seedling Stage. Doctoral Dissertation, University of Yangzhou, China. [ Google Scholar ]
• Li W., Mo W., Ashraf U., Li G., Wen T., Abrar M., et al. (2018). Evaluation of physiological indices of waterlogging tolerance of different maize varieties in South China. Appl. Ecol. Environ. Res. 16 2059–2072. 10.15666/aeer/1602_20592072 [ CrossRef ] [ Google Scholar ]
• Limami A. M., Diab H., Lothier J. (2014). Nitrogen metabolism in plants under low oxygen stress. Planta 239 531–541. 10.1007/s00425-013-2015-9 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lin C., Sauter M. (2019). Polar auxin transport determines adventitious root emergence and growth in rice. Front. Plant Sci. 10 : 444 . 10.3389/fpls.2019.00444 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lin K.-H. R., Weng C.-C., Lo H.-F., Chen J.-T. (2004). Study of the root antioxidative system of tomatoes and eggplants under waterlogged conditions. Plant Sci. 167 355–365. 10.1016/j.plantsci.2004.04.004 [ CrossRef ] [ Google Scholar ]
• Liu B., Sun L., Ma L., Hao F.-S. (2017). Both AtrbohD and AtrbohF are essential for mediating responses to oxygen deficiency in Arabidopsis . Plant Cell Rep. 36 947–957. 10.1007/s00299-017-2128-x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Liu P., Sun F., Gao R., Dong H. (2012). RAP2. 6L overexpression delays waterlogging induced premature senescence by increasing stomatal closure more than antioxidant enzyme activity. Plant Mol. Biol. 79 609–622. 10.1007/s11103-012-9936-8 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Loreti E., van Veen H., Perata P. (2016). Plant responses to flooding stress. Curr. Opin. Plant Biol. 33 64–71. 10.1016/j.pbi.2016.06.005 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Luan H., Guo B., Shen H., Pan Y., Hong Y., Lv C., et al. (2020). Overexpression of Barley Transcription Factor HvERF2. 11 in Arabidopsis enhances plant waterlogging tolerance. Int. J. Mol. Sci. 21 1982 . 10.3390/ijms21061982 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Luan H., Shen H., Pan Y., Guo B., Lv C., Xu R. (2018). Elucidating the hypoxic stress response in barley ( Hordeum vulgare L.) during waterlogging: a proteomics approach. Sci. Rep. 8 1–13. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lv B., Yan Z., Tian H., Zhang X., Ding Z. (2019). Local auxin biosynthesis mediates plant growth and development. Trends Plant Sci. 24 6–9. 10.1016/j.tplants.2018.10.014 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ma Y., Guo S. (2014). 24-epibrassinolide improves cucumber photosynthesis under hypoxia by increasing CO 2 assimilation and photosystem II efficiency. Photosynthetica 52 96–104. 10.1007/s11099-014-0010-4 [ CrossRef ] [ Google Scholar ]
• McDonald M., Visser E. (2003). A study of the interaction between auxin and ethylene in wild type and transgenic ethylene-insensitive tobacco during adventitious root formation induced by stagnant root zone conditions. Plant Biol. 5 550–556. 10.1055/s-2003-44790 [ CrossRef ] [ Google Scholar ]
• Mignolli F., Todaro J. S., Vidoz M. L. (2020). Internal aeration and respiration of submerged tomato hypocotyls are enhanced by ethylene-mediated aerenchyma formation and hypertrophy. Physiol. Plant. 169 49–63. 10.1111/ppl.13044 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Miransari M., Smith D. (2014). Plant hormones and seed germination. Environ. Exp. Bot. 99 110–121. 10.1016/j.envexpbot.2013.11.005 [ CrossRef ] [ Google Scholar ]
• Mondal S., Khan M. I. R., Dixit S., Cruz P. C. S., Septiningsih E. M., Ismail A. M. (2020). Growth, productivity and grain quality of AG1 and AG2 QTLs introgression lines under flooding in direct-seeded rice system. Field Crops Res. 248 107713 10.1016/j.fcr.2019.107713 [ CrossRef ] [ Google Scholar ]
• Moustafa-Farag M., Mahmoud A., Arnao M. B., Sheteiwy M. S., Dafea M., Soltan M., et al. (2020). Melatonin-induced water stress tolerance in plants: recent advances. Antioxidants 9 809 . 10.3390/antiox9090809 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Nan R., Carman J. G., Salisbury F. B. (2002). Water stress, CO2 and photoperiod influence hormone levels in wheat. J. Plant Physiol. 159 307–312. 10.1078/0176-1617-00703 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Nazir F., Fariduddin Q., Hussain A., Khan T. A. (2021). Brassinosteroid and hydrogen peroxide improve photosynthetic machinery, stomatal movement, root morphology and cell viability and reduce Cu-triggered oxidative burst in tomato. Ecotoxicol. Environ. Saf. 207 111081 . 10.1016/j.ecoenv.2020.111081 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Nelissen H., Rymen B., Jikumaru Y., Demuynck K., Van Lijsebettens M., Kamiya Y., et al. (2012). A local maximum in gibberellin levels regulates maize leaf growth by spatial control of cell division. Curr. Biol. 22 1183–1187. 10.1016/j.cub.2012.04.065 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Nishiuchi S., Yamauchi T., Takahashi H., Kotula L., Nakazono M. (2012). Mechanisms for coping with submergence and waterlogging in rice. Rice 5 2 . 10.1186/1939-8433-5-2 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pan D.-L., Wang G., Wang T., Jia Z.-H., Guo Z.-R., Zhang J.-Y. (2019). AdRAP2. 3, a novel ethylene response factor VII from Actinidia deliciosa , enhances waterlogging resistance in transgenic tobacco through improving expression levels of PDC and ADH Genes. Int. J. Mol. Sci. 20 1189 . 10.3390/ijms20051189 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pedersen O., Rich S. M., Colmer T. D. (2009). Surviving floods: leaf gas films improve O2 and CO2 exchange, root aeration, and growth of completely submerged rice. Plant J. 58 147–156. 10.1111/j.1365-313x.2008.03769.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pedersen O., Sauter M., Colmer T. D., Nakazono M. (2020). Regulation of root adaptive anatomical and morphological traits during low soil oxygen. New Phytol. 229 42–49. 10.1111/nph.16375 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Per T. S., Khan M. I. R., Anjum N. A., Masood A., Hussain S. J., Khan N. A. (2018). Jasmonates in plants under abiotic stresses: crosstalk with other phytohormones matters. Environ. Exp. Bot. 145 104–120. 10.1016/j.envexpbot.2017.11.004 [ CrossRef ] [ Google Scholar ]
• Pucciariello C., Parlanti S., Banti V., Novi G., Perata P. (2012). Reactive oxygen species-driven transcription in Arabidopsis under oxygen deprivation. Plant Physiol. 159 184–196. 10.1104/pp.111.191122 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Qi X., Li Q., Ma X., Qian C., Wang H., Ren N., et al. (2019). Waterlogging-induced adventitious root formation in cucumber is regulated by ethylene and auxin through reactive oxygen species signalling. Plant Cell Environ. 42 1458–1470. 10.1111/pce.13504 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Qi X., Li Q., Shen J., Qian C., Xu X., Xu Q., et al. (2020). Sugar enhances waterlogging−induced adventitious root formation in cucumber by promoting auxin transport and signalling. Plant Cell Environ. 43 1545–1557. 10.1111/pce.13738 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rauf M., Arif M., Fisahn J., Xue G.-P., Balazadeh S., Mueller-Roeber B. (2013). NAC transcription factor speedy hyponastic growth regulates flooding-induced leaf movement in Arabidopsis . Plant Cell 25 4941–4955. 10.1105/tpc.113.117861 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Raza A., Charagh S., Zahid Z., Mubarik M. S., Javed R., Siddiqui M. H., et al. (2020). Jasmonic acid: a key frontier in conferring abiotic stress tolerance in plants. Plant Cell Rep. [Epub ahead of print]. [ PubMed ] [ Google Scholar ]
• Saha I., Hasanuzzaman M., Dolui D., Sikdar D., Debnath S. C., Adak M. K. (2021). Silver-nanoparticle and abscisic acid modulate sub1A quantitative trait loci functioning towards submergence tolerance in rice ( Oryza sativa L.). Environ. Exp. Bot. 181 1042276 . [ Google Scholar ]
• Saika H., Okamoto M., Miyoshi K., Kushiro T., Shinoda S., Jikumaru Y., et al. (2007). Ethylene promotes submergence-induced expression of OsABA8ox1, a gene that encodes ABA 8’-hydroxylase in rice. Plant Cell Physiol. 48 287–298. 10.1093/pcp/pcm003 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Salah A., Zhan M., Cao C., Han Y., Ling L., Liu Z., et al. (2019). γ-Aminobutyric acid promotes chloroplast ultrastructure, antioxidant capacity, and growth of waterlogged maize seedlings. Sci. Rep. 9 1–19. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sasidharan R., Voesenek L. A. (2015). Ethylene-mediated acclimations to flooding stress. Plant Physiol. 169 3–12. 10.1104/pp.15.00387 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Schmitz A. J., Folsom J. J., Jikamaru Y., Ronald P., Walia H. (2013). SUB 1 A−mediated submergence tolerance response in rice involves differential regulation of the brassinosteroid pathway. New Phytol. 198 1060–1070. 10.1111/nph.12202 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sharif R., Xie C., Zhang H., Arnao M. B., Ali M., Ali Q., et al. (2018). Melatonin and its effects on plant systems. Molecules 23 2352 . 10.3390/molecules23092352 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sharma P., Jha A. B., Dubey R. S., Pessarakli M. (2012). Reactive oxygen species, oxidative damage, and antioxidative defense mechanism in plants under stressful conditions. J. Bot. 2012 217037 . [ Google Scholar ]
• Shimamura S., Nishimura T., Koshiba T., Yamamoto R., Hiraga S., Nakamura T., et al. (2016). Effects of anti-auxins on secondary aerenchyma formation in flooded soybean hypocotyls. Plant Prod. Sci. 19 154–160. 10.1080/1343943x.2015.1128101 [ CrossRef ] [ Google Scholar ]
• Shimamura S., Yoshioka T., Yamamoto R., Hiraga S., Nakamura T., Shimada S., et al. (2014). Role of abscisic acid in flood-induced secondary aerenchyma formation in soybean ( Glycine max ) hypocotyls. Plant Prod. Sci. 17 131–137. 10.1626/pps.17.131 [ CrossRef ] [ Google Scholar ]
• Shiono K., Ogawa S., Yamazaki S., Isoda H., Fujimura T., Nakazono M., et al. (2011). Contrasting dynamics of radial O2-loss barrier induction and aerenchyma formation in rice roots of two lengths. Ann. Bot. 107 89–99. 10.1093/aob/mcq221 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Steffens B., Rasmussen A. (2016). The physiology of adventitious roots. Plant Physiol. 170 603–617. 10.1104/pp.15.01360 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Steffens B., Geske T., Sauter M. (2011). Aerenchyma formation in the rice stem and its promotion by H2O2. New Phytol. 190 369–378. 10.1111/j.1469-8137.2010.03496.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sun L., Ma L., He S., Hao F. (2018). AtrbohD functions downstream of ROP2 and positively regulates waterlogging response in Arabidopsis . Plant Signal. Behav. 13 e1513300 . 10.1080/15592324.2018.1513300 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tamang B. G., Magliozzi J. O., Maroof M. S., Fukao T. (2014). Physiological and transcriptomic characterization of submergence and reoxygenation responses in soybean seedlings. Plant Cell Environ. 37 2350–2365. [ PubMed ] [ Google Scholar ]
• Tian L., Li J., Bi W., Zuo S., Li L., Li W., et al. (2019). Effects of waterlogging stress at different growth stages on the photosynthetic characteristics and grain yield of spring maize ( Zea mays L.) Under field conditions. Agric. Water Manag. 218 250–258. 10.1016/j.agwat.2019.03.054 [ CrossRef ] [ Google Scholar ]
• Tougou M., Hashiguchi A., Yukawa K., Nanjo Y., Hiraga S., Nakamura T., et al. (2012). Responses to flooding stress in soybean seedlings with the alcohol dehydrogenase transgene. Plant Biotechnol. 29 301–305. 10.5511/plantbiotechnology.12.0301a [ CrossRef ] [ Google Scholar ]
• van Veen H., Akman M., Jamar D. C., Vreugdenhil D., Kooiker M., van Tienderen P., et al. (2014). Group VII E thylene response factor diversification and regulation in four species from flood-prone environments. Plant Cell Environ. 37 2421–2432. [ PubMed ] [ Google Scholar ]
• Vidoz M. L., Loreti E., Mensuali A., Alpi A., Perata P. (2010). Hormonal interplay during adventitious root formation in flooded tomato plants. Plant J. 63 551–562. 10.1111/j.1365-313x.2010.04262.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Visser E. J., Voesenek L. A. (2005). Acclimation to soil flooding—sensing and signal-transduction, in Root physiology: from gene to function. Plant Soil 274 197–214. 10.1007/1-4020-4099-7_10 [ CrossRef ] [ Google Scholar ]
• Voesenek L., Colmer T., Pierik R., Millenaar F., Peeters A. (2006). How plants cope with complete submergence. New Phytol. 170 213–226. 10.1111/j.1469-8137.2006.01692.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wang C., Zhu J., Dai S. (2016). Effects of chemical control and nutrient control on waterlogging of rapeseed in flower and fruit stage. Jiangsu Agric. Sci. 44 136–138. [ Google Scholar ]
• Wang G., Fan W., Peng F. (2015). Physiological responses of the young peach tree to water-logging and spraying SA at different timing. J. Fruit Sci. 32 872–878. [ Google Scholar ]
• Wang J., Song L., Gong X., Xu J., Li M. (2020). Functions of jasmonic acid in plant regulation and response to abiotic stress. Int. J. Mol. Sci. 21 1446 . 10.3390/ijms21041446 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wang X., Li M., Jannasch A. H., Jiang Y. (2020). Submergence stress alters fructan and hormone metabolism and gene expression in perennial ryegrass with contrasting growth habits. Environ. Exp. Bot. 179 104202 10.1016/j.envexpbot.2020.104202 [ CrossRef ] [ Google Scholar ]
• Wei X., Xu H., Rong W., Ye X., Zhang Z. (2019). Constitutive expression of a stabilized transcription factor group VII ethylene response factor enhances waterlogging tolerance in wheat without penalizing grain yield. Plant Cell Environ. 42 1471–1485. 10.1111/pce.13505 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Winkel A., Visser E. J., Colmer T. D., Brodersen K. P., Voesenek L. A., Sand−Jensen K., et al. (2016). Leaf gas films, underwater photosynthesis and plant species distributions in a flood gradient. Plant Cell Environ. 39 1537–1548. 10.1111/pce.12717 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wu H., Chen H., Zhang Y., Zhang Y., Zhu D., Xiang J. (2019). Effects of 1-aminocyclopropane-1-carboxylate and paclobutrazol on the endogenous hormones of two contrasting rice varieties under submergence stress. Plant Growth Regul. 87 109–121. 10.1007/s10725-018-0457-6 [ CrossRef ] [ Google Scholar ]
• Wu Y.-S., Yang C.-Y. (2016). Physiological responses and expression profile of NADPH oxidase in Rice ( Oryza sativa ) seedlings under different levels of submergence. Rice 9 : 2 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Xu K., Xu X., Fukao T., Canlas P., Maghirang-Rodriguez R., Heuer S., et al. (2006). Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature 442 705–708. 10.1038/nature04920 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Xu X., Ji J., Ma X., Xu Q., Qi X., Chen X. (2016). Comparative proteomic analysis provides insight into the key proteins involved in cucumber ( Cucumis sativus L.) adventitious root emergence under waterlogging stress. Front. Plant Sci. 7 : 1515 . 10.3389/fpls.2016.01515 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Xu X., Ji J., Xu Q., Qi X., Weng Y., Chen X. (2018). The major-effect quantitative trait locus Cs ARN 6.1 encodes an AAA ATP ase domain-containing protein that is associated with waterlogging stress tolerance by promoting adventitious root formation. Plant J. 93 917–930. 10.1111/tpj.13819 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Xu X., Wang H., Qi X., Xu Q., Chen X. (2014). Waterlogging-induced increase in fermentation and related gene expression in the root of cucumber ( Cucumis sativus L.). Sci. Hortic. 179 388–395. 10.1016/j.scienta.2014.10.001 [ CrossRef ] [ Google Scholar ]
• Yamauchi T., Colmer T. D., Pedersen O., Nakazono M. (2018). Regulation of root traits for internal aeration and tolerance to soil waterlogging-flooding stress. Plant Physiol. 176 1118–1130. 10.1104/pp.17.01157 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yamauchi T., Shimamura S., Nakazono M., Mochizuki T. (2013). Aerenchyma formation in crop species: a review. Field Crops Res. 152 8–16. 10.1016/j.fcr.2012.12.008 [ CrossRef ] [ Google Scholar ]
• Yamauchi T., Tanaka A., Mori H., Takamure I., Kato K., Nakazono M. (2016). Ethylene−dependent aerenchyma formation in adventitious roots is regulated differently in rice and maize. Plant Cell Environ. 39 2145–2157. 10.1111/pce.12766 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yamauchi T., Tanaka A., Tsutsumi N., Inukai Y., Nakazono M. (2020). A role for auxin in ethylene-dependent inducible aerenchyma formation in rice roots. Plants 9 : 610 10.3390/plants9050610 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yamauchi T., Watanabe K., Fukazawa A., Mori H., Abe F., Kawaguchi K., et al. (2014). Ethylene and reactive oxygen species are involved in root aerenchyma formation and adaptation of wheat seedlings to oxygen-deficient conditions. J. Exp. Bot. 65 261–273. 10.1093/jxb/ert371 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yamauchi T., Yoshioka M., Fukazawa A., Mori H., Nishizawa N. K., Tsutsumi N., et al. (2017). An NADPH oxidase RBOH functions in rice roots during lysigenous aerenchyma formation under oxygen-deficient conditions. Plant Cell 29 775–790. 10.1105/tpc.16.00976 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yan K., Zhao S., Cui M., Han G., Wen P. (2018). Vulnerability of photosynthesis and photosystem I in Jerusalem artichoke ( Helianthus tuberosus L.) exposed to waterlogging. Plant Physiol. Biochem. 125 239–246. 10.1016/j.plaphy.2018.02.017 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yang C.-Y. (2014). Hydrogen peroxide controls transcriptional responses of ERF73/HRE1 and ADH1 via modulation of ethylene signaling during hypoxic stress. Planta 239 877–885. 10.1007/s00425-013-2020-z [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yang C.-Y., Hong C.-P. (2015). The NADPH oxidase Rboh D is involved in primary hypoxia signalling and modulates expression of hypoxia-inducible genes under hypoxic stress. Environ. Exp. Bot. 115 63–72. 10.1016/j.envexpbot.2015.02.008 [ CrossRef ] [ Google Scholar ]
• Yang S.-H., Choi D. (2006). Characterization of genes encoding ABA 8’-hydroxylase in ethylene-induced stem growth of deepwater rice ( Oryza sativa L.). Biochem. Biophys. Res. Commun. 350 685–690. 10.1016/j.bbrc.2006.09.098 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yin D., Sun D., Han Z., Ni D., Norris A., Jiang C.-Z. (2019). PhERF2, an ethylene-responsive element binding factor, plays an essential role in waterlogging tolerance of Petunia . Hortic. Res. 6 1–11. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Yu F., Liang K., Fang T., Zhao H., Han X., Cai M., et al. (2019). A group VII ethylene response factor gene, ZmEREB180, coordinates waterlogging tolerance in maize seedlings. Plant Biotechnol. J. 17 2286–2298. 10.1111/pbi.13140 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zabalza A., Van Dongen J. T., Froehlich A., Oliver S. N., Faix B., Gupta K. J., et al. (2009). Regulation of respiration and fermentation to control the plant internal oxygen concentration. Plant Physiol. 149 1087–1098. 10.1104/pp.108.129288 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhang G., Tanakamaru K., Abe J., Morita S. (2007). Influence of waterlogging on some anti-oxidative enzymatic activities of two barley genotypes differing in anoxia tolerance. Acta Physiol. Plant. 29 171–176. 10.1007/s11738-006-0022-1 [ CrossRef ] [ Google Scholar ]
• Zhang J.-Y., Huang S.-N., Wang G., Xuan J.-P., Guo Z.-R. (2016). Overexpression of Actinidia deliciosa pyruvate decarboxylase 1 gene enhances waterlogging stress in transgenic Arabidopsis thaliana. Plant Physiol. Biochem. 106 244–252. 10.1016/j.plaphy.2016.05.009 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhang P., Lyu D., Jia L., He J., Qin S. (2017). Physiological and de novo transcriptome analysis of the fermentation mechanism of Cerasus sachalinensis roots in response to short-term waterlogging. BMC Genomics 18 : 649 . 10.1186/s12864-017-4055-1 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhang Q., Liu X., Zhang Z., Liu N., Li D., Hu L. (2019). Melatonin improved waterlogging tolerance in alfalfa ( Medicago sativa ) by reprogramming polyamine and ethylene metabolism. Front. Plant Sci. 10 : 44 . 10.3389/fpls.2019.00044 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhang R., Zhou Y., Yue Z., Chen X., Cao X., Xu X., et al. (2019). Changes in photosynthesis, chloroplast ultrastructure, and antioxidant metabolism in leaves of sorghum under waterlogging stress. Photosynthetica 57 1076–1083. 10.32615/ps.2019.124 [ CrossRef ] [ Google Scholar ]
• Zhang Y., Chen Y., Lu H., Kong X., Dai J., Li Z., et al. (2016). Growth, lint yield and changes in physiological attributes of cotton under temporal waterlogging. Field Crops Res. 194 83–93. 10.1016/j.fcr.2016.05.006 [ CrossRef ] [ Google Scholar ]
• Zhang Y., Song X., Yang G., Li Z., Lu H., Kong X., et al. (2015). Physiological and molecular adjustment of cotton to waterlogging at peak-flowering in relation to growth and yield. Field Crops Res. 179 164–172. 10.1016/j.fcr.2015.05.001 [ CrossRef ] [ Google Scholar ]
• Zheng X., Zhou J., Tan D.-X., Wang N., Wang L., Shan D., et al. (2017). Melatonin improves waterlogging tolerance of Malus baccata (Linn.) Borkh. seedlings by maintaining aerobic respiration, photosynthesis and ROS migration. Front. Plant Sci. 8 : 483 . 10.3389/fpls.2017.00483 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhou W., Chen F., Meng Y., Chandrasekaran U., Luo X., Yang W., et al. (2020). Plant waterlogging/flooding stress responses: from seed germination to maturation. Plant Physiol. Biochem. 148 228–236. 10.1016/j.plaphy.2020.01.020 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhou Z. S., Guo K., Elbaz A. A., Yang Z. M. (2009). Salicylic acid alleviates mercury toxicity by preventing oxidative stress in roots of Medicago sativa . Environ. Exp. Bot. 65 27–34. 10.1016/j.envexpbot.2008.06.001 [ CrossRef ] [ Google Scholar ]
• Zhu J.-K. (2016). Abiotic stress signaling and responses in plants. Cell 167 313–324. 10.1016/j.cell.2016.08.029 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

REVIEW article

Mechanisms of waterlogging tolerance in plants: research progress and prospects.

• 1 School of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
• 2 Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China

Waterlogging is one of the main abiotic stresses suffered by plants. Inhibition of aerobic respiration during waterlogging limits energy metabolism and restricts growth and a wide range of developmental processes, from seed germination to vegetative growth and further reproductive growth. Plants respond to waterlogging stress by regulating their morphological structure, energy metabolism, endogenous hormone biosynthesis, and signaling processes. In this updated review, we systematically summarize the changes in morphological structure, photosynthesis, respiration, reactive oxygen species damage, plant hormone synthesis, and signaling cascades after plants were subjected to waterlogging stress. Finally, we propose future challenges and research directions in this field.

Introduction

Plants achieve normal growth through the coordination of water absorption by the roots with transpiration from the leaves. Sufficient water is a prerequisite for normal growth of plants, but saturation of the soil water-holding capacity, or even super-saturation, easily leads to waterlogging stress. The inhibition of root respiration and accumulation of toxic substances during waterlogging stress have adverse effects not only on vegetative growth, but also on reproductive growth, eventually leading to yield loss or even complete harvest failure ( Hirabayashi et al., 2013 ; Xu et al., 2014 ; Herzog et al., 2016 ; Tian et al., 2019 ; Ding et al., 2020 ; Zhou et al., 2020 ). Therefore, in the context of global warming, with predictions of more frequent and/or heavy rainfall and frequent flood disasters, there is a pressing need to study plant waterlogging tolerance and its mechanisms in order to maintain successful agriculture and promote effective adaptations to the changing climate ( Bailey-Serres et al., 2012 ; Nishiuchi et al., 2012 ; Mondal et al., 2020 ).

During waterlogging, leaf stomata close, whereas chlorophyll degradation, leaf senescence, and yellowing reduce the ability of leaves to capture light and ultimately lead to a decline in photosynthetic rate ( Kuai et al., 2014 ; Yan et al., 2018 ). Waterlogging removes air from soil pores, resulting in blocked gas exchange between soil and atmosphere; at the same time, the oxygen diffusion rate in water is only 1/10,000 of that in air. Consequently, oxygen availability in waterlogged soil is greatly restricted, resulting in suppressed roots respiration, decreased root activity, and energy shortage ( van Veen et al., 2014 ). Plants can temporarily maintain energy production to some extent during hypoxia caused by waterlogging, via glycolysis and ethanol fermentation. However, prolonged duration of waterlogging and anaerobic respiration ultimately leads to the accumulation of toxic metabolites such as lactic acid, ethanol, and aldehydes, combined with an increases in reactive oxygen species (ROS), notably hydrogen peroxide, thus eventually leading to cell death and plant senescence ( Xu et al., 2014 ; Zhang P. et al., 2017 ). Hindered gaseous exchange can also lead to rapid accumulation or degradation of plant hormones and further affect plant waterlogging tolerance ( Hattori et al., 2009 ; Kuroha et al., 2018 ). Although most plants perform poorly when waterlogged, they can adapt to the damage caused by such environmental stress through various strategies ( Fukao et al., 2006 ; Xu et al., 2016 ; Doupis et al., 2017 ; Yin et al., 2019 ).

The flooding stress, which further causes the submergence; hypoxia; and waterlogging stress are the main limiting factors of crop productivity. Flooding imposes submergence and ultimately raises the ground water table, which creates a hypoxic condition in the rhizosphere. The hypoxic condition in the rhizosphere restricts the oxygen uptake by causing an anaerobic environment, which further leads to plant death ( Fukao et al., 2019 ), Therefore, the flooding, submergence, and waterlogging stress are interconnected and affect the plant in nearly similar fashion ( Fukao et al., 2019 ).

In this updated review, we summarize the progress of research on plant adaptations to waterlogging stress with a focus on six aspects: morphological and anatomical adaptations, photosynthesis, respiration, ROS injury, plant hormone biosynthesis and signaling cascades, and genetic engineering in enhancing tolerance of plant against waterlogging stress ( Figure 1 ). Finally, the future challenges and research direction in this field are discussed, aiming to provide a source of reference and recommendations for further research on plant waterlogging resistance.

Figure 1. Schematic representation of plant response to waterlogging stress and hormonal effects resistance in plants.

Morphological and Anatomical Adaptation

Most plants are sensitive to waterlogging, as the diffusion rates of O 2 and CO 2 in roots and stems of plants decrease significantly during waterlogging, and photosynthesis and respiration are significantly inhibited. However, various morphological changes occur in some plants and can relieve root respiratory depression and damage caused by disrupted energy metabolism under waterlogging. Morphological changes are mainly manifested as the formation of adventitious roots (ARs) or other aeration tissues, rapid elongation of apical meristematic tissue, barriers to radial oxygen loss (ROL), and the formation of air films in the upper cuticle ( Hattori et al., 2009 ; Pedersen et al., 2009 ; Yamauchi et al., 2017 ; Qi et al., 2019 ).

Formation of ARs is a typical adaptive change in morphology ( Steffens and Rasmussen, 2016 ). During extended waterlogging, ARs develop in the internodes on the hypocotyl or at the base of the stem, where they promote the exchange of gases and the absorption of water and nutrients. To a certain extent, AR formation can replace the primary roots that die because of hypoxia stress, maintaining metabolic cycles, and enabling normal growth and development ( Xu et al., 2016 ; Eysholdt−Derzsó and Sauter, 2019 ). The newly formed ARs contain more aerenchyma than the primary roots, which augment both O 2 uptake and diffusion ability ( Visser and Voesenek, 2005 ).

Programmed cell death and degradation occur in cortical cells of plant root under hypoxia, producing tissue cavities and leading to aerenchyma formation. Aerenchyma not only can transport O 2 from non-waterlogged tissue to the root system, but also discharge CO 2 and toxic volatile substances from waterlogged tissue. Therefore, aerenchyma provides the possibility of gas exchange within plants and is vital for maintaining the normal physiological metabolism in the cells of waterlogged roots ( Drew et al., 2000 ; Evans, 2004 ; Yamauchi et al., 2013 ).

Radial oxygen loss refers to the fact that O 2 can be consumed by respiration during the longitudinal transport of O 2 along the aerenchyma to the root tip and can also be lost by lateral leakage into the intercellular spaces of the rhizosphere ( Yamauchi et al., 2018 ). Plants are able to produce a barrier to ROL, thereby reducing the loss of O 2 to the intercellular spaces of the rhizosphere and O 2 diversion between and around the root tip ( Pedersen et al., 2020 ). Abiko and Miyasaka (2020) used methylene blue to stain the ARs of taro [ Colocasia esculenta (L.) Schott] after 8 days of waterlogging and found that the root tips turned blue, whereas no blue areas appeared in the middle sections of the roots. This indicated that O 2 leakage was detected only near the root tip along the intercellular spaces of the rhizosphere, as the ROL barrier was formed in the middle of the root and prevented lateral losses ( Shiono et al., 2011 ). The formation of the ROL barrier inhibited the release of O 2 in the primordia of aerenchyma in rice ( Oryza sativa ) after 12 h of waterlogging ( Shiono et al., 2011 ). Moreover, deepwater rice cultivars form a tighter ROL barrier under low oxygen conditions than upland rice ( Colmer, 2002 ).

The rapid elongation of plant apical meristems is another adaptation of plants to waterlogging. The rapid elongation of tender stems and internodes facilitates escape from the anoxic environment and contact with the air as soon as possible, thereby enabling normal respiration ( Kuroha et al., 2018 ). This response is known as low oxygen escape syndrome (LOES). Internodes of deepwater rice cultivars elongate rapidly: waterlogging induces accumulation of ethylene (ET) and promotes synthesis of gibberellins (GAs) (largely GA 4 ), thus promoting internode elongation ( Kuroha et al., 2018 ) (see also Waterlogging stress mediated by plant hormones).

As an adaptation to waterlogging, some plants maintain a gas film on the leaf surface when submerged ( Winkel et al., 2016 ; Kurokawa et al., 2018 ). The gas film promotes the entry of O 2 in darkness and CO 2 when in light, thus contributing to the maintenance of aerobic respiration and photosynthesis. After artificial removal of the gas film in waterlogged rice, the underwater net photosynthetic rate was found to be only 20% of that with the gas film in place ( Pedersen et al., 2009 ).

Photosynthetic Adaptation

During waterlogging, stomatal conductance of leaves decreases, stomatal resistance increases, stomatal closure increases, and absorption of CO 2 is reduced ( Li et al., 2010 ). However, plants need CO 2 and light for photosynthesis to maintain growth and development. Under prolonged waterlogging condition, the enzyme activities related to photosynthesis were inhibited; the chlorophyll synthesis ability of leaves decreased, leading to leaf senescence, yellowing, and peeling; the formation of new leaves was blocked, and then the photosynthetic rate decreased, finally leading to death of the plants ( Voesenek et al., 2006 ; Wu and Yang, 2016 ).

Photosynthetic pigments are the material basis of plant photosynthesis, and the change of pigment content and composition directly affects the photosynthetic rate. Anee et al. (2019) conducted waterlogging experiments on sesame ( Sesamum indicum L.) seeds for 2, 4, 6, and 8 days to explore the changes in physiological and biochemical characteristics with time under waterlogging. The content of the photosynthetic pigments, chlorophyll A, B chlorophyll A + B, and carotenoids, was significantly lower in waterlogged seeds than in the unwaterlogged control; as the content of photosynthetic pigments decreased, the photosynthetic capacity also decreased.

The enzyme rubisco catalyzes the first step of both the photosynthetic carbon cycle and photorespiration and plays a key role in regulating the photosynthetic rate. After 24 h upon waterlogging stress, the expression of rubisco and rubisco activase genes in cotton ( Gossypium hirsutum L.) leaves was down-regulated; a reduction in net photosynthetic rate of cotton was mainly caused by lower rubisco activity. Sucrose and starch are the main products of photosynthesis in most plants. Sucrose is the main transport carbohydrate from source to sink, a process that is very sensitive to waterlogging. The decreased photosynthetic rate, sucrose conversion rate, and initial rubisco activity directly reduced the boll weight of waterlogged cotton. The enzyme sucrose synthase is central to the metabolic breakdown of sucrose required for cellulose biosynthesis; increased gene expression and enzyme activity of sucrose synthase during waterlogging were associated with prolonging the period of rapid accumulation of seed fiber weight, tending to reduce the phenomenon of boll weight decline caused by waterlogging ( Kuai et al., 2014 ).

Respiratory Adaptation

The generation of energy is crucial for plant growth and development. The lack of energy caused by hypoxia and consequent inhibition of root respiration are some of the most serious problems faced by plants under waterlogging ( Loreti et al., 2016 ). In cultivated soil, the concentration of dissolved oxygen in water is generally approximately 0.23 mol/m 3 , whereas in waterlogged conditions, the concentration of dissolved oxygen in water is less than 0.05 mmol/m 3 . The diffusion rate of O 2 in waterlogged soil is only 1/10,000 of that in the air. O 2 is the electron acceptor at the end of the mitochondrial electron transport chain. Decreased O 2 availability rapidly inhibits the production of adenosine triphosphate (ATP) by interfering with the electron transport chain, leading to inhibition of mitochondrial respiration ( Bailey-Serres and Voesenek, 2008 ; Limami et al., 2014 ). Plants need to obtain the necessary energy supply through glycolysis and ethanol fermentation so as to cope with the energy shortage caused by waterlogging stress ( Baxter-Burrell et al., 2002 ). However, 1 mol glucose can produce 36 to 38 mol ATP through the tricarboxylic acid cycle, whereas only 2 mol ATP can be obtained through glycolysis and ethanol fermentation. Therefore, plants need to accelerate glycolysis and ethanol fermentation in order to obtain the necessary amounts of ATP needed to sustain life.

Pyruvate accumulated from glycolysis can be used for anaerobic fermentation. Pyruvate fermentation produces energy in two different ways, producing lactic acid either via lactate dehydrogenase (LDH) or via pyruvate decarboxylase (PDC) turning pyruvate into acetaldehyde, which is then reduced to ethanol by alcohol dehydrogenase (ADH) ( Zabalza et al., 2009 ; Caruso et al., 2012 ; Borella et al., 2019 ). ADH and PDC play key roles in the ethanol fermentation pathway, and their activity is usually considered as one of the important indexes reflecting the tolerance of plants to waterlogging. Waterlogging-tolerant plants can improve the ethanol fermentation rate by regulating the expression of ADH , PDC , and other related enzyme genes, which can temporarily provide energy for the growth of plants under waterlogging ( Zhang P. et al., 2017 ). Therefore, fermentation is a necessary process of energy metabolism under waterlogging, as shown by the up-regulated expression of anaerobic metabolism genes such as PDCs and ADHs in cucumber, cotton, and soybean ( Komatsu et al., 2011 ; Xu et al., 2014 ; Zhang et al., 2015 ). The seed germination ability of GmADH2 -transgenic soybeans was enhanced under waterlogging, and the GmADH2 gene was induced during glycolysis and ethanol fermentation ( Tougou et al., 2012 ). The overexpression of kiwifruit PDC1 gene in transgenic Arabidopsis enhanced waterlogging tolerance ( Zhang J.Y. et al., 2016 ). These results indicate that PDC and ADH genes play key roles in plant waterlogging tolerance.

Lactate dehydrogenase also participates in the waterlogging stress response, alongside PDC and ADH. Overexpression of LDH significantly enhanced the PDC activity and hypoxia resistance of Arabidopsis , whereas LDH loss of function mutant ldh showed the opposite phenotype ( Dolferus et al., 2008 ). Therefore, lactic acid fermentation is an important pathway in response to waterlogging stress in some plants. The transcript abundances of the ethanol dehydrogenase genes ADH1-1 , ADH1-2 , ADH1-3 , and PDC genes PDC1 and PDC2 were down-regulated in Petunia plants in which an ET-responsive element–binding factor PhERF2 was silenced, whereas they were up-regulated in PhERF2- overexpressing plants. In contrast, the expression of LDH gene LDH was up-regulated in PhERF2- silenced lines and down-regulated in PhERF2- overexpressing lines. This result suggests that the main pathway for NAD + regeneration in PhERF- overexpressing plants is ethanol fermentation, whereas PhERF2- silenced plants might rely on lactic acid fermentation in response to waterlogging stress ( Yin et al., 2019 ).

Although the energy generated via glycolysis and ethanol fermentation can temporarily alleviate the energy deficiency caused by the inhibition of respiration in roots, the accumulation of toxic substances such as lactic acid, alcohols, aldehydes, and other anaerobic metabolites eventually leads to plant death as the time of waterlogging is prolonged ( Tamang et al., 2014 ).

Damage by Reactive Oxygen Species

Reactive oxygen species are a normal product of plant cell metabolism. Insufficient O 2 will also lead to increases in intracellular ROS under waterlogging stress ( Bailey-Serres and Chang, 2005 ; Pucciariello et al., 2012 ). For example, superoxide radicals (⋅O 2 ), hydroxyl radicals (⋅OH), and hydrogen peroxide (H 2 O 2 ) have strong oxidizing activity that can lead to lipid peroxidation and delipidation of leaf membranes, oxidative damage to proteins, oxidative damage to DNA, and severe damage to cell membranes and organelles ( Sharma et al., 2012 ; Baxter et al., 2014 ).

Although excessive ROS are harmful to plant cells, ROS can also act as signaling molecules in plant cells under stress. Plant NADPH oxidase is a key enzyme in the production of ROS and plays a vital role in ROS-mediated signal transduction. The expression of NADPH oxidase–related gene Atrboh D , a gene associated with ROS production, is induced by waterlogging and positively regulates the production of H 2 O 2 and the increase of ADH1 gene expression in Arabidopsis . Therefore, this signal improves the capacity for ethanol fermentation and increases the survival rate of plants under waterlogging ( Sun et al., 2018 ). Analysis of the atrboh d mutant by Yang and Hong (2015) showed that AtRboh D is involved in the primary hypoxia signaling pathway and can regulate the transcription of ET synthesis gene ACC synthetase7/8 (ACS7/8 ), as well as the regulation of hypoxia-induced downstream genes such as ERF73/HRE 1 and ADH1 and the expression of genes encoding peroxidase and cytoplasmic P450. Subsequently, Liu et al. (2017) analyzed the single mutant atrboh d and atrboh f and the double-mutant atrbohd/f. Both Atrboh D and Atrboh F play a role in hypoxia signal through the production of ROS, promoting the increase of Ca 2+ and mediating hypoxia-induced expression of downstream genes, such as ADH1 , PDC1 , ERF73 , MYB2 , LDH , SUS1 , SUS4 , HsfA2 , and HSP18.2 , thus improving the tolerance of Arabidopsis to hypoxia stress. These findings provide new insights into the adaptation mechanism of Rboh gene regulation under waterlogging stress in plants.

H 2 O 2 is an essential signaling molecule involved in ET-induced epidermal cell death. The formation of aerenchyma in rice stems is controlled by H 2 O 2 , indicating that ROS play a key role in regulating various cell death processes in rice ( Steffens et al., 2011 ). H 2 O 2 plays a role in primary hypoxia signaling by regulating ET signal transduction and modulating the transcription of downstream hypoxia-induced genes such as ERF73/HRE1 and ADH1 in Arabidopsis ( Yang, 2014 ). This signal promoted the capacity for ethanol fermentation, temporarily alleviated the energy shortage, and improved the adaptability of the plants to waterlogging.

Under waterlogging stress, plants can rely on antioxidant enzyme systems and other active antioxidants to maintain the dynamic balance of ROS, thus reducing the extent of oxidative damage ( Zhang et al., 2007 ; Bin et al., 2010 ; Doupis et al., 2017 ; Hasanuzzaman et al., 2020 ). Waterlogging treatment resulted in increased activities of catalase (CAT), ascorbate peroxidase (APX), and superoxide dismutase (SOD), as well as polyphenol oxidase. Furthermore, the enzyme activity of waterlogging-resistant lines was significantly higher than that of waterlogging-sensitive lines ( Bansal and Srivastava, 2012 ). Li (2007) took two cucumber varieties with significantly different waterlogging tolerance as test materials and found that the activities of SOD, POD, and CAT, as well as chlorophyll content, soluble sugar content, and CAT content of waterlogging-sensitive lines, decreased rapidly; there was no significant difference between waterlogging-resistant lines in the early stress (1–3 days) treatment and the control. After 3 days, they all decreased rapidly, but the extent of the decrease was smaller than that of waterlogging-sensitive lines. Several genotypes of maize were subjected to waterlogging stress. Genotypes withstanding the waterlogging stress displayed higher SOD, POD, and CAT activities ( Li et al., 2018 ). Similarly, induced SOD and CAT activities were observed in the Sorghum bicolor waterlogging-resistant lines JN01 and JZ31 ( Zhang R. et al., 2019 ). Waterlogging stress was given to barley-tolerant and -sensitive genotypes for 21 days to evaluate the antioxidant response ( Luan et al., 2018 ). The study revealed that SOD, POD, and CAT activities were increased in both the tolerant and sensitive genotypes ( Luan et al., 2018 ). It could be presumed that enhanced antioxidant activities under waterlogging stress can increase the tolerance of plant for a certain amount of time. However, extended waterlogging stress leads to the dysfunctioning of mitochondria, which is the key regulator of antioxidant enzyme activities ( Sharif et al., 2018 ).

The activity of APX in eggplant roots under waterlogging was higher than that of other antioxidant enzymes, and the activity of APX was higher than that of tomato. Consequently, eggplant had higher adaptation ability to waterlogging ( Lin et al., 2004 ). Lee et al. (2014) conducted waterlogging experiments on rapeseed seedlings and found that a CAT-encoding gene was down-regulated, whereas SOD and POD genes were up-regulated. CAT might be involved in controlling H 2 O 2 content by converting H 2 O 2 into O 2 . The down-regulation of this gene would then increase the content of H 2 O 2 in the leaves of rape seedlings and eventually damage the photosynthetic organs, leading to premature aging.

The application of exogenous regulatory substances is one of the main ways to improve the antioxidant capacity of waterlogged crops ( An et al., 2016 ). For example, application of γ-aminobutyric acid can increase the photosynthetic rate and chlorophyll content by triggering the activity of antioxidant enzymes (SOD, POD, CAT, GR, APX), suppress the malondialdehyde (MDA) contents and H 2 O 2 , and thus improve the waterlogging tolerance of maize ( Zea mays L.) ( Salah et al., 2019 ). The H 2 O 2 application at low concentrations can also induce plant tolerance to stress ( Hossain et al., 2015 ). In line with that, Andrade et al. (2018) pretreated soybean seeds with 70 mM H 2 O 2 solution for 24 h and then subjected the seedlings to waterlogging for 32 days. The obtained results revealed that H 2 O 2 pretreatment promoted the antioxidant system activity and net photosynthetic rate under waterlogging and at the same time reduced the production of ROS and the degree of cell membrane damage, conferring enhanced waterlogging tolerance of soybean. The above results indicate that the ROS-scavenging ability of plants can be enhanced by increasing in active antioxidant substances, and the waterlogging-resistant lines maintained high antioxidant enzyme activities that enabled them to resist oxidative damage caused by waterlogging.

Waterlogging Stress Mediated by Plant Hormones

Endogenous plant hormones are closely involved in the regulation of the entire life process of plants, and the balance of various hormones is the basis to ensure normal physiological metabolism, growth, and development of plants ( Bartoli et al., 2013 ; Miransari and Smith, 2014 ; Wang X. et al., 2020 ). The plant changes the balance of synthesis and transport of plant hormones and regulates the response to waterlogging via complex signaling. Plant hormones, as important endogenous signals, play a central role in the mechanism of waterlogging tolerance ( Benschop et al., 2006 ; Wu et al., 2019 ; Yamauchi et al., 2020 ). Some selected recent studies on phytohormones and plant growth regulator–mediated waterlogging tolerance in plants are presented in Table 1 . A model drawing together the interactions of the various signals, growth regulators, genes, and processes involved in the response of plants to waterlogging is summarized in Figure 2 .

Table 1. Recent studies on phytohormones and plant growth regulator mediated waterlogging tolerance in plants.

Figure 2. Model of waterlogging response mechanism in plants. Arrows indicate positive stimuli; lines with blocked ends denote inhibitory effects. Waterlogging-tolerant plants can improve the rate of ethanol and lactic fermentation by enhancing the expression of ADHs , PDCs , and LDHs , whose gene products temporarily provide ATP for the growth of plants under waterlogging. OsEIL1a (an ethylene-responsive transcription factor) promotes SK1/2 transcription and also directly binds the promoter of GA biosynthesis gene SD1 , thereby increasing the synthesis of GA, which stimulates shoot elongation. Increased ethylene levels (ET) inhibit ABA biosynthesis, which leads to increased GA content and induces shoot elongation in deepwater rice cultivars. However, in non-deepwater cultivars, Sub1A negatively regulates the GA response by limiting the degradation of the GA signal inhibitor protein SLR1/SLRL1, which inhibits shoot elongation. An increased BR level in Sub1A rice genotype induces the expression of GA catabolism gene GA2ox7 , which represses GA signaling, so then shoot elongation is inhibited. In addition, the expression of ACS and ACO5 is induced in rice root aerenchyma under waterlogging, thereby promoting ethylene synthesis. Ethylene accumulation enhances auxin biosynthesis and transport, and vice versa . Ethylene enhances the expression of RBOH (NADPH oxidase, respiratory burst oxidase homolog) and induces ROS signals, which finally lead to the formation of ARs and aerenchyma. Furthermore, SA triggers a programmed cell death response, which leads to the development of aerenchyma cells. At the same time, the accumulation of SA stimulates the formation of AR primordia. JA inhibits AR growth and inhibits the action of SA under waterlogging. The application of MT enhanced tolerance to waterlogging stress by triggering the generation of PA biosynthesis, suppression of excessive ROS, and then improved photosynthetic machinery and aerobic respiration. Interestingly, the MT-treated plants under waterlogging stress exhibited decrease expression pattern of ethylene biosynthesis and signaling gene.

Ethylene is a gaseous hormone in plants, and its diffusion rate is extremely low in water. The rapid accumulation of ET is an important way in which plants respond to waterlogging ( Alpuerto et al., 2016 ; Hartman et al., 2019a,b ).

1-Aminocyclopropane-1-carboxylic acid (ACC), the direct precursor in the biosynthesis of ET, is produced in large quantities under the catalysis of ACC synthase (ACS), and the process can occur under hypoxic conditions. ACC is converted to ET under the catalysis of ACC oxidase (ACO), but the process needs the participation of O 2 ; thus, ACC needs to be continuously transferred from the hypoxic environment of the root system to the lower region of the plant’s aerobic part where the oxidation reaction can take place, finally producing ET. Rauf et al. (2013) found that waterlogging directly or indirectly activates the expression of ACO5 and ACS genes in Arabidopsis and increases ET biosynthesis.

ET synthesis and perception are necessary for AR formation. Waterlogging treatment was carried out on 4-week-old tomato ( Solanum lycopersicum ) seedlings, and 500 μM aminoethoxyvinylglycine (AVG), which inhibits ET biosynthesis, was sprayed on the above-ground parts daily. After 72 h of waterlogging, AR primordia became visible in the stem base of waterlogged plants that had not been treated with AVG, and these primordia elongated and generated a large number of ARs within 7 days. The number of ARs in tomato plants treated with the inhibitor AVG was significantly lower than in untreated plants ( Vidoz et al., 2010 ). Qi et al. (2019) found that treating cucumber seedlings with 1 mg/L 1-methylcyclopropene (1-MCP, an ET receptor inhibitor) before waterlogging inhibited the formation of ARs, whereas exogenous 10 μM ACC promoted the formation of ARs under waterlogging. Kim et al. (2018) not only significantly induced the occurrence of ARs on soybean plants but also increased the root surface area by exogenous application of 50, 100, or 200 μM ethephon, a synthetic plant growth regulator that produces ET when metabolized.

The production of endogenous ET is closely related to the development of aerenchyma cells ( Kreuzwieser and Rennenberg, 2014 ; Mignolli et al., 2020 ). The expression of ACS1 and ACO5 is induced in rice root aerenchyma under hypoxia and promotes ET synthesis. At the same time, ET induces cortical cell death, mediated by ROS, leading to aerenchyma formation ( Yamauchi et al., 2017 ). ET accumulates in roots under waterlogging as its biosynthesis continues and the diffusion rate in water is low. ET stimulates programmed cell death that occurs during the formation of lysogenic aerenchyma ( Sasidharan and Voesenek, 2015 ). The accumulation of ET triggers the formation of lysosomal aerenchyma in maize ( Yamauchi et al., 2016 ), rice ( Yamauchi et al., 2017 ), and wheat ( Yamauchi et al., 2014 ).

ET response factor ( ERF ) is an important transcription factor involved in plant responses to several different biotic and abiotic stresses. The ERF family genes specifically induce genes containing AGCCGCC elements and DRE/CRT cis -elements, activating or inhibiting the expression of downstream functional genes, and thereby mediating plant tolerance to various stresses ( Yin et al., 2019 ). ERF transcription factors are regulated by ET, and exogenous ET significantly promotes ERF transcription in Arabidopsis and soybean ( Hess et al., 2011 ; Tamang et al., 2014 ). ET regulates the response of Arabidopsis to hypoxia stress through ERF73/HRE1 ( Hess et al., 2011 ).

Group VII ET-response factors ( ERF -VIIs) play an important role in ET signal transduction and plant responses to waterlogging ( Gasch et al., 2016 ; Giuntoli and Perata, 2018 ). The gene ZmEREB180 , a member of the ERF -VII family in maize, positively regulates the growth and development of ARs and the level of ROS: overexpression of ZmEREB180 in maize also improves the survival rate after long-term waterlogging stress ( Yu et al., 2019 ). The PhERF2 protein binds directly with the promoter of ADH-related gene ADH1-2. PhERF2 -RNAi lines had a mortality rate of 96% after flooding. Almost all PhERF2- overexpressing lines survived and showed faster and stronger recovery than WT plants ( Yin et al., 2019 ).

The rice Sub1A ( Submergence1A ) gene is another member of the ET-response factor ERF -VII family. Overexpression of Sub1A enhanced the transcription of ADH1 in transgenic rice and at the same time led to the enhanced ability to withstand waterlogging stress. Therefore, Sub1A gene could be the main determinant of submergence tolerance ( Xu et al., 2006 ). Interestingly, the other two ERF -VII gene family members in rice, SK1/2 ( SNORKEL1/2 ), can also regulate the waterlogging tolerance of rice. Overexpression of SK1/2 led to internode elongation and significantly improved the waterlogging tolerance of deepwater rice cultivars ( Hattori et al., 2009 ).

However, Sub1A and SK1/2 have opposite functions in regulating rice growth in response to waterlogging. Sub1A negatively regulates the GA response by limiting the degradation of the DELLA family protein SLR1 (Slender Rice-1), which are GA signal inhibitors, and thereby inhibits the elongation of rice ( Fukao and Bailey-Serres, 2008 ; Hattori et al., 2009 ). Plants temporarily inhibit energy metabolism until water recedes, an effective long-term submergence strategy that occurs in rice mainly in non-deepwater cultivars ( Xu et al., 2006 ; Bailey-Serres and Voesenek, 2008 ). In contrast, SK1/2 stimulates GA synthesis, which promotes rapid growth of rice stems and internode petioles, a structural change that allows rice leaves to respire normally once they have extended away from the water. The reason was found to be that submersion induced ET accumulation in rice and positively regulated the stability of OsEIL1a , an ET-responsive transcription factor ( Kuroha et al., 2018 ). OsEIL1a protein promotes SK1/2 transcription by directly binding to the SK1/2 promoter, and then SK1/2 mediates the expression of downstream genes to initiate shoot elongation ( Kuroha et al., 2018 ). OsEIL1a also directly binds and transcribes the promoter of GA biosynthesis gene SEMIDWARF1 ( SD1 ), and SD1 protein promotes the synthesis of GA, mainly GA 4 , thus promoting shoot elongation ( Kuroha et al., 2018 ). This evidence indicates that the OsEIL1a–SD1–SK1/2 cascade is closely related to waterlogging tolerance in deepwater rice cultivars.

Abscisic Acid

Abscisic acid (ABA) has a main role in regulating stomata by adjusting the size of guard cells, thereby regulating the water potential in plants. Because of this, ABA is considered to be a key hormone in water stress responses ( Zhu, 2016 ; He et al., 2018 ).

Abscisic acid is involved in the development of root aerenchyma under waterlogging. The ABA concentration in soybean hypocotyls decreased rapidly under waterlogging, falling by 50% within 24 h compared with plants without waterlogging. In addition, secondary aeration tissues appeared after 72 h. Exogenous 1 μM ABA treatment inhibited the cell development of aerenchyma, suggesting that the formation of secondary aerenchyma required a reduction in the concentration of the negative regulatory factor ABA ( Shimamura et al., 2014 ).

During waterlogging stress of Solanum dulcamara , following the rapid down-regulation of ABA biosynthesis and up-regulation of ABA decomposition, the ABA concentration in the stem and AR primordia decreased sharply ( Dawood et al., 2016 ). Waterlogging resulted in ET accumulation in the lower stem and subsequently reduced ABA concentrations in the stem and AR primordia. 1 mM ABA treatment significantly inhibited the formation of ARs induced by waterlogging, whereas 100 μM ABA inhibitor (Fluridone) induced AR production ( Dawood et al., 2016 ). These results showed that ABA, in contrast to ET, negatively regulated the formation of ARs under waterlogging. Kim et al. (2015) determined the plant hormone content in soybeans after waterlogging for 5 and 10 days and found that the ABA content significantly decreased. The ABA content in waterlogging-resistant lines was significantly lower than that in sensitive lines, indicating that ABA might be negatively correlated with waterlogging tolerance. Waterlogging increased shoot elongation in deepwater rice cultivars partly by reducing the endogenous ABA content and thereby increasing the GA concentration ( Yang and Choi, 2006 ). Similarly, ET and its precursor ACC rapidly induced the expression of OsABA8ox1 . In addition, ET receptor inhibitor 1-MCP pretreatment partially inhibited the expression of OsABA8ox1 . These results indicated that the rapid decline of ABA in deepwater rice cultivars under waterlogging was partly controlled by ET-induced OsABA8ox1 expression ( Saika et al., 2007 ).

The relative expression of the kiwifruit ( Actinidia deliciosa ) gene AdPDC1 encoding pyruvate decarboxylase was significantly up-regulated under waterlogging, suggesting that the gene played an important role in the waterlogging response. ABA down-regulated the expression of AdPDC1 under waterlogging, whereas the overexpression of AdPDC1 in Arabidopsis inhibited seed germination and root elongation under ABA treatment, indicating that ABA might negatively regulate AdPDC1 under waterlogging ( Zhang J.Y. et al., 2016 ).

However, other studies have shown that accumulation of ABA accelerated in the above-ground parts of the plant under waterlogging. ABA increased the accumulation of H 2 O 2 and promoted stomatal closure, thus reducing the water loss from transpiration and improving the resistance of plants to waterlogging and related adverse environmental conditions. Overexpression of AP2/ERF family gene RAP2.6L in Arabidopsis promoted the expression of ABA biosynthesis genes, thus increasing ABA concentration. The increased ABA in RAP2.6L -overexpressing plants led to initiation of the antioxidant defense system and stomatal closure and finally resulted in reduced oxidative damage, delayed senescence, and significantly improved waterlogging tolerance ( Liu et al., 2012 ). A significant increase in ABA content induced by waterlogging has been reported in cotton ( Zhang Y. et al., 2016 ), wheat ( Nan et al., 2002 ), and other crops. Komatsu et al. (2013) found that addition of 5, 10, and 50 μM ABA during waterlogging significantly improved soybean survival compared with waterlogging treatment alone. Similarly, pretreatment with 10 μM ABA had recorded affirmative responses in rice net assimilation rate, relative growth rate, and chlorophyll content under submergence ( Saha et al., 2021 ).

Auxin (IAA) plays an important role in plant growth and development ( Kazan and Manners, 2009 ; Lv et al., 2019 ). ET production, as an early response to waterlogging, can promote the transport of auxin, and conversely, the accumulation of auxin can prompt ET biosynthesis, further stimulating auxin transport to flooded parts of the plant, where the accumulation of auxin can induce ARs by initiating cell division. Exogenous application of the auxin transport inhibitor 1-naphthylphthalamic acid (NPA) to tomato ( Vidoz et al., 2010 ), cucumber ( Qi et al., 2019 ), and tobacco ( McDonald and Visser, 2003 ) led to inhibition of AR growth after flooding.

The dynamic transport of auxin in plants is mediated by the auxin polar transport carrier protein PIN (PIN-FORMED), and treatment of rice with the transport inhibitor NPA decreased the expression of OsPIN2 , suggesting that NPA might inhibit the production of ARs through an effect on PIN ( Lin and Sauter, 2019 ). Similarly, when auxin polar transport was blocked in PIN expression–deficient mutants of S. dulcamara , the formation of ARs was inhibited, which further confirmed that AR production required auxin transport ( Dawood et al., 2016 ).

However, some studies found that waterlogging reduced the content of IAA in soybean plants. Shimamura et al. (2016) found that the hypocotyl could form ARs and aerenchyma after 72 h of waterlogging, but physiological tests showed no significant difference within 72 h in the endogenous IAA concentration in the hypocotyl between the waterlogged and the control groups. This result showed that the accumulation of IAA was not a necessary condition for the formation of secondary aerenchyma in soybean hypocotyls under waterlogging.

Waterlogging can cause a large amount of carbohydrate consumption in plants, leading to energy shortage. Qi et al. (2020) first proposed a model for the interaction of sugars with auxin-induced AR initiation and elongation in waterlogged cucumber. Under waterlogging stress and in light conditions, photosynthesis supported the biosynthesis of sugars, whose accumulation induced auxin transport and subsequent signal transduction, and finally induced the formation of ARs in the hypocotyl.

Gibberellin

GAs are one of the essential plant hormones regulating growth and development. GAs regulate multiple processes in plant growth and development, mainly by controlling the size and number of cells ( Nelissen et al., 2012 ).

Studies on different genotypes of soybean found that GA content in waterlogging-tolerant lines significantly increased under waterlogging, and GA content in waterlogging-resistant lines was significantly higher than that in waterlogging-sensitive lines ( Kim et al., 2015 ). Huang et al. (2018) determined physiological indexes of peanuts ( Arachis hypogaea ) under waterlogging and found that spraying GA on the leaf surface could promote the growth of upper and underground parts of peanut plants and significantly increase the yield. Wang et al. (2016) showed that exogenous GA could effectively reduce the MDA content in the leaves and roots of rape under waterlogged conditions, thus improving the tolerance of plants to waterlogging.

Treatment with inhibitors of GA biosynthesis significantly reduced internode elongation in rice under waterlogging ( Hattori et al., 2009 ; Ayano et al., 2014 ). Mutations in GA biosynthesis ( Os1 , OsCPS2 , OsKS2 , OsKS5 , OsKO2 , OsKAO , Os13ox , OsGA20ox1 , OsGA20ox2 , OsGA20ox3 , OsGA3ox1 , OsGA3ox2 ) and signal transduction genes ( OsGID1 , OsGID2 , OsSPY , OsSEC , OsGAMYB ) also inhibited internode elongation ( Ayano et al., 2014 ). Waterlogged rice plants treated with exogenous GA were able to restore internode elongation, enabling the leaves to respire normally once away from the flood water. GA has been shown to be a key hormone in improving rice tolerance under waterlogged conditions. Under waterlogging, GA participates in the SK1/2 gene-mediated response pathway, and the GA content is up-regulated, leading to internode elongation. This structural change causes rice to extend above the water surface and reestablish gas exchange between plant tissue and the air ( Hattori et al., 2009 ; Ayano et al., 2014 ). GA biosynthesis gene SD1 was shown to be the cause of internode elongation under waterlogging. When submerged, the SD1 gene was activated by OsEIL1a , an ET-responsive transcription factor, and SD1 protein promoted the synthesis of GA, mainly GA 4 , which promoted the rapid growth of leaf stalk internodes in rice ( Kuroha et al., 2018 ). The results indicated that GA is centrally involved in promoting internode elongation in rice under waterlogged conditions.

Salicylic Acid

Salicylic acid (SA) is a common phenolic compound in plants, which regulates the antioxidant mechanism of cells by inducing the expression of stress-related genes, thus enhancing the adaptability of plants to adverse conditions ( Zhou et al., 2009 ; Hayat et al., 2010 ; Arif et al., 2020 ).

Salicylic acid, as a signal substance, can induce changes in physiological characteristics of waterlogged plants. Peach trees ( Prunus persica L.) were subjected to waterlogging stress. Spraying exogenous SA on day 1 of waterlogging can significantly increase the activities of ethanol dehydrogenase, protective enzymes such as POD and CAT, and the content of proline in leaves and roots, thereby protecting leaves and root membranes from damage and stabilizing photosynthetic capacity of leaves as well as root activity. Together, these protective effects are conducive to the alleviation of waterlogging-induced stress ( Wang et al., 2015 ).

An increase of SA content might be an important factor in tolerance of waterlogging stress. Studies have shown that SA regulates two different physiological responses. First, an increase in intracellular SA triggers a programmed cell death response, leading to an increase in lipid peroxidation in the root cell walls, which in turn leads to the development of aerenchyma cells within the root. Aerenchyma cells can increase oxygen transfer into the root tissues and alleviate waterlogging stress. Second, the accumulation of SA stimulates the formation of AR primordia and further enhances waterlogging tolerance by inducing the development of a large number of ARs ( Kim et al., 2015 ).

Kim et al. (2015) measured SA content in soybean after 5 and 10 days of waterlogging and found that the content of SA in waterlogging-tolerant soybean PI408105A was significantly higher than that in the unstressed control, whereas the content of SA in waterlogging-sensitive soybean S99-2281 was not significantly different from that in the control. Elevated SA would stimulate the formation of ARs, promote gas exchange, and ultimately enhance waterlogging tolerance. Bai et al. (2009) found that spraying exogenous SA alleviated oxidative stress damage caused by hypoxia stress on plants, and enhanced the hypoxia tolerance of Begonia occidentalis . The above results indicate that appropriate SA level can promote the formation of ARs and aerenchyma, which is positively correlated with the waterlogging tolerance of plants.

Jasmonic Acid

Jasmonic acid (JA) is a basic plant growth regulator that is known to be involved in the defense response produced by abiotic stress, but there are few studies on the relationship between JA and waterlogging tolerance ( Per et al., 2018 ; Farhangi-Abriz and Ghassemi-Golezani, 2019 ; Raza et al., 2020 ; Wang J. et al., 2020 ).

Xu et al. (2016) found that the JA content in hypocotyl of Pepino, a waterlogging-sensitive cucumber line, was about twice that of the unstressed control after 2 days of waterlogging. However, JA content in the hypocotyl of the waterlogging-resistant line Zaoer-N decreased significantly during waterlogging to only 0.33 that of the control. The result suggested that JA is negatively correlated with the waterlogging tolerance of plants. However, other research showed that JA treatment inhibited root growth and the action of SA under waterlogging. Compared with the control, 649 different proteins were found in waterlogged soybeans treated with JA, which were mainly related to the stress response metabolite pathway, glycolysis, ethanol fermentation, and cell wall and cell tissue metabolism. The application of JA significantly reduced the damage to soybean plants under waterlogging and promoted plant growth by changing the proteomic profile ( Kamal and Komatsu, 2016 ). There can be significant differences in JA content in different tissues of the same plant under waterlogging conditions. Under waterlogging stress, the JA content in citrus leaves increased significantly compared with the unstressed control, but the JA concentration in the root system decreased sharply. This might be caused by inhibition of the key lipoxygenase of the JA synthesis pathway under hypoxic conditions ( Arbona and Gómez-Cadenas, 2008 ).

The interaction between JA and ET plays an important role in the formation and development of the root system and aerenchyma under waterlogging stress. Spraying methyl jasmonate on the leaves increased the content of ET ( Hudgins and Franceschi, 2004 ). Thus, exogenous JA can increase the content of ET, which is beneficial in relieving waterlogging stress.

Brassinosteroid

Brassinosteroid (BR) is a naturally occurring steroid in plants. BR can induce resistance to a variety of biological and abiotic stresses, thus promoting plant growth and development ( Bajguz and Hayat, 2009 ; Huang et al., 2020 ; Nazir et al., 2021 ).

Exogenous 24-epi-brassinolide (EBR) promotes the transfer of carbohydrates from leaves to roots of cucumber seedlings under hypoxic stress, enhances the activity of glycolytic enzymes in the roots, and triggers the antioxidant enzymes activity and reduced ROS production, thus improving the resistance of the seedlings to hypoxic stress ( Kang et al., 2009 ). EBR also improved enzyme activity related to cell wall degradation by promoting ET production in cucumber seedlings. It further promoted the expansion and loosening of cucumber hypocotyl and formation of ARs, thus improving the oxygen supply status of the plant and enhancing the tolerance of the plant to hypoxic stress ( Ma and Guo, 2014 ).

The Sub1A gene, an ET-response factor ERF-VII family member, has different regulatory effects on brassinolide biosynthetic gene expression and rice shoot elongation under waterlogging, compared with exogenous BR. Exogenous BR pretreatment can activate the tolerance mechanism in waterlogging-tolerant rice genotypes and inhibit shoot elongation under waterlogging. Compared to the LOES, higher expression of BR biosynthesis genes was observed in the Sub1A rice genotype, which triggered the endogenous BR level. The enhanced BR level induced the transcription of GA catabolism gene GA2ox7 resulting in reduced GA contents. At the same time, GA-mediated responses can be negatively regulated under submerged conditions by a DELLA family member, the GA-signal inhibitory factor SLR1 protein, so that the elongation of rice plants is inhibited ( Schmitz et al., 2013 ). Therefore, BR limited shoot elongation by inhibiting GA biosynthesis and decreasing the action of GA in the rice Sub1A genotype.

Some selected recent studies on Phytohormones and plant growth regulator mediated waterlogging tolerance in plants are presented in Table 1 .

Melatonin (MT) is a phytohormone and an excellent antioxidant molecule that augments plant growth under adverse conditions ( Sharif et al., 2018 ). The MT has been previously reported for its mitigatory role of numerous abiotic stresses ( Sharif et al., 2018 ). Owing to that, research related to MT and its involvement in improving waterlogging stress tolerance is relatively less, and only few research articles are available ( Moustafa-Farag et al., 2020 ).

The very first report over MT in response to waterlogging stress unraveled that it can mend plant tolerance by inducing the activity of antioxidant enzymes, suppression of harmful ROS, and maintained proper growth to ensure good yield ( Chen et al., 2015 ). Following that, the young apple seedlings subjected to waterlogging stress were treated with MT ( Zheng et al., 2017 ). The study showed that seedling treated with MT presented enhanced tolerance to waterlogging stress by triggering the generation of antioxidant enzymes activities, improved aerobic respiration, and photosynthetic machinery ( Zheng et al., 2017 ). On the other hand, the application of MT significantly inhibited the deleterious effects of anaerobic respiration and MDA- and ROS-induced chlorosis ( Zheng et al., 2017 ). The induced expression level of MT biosynthesis genes such as MbT5H1 , MbAANAT3 , and MbASMT9 increased the production of endogenous MT in the seedlings treated with MT ( Zheng et al., 2017 ). Therefore, it can be assumed that MT plays a key role in regulating the response of plants to waterlogging stress. The growth of the alfalfa plant has been hampered by the waterlogging stress by dysfunctioning the photosynthetic ability and boosted the generation of electrolyte leakage and MDA contents ( Zhang Q. et al., 2019 ). The up-regulated expression level of PA biosynthesis genes also highlighted their involvement in regulating the alfalfa response to waterlogging stress ( Zhang Q. et al., 2019 ). The application of MT at the rate of 100 μM over 6-week-old alfalfa seedlings displayed tolerance to waterlogging stress ( Zhang Q. et al., 2019 ). The enhanced tolerance post–MT application was associated with the further induction in the expression of PAs biosynthesis genes ( SPDS , SPMS , and ADC ). Also, the exogenous MT treatment not only increased the endogenous MT level but also stabilized the normal functioning of other biochemical and physiological parameters ( Zhang Q. et al., 2019 ). Further, the MT-treated plants under waterlogging stress exhibited decreased expression pattern of ET biosynthesis and signaling genes ( ACS , ACO , and ERF ) ( Zhang Q. et al., 2019 ). This means that MT and ET possess an antagonistic relationship under waterlogging stress. However, no report is available to confirm the antagonistic crosstalk between MT and ET. P. persica is considered one of the most hypoxia-intolerant stone fruits. However, waterlogging, which causes hypoxia, occurs frequently in southern China, where peaches are commercially important ( Gu et al., 2020 ). The application of MT at the rate of 200 μM substantially augmented the antioxidant activities, suppressed the lipid peroxidation, and H 2 O 2 , positively regulated the size of aerenchyma for better anaerobic respiration activities and induced mRNA level of Ca 2+ signaling and hypoxia-related ERF VII transcription factor genes ( Gu et al., 2020 ). Therefore, it can be suggested that the application of MT positively regulates the ET homeostasis, which is an important and crucial factor in inducing waterlogging stress tolerance.

Inducing Waterlogging Tolerance via Genetic Engineering

The manipulation of targeted plant genes to increase the production capacity or tolerance against a certain stress is becoming the need of the day ( Lemay and Moineau, 2020 ). As the climate threat looms over the safe production of agronomic and horticultural crops, genome editing techniques can play a significant role in decreasing the adverse environmental effects ( Lemay and Moineau, 2020 ). Previous studies have shown that the deleterious effects of the waterlogging stress can be mimicked by utilizing the genome editing tools. For example, the overexpression of AtACO5 gene in Arabidopsis triggered the ET production, and cell expansion activities resulted in enhanced tolerance against waterlogging stress ( Rauf et al., 2013 ). The overexpression of CsARN6.1 gene in cucumber facilitates the formation of ARs independent of hormonal generations. However, the increased number of ARs in the overexpressed CsARN6.1 lines was associated with the intense cellular activities and hydrolysis of the ATP energy packets ( Xu et al., 2018 ). The ERF transcription factors are directly involved in the regulation of waterlogging stress. A member of ERF transcription factor family PhERF2 was characterized in petunia ( Yin et al., 2019 ). Up-regulation in the transcript abundance of PhERF2 was observed under waterlogging stress. To further highlight the role, the PhERF2 overexpressed lines were generated, which displayed enhanced tolerance to waterlogging stress. On the contrary, the RNAi line of PhERF2 showed sensitivity to waterlogging ( Yin et al., 2019 ). The genes influence the alcoholic fermentation process such as ADH1-1 , ADH1-2 , ADH1-3 , PDC1 , and PDC2 induced and suppressed in overexpressed and silenced plants, respectively ( Yin et al., 2019 ). Similarly, the induced expression levels of NtPDC , NtADH , NtHB1 , NtHB2 , NtPCO1 , and NtPCO2 genes in AdRAP2.3 overexpressed tobacco plants presented its association with the enhanced waterlogging stress tolerance ( Pan et al., 2019 ). In wheat, waterlogging stress can significantly hinder the physiological activities particularly photosynthesis, which ultimately reduce the grain yield and affect overall yield. The constitutive expression of TaERFVII.1 gene in wheat alleviated the negative effects of waterlogging stress by boosting the immunity resulting in increased grain weight per plant, improved survival rate, and better chlorophyll content of leaves ( Wei et al., 2019 ). On the other hand, the compromised expression of TaERFVII.1 in silenced plants also decreased the transcript of several waterlogging−responsive genes ( Wei et al., 2019 ). Interestingly, the constitutive expression of TaERFVII.1 did not negatively impact both plant development and grain yield under standard conditions by suppressing the TaSAB18.1 gene ( Wei et al., 2019 ). The barley HvERF2.11 when overexpressed in Arabidopsis triggered the expression level of antioxidant enzyme biosynthesis genes ( AtSOD1 , AtPOD1 ) and ET biosynthesis gene ( AtACO1 ), conferring resistance to waterlogging stress ( Luan et al., 2020 ). The HD-ZIP I subfamily gene HaHB11 was overexpressed in the Arabidopsis and exposed to waterlogging stress ( Cabello et al., 2016 ). The transgenic Arabidopsis plants carrying gain-of-function HaHB11 gene not only induced the tolerance to waterlogging stress but also increased the biomass and yielded more seeds than control by inducing the glucose and sucrose level ( Cabello et al., 2016 ). In addition, the HaHB11 were notably involved in the increment of expression of genes involved in the alcohol fermentation ( Cabello et al., 2016 ). Multiple studies highlighting the importance of genetic engineering in augmenting the immunity of plants to waterlogging stress are presented in Table 2 .

Table 2. Listed studies related to improved waterlogging tolerance via genetic engineering.

Conclusion and Outlook

The regulation of plant growth and development processes under waterlogging stress is very complex, with different crops, different varieties of the same crop, and different growth periods of the same crop often showing great differences, while different plant species evolved different adaptation strategies. At present, research on crop waterlogging tolerance is mainly carried out from the perspective of morphological, structural, physiological, biochemical, and metabolic gene signal regulation. The most effective ways to enhance plant waterlogging tolerance will be (1) improving cultivation management to reduce the direct damage to crops caused by waterlogging and (2) using modern molecular biology technology to discover the key genes regulating waterlogging tolerance and verify their functions.

Building on existing research results and aiming to address identified problems, the following aspects should receive increased attention in future research on plant waterlogging tolerance:

(1) Current studies focus mainly on the vegetative growth stage of plants under waterlogging stress. However, the molecular responses during seed germination, early seedling morphogenesis, and late reproductive growth under waterlogging stress are neglected topics that warrant further study.

(2) Although a large number of related genes regulating plant waterlogging tolerance have been obtained by transcriptomics, proteomics, and other methods. However, most of them are preliminary study and required functional characterization.

(3) There is a need to exploit additional genetic resources for waterlogging tolerance, using both isolated populations and natural populations to identify waterlogging tolerance–related genes.

(4) The hormonal-induced waterlogging resistance has been studied extensively. Majority of the available studies mainly reported the effects of growth hormones on vegetative stages under waterlogging stress. Although studies are missing to investigate the role of these phytohormones when waterlogging stress happens at reproductive stages of the plant. Hormonal crosstalk under waterlogging stress in the early developmental stages of plant has been investigated and is presented in Figure 2 . However, it could be interesting to examine the complex hormonal crosstalk under waterlogging stress during reproductive stages, such as how these hormones ensure plant productivity under prolonged waterlogging stress. Additionally, is there an unknown genetic factor(s) controlling phytohormone-mediated cascades under waterlogging condition? Therefore, it is of great importance to elucidate these mechanisms to develop waterlogging resilience plants to increase crop productivity particularly in the areas that have poor soil drainage properties, those affected by frequent heavy rainfall, and areas with duplex soil.

Author Contributions

JP wrote the manuscript. RS, XX, and XC revised and finally approved the manuscript for publication. All the authors contributed to the article and approved the submitted version.

This research was supported by the National Natural Science Foundation of China (grant nos. 32030093 and 31801883) and Natural Science Foundation of Jiangsu Province (BK20180913).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank Dr. Qi Xioahua (College of Horticulture and Plant Protection, Yangzhou University) for critically revising the manuscript.

Abiko, T., and Miyasaka, S. C. (2020). Aerenchyma and barrier to radial oxygen loss are formed in roots of Taro (Colocasia esculenta) propagules under flooded conditions. J. Plant Res. 133, 49–56. doi: 10.1007/s10265-019-01150-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Alpuerto, J. B., Hussain, R. M. F., and Fukao, T. (2016). The key regulator of submergence tolerance, SUB1A, promotes photosynthetic and metabolic recovery from submergence damage in rice leaves. Plant Cell Environ. 39, 672–684. doi: 10.1111/pce.12661

An, Y., Qi, L., and Wang, L. (2016). ALA pretreatment improves waterlogging tolerance of fig plants. PLoS One 11:e0147202. doi: 10.1371/journal.pone.0147202

Andrade, C. A., de Souza, K. R. D., de Oliveira Santos, M., da Silva, D. M., and Alves, J. D. (2018). Hydrogen peroxide promotes the tolerance of soybeans to waterlogging. Sci. Horticult. 232, 40–45. doi: 10.1016/j.scienta.2017.12.048

CrossRef Full Text | Google Scholar

Anee, T. I., Nahar, K., Rahman, A., Mahmud, J. A., Bhuiyan, T. F., Alam, M. U., et al. (2019). Oxidative damage and antioxidant defense in Sesamum indicum after different waterlogging durations. Plants 8:196. doi: 10.3390/plants8070196

Arbona, V., and Gómez-Cadenas, A. (2008). Hormonal modulation of citrus responses to flooding. J. Plant Growth Regulat. 27:241. doi: 10.1007/s00344-008-9051-x

Arif, Y., Sami, F., Siddiqui, H., Bajguz, A., and Hayat, S. (2020). Salicylic acid in relation to other phytohormones in plant: a study towards physiology and signal transduction under challenging environment. Environ. Exp. Bot. 175:104040. doi: 10.1016/j.envexpbot.2020.104040

Ayano, M., Kani, T., Kojima, M., Sakakibara, H., Kitaoka, T., Kuroha, T., et al. (2014). Gibberellin biosynthesis and signal transduction is essential for internode elongation in deepwater rice. Plant Cell Environ. 37, 2313–2324. doi: 10.1111/pce.12377

Bai, T., Li, C., Ma, F., Shu, H., and Han, M. (2009). Exogenous salicylic acid alleviates growth inhibition and oxidative stress induced by hypoxia stress in Malus robusta Rehd. J. Plant Growth Regulat. 28, 358–366. doi: 10.1007/s00344-009-9104-9

Bailey-Serres, J., and Chang, R. (2005). Sensing and signalling in response to oxygen deprivation in plants and other organisms. Ann. Bot. 96, 507–518. doi: 10.1093/aob/mci206

Bailey-Serres, J., and Voesenek, L. (2008). Flooding stress: acclimations and genetic diversity. Annu. Rev. Plant Biol. 59, 313–339. doi: 10.1146/annurev.arplant.59.032607.092752

Bailey-Serres, J., Fukao, T., Gibbs, D. J., Holdsworth, M. J., Lee, S. C., Licausi, F., et al. (2012). Making sense of low oxygen sensing. Trends Plant Sci. 17, 129–138.

Google Scholar

Bajguz, A., and Hayat, S. (2009). Effects of brassinosteroids on the plant responses to environmental stresses. Plant Physiol. Biochem. 47, 1–8. doi: 10.1016/j.plaphy.2008.10.002

Bansal, R., and Srivastava, J. P. (2012). Antioxidative defense system in pigeonpea roots under waterlogging stress. Acta Physiol. Plant. 34, 515–522. doi: 10.1007/s11738-011-0848-z

Bartoli, C. G., Casalongué, C. A., Simontacchi, M., Marquez-Garcia, B., and Foyer, C. H. (2013). Interactions between hormone and redox signalling pathways in the control of growth and cross tolerance to stress. Environ. Exp. Bot. 94, 73–88. doi: 10.1016/j.envexpbot.2012.05.003

Baxter, A., Mittler, R., and Suzuki, N. (2014). ROS as key players in plant stress signalling. J. Exp. Bot. 65, 1229–1240. doi: 10.1093/jxb/ert375

Baxter-Burrell, A., Yang, Z., Springer, P. S., and Bailey-Serres, J. (2002). RopGAP4-dependent Rop GTPase rheostat control of Arabidopsis oxygen deprivation tolerance. Science 296, 2026–2028. doi: 10.1126/science.1071505

Benschop, J. J., Bou, J., Peeters, A. J., Wagemaker, N., Gühl, K., Ward, D., et al. (2006). Long-term submergence-induced elongation in Rumex palustris requires abscisic acid-dependent biosynthesis of gibberellin1. Plant Physiol. 141, 1644–1652. doi: 10.1104/pp.106.082636

Bin, T., Xu, S.-Z., Zou, X.-L., Zheng, Y.-L., and Qiu, F.-Z. (2010). Changes of antioxidative enzymes and lipid peroxidation in leaves and roots of waterlogging-tolerant and waterlogging-sensitive maize genotypes at seedling stage. Agricult. Sci. China 9, 651–661. doi: 10.1016/s1671-2927(09)60140-1

Borella, J., Becker, R., Lima, M. C., Oliveira, D. D. S. C. D., Braga, E. J. B., Oliveira, A. C. B. D., et al. (2019). Nitrogen source influences the antioxidative system of soybean plants under hypoxia and re-oxygenation. Sci. Agricol. 76, 51–62. doi: 10.1590/1678-992x-2017-0195

Cabello, J. V., Giacomelli, J. I., Piattoni, C. V., Iglesias, A. A., and Chan, R. L. (2016). The sunflower transcription factor HaHB11 improves yield, biomass and tolerance to flooding in transgenic Arabidopsis plants. J. Biotechnol. 222, 73–83. doi: 10.1016/j.jbiotec.2016.02.015

Caruso, P., Baldoni, E., Mattana, M., Paolo, D. P., Genga, A., Coraggio, I., et al. (2012). Ectopic expression of a rice transcription factor, Mybleu, enhances tolerance of transgenic plants of Carrizo citrange to low oxygen stress. Plant Cell Tissue Organ Cult. (PCTOC) 109, 327–339. doi: 10.1007/s11240-011-0098-1

Chen, H., Feng, C., Kong, J., Wang, L., Wang, N., Zheng, X., et al. (2015). Use of product containing melatonin as effective component for improving waterlogging stress resistance in plants. Google Patent No. A01N-043/38 201612.

Colmer, T. (2002). Aerenchyma and an inducible barrier to radial oxygen loss facilitate root aeration in upland, paddy and deep−water rice ( Oryza sativa L.). Ann. Bot. 91, 301–309. doi: 10.1093/aob/mcf114

Dawood, T., Yang, X., Visser, E. J., Te Beek, T. A., Kensche, P. R., Cristescu, S. M., et al. (2016). A co-opted hormonal cascade activates dormant adventitious root primordia upon flooding in Solanum dulcamara. Plant Physiol. 170, 2351–2364. doi: 10.1104/pp.15.00773

Ding, J., Liang, P., Wu, P., Zhu, M., Li, C., Zhu, X., et al. (2020). Effects of waterlogging on grain yield and associated traits of historic wheat cultivars in the middle and lower reaches of the Yangtze River, China. Field Crops Res. 246:107695. doi: 10.1016/j.fcr.2019.107695

Dolferus, R., Wolansky, M., Carroll, R., Miyashita, Y., Ismond, K., and Good, A. (2008). Functional analysis of lactate dehydrogenase during hypoxic stress in Arabidopsis . Funct. Plant Biol. 35, 131–140. doi: 10.1071/fp07228

Doupis, G., Kavroulakis, N., Psarras, G., and Papadakis, I. (2017). Growth, photosynthetic performance and antioxidative response of ‘Hass’ and ‘Fuerte’avocado (Persea americana Mill.) plants grown under high soil moisture. Photosynthetica 55, 655–663. doi: 10.1007/s11099-016-0679-7

Drew, M. C., He, C.-J., and Morgan, P. W. (2000). Programmed cell death and aerenchyma formation in roots. Trends Plant Sci. 5, 123–127. doi: 10.1016/s1360-1385(00)01570-3

Evans, D. E. (2004). Aerenchyma formation. New Phytol. 161, 35–49. doi: 10.1046/j.1469-8137.2003.00907.x

Eysholdt−Derzsó, E., and Sauter, M. (2019). Hypoxia and the group VII ethylene response transcription factor HRE2 promote adventitious root elongation in Arabidopsis . Plant Biol. 21, 103–108. doi: 10.1111/plb.12873

Farhangi-Abriz, S., and Ghassemi-Golezani, K. (2019). Jasmonates: mechanisms and functions in abiotic stress tolerance of plants. Biocatalys. Agricult. Biotechnol. 20:101210. doi: 10.1016/j.bcab.2019.101210

Fukao, T., and Bailey-Serres, J. (2008). Submergence tolerance conferred by Sub1A is mediated by SLR1 and SLRL1 restriction of gibberellin responses in rice. Proc. Natl. Acad. Sci. U.S.A. 105, 16814–16819. doi: 10.1073/pnas.0807821105

Fukao, T., Barrera-Figueroa, B. E., Juntawong, P., and Peña-Castro, J. M. (2019). Submergence and waterlogging stress in plants: a review highlighting research opportunities and understudied aspects. Front. Plant Sci. 10:340. doi: 10.3389/fpls.2019.00340

Fukao, T., Xu, K., Ronald, P. C., and Bailey-Serres, J. (2006). A variable cluster of ethylene response factor–like genes regulates metabolic and developmental acclimation responses to submergence in rice. Plant Cell 18, 2021–2034. doi: 10.1105/tpc.106.043000

Gasch, P., Fundinger, M., Müller, J. T., Lee, T., Bailey-Serres, J., and Mustroph, A. (2016). Redundant ERF-VII transcription factors bind to an evolutionarily conserved cis-motif to regulate hypoxia-responsive gene expression in Arabidopsis . Plant Cell 28, 160–180. doi: 10.1105/tpc.15.00866

Giuntoli, B., and Perata, P. (2018). Group VII ethylene response factors in Arabidopsis : regulation and physiological roles. Plant Physiol. 176, 1143–1155. doi: 10.1104/pp.17.01225

Gu, X., Xue, L., Lu, L., Xiao, J., Song, G., Xie, M., et al. (2020). Melatonin Enhances the waterlogging tolerance of prunus persica by modulating antioxidant metabolism and anaerobic respiration. J. Plant Growth Regulat. 1–13. doi: 10.9734/ijbcrr/2016/32087

Hartman, S., Liu, Z., Van Veen, H., Vicente, J., Reinen, E., Martopawiro, S., et al. (2019a). Ethylene-mediated nitric oxide depletion pre-adapts plants to hypoxia stress. Nat. Commun. 10, 1–9.

Hartman, S., Sasidharan, R., and Voesenek, L. A. (2019b). The role of ethylene in metabolic acclimations to low oxygen. New Phytol. 229, 64–70. doi: 10.1111/nph.16378

Hasanuzzaman, M., Bhuyan, M., Zulfiqar, F., Raza, A., Mohsin, S. M., Mahmud, J. A., et al. (2020). Reactive oxygen species and antioxidant defense in plants under abiotic stress: revisiting the crucial role of a universal defense regulator. Antioxidants 9:681. doi: 10.3390/antiox9080681

Hattori, Y., Nagai, K., Furukawa, S., Song, X.-J., Kawano, R., Sakakibara, H., et al. (2009). The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water. Nature 460, 1026–1030. doi: 10.1038/nature08258

Hayat, Q., Hayat, S., Irfan, M., and Ahmad, A. (2010). Effect of exogenous salicylic acid under changing environment: a review. Environ. Exp. Bot. 68, 14–25. doi: 10.1016/j.envexpbot.2009.08.005

He, F., Wang, H.-L., Li, H.-G., Su, Y., Li, S., Yang, Y., et al. (2018). PeCHYR 1, a ubiquitin E3 ligase from Populus euphratica, enhances drought tolerance via ABA−induced stomatal closure by ROS production in Populus. Plant Biotechnol. J. 16, 1514–1528. doi: 10.1111/pbi.12893

Herzog, M., Striker, G. G., Colmer, T. D., and Pedersen, O. (2016). Mechanisms of waterlogging tolerance in wheat–a review of root and shoot physiology. Plant Cell Environ. 39, 1068–1086. doi: 10.1111/pce.12676

Hess, N., Klode, M., Anders, M., and Sauter, M. (2011). The hypoxia responsive transcription factor genes ERF71/HRE2 and ERF73/HRE1 of Arabidopsis are differentially regulated by ethylene. Physiol. Plant. 143, 41–49. doi: 10.1111/j.1399-3054.2011.01486.x

Hirabayashi, Y., Mahendran, R., Koirala, S., Konoshima, L., Yamazaki, D., Watanabe, S., et al. (2013). Global flood risk under climate change. Nat. Clim. Change 3, 816–821. doi: 10.1038/nclimate1911

Hossain, M. A., Bhattacharjee, S., Armin, S.-M., Qian, P., Xin, W., Li, H.-Y., et al. (2015). Hydrogen peroxide priming modulates abiotic oxidative stress tolerance: insights from ROS detoxification and scavenging. Front. Plant Sci. 6:420. doi: 10.3389/fpls.2015.00420

Huang, H., Liu, D., Li, L., Wu, J., Wang, S., and Li, X. (2018). Effects of spraying plant growth regulators on peanut growth and yield & quality under waterlogging stress. J. Hum. Agric. Univ. 44, 129. (in Chinese), Google Scholar

Huang, L., Zhang, L., Zeng, R., Wang, X., Zhang, H., Wang, L., et al. (2020). Brassinosteroid priming improves peanut drought tolerance via eliminating inhibition on genes in photosynthesis and hormone signaling. Genes 11, 919. doi: 10.3390/genes11080919

Hudgins, J., and Franceschi, V. R. (2004). Methyl jasmonate-induced ethylene production is responsible for conifer phloem defense responses and reprogramming of stem cambial zone for traumatic resin duct formation. Plant Physiol. 135, 2134–2149. doi: 10.1104/pp.103.037929

Kamal, A. H. M., and Komatsu, S. (2016). Jasmonic acid induced protein response to biophoton emissions and flooding stress in soybean. J. Proteom. 133, 33–47. doi: 10.1016/j.jprot.2015.12.004

Kang, Y.-Y., Guo, S.-R., Li, J., and Duan, J.-J. (2009). Effect of root applied 24-epibrassinolide on carbohydrate status and fermentative enzyme activities in cucumber ( Cucumis sativus L.) seedlings under hypoxia. Plant Growth Regul. 57, 259–269. doi: 10.1007/s10725-008-9344-x

Kazan, K., and Manners, J. M. (2009). Linking development to defense: auxin in plant–pathogen interactions. Trends Plant Sci. 14, 373–382. doi: 10.1016/j.tplants.2009.04.005

Kim, Y., Seo, C.-W., Khan, A. L., Mun, B.-G., Shahzad, R., Ko, J.-W., et al. (2018). Exo-ethylene application mitigates waterlogging stress in soybean ( Glycine max L.). BMC Plant Biol. 18:254. doi: 10.1186/s12870-018-1457-4

Kim, Y.-H., Hwang, S.-J., Waqas, M., Khan, A. L., Lee, J.-H., Lee, J.-D., et al. (2015). Comparative analysis of endogenous hormones level in two soybean ( Glycine max L.) lines differing in waterlogging tolerance. Front. Plant Sci. 6:714. doi: 10.3389/fpls.2015.00714

Komatsu, S., Han, C., Nanjo, Y., Altaf-Un-Nahar, M., Wang, K., He, D., et al. (2013). Label-free quantitative proteomic analysis of abscisic acid effect in early-stage soybean under flooding. J. Proteome Res. 12, 4769–4784. doi: 10.1021/pr4001898

Komatsu, S., Thibaut, D., Hiraga, S., Kato, M., Chiba, M., Hashiguchi, A., et al. (2011). Characterization of a novel flooding stress-responsive alcohol dehydrogenase expressed in soybean roots. Plant Mol. Biol. 77, 309–322. doi: 10.1007/s11103-011-9812-y

Kreuzwieser, J., and Rennenberg, H. (2014). Molecular and physiological responses of trees to waterlogging stress. Plant Cell Environ. 37, 2245– 2259.

Kuai, J., Liu, Z., Wang, Y., Meng, Y., Chen, B., Zhao, W., et al. (2014). Waterlogging during flowering and boll forming stages affects sucrose metabolism in the leaves subtending the cotton boll and its relationship with boll weight. Plant Sci. 223, 79–98. doi: 10.1016/j.plantsci.2014.03.010

Kuroha, T., Nagai, K., Gamuyao, R., Wang, D. R., Furuta, T., Nakamori, M., et al. (2018). Ethylene-gibberellin signaling underlies adaptation of rice to periodic flooding. Science 361, 181–186. doi: 10.1126/science.aat1577

Kurokawa, Y., Nagai, K., Huan, P. D., Shimazaki, K., Qu, H., Mori, Y., et al. (2018). Rice leaf hydrophobicity and gas films are conferred by a wax synthesis gene (LGF 1) and contribute to flood tolerance. New Phytol. 218, 1558–1569. doi: 10.1111/nph.15070

Lee, Y.-H., Kim, K.-S., Jang, Y.-S., Hwang, J.-H., Lee, D.-H., and Choi, I.-H. (2014). Global gene expression responses to waterlogging in leaves of rape seedlings. Plant Cell Rep. 33, 289–299. doi: 10.1007/s00299-013-1529-8

Lemay, M.-L., and Moineau, S. (2020). “How are genes modified? Crossbreeding, mutagenesis, and CRISPR-Cas9,” in Genetically Modified and Irradiated Food , ed. V. Andersen (Cambridge, MA: Academic Press), 39–54. doi: 10.1016/b978-0-12-817240-7.00003-6

Li, C.-X., Wei, H., Geng, Y.-H., and Schneider, R. (2010). Effects of submergence on photosynthesis and growth of Pterocarya stenoptera (Chinese wingnut) seedlings in the recently-created Three Gorges Reservoir region of China. Wetl. Ecol. Manag. 18, 485–494. doi: 10.1007/s11273-010-9181-3

Li, T. (2007). Preliminary Studies of Waterlogging in Physiology of Cucumber at the Seedling Stage. Doctoral Dissertation, University of Yangzhou, China.

Li, W., Mo, W., Ashraf, U., Li, G., Wen, T., Abrar, M., et al. (2018). Evaluation of physiological indices of waterlogging tolerance of different maize varieties in South China. Appl. Ecol. Environ. Res. 16, 2059–2072. doi: 10.15666/aeer/1602_20592072

Limami, A. M., Diab, H., and Lothier, J. (2014). Nitrogen metabolism in plants under low oxygen stress. Planta 239, 531–541. doi: 10.1007/s00425-013-2015-9

Lin, C., and Sauter, M. (2019). Polar auxin transport determines adventitious root emergence and growth in rice. Front. Plant Sci. 10:444. doi: 10.3389/fpls.2019.00444

Lin, K.-H. R., Weng, C.-C., Lo, H.-F., and Chen, J.-T. (2004). Study of the root antioxidative system of tomatoes and eggplants under waterlogged conditions. Plant Sci. 167, 355–365. doi: 10.1016/j.plantsci.2004.04.004

Liu, B., Sun, L., Ma, L., and Hao, F.-S. (2017). Both AtrbohD and AtrbohF are essential for mediating responses to oxygen deficiency in Arabidopsis . Plant Cell Rep. 36, 947–957. doi: 10.1007/s00299-017-2128-x

Liu, P., Sun, F., Gao, R., and Dong, H. (2012). RAP2. 6L overexpression delays waterlogging induced premature senescence by increasing stomatal closure more than antioxidant enzyme activity. Plant Mol. Biol. 79, 609–622. doi: 10.1007/s11103-012-9936-8

Loreti, E., van Veen, H., and Perata, P. (2016). Plant responses to flooding stress. Curr. Opin. Plant Biol. 33, 64–71. doi: 10.1016/j.pbi.2016.06.005

Luan, H., Guo, B., Shen, H., Pan, Y., Hong, Y., Lv, C., et al. (2020). Overexpression of Barley Transcription Factor HvERF2. 11 in Arabidopsis enhances plant waterlogging tolerance. Int. J. Mol. Sci. 21, 1982. doi: 10.3390/ijms21061982

Luan, H., Shen, H., Pan, Y., Guo, B., Lv, C., and Xu, R. (2018). Elucidating the hypoxic stress response in barley ( Hordeum vulgare L.) during waterlogging: a proteomics approach. Sci. Rep. 8, 1–13.

Lv, B., Yan, Z., Tian, H., Zhang, X., and Ding, Z. (2019). Local auxin biosynthesis mediates plant growth and development. Trends Plant Sci. 24, 6–9. doi: 10.1016/j.tplants.2018.10.014

Ma, Y., and Guo, S. (2014). 24-epibrassinolide improves cucumber photosynthesis under hypoxia by increasing CO 2 assimilation and photosystem II efficiency. Photosynthetica 52, 96–104. doi: 10.1007/s11099-014-0010-4

McDonald, M., and Visser, E. (2003). A study of the interaction between auxin and ethylene in wild type and transgenic ethylene-insensitive tobacco during adventitious root formation induced by stagnant root zone conditions. Plant Biol. 5, 550–556. doi: 10.1055/s-2003-44790

Mignolli, F., Todaro, J. S., and Vidoz, M. L. (2020). Internal aeration and respiration of submerged tomato hypocotyls are enhanced by ethylene-mediated aerenchyma formation and hypertrophy. Physiol. Plant. 169, 49–63. doi: 10.1111/ppl.13044

Miransari, M., and Smith, D. (2014). Plant hormones and seed germination. Environ. Exp. Bot. 99, 110–121. doi: 10.1016/j.envexpbot.2013.11.005

Mondal, S., Khan, M. I. R., Dixit, S., Cruz, P. C. S., Septiningsih, E. M., and Ismail, A. M. (2020). Growth, productivity and grain quality of AG1 and AG2 QTLs introgression lines under flooding in direct-seeded rice system. Field Crops Res. 248, 107713. doi: 10.1016/j.fcr.2019.107713

Moustafa-Farag, M., Mahmoud, A., Arnao, M. B., Sheteiwy, M. S., Dafea, M., Soltan, M., et al. (2020). Melatonin-induced water stress tolerance in plants: recent advances. Antioxidants 9, 809. doi: 10.3390/antiox9090809

Nan, R., Carman, J. G., and Salisbury, F. B. (2002). Water stress, CO2 and photoperiod influence hormone levels in wheat. J. Plant Physiol. 159, 307–312. doi: 10.1078/0176-1617-00703

Nazir, F., Fariduddin, Q., Hussain, A., and Khan, T. A. (2021). Brassinosteroid and hydrogen peroxide improve photosynthetic machinery, stomatal movement, root morphology and cell viability and reduce Cu-triggered oxidative burst in tomato. Ecotoxicol. Environ. Saf. 207, 111081. doi: 10.1016/j.ecoenv.2020.111081

Nelissen, H., Rymen, B., Jikumaru, Y., Demuynck, K., Van Lijsebettens, M., Kamiya, Y., et al. (2012). A local maximum in gibberellin levels regulates maize leaf growth by spatial control of cell division. Curr. Biol. 22, 1183–1187. doi: 10.1016/j.cub.2012.04.065

Nishiuchi, S., Yamauchi, T., Takahashi, H., Kotula, L., and Nakazono, M. (2012). Mechanisms for coping with submergence and waterlogging in rice. Rice 5, 2. doi: 10.1186/1939-8433-5-2

Pan, D.-L., Wang, G., Wang, T., Jia, Z.-H., Guo, Z.-R., and Zhang, J.-Y. (2019). AdRAP2. 3, a novel ethylene response factor VII from Actinidia deliciosa , enhances waterlogging resistance in transgenic tobacco through improving expression levels of PDC and ADH Genes. Int. J. Mol. Sci. 20, 1189. doi: 10.3390/ijms20051189

Pedersen, O., Rich, S. M., and Colmer, T. D. (2009). Surviving floods: leaf gas films improve O2 and CO2 exchange, root aeration, and growth of completely submerged rice. Plant J. 58, 147–156. doi: 10.1111/j.1365-313x.2008.03769.x

Pedersen, O., Sauter, M., Colmer, T. D., and Nakazono, M. (2020). Regulation of root adaptive anatomical and morphological traits during low soil oxygen. New Phytol. 229, 42–49. doi: 10.1111/nph.16375

Per, T. S., Khan, M. I. R., Anjum, N. A., Masood, A., Hussain, S. J., and Khan, N. A. (2018). Jasmonates in plants under abiotic stresses: crosstalk with other phytohormones matters. Environ. Exp. Bot. 145, 104–120. doi: 10.1016/j.envexpbot.2017.11.004

Pucciariello, C., Parlanti, S., Banti, V., Novi, G., and Perata, P. (2012). Reactive oxygen species-driven transcription in Arabidopsis under oxygen deprivation. Plant Physiol. 159, 184–196. doi: 10.1104/pp.111.191122

Qi, X., Li, Q., Ma, X., Qian, C., Wang, H., Ren, N., et al. (2019). Waterlogging-induced adventitious root formation in cucumber is regulated by ethylene and auxin through reactive oxygen species signalling. Plant Cell Environ. 42, 1458–1470. doi: 10.1111/pce.13504

Qi, X., Li, Q., Shen, J., Qian, C., Xu, X., Xu, Q., et al. (2020). Sugar enhances waterlogging−induced adventitious root formation in cucumber by promoting auxin transport and signalling. Plant Cell Environ. 43, 1545–1557. doi: 10.1111/pce.13738

Rauf, M., Arif, M., Fisahn, J., Xue, G.-P., Balazadeh, S., and Mueller-Roeber, B. (2013). NAC transcription factor speedy hyponastic growth regulates flooding-induced leaf movement in Arabidopsis . Plant Cell 25, 4941–4955. doi: 10.1105/tpc.113.117861

Raza, A., Charagh, S., Zahid, Z., Mubarik, M. S., Javed, R., Siddiqui, M. H., et al. (2020). Jasmonic acid: a key frontier in conferring abiotic stress tolerance in plants. Plant Cell Rep. [Epub ahead of print].

Saha, I., Hasanuzzaman, M., Dolui, D., Sikdar, D., Debnath, S. C., and Adak, M. K. (2021). Silver-nanoparticle and abscisic acid modulate sub1A quantitative trait loci functioning towards submergence tolerance in rice ( Oryza sativa L.). Environ. Exp. Bot. 181, 1042276.

Saika, H., Okamoto, M., Miyoshi, K., Kushiro, T., Shinoda, S., Jikumaru, Y., et al. (2007). Ethylene promotes submergence-induced expression of OsABA8ox1, a gene that encodes ABA 8’-hydroxylase in rice. Plant Cell Physiol. 48, 287–298. doi: 10.1093/pcp/pcm003

Salah, A., Zhan, M., Cao, C., Han, Y., Ling, L., Liu, Z., et al. (2019). γ-Aminobutyric acid promotes chloroplast ultrastructure, antioxidant capacity, and growth of waterlogged maize seedlings. Sci. Rep. 9, 1–19.

Sasidharan, R., and Voesenek, L. A. (2015). Ethylene-mediated acclimations to flooding stress. Plant Physiol. 169, 3–12. doi: 10.1104/pp.15.00387

Schmitz, A. J., Folsom, J. J., Jikamaru, Y., Ronald, P., and Walia, H. (2013). SUB 1 A−mediated submergence tolerance response in rice involves differential regulation of the brassinosteroid pathway. New Phytol. 198, 1060–1070. doi: 10.1111/nph.12202

Sharif, R., Xie, C., Zhang, H., Arnao, M. B., Ali, M., Ali, Q., et al. (2018). Melatonin and its effects on plant systems. Molecules 23, 2352. doi: 10.3390/molecules23092352

Sharma, P., Jha, A. B., Dubey, R. S., and Pessarakli, M. (2012). Reactive oxygen species, oxidative damage, and antioxidative defense mechanism in plants under stressful conditions. J. Bot. 2012, 217037.

Shimamura, S., Nishimura, T., Koshiba, T., Yamamoto, R., Hiraga, S., Nakamura, T., et al. (2016). Effects of anti-auxins on secondary aerenchyma formation in flooded soybean hypocotyls. Plant Prod. Sci. 19, 154–160. doi: 10.1080/1343943x.2015.1128101

Shimamura, S., Yoshioka, T., Yamamoto, R., Hiraga, S., Nakamura, T., Shimada, S., et al. (2014). Role of abscisic acid in flood-induced secondary aerenchyma formation in soybean ( Glycine max ) hypocotyls. Plant Prod. Sci. 17, 131–137. doi: 10.1626/pps.17.131

Shiono, K., Ogawa, S., Yamazaki, S., Isoda, H., Fujimura, T., Nakazono, M., et al. (2011). Contrasting dynamics of radial O2-loss barrier induction and aerenchyma formation in rice roots of two lengths. Ann. Bot. 107, 89–99. doi: 10.1093/aob/mcq221

Steffens, B., and Rasmussen, A. (2016). The physiology of adventitious roots. Plant Physiol. 170, 603–617. doi: 10.1104/pp.15.01360

Steffens, B., Geske, T., and Sauter, M. (2011). Aerenchyma formation in the rice stem and its promotion by H2O2. New Phytol. 190, 369–378. doi: 10.1111/j.1469-8137.2010.03496.x

Sun, L., Ma, L., He, S., and Hao, F. (2018). AtrbohD functions downstream of ROP2 and positively regulates waterlogging response in Arabidopsis . Plant Signal. Behav. 13, e1513300. doi: 10.1080/15592324.2018.1513300

Tamang, B. G., Magliozzi, J. O., Maroof, M. S., and Fukao, T. (2014). Physiological and transcriptomic characterization of submergence and reoxygenation responses in soybean seedlings. Plant Cell Environ. 37, 2350– 2365.

Tian, L., Li, J., Bi, W., Zuo, S., Li, L., Li, W., et al. (2019). Effects of waterlogging stress at different growth stages on the photosynthetic characteristics and grain yield of spring maize ( Zea mays L.) Under field conditions. Agric. Water Manag. 218, 250–258. doi: 10.1016/j.agwat.2019.03.054

Tougou, M., Hashiguchi, A., Yukawa, K., Nanjo, Y., Hiraga, S., Nakamura, T., et al. (2012). Responses to flooding stress in soybean seedlings with the alcohol dehydrogenase transgene. Plant Biotechnol. 29, 301–305. doi: 10.5511/plantbiotechnology.12.0301a

van Veen, H., Akman, M., Jamar, D. C., Vreugdenhil, D., Kooiker, M., van Tienderen, P., et al. (2014). Group VII E thylene response factor diversification and regulation in four species from flood-prone environments. Plant Cell Environ. 37, 2421–2432.

Vidoz, M. L., Loreti, E., Mensuali, A., Alpi, A., and Perata, P. (2010). Hormonal interplay during adventitious root formation in flooded tomato plants. Plant J. 63, 551–562. doi: 10.1111/j.1365-313x.2010.04262.x

Visser, E. J., and Voesenek, L. A. (2005). Acclimation to soil flooding—sensing and signal-transduction, in Root physiology: from gene to function. Plant Soil 274, 197–214. doi: 10.1007/1-4020-4099-7_10

Voesenek, L., Colmer, T., Pierik, R., Millenaar, F., and Peeters, A. (2006). How plants cope with complete submergence. New Phytol. 170, 213–226. doi: 10.1111/j.1469-8137.2006.01692.x

Wang, C., Zhu, J., and Dai, S. (2016). Effects of chemical control and nutrient control on waterlogging of rapeseed in flower and fruit stage. Jiangsu Agric. Sci. 44, 136–138.

Wang, G., Fan, W., and Peng, F. (2015). Physiological responses of the young peach tree to water-logging and spraying SA at different timing. J. Fruit Sci. 32, 872–878.

Wang, J., Song, L., Gong, X., Xu, J., and Li, M. (2020). Functions of jasmonic acid in plant regulation and response to abiotic stress. Int. J. Mol. Sci. 21, 1446. doi: 10.3390/ijms21041446

Wang, X., Li, M., Jannasch, A. H., and Jiang, Y. (2020). Submergence stress alters fructan and hormone metabolism and gene expression in perennial ryegrass with contrasting growth habits. Environ. Exp. Bot. 179, 104202. doi: 10.1016/j.envexpbot.2020.104202

Wei, X., Xu, H., Rong, W., Ye, X., and Zhang, Z. (2019). Constitutive expression of a stabilized transcription factor group VII ethylene response factor enhances waterlogging tolerance in wheat without penalizing grain yield. Plant Cell Environ. 42, 1471–1485. doi: 10.1111/pce.13505

Winkel, A., Visser, E. J., Colmer, T. D., Brodersen, K. P., Voesenek, L. A., Sand−Jensen, K., et al. (2016). Leaf gas films, underwater photosynthesis and plant species distributions in a flood gradient. Plant Cell Environ. 39, 1537–1548. doi: 10.1111/pce.12717

Wu, H., Chen, H., Zhang, Y., Zhang, Y., Zhu, D., and Xiang, J. (2019). Effects of 1-aminocyclopropane-1-carboxylate and paclobutrazol on the endogenous hormones of two contrasting rice varieties under submergence stress. Plant Growth Regul. 87, 109–121. doi: 10.1007/s10725-018-0457-6

Wu, Y.-S., and Yang, C.-Y. (2016). Physiological responses and expression profile of NADPH oxidase in Rice ( Oryza sativa ) seedlings under different levels of submergence. Rice 9:2.

Xu, K., Xu, X., Fukao, T., Canlas, P., Maghirang-Rodriguez, R., Heuer, S., et al. (2006). Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature 442, 705–708. doi: 10.1038/nature04920

Xu, X., Ji, J., Ma, X., Xu, Q., Qi, X., and Chen, X. (2016). Comparative proteomic analysis provides insight into the key proteins involved in cucumber ( Cucumis sativus L.) adventitious root emergence under waterlogging stress. Front. Plant Sci. 7:1515. doi: 10.3389/fpls.2016.01515

Xu, X., Ji, J., Xu, Q., Qi, X., Weng, Y., and Chen, X. (2018). The major-effect quantitative trait locus Cs ARN 6.1 encodes an AAA ATP ase domain-containing protein that is associated with waterlogging stress tolerance by promoting adventitious root formation. Plant J. 93, 917–930. doi: 10.1111/tpj.13819

Xu, X., Wang, H., Qi, X., Xu, Q., and Chen, X. (2014). Waterlogging-induced increase in fermentation and related gene expression in the root of cucumber ( Cucumis sativus L.). Sci. Hortic. 179, 388–395. doi: 10.1016/j.scienta.2014.10.001

Yamauchi, T., Colmer, T. D., Pedersen, O., and Nakazono, M. (2018). Regulation of root traits for internal aeration and tolerance to soil waterlogging-flooding stress. Plant Physiol. 176, 1118–1130. doi: 10.1104/pp.17.01157

Yamauchi, T., Shimamura, S., Nakazono, M., and Mochizuki, T. (2013). Aerenchyma formation in crop species: a review. Field Crops Res. 152, 8–16. doi: 10.1016/j.fcr.2012.12.008

Yamauchi, T., Tanaka, A., Mori, H., Takamure, I., Kato, K., and Nakazono, M. (2016). Ethylene−dependent aerenchyma formation in adventitious roots is regulated differently in rice and maize. Plant Cell Environ. 39, 2145–2157. doi: 10.1111/pce.12766

Yamauchi, T., Tanaka, A., Tsutsumi, N., Inukai, Y., and Nakazono, M. (2020). A role for auxin in ethylene-dependent inducible aerenchyma formation in rice roots. Plants 9:610. doi: 10.3390/plants9050610

Yamauchi, T., Watanabe, K., Fukazawa, A., Mori, H., Abe, F., Kawaguchi, K., et al. (2014). Ethylene and reactive oxygen species are involved in root aerenchyma formation and adaptation of wheat seedlings to oxygen-deficient conditions. J. Exp. Bot. 65, 261–273. doi: 10.1093/jxb/ert371

Yamauchi, T., Yoshioka, M., Fukazawa, A., Mori, H., Nishizawa, N. K., Tsutsumi, N., et al. (2017). An NADPH oxidase RBOH functions in rice roots during lysigenous aerenchyma formation under oxygen-deficient conditions. Plant Cell 29, 775–790. doi: 10.1105/tpc.16.00976

Yan, K., Zhao, S., Cui, M., Han, G., and Wen, P. (2018). Vulnerability of photosynthesis and photosystem I in Jerusalem artichoke ( Helianthus tuberosus L.) exposed to waterlogging. Plant Physiol. Biochem. 125, 239–246. doi: 10.1016/j.plaphy.2018.02.017

Yang, C.-Y. (2014). Hydrogen peroxide controls transcriptional responses of ERF73/HRE1 and ADH1 via modulation of ethylene signaling during hypoxic stress. Planta 239, 877–885. doi: 10.1007/s00425-013-2020-z

Yang, C.-Y., and Hong, C.-P. (2015). The NADPH oxidase Rboh D is involved in primary hypoxia signalling and modulates expression of hypoxia-inducible genes under hypoxic stress. Environ. Exp. Bot. 115, 63–72. doi: 10.1016/j.envexpbot.2015.02.008

Yang, S.-H., and Choi, D. (2006). Characterization of genes encoding ABA 8’-hydroxylase in ethylene-induced stem growth of deepwater rice ( Oryza sativa L.). Biochem. Biophys. Res. Commun. 350, 685–690. doi: 10.1016/j.bbrc.2006.09.098

Yin, D., Sun, D., Han, Z., Ni, D., Norris, A., and Jiang, C.-Z. (2019). PhERF2, an ethylene-responsive element binding factor, plays an essential role in waterlogging tolerance of Petunia . Hortic. Res. 6, 1–11.

Yu, F., Liang, K., Fang, T., Zhao, H., Han, X., Cai, M., et al. (2019). A group VII ethylene response factor gene, ZmEREB180, coordinates waterlogging tolerance in maize seedlings. Plant Biotechnol. J. 17, 2286–2298. doi: 10.1111/pbi.13140

Zabalza, A., Van Dongen, J. T., Froehlich, A., Oliver, S. N., Faix, B., Gupta, K. J., et al. (2009). Regulation of respiration and fermentation to control the plant internal oxygen concentration. Plant Physiol. 149, 1087–1098. doi: 10.1104/pp.108.129288

Zhang, G., Tanakamaru, K., Abe, J., and Morita, S. (2007). Influence of waterlogging on some anti-oxidative enzymatic activities of two barley genotypes differing in anoxia tolerance. Acta Physiol. Plant. 29, 171–176. doi: 10.1007/s11738-006-0022-1

Zhang, J.-Y., Huang, S.-N., Wang, G., Xuan, J.-P., and Guo, Z.-R. (2016). Overexpression of Actinidia deliciosa pyruvate decarboxylase 1 gene enhances waterlogging stress in transgenic Arabidopsis thaliana. Plant Physiol. Biochem. 106, 244–252. doi: 10.1016/j.plaphy.2016.05.009

Zhang, P., Lyu, D., Jia, L., He, J., and Qin, S. (2017). Physiological and de novo transcriptome analysis of the fermentation mechanism of Cerasus sachalinensis roots in response to short-term waterlogging. BMC Genomics 18:649. doi: 10.1186/s12864-017-4055-1

Zhang, Q., Liu, X., Zhang, Z., Liu, N., Li, D., and Hu, L. (2019). Melatonin improved waterlogging tolerance in alfalfa ( Medicago sativa ) by reprogramming polyamine and ethylene metabolism. Front. Plant Sci. 10:44. doi: 10.3389/fpls.2019.00044

Zhang, R., Zhou, Y., Yue, Z., Chen, X., Cao, X., Xu, X., et al. (2019). Changes in photosynthesis, chloroplast ultrastructure, and antioxidant metabolism in leaves of sorghum under waterlogging stress. Photosynthetica 57, 1076–1083. doi: 10.32615/ps.2019.124

Zhang, Y., Chen, Y., Lu, H., Kong, X., Dai, J., Li, Z., et al. (2016). Growth, lint yield and changes in physiological attributes of cotton under temporal waterlogging. Field Crops Res. 194, 83–93. doi: 10.1016/j.fcr.2016.05.006

Zhang, Y., Song, X., Yang, G., Li, Z., Lu, H., Kong, X., et al. (2015). Physiological and molecular adjustment of cotton to waterlogging at peak-flowering in relation to growth and yield. Field Crops Res. 179, 164–172. doi: 10.1016/j.fcr.2015.05.001

Zheng, X., Zhou, J., Tan, D.-X., Wang, N., Wang, L., Shan, D., et al. (2017). Melatonin improves waterlogging tolerance of Malus baccata (Linn.) Borkh. seedlings by maintaining aerobic respiration, photosynthesis and ROS migration. Front. Plant Sci. 8:483. doi: 10.3389/fpls.2017.00483

Zhou, W., Chen, F., Meng, Y., Chandrasekaran, U., Luo, X., Yang, W., et al. (2020). Plant waterlogging/flooding stress responses: from seed germination to maturation. Plant Physiol. Biochem. 148, 228–236. doi: 10.1016/j.plaphy.2020.01.020

Zhou, Z. S., Guo, K., Elbaz, A. A., and Yang, Z. M. (2009). Salicylic acid alleviates mercury toxicity by preventing oxidative stress in roots of Medicago sativa . Environ. Exp. Bot. 65, 27–34. doi: 10.1016/j.envexpbot.2008.06.001

Zhu, J.-K. (2016). Abiotic stress signaling and responses in plants. Cell 167, 313–324. doi: 10.1016/j.cell.2016.08.029

Keywords : waterlogging stress, morphological structure, photosynthesis, energy metabolism, plant hormones, molecular mechanism

Citation: Pan J, Sharif R, Xu X and Chen X (2021) Mechanisms of Waterlogging Tolerance in Plants: Research Progress and Prospects. Front. Plant Sci. 11:627331. doi: 10.3389/fpls.2020.627331

Received: 09 November 2020; Accepted: 30 December 2020; Published: 10 February 2021.

Reviewed by:

Copyright © 2021 Pan, Sharif, Xu and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xuehao Chen, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

We apologize for the inconvenience...

To ensure we keep this website safe, please can you confirm you are a human by ticking the box below.

If you are unable to complete the above request please contact us using the below link, providing a screenshot of your experience.

https://ioppublishing.org/contacts/

Advertisement

Dhaka city water logging hazards: area identification and vulnerability assessment through GIS-remote sensing techniques

• Open access
• Published: 05 April 2023
• Volume 195 , article number  543 , ( 2023 )

Cite this article

You have full access to this open access article

• Rafiul Alam   ORCID: orcid.org/0000-0001-5170-5842 1 ,
• Zahidul Quayyum   ORCID: orcid.org/0000-0002-2276-4576 1 ,
• Simon Moulds   ORCID: orcid.org/0000-0002-7297-482X 2 ,
• Marzuka Ahmad Radia   ORCID: orcid.org/0000-0001-5956-5426 1 ,
• Hasna Hena Sara   ORCID: orcid.org/0000-0002-2739-5423 1 ,
• Md Tanvir Hasan   ORCID: orcid.org/0000-0002-5806-060X 1 &
• Adrian Butler   ORCID: orcid.org/0000-0001-9125-6105 2  

8846 Accesses

5 Citations

4 Altmetric

Explore all metrics

Water logging is one of the most detrimental phenomena continuing to burden Dhaka dwellers. This study aims to spatio-temporarily identify the water logging hazard zones within Dhaka Metropolitan area and assess the extent of their water logging susceptibility based on informal settlements, built-up areas, and demographical characteristics. The study utilizes integrated geographic information system (GIS)-remote sensing (RS) methods, using the Normalized Difference Vegetation Water and Moisture Index, distance buffer zone from drainage streams, and built-up distributions to identify waterlogged zones with a temporal extent, incorporating social and infrastructural attributes to evaluate water logging effects. These indicators were integrated into an overlay GIS method to measure the vulnerability level across Dhaka city areas. The findings reveal that south and south-western parts of Dhaka were more susceptible to water logging hazards. Almost 35% of Dhaka belongs to the high/very highly vulnerable zone. Greater number of slum households were found within high to very high water logging vulnerable zones and approximately 70% of them are poorly structured. The built-up areas were observed to be increased toward the northern part of Dhaka and were exposed to severe water logging issues. The overall findings reveal the spatio-temporal distribution of the water logging vulnerabilities across the city as well as its impact on the social indicators. An integrated approach is necessary for future development plans to mitigate the risk of water logging.

Similar content being viewed by others

Integrating GIS and Remote Sensing for Suitability Assessment of Dams in Solai Nakuru: Kenya

Application of Remote Sensing and GIS for Risk Assessment in Monastir, Tunisia

Ecological Risk Assessment of World Heritage Sites Using RS and GIS: A Case Study of Huangshan Mountain, China

Shiman Huang, Qingwu Hu, … Haidong Li

Avoid common mistakes on your manuscript.

Introduction

Bangladesh is undergoing environmental degradation due to rapid urbanization, increasing population growth, and rapid industrialization (Tawhid,  2004a , b ). Rapid urbanization is linked with economic development, which has an increasingly higher contribution to the national economy, with almost 36% of the gross domestic product (GDP) coming from the urban economy (Hussain, 2013 ). However, when the growth of the urban population takes place at an exceptionally rapid rate, people and governments face difficulties in keeping pace with the changing situations due to resource constraints and the inability to manage and respond quickly (Bari & Hasan, 2001 ). The country has also been exposed to several types of climate-induced hazards including variations in temperature, excessive and erratic rainfall, water logging, and flooding which adversely affect urban life and livelihoods (Rabbani et al., 2011 ). The situation gets worse when climatic phenomena become tied with non-climatic factors including population density, poverty, rural–urban migration, illiteracy, unplanned urbanization, poor management of natural resources, and lack of public utilities and services (Adri, 2013 ).

Dhaka, the capital of Bangladesh, has been ranked top in terms of urban population density (Demographia World Urban Areas,  2020 ). Due to the speedy industrialization and urbanization process, the city is among the top 5 fastest growing megacities in the world (United Nations, 2018 ) and at the same time a development hub for Bangladesh. However, this development is also bringing in several adverse impacts such as deterioration of environmental quality, increased air and water pollution, and congestion. Dhaka city is also experiencing several socio-economic problems such as rising inequality, poverty, inadequate social security, and corruption among others. Water logging, traffic congestion, improper solid waste disposal, black smoke emission from vehicles and industry, air and noise pollution, and water pollution from industrial discharge are also very common problems of the city (Tawhid,  2004a , b ). In recent times, water logging has become one of the main causes for apprehension damaging infrastructures, disrupting daily lives, and demolishing vegetation and aquatic habitats. Several initiatives undertaken by WASA (Water and Sewerage Authority) and the two City Corporations to improve the existing condition have failed due to the absence of proper urban design and planning, landscape architecture, and most importantly lack of coordination between project activities and stakeholders (Subrina & Chowdhury,  2018 ).

Urban water logging disaster refers to the phenomenon when a rainstorm or short-time heavy rain surpasses the capacity of the urban drainage system (Xue et al., 2016 ), a very common situation during rainy season in Dhaka. Water logging in Dhaka has become an increasingly predominant burden for the city dwellers and is creating adverse social, physical, economic, and environmental consequences by disrupting regular life, causing traffic paralysis and infrastructural damage, and destruction of flora and fauna (Subrina & Chowdhury,  2018 ). Urban infrastructures including low-lying houses, schools, colleges, shops, and business premises are greatly affected by the water logging problem. People of low-income groups, particularly grocery shop owners, vegetable vendors, and day laborers, are the main sufferers (Majumder et al., 2018 ). In addition to the water logging problem, previous studies have shown that almost every year about 60% of Dhaka city becomes submerged due to flooding by the Balu River in the east and the Tongi Khal in the north (Gain et al., 2015 ). While actions have been taken to ease the growing problem of fluvial flooding and water logging (Papry & Ahmed, 2015 ), these have largely been inadequate. Substantial increase in the impervious area and improper solid waste management obstruct the natural drainage pattern leading to a shortening of the runoff concentration time and an increase of the peak flow (Mowla & Islam, 2013 ). Most drains in Dhaka city are clogged by solid waste and plastic waste, due to irregular cleanup, improper management, and poor littering and fly-tipping by city dwellers (Anik, 2019 ). Excessive rainfall, disappearance of the natural drainage system, and lower capacity of the drainage system are considered the main reasons behind this.

The highest rainfall in Dhaka was in 2017 which was 2892 mm and the lowest was 1329 mm in the year 2012 (Chakraborty,  2019 ). Besides, the average rainfall in winter is around 35.3 mm compared to 1353.6 mm in monsoon and the annual average rainfall is 2059.9 mm (Mahbub et al., 2021 ). Furthermore, unplanned city development, uncontrolled silt load arising from the construction works, and major road works involving huge digging during the rainy season further worsen the situation (Tawhid, 2004a , b ). According to the Bangladesh Institute of Planners (BIP), from 2011 to 2019, minimum 3483 acres of water bodies and lowlands across the metropolitan area in Dhaka have been loaded up (Nabi, 2019 ). However, the city lacks adequate retention and detention capacity of rainwater and sustainable development of the drainage system during urban planning and design (Mowla & Islam, 2013 ). Several studies have addressed water logging hazards and risks of south-west and south-east coastal zones, at different river basins of Bangladesh adapting mix-method approach and GIS-remote sensing techniques (Hassan & Mahmud-ul-islam,  2014 ; Rahman et al., 2009 ; Tareq et al., 2018 ; Islam et al., 2020 ; Huda et al.,  2022 ). However, to the best of our knowledge, no studies have evaluated water logging hazards through the lens of GIS and remote sensing integrated approach and have not emphasized the contribution of rapid urbanization. This study has incorporated several techniques to identify water logging hazards using historical data with GIS and remote sensing techniques coupled with rapid urbanization to identify the water logging hazard zone.

This study attempts to delineate the surface waterlogged area by analyzing spatio-temporal data of 1990, 2010, and 2019 through establishing a GIS-remote sensing–based spatial model. After identifying the waterlogged hazard areas, the study also aims to assess the vulnerability in those identified water logging hazard zones based on the spatial distribution of built-up areas, slums, Footnote 1 dwelling housing types, and population density and rank them based on predetermined scales.

Materials and methods

This study was conducted in two steps. First, we utilized different spatial hazard attributes using multi-temporal Landsat and Sentinel satellite imagery. We combined images from 1990, 2010, and 2019 with topographical data including slope, elevation, and drainage network to detect the water logging hazard zones. Then, we merged the social attributes with spatial data of the hazard zones across Dhaka city to assess the exposure and vulnerability of Dhaka residents to water logging. Data collection and analysis workflow are elaborated in Fig.  1 .

Flow diagram of research and data integration method

Identifying the surface water logging hazard areas

We developed an overlay model to identify the surface water logging hazard zones. An overlay model is a GIS operation that superimposes multiple data points to identify relationships between them. For deploying this model, Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Moisture Index (NDMI) were analyzed for the years 1990, 2010, and 2019 for Dhaka city. Topographical data such as slope and elevation, and buffer drainage distance were determined by using MERIT Hydro digital elevation data which is a new global flow direction map at 3 arc-second resolution (~ 90 m at the equator) derived from the latest elevation data (MERIT DEM) and water body datasets (G1WBM, GSWO, and OpenStreetMap). The corresponding variables (NDVI, NDWI, NDMI, topographical variation and drainage density, and built-up areas) were initially assigned with equal weight. Then, an overlay was generated by adjusting the rank and weight for mapping the water logging hazard zones.

Normalized Difference Vegetation Index

Normalized Difference Vegetation Index (NDVI) Footnote 2 is a globally accepted remote sensing index widely used to detect the vegetation, forest extension, and the water bodies over the surface using red and near-infrared light (Jackson & Huete, 1991 ; Sahu, 2014 ; Tucker, 1979 ). An NDVI value always ranges from −1 to +1. A value of +1 indicates dense vegetation, while −1 implies the presence of extensive deep-water bodies, with 0 signifying the absence of any vegetation. For this study, we followed the methods for segregating vegetated areas from water-logged areas used by Dwivedi and Sreeniwas ( 2002 ) who measured NDVI value of 0.13 as a threshold using Landsat MSS and TM, and IRS-1A LISS-I data.

Normalized Difference Water Index

The Normalized Difference Water Index (NDWI) examines water content pixels analogous to the way NDVI measures vegetation (Geogr et al.,  2003 ; Gao, 1996 ). The values of the NDWI range from −1 to +1 (McFeeters, 1996 ). According to Chowdary et al. ( 2008 ), NDWI for waterlogged areas ranges from 0 to +1 where +1 indicates the existence of deep waterbodies with 0 for non-waterbodies. Multi-temporal satellite imageries were used to generate the NDWI by using the formula Footnote 3 used in the study by McFeeters ( 1996 ).

Normalized Difference Moisture Index

NDMI Footnote 4 is a modified version of NDWI which is theoretically a similar measure of the previous indices that refers to the spatial variation of surface moisture and wetness (Wilson & Sader, 2002 ). Higher values of NDMI indicate high soil moisture and low values denote low soil moisture content. According to Wilson and Sader ( 2002 ) and Goodwin et al. ( 2008 ), an NDMI of more than +0.20 indicates moist soil surface with the very good potentiality of groundwater and from +0.20 to +0.10 indicates wet to dry soil with moderate potentiality.

These three indices were analyzed in the GIS environment using raster calculator tools Footnote 5 (Sar et al., 2015 ). After downloading the satellite images, all the necessary corrections, band composition, and masking were accurately completed prior to analysis. Radiometric correction was applied including haze and noise reduction with histogram equalization using Erdas Imagine software. Reprojection tool was used to project all images into World Geodetic System (WGS) 1984. After that, all the essential seven bands of satellite images were composed into one single image using data management tool. Subsequently, the cells were extracted from the composed image corresponding to the study area using extract by mask tool in GIS environment.

Topographical variation in terms of elevation and slope

Topographical variation was considered a significant indicator for water logging analysis. Elevation and slope data of 2019 were derived from the MERIT DEM images as topographical variables. Higher altitudes are associated with a lower probability of water logging, while lower altitudes are more susceptible to water logging. A lower topographic slope allows the landscape to retain water and cause water logging, while a steep slope drains quicker.

Drainage buffer distance

The drainage buffer distance was used as a proxy to establish the spatial relation between the drainage network and waterlogged areas. Shapefiles of lake and large water bodies were collected from the Survey of Bangladesh dataset to determine the area boundary and their extent. Survey of Bangladesh has been providing spatial data of natural features, services and utilities, transport network, distribution of industries, etc. After that, a distance tool in spatial analysis was applied. Sahu ( 2014 ) conducted a study on mapping of waterlogged areas in Moyna Basin of West Bengal. He found that high density of waterlogged areas is positively correlated with high canal density. Another study found a higher water logging probability for areas close to the canals (Sar et al., 2015 ). Therefore, the drainage density and their proximity to a particular buffer zone can be considered potential determinants of waterlogged vulnerable areas.

Changes in built-up areas

The built-up area was measured using Landsat and Sentinel multispectral satellite imageries through unsupervised classification. The unsupervised classification used a grouping algorithm which can automatically determine the frequently repetitive texture patterns to detect built-up areas (Gowthami & Thilagavathi, 2014 ). The analysis was simplified with two likelihood classes: built-up area pixels and other pixels. The temporal variation of the built-up area shows that its density has been increasing continuously since 1990. In this study, built-up area includes all infrastructure, residential, commercial, mixed-use and industrial areas, villages, settlements, road networks, pavements, and man-made structures. These infrastructures make the surface impervious, both increasing the amount of surface runoff and collecting water in surface depressions. The situation is exacerbated by the lack of effective drainage system in the city.

All the above indicators are considered input variables to the overlay model. After assigning these variables to equal weights and rank, the overlay analysis was applied to identify the water logging hazard zone.

Water logging vulnerability assessment with social attributes

For generating vulnerability index, slum distribution, population density, dwelling house types, and its floor materials along with changing trend of built-up areas from 1990 to 2019 has been considered. The slum distribution map was generated from slum census 2014 data and BRAC urban slum web portal. The population density map was developed from the global human settlement dataset. Housing characteristics and floor materials data were derived from the Slum census survey 2014 dataset. Built-up areas were extracted from the Landsat and Sentinel satellite imageries. Dot density method was applied to represent the spatial distribution of social attributes over the water logging hazard zones. Categorical values of the social attributes were represented by dots over the identified waterlogged areas to quantify their extent. Each dot represents a particular number of group values and the density of the dots reflected the status of that attribute.

Finally, an integrated spatial model was used to map the water logging hazard and socio-economic risk level using GIS environment over the entire Dhaka city with the aim to provide useful information for better urban planning, management and mitigation of the urban water logging hazard along with its risk factors. For instance, identification of poorly structured households within water logging hazard zones may be prioritized while planning development initiatives. The sources of data that have been used are given in Table 1 .

Water logging hazard attributes

In the present study, NDVI technique on multi-temporal data has been used for the identification of water-containing pixels. Figure  2 depicts the NDVI map for 1990, 2010, and 2019. In 1990, the ranges of NDVI were found to be greater than 0.2 which indicates moderate to high vegetation coverage in some areas. On the other hand, in 2010, the NDVI value became lower than 0.2 indicating lower vegetation coverage than 1990. In 1990, the city had a large number of vegetation coverage which were later covered up by land due to the higher growth rate of population and rapid urbanization. Later in 2019, the vegetation coverage declined sharply and made the city more vulnerable to water logging. The value of NDVI reveals that the city did not have much dense forest cover since 1990, while the NDVI value in 2010 and 1990 represents the agricultural land. In 1990, the city had a large coverage of natural and artificial canals vegetation compared to other years. Subsequently, in 2010, rapid urbanization took place, which slightly decreased greeneries. This notion also supports the study findings of Rahman et al. ( 2011 ), where they found Dhaka obtained copious vegetation from the 1989 to 2010 period. However, from the measured values of both vegetation coverage, greeneries and water bodies have declined drastically in 2019, as shown in Fig.  2

Temporal distribution of the NDVI map of Dhaka city in 1990, 2010, and 2019 respectively

The NDWI map illustrated in Fig.  3 shows the temporal variation of NDWI value of the years of 1990, 2010, and 2019. The highest value of NDWI was observed in 1990 and 2010. In 2019, the highest value of NDWI was observed as 0.12 since urbanization and expansion of built-up areas took place, which was also responsible for lowering water content in 2019. According to Chatterjee et al. ( 2005 ), the NDWI value ranging from −0.34 to +0.59 represents some water-logged areas. Nevertheless, in Dhaka city, poor drainage networks and other anthropogenic factors have influenced the value of the index.

Temporal distribution of the NDWI map of Dhaka city in 1990, 2010, and 2019

In NDMI, the higher values of +0.85 indicate the existence of more soil moisture under massive water bodies and lower values of +0.1 indicate low soil moisture content, as depicted in Fig.  4 . It shows the temporal variation of NDMI where the value ranges of NDMI, indicating that the soil in 1990 was highly moist, which has come from the surface runoff and might have resulted from the rainfall; in 2010, value ranges of NDMI manifest the soil was comparatively dry, whereas the highest ranges of value around +0.39 indicate the soil had higher level of moisture in 2019 than in 2010. However, the observed soil moisture in the middle part of Dhaka city reflected susceptibility to water logging.

Temporal distribution of the NDMI map of Dhaka city in 1990, 2010, and 2019 respectively

According to FAO ( 1988 ), Dhaka is located in Deep Red Brown Terrace soil region. This type of soil is moderately well drained, reddish to yellow–brown, and strongly to extremely acidic. Besides, the soil texture is silty loam which is predominant on the Meghna estuarine floodplain. As for silty soil, it tends to have moist soil contents. The NDMI values also found the soil moisture in Dhaka city, indicating the likelihood of natural water logging prevailing is high in Dhaka city.

Topographic and slope variation in term of DEM model

Topographic variation is an important factor for the waterlogged situation in flat terrain (Kaiser et al., 2013 ). The elevation map and slope map of the study region have been generated from the Multi-Error-Removed Improved-Terrain (MERIT) DEM satellite data. The highest altitude observed from the analysis is 23 m. The lowest altitude of 0–10 m indicates highest waterlogged zones in the study site which lies in the northeastern part of Dhaka city. Besides, the slope of the study area varies from 0.16 to 3.8° (Fig.  5 ). Areas with high slope and higher altitudes are affected comparatively less by water logging while areas of lower altitude are highly susceptible to the water logging phenomenon.

Elevation and slope distribution map of Dhaka city

Distance buffer zone from the drainage stream

In this study, the drainage buffer distance was used to establish the spatial relationship with the existing natural drainage municipality network. In Fig.  6 , the distance from drainage ranges from 0 to 990 m. Closer proximity of area from a particular stream indicates a lower possibility of water logging as the water runs off to the nearest stream, e.g., lakes and canal, quickly.

Distance buffer from the streams in Dhaka city

In particular, during monsoon season, improperly treated drainage is a major cause of water logging. Besides, half of the drains in the city are not covered, and it is common to find them clogged with garbage (Kabir et al., 2018 ). Dhaka has 12 drainage catchment zones depending on the drainage network (Tawhid, 2004a , b ). WASA provides 38% of the city’s drainage and sewerage network. Open canals, box culverts, storm sewer lines, and surface drain facilities make up the Storm Sewer Network. Aside from that, the natural drainage network drains around 80% of the water through canals and retention areas (Subrina & Chowdhury, 2018 ).

Water logging vulnerable zone and influencing social attributes

Water logging and distribution of built-up areas.

Built-up areas have been increasing due to rapid urbanization of Dhaka city. In 1990, the south part of Dhaka city, currently known as Dhaka South City Corporation, became more urbanized than other parts of Dhaka. Later in 2010 and 2019, the built-up areas spread over the middle and northern part of the Dhaka city. Figure  7 shows the distribution of built-up areas in the present day. Due to population growth and rural-to-urban migration, the trend of the population, as well as urbanization, has increased from 12% in 1990 to around 50% in 2011 (Grimm et al., 2008 ; United Nations, 2012 ). In 2019, larger areas of built-up zones were observed over most of Dhaka city. Therefore, the areas became highly vulnerable to becoming clogged down by water as the drainage network has not improved proportionately. On the contrary, the eastern part of the city, much of it brought within the jurisdiction of the greater Dhaka, is yet to develop and similar levels of built-up areas cannot be observed compared to the other areas.

Built-up areas in Dhaka city in 2019

Water logging and population density map

The extent of calamities associated with water logging will depend on the population density of the affected area. The population density map reflects the population densification in a particular area and its association with water logging. Figure  8 shows the water logging vulnerability zone and population density. In this figure, vulnerability zones are segmented in 5 different layers as very low, low, medium, high, and very high and these zones are associated with the existing population density. It was found that water logging vulnerability was very high in the wards having high population density. On the other hand, areas with medium to high water logging vulnerability also had high population density. In this map, medium vulnerable areas were found in Cantonment restricted area, Badda union, and some wards that had a decent population density. The map also shows that Hariramp union, Uttar khan union, Dakshinkhan union, Bhatara union, Dakshingaon union, Manda union, Matuail union, Sarail union, Shyampur union, Sultanganj union, and ward 8, 9, 33 were low water logging vulnerable areas and Dumni union, Beraid union, Satarkul union, Nasirabad union, and Demra union were very low water logging vulnerable areas with very small population density. In general, more areas with high population density are found to have a higher risk of water logging, the notable exception being the eastern and north-western part of the city which are mainly suburban areas surrounded by wetlands and rivers.

Water logging vulnerability zone and population density in Dhaka city

However, there has been rapid urbanization with increasing anthropogenic activities in Dhaka city, which has resulted in land cover changes over the years (Yao et al., 2015 ). Disparities in population distribution exist sharply in Dhaka. Some rich neighborhoods have a very small population density compared to neighborhoods with a high population density. The following Table 2 shows the Dhaka population and growth rate over the years from 1990. It depicts the population follows an increasing trend from 1990 to 2020.

Water logging and slum household distribution

Slum population are one of the most vulnerable communities in the city living in informal settlements with poor living conditions. Their susceptibility level regarding water logging hazards are clearly depicted in the final generated map. Figure  9 depicts the dot density map of the slum households according to the Slum Census 2014 where 1 dot represents 50 households. The severity of water logging is high among the slum households because of the higher population density in slum areas, unplanned and unhygienic housing and sanitation systems, with very poor access roads and poor environment, etc. Figure  9 shows the water logging vulnerability zone and slum household distribution depict how many slum households are vulnerable to the problems of water logging. The vulnerability of water logging was very high among the wards with the existence of slum households. Also, the existence of slum households was common among the areas of high susceptibility of water logging such as wards (2, 5, 14, 7), which reveals that most of the slum households of Dhaka city are facing serious water logging problem.

Water logging vulnerability zone and slum household’s distribution in Dhaka city

Water logging and housing types of the dwellers

Among the housing types of the dwellers in Dhaka city, good housing (Pacca and Semi pacca) Footnote 6 and poor housing condition (Jhupri and Kacca) Footnote 7 have been categorized from the Slum Census 2014. The consequences and severity of the problem of water logging vary based on the housing types, making it necessary to consider housing types and associate that with water logging. Figure  10 depicts the housing types in the water logging vulnerable zones. It was found that water logging susceptibility was very high within the wards with good housing (Pacca and Semi Pacca). Within same wards, the vulnerability of water logging was also very high in the households with poor housing structures. The water logging susceptibility was very high among other wards with poor housing as well. Lastly, the following analysis implies that almost 70% of poorly structured households lies within high to very high water logging vulnerable zone.

Water logging vulnerability zone and housing characteristics in Dhaka city

Water logging and associated floor materials

A study on water logging conducted in the 4 urban areas (Sylhet, Dhaka, Mymensingh, and Chittagong) in Bangladesh found that 69% of houses in those areas became damaged due to water logging (Anisha & Hossain,  2014 ). That signifies that a poor housing structure in a water logging vulnerable zone will be more prone to experience adverse consequences, especially if floor materials of houses are made from poor construction materials. It can be assumed that water logging causes dampness in some floor materials, making it remain wet for a long period (Gazi & Hossain, 2019 ) and the issues of slipperiness or wetness occurred in the houses with mud floors. Figure  11 shows the water logging vulnerability zones and the poor and good flooring status in those areas. Bamboo and mud types floor were considered poor floor and the floor made of brick type materials belonged to good flooring condition. The existence of a huge number of houses with poor flooring was found in north and north-western part of Dhaka where the severity of water logging is also very high. A huge number of houses with good floor materials were found throughout Dhaka city, especially in ward 11, 12, and 13, where the vulnerability of water logging is also very high. As Dhaka is an urbanized city, most houses are made of brick; mud and bamboo-made floor was found in the peripheral areas of north, north-western part, and also in some slum areas in the middle part of Dhaka city where water logging vulnerability was also very high.

Water logging vulnerability zone and flooring condition in Dhaka city

This study delineated the water logging vulnerable zone in a comprehensive way depicting the variables and indicators using an overlay weighted technique. The inclusion of temporal extension and social attributes made the research encompassing and exceptional. The method used the inclusion and integration of spatial, social, and demographic data for addressing water logging problem, make it unique, and will have significant contribution to advance scientific knowledge.

Moniruzzaman ( 2012 ), Tareq et al. ( 2018 ), and Awal ( 2014 ) conducted several studies on water logging in the south-west coastal region of Bangladesh. Severe flood, frequent cyclone events, tidal river mismanagement, and excessive rainfall were mentioned as reasons for water logging hazard. Climatic phenomena were considered an important factor of coastal water logging. Among the studies, Tareq et al. ( 2018 ) conducted his study using geo-informatics and qualitative methods where he suggested to re-excavate the silted riverbed to solve the situation. The methodological framework and conceptualization of this study were similar but the locational characteristics and geomorphological attributes were quite different as Dhaka is a highly urbanized city and the capital of Bangladesh.

Since Dhaka has been undergoing a rapid unplanned urban development in the last two decades. As a result, the city has exceeded its carrying capacity due to extensive urban migration and along with untenable development resulting in several hazards. The development plan has not been implemented in a holistic and integrated way. Moreover, there is no integration within the different institutions of the interconnected neighborhood domains while deploying the interventions. WASA and the two City Corporations have mostly implemented their development projects individually without coordination. Also, the economic gap between rich and poor has been noticeably increasing, with the floating and informal population being deprived of the basic amenities; hence, the higher population density neighborhood areas always suffer from water logging hazards. Furthermore, 70 to 75% informal settlements are observed in the high to very high water logging vulnerable zone. This scenario demarcates that informal settlements are less prioritized while initiating a development plan. Also, almost 70% of poorly structured houses are found in high to very high water logging susceptible zone. These household members are the worst sufferers of the water logging hazard due to problems arising from floor dampness. The growing expansion of built-up areas has not been properly planned resulting in submersion of these areas during heavy rainfall.

Thiele-Eich et al. ( 2015 ) analyzed a trend of water level and flooding in Dhaka for the past 100 years and their findings suggested that minimum surface water levels have decreased by 0.71 to 0.61 m. While the magnitude and duration of the flood have reduced, the frequency of extreme flood events has increased in Bangladesh. Nevertheless, the study could not conclusively show a direct link with rise in mortality or higher morbidity rate due to extreme flood, but the relative risk of death was found to reduce with the decrease in water levels (Thiele-Eich et al., 2015 ). Inadequate draining capacity and inappropriate lining of pipes were considered the main cause of long-lasting floods in Dhaka (Pirumanekul & Mark,  2001 ). The geo-referenced model and simulation found that water levels in the street mainly cause urban flooding. The flood simulation model also implied that Shantinagar crossing had the highest inundation (55 cm/6 h) in 1997 and then Kakrail and Topkhana areas had the flood depth of 19 cm/6 h and 25 cm/12 h respectively. Dewan et al. ( 2004 ) delineated the flood extent map in Dhaka city using DEM, where 1988 and 1998 floods were also taken into consideration. During the 1988 flood, almost all the areas were inundated. However, owing to the construction of several embankments, areas in Dhaka city remain flood-free from river water but the rainfall-induced flooding has been very severe.

In several areas of Dhaka, the fast rate of urbanization has prompted water logging and urban floods. Moniruzzaman et al. ( 2020 ) in their study observed that from 1978 to 2018, there were 13.1%, 4.8%, and 7.8% decreases in agricultural land, green spaces, and aquatic bodies, respectively, and an estimated 22.1% rise in the built-up area in this region. Besides, they also found that the area with very high runoff has expanded from 74.24 km 2 (24.44%) in 1978 to 174.23 km 2 (57.36%) in 2018. It indicates that the land use land cover change, especially the decreasing trend of green spaces and water bodies of the study area, refers the significant rise in water logging frequency and intensity. Besides, regarding the rainfall pattern, September 2004 had seen the highest daily precipitation of 341 mm/day. And the annual maximum daily rainfall variation (1990–2018) ranges between 50 and 180 mm, with the exception of 2004 and 2009, when it exceeds 300 mm (Moniruzzaman et al., 2020 ).

Dewan et al. ( 2007 ) illustrated a hazard map that shows that a major portion of Dhaka city was located within a moderate to very high hazard vulnerable zone, especially the suburb areas which have become urbanized in 2010. Masood and Takeuchi ( 2012 ) found in their study that about 60% of eastern Dhaka regularly submerged in water every year in monsoon due to absence of flood embankment. Due to a lack of proper drainage system, water became clogged down for several hours. The study findings also support this outcome. Besides, Rashid et al. ( 2007 ) conducted a research on slum dwellers of Mirpur and Vasantek neighborhood areas. The study found that the respondents from Vasantek experienced flooding inside their homes more often and the inundation depth was higher in Vasantek areas than Mirpur areas. It also revealed that all slum dwellers were being exposed to mosquito-borne diseases due to the long-lasting floodwater.

In the urban context, Datta and Mandal ( 2017 ) stated that traffic congestion and water logging are the worst problems in Dhaka city. The study found a significant loss of natural water bodies across the city. They suggested forming a “blue network” within the city to solve the transportation and water logging problem. Besides, Subrina and Chowdhury ( 2018 ) conducted a study in Dhaka city to identify the causations and evaluate its impact based on internet open-source data and information. Population growth, unplanned development, the disappearance of natural drainage systems and green spaces, topography, waste management, and drainage capacity were identified as the major reasons for water logging. The findings of this study which were derived by utilizing open-source data were quite analogous to Subrina and Chowdhury’s study in the Dhaka context. The study recommended macro-scale solutions, including retrieval of canal networking and developing urban fringe areas. Lastly, the poor drainage network, dumping of waste everywhere resulting in the hindrance of water flow as well as clogging down the existing drainage channels. Additionally, absence of sufficient canals and reservoirs to hold extra water, pollution of surrounding rivers, etc. were identified as the main reasons behind worsening the water logging situation.

While the present study was able to identify and evaluate the water logging hazard in a highly urbanized area and analyze the risk by overlapping the infrastructure and demographic attributes through the lens of the GIS-RS approach in a temporal extent, a huge strength, it had some limitations too. The main limitation of the study was the unavailability of high-resolution satellite images. Also, we could not utilize the high-resolution DEM data. It could have more accurate if we used the high-resolution intra-annual satellite imageries. Updated socio-demographical dataset was also not available for use. Inadequately published literature and lack of data were considered the major drawback, which would have further enriched the study. Furthermore, it was not possible to acquire the groundwater and flooding data for the study because of its unavailability in a large capacity.

Conclusions

The present research demarcated the water logging hazard zones in Dhaka city through an integrated GIS-remote sensing method and has shown the spatial distribution of the water logging vulnerabilities over the indicators of slum, population density, housing types, and floor materials. The results of the study suggest that the south and south-western part of the Dhaka city are comparatively susceptible to water logging hazards as these areas lie on highly to very highly vulnerable zones. Moreover, the slums were densified in the “very high” waterlogged areas. The waterlogged hazard and the vulnerability maps may possibly be used by planners, policymakers, and local people for urban development, water resources management, drainage network development, infrastructure expansion and housing management, etc. An inclusive and integrated approach needs to be included in the future development plans of all sectors to make it sustainable. It is also essential to give extra attention to the lower elevated areas. Informal settlement areas should also be specially focused while initiating an intervention. A proper drainage system needs to be established and the existing canals should also be well maintained and re-excavated regularly to enhance the retention capacity. The identified water logging hazard zones will also be useful for designing future projects in the urban neighborhood context and planning for an healthy city. The applied integrated GIS and remote sensing method can also be efficiently used for sustainable water resource management purposes.

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

According to Census of Slum Areas and Floating Population 2014, slum is a cluster of compact settlements of five or more households which generally grow very unsystematically and haphazardly in an unhealthy condition and atmosphere on government, private vacant land, or owner-based household premises.

NDVI = [Band 5 − Band 4]/[Band 5 + Band 4].

NDWI = [Band 2 − Band 1]/Band 2 + Band 1].

NDMI = (Band 4 − Band 5)/(Band 4 + Band 5).

The Raster Calculator tool allows to create and execute map algebra expressions and calculations like other geoprocessing tools. It can be used in Model Builder to maintain workflows in an integrated way.

Pacca is a housing type which is designed to be solid and permanent, typically made of brick with or without cemented. Semi pacca house is in between Pacca and Kacca such as the wall has made up of pacca materials but the roof is made up of tin, etc.

Kacca is narrow and built of mud brick or other temporary materials which is cheap and easy to make. Jhupri is a temporary house or shades mainly found in roadside, train or bus stations which is made of polythene, straw, and cheap plastic materials.

Adri, N. (2013). Climate-induced rural-urban migration in Bangladesh: Experience of migrants in Dhaka City.

Anik, S. A. B. (2019).  The never ending woe of water logging in Dhaka. Dhaka Tribune. Viewed 13 July, 2019.

Anisha, N. F., & Hossain, S. (2014, December). A case study on water logging problems in an urban area of Bangladesh and probable analytical solutions. In  2nd International Conference on Advances in Civil Engineering,   26 , 28.

Awal, M. A. (2014). Water logging in southwestern coastal region of Bangladesh: Local adaptation and policy options. Science Postprint, 1 (1), e00038.

Article   Google Scholar  

Bari, F. M., & Hasan, M. (2001). Effect of urbanisation on storm runoff characteristics of Dhaka City . Tsinghua University Press. XXIX IAHR Congress.

Google Scholar  

Chakraborty, D. (2019). The climatic condition of Bangladesh: Scenario of Dhaka.

Chatterjee, C., Kumar, R., Chakravorthy, B., Lohani, A. K., & Kumar, S. (2005). Integrating remote sensing and GIS techniques with groundwa-ter flow modeling for assessment of waterlogged areas. Water Re-Source Management, 19 , 539–554. https://doi.org/10.1007/s11269-005-2071-4

Chowdary, V. M., Chandran, R. V., Neeti, N., Bothale, R. V., Srivastava, Y. K., Ingle, P., & Singh, R. (2008). Assessment of surface and sub-surface waterlogged areas in irrigation command areas of Bihar state using remote sensing and GIS. Agricultural Water Management, 95 (7), 754–766.

Datta, U., & Mandal, D. (2017). Creating blue network: A solution of present water logging and transportation problem for the Dhaka metropolitan area.  Design that cares-inter disciplinary approach to making built environments efficient and meaningful .

Demographia World Urban Areas. (2020). 16 th Annual Edition, June, 2020.

Dewan, A. M., Nishigaki, M., & Komatsu, M. (2004). DEM based flood extent delineation in Dhaka City. Bangladesh. 岡山大学環境理工学部研究報告, 9 (1), 99–110.

Dewan, A. M., Islam, M. M., Kumamoto, T., & Nishigaki, M. (2007). Evaluating flood hazard for land-use planning in Greater Dhaka of Bangladesh using remote sensing and GIS techniques. Water Resources Management, 21 (9), 1601–1612.

Dwivedi, R. S., & Sreeniwas, K. (2002). The vegetation and water logging dynamics as derived from spaceborne multispectral and multitempo-ral data. International Journal of Remote Sensing, 21 (3), 519–531.

FAO. (1988). Land resources appraisal of Bangladesh for agricultural development, Vol 2, Rome, FAO/ UNDP, Classification of the soils of Bangladesh, 1986; H Brammer, The Geography of the Soils of Bangladesh, UPL, Dhaka, 1996.

Gain, A. K., Mojtahed, V., Biscaro, C., Balbi, S., & Giupponi, C. (2015). An integrated approach of flood risk assessment in the eastern part of Dhaka City. Natural Hazards, 79 (3), 1499–1530.

Gao, B. C. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58 (3), 257–266.

Gazi, M., & Hossain, A. (2019).  Impact of water logging in south western coastal zone of Bangladesh: A case study  (Doctoral dissertation, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh).

Geogr, J., Sims, D. A., & Gamon, J. A. (2003). Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: A comparison of indices based on liquid water and chlorophyll absorption. Remote Sensing of Environment, 84 , 526–537.

Goodwin, N. R., Coops, N. C., Wulder, M. A., Gillanders, S., Schroeder, T. A., & Nelson, T. (2008). Estimation of insect dynamics using a temporal se-quence of Landsat data. Remote Sensing of Environment, 112 , 3680–3689.

Gowthami, K., & Thilagavathi, K. (2014, February). Built-up area detection of remote sensing images using static clustering technique. In 2014 International Conference on Electronics and Communication Systems (ICECS) (pp. 1–5). IEEE.

Grimm, N. B., Faeth, S. H., Golubiewski, N. E., et al. (2008). Global change and the ecology of cities. Science, 319 (5864), 756–760.

Article   CAS   Google Scholar  

Hassan, M. S., & Mahmud-ul-islam, S. (2014). Detection of water logging areas based on passive remote sensing data in Jessore District of Khulna Division, Bangladesh. International Journal of Scientific and Research Publications (IJSRP), 4 , 12.

Hussain, Z. (2013). In Bangladesh, the alternative to urbanization is urbanization.  End Poverty in South Asia blog .

Huda, N., Terao, T., Nonomura, A., & Suenaga, Y. (2022). Remote sensing spatial analysis of waterlogging due to cyclones and storms in Bangladesh.

Islam, E., Khan, S. A., Khaleque, M. A., & Ahammed, S. S. (2020). Waterlogging in the southwest coastal areas of Bangladesh: Local adaptation techniques and challenges. American Academic Scientific Research Journal for Engineering, Technology, and Sciences, 68 (1), 112–119.

Jackson, R. D., & Huete, A. R. (1991). Interpreting vegetation indices. Prevent. Veterinarni Medicina, 11 (3), 185–200.

Kabir, M. H., Sato, M., Habbiba, U., & Yousuf, T. B. (2018). Assessment of urban disaster resilience in Dhaka North City Corporation (DNCC), Bangladesh. Procedia Engineering, 212 , 1107–1114.

Kaiser, M. F., El Rayes, A., Ghodeif, K., & Geriesh, B. (2013). GIS data integration to manage water logging problem on the eastern Niledelta of Egypt.

Mahbub, F., Rahman, M. M., Mannan, M. A., & Akter, F. (2021). Study on climate variability, climate extremes over Dhaka city and people’s perception about its impact.

Majumder, A. K., Hossain, M. S., & Al Nayeem, A. (2018). Assessment of people’s perception on water logging in Chittagong City Corporation Area, Bangladesh.  Assessment ,  5 (2).

Masood, M., & Takeuchi, K. (2012). Assessment of flood hazard, vulnerability and risk of mid-eastern Dhaka using DEM and 1D hydrodynamic model. Natural Hazards, 61 (2), 757–770.

McFeeters, S. K. (1996). The use of the normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17 (7), 1425–1432.

Moniruzzaman, M., Thakur, P. K., Kumar, P., Ashraful Alam, M., Garg, V., Rousta, I., & Olafsson, H. (2020). Decadal urban land use/land cover changes and its impact on surface runoff potential for the Dhaka City and surroundings using remote sensing. Remote Sensing, 13 (1), 83.

Moniruzzaman, M. (2012). Impact of climate change in Bangladesh: Water logging at south-west coast. In  Climate change and the sustainable use of water resources  (pp. 317–336). Springer, Berlin, Heidelberg.

Mowla, Q. A., & Islam, M. S. (2013). Natural drainage system and water logging in Dhaka: Measures to address the problems. Journal of Bangladesh Institute of Planners ISSN, 2075 , 9363.

Nabi, M. S. (2019). 36% of Dhaka’s water bodies filled up in 9 years, Bangla Tribune.

Papry, R. I., & Ahmed, G. U. (2015). Drainage condition in water logged areas of central part in Chittagong City Corporation. International Journal of Engineering Science Invention ISSN Online , 4 (1), 2319–6734.

Pirumanekul, C., & Mark, O. (2001, June). Modelling of urban flooding in Dhaka City. In  Proceedings of 4th DHI Software Conference  (pp. 101–108).

Rabbani, G., Rahman, A. A., & Islam, N. (2011). Climate change implications for Dhaka City: A need for immediate measures to reduce vulnerability. In  Resilient cities  (pp. 531–541). Springer, Dordrecht.

Rahman, M. M., Akteruzzaman, A. K. M., Khan, M. M. H., Jobber, A., & Rahman, M. M. (2009). Analysis of water logging problem and its environmental effects using GIS approaches in Khulna City of Bangladesh. Journal of Socioeconomic Research and Development, 6 (2), 572–577.

Rahman, S., Hasan, S. M. R., Islam, M. A., & Maitra, M. K. (2011). Temporal change detection of vegetation coverage of Dhaka using Remote Sensing. International Journal of Geomatics and Geosciences, 2 (2), 481–490.

Rashid, H., Hunt, L. M., & Haider, W. (2007). Urban flood problems in Dhaka, Bangladesh: Slum residents’ choices for relocation to flood-free areas. Environmental Management, 40 (1), 95–104.

Sahu, A. S. (2014). A study on Moyna Basin water-logged areas (India) using remote sensing and GIS methods and their contemporary economic significance.

Sar, N., Chatterjee, S., & Adhikari, M. D. (2015). Integrated remote sensing and GIS based spatial modelling through analytical hierarchy process (AHP) for water logging hazard, vulnerability and risk assessment in Keleghai river basin. India. Modeling Earth Systems and Environment, 1 (4), 31.

Subrina, S., & Chowdhury, F. K. (2018). Urban dynamics: An undervalued issue for water logging disaster risk management in case of Dhaka city, Bangladesh. Procedia Engineering, 212 , 801–808.

Tareq, S. M., Rahman, M. T. U., Islam, A. Z., Baddruzzaman, A. B. M., & Ali, M. A. (2018). Evaluation of climate-induced water logging hazards in the south-west coast of Bangladesh using Geoinformatics. Environmental Monitoring and Assessment, 190 (4), 230.

Tawhid, K. G. (2004a). Causes and effects of water logging in Dhaka city, Bangladesh, Master’s Thesis, Royal Institute of Technology, Stockholm.

Tawhid, K. G. (2004b). Causes and effects of water logging in Dhaka City, Bangladesh.  TRITA-LWR master thesis, Department of Land and Water Resource Engineering, Royal Institute of Technology, Stockholm .

Thiele-Eich, I., Burkart, K., & Simmer, C. (2015). Trends in water level and flooding in Dhaka, Bangladesh and their impact on mortality. International Journal of Environmental Research and Public Health, 12 (2), 1196–1215.

Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8 , 127–150.

Ullah, G. W., & Islam, A. (2017). A case study on Pathao: Technology based solution to Dhaka’s traffic congestion problem. Case Studies in Business and Management, 4 (2), 100–108.

United Nations. (2018). 2018 revision of world urbanization prospects, accessible online at https://population.un.org/wup/

United Nations (UN). (2012). World urbanization prospects: The 2011 revision. United Nations. Available from: http://www.un.org/en/

Wilson, E. H., & Sader, S. A. (2002). Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sensing of Environ-Ment, 80 , 385–396.

Xue, F., Huang, M., Wang, W., & Zou, L. (2016). Numerical simulation of urban water logging based on floodarea model. Advances in Meteorology.

Yao, X., Wang, Z., & Wang, H. (2015) Impact of urbanization and land-use change on surface climate in middle and lower reaches of the Yangtze River, 1988–2008.  Advances in Meteorology.

Download references

Acknowledgements

The authors would like to acknowledge Shahriar Hasan and Priyanka Sultana Hema, who contributed to the data extraction and compiling open-source internet data.

This research was funded by the Wellcome Trust (Grant number 209376/Z/17/Z). For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.

Author information

Authors and affiliations.

BRAC James P Grant School of Public Health, BRAC University, 6th Floor, Medona Tower, 28 Mohakhali Commercial Area, Bir Uttom A K Khandakar Road, Dhaka, 1213, Bangladesh

Rafiul Alam, Zahidul Quayyum, Marzuka Ahmad Radia, Hasna Hena Sara & Md Tanvir Hasan

Imperial College, South Kensington Campus, London, SW7 2AZ, UK

Simon Moulds & Adrian Butler

You can also search for this author in PubMed   Google Scholar

Contributions

ZQ initiated and contributed to the preliminary concept and idea of the study. RA developed the methodological framework and design of the study under the supervision of ZQ and MTH, with essential critical feedback of SM. RA conducted the spatial analysis and interpreted the results and drafted the initial version of the manuscript. MAR and HHS revised it critically and gave essential input. ZQ, SM, and APB reviewed the revised manuscript critically and gave essential intellectual feedback. Finally, all the authors approved this final version and agreed to be accountable for any kind of questions related to the accuracy or integrity of any part of the work that has been investigated and resolved.

Corresponding author

Correspondence to Zahidul Quayyum .

Ethics declarations

Ethical approval.

This study did not require ethical approval as this was based on secondary data. However, this study has been conducted under the project “Pathways to Equitable Healthy Cities” which has received ethical approval from the Institutional Review Board (IRB) of BRAC James P Grant School of Public Health (Protocol No: 2019–012-IR), BRAC University.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Alam, R., Quayyum, Z., Moulds, S. et al. Dhaka city water logging hazards: area identification and vulnerability assessment through GIS-remote sensing techniques. Environ Monit Assess 195 , 543 (2023). https://doi.org/10.1007/s10661-023-11106-y

Download citation

Received : 17 May 2022

Accepted : 09 March 2023

Published : 05 April 2023

DOI : https://doi.org/10.1007/s10661-023-11106-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Water logging
• Spatio-temporal
• Find a journal
• Publish with us
• Track your research

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 28 March 2024

New water accounting reveals why the Colorado River no longer reaches the sea

• Brian D. Richter   ORCID: orcid.org/0000-0001-7216-1397 1 , 2 ,
• Gambhir Lamsal   ORCID: orcid.org/0000-0002-2593-8949 3 ,
• Landon Marston   ORCID: orcid.org/0000-0001-9116-1691 3 ,
• Sameer Dhakal   ORCID: orcid.org/0000-0003-4941-1559 3 ,
• Laljeet Singh Sangha   ORCID: orcid.org/0000-0002-0986-1785 4 ,
• Richard R. Rushforth 4 ,
• Dongyang Wei   ORCID: orcid.org/0000-0003-0384-4340 5 ,
• Benjamin L. Ruddell 4 ,
• Kyle Frankel Davis   ORCID: orcid.org/0000-0003-4504-1407 5 , 6 ,
• Astrid Hernandez-Cruz   ORCID: orcid.org/0000-0003-0776-5105 7 ,
• Samuel Sandoval-Solis 8 &
• John C. Schmidt 9  

Communications Earth & Environment volume  5 , Article number:  134 ( 2024 ) Cite this article

9631 Accesses

751 Altmetric

Metrics details

• Water resources

Persistent overuse of water supplies from the Colorado River during recent decades has substantially depleted large storage reservoirs and triggered mandatory cutbacks in water use. The river holds critical importance to more than 40 million people and more than two million hectares of cropland. Therefore, a full accounting of where the river’s water goes en route to its delta is necessary. Detailed knowledge of how and where the river’s water is used can aid design of strategies and plans for bringing water use into balance with available supplies. Here we apply authoritative primary data sources and modeled crop and riparian/wetland evapotranspiration estimates to compile a water budget based on average consumptive water use during 2000–2019. Overall water consumption includes both direct human uses in the municipal, commercial, industrial, and agricultural sectors, as well as indirect water losses to reservoir evaporation and water consumed through riparian/wetland evapotranspiration. Irrigated agriculture is responsible for 74% of direct human uses and 52% of overall water consumption. Water consumed for agriculture amounts to three times all other direct uses combined. Cattle feed crops including alfalfa and other grass hays account for 46% of all direct water consumption.

Similar content being viewed by others

Disappearing cities on US coasts

Leonard O. Ohenhen, Manoochehr Shirzaei, … Robert J. Nicholls

Meta-analysis shows the impacts of ecological restoration on greenhouse gas emissions

Tiehu He, Weixin Ding, … Quanfa Zhang

Irrigation-driven groundwater depletion in the Ganges-Brahmaputra basin decreases the streamflow in the Bay of Bengal

Fadji Z. Maina, Augusto Getirana, … Ravi Appana

Introduction

Barely a trickle of water is left of the iconic Colorado River of the American Southwest as it approaches its outlet in the Gulf of California in Mexico after watering many cities and farms along its 2330-kilometer course. There were a few years in the 1980s in which enormous snowfall in the Rocky Mountains produced a deluge of spring snowmelt runoff capable of escaping full capture for human uses, but for most of the past 60 years the river’s water has been fully consumed before reaching its delta 1 , 2 . In fact, the river was overconsumed (i.e., total annual water consumption exceeding runoff supplies) in 16 of 21 years during 2000–2020 3 , requiring large withdrawals of water stored in Lake Mead and Lake Powell to accommodate the deficits. An average annual overdraft of 10% during this period 2 caused these reservoirs– the two largest in the US – to drop to three-quarters empty by the end of 2022 4 , triggering urgent policy decisions on where to cut consumption.

Despite the river’s importance to more than 40 million people and more than two million hectares (>5 million acres) of cropland—producing most of the vegetable produce for American and Canadian plates in wintertime and also feeding many additional people worldwide via exports—a full sectoral and crop-specific accounting of where all that water goes en route to its delta has never been attempted, until now. Detailed knowledge of how and where the river’s water is used can aid design of strategies and plans for bringing water use into balance with available supplies.

There are interesting historical reasons to explain why this full water budget accounting has not been accomplished previously, beginning a full century ago when the apportionment of rights to use the river’s water within the United States was inscribed into the Colorado River Compact of 1922 5 . That Compact was ambiguous and confusing in its allocation of water inflowing to the Colorado River from the Gila River basin in New Mexico and Arizona 6 , even though it accounts for 24% of the drainage area of the Colorado River Basin (Fig.  1 ). Because of intense disagreements over the rights to the Gila and other tributaries entering the Colorado River downstream of the Grand Canyon, the Compact negotiators decided to leave the allocation of those waters rights to a later time so that the Compact could proceed 6 . Arizona’s formal rights to the Gila and other Arizona tributaries were finally affirmed in a US Supreme Court decision in 1963 that also specified the volumes of Colorado River water allocated to California, Arizona, and Nevada 7 . Because the rights to the Gila’s waters lie outside of the Compact allocations, the Gila has not been included in formal accounting of the Colorado River Basin water budget to date 8 . Additionally, the Compact did not specify how much water Mexico—at the river’s downstream end—should receive. Mexico’s share of the river was not formalized until 22 years later, in the 1944 international treaty on “Utilization of the Waters of the Colorado and Tijuana Rivers and of the Rio Grande” (1944 Water Treaty) 9 . As a result of these political circumstances, full accounting for direct water consumption at the sectoral level—in which water use is accounted according to categories such as municipal, industrial, commercial, or agricultural uses—has not previously been compiled for the Gila River basin’s water, and sectoral accounting for Mexico was not published until 2023 10 .

The physical boundary of the Colorado River Basin is outlined in black. Hatched areas outside of the basin boundary receive Colorado River water via inter-basin transfers (also known as ‘exports’). The Gila River basin is situated in the far southern portion of the CRB in Arizona, New Mexico, and Mexico. Map courtesy of Center for Colorado River Studies, Utah State University.

The US Bureau of Reclamation (“Reclamation”)—which owns and operates massive water infrastructure in the Colorado River Basin—has served as the primary accountant of Colorado River water. In 2012, the agency produced a “Colorado River Basin Water Supply and Demand Study” 8 that accounted for both the sectoral uses of water within the basin’s physical boundaries within the US as well as river water exported outside of the basin (Fig.  1 ). But Reclamation did not attempt to account for water generated from the Gila River basin because of that sub-basin’s exclusion from the Colorado River Compact, and it did not attempt to explain how water crossing the border into Mexico is used. The agency estimated riparian vegetation evapotranspiration for the lower Colorado River but not the remainder of the extensive river system. Richter et al. 11 published a water budget for the Colorado River that included sectoral and crop-specific water consumption but it too did not include water used in Mexico, nor reservoir evaporation or riparian evapotranspiration, and it did not account for water exported outside of the Colorado River Basin’s physical boundary as illustrated in Fig.  1 . Given that nearly one-fifth (19%) of the river’s water is exported from the basin or used in Mexico, and that the Gila is a major tributary to the Colorado, this incomplete accounting has led to inaccuracies and misinterpretations of “where the Colorado River’s water goes” and has created uncertainty in discussions based on the numbers. This paper provides fuller accounting of the fate of all river water during 2000–2019, including averaged annual consumption in each of the sub-basins including exports, consumption in major sectors of the economy, consumption in the production of specific types of crops, and water consumed by reservoir evaporation and riparian/wetland evapotranspiration.

Rising awareness of water overuse and prolonged drought has driven intensifying dialog among the seven US states sharing the basin’s waters as well as between the United States, Mexico, and 30 tribal nations within the US. Since 2000, six legal agreements affecting the US states and two international agreements with Mexico have had the effect of reducing water use from the Colorado River 7 :

In 2001, the US Secretary of the Interior issued a set of “Interim Surplus Guidelines” to reduce California’s water use by 14% to bring the state within its allocation as determined in the 1963 US Supreme Court case mentioned previously. A subsequent “Quantification Settlement Agreement” executed in 2003 spelled out details about how California was going to achieve the targeted reduction.

In 2007, the US Secretary of the Interior adopted a set of “Colorado River Interim Guidelines for Lower Basin Shortages and the Coordinated Operations for Lake Powell and Lake Mead” that reduced water deliveries to Arizona and Nevada when Lake Mead drops to specified levels, with increasing cutbacks as levels decline.

In 2012, the US and Mexican federal governments signed an addendum to the 1944 Water Treaty known as Minute 319 that reduced deliveries to Mexico as Lake Mead elevations fall.

In 2017, the US and Mexican federal governments established a “Binational Water Scarcity Contingency Plan” as part of Minute 323 that provides for deeper cuts in deliveries to Mexico under specified low reservoir elevations in Lake Mead.i

In 2019, the three Lower Basin states and the US Secretary of the Interior agreed to commitments under the “Lower Basin Drought Contingency Plan” that further reduced water deliveries beyond the levels set in 2007 and added specifications for deeper cuts as Lake Mead drops to levels lower than anticipated in the 2007 Guidelines.

In 2023, the states of California, Arizona and Nevada committed to further reductions in water use through the year 2026 12 .

With each of the above agreements, overall water consumption has been reduced but many scientists assert that these reductions still fall substantially short of balancing consumptive use with 21st century water supplies 2 , 13 . With all of these agreements—excepting the Interim Surplus Guidelines of 2001—set to expire in 2026, management of the Colorado River’s binational water supply is now at a crucial point, emphasizing the need for comprehensive water budget accounting.

Our tabulation of the Colorado River’s full water consumption budget (Table  1 ) provides accounting for all direct human uses of water as either agricultural or MCI (municipal, commercial, industrial), as well as indirect losses of water to reservoir evaporation and evapotranspiration from riparian or wetland vegetation including in the Salton Sea and in a wetland in Mexico (Cienega de Santa Clara) that receives agricultural return flows from irrigated areas in Arizona. We explicitly note that all estimates represent consumptive use , resulting from the subtraction of return flows from total water withdrawals. Table  2 provides a summary based only on direct human uses and does not include indirect consumption of water. We have provided Tables  1 and 2 in English units in our Supplementary Information as Tables SI-1 and SI-2 . We have lumped municipal, commercial, and industrial (MCI) uses together because these sub-categories of consumption are not consistently differentiated within official water delivery data for cities utilizing Colorado River water. More detail on urban water use by cities dependent on the river is available in Richter 14 , among other studies.

We differentiated water consumption geographically using the ‘accounting units’ mapped in Fig.  2 , which are based on the Colorado River Basin map as revised by Schmidt 15 ; importantly, these accounting units align spatially with Reclamation’s accounting systems for the Upper Basin and Lower Basin as described in our Methods, thereby enabling readers accustomed to Reclamation’s water-use reports to easily comprehend our accounting. We have also accounted for all water consumed within the Colorado River Basin boundaries as well as water exported via inter-basin transfers. Water exported outside of the basin includes 47 individual inter-basin transfer systems (i.e., canals, pipelines, pumps) that in aggregate export ~12% of the river’s water. We note that the Imperial Irrigation District of southern California is often counted as a recipient of exported water, but we have followed the rationale of Schmidt 15 by including it as an interior part of the Lower Basin even though it receives its Colorado River water via the All American Canal (Fig.  2 ).

The water budget estimates presented in Tables  1 and 2 are summarized for each of the seven “accounting units” displayed here.

These results confirm previous findings that irrigated agriculture is the dominant consumer of Colorado River water. Irrigated agriculture accounts for 52% of overall consumption (Table  1 ; Figs.  3 and 4 ) and 74% of direct human consumption (Table  2 ) of water from the Colorado River Basin. As highlighted in Richter et al. 11 , cattle-feed crops (alfalfa and other hay) are the dominant water-consuming crops dependent upon irrigation water from the basin (Tables  1 and 2 ; Figs.  3 and 4 ). Those crops account for 32% of all water consumed from the basin, 46% of all direct water consumption, and 62% of all agricultural water consumed (Table  1 ; Fig.  3 ). The percentage of water consumed by irrigated crops is greatest in Mexico, where they account for 86% of all direct human uses (Table  2 ) and 80% of total water consumed (Table  1 ). Cattle-feed crops consume 90% of all water used by irrigated agriculture within the Upper Basin, where the consumed volume associated with these cattle-feed crops amounts to more than three times what is consumed for municipal, commercial, or industrial uses combined.

All estimates based on 2000–2019 averages. Both agriculture and MCI (municipal, commercial, and industrial) uses are herein referred to as “direct human uses.” “Indirect uses” include both reservoir evaporation as well as evapotranspiration by riparian/wetland vegetation.

Water consumed by each sector in the Colorado River Basin and sub-basins (including exports), based on 2000–2019 averages.

Another important finding is that a substantial volume of water (19%) is consumed in supporting the natural environment through riparian and wetland vegetation evapotranspiration along river courses. This analysis—made possible because of recent mapping of riparian vegetation in the Colorado River Basin 16 —is an important addition to the water budget of the Colorado River Basin, given that the only previous accounting for riparian vegetation consumption has limited to the mainstem of the Colorado River below Hoover Dam and does not include vegetation upstream of Hoover Dam nor vegetation along tributary rivers 17 . Given that many of these habitats and associated species have been lost or became imperiled due to river flow depletion 18 —including the river’s vast delta ecosystem in Mexico—an ecologically sustainable approach to water management would need to allow more water to remain in the river system to support riparian and aquatic ecosystems. Additionally, 11% of all water consumed in the Colorado River Basin is lost through evaporation from reservoirs.

It is also important to note a fairly high degree of inter-annual variability in each sector of water use; for example, the range of values portrayed for the four water budget sectors shown in Fig.  5 equates to 24–47% of their 20-year averages. Also notable is a decrease in water consumed in the Lower Basin between the years 2000 and 2019 for both the MCI (−38%) and agricultural sectors (−15%), which can in part be attributed to the policy agreements summarized previously that have mandated water-use reductions.

Inter-annual variability of water consumption within the Lower and Upper Basins, including water exported from these basins. The average (AVG) values shown are used in the water budgets detailed in Tables  1 and 2 .

The water accounting in Richter et al. 11 received a great deal of media attention including a front-page story in the New York Times 19 . These stories focused primarily on our conclusion that more than half (53%) of water consumed in the Colorado River Basin was attributable to cattle-feed crops (alfalfa and other hays) supporting beef and dairy production. However, that tabulation of the river’s water budget had notable shortcomings, as discussed previously. In this more complete accounting that includes Colorado River water exported outside of the basin’s physical boundary as well as indirect water consumption, we find that irrigated agriculture consumes half (52%) of all Colorado River Basin water, and the portion of direct consumption going to cattle-feed crops dropped from 53% as reported in Richter et al. 11 to 46% in this revised analysis.

These differences are explained by the fact that we now account for all exported water and also include indirect losses of water to reservoir evaporation and riparian/wetland evapotranspiration in our revised accounting, as well as improvements in our estimation of crop-water consumption. However, the punch line of our 2020 paper does not change fundamentally. Irrigated agriculture is the dominant consumer of water from the Colorado River, and 62% of agricultural water consumption goes to alfalfa and grass hay production.

Richter et al. 20 found that alfalfa and grass hay were the largest water consumers in 57% of all sub-basins across the western US, and their production is increasing in many western regions. Alfalfa is favored for its ability to tolerate variable climate conditions, especially its ability to persist under greatly reduced irrigation during droughts and its ability to recover production quickly after full irrigation is resumed, acting as a “shock absorber” for agricultural production under unpredictable drought conditions. The plant is also valued for fixing nitrogen in soils, reducing fertilizer costs. Perhaps most importantly, labor costs are comparatively low because alfalfa is mechanically harvested. Alfalfa is increasing in demand and price as a feed crop in the growing dairy industry of the region 21 . Any efforts to reduce water consumed by alfalfa—either through shifting to alternative lower-water crops or through compensated fallowing 20 —will need to compete with these attributes.

This new accounting provides a more comprehensive and complete understanding of how the Colorado River Basin’s water is consumed. During our study period of 2000–2019, an estimated average of 23.7 billion cubic meters (19.3 million acre-feet) of water was consumed each year before reaching its now-dry delta in Mexico. Schmidt et al. 2 have estimated that a reduction in consumptive use in the Upper and Lower Basins of 3–4 billion cubic meters (2.4–3.2 million acre-feet) per year—equivalent to 22–29% of direct use in those basins—will be necessary to stabilize reservoir levels, and an additional reduction of 1–3 billion cubic meters (~811,000–2.4 million acre-feet) per year will likely be needed by 2050 as climate warming continues to reduce runoff in the Colorado River Basin.

We hope that this new accounting will add clarity and a useful informational foundation to the public dialog and political negotiations over Colorado River Basin water allocations and cutbacks that are presently underway 2 . Because a persistent drought and intensifying aridification in the region has placed both people and river ecosystems in danger of water shortages in recent decades, knowledge of where the water goes will be essential in the design of policies for bringing the basin into a sustainable water supply-demand balance.

The data sources and analytical approaches used in this study are summarized below. Unless otherwise noted, all data were assembled for each year from 2000–2019 and then averaged. We acknowledge some inconsistency in the manner in which water consumption is measured or estimated across the various data sources and sectors used in this study, as discussed below, and each of these different approaches entail some degree of inaccuracy or uncertainty. We also note that technical measurement or estimation approaches change over time, and new approaches can yield differing results. For instance, the Upper Colorado River Commission is exploring new approaches for estimating crop evapotranspiration in the Upper Basin 22 . When new estimates become available we will update our water budget accordingly.

MCI and agricultural water consumption

The primary source of data on aggregate MCI (municipal, commercial, and industrial) and agricultural water consumption from the Upper and Lower Basins was the US Bureau of Reclamation. Water consumed from the Upper Basin is published in Reclamation’s five-year reports entitled “Colorado River—Upper Basin Consumptive Uses and Losses.” 23 These annual data have been compiled into a single spreadsheet used for this study 24 . Because measurements of agricultural diversions and return flows in the Upper Basin are not sufficiently complete to allow direct calculation of consumptive use, theoretical and indirect methods are used as described in the Consumptive Uses and Losses reports 25 . Reclamation performs these estimates for Colorado, Wyoming, and Utah, but the State of New Mexico provides its own estimates that are collaboratively reviewed with Reclamation staff. The consumptive use of water in thermoelectric power generation in the Upper Basin is provided to Reclamation by the power companies managing each generation facility. Reclamation derives estimates of consumptive use for municipal and industrial purposes from the US Geological Survey’s reporting series (published every 5 years) titled “Estimated Use of Water in the United States” at an 8-digit watershed scale 26 .

Use of shallow alluvial groundwater is included in the water accounting compiled by Reclamation but use of deeper groundwater sources—such as in Mexico and the Gila River Basin—is explicitly excluded in their accounting, and in ours. Reclamation staff involved with water accounting for the Upper and Lower Basins assume that groundwater use counted in their data reports is sourced from aquifers that are hydraulically connected to rivers and streams in the CRB (James Prairie, US Bureau of Reclamation, personal communication, 2023); because of this high connectivity, much of the groundwater being consumed is likely being sourced from river capture as discussed in Jasechko et al. 27 and Wiele et al. 28 and is soon recharged during higher river flows.

Water consumed from the Lower Basin (excluding water supplied by the Gila River Basin) is published in Reclamation’s annual reports entitled “Colorado River Accounting and Water Use Report: Arizona, California, and Nevada.” 3 These consumptive use data are based on measured deliveries and return flows for each individual water user. These data are either measured by Reclamation or provided to the agency by individual water users, tribes, states, and federal agencies 29 . When not explicitly stated in Reclamation reports, attribution of water volumes to MCI or agricultural uses was based on information obtained from each water user’s website, information provided directly by the water user, or information on export water use provided in Siddik et al. 30 . Water use by entities using less than 1.23 million cubic meters (1000 acre-feet) per year on average was allocated to MCI and agricultural uses according to the overall MCI-agricultural percentages calculated within each sub-basin indicated in Tables  1 and 2 for users of greater than 1.23 million cubic meters/year.

Disaggregation of water consumption by sector was particularly important and challenging for the Central Arizona Project given that this canal accounts for 21% of all direct water consumption in the Lower Basin. Reclamation accounts for the volumes of annual diversions into the Central Arizona Project canal but the structure serves 1071 water delivery subcontracts. We classified every unique Central Arizona Project subcontract delivery between 2000–2019 by its final water use to derive an estimated split between agricultural and MCI uses. Central Arizona Project subcontract delivery data were obtained from the current and archived versions of the project’s website summaries in addition to being directly obtained from the agency through a public information request. Subcontract deliveries were classified based on the final end use, including long-term and temporary leases of project water. This accounting also includes the storage of water in groundwater basins for later MCI or agricultural use. Additionally, water allocated to Native American agricultural uses that was subsequently leased to cities was classified as an MCI use.

Data for the Gila River basin was obtained from two sources. The Arizona Department of Water Resources has published data for surface water use in five “Active Management Areas” (AMAs) located in the Gila River basin: Prescott AMA, Phoenix AMA, Pinal AMA, Tucson AMA, and Santa Cruz AMA 31 . The water-use data for these AMAs is compiled from annual reports submitted by each water user (contractor) and then reviewed by the Arizona Department of Water Resources. The AMA water-use data are categorized by purpose of use, facilitating our separation into MCI and agricultural uses. These data are additionally categorized by water source; only surface water sourced from the Gila River hydrologic system was counted (deep groundwater use was not). The AMA data were supplemented with data for the upper Gila River basin provided by the University of Arizona 32 . We have assumed that all water supplied by the Gila River Basin is fully consumed, as the river is almost always completely dry in its lower reaches (less than 1% flows out of the basin into the Colorado River, on average 33 ).

Data for Mexico were obtained from Hernandez-Cruz et al. 10 based on estimates for 2008–2015. Agricultural demands were estimated from annual reports of irrigated area and water use published by the Ministry of Agriculture and the evapotranspiration estimates of the principal crops published by the National Institute for Forestry, Animal Husbandry, and Agricultural Research of Mexico 10 . The average annual volume of Colorado River water consumption in Mexico estimated by these researchers is within 1% of the cross-border delivery volume estimated by the Bureau of Reclamation for 2000–2019 in its Colorado River Accounting and Water Use Reports 3 .

Exported water consumption

Annual average inter-basin transfer volumes for each of 46 canals and pipelines exporting water outside of the Upper Basin were obtained from Reclamation’s Consumptive Uses and Losses spreadsheet 34 . Data for the Colorado River Aqueduct in the Lower Basin were obtained from Siddik et al. 30 Data for exported water in Mexico was available from Hernandez-Cruz et al. 10 . We assigned any seepage or evaporation losses from inter-basin transfers to their proportional end uses. All uses of exported water are considered to be consumptive uses with respect to the Colorado River, because none of the water exported out of the basin is returned to the Colorado River Basin.

We relied on data from Siddik et al. (2023) to identify whether the water exported out of the Colorado River Basin was for only MCI or agricultural use. When more than one water use purpose was identified, as well as for all major inter-basin transfers, we used government and inter-basin transfer project websites or information obtained directly from the project operator or water manager to determine the volume of water transferred and the end uses. Major recipients of exported water include the Coachella Valley Water District (California); Metropolitan Water District of Southern California (particularly for San Diego County, California); Northern Colorado Water Conservancy District; City of Denver (Colorado); the Central Utah Project; City of Albuquerque (New Mexico); and the Middle Rio Grande Conservancy District (New Mexico). We did not pursue sectoral water-use information for 17 of the 46 Upper Basin inter-basin transfers due to their relatively low volumes of water transferred by each system (<247,000 cubic meters or 2000 acre-feet), and instead assigned the average MCI or agricultural percentage (72% MCI, 28% agricultural) from all other inter-basin transfers in the Upper Basin. The export volume of these 17 inter-basin transfers sums to 9.76 million cubic meters (7910 acre-feet) per year, equivalent to 1% of the total volume exported from the Upper Basin.

Reservoir evaporation

Evaporation estimates for the Upper Basin and Lower Basin are based upon Reclamation’s HydroData repository 35 . Reclamation’s evaporation estimates are based on the standardized Penman-Monteith equation as described in the “Lower Colorado River Annual Summaries of Evapotranspiration and Evaporation” reports 17 . The Penman-Monteith estimates are based on pan evaporation measurements. Evaporation estimates for the Salt River Project reservoirs in the Gila River basin were provided by the Salt River Project in Arizona (Charlie Ester, personal communication, 2023).

Another consideration with reservoirs is the volume of water that seeps into the banks or sediments surrounding the reservoir when reservoir levels are high, but then drains back into the reservoir as water levels decline 36 . This has the effect of either exacerbating reservoir losses (consumptive use) or offsetting evaporation when bank seepage flows back into a reservoir. The flow of water into and out of reservoir banks is non-trivial; during 1999–2008, an estimated 247 million cubic meters (200,000 acre-feet) of water drained from the canyon walls surrounding Lake Powell into the reservoir each year, providing additional water supply 36 . However, the annual rate of alternating gains or losses has not been sufficiently measured at any of the basin’s reservoirs and therefore is not included in Tables  1 and 2 .

Riparian and wetland vegetation evapotranspiration

We exported the total annual evapotranspiration depth at a 30 meter resolution from OpenET 37 using Google Earth Engine from 2016 to 2019 to align with OpenET’s data availability starting in 2016. Total annual precipitation depths, sourced from gridMET 38 , were resampled to align with the evapotranspiration raster resolution. Subsequently, a conservative estimate of the annual water depth utilized by riparian vegetation from the river was derived by subtracting the annual precipitation raster from the evapotranspiration raster for each year. Positive differentials, indicative of river-derived evapotranspiration, were then multiplied by the riparian vegetation area as identified in the CO-RIP 16 dataset to estimate the total annual volumetric water consumption by riparian vegetation across the Upper, Lower, and Gila River Basins. The annual volumetric water consumption calculated over four years were finally averaged to get riparian vegetation evapotranspiration in the three basins. Because the entire flow of the Colorado River is diverted into the Canal Alimentador Central near the international border, very little riparian evapotranspiration occurs along the river south of the international border in the Mexico basin.

In addition to water consumed by riparian evapotranspiration within the Lower Basin, the Salton Sea receives agricultural drain water from both the Imperial Irrigation District and the Coachella Valley Irrigation District, stormwater drainage from the Coachella Valley, and inflows from the New and Alamo Rivers 39 . Combined inflows to the Sea during 2015–2019 were added to our estimates of riparian/wetland evapotranspiration in the Lower Basin.

Similarly, Mexico receives drainage water from the Wellton–Mohawk bypass drain originating in southern Arizona that empties into the Cienega de Santa Clara (a wetland); this drainage water is included as riparian/wetland evapotranspiration in the Mexico basin.

Crop-specific water consumption

The volumes of total agricultural consumption reported for each sub-basin in Tables  1 and 2 were obtained from the same data sources described above for MCI consumption and exported water. The portion (%) of those agricultural consumption volumes going to each individual crop was then allocated according to percentage estimates of each crop’s water consumption in each accounting unit using methods described in Richter et al. 20 and detailed here.

Monthly crop water requirements during 1981–2019 for 13 individual crops, representing 68.8% of total irrigated area in the US in 2019, were estimated using the AquaCrop-OS model (Table SI- 3 ) 40 . For 17 additional crops representing about 25.4% of the total irrigated area, we used a simple crop growth model following Marston et al. 41 as crop parameters needed to run AquaCrop-OS were not available. A list of the crops included in this study is shown in Table SI- 3 . The crop water requirements used in Richter et al. 11 were based on a simplistic crop growth model, often using seasonal crop coefficients whereas we use AquaCrop-OS 40 , a robust crop growth model, to produce more realistic crop growth and crop water estimates for major crops. AquaCrop-OS is an open-source version of the AquaCrop model 42 , a crop growth model capable of simulating herbaceous crops. Additionally, we leverage detailed local data unique to the US, including planting dates and subcounty irrigated crop areas, to produce estimates at a finer spatial resolution than the previous study. We obtained crop-specific planting dates from USDA 43 progress data at the state level. For crops that did not have USDA crop progress data, we used data from FAO 44 and CUP+ model 45 for planting dates. We used climate data (precipitation, minimum and maximum air temperature, reference ET) from gridMET 38 , soil texture data from ISRIC 46 database and crop parameters from AquaCrop-OS to run the model. The modeled crop water requirement was partitioned into blue and green components following the framework from Hoekestra et al. 47 , assuming that blue and green water consumed on a given day is proportional to the amount of green and blue water soil moisture available on that day. When applying a simple crop growth model, daily gridded (2.5 arc minutes) crop-specific evapotranspiration (ETc) was computed by taking the product of reference evapotranspiration (ETo) and crop coefficient (Kc), where ETo was obtained from gridMET. Crop coefficients were calculated using planting dates and crop coefficient curves from FAO and CUP+ model. Kc was set to zero outside of the growing season. We partitioned the daily ETc into blue and green components by following the methods from ref. 41 It is assumed that the crop water demands are met by irrigation whenever it exceeds effective precipitation (the latter calculated using the USDA Soil Conservation Service method (USDA, 1968 48 ). We obtained county level harvested area from USDA 43 and disaggregated to sub-county level using Cropland Data Layer (CDL) 49 and Landsat-based National Irrigation Dataset (LANID) 50 . The CDL is an annual raster layer that provides crop-specific land cover data, while the LANID provides irrigation status information. The CDL and LANID raster were multiplied and aggregated to 2.5 arc minutes to match the AquaCrop-OS output. We produced a gridded crop area map by using this resulting product as weights to disaggregate county level area. CDL is unavailable before 2008. Therefore, we used land use data from ref. 51 in combination with average CDL map and county level harvested area to produce gridded crop harvested area. We computed volumetric water consumption by multiplying the crop water requirement depth by the corresponding crop harvested area.

Data availability

All data compiled and analyzed in this study are publicly available as cited and linked in our Methods section. Our compilation of these data is also available from Hydroshare at: http://www.hydroshare.org/resource/2098ae29ae704d9aacfd08e030690392 .

Code availability

All model code and software used in this study have been accessed from sources cited in our Methods section. We used AquaCrop-OS (v5.0a), an open source version of AquaCrop crop growth model, to run crop simulations. This model is publicly available at http://www.aquacropos.com/ . For estimating riparian evapotranspiration, we used ArcGIS Pro 3.1.3 on the Google Earth Engine. Riparian vegetation distribution maps were sourced from Dryad at https://doi.org/10.5061/dryad.3g55sv8 .

Stromberg, J. C., Andersen, D. C. & Scott, M. L. Riparian floodplain wetlands of the arid and semiarid southwest In Wetland Habitats of North America: Ecology and Conservation Concern s , Chapter 24, pp. 343–356. (University of California Press, 2012). https://www.ucpress.edu/book/9780520271647/wetland-habitats-of-north-america .

Schmidt, J. C., Yackulic, C. B. & Kuhn, E. The Colorado River water crisis: Its origin and the future. WIREs Water https://doi.org/10.1002/wat2.1672 (2023).

Article   Google Scholar  

Colorado River Accounting and Water Use Report: Arizona, California, and Nevada. Interior Region 8: Lower Colorado Basin (US Bureau of Reclamation, 2023). Annual reports available under “Water Accounting Reports” at https://www.usbr.gov/lc/region/g4000/wtracct.html .

Water Operations: Historic Data (US Bureau of Reclamation, 2023). https://www.usbr.gov/rsvrWater/HistoricalApp.html .

Colorado River Compact , 1922 . US Bureau of Reclamation. https://www.usbr.gov/lc/region/pao/pdfiles/crcompct.pdf .

Kuhn, E. & Fleck, J. Science Be Dammed:How Ignoring Inconvenient Science Drained the Colorado River (The University of Arizona Press, 2019) https://uapress.arizona.edu/book/science-be-dammed .

Castle, A. & Fleck, J. The Risk of Curtailment under the Colorado River Compact ( https://doi.org/10.2139/ssrn.3483654 (2019).

US Bureau of Reclamation. Colorado River Basin Water Supply and Demand Study: Technical Report C – Water Demand Assessment https://www.usbr.gov/lc/region/programs/crbstudy/finalreport/Technical%20Report%20C%20-%20Water%20Demand%20Assessment/TR-C-Water_Demand_Assessmemt_FINAL.pdf (2012).

Utilization of the Waters of the Colorado and Tijuana Rivers and of the Rio Grande . International Treaty between the United States and Mexico, February 3, 1944. (International Boundary and Waters Commission, 1944). https://www.ibwc.gov/wp-content/uploads/2022/11/1944Treaty.pdf .

Hernández-Cruz, A. et al. Assessing water management strategies under water scarcity in the Mexican portion of the Colorado River Basin. J. Water Resour. Plan. Manag. 149 , 04023042 (2023).

Richter, B. D. et al. Water scarcity and fish imperilment driven by beef production. Nat. Sustain. 3 , 319–328 (2020).

Biden-Harris Administration announces historic Consensus System Conservation Proposal to protect the Colorado River Basin . US Department of the Interior, May 22, 2023. https://www.doi.gov/pressreleases/biden-harris-administration-announces-historic-consensus-system-conservation-proposal .

Wheeler, K. G. et al. What will it take to stabilize the Colorado River? Science 377 , 373–375 (2022).

Article   ADS   CAS   PubMed   Google Scholar  

Richter, B. D. Decoupling urban water use from population growth in the Colorado River Basin. J. Water Plan. Manag. 149 , 2 (2023).

Google Scholar  

Schmidt, J. C. Maps Matter: A few suggested changes to the Colorado River basin base map . Center for Colorado River Studies. (Utah State University, 2022).

Woodward, B. D. et al. Co-Rip: A riparian vegetation and corridor extent dataset for Colorado river basin streams and rivers. ISPRS Int. J. Geo Inform. 7 , 397 (2018).

Article   ADS   Google Scholar  

Lower Colorado River Annual Summaries of Evapotranspiration and Evaporation . (US Bureau of Reclamation, Lower Colorado Region, 2023). https://www.usbr.gov/lc/region/g4000/wtracct.html .

Richter, B. D., Powell, E. M., Lystash, T. & Faggert, M. Protection and restoration of freshwater ecosystems. Chapter 5 in Miller, Kathleen A., Alan F. Hamlet, Douglas S. Kenney, and Kelly T. Redmond (Eds.) Water Policy and Planning in a Variable and Changing Climate . (CRC Press - Taylor & Francis Group, 2016).

Shao, Elena. “The Colorado River is shrinking. See what’s using all the water.” New York Times , May 22, 2023. https://www.nytimes.com/interactive/2023/05/22/climate/colorado-river-water.html .

Richter, B. D., et al. Alleviating water scarcity by optimizing crop mixes. Nat. Water . https://doi.org/10.1038/s44221-023-00155-9 .

Njuki, E. U.S. dairy productivity increased faster in large farms and across southwestern states . U.S. Economic Research Service, US Department of Agriculture, March 22, 2022. https://www.ers.usda.gov/amber-waves/2022/march/u-s-dairy-productivity-increased-faster-in-large-farms-and-across-southwestern-states/ .

Mefford, B. & Prairie J., eds. Assessing Agricultural Consumptive Use in the Upper Colorado River Basin - Phase III Report U.S. Bureau of Reclamation and the Upper Colorado River Commission. http://www.ucrcommission.com/reports-studies/ (2022).

Upper Basin Consumptive Uses and Losses (Bureau of Reclamation). Annual reports available at https://www.usbr.gov/uc/envdocs/plans.html .

Bureau of Reclamation. “Consumptive Uses and Losses spreadsheet 1971–2020” Colorado River Basin Natural Flow and Salt Data, Supporting data for consumptive uses and losses computation. https://www.usbr.gov/lc/region/g4000/NaturalFlow/documentation.html .

Upper Colorado River Basin Consumptive Uses and Losses Report 2016–2020 . US Department of Interior: Bureau of Reclamation. Five year reports available under “Colorado River-Consumptive Uses and Losses Reports” at https://www.usbr.gov/uc/envdocs/plans.html .

Estimated Use of Water in the United States . US Department of Interior: US Geological Survey. Reports available every five years at https://www.usgs.gov/mission-areas/water-resources/science/water-use-united-states .

Jasechko, S. et al. Widespread potential loss of streamflow into underlying aquifers across the USA. Nature 591 , 391–395 (2021).

Wiele, S. M., Leake, S. A., Owen-Joyce, S. J. & and McGuire, E. H. Update of the Accounting Surface Along the Lower Colorado River US Department of the Interior: US Geological Survey Scientific Investigations Report 2008–5113 (2008).

Bruce, B. W., et al. Comparison of U.S. Geological Survey and Bureau of Reclamation water-use reporting in the Colorado River Basin U.S. Geological Survey Scientific Investigations Report 2018–5021 . https://doi.org/10.3133/sir20185021 (2018).

Siddik, M. A. B., Dickson, K. E., Rising, J., Ruddell, B. L. & Marston, L. T. Interbasin water transfers in the United States and Canada. Sci. Data 10 , 27 (2023). Data spreadsheet provided by M.A.B. Siddik.

Article   PubMed   PubMed Central   Google Scholar  

Active Management Areas : AMA Annual Supply and Demand Dashboard (Arizona Department of Water Resources, 2023). https://azwater.gov/ama/ama-data .

Lacroix, K. M. et al. Wet water and paper water in the Upper Gila River Watershed https://extension.arizona.edu/sites/extension.arizona.edu/files/pubs/az1708-2016_0.pdf The University of Arizona Cooperative Extension, AZ1708. Data spreadsheet provided by A. Hullinger (2016).

Surface-Water Annual Statistics for the Nation: Gila River at Dome, Arizona . US Geological Survey. Available at https://waterdata.usgs.gov/nwis/annual/?referred_module=sw&site_no=09520500&por_09520500_5810=19975,00060,5810,1905,2024&year_type=C&format=html_table&date_format=YYYY-MM-DD&rdb_compression=file&submitted_form=parameter_selection_list .

Consumptive Uses and Losses spreadsheet 1971–2020 . Bureau of Reclamation, Colorado River Basin Natural Flow and Salt Data, Supporting data for consumptive uses and losses computation. https://www.usbr.gov/lc/region/g4000/NaturalFlow/documentation.html .

HydroData: Reservoir Data . US Bureau of Reclamation. https://www.usbr.gov/uc/water/ .

Myers, T. Loss rates from Lake Powell and their impact on management of the Colorado River. J. Am. Water Resour. Assoc. 49 , 1213–1224 (2013).

Melton, F. S. et al. OpenET: filling a critical data gap in water management for the western United States. J. Am. Water Resour. Assoc. 58 , 971–994 (2022).

Abatzoglou, J. T. Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol. 33 , 121–131 (2013).

Salton Sea Management Program: Long-Range Plan Public Draft (2022). California Natural Resources Agency. https://saltonsea.ca.gov/wp-content/uploads/2022/12/Salton-Sea-Long-Range-Plan-Public-Draft-Dec-2022.pdf .

Foster, T. et al. AquaCrop-OS: an open source version of FAO’s crop water productivity model. Agricul. Water Manag. 181 , 18–22 (2017).

Marston, L. T., et al. Reducing water scarcity by improving water productivity in the United States. Environ. Res. Lett. 15 https://doi.org/10.1088/1748-9326/ab9d39 (2020).

Steduto, P., Hsiao, T. C., Fereres, E. & Raes, D. Crop yield response to water (2012). 1028. Rome: Food and Agriculture Organization of the United Nations.

USDA, National Agricultural Statistics Service. “Quick Stats.” http://quickstats.nass.usda.gov .

Allen, R. G., Pereira, L. S., Raes, D. & Smith, M. FAO Irrigation and drainage paper No. 56 56, (e156. Food and Agriculture Organization of the United Nations, Rome, 1998).

Orange, M. N., Scott Matyac, J. & Snyder, R. L. Consumptive use program (CUP) model. IV Int. Symp. Irrig. Horticult. Crops 664 , 461–468 (2003).

Hengl, T. et al. SoilGrids250m: Global gridded soil information based on machine learning. PLoS One 12 , e0169748 (2017).

Hoekstra, A. Y. Green-blue water accounting in a soil water balance. Adv. Water Resour. 129 , 112–117 (2019).

USDA (US Department of Agriculture). A Method for Estimating Volume and Rate of Runoff in Small Watersheds . SCS-TP-149. Washington DC: Soil Conservation Service (1968).

Johnson, D. M., & Mueller, R. 2010. “Cropland Data Layer.” https://nassgeodata.gmu.edu/CropScape/ .

Xie, Y., Gibbs, H. K. & Lark, T. J. Landsat-based Irrigation Dataset (LANID): 30m resolution maps of irrigation distribution, frequency, and change for the US, 1997–2017. Earth Syst. Sci. Data 13 , 5689–5710 (2021).

Sohl, T. et al. Modeled historical land use and land cover for the conterminous United States. J. Land Use Sci. 11 , 476–499 (2016).

Download references

Acknowledgements

This paper is dedicated to our colleague Jack Schmidt in recognition of his retirement and enormous contributions to the science and management of the Colorado River. The authors thank James Prairie of the US Bureau of Reclamation, Luke Shawcross of the Northern Colorado Water Conservancy District, Charlie Ester of the Salt River Project, and Brian Woodward of the University of California Cooperative Extension for their assistance in accessing data used in this study. The authors also thank Rhett Larson at the Sandra Day O’Connor School of Law at Arizona State University for their review of Arizona water budget data, and the Central Arizona Project for providing delivery data by each subcontract. G.L., L.M., and K.F.D. acknowledge support by the United States Department of Agriculture National Institute of Food and Agriculture grant 2022-67019-37180. L.T.M. acknowledges the support the National Science Foundation grant CBET-2144169 and the Foundation for Food and Agriculture Research Grant No. FF-NIA19-0000000084. R.R.R. acknowledges the support the National Science Foundation grant CBET-2115169.

Author information

Authors and affiliations.

World Wildlife Fund, 1250 24th St NW, Washington, DC, 20037, USA

Brian D. Richter

Sustainable Waters, Crozet, Virginia, 22932, USA

The Charles E.Via, Jr, Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, 24061, USA

Gambhir Lamsal, Landon Marston & Sameer Dhakal

Northern Arizona University, Flagstaff, AZ, 86011, USA

Laljeet Singh Sangha, Richard R. Rushforth & Benjamin L. Ruddell

Department of Geography and Spatial Sciences, University of Delaware, Newark, DE, 19716, USA

Dongyang Wei & Kyle Frankel Davis

Department of Plant and Soil Sciences, University of Delaware, Newark, DE, 19716, USA

Kyle Frankel Davis

Instituto de Investigaciones Oceanologicas, Universidad Autonoma de Baja California, Ensenada, Baja California, México

Astrid Hernandez-Cruz

Department of Land, Air and Water Resources, Univeristy of California at Davis, Davis, CA, 95616, USA

Samuel Sandoval-Solis

Center for Colorado River Studies, Utah State University, Logan, UT, 84322, USA

John C. Schmidt

You can also search for this author in PubMed   Google Scholar

Contributions

B.D.R. designed the study, compiled and analyzed data, wrote the manuscript and supervised co-author contributions. G.L. compiled all crop data, estimated crop evapotranspiration, and prepared figures. S.D. compiled all riparian vegetation data and estimated riparian evapotranspiration. L.S.S. and R.R.R. accessed, compiled, and analyzed data from the Central Arizona Project. D.W. compiled data and prepared figures. A.H.-C. and S.S.-S. compiled and analyzed data for Mexico. J.C.S. compiled and analyzed reservoir evaporation data and edited the manuscript. L.M., B.L.R., and K.F.D. supervised data compilation and analysis and edited the manuscript.

Corresponding author

Correspondence to Brian D. Richter .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Communications Earth & Environment thanks James Booker and Becky Bolinger for their contribution to the peer review of this work. Primary Handling Editors: Aliénor Lavergne and Carolina Ortiz Guerrero. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Peer review file, supplementary information, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Richter, B.D., Lamsal, G., Marston, L. et al. New water accounting reveals why the Colorado River no longer reaches the sea. Commun Earth Environ 5 , 134 (2024). https://doi.org/10.1038/s43247-024-01291-0

Download citation

Received : 03 October 2023

Accepted : 27 February 2024

Published : 28 March 2024

DOI : https://doi.org/10.1038/s43247-024-01291-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

2024 Global Climate Challenge

How Can we get rid from Waterlogging Problem in a City?

Sayed Huzaifa Mumit

Our Organization

What is the name of your solution, provide a one-line summary of your solution..

Production of Methane Gas from Rainwater and Carbon dioxide

In what city, town, or region is your solution team headquartered?

In what country is your solution team headquartered, what type of organization is your solution team.

Not registered as any organization

What specific problem are you solving?

When it rains in Bangladesh many city areas go underwater and waterlogging in the streets. These cities are situated on the riverside. The project was conducted to solve this problem and to get benefits from the environment. The procedure was Collecting rainwater samples in a flask or large area requires separating pure water vapor in a balloon or any alternative container. Reduced heat, analogous to condensation, causes it to form liquid water. Now, need to separate hydrogen gas from water using the best method of electrolysis at an affordable cost. The production of hydrogen gas is one of the final products that produces methane gas. Now, pure carbon dioxide needs to be collected from any source in a wolf bottle or any other alternative container, like a flask. Collected hydrogen gas and carbon dioxide need to be mixed in a bottle. Mixed gases are called water gases, and where they need to provide heat, therefore, they become methane gas, and as a side product, water vapor is also produced. But when products need to decrease heat, like condensation, then methane gas will separate. The final product will grow the country’s economy by exporting and meeting the needs of citizens.

What is your solution?

The environment will also be balanced if carbon dioxide emissions decrease. Produced Methane gas can be utilized in manufacturing to drive or power motors and turbines. The energy released is used by industries such as pulp and paper, food processors, petroleum refineries, and firms that work with stone, clay, and glass. Businesses may use methane-based combustion to dry, dehumidify, melt, and clean their products. It is also utilized to generate energy for illumination. Some other countries where yearlong wet places exist have a great chance to use them. This country can grow their economy and also meet their mineral needs. Some Places in many countries are Emei Shan, Sichuan Province, China Average annual rainfall: is 8169mm. Kukui, Maui, HawaiiAverage annual rainfall: 9293mm.Mt Waialeale, Kauai, Hawaii Average annual rainfall: 9763mm. Etc.[c.1] It was easy to collect samples. But the large area will require a cost. The product can be profitable after being exported outside of the country. Water also produces methane, s

water can be recycled while rainwater can’t be collected. In the street when water together to make the project profitable and directly or indirectly increase the quality of life of the people for whom it was conducted. Here the graph shows the previous four years of data on the waterlogging road of Chittagong city in percent. The red dot shows a blocked road by rainwater, and the green dot shows an unblocked road. Graph 2: Here Climate chart of Chittagong city[c.2] Some data on air pollution by carbon of Chittagong, Bangladesh: The mission inventory of Chittagong city is 20 X 32 km2, with the pivot point at 377374.00 mE and 2472510.00 mN and cell resolution of 1x1 km2.The whole Chittagong City Corporation region, as well as sections of the Sitakunda, Hathhazari, Raozan, BoalKhali, Patiya, and Anowara Upazilas, are included.[9]

Who does your solution serve, and in what ways will the solution impact their lives?

In Bangladesh, many cities and towns go underwater during the rainy season. Bangladesh has a value geographically; it has 6 seasons, of which 3 are mostly rainy. Chittagong and Dhaka have a common waterlogging problem due to all the canals containing trash and pollution. If using the method or experiment explained above, we collect rainwater, purify it, and then produce methane gas, it can meet the demand of certain areas where people live in middle-class families, and after meeting the demand, we can export it outside Bangladesh. The cost of production will be lower than the procurement cost of methane from minerals.

How are you and your team well-positioned to deliver this solution?

My team Will contact the government and after getting permission then will contact the Industries that emit CO2. To Capture CO2 there will be a contract. 

Then talking with the municipality mayor about collecting the rainwater from the street where waterlogged. 

Both will bring a Factory and Use the procedure of the research to produce methane gas and distribute it to the nation.

Which dimension of the Challenge does your solution most closely address?

Which of the un sustainable development goals does your solution address.

• 3. Good Health and Well-Being
• 6. Clean Water and Sanitation
• 7. Affordable and Clean Energy
• 8. Decent Work and Economic Growth
• 9. Industry, Innovation, and Infrastructure
• 11. Sustainable Cities and Communities
• 13. Climate Action

What is your solution’s stage of development?

Please share details about why you selected the stage above..

I have developed the Model for solving specific cities and environmental disasters.

Production of Methane Gas from Rainwater caused unwantedly fro Climate changes By Carbon dioxide Emission.

Why are you applying to Solve?

It has several answers, 

The growth of the economy by exporting, To get rid of the people of the city. CIlmate changes or the disasters of nature to get rid.To meet the demand of the people.

In which of the following areas do you most need partners or support?

• Product / Service Distribution (e.g. delivery, logistics, expanding client base)
• Technology (e.g. software or hardware, web development/design)

Who is the Team Lead for your solution?

Solution team.

The Solve team will review your report and remove any inappropriate content.

Why is this item inappropriate?

We use cookies.

We use cookies and other tracking technologies to improve your browsing experience on our website and to understand where our visitors are coming from. By browsing our website, you consent to our use of cookies and other tracking technologies.

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Causes and effects of water logging in Dhaka City, Bangladesh

2004, TRITA-LWR Master thesis, Department of Land and …

Related Papers

Mohammed Arifur Rahman

The rapidly growing urban population in metropolitan cities and its outskirts is increasing environmental pollution posing 'problems to human health and threatening the general quality of life. A desirable state of urbanization with the overriding considerations of communications, traffic system, and housing and residential patterns has been stressed upon recently by the urban planners. What the city dwellers expect from the city development authority is a well planned city with systematic clustering of houses in the residential area well connected to the city's main points-administrative and commercial districts-through linking roads accessible by transports.The study focues the problem of urbanization in Dhaka and Chittagong in respect of Environmental degradation stems from rural-urban migration from villages and small market towns with rural characteristics to the metropolitan urban centers full of development activities. All such development activities centering on urbanization come in disharmony with ecological factors leading to 'gradual degradation of life-support systems including air, water and land'. Enormous population pressure in the core of the city even downtowns aggravates situation. Drainage is poor. Most drains remain chocked. Flooding and water logging during rainy season very much trouble the pedestrians. Rain water with waste accumulates. resultantly roads, lanes and by-lanes become the 'pools of water'. 'Waste-water goes out through open drains which run along the roads.'

Md. Tanvir Alam

Research about population

SSRN Electronic Journal

Rezwanul Kabir

Rapid urbanization has been a boon for industrial growth in Bangladesh, leading the Dhaka megapolis to become one of the least livable places in the world. These circumstances, however, have received little attention by policy makers and in academic research. Using mainly secondary data, this article explores the water quality of the river Buriganga that flows across Dhaka and identifies major sources of pollutants. While much of the article analyzes the sources and extent of pollution, it also points toward a great threat to public health from the presence of high levels of heavy metals, such as chromium, lead, and iron, as well as chemicals, including ammonia and phosphate. Moreover, the article recommends some policy changes that could potentially reduce pollution levels and boost water sustainability not only in Dhaka but also in other fast-growing cities in the least developed countries (LDCs).

The paper discusses the Dwindling Urban Water-bodies of Dhaka and the resultant City Fabric. A historical review has been made to see the water urbanism in the past and the impact of the loss of wetlands and water bodies in Dhaka due to the pressure of unplanned urbanization. The study was carried out in the context of Metropolitan Development Area and Its Planning Problems, Issues and Policies.

Sushil K Das, PhD

Masrur Iqbal Maruf

Bangladesh is one of the most environmentally hazard countries and it will face serious environmental problems in near future. The environmental condition is degrading day after day and it is acute in urban area. Environmental degradation threatens all development endeavors. In the context of developing economics Bangladesh to faces a wide array of environmental problems which affect the wellbeing of its citizens. Bangladesh government, NGOs and civil society has taken some policies and programs to control the environmental problems but these efforts are not fruitful

Qazi Mowla , Mohammed Saiful Islam

Dhaka city faces extensive water logging during the monsoon (May to October) as a regular phenomenon due to fast and uncontrolled urbanization. This water logging is a problem creating adverse social, physical, economic and environmental impacts in the life and living in Dhaka. Disruption of traffic movement and normal life, damage of structures and infrastructure, destruction of vegetation and aquatic habitats, loss of income potentials are the prime effects of water logging.This paper focuses on the rainfall induced flooding that is caused by high intensity rainfall runoff in the city area, mainly due to the lack of proper drainage system and inefficient management. Urban design and planning, responsive to the geo-climate and hydrological characteristics of the place will help mitigate water logging problem in the city. A close coordination among urban authorities and collaboration between public and private sectors is needed for sustainable operation of the drainage system to minimize water logging in Dhaka.

RELATED PAPERS

International Journal of Pest Management

Muhammad Hidayat

Aletria: Revista de Estudos de Literatura

Emilie Combes

Scientific Papers of Silesian University of Technology. Organization and Management Series

Sylwia Jarosławska-Sobór

Denis Trierweiler

Procedia Engineering

Khadija Tahera

Acta Bot Bras

Maria de Fatima Agra

piotr markowski

MAY AL-DOORI

Parveen Kumar

CERMIN: Jurnal Penelitian

Aziza Rahmah

Slauga. Mokslas ir praktika

Romualdas Malinauskas

Papers on Joyce

Katarzyna Bazarnik

Titis Widias

Optics and Lasers in Engineering

Gyanendra Sheoran

Carlos Augusto De la Cruz Villanueva

Patrick LUSTENBERGER

Proceedings of the National Academy of Sciences

Kelly-Anne Twist

Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology

Subhrajit Pradhan

Revista Peruana De Quimica E Ingenieria Quimica

Leoncio Reyna

International Journal of Mineral Processing

Chandan Guria

Food Control

Snehal Shitole

Environmental Science: Processes & Impacts

Nicola Carslaw

Molecular neurodegeneration

Mathew Blurton-jones

Journal of the Science of Food and Agriculture

Jeff Wilson

Kapadokya Akademik Bakış

Mustafa Ünsalan

See More Documents Like This

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• canva icon Canvas
• Panther Mail (students)
• Arts & Film
• Business & Economy
• Campus & Students
• College Knowledge
• Health & Behavior
• Humanities & Society
• Science & Engineering
• University News
• Chapman Magazine
• Chapman Forward
• Maps & Directions
• Visit Chapman
• Discover Chapman
• Facts & Rankings
• Campus Services
• Degrees & Programs
• Schools & Colleges
• Academic Calendar
• Faculty Directory
• Course Catalogs
• International Study
• Undergraduate Admission
• Undergraduate Application
• Graduate Admission
• Graduate Application
• Affordability
• Financial Aid Calculator
• Campus Tours
• Get Involved
• Career Support
• Diversity & Inclusion
• Fish Interfaith Center
• Health & Safety
• Residence Life
• Student Life
• Pre-Award Administration
• Post-Award Administration
• Research Integrity
• Institutes & Centers
• Center for Undergraduate Excellence
• Graduate Research Support
• Contact Development
• Areas to Support
• Alumni Involvement
• Prospective Students
• Current Students
• Faculty & Staff
• Parents & Families
• All Directories

Common Loons Threatened by Declining Water Clarity

The Common Loon, an icon of the northern wilderness, is under threat from climate change due to reduced water clarity, according to a new study authored by Chapman University professor, Walter Piper .  The study , published April 1 in Ecology, followed up an earlier paper that showed substantial reproductive decline in the author’s study area in northern Wisconsin. 

The paper is the first clear evidence demonstrating an effect of climate change on this charismatic species. Specifically, the paper shows that July rainfall results in reduced July water clarity in loon territories. Reduced water clarity, in turn, makes it difficult for adult loons to find and capture their prey (mainly small fishes) under water, so they are not able to meet their chicks’ metabolic needs. The result is low chick weight and higher chick mortality. Since loons use the same foraging mode across their breeding range, the impact of water clarity on loon breeding success found in Wisconsin is likely to be echoed from Alaska to Iceland. 

Piper, in collaboration with Max Gline and Kevin Rose from Rensselaer Polytechnic Institute, reports several important findings. Over the past 25 years, there has been a consistent decline in water clarity. During the same period, body weights of adult males, adult females, and chicks have also declined. By searching among a large number of environmental variables, the authors were able to pinpoint mean water clarity during the month of July – the month of most rapid growth in chicks – as the strongest predictor of body weight. In a separate analysis, the authors found that rainfall in July impacts water clarity negatively. That is, heavy rainfall in July results in reduced water clarity, whereas light rainfall leads to high clarity and good foraging conditions for loons. Consequently, the rise in rainfall observed in recent decades, attributed to climate change, poses challenges for adult loons in feeding their offspring and diminishes chick survival rates.

The precise way in which rainfall leads to reduced water clarity is currently under investigation. The authors suggest that rain might carry dissolved organic matter (DOM) into lakes from adjacent streams and shoreline areas. But it is also possible that nutrients (such as fertilizers used on lawns by lake residents), pet waste, or even leaks from septic systems might be to blame.

This study represents a unique partnership between diverse fields. Piper’s three-decade-long study of loon behavioral ecology in northern Wisconsin intersects with Gline and Rose’s use of Landsat imagery to calculate freshwater lake clarity. Combining data from these sources has illuminated the cause behind the sharp decline in breeding success in northern Wisconsin. It is now evident that both the loss of water clarity – as well as increasing populations of black flies, which have increased due to greater rainfall – are to blame for the population downturn.

“Few animals on Earth are at once so beloved and so poorly understood as Common Loons”, Piper said. “This partnership between a loon behaviorist and lake ecologists who collect satellite data on water clarity has given us a unique and powerful window onto foraging efficiency and the loon population as a whole that might help us conserve the species.”

Piper is in the process of establishing a second marked study population of loons, equal in size to the first, in Minnesota. There he will determine whether the recent decline in loon breeding success recorded by the Minnesota Department of Natural Resources results from a loss of water clarity, as in Wisconsin. 

About Chapman University

Founded in 1861, Chapman University is a nationally ranked private university in Orange, California, about 30 miles south of Los Angeles. Chapman serves nearly 10,000 undergraduate and graduate students, with a 12:1 student-to-faculty ratio. Students can choose from 123 areas of study within 11 colleges for a personalized education. Chapman is categorized by the Carnegie Classification as an R2 “high research activity” institution. Students at Chapman learn directly from distinguished world-class faculty including Nobel Prize winners, MacArthur fellows, published authors and Academy Award winners. The campus has produced a Rhodes Scholar, been named a top producer of Fulbright Scholars and hosts a chapter of Phi Beta Kappa, the nation’s oldest and most prestigious honor society. Chapman also includes the Harry and Diane Rinker Health Science Campus in Irvine. The university features the No. 4 film school and No. 60 business school in the U.S. Learn more about Chapman University: www.chapman.edu .

Media Contact: Carly Murphy, Public Relations Coordinator | [email protected] | Desk: 714-289-3196 | Mobile: 714-497-9683

Carly Murphy

Media Contacts

Newsroom site, chapman site, services & policies.

© 2023 Chapman University

• Arts & Film
• Business & Economy
• Campus & Students
• Health & Behavior
• Humanities & Society
• Science & Engineering

Your Header Sidebar area is currently empty. Hurry up and add some widgets .

• Environment

Sea levels are rising but parts of Florida are also sinking, research shows

• Alex Harris Miami Herald staff writer

MIAMI — In South Florida, sea levels have already risen several inches since the start of the century and could be around 6 feet higher by 2100. But another factor could be making those sunny day floods in South Florida worse: We’re sinking.

Well, only a little bit. And only in some places. That’s according to new and old research on the phenomena of sinking land — also known as subsidence — along the entire U.S. coast.

New research published in the journal Nature on March 6 showed the potential risk of a one-two combo of sinking land and rising seas to cities along the coast, and Miami topped the list as a location that could see quite a bit of flooded property by mid-century.

The paper, led by researchers at Virginia Tech, suggested that Miami could have around 80,000 properties flooding by mid-century, a multibillion-dollar risk, due to the combination of sinking land and rising seas.

Associate Professor Manoochehr Shirzaei at Virginia Tech’s Earth Observation and Innovation Lab, co-author of the study, said he believes cities aren’t taking the slipping elevation of their coastal land as seriously as they take sea level rise.

“The coastal hazard through 2050 is more likely driven by land subsidence than sea level rise, and this has to come across very clearly in every sea rise strategy,” he said. “I’m confident in this moment in most places, this is not the case.”

Subsidence is caused by several things, from glaciers moving or melting in the North Pole to overpumping oil, gas and groundwater, or, in South Florida’s case, compacting soil.

While the nationwide maps make clear that the real problem area for subsidence is in the Gulf Coast, specifically in places like Louisiana, Shirzaei said South Florida should still be paying attention to the future risk.

Specifically, he said, on the glitzy, expensive island communities that ring the coast of the Sunshine State.

“You do have some of the famous barrier islands. All of them are sinking,” he said.

How South Florida stacks up

Local research into subsidence in South Florida has found that yes, indeed, there are spots along the coast that are lower than they were decades ago. That’s especially true on barrier islands, said Shimon Wdowinski, a geophysics professor at Florida International University who has published several papers on subsidence.

But it’s only a minuscule amount.

His 2020 paper compared Miami Beach to Norfolk, Virginia, and found that Miami Beach experienced very little subsidence overall. It also happens in small patches, typically around new construction. In that paper, he noted that the Champlain Towers condominium building in Surfside sank at a rank of 2 millimeters a year from 1993 to 1997 — about the width of two credit cards stacked on top of each other.

His research, released before the tragic 2021 collapse, initially led some to believe that sinking earth could have played a role in the disaster, but the investigation has so far not pointed to land change as a culprit.

Keep up with Tampa Bay’s top headlines

Subscribe to our free DayStarter newsletter

You’re all signed up!

Want more of our free, weekly newsletters in your inbox? Let’s get started.

Wdowinski said that his research suggests that land subsidence is mostly localized to the space of a single building in South Florida, and it’s by design. Heavy buildings compact the soil, so good engineers design buildings with the knowledge that they will slowly settle over a long period of time.

And that’s not just because of South Florida’s dirt. It can be what’s underneath, too. When barrier islands like Miami Beach were first built or expanded, it was common practice to mow down trees and mangroves and use those cuttings to expand the island. Decades later, those trees have rotted, sinking the earth down a bit.

“In southeast Florida, we have mostly localized subsidence, which is associated with construction of new buildings,” Wdowinski said. “The weight of the building is actually pushing down, and if you have the proper foundation it should be fine.”

The problem comes when one side of the building sinks faster or further than another side, potentially straining the building’s foundation or the pipes underneath.

That is, unless the seas are rising.

South Florida is already a low-lying place, so millimeters matter here. Continued subsidence, paired with rising seas, rising groundwater levels and more intense rainstorms could leave South Florida at risk of more frequent and more intense floods.

That’s why Wdowinski is pursuing more grants and more research into the phenomenon all across the state. While he’s confident that sinking is a bigger problem on the Gulf Coast — including Florida’s west coast — he noted that all information is important when it comes to planning for climate change.

“It’s a factor. It’s not the most important one. But still, if we can get a better grip on that it would be helpful,” he said.

©2024 Miami Herald. Visit miamiherald.com . Distributed by Tribune Content Agency, LLC.

Alex Harris covers climate change for the Miami Herald, including how South Florida communities are adapting to the warming world. She attended the University of Florida.

MORE FOR YOU

• Advertisement

ONLY AVAILABLE FOR SUBSCRIBERS

The Tampa Bay Times e-Newspaper is a digital replica of the printed paper seven days a week that is available to read on desktop, mobile, and our app for subscribers only. To enjoy the e-Newspaper every day, please subscribe.