Soil detachment and sediment transport are the two primary rill erosion processes. The sediment load in rill flow undergoes continuous variation due to the continuity and feedback of soil detachment and sediment transport processes, potentially impacting the soil detachment rate in the next stage. However, numerous studies focus on the soil detachment process by clear rill flow, and the few existing

Geogenic contaminants and emerging contaminants co-occur frequently in disturbed aquifer environments, complicating the evolution of geogenic contaminated groundwater and resultant health risk posed to human beings. The development of antimicrobial resistance (AMR) was found to affect critical microbial activities responsible for arsenic (As) mobilization, yet the underlying processes and mechanism

Conventional drought studies have predominantly focused on elucidating the temporal-spatial evolution of drought while neglecting research on drought propagation. Various degrees of correspondence exist within the same drought propagation mode. This study utilized the Standardized Precipitation Evapotranspiration Index (SPEI) and Vegetation Condition Index (VCI) to characterize meteorological drought

Ditches and ponds are widely used in rural landscapes, forming integrated adaptation systems that play a pivotal role in reducing non-point source (NPS) pollution. However, existing semi-distributed models are not capable of accurately simulating pollution removals of ditches and ponds, resulting in a critical gap in integrating simulation, optimization, and spatial configuration for effective pollution

Seasonal hydrological forecasts are vital for managing water resources and adapting to climate change, aiding in diverse planning and decision-making processes. Currently it is unknown how different forecasting methods, considering initial hydrological conditions and dynamic meteorological forcing, perform across the Swedish river systems, despite the significant socio-economic implications. Here we

Soil moisture data is essential for estimating groundwater storage anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) data, but the general lack of direct in-situ root-zone soil moisture observations has typically resulted in a reliance on modelled soil moisture estimates instead. These model-simulated soil moisture profiles – upper (0 to 10 cm), lower (10 to 100 cm), and deep

Ecological water replenishment (EWR) integrates surface and groundwater regulation to promote riverine baseflows and support groundwater recovery, affecting their interactions. This study introduces SWAT-LSTM-MODFLOW, an advanced SWAT-MODFLOW model incorporating LSTM networks to improve predictive accuracy in data-scarce watersheds. Applied to the Beijing section of the Yongding River Basin, the model

The loss of land due to riverbank erosion is a crucial factor in shaping landforms and plays a significant role in fluvial geomorphology. Understanding and the quantification of the movement and the initiation of sediment particles are the key elements in various engineering and environmental studies. The entrainment and the transportation of sediment particles are controlled by many different physical

As the intensity and frequency of droughts increase, the vegetation community structure and terrestrial ecosystem are therefore threatened. However, the terrestrial ecosystem resilience under drought stress or its underlying drivers, remains poorly understood, hindering effective ecological protection and sustainable development efforts. Taking the Yellow River Basin (YRB) as an example, we constructed

The hyporheic zone is a crucial ecohydrological interface that plays a substantial role in the biogeochemical activity of iron and its mediated pollutant conversion. It is significantly influenced by dissolved oxygen and temperature fluctuations, but the combined effects and mechanisms are unknown. In this study, the co-transport behavior of goethite colloid (Goe), aqueous Fe2+ and oxytetracycline

Coastal groundwater is susceptible to physico-chemical modification from interaction with seawater and other surface waters. Surface water-groundwater (SW-GW) interaction can alter the Sr concentration and radiogenic 87Sr/86Sr signature of both seawater and groundwater from multi-depth aquifers. In this study, we document such an interaction between a tropical ocean (Bay of Bengal [BoB]) and the coastal

Due to the significant influence of climate change and human activities on the water cycle, accurately estimating short- and long-term water availability has become imperative. This study introduces a time series model specifically crafted to decompose river flow time series, enabling estimation of trends, seasonality, and long memory components. This decomposition is interesting as it allows to separate

Globally, vegetation restoration has long been a crucial method for ecohydrological remediation in fragile ecosystems. However, a more comprehensive understanding of how vegetation attributes and environmental factors collectively influence hydrological processes is essential for ensuring the practicability and attainability of sustainable vegetation restoration. This study focused on four typical

Deep learning-based surrogate models have been a promising way of dealing with the computational effort of data assimilation. Although the surrogate can reduce the computational cost, the results are influenced by the approximation error of the surrogate. Online learning methods refit surrogates to improve the accuracy using newly generated samples during iterations. However, it is still a challenge

Pedotransfer functions are valuable in hydrologic analysis because they transform readily available measurements into structured data. This work develops a pseudocontinuous pedotransfer function for prediction of cumulative infiltration using Soil Water Infiltration Global (SWIG) database. Ten different datasets were provided as input data of infiltration characteristics. The largest input data has

This study investigates the correlations between key wastewater parameters – water level, turbidity, and electrical conductivity – under varying weather conditions, including extreme rainfall events such as the May 2023 flood event in Bologna, Italy. Data collected via IoT-based sensors are analyzed using Detrended Cross-Correlation Analysis and Autoregressive Distributed Lag (ARDL) models. The results

The Andes of southern Chile have isolated glaciers on volcanic edifices that, together with the precipitation, contribute to several important river systems in the region. The decrease in the extension of glaciers and the negative trend in precipitation will reduce the downstream water availability. Nonetheless, studies on the sensitivity of hydrological systems due to climate change focus mainly on

The inference of velocity fields from the displacement of objects and/or fields visible within a series of consecutive images over known time intervals has been explored extensively within experimental fluid dynamics. Real image sequences of environmental hydrodynamic flows, however, pose additional challenges for velocity field inference due to factors such as lighting inhomogeneity, particle density

Rain-induced flooding hazards are prevalent on the Loess Plateau (LP). Descriptive statistics, kernel density estimation, and geographical detector methods were used to explore the spatial and temporal distribution, driving factors, and their high-risk intervals of rain-induced flooding hazard events (RFHEs) on the LP and whether they differ across the entire LP and its ecological subregions. The findings

The simulation of phosphorus (P) transport processes in rice irrigation areas plays a crucial role in managing eutrophication issues in downstream water bodies within the context of water conservation. Rice cultivation typically occurs in flat plains, where the soil and water environment of paddy fields undergo significant changes during the growth phase, particularly under water conservation practices

Hydropower was considered a traditional clean energy compared to thermal power. However, the carbon emissions from the drawdown zone could reduce the carbon benefits, which were seldom considered in reservoir operation. This study aimed to balance the carbon emissions of the drawdown zone and the hydropower benefits through reservoir operation. Firstly, the carbon emissions of the drawdown zone were

The GRACE satellite provides tools for accurately characterizing the spatiotemporal variations of regional groundwater storage anomalies (GWSA) under the background of climate change and anthropogenic disturbances. However, its low spatial resolution restricts the refined management of groundwater. Multi-scale geographically weighted regression (MGWR) residuals are innovatively introduced for bias

Recently, differentiable modeling techniques have emerged as a promising approach to bidirectionally integrating neural networks and hydrologic models, achieving performance levels close to deep learning models while preserving the ability to output physical states and fluxes. However, there remains a lack of systematic exploration into the performance and physical interpretability of hybrid models

Recent advancements in deep learning (DL) have significantly improved hydrological modeling by extracting generalities from large-sample datasets and enhancing predictive accuracy. However, DL models often rely heavily on large volumes of data, which are often unavailable or insufficient in many real-world hydrological applications. This challenge has prompted interest in integrating DL with physically

Climate change and urbanization have imposed significant stress on urban drainage systems, resulting in hydraulic overloading and urban flooding. The implementation of Low Impact Development (LID) practices exhibits promising potential in mitigating these impacts. In this study, a modeling task was proposed for the drainage district of Haikou City, Hainan Province, China. The tracer-aided urban flood

China has been frequently affected by urban flooding incidents in recent years. Using hydrodynamic models to simulating urban flooding process is an effective measure in flood control. Considerable literatures of hydrodynamic models confine its scope to relatively small areas or low-resolution limited by computing resources and model performance. Relatively less research of HPC in urban flood modeling

Reliable prediction of river discharge can contribute remarkably for flood control, water resources planning and management. In recent times, several machine learning (ML) models have been utilized to predict river discharge, revealing that their performances are superior to conventional statistical models. In this study, a new hybrid ML model was developed based on the hybridization of Long Short-Term

Much of the stochastic analysis of flow fields in heterogeneous formations in the literature treats the random input parameters that appear in the stochastic differential equation for the groundwater flow perturbations can be characterized by a covariance function. However, it may be that the covariance functions of the input parameters cannot be identified with the limited field data or that the covariance

Tidal channels are essential morphological structures that mediate hydrological connectivity and maintain coastal resilience. Previous studies on vegetation-induced channel development primarily focused on the stages of initial establishment or later elaboration, characterized by slow and localized changes. However, the impact of rapid shifts in landscape vegetation on the initiation of tidal channels

An in-depth understanding of drought evolution in the Yellow River Basin (YRB) is essential for effective drought prevention and water resource management. This study coupled the model data released by CMIP6 and the PCR-GLOBWB model to simulate the hydrological processes in the YRB, and characterize the spatial and temporal distributions of meteorological and hydrological droughts in the period of

Understanding the dynamics of pCO2 and pCH4 is important for evaluating carbon emissions from the aquatic environment. While temporal dynamics of pCO2 and pCH4 have been extensively studied, there is a noticeable gap in the literature concerning their spatial characteristics. In this study, we used boat-mounted sensors to directly measure pCO2 and pCH4 with high spatial resolution across seasons in

Remote sensing techniques for river monitoring facilitate faster measurement campaigns compared to traditional methods, reduce risks to personnel and instruments, and allow measurements under critical flow conditions. An alpha coefficient (α) is commonly employed to convert surface velocities, obtained by contactless techniques, into depth-averaged velocities, which are used for the application of

Traditional chemical analysis for monitoring the remediation process of contaminated soil and groundwater is limited in its spatiotemporal resolution and high cost. To overcome this shortcoming, we applied induced polarization (IP) tomograms to monitor the process of in-situ chemical oxidation coupled with thermal desorption in a field-scale NAPLs contaminated site. To compare the effectiveness of

To improve the quantitative precipitation forecast (QPF) over river-subbasin wise, analysis is conducted using the India Meteorological Department (IMD) Global Forecast System (GFS) model output and high-resolution Flood Monitoring Office (FMO) Bhubaneswar (includes ten catchments (sub-basins) observations. Bilinear interpolation technique is performed to extract the GFS model data to nearest grid

Anthropogenic activities pose significant threats to hydrological regimes, leading to water resource exhaustion through intensive streamflow consumption. To identify regions where anthropogenic activities have a significant impact on streamflow under conditions of non-stationarity and non-linearity, this study developed the Anthropogenic Disturbance for Sustainable Hydrological Regimes (ADS) index

Seepage deformation in sand results from complex water-soil interactions, which are the primary reasons of sand surface collapse, as well as instability and deformation in dam foundations, building foundations, and slopes. Frequent fluctuations in groundwater levels cause changes in the direction, velocity, and pore water pressure of groundwater within the sand. Further research is essential to fully

Traditional high-resolution flood models are too slow for real-time predictions. The most common industry practice is to use a lookup table or interpolation algorithm to derive flood extents from a pre-generated library of flood maps. For the library interpolation approach to be effective, the input flood data need to closely match those in the map library. To effectively emulate complex and dynamic

Spatially distributed hydrologic models are effective tools to simulate the terrestrial water cycle at a large scale, but limitations in flow routing would suffer modeling accuracy for their applications over river basins featuring hydraulically complex drainage systems. Passing outputs from the hydrologic model into the hydraulic model for flow routing as the so-called external coupling has been a

Quantifying fluid fluxes between surface water (SW) and groundwater (GW) is essential for understanding nutrient transport processes across the terrestrial-aquatic interface and river ecosystems. For highly dynamic rivers (e.g., dam-regulated river, tidal river), frequent fluctuations in river stages present challenges in the assessment of SW-GW interactions. To address this challenge, an ensemble

Quantifying the contributions of driving factors and analyzing dynamic changes of water erosion in mountain areas are crucial for water erosion control and sustainable soil resource utilization. In this study, the Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) model were integrated, and the Geographically Weighted Regression (GWR) and path analysis models were used to

Global warming has increased intensity of extreme precipitation events, and it is expected that the intensity of resulting floods will also rise, especially as intensified short-duration extreme precipitation may exacerbate dangerous flash floods. However, quantitative evidence remains limited, and existing research tends to focus on large river basins. Here we analyzed and compared how hourly extreme

Groundwater nitrate pollution is a global environmental issue impacted by complex biogeochemical processes. The biogeochemical behavior of nitrogen in groundwater can significantly influence the hydrogeochemical processes and the carbon cycle. This study, taking the Jinghuiqu Irrigation District in China as an example, analyzed the biogeochemical processes of nitrate in groundwater, and discussed their

For the potential application of electrical resistivity measurements in hydrogeological investigations, the knowledge of soil electrical conductivity mechanism with moisture content variation is the key issue. The impact of interconnections between pores and weak connection to physical processes were the two limitations for unsaturated soil electrical conductivity research. In this work, we introduced

In the present climate, almost all high-latitude rivers in northern regions freeze every winter. In the future, however, climate change may cause shifts in freezing, duration and breakup of river ice cover, runoff, and sediment transport. The main aim of the study is to determine changes in surface flow velocity during river ice freezing and melting periods. We also examine the interplay between surface

Submarine groundwater discharge (SGD) serves not only as an additional source of water, nutrients, and other associated solutes from the land to the sea, but also as a potential freshwater resource, especially under drought conditions. Therefore, it is crucial to quantify SGD and characterize its seasonal and temporal variations. However, sparse studies have examined SGD during a drought period. In

In large lakes, ice cover plays an important role in shipping and navigation, coastal erosion, regional weather and climate, and aquatic ecosystem function. In this study, a novel deep learning model for ice cover concentration prediction in Lake Michigan is introduced. The model uses hindcasted meteorological variables, water depth, and shoreline proximity as inputs, and NOAA ice charts for training

Transpiration in artificial forests has a vital role in the ecohydrological cycle and evolution of afforestation in semi-arid regions. However, further research is required to understand the impacts of biotic and abiotic factors on transpiration and water regulation strategies in tree species under climate change. We used the sap flow method to quantify transpiration in three adjacent plantations (Pinus

Water level prediction is crucial for water resource management and flood warnings. Hybrid LSTM-based methods are widely used but face the following challenges: (1) The attention mechanism based on the universal approximation theorem (UAT) is the mainstream method for improving performance, but its essence is infinite approximation of functions, and the accuracy is difficult to improve; (2) LSTM struggles

While holistic trend identification is essential, it does not consider the periodic, e.g., monthly, trend characteristics needed to identify seasonal trend behavior. Furthermore, identifying seasonal trends can help manage or regulate water resources systems and irrigation and agricultural operations. In this study, the innovative trend significance test (ITST), the revised ITST, and the Wilcoxon signed-rank

The Chah Nimeh Reservoirs (CNRs), located in Iran’s Sistan region, are critical arid inland lakes that support agriculture and supply drinking water to the region. A major concern regarding water quality in these reservoirs is the concentration of Total Suspended Matter (TSM), which has significant implications for both the local communities and the aquatic ecosystem. This study demonstrates the complicated

The risk of sudden water pollution is one of the biggest obstacles to ensuring the safety of river basin water environments. While external pressure factors such as illegal discharge have been extensively studied with regard to their impact on the risk of sudden pollution, the influence of the river network topology has received limited attention. To fill this gap, extensive computational experiments

The progressive industrialisation and urbanisation of urban areas have significantly altered hydrological factors such as terrain, imperviousness, and surface flow. These developments, accompanied by increased traffic congestion and carbon emissions, contribute to climate change. Consequently, implementing Mass Rapid Transit (MRT) systems is crucial for alleviating traffic congestion and reducing carbon

Integrating monitoring data to efficiently update reservoir pressure and CO2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian

Riverbank filtration has a very important role in the supply of drinking water globally. However, this water source is vulnerable, because rivers are easily contaminated. To assess its vulnerability, it is essential to understand the properties of the aquifer including the sources of the water and the transit time. Therefore, a comprehensive investigation of the Hungarian Danube River-‘riverbank’ system

Accelerating global warming has led to the retreat of glaciers and the concurrent expansion of glacial lakes in the Himalayas, increasing the risk of glacial lake outburst floods (GLOFs) with potential to destroy infrastructure and lives in the downstream river valley. In the Sikkim Himalayas, the potentially hazardous Gurudongmar lake complex (GLC) consists of four lakes containing approximately 148 × 106

Daily water balance modeling is important for both hydrological science and water resources management. The majority of daily water balance models express the output fluxes (including runoff and evapotranspiration) as independent functions of soil moisture store(s), and as such they involve a large number of parameters, the estimation of which is a major challenge. In this paper, following a downward

Researchers use sediment hysteresis in watershed sedimentation studies, however underlying processes controlling sediment hysteresis observations remain an open topic of investigation. We investigate the hypothesis that baseflow water and sediment can control sediment hysteresis in some cases by: (i) modelling water–sediment mixing permutations that considers baseflow and runoff with their own sediment

The availability of accurate precipitation data is crucial for water resources management, disaster prevention, and related research. While gridded products offer precipitation information at high spatial resolution, they still exhibit significant errors in precipitation estimation. The merging of multi-source gridded products has become a mainstream approach for improving precipitation estimation

Rewetting is accepted as an effective technique in restoring degraded peatlands. However, it may adversely impact water quality, particularly in nutrient-rich peatlands. The aim of this study was to review water quality models applied to peatlands, with a focus on evaluating the performance (such as stability and accuracy) and complexity of the models. In a systematic review of published studies from