The Three Gorges Dam (TGD) and its impoundment significantly alter natural river properties and local land cover, drawing considerable concerns regarding its climatic and environmental effects. However, with the role of the Three Gorges Reservoir (TGR) in narrowing temperature ranges and changing precipitation patterns is well understood, its impact on moisture recycling is little known. Here, we tracked

The National Water Model (NWM) is a key tool for flood forecasting, planning, and water management. Key challenges facing the NWM include calibration and parameter regionalization when confronted with big data. We present two novel versions of high-resolution (∼37 km2) differentiable models (a type of hybrid model): one with implicit, unit-hydrograph-style routing and another with explicit Muskingum-Cunge

Urban flood monitoring is crucial for understanding flood processes and implementing management strategies. However, current monitoring systems cannot comprehensively capture urban flooding dynamics. Here we explore the use of cutting-edge Large Multimodal Models (LMMs) to estimate floodwater depth from ground-level images, as alternative observational approaches. Evaluated on two urban flood image

Gas bubbles are commonly observed in both natural and human-made water systems, and their generation and distribution play pivotal roles in water quality and aquatic habitats. This study explores methods for predicting bubble size distribution within various types of turbulent flows. Models for bubble size distribution, both with and without bubble breakup, are developed and validated using experimental

Recent developments in control theory, coupled with the growing availability of real-time data, have paved the way for improved data-driven control methodologies. This study explores the application of the Data-Enabled Predictive Control (DeePC) algorithm to optimize the operation of water distribution systems (WDS). WDS are characterized by inherent uncertainties and complex nonlinear dynamics. Hence

Flood insurance is an important financial measure for flood risk management. However, a significant protection gap in flood insurance exists in many countries due to high flood insurance costs. Reducing flood insurance costs for both policyholders and insurance companies is crucial for implementing flood insurance. This study introduces the concept of geographic complementarity of flood risk to reduce

Urban water resources planning is complicated by unprecedented uncertainty in supply and demand. Real-world planning often simplifies the full range of uncertainty faced by a system into a limited set of deterministic scenarios to enhance accessibility for decision-makers and the public. However, overlooking uncertainty can expose the system to failures. On the other end of the spectrum, academically

Surface cover influences the hydraulic parameters of overland flow, subsequently affecting soil erosion. Therefore, exploring the flow dynamic mechanisms under different surface cover types is crucial. A series of flume experiments were conducted to investigate the impact of surface cover on the hydraulic parameters of overland flow. The specific experimental conditions were as follows: one slope gradient

Advances in data analytics create an opportunity to enhance reservoir operation. A challenge arising is how to utilize operational data to form realistic constraints of the reservoir operation practice. To address this issue, a novel approach is proposed to extract operational intervals of reservoir outflow by a deep learning method, namely the physics-guided long-short term memory network. The knowledge-informed

Understanding and predicting coastal change is of the foremost importance to protect coastal communities and coastal assets. This study analyzes field data from 125 locations along the Morecambe coastline, consisting of beach transects collected twice a year for more than a decade (2007–2022). Wave data at these 125 locations were simulated using the hydrodynamic Delft3D model, with full coupling of

The hydrological dynamics of intermittent rivers and ephemeral streams (IRES) impacts the availability of water to riparian ecosystems, the height of downstream runoff peaks, and the replenishment of groundwater systems. Despite its significance, the influence of superficial geology on IRES flow processes remains an area of limited understanding. Here we first present a comprehensive data set encompassing

Poyang Lake, the largest freshwater lake in China and a globally significant wetland, is intricately connected to the hydrological dynamics of the Yangtze River via a complex river-lake exchange system. This system generates to unique seasonal fluctuations, forming a distinctive seasonal lake system, which influences hydrological and hydrodynamic processes across floodplains. Recent years have witnessed

Freshwater lakes are vital water resources, especially in the context of a changing climate. Supplementing existing hydrological methods to monitor lake levels may greatly improve resource management, particularly in drought-prone regions. In this study, we performed dual-isotope (δ18O and δ2H) calculations to model the hydrological balance of Bear Lake, Utah-Idaho. The lake is a critical water resource

In the absence of adequate observations on the off-channel areas, flood models are typically trained and validated against stream water depths. This approach can be efficient for physics-based models, which incorporate the underlying physical processes, but the efficiency for data-driven models like machine learning (ML) algorithms is unclear. The existing off-channel observations like high-water marks

Forest thinning and prescribed fire are expected to improve the climate resilience and water security of forests in the western U.S., but few studies have directly modeled the hydrological effects of multi-decadal landscape-scale forest disturbance. By updating a distributed process-based hydrological model (DHSVM) with vegetation maps from a distributed forest ecosystem model (LANDIS-II), we simulate

Diminishing glaciers affect streamflow, and given the extent of glaciers in Alaska and adjacent Canada, continued glacier mass loss is likely to have profound effects on ecosystems sensitive to runoff. The effects of glacier mass loss on streamflow are likely to vary across the wide ranges of basin size, glacier cover, and precipitation in this region. In this study, we use U.S. Geological Survey (USGS)

Mineral dissolution releases ions into fluids and alters pore structures, affecting geochemistry and subsurface fluid flow. Thus, mineral dissolution plays a crucial role in many subsurface processes and applications. Pore-scale fluid flow often controls mineral dissolution by controlling concentration gradients at fluid-solid interfaces. In particular, recent studies have shown that fluid inertia

Groundwater flows have been recognized as an important factor controlling bank collapse in both fluvial and tidal environments. These flows are strongly related to water-level fluctuations in the channel and contribute to seepage erosion and variations in bank soil properties. Despite the more frequent, periodic water level changes in tidal settings, seepage-driven bank collapses of tidal channels

The Qinghai-Tibetan Plateau (QTP) has undergone significant warming, wetting, and greening (WWG) over decades, alongside substantial alterations in hydrological regimes. These changes present great challenges for safeguarding water resources and ecosystems downstream. However, the lack of field observation and systematic research has obscured our understanding of how hydrological processes respond

In a high-pressure injection fault activation experiment conducted at the Mont Terri underground research laboratory in Switzerland, the transmissivity of the Opalinus Clay fault significantly increased due to opening and shearing. The fluid injection, spanning a few hours, generated a 10 m radius fault activation patch. Subsequent pressure pulse tests conducted bi-weekly for a year revealed the gradual

Toxic harmful algal blooms produce public health hazards in freshwater systems around the world. There is a need for forecast systems that can mitigate risk of public exposure to toxins. We improved an approach to predict the spatially and temporally resolved probability of microcystins (MCs) exceeding a threshold level (6 μg L−1) in western Lake Erie. This approach combines a 5-day chlorophyll-a forecast

Ongoing climate change is modifying snow dynamics, further altering streamflow (Q) in cold regions. Despite extensive research over the past decades, the impact of changes in snow on mean annual Q remains debated, and the underlying mechanisms driving these responses are still unclear. In this study, we employ the Budyko framework to establish multivariate relationships between a Budyko model parameter

The H-shaped feature, characterized by a single connecting channel (CC) linking two inflows, is a common geomorphological unit in delta river networks. This structure plays a critical role in redistributing upstream flows, affecting the hydrological connectivity of the network. Despite previous studies on geometric structures and flow distribution, the mechanisms influencing hydrological connectivity

Remote sensing (RS) soil moisture retrievals are frequently assimilated into land surface models (LSMs) to enhance model estimates. However, soil moisture data assimilation (DA) efficiency is highly model-dependent, making it imperative to investigate whether current LSMs can achieve expected DA efficiencies and identify potential model limitations for DA. Here, we examine soil moisture DA efficiency

Headwater catchments have strong impacts on downstream waterways, near-shore ecosystems, and the quality of water available for growing human populations. Thus, understanding how water and solutes are exported through these upland landscapes is critically important. A growing body of literature highlights the interaction of topography, climate, and the critical zone structure as a key control on streamflow

Channel networks are important landscape features that transport water, sediment, and nutrients. Their emergence and evolution are controlled by the competition between hillslope and fluvial processes on landscapes. Investigating the geomorphic and topologic properties of these networks is crucial for quantifying the roles of processes in creating distinct patterns of channel networks and developing

Moisture recycling is an integral component of the hydrological cycle, enhancing regional water availability by returning evaporated moisture as precipitation either locally or downwind. In China, characterized by uneven water resource distribution and regional water scarcity, understanding moisture recycling dynamics is crucial for sustainable water management. Our study quantified the contribution

Meteorological droughts can reverberate through the water cycle, impacting water resources, ecosystems, agriculture, and socio-economic sectors. Despite this, there remains a scarcity of studies delving into the transition from meteorological to hydrological droughts and the influencing factors operating at the event level. Using long-term observations spanning nominally from 1979 to 2017, we identified

On behalf of the editorial board of Water Resources Research (WRR) and the entire water science community, we want to express our most heartfelt gratitude to all who reviewed manuscripts for the journal in 2024. Your great efforts have ensured and improved the high quality and impact of the WRR papers and generally of research in our field. In 2024, the 2832 individuals listed below have contributed

No abstract is available for this article.

Sparse precipitation data in karst catchments challenge hydrologic models to accurately capture the spatial and temporal relationships between precipitation and karst spring discharge, hindering robust predictions. This study addresses this issue by employing a coupled deep learning model that integrates a variation autoencoder (VAE) for augmenting precipitation and a long short-term memory (LSTM)

Despite its energy benefits, hydropower dam development often causes ecological damages and social disruption, including downstream livelihood impacts, and biodiversity loss. Current methods for analyzing changes in downstream inundation extent due to dam operation typically rely on historical ground or satellite observations, or on coupled hydrological-hydrodynamic modeling. However, while the former

Land surface models consider the exchange of water, energy, and carbon along the soil-canopy-atmosphere continuum, which is challenging to model due to their complex interdependency and associated challenges in representing and parameterizing them. Differentiable modeling provides a new opportunity to capture these complex interactions by seamlessly hybridizing process-based models with deep neural

Plenty of information on evapotranspiration (ET) dynamics and partitioning into nonbiological (evaporation, E) and biological (transpiration, T) components is available in literature. However, in agro-ecosystems where more than one vegetation group is found, like intercropping or grassed orchards and vineyards, it is of great use to understand the contribution to T due to the single plant type or group

Friction is one of the cruxes of hydrodynamic modeling; flood conditions are highly sensitive to the Friction Factors (FFs) used to calculate momentum losses. However, empirical FFs are challenging to derive, causing flood models to rely on surrogate observations (such as land cover) and introducing uncertainty. This research presents a laboratory-trained Deep Neural Network (DNN), developed using

The soil freezing characteristic curve (SFCC) is used as a tool for interpreting various properties of frozen soils such as hydraulic conductivity, volume change, and shear strength. Existing SFCC models are commonly based on empirical relationships, pore size distribution (POSD), or adaptations of the Soil-Water Characteristic Curve (SWCC). Empirical models often lack a theoretical foundation, limiting

We provide a sound theoretical framework for the characterization of randomly heterogeneous spatial fields exhibiting multi-modal, long-tailed probability densities. Multi-modal distributions are at the core of conceptual models employed to represent heterogeneity of hydrogeological or geochemical systems across which one can otherwise distinguish diverse regions whose location is uncertain. Within

Coastal marshes are important ecosystems providing numerous ecological services, including coastal protection, carbon storage, and biodiversity enhancement. Salt marshes are dissected by dendritic creeks dividing the marsh into distinct watersheds. The size and location of watersheds influence marsh hydrodynamics, which in turn, affect sediment and nutrient transport. Consequently, these processes

Sanitary engineered landfills require extensive aftercare to safeguard human health and the environment. This involves monitoring emissions like leachate and gas, maintaining cover layers, and managing leachate and gas collection systems. Researchers have explored methods to conclude or extend aftercare. Quantifying emission potential, a key concept integrating various processes influencing emissions

Nitrate is a common groundwater contaminant resulting from excessive agricultural fertilizer use, especially in coastal regions. Negative hydraulic barriers (NHBs) are widely used to mitigate seawater intrusion by altering groundwater behavior and pumping saline groundwater, but their impact on nitrate pollution remains unclear. This study investigated the mechanisms and impacts of NHBs on nitrate

Northern temperate forests are experiencing changes from climate and acidification recovery that influence catchment nitrate-nitrogen (N) flushing behavior. N flushing behavior is characterized by metrics such as: (a) N flushing time—the exponential decrease in stream N concentration during the peak snowmelt episode; and (b) N concentration (C) and discharge (Q) hysteresis metrics—flushing index (FI)

This study presents an innovative approach to risk-aware decision-making in water resource management. We focus on a case study in the Netherlands, where risk awareness is key to water system design and policy-making. Recognizing the limitations of deterministic methods in the face of weather, energy system, and market uncertainties, we propose a scalable stochastic Model Predictive Control (MPC) framework

The amount and quality of dissolved organic carbon (DOC) exported from terrestrial to riverine ecosystems are critical factors influencing aquatic metabolism and ecosystem health in streams, rivers, and lakes. This study investigates the interplay between hydrologic conditions and DOC dynamics in an alpine catchment, focusing on how DOC concentration and quality shift during baseflow, snowmelt, and

Phosphorus fertilization has supported remarkable improvements in agricultural productivity but also degraded water quality. Watershed simulation models have been broadly instrumental to crafting phosphorus management responses. However, simulation-based studies rely on predesigned watershed scenarios (e.g., initial conditions and management actions) and are blind to outcomes that might only emerge

Pipe bursts in water distribution networks (WDNs) not only cause significant water wastage but also pose risks of secondary disasters, such as road collapses. In most cases, these failures often result in a simultaneous decrease in values across multiple pressure sensors, indicating strong correlations in pressure data from the same event. This correlation suggests that leveraging the cooperative interaction

Our study proposes a data-driven framework that identifies the level of functional simplicity of catchment's stormflow generation during dormant/growing seasons, using daily scale observations of streamflow and precipitation. We classify 619 rain-dominated catchments across Canada, the United States, Great Britain, and Australia into three behavioral classes—simple, intermediate, and complex—based

Uncalibrated global hydrological models are primarily used to inform projections of flood and drought changes under global warming and their impacts, but it remains unclear how model calibration might benefit these projections. Using the Yangtze River Basin as a case study, we compare projected changes in flood and drought frequencies and their impacts—area, population, and gross domestic product affected—at

Satellite-based precipitation observations can provide near-global coverage with high spatiotemporal resolution in near-realtime. Their utility, however, is hindered by oftentimes large uncertainties that vary substantially in space and time. This problem is particularly pronounced in regions which lack dense ground-based measurements to quantify or reduce such uncertainty. Since this uncertainty is

In Weber et al. (2019), https://doi.org/10.1029/2018wr024584 (hereafter W19), modeling soil hydraulic properties (SHP) was systematically framed and presented in a didactic, carefully thought-out approach. In doing so, the authors coined the term SHP model system/model framework, acknowledging the decade old research on effective modeling of the SHP. At the heart of the model an integral was formulated

Hydrologic regimes are affecting terrestrial carbon transformation, chemical weathering and lateral transport. However, its impacts on dissolved carbon export patterns remains elusive. In this study, we collected a 2-year high-frequency dissolved inorganic (DIC) and organic carbon (DOC) dataset, namely a wet year (Rainfall = 1,158 mm) and a dry year (Rainfall = 603 mm). The results showed that drought

Streamflow observations, essential for various water resource applications, are often unavailable at critical locations in need. Although different models have been proposed to enhance streamflow predictability at ungauged locations, the challenge extends beyond model fidelity. Differences in meteorologic forcing data sets, precipitation in particular, can significantly affect the accuracy of hydrologic

Conventional methods of measuring water discharge and suspended sediment concentration (e.g., water sampling and moving acoustic Doppler current profiler [ADCP]) present challenges in large tidal rivers due to temporal and spatial constraints. This study introduces a novel approach to monitor water discharge and suspended sediment discharge (SSD) in large tidal rivers. Total water discharge and SSD

Below-ground urban stormwater networks (BUSNs) significantly influence urban flood dynamics, yet their representation at the watershed or larger scales remains challenging. We introduce a scalable urban hydrologic framework that centers on a novel network-level BUSN representation, balancing the needs for physical basis, parameter parsimony, and computational efficiency. Our framework conceptualizes

Lakes are among the most prevalent and predominant water repositories on the Earth's land surface. A primary objective of the Surface Water and Ocean Topography (SWOT) satellite mission is to monitor surface water elevation, area, and storage change in lakes globally. To meet this objective, prior information on lakes, such as locations and benchmark extents, is required to organize SWOT's KaRIn observations

Remarkable vegetation greening has been observed in the Yangtze River Basin (YRB) during the past two decades, triggering noteworthy hydrological consequences. Previous studies have assessed the hydrological effect of vegetation greening but ignored the vegetation-precipitation feedbacks from land-atmosphere interactions. To address this knowledge gap, here we conduct coupled land-atmosphere model

Analytical models interpreting aquifer pumping test data often rely on water table kinematic conditions that assume instantaneous gravity drainage, leading to underestimation of specific yield during the drainage process. This study derives a new water table condition based on a coupled saturated-unsaturated flow model that fully accounts for both unsaturated and saturated flow dynamics. The new condition

Machine learning (ML) is increasingly considered the solution to environmental problems where limited or no physico-chemical process understanding exists. But in supporting high-stakes decisions, where the ability to explain possible solutions is key to their acceptability and legitimacy, ML can fall short. Here, we develop a method, rooted in formal sensitivity analysis, to uncover the primary drivers

This study investigates the impact of the transition from viscous linear to inertial nonlinear flows on solute mixing and partitioning at rough-walled fracture intersections, using direct observations of flow dynamics and solute partitioning processes through microscopic particle image velocimetry. It is generally known that mixing at fracture intersections decreases when transport shifts from diffusion-dominated

Continuous, high-resolution data for characterizing freshwater habitat conditions can support successful management of endangered salmonids. Uncrewed aircraft systems (UAS) make acquiring such fine-scale data along river channels more feasible, but workflows for quantifying reach-scale salmon habitats are lacking. We evaluated the potential for UAS-based mapping of hydraulic habitats using spectrally