Conceptual snowmelt runoff hydrological models involve uncertainties originating from various sources. For example, uncertainties related to the structure of hydrological models, robustness, parameters, calibration approaches, and input and output datasets may lead to considerably uncertain hydrological predictions. Quantifying such uncertainties is an essential engineering and scientific endeavor

Model development in groundwater simulation and physics informed deep learning (DL) has been advancing separately with limited integration. This study develops a general hybrid model for groundwater level (GWL) simulations, wherein water balance-based groundwater processes are embedded as physics constrained recurrent neural layers into prevalent DL architectures. Because of the automatic parameterizing

The rapid acceleration of the global water cycle caused by changes in global climate trigger complex processes that make conventional machine learning techniques limited in assessing impacts of such changes on terrestrial water storage (TWS). This study introduces an assimilated deep learning neural network to improve the modeling of TWS dynamics. Key predictors and inputs to this deep learning framework

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One of the most important parameters in the design and implementation of drip irrigation systems is the accurate prediction of the wetting dimensions pattern around the emitters, which leads to the precise determination of the distance between the emitters and the drippers. This search provides a comprehensive experimental and computational investigation to predict accurate wetting patterns (dimensions

Short-term rainfall forecasting plays an important role in hydrologic modeling and water resource management problems such as flood warning and real time control of urban drainage systems. This paper compares the performances of three machine and deep learning-based rainfall forecasting approaches including a hybrid optimized-by-PSO support vector regression (PSO-SVR), long-short term memory (LSTM)

Water options trading (WOT) is an effective way to promote efficient allocation of water resources and to manage risks of water scarcity. Scientific prediction information can help hedge the risks brought by uncertain hydrological and market environment to WOT. However, confronting with the prediction information, irrigation areas characterizing with heterogeneous resource endowments often exhibit

Floods are the most commonly occurring natural disaster, with the Centre for Research on the Epidemiology of Disasters 2021 report on “The Non-COVID Year in Disasters” estimating economic losses worth over USD 51 million and over 6000 fatalities in 2020. The hydrodynamic models which are used for flood forecasting need to be evaluated and constrained using observations of water depth and extent. While

Recently, gridded precipitation datasets (GPDs) have become an essential input in hydrological modeling. Evaluation of their performance is a priori step before their application. When they are applied to a glaciated catchment, the glacier mass balance adds another dimension to the evaluation. This study has attempted to introduce the Turc-Budyko formula for validating the GPDs in glaciated catchments

Large-scale vegetation restoration projects have been ongoing in the karst region of southwest China for several years. However, the influence of vegetation restoration alone on soil moisture (SM) changes in this region remains unclear. In this study, a random forest model was constructed using meteorological data, the ERA5-Land SM dataset, and the enhanced vegetation index to analyze SM changes in

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The influence of climate change and human interference bring high nonstationary characteristics that are different from the original long-term stable state. So that, investigating runoff variation and attribution under changing environments is important for implementing adaptive management of global water resources, especially on the interannual scale. In this study, the attribution of measured runoff

One of the major advantages of satellite precipitation estimates is that they can provide a complete picture of precipitation systems; a difficult task to achieve using sparsely distributed rain gauges. This advantage greatly enhances our understanding of natural precipitation. Also, for this reason, it is difficult to know satellite-derived precipitation system performance using a direct “object-to-object”

The East Asian summer monsoon (EASM) and Indian summer monsoon (ISM) are two interactive climate systems dominating the moisture variability of Monsoon Asia. However, ISM-EASM interactions and their effects on regional moisture dynamics remain unclear. This study investigated the spatiotemporal characteristics of monsoon-related hydroclimate variability by establishing a new tree-ring oxygen isotope

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Persistent eutrophication frequently causes toxic algal blooms, which is a serious threat to drinking water safety, food security, and public health. Nutrient thresholds, the maximum nutrient load that an aquatic ecosystem can absorb while meeting management objective, are key to avoiding and reducing blooms. The determination of thresholds relies on nutrient load-response curves. The spatial heterogeneity

Locally recycled moisture from transpiration and surface evaporation is of great importance in the terrestrial hydrological cycle, especially in the widely distributed oases across arid central Asia. Quantitative assessment of the proportional contribution of recycled moisture to local precipitation, i.e., the recycling ratio, is useful to understand the land-air interaction as well as the anthropogenic

Flood is the most common worldwide natural disaster with enormous impacts on human society and the ecosystem. Consequently, the research of flood risk assessment and zonation is critical. Its research scope is changeable, wherein the basin-scale research has become more and more important due to the increasing boom of cascade hydropower development in the river basin. The study proposed a basin-wide

Common approaches for characterizing streambed architecture, and its influence on groundwater-surface water (GW-SW) exchanges, are generally limited by their invasiveness and low spatial sampling density, which is a particular issue in streambeds that typically have high spatial heterogeneity. Combined DC resistivity and induced polarization (DC-IP) imaging can provide rapid, non-invasive and continuous

In response to the increasing threats of flash flooding, how to generate flood maps in real time has drawn great attention. In this study, a hybrid ML model was developed for flood map generation with multiple lead times based on the combination of the support vector regression (SVR) method and Heun’s scheme for numerical correction, in which the hydraulic simulation results are used for model training

The validation of satellite soil moisture (SM) products is challenged by the large scale difference between in situ-satellite based measurements. In order to tackle the significant spatial scale mismatch, this study conducted a multi-scale validation of three typical SM products (i.e., SMOS-IC, SMAP L3, and AMSR2 LPRM) over Qinghai-Tibet Plateau. First, a 25-km better-performing SM dataset was produced

This study evaluates the effect of cloud seeding on the increase of runoff or securing of additional water resources. Unlike previous studies, this study concentrates more on the change of various components of the hydrologic processes. Both the event-based analysis and the annual analysis are conducted to evaluate the change of these components. The Boryeong Dam Basin in Korea is considered as a study

Healthy soils are one of the key priorities of the EU Soil Strategy, and soil erosion can present a threat to soils around the world. Rainfall erosivity is the main driver of soil erosion by water. Rainfall interception by vegetation can reduce the erosive power of raindrops, and consequently measures involving vegetation can mitigate soil erosion losses. In this study, the effect of rainfall interception

A novel framework that integrally uses groundwater and streamflow observations to calibrate a physically based sub surface model to generate base flow on a daily time step is presented in this study. Trend analysis on mean annual base flow time series showed that a declining trend was present in the basin though the upstream humid region was devoid of any trend. GLUE analysis was adopted to the simulation

Remote sensing has become a data source long ago for estimating evapotranspiration (ET), but often with a dilemma between temporal and spatial resolution. The recent ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) reaches a satisfactory compromise. It provides 70 m spatial resolution and an average 4-day revisit cycle at different times of a day, making granular analysis

Accurate evapotranspiration (ET) measurements are fundamental for improving the understanding of water-energy related processes and for validating model simulations. However, ET is inherently difficult to measure unambiguously. The surface renewal (SR) method, which describes the turbulence exchange process from a new perspective, has been successfully applied within affordable costs from crops to

Soil moisture is a key variable controlling the energy and water balance at the land surface and satellite-derived soil moisture (SDSM) products can therefore be helpful to constrain parameters of (eco)hydrological models. Due to coarse resolution of many SDSM products (> 25 km), previous studies mostly focused on large catchments (> 500 km2). However, recent developments in soil moisture remote sensing

Nitrate Concentration–discharge (C-Q) relationships have been used to infer nitrate sources, storage, reactions, and transport in watersheds, and to reveal key processes that control runoff chemistry. Yet, studies on long-term nitrate C-Q relationships are limited due to scarce high frequency (e.g., daily) concentration data. In this paper, using a long-term high-frequency dataset (1976-2019) comprising

Under the double pressure of ecological vulnerability and economic development, natural resources and ecological environment have become the key constraints to the development of the Yellow River Basin (YRB). This paper proposed a theoretical framework for the relationship between water-energy-food (WEF) and poverty. An improved coupling coordination degree model and the geographical detector were

In intertidal zones, groundwater is often present as seepage that provides freshwater and nutrients to marine ecosystems. Point discharge or springs in intertidal zones have been observed in many locations, often in the form of sand boils. The spatial extent, temporal variability and source of intertidal springs are rarely documented and typically, not well understood. This study examined four intertidal

The applications of the Gravity Recovery and Climate Experiment (GRACE) on local scales are obstructed owing to the coarser spatial resolution of GRACE observations. Much attempts recently have been taken to improve the resolution of GRACE-based water storage estimates based on machine learning algorithms, focusing on new algorithm development. However, there are still two deficiencies in previous

We conducted several field surveys to measure velocity and channel geometry in 15 cross-sections distributed along three reaches in the Boi River (Southern Brazil), a canyon river that belongs to the most extensive canyon chain in South America. The three reaches present, respectively, canyon, transition, and floodplain landscapes. The resulting data were used to compute the flow resistance. A downstream

Water abstraction is a key aspect when performing drinking water risk assessment within the scope of Water Safety Plan (WPS). In this context, evaluating aquifer vulnerability could be not exhaustive. Care must be taken to consider the well structure and dynamic behavior that can determine different water quality and vulnerability than those of the tapped aquifer. Here, a methodological approach to

Reservoir flood control operation is an important and effective measure for avoiding or reducing flood disasters. Considering that reservoir operation is a control process that essentially manages the spillway gates to increase or decrease the amount of released water, this paper focuses on studying the reservoir flood control operation which considers spillway gate scheduling. Minimizing the peak

Improving the understanding of the future hydrological drought variability in cascade reservoirs area is indispensable for water resource management, especially in the context of changing climate. This study aims to investigate the hydrological drought variations in the upper Yellow River Basin (UYRB) during 2021–2100 employing the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets

Changes in hydrological processes caused by rapid urbanization lead to the growing incidence of urban flooding, which is a major challenge to urban sustainability. Urban floods have seriously threatened the natural environment and human life. Understanding the spatial patterns and influencing factors of urban flooding has important implications for mitigating urban flood hazards. Previous studies have

Optimal operation of multi-purpose multi-reservoir dams is a challenging problem for dams’ stakeholders and decision-makers. Optimization algorithms are able to present reliable solutions for such complex problems. This study compared the capability of 20 state-of-the-art robust meta-heuristic algorithms for determining the optimal operating policy of Halilrood multi-reservoir system under the three

Merging the satellite and gauge precipitation has been proofed as an efficient approach to improve the accuracy of quantitative precipitation estimation. However, for areas with few and unevenly distributed rain gauges, accurate precipitation estimation still remains challenging. To address this problem, this paper proposes a framework to improve precipitation estimation for the data scarce area based

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As an important technology for measuring water levels, satellite altimetry has been widely using in the lake, river, and wetland in the past two decades. However, the waveform pollution limits its application in areas with complex topography, the accuracy of the existing retracking algorithms need to be further improved. In this study, a new retracking algorithm, named Improved Narrow Primary Peak

Transient measurements from soil water monitoring installments are frequently coupled with Richards-based solvers to inversely estimate soil hydraulic parameters (SHPs) and numerically describe vadose zone water fluxes, such as groundwater recharge. To reduce model predictive uncertainty, the experimental setup should be designed to maximize the information content of observations. However, in practice

Statistical calibration of precipitation forecasts from numerical weather prediction (NWP) models is routinely performed grid-cell by grid-cell, aiming to produce accurate and reliable ensemble forecasts for precipitation fields. Calibrated ensemble members from different grid-cells are then connected using ensemble reordering to form spatially structured ensemble forecasts. However, ensemble reordering

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Evaluation of peak flood magnitude and frequency in the future at a catchment scale under global warming is crucial for water resource management and flood risk management. Climate model outputs provide a leading source of information to quantify the effect of the foreseen natural and anthropogenic climate change on the environment and natural systems. However, modelling climate change impact on peak

The depletion of groundwater resources (GR) in Iran, which is an arid and semi-arid country, has reached a critical level, so managing the remaining of these resources is an urgent need. In this respect, institutions are a key element of GR protection and management and their social capital is instrumental in the management of these resources because social capital can create a synergy in the collective

A new dynamic-wave cellular automata framework for two-dimensional (2D) shallow water flow (SWF) modeling is herein proposed. During the last decade, the concept of cellular automata (CA) has been widely adopted to develop various 2D shallow water flow models. Such CA models use simple transition rules that only consider the conservation of mass and neglect the conservation of momentum, as a result

Prediction of river flow rates is an essential task for both flood protection and optimal water resource management. The high uncertainty associated with basin characteristics, hydrological processes, and climatic factors affecting river flows make streamflow prediction a very challenging problem. These reasons, together with the increasingly wide availability of data relating to flow rates and rainfall

The projected increase in the frequency of extreme rainfall events with climate change has serious implications for flood risk management. This study developed a novel method to evaluate future flood inundation risk in the Kakehashi River basin, Japan. First, a pseudo global warming (PGW) method and ensemble simulation techniques were combined to develop rainfall projections with different return periods

Groundwater optimization models coupling Non-dominated Sorting Genetic Algorithm II (NSGAII) with surrogate models have shown great success in recent years. However, most previous models adopted global optimization over time steps while ignoring the time-varying properties of optimization objectives, which may lead to an unrealistic strategy for specific months. Moreover, employing global optimization

Evapotranspiration (ET) is an essential ecohydrological process linking the land surface energy, water and carbon cycles, and plays a critical role in the earth system. ET remains one of the most problematic components of the water cycle to be determined due to the heterogeneity of the landscape and the complexity of driving factors. The satellite-based earth observation is expected to provide ET information

Interception loss is a crucial part of the hydrological cycle and can influence the water and energy balance between the soil surface and atmosphere. Fire alters forest structure and then can immediately modify hydrological factors that influence interception loss. We monitored and simulated canopy rainfall partitioning responses to fire were monitored in a coniferous and broadleaved mixed forest.

Electrokinetic remediation (EKR) is a promising remediation technology for low-permeability porous media contaminated with organic pollutants. To reveal the processes of nonlinear electroosmotic flow (EOF) and to elucidate the key factors controlling the efficiency of EKR, a process-based pore-scale numerical model was established. Nernst-Planck-Poisson Equation is coupled with Navier-Stokes Equation