Understanding the process of groundwater recharge is crucial for ensuring the availability of this dwindling resource. Indo-Gangetic Aquifer in the Ganga Plains is one of the largest and heavily oppressed aquifer systems in the world. The Upper Ganga Canal, which transports water in the Ganga Plain for irrigation (area: 2.0 × 106 ha), is key to the region’s groundwater recharge. However, no research

Precipitation is complex due to its significant temporal and spatial variability, and current mainstream precipitation estimation techniques have their inherent limitations. The complementary role of ground-based microwave radiometer in precipitation monitoring to these technologies is gaining increasing attention. Based on the physical characteristics of microwave radiation signals affected by raindrops

Convection-permitting regional climate models (CPRCMs) have been shown to improve the representation of extreme precipitation compared to coarser resolution regional climate models (RCMs). Their benefits for hydrological extremes, such as floods, remains uncertain. This study evaluates the performance of a 3-km resolution convection-permitting model (HCLIM3) against a coarser 12-km resolution climate

Quantifying connectivity patterns in dryland ecosystems enables us to understand how changes in the vegetation structure influence the runoff and erosion processes. This knowledge is crucial for mitigating the impacts of climate change and land use modifications. We quantify the multi-scale water-mediated connectivity within grassland and shrubland hillslopes using a weighted, directed network model

Obtaining accurate spatial information on soil organic matter (SOM) is crucial for understanding global carbon cycle. Digital soil mapping (DSM) has become an effective method for mapping SOM, in which selection of influential environmental covariates plays an important role. Soil moisture (SM) can serve as a potential covariate, especially it can be estimated at large spatial scales thanks to remote

Multispecies contaminant transport occurs frequently in groundwater systems. Currently, most solutions to multispecies transport problems do not consider parameter variability which has a determinant impact on concentration distribution. In this paper, a physics-informed neural network (PINN) containing a locally adaptive residual network and a probabilistic point selection strategy referred to as

With the impact of global climate change, floods triggered by extreme rainfall events seriously threaten the operation of urban systems in recent years. Real time and accurate urban flood inundation information is critical for disaster management and emergency response. With emergent technologies and citizen sensing, video image has become a core data source of urban system and exhibits great potential

Tidal asymmetry plays a crucial role in sediment transport and morphological evolution in estuarine environments. While there is more than one tidal asymmetry, their individual contributions to residual sediment transport remain insufficiently quantified. In this study, we introduce a multi-asymmetry approach, utilizing short-term field data to quantify the contributions of flood-ebb asymmetries in

Since the 1970s, human activities such as navigational projects, land reclamations, sand mining, and upstream damming have significantly impacted the geomorphology of Oujiang River Estuary (ORE). This study utilized bathymetric surveys, river discharge data, tide records, historical current velocity and suspended sediment concentration, and historical satellite imagery to investigate the geomorphological

Real-time error correction of flood forecasting is a key method for improving forecast accuracy. However, due to the rapid and unpredictable rise of flash flood discharge and the limited availability of analysis data on short temporal scales, developing robust forecast error correction methods remains a challenge. In this study, we employed a physically-based distributed hydrological model combined

This study evaluates the performance of different retention solutions in stormwater drainage systems. The outcome of this study proposes a method to determine the hydraulic efficiency of different stormwater drainage retention components, in which instead of assessing retention capacities, the resistance time is used. The study was conducted in a laboratory setting, involving four different hydraulic

The spatial heterogeneity and temporal dynamics under hydrological and hydrogeological conditions for the large endorheic river basins urgently need to implement spatiotemporal hydro-economic optimization for agricultural and environmental water demand. However, the current optimization lacks a comprehensive modeling framework that fully integrates the crop pattern with conjunctive use of surface water

The ever-increasing food demand globally exerts a pressing need to develop efficient water resource management to meet crop water requirements. While satellite remote sensing has proven invaluable for assessing basin-scale crop water conditions (CWC), foreseeable challenges still exist to evaluate field-scale water status in crop-intensive regions. In this study, we present a systematic framework to

Recent global shifts in climate have intensified variability in the hydrological cycle and heightened occurrences of extreme weather events. In arid regions, sporadic and intense rainfall often leads to extreme flash floods, posing serious risks to infrastructure, ecosystems, and public safety. This study investigates the frequency dynamics of rainstorm characteristics in arid and semi-arid climates

Rivers are vital for ecosystems, water resources, and sustaining life on Earth. Modeling pollutant transport in river networks is essential for reducing environmental contamination but classical numerical methods struggle with the complexities of these networks. This research introduces a novel Equation Oriented Modeling approach using open-source mathematical software to enhance flexibility, transparency

This article investigates sediment transport dynamics in the western Greater Caucasus region over the last 50 years, focusing on the Krasnodar Reservoir, the largest artificial reservoir in the Western Caucasus. Built between 1973 and 1975 on the Kuban River, the reservoir’s catchment has experienced significant hydrological and land-use alterations over the past several decades.

Blue-Green Infrastructure (BGI) is amongst the most promising solutions to urban pluvial flooding. Optimum siting of BGI for maximum efficiency based on demand–supply assessment is a challenging problem investigated by earlier researchers. However, risk-based demand assessments focus on system vulnerabilities and often overlook the inherent system capacity to absorb and adapt to floods. A more effective

Addressing the nitrogen geochemical cycle, accompanied with hydrological processes, influenced by anthropogenic nitrogen inputs provides new insights on policymaking for water resource management and aquatic ecosystems protection. However, there is currently a lack of further understanding on the source contributions of nitrate (NO3–) and transformations under explicit hydrological conditions. Due

Future urban flood risk is expected to accelerating rise, comprehensive prediction of future risk changes is essential for planning effective flood adaptation strategies in cities. However, current flood risk assessments have not integrated flood hazard, exposure, and vulnerability as a comprehensive flood risk score, and neglecting the combined impacts of climate change and urbanization. This study

Shallow groundwater discharge from unconfined aquifers is known to affect ocean carbon budget and ocean acidification. However, the role of deeper groundwater discharge from confined aquifers in ocean carbonate chemistry was previously overlooked. Here, we characterized dissolved inorganic carbon (DIC) and total alkalinity (TA) concentrations and estimated DIC and TA fluxes from confined aquifers (50 ∼ 520 m

The significant influence of hydro(bio)geochemical processes induced by organic matter (OM) on groundwater nitrogen contamination has been widely reported. However, the mechanisms controlling the heterogeneous distribution of this contamination as well as the impact of the biodegradability of OM on nitrogen species in sedimentary aquifers are not yet well understood. In the West Liao River Plain (WLRP)

Stable isotopic ratios of hydrogen and oxygen (i.e., δ2H and δ18O) are widely used to generate δ2H–δ18O plots for studying soil water or groundwater evaporation. However, few studies have investigated whether δ2H–δ18O plots of soil water and groundwater consistently reflect the evaporation characteristics of a watershed. In this study, δ2H and δ18O values of precipitation, soil water, and groundwater

Irrigation benefits crop yields directly by providing additional water and indirectly by reducing extreme high temperature stress (i.e., irrigation cooling benefit). To date, how irrigation cooling benefit is spatial-temporally distributed remains elusive at the global scale. Here, by synthesizing various datasets and data-driven models, we quantify global irrigation cooling benefits and explore the

Groundwater level fluctuations (GLF) reflect the dynamic response of an aquifer to external hydrogeological complexities and inherent properties. These fluctuations, characterized by their temporal oscillations and spatial distribution, provide insight into groundwater circulation across various temporal scales, and the heterogeneity of the subsurface environment. In this study, we aimed to elucidate

The flow structure at river confluences is complex, and is closely linked to sediment transport and fish migration. This study employed large eddy simulation to explore the three-dimensional flow field at an equal-width confluence under varying confluence angles and flow ratios. Based on flow characteristics, the confluence area was divided into six zones: stagnation zone, flow deflection zone, separation

Nonhomogeneous geological features and changing environmental conditions bring great uncertainty and modeling difficulty to karst runoff prediction, probabilistic runoff forecasting is thus of great significance to flood control and water resource management in karst basins. To enhance the accuracy, reliability, and interpretability of runoff prediction, this paper presents an interpretable concep

Karst spring discharges arise from intricate hydrological processes involving spatial and temporal coupling of various hydrological factors, including precipitation, infiltration, and water flow through complex karst aquifers. As a new method for simulating karst spring discharges, deep learning yields better results compared with traditional numerical modelling methods. Existing deep learning methods

The generation of flood projection ensembles for large areas and at a high resolution has been a long-standing computational challenge. Previous studies focused on improving model efficiency and hardware acceleration. An intriguing question arises; is it possible to reduce the computational demand for obtaining specific flood characteristics (e.g., flood frequency curves, FFCs) through precipitation

Evaporation from saline soils is a crucial process with wide-ranging implications for diverse sectors, such as civil engineering, agriculture, and the global hydrological cycle. This study conducted soil column experiments to investigate salt precipitation of four major chlorides (NaCl, KCl, CaCl2 and MgCl2), and their effects on soil evaporation as compared with the control (CK) of distilled water

The Natural Resources Conservation Service Curve Number method (NRCS-CN) is the most widely used approach to estimate runoff from rainfall events. However, some uncertainties in the method remain linked to the value of the standard initial abstraction ratio (λ) and discrepancies between computed and standard tabulated Curve Number (CN) values. Here, we compute CN values and investigate the effects

A reliable monitoring of erosion over large areas is crucial for the control of soil erosion. Spaceborne remote sensing techniques (e.g. Interferometric synthetic aerture radar, InSAR), provide a promising tool for the large-scale erosion monitoring, while their accuracy was rarely quantitatively assessed. In the study, the accuracy of InSAR for erosion mointoring was quantitatively assessed in a small

Potential evapotranspiration (PET) is a necessary input for various offline drought indices and, therefore, crucial for accurately evaluating drought conditions. Since representing land surface characteristics is needed for estimating PET, studying the impacts of land surface parameters on PET and offline drought indices is significant. Therefore, this study used the Food and Agriculture Organization

The rising water demand has significantly altered the hydrologic response of the watersheds, necessitating the incorporation of management activities at the river basin scale. One of the common water management activities is to intentionally regulate the streamflow using numerous Small and Medium Reservoirs (SMRs). Continuous hydrologic models like the Soil and Water Assessment Tool (SWAT) have been

Climate change has markedly intensified the frequency and intensity of extreme rainfall events globally over recent decades. The present investigation introduces a novel approach to modeling Intensity-Duration-Frequency (IDF) curves for major river basins in India using max-stable processes (MSPs). In contrast to earlier studies that mainly dealt with univariate extreme value theory and point-based

Vegetated earthen cover is a common practice after the landfilling of municipal solid waste. However, the impact of vegetation growth, particularly plant ageing and root depth, on the performance of landfill cover systems remains unclear. This study aims to numerically investigate the influence of vegetation growth-induced changes in soil hydraulic properties on percolation under heavy rainfall conditions

Urbanization significantly influences urban hydrological responses, yet existing studies focus on identifying and estimating the effective impervious area and often neglecting the interplay of multiple factors influenced by overland flow paths. To address this, the Variable Source Index (VSI) was introduced to assess the variability of impervious areas contributing to runoff of drainage system, and

Evaporation (E) represents a pivotal process interlinking the water, energy, and carbon cycles within the Earth system. In the context of global climate change, the significant increase in global E has been well-documented since the early 1980 s. However, substantial uncertainties remain in assessing the trajectory of estimated E trends, with the magnitude of global E trends varying by more than an

Biocrusts are an important factor affecting hydrology in drylands, typically forming patches across landscapes. Although their effects on infiltration and runoff were extensively studied, their impacts on runoff movement remained unanswered, significantly hindering our understanding of biocrust roles in hydrological processes. To address this gap, we developed new indicators to quantify the runoff

Groundwater nitrate-nitrogen pollution is common in many agricultural regions and involves several natural and anthropogenic factors. The DRASTIC vulnerability model is frequently used to investigate groundwater nitrate-nitrogen pollution. Because the parameters of the traditional DRASTIC model are insufficient for exploring the incidence of groundwater nitrate-nitrogen pollution, expanding its parameters

Extreme flooding events are becoming more common with climate change and human activities. Rapid and accurate flood inundation simulations are essential for defending against flood hazards and protecting lives and property. Surrogate models have been developed to speedily predict accurate flood inundation dynamics. Recently, the Low-fidelity, Spatial analysis, and Gaussian process learning (LSG) surrogate

Drought, a recurring disturbance in water cycle, significantly impacts terrestrial ecosystems. Understanding the response and recovery times of ecosystems to drought is imperative for assessing drought impacts and unraveling ecological dynamics. However, the dominant factors influencing response and recovery times of vegetation productivity to drought remain unclear. This study first evaluated the

Rainfall partitioning by forest canopies plays a crucial role in the hydrological cycle of forest ecosystems, impacting soil moisture, evaporation, surface runoff, and groundwater recharge. While significant research has focused on rainfall partitioning dynamics at the inter-event scale, less is known about the dynamics and influential factors at the intra-event scale. This study compares rainfall

In recent years, drought has become increasingly frequent and prominent in South China. Comprehending the hydrological processes in response to meteorological droughts and their repercussions plays a crucial role in the effective management of groundwater resources, particularly in fragile karst regions. This study presents how various components of a karst aquifer in subtropical monsoon regions responded

The Chinese Loess Plateau, characterized by complex and fragmented topography, has undergone severe soil loss over the past century. While over thirty soil erosion models have been used in the region, most contemporary models are either catchment-scale or event-based. There is a notable absence of regional-scale models that account for erosion-relevant processes specific to the Plateau. In this study

Quantifying the propagation threshold (PT) from meteorological drought (MD) to agricultural drought (AD) is vital for constructing resilient agricultural systems. This study quantitatively analyzes the propagation thresholds from MD to MD in different climatic regions of China by using a drought propagation model constructed with Copula. It also reveals the impacts of vegetation types, irrigation methods

As global warming intensifies, the frequency of drought events increases, drawing attention to enhanced drought monitoring. While drought indices play a crucial role, most are available only on a monthly scale, and daily indicators remain limited. This study addresses this gap by reconstructing daily Terrestrial Water Storage Anomalies (TWSA) from 1963 to 2022 and proposing a Daily Standardized GRACE

With the accelerated pace of urbanization, urban flooding is more frequent and the probability of transparent waterlogging is higher than before. However, traditional water-level sensors are costly and impractical for widespread deployment in urban areas, and existing image-based methods do not involve quantitatively measuring the depth of transparent waterlogging. Fortunately, transparent waterlogging

The effect of hillslope shape on runoff and soil erosion is a critical factor in understanding erosion dynamics and developing effective soil conservation strategies. This research employs the Water Erosion Prediction Project (WEPP) model, which is calibrated using observed runoff and sediment data from a bare fallow runoff plot located in the red soil hilly areas of southern China, to simulate the

Frequent and severe floods in the transboundary river pose a great threat to the lives and well-being of people in riparian countries, which urgently requires basin-wide s joint flood control operation of those reservoirs. However, coordinating a large number of reservoirs presents challenges in both solution development via complex models and practical implementation. To resolve those challenges,

Glacier meltwater is one of the most important components of water resources in arid region of Northwest China. When glaciers accelerate retreat, water supply capacity of glaciers will decline. Therefore, understanding of future changes in glacier runoff are crucial for water resource management in the arid region. However, the spatio-temporal differences of transition between glacier melt and glacier

This study investigates Water Use Efficiency (WUE) in tropical forests, emphasizing the principal environmental drivers and their seasonal variations. Tropical forests play a pivotal role in global carbon and water cycles; however, the dominant environmental drivers influencing tropical forest WUE and its seasonal differences remain inadequately understood. Using simulations from terrestrial biosphere

Recurrent and prolonged severe hot droughts during the winter–spring period across the low-latitude highlands of China (CLLH) have caused major problems in recent decades, including disruption to the growing season of crops, drinking water shortages, and degradation of ecosystems. This study, which focuses on the period 1979–2022, uses reanalysis datasets and data generated as part of the Coupled Model

Global warming is disrupting the natural balance of ecosystems in the Tienshan Mountains of Central Asia (TMCA), leading to an increase in extreme precipitation (EP) events. However, the process of remote correlation between EP and climatic factors in the TMCA is not yet fully elucidated. This study employs partial correlation analysis, wavelet coherence and elastic net regression to explore the seasonal

Accurately estimating snow hydrology parameters, including snow coverage mapping and snow depth, plays a significant role in comprehending water resource dynamics, flood forecasting, and environmental management in regions influenced by snow cover. These parameters are critical for hydrological models that simulate snowmelt and runoff, which are essential for predicting water availability and managing

Accurately estimating water resource potential and optimizing its utilization under uncertainty is a critical challenge in reservoir management. While traditional fuzzy logic methods address some uncertainties, they often fail to adequately represent the reliability of data. In this context, Z-numbers, as a new generation of fuzzy logic, hold notable potential for describing the uncertainty of human

Climate change and human water demands are altering streamflow droughts. Most research focuses on natural basins due to challenges in distinguishing between climate and human effects. Moreover, the lack of consensus on how to separate these effects sometimes leads to conflicting results. To investigate the impacts of human activities on streamflow droughts, we conducted spatial and temporal analyses

Multivariate time series forecasting, particularly in environmental and hydrological sciences, plays a pivotal role in understanding and predicting complex system dynamics. Traditionally, statistical analysis such as Vector Autoregressive (VAR) modeling has been employed to capture multivariate relationships along with correlation analyses utilizing linear, nonlinear, and mutual information measures

In urban areas, pluvial flooding is one of the biggest disasters caused by climate change and unplanned urbanization. In underdeveloped countries, such as Pakistan, the impact of pluvial flooding in megacities, especially Karachi, is widespread and needs to be studied scientifically. This study investigated the extent of pluvial flooding using cloud computing open-source platforms such as Google Earth

Addressing uncertainties in hydrological modelling is critical for improving model accuracy. Pre-processing and post-processing techniques offer effective ways to reduce these uncertainties, but strategic selection and combination of these methods with machine learning models require further exploration. In this study, we introduced input uncertainty into a hydrological model using satellite precipitation