Search Results (25)

Inundation dynamics in low-lying deltas are becoming increasingly important to monitor due to the impacts of climate change and human alterations to hydrological systems, which disrupt natural inundation patterns. In the Nemunas River Delta, where seasonal and extreme floods impact agricultural and natural landscapes, we used Sentinel-1 synthetic aperture radar (SAR) imagery (2015–2019), validated with drone data, to map flood extents. SAR provides consistent, 10 m resolution data unaffected by cloud cover, while drone imagery provides high-resolution (10 cm) data at 90 m flight height for validation during SAR acquisitions. Results revealed peak inundation during spring snowmelt and colder months, with shorter, rainfall-driven summer floods. Approximately 60% of inundated areas were low-lying agricultural fields, which experienced prolonged waterlogging due to poor drainage and soil degradation. Inundation duration was shaped by lithology, land cover, and topography. A consistent 5–10-day lag between peak river discharge and flood expansion suggests discharge data can complement SAR when imagery is unavailable. This study confirms SAR’s value for flood mapping in cloud-prone, temperate regions and highlights its scalability for monitoring flood-prone deltas where agriculture and infrastructure face increasing climate-related risks. Full article

Urban metro systems (UMSs) primarily consist of underground structures and are therefore highly susceptible to disasters, such as rainstorms and waterlogging. The damages caused by such events are often substantial and difficult to recover from, highlighting the urgent need to enhance the resilience of metro networks against waterlogging. Based on the principles of urban hydrology, this paper constructs scenarios to analyze the risk of waterlogging under varying rainstorm recurrence intervals and intensities. The ArcGIS geographic information system was employed to improve the existing passive inundation algorithm, enabling more accurate identification of flood-prone areas during heavy rainfall, which supports the topological modeling of UMSs. Structural connectivity was used as an external indicator of network resilience, and tools such as Gephi and NetworkX were applied to evaluate network performance. Using the Nanjing Metro as a case study, the resilience of the UMS under different risk scenarios was assessed by analyzing the impact of waterlogging events. Subsequently, recovery sequences following disruptions were prioritized to optimize post-disaster restoration, and targeted strategies for improving network resilience were proposed. The calculation results indicate that the overall resilience of the Nanjing UMS network is at a relatively high level. When connectivity is used as the performance indicator, the operating network resilience value is between 0.78 and 0.952, while the planned network resilience value is between 0.887 and 0.939. Full article

With the acceleration of urbanization and due to the impact of climate warming, economic losses caused by urban waterlogging have become increasingly severe. To reduce urban waterlogging losses under the constraints of limited economic and time resources, it is essential to identify key waterlogging-prone areas for focused governance. Previous studies have often overlooked the spatial heterogeneity in the distribution of value and risk. Therefore, identifying the spatial distribution of land value and risk, and analyzing their spatial overlay effects, is crucial. This study constructs a “Waterlogging-Value-Loss” spatial analysis framework based on the hydrological and value attributes of land use. By developing a 1D–2D coupled hydrodynamic model, the study determines waterlogging risk distributions for different return periods. Combining these results with disaster loss curves, it evaluates land-use values and employs the bivariate local Moran’s I index to comprehensively assess waterlogging risk and land value, thereby identifying key areas. Finally, the SHAP method is used to quantify the contribution of water depth and value to waterlogging losses, and a Birch-K-means combined clustering algorithm is applied to identify dominant factors at the street scale. Using the central urban area of Beijing as a case study, the results reveal significant spatial heterogeneity in the distribution of urban waterlogging risks and values. Compared to traditional assessment methods that only consider waterlogging risk, the bivariate spatial correlation analysis method places greater emphasis on high-value areas, while reducing excessive attention to low-value, high-risk areas, significantly improving the accuracy of identifying key waterlogging-prone areas. Furthermore, the Birch-K-means combined clustering algorithm classifies streets into three types based on dominant factors of loss: water depth-dominated (W), value-dominated (V), and combined-dominated (WV). The study finds that as the return period increases, the dominant factors for 22.23% of streets change, with the proportion of W-type streets rising from 29% to 38%. This study provides a novel analytical framework that enhances the precision of urban flood prevention and disaster mitigation efforts. It helps decision-makers formulate more effective measures to prevent and reduce urban waterlogging disasters. Full article

With the intensification of global climate change and urbanization, extreme rainfall and urban flooding have become increasingly frequent, making the flood tolerance of garden plants a key issue in urban landscaping and ecology. Identifying research progress and development trends in the waterlogging tolerance of garden plants, as well as selecting waterlogging-tolerant species, is a core strategy for advancing urban ecological development. This study employed the Web of Science database to conduct a systematic search using subject, title, and keyword criteria. After excluding irrelevant studies through full-text reviews, 164 articles were selected. Using bibliometric analysis, the research systematically reviewed relevant literature published over the past 21 years on waterlogging tolerance in landscape plants, both domestically and internationally, analyzing research trends and hotspots, while summarizing the physiological and molecular responses of garden plants in flood-prone environments. The research indicates significant differences in flood tolerance among different species of garden plants. The main research directions include morphology, physiology, molecular biology, ecology, cultivation, and species selection, with molecular biology emerging as a key area of development in recent years. Furthermore, in the context of global climate change, this study identifies 50 flood-tolerant plants with high ecological value, and proposes guidelines for selecting flood-tolerant species. It concludes by discussing future research directions in flood tolerance and the potential applications of these plants in urban landscaping, sponge city construction, and ecological restoration. Full article

To enhance the scientific and accurate assessment methods for urban waterlogging risk in City B and to promote sustainable urban development, this paper conducts a detailed evaluation of waterlogging risk from three dimensions: pedestrian safety, road traffic, and waterlogging-prone areas. After considering existing monitoring technologies and the constructed waterlogging model, the paper identifies standing water depth, standing water duration, and standing water velocity as the key indicators for waterlogging risk assessment and utilizes scenario simulation methods to evaluate waterlogging risk across these dimensions. Additionally, the paper employs boundary conditions of 2-h short-duration rainfall with a 5-year return period and 24-h long-duration rainfall with a 50-year return period for the assessment. The evaluation results indicate that, for pedestrian safety, under both short and long-duration rainfall conditions, low-risk areas represent the largest proportion of risk areas, reaching 6.36% and 10.83% of the total area, respectively. In the road traffic assessment, the proportions of severely congested roads under short- and long-duration rainfall conditions are 27.06% and 57.15%, respectively. In the evaluation of waterlogging-prone areas, high-risk areas account for the largest proportion of risk areas under both short- and long-duration rainfall conditions, reaching 0.64% and 1.42% of the total area, respectively. Full article

Herbaceous peony (Paeonia lactiflora Pall) is resistant to drought but not waterlogging. The main production areas of peony are prone to waterlogging, seriously affecting the growth and development of herbaceous peony. Polyamines have been observed to significantly enhance the ability of plants to defend and repair adverse damage and affect the synthesis and accumulation of the endogenous growth hormones indole-3-acetic acid (IAA) and abscisic acid (ABA). In this study, two herbaceous peony varieties (‘Lihong’, ‘Qihualushuang’) with different waterlogging tolerances were selected for artificial simulated waterlogging treatment to observe their morphological indexes and to determine their endogenous polyamine and hormone contents. Simultaneously, transcriptome sequencing and bioinformatics analysis were performed, focusing on screening differentially expressed genes in the polyamine metabolism pathway. The results showed that flood-tolerant varieties of herbaceous peony respond to waterlogging stress by continuously synthesizing spermidine (Spd) and spermine (Spm) through putrescine (Put) to counteract adversity. In the waterlogging-intolerant varieties, the expression of polyamine oxidase-related genes was annotated; their response to waterlogging stress was the simultaneous degradation of Spm and Spd to Put in the process of synthesis, and a decrease in the accumulation of Spm and Spd led to the early appearance of the symptoms of damage. In addition, polyamines influence key hormones that respond to plant adversity (IAA; ABA). The objective of this work was to initially analyze the mechanism of the polyamine signaling pathway in response to flooding in herbaceous peonies for further in-depth research on the mechanism of flooding tolerance in herbaceous peony, screen flood-tolerant varieties, and promote of their use. Full article

Extreme precipitation and flooding frequency associated with global climate change are expected to increase worldwide, with major consequences in floodplains and areas susceptible to flooding. The purpose of this review was to examine the effects of flooding events on changes in soil properties and their consequences on agricultural production. Flooding is caused by natural and anthropogenic factors, and their effects can be amplified by interactions between rainfall and catchments. Flooding impacts soil structure and aggregation by altering the resistance of soil to slaking, which occurs when aggregates are not strong enough to withstand internal stresses caused by rapid water uptake. The disruption of soil aggregates can enhance soil erosion and sediment transport during flooding events and contribute to the sedimentation of water bodies and the degradation of aquatic ecosystems. Total precipitation, flood discharge, and total water are the main factors controlling suspended mineral-associated organic matter, dissolved organic matter, and particulate organic matter loads. Studies conducted in paddy rice cultivation show that flooded and reduced conditions neutralize soil pH but changes in pH are reversible upon draining the soil. In flooded soil, changes in nitrogen cycling are linked to decreases in oxygen, the accumulation of ammonium, and the volatilization of ammonia. Ammonium is the primary form of dissolved inorganic nitrogen in sediment porewaters. In floodplains, nitrate removal can be enhanced by high denitrification when intermittent flooding provides the necessary anaerobic conditions. In flooded soils, the reductive dissolution of minerals can release phosphorus (P) into the soil solution. Phosphorus can be mobilized during flood events, leading to increased availability during the first weeks of waterlogging, but this availability generally decreases with time. Rainstorms can promote the subsurface transport of P-enriched soil particles, and colloidal P can account for up to 64% of total P in tile drainage water. Anaerobic microorganisms prevailing in flooded soil utilize alternate electron acceptors, such as nitrate, sulfate, and carbon dioxide, for energy production and organic matter decomposition. Anaerobic metabolism leads to the production of fermentation by-products, such as organic acids, methane, and hydrogen sulfide, influencing soil pH, redox potential, and nutrient availability. Soil enzyme activity and the presence of various microbial groups, including Gram+ and Gram− bacteria and mycorrhizal fungi, are affected by flooding. Waterlogging decreases the activity of β-glucosidase and acid phosphomonoesterase but increases N-acetyl-β-glucosaminidase in soil. Since these enzymes control the hydrolysis of cellulose, phosphomonoesters, and chitin, soil moisture content can impact the direction and magnitude of nutrient release and availability. The supply of oxygen to submerged plants is limited because its diffusion in water is extremely low, and this impacts mitochondrial respiration in flooded plant tissues. Fermentation is the only viable pathway for energy production in flooded plants, which, under prolonged waterlogging conditions, is inefficient and results in plant death. Seed germination is also impaired under flooding stress due to decreased sugar and phytohormone biosynthesis. The sensitivity of different crops to waterlogging varies significantly across growth stages. Mitigation and adaptation strategies, essential to the management of flooding impacts on agriculture, enhance resilience to climate change through improved drainage and water management practices, soil amendments and rehabilitation techniques, best management practices, such as zero tillage and cover crops, and the development of flood-tolerant crop varieties. Technological advances play a crucial role in assessing flooding dynamics and impacts on crop production in agricultural landscapes. This review embarks on a comprehensive journey through existing research to unravel the intricate interplay between flooding events, agricultural soil, crop production, and the environment. We also synthesize available knowledge to address critical gaps in understanding, identify methodological challenges, and propose future research directions. Full article

The drainage capacity of stormwater inlets, which serve as the connection between the surface and the underground drainage system, directly affects surface runoff and the drainage capacity of underground drainage systems. However, in reality, stormwater inlets are often blocked due to the accumulation of leaves, human waste disposal and other factors, resulting in a greatly reduced drainage capacity of the drainage network and, in turn, urban waterlogging disasters. In view of the problem of stormwater inlet blockage, employing a typical waterlogging point in the Lianjiang Middle Road area of Fuzhou city as the research object, the stormwater inlet equivalent drainage method was adopted in this paper to characterize the drainage capacity of the pipe network and enable the control of the stormwater inlet blockage state. Coupled with the stormwater inlet drainage equation, an improved ITF-FLOOD two-dimensional hydrodynamic model was constructed, and the influence of stormwater inlet blockage on urban waterlogging under different rainfall return periods was simulated and analyzed. With increasing rainfall return period, the influences of stormwater inlet blockage on both the maximum area and the depth of accumulated water in the study area gradually decreased compared with those of a nonblocked stormwater inlet, and the growth proportions decreased from 43.35% and 34.58% under the 1-year rainfall scenario to 3.34% and 9.76% under the 50-year rainfall scenario, respectively. However, in terms of the change in the accumulated water level, stormwater inlet blockage will cause an increase, and the influence will always be significant. Overall, stormwater inlet blockage aggravated the waterlogging risk and the extent of waterlogging. Therefore, the results provided a reference for the construction of an urban waterlogging model and have certain guiding significance for waterlogging prevention and control in the study area prone to stormwater inlet blockage. Full article

Τhe production of fresh fruit as well as olive orchards is increasing around the world, in order to meet the global demand for both fruits and olive products. This results in the spread and establishment of fruit and olive tree cultivation in areas where they were not found before, for example, plains and lowlands prone to waterlogging. Climate change is having a significant impact on the natural environment. Agricultural open-field crops have less growth and yield under these harsh weather conditions. Nowadays, unpredictable rainfall more often exposes field crops to waterlogging on a regular basis. This is a very stressful factor which can cause a reduction in yield and even total crop elimination. In this review, the morphological and physiological parameters affected by waterlogging are developed in order to understand better how olive and other fruit crops respond to waterlogging conditions and how this affects their development and productivity. Having a better understanding of these mechanisms can help us design strategies and approaches to increase fruit crop resistance to waterlogging stress. Full article

Climate change requires the introduction of alternative crops in certain temperate areas due to the warmer and drier growing seasons. Maize, one of the most important crops, is projected to become less tolerant of a drier climate. Therefore, it is necessary to find an alternative species that is less susceptible to environmental stressors. This study compared the germination, growth vigour, and stress tolerance of maize and sorghum grow in six types of soil under three water regimes. The results indicate that sorghum germination is faster and more uniform. The most significant differences in germination rates were found in chernozem (88.9% and 72.2% for sorghum and maize, respectively) and saline solonetz (74.4% and 63.3% for sorghum and maize, respectively). Maize exhibited higher growth vigour only in three cases, i.e., under solonetz–flooding, shifting sand–drought, and brown forest floor–flooding conditions. An ANOVA showed a significant difference between sorghum and maize stress conditions due to soil conditions and water availability (p < 0.0001). Sorghum can be a suitable alternative to maize, but only in areas with hot, dry periods and in areas where the soil is not too prone to waterlogging, regardless of its quality. Full article

The development of an accurate root water-uptake model is pivotal for evaluating crop evapotranspiration; understanding the combined effect of drought and waterlogging stresses; and optimizing water use efficiency, namely, crop yield [kg/ha] per unit of ET [mm]. Existing models often lack quantitative approaches to depicting crop root water uptake in scenarios of concurrent drought and waterlogging moisture stresses. Addressing this as our objective; we modified the Feddes root water-uptake model by revising the soil water potential response threshold and by introducing a novel method to calculate root water-uptake rates under simultaneous drought and waterlogging stresses. Then, we incorporated a water stress lag effect coefficient, $\phi \left(W_s\right)$, that investigated the combined effect of historical drought and waterlogging stress events based on the assumption that the normalized influence weight of each past stress event decreases with an increase in the time interval before simulation as an exponential function of the decay rate. Further, we tested the model parameters and validated the results obtained with the modified model using data from three years (2016–2018) of rice (Oryza sativa, L) trails with pots in Bengbu, China. The modified Feddes model significantly improved precision by 9.6% on average when calculating relative transpiration rates, particularly post-stress recovery, and by 5.8% on average when simulating soil moisture fluctuations during drought periods. The root mean square error of relative transpiration was reduced by 60.8%, and soil water was reduced by 55.1%. By accounting for both the accumulated impact of past moisture stress and current moisture conditions in rice fields, the modified model will be useful in quantifying rice transpiration and rice water use efficiency in drought–waterlogging-prone areas in southern China. Full article

Polders are low-lying areas located in deltas, surrounded by embankments to prevent flooding (river or tidal floods). They rely on pumping systems to remove water from the inner rivers (artificial rivers inside the polder area) to the outer rivers, especially during storms. Urbanized polders are especially vulnerable to pluvial flooding if the drainage, storage, and pumping capacity of the polder is inadequate. In this paper, a Monte Carlo (MC) framework is proposed to evaluate the benefits of rainfall threshold-based flood warnings when mitigating pluvial flooding in an urban flood-prone polder area based on 24 h forecasts. The framework computes metrics that give the potential waterlogging duration, maximum inundated area, and pump operation costs by considering the full range of potential storms. The benefits of flood warnings are evaluated by comparing the values of these metrics across different scenarios: the no-warning, perfect, deterministic, and probabilistic forecast scenarios. Probabilistic forecasts are represented using the concept of “predictive uncertainty” (PU). A polder area located in Nanjing was chosen for the case study. The results show a trade-off between the metrics that represent the waterlogging and the pumping costs, and that probabilistic forecasts of rainfall can considerably enhance these metrics. The results can be used to design a rainfall threshold-based flood early warning system (FEWS) for a polder area and/or evaluate its benefits. Full article

The objective of this study was to discern the spatial and temporal patterns of areas in Nanning that are susceptible to waterlogging, particularly during various phases of urban expansion. Furthermore, this study presents a proposal outlining strategies aimed at preventing and controlling waterlogging. These strategies are based on the integration of the concepts of sponge city and resilient city construction. This study employed remote sensing (RS) and geographic information system (GIS) techniques to provide technical support. The supervised classification method and normalized difference index method were utilized to compare and extract impervious surfaces in Nanning from 2013 to 2020. The present investigation utilized the acquired impervious surfaces to compute the fractal dimension as a weighting factor, incorporating a digital elevation model (DEM) for the purpose of conducting a hydrological analysis in ArcGIS. Based on the findings of the study, several conclusions can be derived. The following conclusions can be drawn from the study: (1) The fractal dimension of Nanning varied over the study period, with values of 1.32, 1.41, and 1.58 in 2013, 2017, and 2020, respectively. The distribution of impervious surfaces showed a decreasing trend from the city center to the periphery. Urban planning and construction activities have significantly influenced the distribution of impervious surfaces, resulting in a progressively more complex and unstable structure. (2) From 2013 to 2020, the urban expansion fractal dimension increased from 1.32 to 1.58, indicating a decrease in the stability of impervious surfaces. The areas with higher concentrations of impervious surfaces coincided with frequent waterlogging-prone areas. Furthermore, the distribution of waterlogging-prone points transformed from a concentrated pattern to a scattered one. (3) In terms of waterlogging prevention and control strategies, the old urban areas are recommended to be transformed into sponge city projects, and the new development areas are planned, designed and implemented with the concept of “resilience”. Full article

In humid climates, waterlogging from excessive rainfalls can be a major limiting factor for soybean production, particularly during the reproductive stage. However, there is a limited understanding of how soybean growth and physiology respond to waterlogging during this critical stage. Here, we investigated the effects of waterlogging and subsequent reoxygenation on the growth, physiology, yields, and leaf hyperspectral reflectance traits of the soybean cultivar ‘Asgrow AG5332’. The crop was grown to stage R1 (initial flowering) in outdoor pot culture conditions, and then waterlogged for 16 days. The flooded pots were drained and continuously monitored for recovery for an additional 16 days. The results showed that soil oxygen levels declined rapidly to zero in about 5 days after waterlogging, and slowly recovered in about 5–16 days. However, it did not reach the same level as the control plants, which maintained an oxygen concentration of 18%. Increasing waterlogging duration negatively affected leaf chlorophyll index, water potential, and stomatal conductance, with a consequent decline in the photosynthetic rate. Further, decreased photosynthetic rate, leaf area, and mineral nutrients resulted in lower biomass and seed yield. Pod dry weight and leaf number were the most and least sensitive parameters, respectively, decreasing by 81% and 15% after 16 days of waterlogging. Waterlogged plants also had higher reflectance in the PAR, blue, green, and red regions, and lower reflectance in the near-infrared, tissue, and water band regions, indicating changes in chemistry and pigment content. The current study reveals that the soybean crop is susceptible to waterlogging during the reproductive stage, due to poor recovery of soil oxygen levels and physiological parameters. Understanding and integrating the growth, physiology, and hyperspectral reflectance data from this study could be used to develop improved cultivars to ensure the stability of soybean production in waterlogging-prone areas. Full article

The reproductive stage of cotton (Gossypium sp.) is highly sensitive to waterlogging. The identification of potential elite upland cotton (Gossypium hirsutum) cultivar(s) having higher waterlogging tolerance is crucial to expanding cotton cultivation in the low-lying areas. The present study was designed to investigate the effect of waterlogging on the reproductive development of four elite upland cotton cultivars, namely, Rupali-1, CB-12, CB-13, and DM-3, against four waterlogging durations (e.g., 0, 3, 6, and 9-day). Waterlogging stress significantly impacted morpho-physiological, biochemical, and yield attributes of cotton. Two cotton cultivars, e.g., CB-12 and Rupali-1, showed the lowest reduction in plant height (6 and 9%, respectively) and boll weight (8 and 5%, respectively) at the highest waterlogging duration of 9 days. Physiological and biochemical data revealed that higher leaf chlorophyll, proline, and relative water contents, and lower malondialdehyde contents, particularly in CB-12 and Rupali-1, were positively correlated with yield. Notably, CB-12 and Rupali-1 had higher seed cotton weight (90.34 and 83.10 g, respectively), lint weight (40.12 and 39.32 g, respectively), and seed weight (49.47 and 43.78 g, respectively) per plant than CB-13 and DM-3 in response to the highest duration of waterlogging of 9 days. Moreover, extensive multivariate analyses like Spearman correlation and the principle component analysis revealed that CB-12 and Rupali-1 had greater coefficients in yield and physiological attributes at 9-day waterlogging, whereas CB-13 and DM-3 were sensitive cultivars in response to the same levels of waterlogging. Thus, CB-12 and Rupali-1 might be well adapted to the low-lying waterlogging-prone areas for high and sustained yield. Full article