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Osypov et al. (2025) A High‐Resolution Hydrological Dataset for Ukrainian River Basins With an Interactive Web Interface
The study developed a high-resolution hydrological model of the Ukrainian Watershed using the SWAT model and integrated it into a FAIR-compliant web interface ('Land & Water') to support water resource management and post-war reconstruction.
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Vicente‐Serrano et al. (2025) Characteristics of widespread extreme precipitation events in Peninsular Spain and the Balearic Islands: spatio-temporal dynamics and driving mechanisms
This study investigates the spatiotemporal trends and atmospheric drivers of widespread extreme precipitation events (WEPEs) in Spain from 1961 to 2022. It finds no significant trend in WEPE frequency or intensity, but identifies five distinct synoptic patterns and associated moisture sources that govern their regional distribution.
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Bouizrou et al. (2025) The potential of novel remote sensing evapotranspiration data and global soil maps for SWAT+ agro-hydrological modeling in data-scarce regions of the North Mediterranean
This study utilized the SWAT+ model with novel remote sensing evapotranspiration (RS-ET) data, a high-resolution global soil map (DSOLMap), and detailed agricultural practices for agro-hydrological modeling and multisite calibration in four ungauged watersheds in the data-scarce Messinia region, Greece. The findings demonstrate that integrating DSOLMap and GLEAM RS-ET significantly improved model performance (Nash-Sutcliffe Efficiency > 0.5; Percent Bias < ±15 %) compared to local soil maps and MODIS RS-ET, providing a valuable tool for water resource management.
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Gómez et al. (2025) Evaluation using in-situ observations from national governments and Citizen Scientists suggests nadir altimeters can accurately measure water level changes regardless of lake area
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Lin et al. (2025) The Positive Pacific–Japan Pattern Drives Compound Heat and Dry Extremes in Summer over Taiwan
This study examines how the positive phase of the Pacific–Japan (PJ) pattern triggers compound heat wave–drought events in Taiwan via land–atmosphere feedback mechanisms.
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Li et al. (2025) Divergent Seasonal Biophysical Effects Induced by the Three Gorges Reservoir
## Identification - **Journal:** Water Resources Research - **Year:** 2025...
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Sepp et al. (2025) Impacts of climate change on the dilution capacity of perennial and non-perennial European rivers
This study evaluates the current and future capacity of perennial and non-perennial European river reaches to dilute wastewater treatment plant (WWTP) effluents under climate change. It reveals that non-perennial reaches have significantly lower dilution capacity, which is projected to decrease further in two-thirds of reaches under a high emissions scenario, particularly in vulnerable Mediterranean and semi-arid regions.
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Zhang et al. (2025) Flood risk assessment in data-scarce South Sudan using a flood modeling framework
This study develops a national flood modeling framework for data-scarce South Sudan using integrated ground observations and satellite data with a coupled hydrological-hydrodynamic model. It reveals that the 2021–2023 flood caused unprecedented Nile River backflow into the Ghazal basin at Lake NOE, and that high-return-period floods (≥50-year) induce significant Nile discharge into the Ghazal basin via Nerboar, challenging previous hydrological assumptions.
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Liu et al. (2025) Evaluating ISIMIP3b bias-corrected data for precipitation extremes in China during 1981–2100
This study evaluates the accuracy of ISIMIP3b bias-corrected data in representing historical precipitation extremes in China and projects future changes, confirming its reliability for climate change impact assessments and forecasting increased heavy precipitation and fewer dry days under higher emission scenarios.
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Li et al. (2025) The Thermodynamic and Dynamic Cause Analysis of Three Extensive Compound Heatwaves from 2011 to 2024 in Mainland Spain
This study investigates the thermodynamic and dynamic drivers of three extensive compound heatwaves in mainland Spain (2011–2024), identifying soil moisture deficit as the primary thermodynamic factor and a persistent large-scale circulation pattern (intense Azores High and warm high-pressure ridge) as the dynamic cause.
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Qi et al. (2025) Spatiotemporal Patterns, Driving Mechanisms, and Response to Meteorological Drought of Terrestrial Ecological Drought in China
This study analyzed the spatiotemporal dynamics and driving mechanisms of ecological drought in China from 1982 to 2022, revealing a significant intensification trend and the dominant roles of evapotranspiration, soil moisture, and air humidity in its development.
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Berényi et al. (2025) Validation of Euro‐ CORDEX Simulations Focusing on Mean and Extreme Precipitation in European Plain Areas
This study assesses the performance of ten historical Euro-CORDEX simulations against observational data for extreme precipitation indices across 14 European plain regions from 1970 to 2005. It finds a general overestimation of precipitation with seasonal and regional biases, but concludes that the models are capable of reproducing historical patterns and the ensemble is adequate for future climate analysis.
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Qiu et al. (2025) Enhancing flood prediction in the Lower Mekong River Basin by a scale-independent interpretable deep learning model
This study develops an interpretable Long Short-Term Memory (LSTM) model for flood prediction in the Lower Mekong River Basin, employing SHapley Additive exPlanation (SHAP) and Universal Multifractal (UM) analyses to identify key contributing variables and their scale-dependent and scale-independent impacts on river discharge. The model demonstrates high predictive power, with interpretations revealing the dynamic influence of soil, vegetation, and hydrometeorological variables on flood events across different temporal scales.
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Mouassom et al. (2025) Convolutional Neural Network‐Based Insights Into Extreme Precipitation Regional Dynamics Over Central Africa Using Moisture Flux Patterns
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Han et al. (2025) Recombining past event precipitation and antecedent catchment states generates unprecedented floods
This study introduces a "perfect storm" approach to generate plausible, unprecedented flood scenarios by recombining historical extreme precipitation events with antecedent catchment soil moisture conditions in Germany, demonstrating that these scenarios can significantly exceed historical flood magnitudes and damages.
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Saeedi et al. (2025) Introducing a new clustering-based method for regionalization framework for continental-scale rainfall estimates from soil moisture dynamics using machine learning methods
This study introduces a novel calibration-free regionalization framework for continental-scale rainfall estimation from soil moisture dynamics, combining unsupervised (K-means) and supervised (rainfall-intensity classification) clustering with a genetic algorithm. The framework, demonstrated with the SM2RAIN-Net Water Flux (NWF) algorithm over the contiguous United States (CONUS), significantly outperforms classical SM2RAIN methods by achieving a 20 % improvement in Nash–Sutcliffe efficiency and a 10 % reduction in root mean square error.
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Anker et al. (2025) Integrative Runoff Infiltration Modeling of Mountainous Urban Karstic Terrain
The study proposes a refined hydrological modeling procedure for urban karstic watersheds by integrating optimal DEM resolution and land use classification within a GIS-HEC-HMS framework to accurately predict runoff volume and discharge.
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Liu et al. (2025) Global Evapotranspiration Retrieval Using Fengyun‐3D Passive Microwave Measurements With Genetic Algorithm Optimization
This study developed a new global evapotranspiration product ($ET_{FY3D}$) by using a genetic algorithm to optimize a passive microwave retrieval method based on FY-3D satellite observations.
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Lee et al. (2025) Multiple Cloud Feedbacks in a Global Model From a Single Perturbation Experiment
This study demonstrates that different implementation choices for calculating cloud feedbacks within a single GEOS model perturbation experiment lead to a wide range of resulting feedback values.
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Zhang et al. (2025) Cascading Spatial Scales in the Hydrological Cycle Over Africa
This study quantifies the spatial scales of precipitation, soil moisture, and vegetation across Africa from 2016 to 2023 to investigate the existence of a spatial cascading link in the hydrological cycle. The results demonstrate that spatial scales increase sequentially from precipitation to soil moisture to vegetation, with the strongest coupling observed between soil moisture and vegetation.
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Xue et al. (2025) Identifying Forest Drought Sensitivity Drivers in China Under Lagged and Accumulative Effects via XGBoost-SHAP
This study develops a drought sensitivity model for forests in China that incorporates lagged and accumulative effects, using machine learning and spatial analysis to identify the climatic and structural drivers of forest GPP response to drought.
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Ahmed et al. (2025) Vegetation Dynamics and Climate Variability in Conflict Zones: A Case Study of Sortony Internally Displaced Camp, Darfur, Sudan
This study analyzes vegetation dynamics and climate variability around the Sortony IDP camp in Darfur, Sudan, revealing a significant increase in vegetation cover and a reduction in drought severity since 2015.
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Tang et al. (2025) Global change exacerbates water cycle imbalances and intensifies water resource crises
This News Focus article synthesizes recent scientific literature to highlight how global change exacerbates water cycle imbalances and intensifies water resource crises, underscoring the urgent need for integrated management.
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Jana (2025) Developing high-resolution data to assess spatiotemporal patterns of meteorological drought in India (1981–2021)
This study developed a high-resolution (5 km) Standardized Precipitation Evapotranspiration Index (SPEI) dataset for India (1981–2021) to assess meteorological drought, revealing rising temperatures and precipitation, alongside an increasing frequency and severity of droughts, particularly in western and central regions.
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Zhang et al. (2025) Spatiotemporal Dynamics of Drought Propagation in the Loess Plateau: A Geomorphological Perspective
This study analyzes the spatiotemporal characteristics and driving mechanisms of drought propagation from meteorological to agricultural drought in the Loess Plateau. It identifies significant seasonal and geomorphological variations in propagation lags and rates, driven primarily by precipitation, soil moisture, and temperature.
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Carril-Rojas et al. (2025) A Flood Forecasting Method in the Francolí River Basin (Spain) Using a Distributed Hydrological Model and an Analog-Based Precipitation Forecast
This paper proposes a probabilistic flood forecasting tool for the Francolí river basin in Catalonia, Spain, by calibrating the RIBS distributed hydrological model and using analog-method-based rainfall forecasts to generate real-time probabilistic streamflow predictions.
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Diaz et al. (2025) Evaluation of daily stream temperature predictions (1979–2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm
This study developed and evaluated a recurrent graph convolution network to predict daily minimum, mean, and maximum stream temperatures across over 50,000 stream reaches in the contiguous United States (CONUS) for 42 years (1979–2021). The model achieved satisfactory performance with reach-level root mean square errors (RMSE) below 2 °C and robust uncertainty quantification, providing the most spatially complete stream temperature modeling to date for water availability assessments.
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Wang et al. (2025) Development of a Real-Time Irrigation Strategy Based on Cumulative Reference Evapotranspiration (ET0) for Cabbage Cultivation in Paddy-Converted Fields
This study evaluates the use of discarded coir substrates (CS) and an IoT-based automated irrigation system to optimize cabbage production in paddy fields. The findings demonstrate that moderate irrigation levels combined with CS significantly enhance photosynthetic efficiency and crop yield compared to conventional paddy soil.
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Chen et al. (2025) Diurnal Cycle of Extreme Rainfall Over the Dabie Mountain in Summer Under Typical Synoptic Patterns and Associated Mechanisms
This study investigates the influence of synoptic patterns and topography on extreme summer rainfall in the Dabie Mountains from 2008 to 2020, identifying two distinct patterns (P1 and P2) that modulate rainfall duration and intensity.
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Liu et al. (2025) Time of Emergence of Record‐Shattering Compound Heatwave‐Extreme Precipitation Events and Their Socio‐Economic Exposures
This study quantifies the global time of emergence (ToE) for record-shattering compound heatwave-extreme precipitation events (CHEPs) and assesses the associated socio-economic risks. It finds that while the majority of global areas will experience these events by 2100, the poorest regions face the most significant population and GDP exposures.
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Zhang et al. (2025) RiceStageSeg: A Multimodal Benchmark Dataset for Semantic Segmentation of Rice Growth Stages
The paper introduces RiceStageSeg, a multimodal UAV-based benchmark dataset of RGB and multispectral imagery for rice growth stage segmentation, demonstrating that multimodal fusion improves identification accuracy.
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O'Sullivan et al. (2025) Efficient Likelihood and Machine‐Learning Models for Spatiotemporal Rainfall Estimation and Imputation
The study develops and evaluates a likelihood-based imputation method and a DeepKriging approach to efficiently handle missing values in large spatiotemporal precipitation datasets.
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Huang et al. (2025) Thermodynamical and Dynamical Background Characteristics and Microphysical Structures of the Mesoscale Convective Systems Over the Tibetan Plateau: A 7‐Year Statistic
This study analyzes the vertical structure of Tibetan Plateau mesoscale convective systems (TP_MCSs) using a 7-year database, ERA5 reanalysis, and satellite data to identify the thermodynamic, dynamic, and microphysical drivers of their intensity and precipitation.
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Mostafazadeh et al. (2025) Variability in Time and Space: Flow Regimes and Seasonality Indices in the Mountainous Rivers of Northern Iran
This study analyzes the spatiotemporal variability of river flow seasonality in northern Iran using the Seasonality Index (SI), finding that the northeastern region exhibits the highest seasonality driven by snowmelt.
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Pan et al. (2025) Intraseasonal Variations in Spring East Asian Subtropical Jet: Role of Mid–High Latitude Wave Trains and Influence on Rainfall Anomalies in China
This study identifies eight phases of the spring East Asian subtropical westerly jet (EAWJ) intraseasonal variability and demonstrates that its northward shift significantly increases precipitation and extreme weather events in the Yangtze–Huai River valley.
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Qin et al. (2025) Warm Rain Processes Affected by Explosion: Insights From First 3D Large‐Eddy Simulation and Implications for Weather Modification
This study utilizes a coupled explosion and 3D large-eddy simulation model to demonstrate that explosions in warm cumulus clouds accelerate rain formation while simultaneously reducing maximum rain intensity.
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Werner et al. (2025) Impact of emerging compound droughts on forests: A water supply and demand perspective
This review examines the physiological and ecological mechanisms of tree and forest responses to compound droughts—characterized by co-occurring soil drought, high temperatures, and elevated vapour pressure deficit—to understand the drivers of global forest die-offs.
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Jahangir et al. (2025) Comparison of different distributive functions based on drought indices: SRI and SSI in the Anzali watershed
The study evaluates the most suitable cumulative distribution function for calculating drought using the Surface Runoff Index (SRI) and Standardized Surface Flow Index (SSI) within the Anzali watershed. It concludes that the Gamma distribution is the most appropriate for these indices in the study area.
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Jarrett et al. (2025) Application of SAR to Delineate Peatland from Other Land Cover and Assess Relative Condition in Relation to Surface Moisture
This study demonstrates that Sentinel-1 SAR backscatter intensity can be used to delineate peatland from other land covers and assess its condition, particularly when utilizing imagery captured during frozen conditions.
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Rahman et al. (2025) Flood susceptibility mapping using supervised machine learning models: insights into predictors’ significance and models’ performance
This study evaluates six supervised machine learning models to map flood susceptibility in the transboundary Kabul River Basin, identifying XGBoost as the most accurate predictive model.
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Simeón et al. (2025) Assessment of Water Depth Variability and Rice Farming Using Remote Sensing
This study evaluates the relationship between Sentinel-2 reflectance and water depth in rice fields in Valencia, Spain, demonstrating that NIR band anomalies during the tillering stage can effectively indicate final yield deviations.
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He et al. (2025) Seasonal and Interannual Variations in Hydrological Dynamics of the Amazon Basin: Insights from Geodetic Observations
This study analyzes spatiotemporal terrestrial water storage (TWS) changes in the Amazon Basin from 2002 to 2021 using GRACE and GNSS data, concluding that ENSO-driven precipitation anomalies are the primary drivers of interannual hydrological variability.
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Yan et al. (2025) Simulating Continental Dust on a Hard Snowball Earth: 1. Limited Dust Emission
This study simulates continental dust emissions during the "snowball Earth" period, finding that emissions were significantly lower than previously estimated due to the suppressive effects of ice and frozen soil.
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Ghosh et al. (2025) Change in convection and thunderstorm occurrences over the Indian subcontinent during the COVID-19 pandemic
This study utilizes the 2020 COVID-19 lockdowns as a natural experiment to demonstrate that reduced anthropogenic aerosols in the Indian subcontinent increased thunderstorm frequency via radiative destabilization, while simultaneously decreasing the electrification (lightning flashes) of individual storms.
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Feng et al. (2025) Modeling and Spatiotemporal Analysis of Actual Evapotranspiration in a Desert Steppe Based on SEBS
This study utilizes the Surface Energy Balance System (SEBS) model and Landsat-8 imagery to accurately quantify actual evapotranspiration (ET) in arid desert steppe ecosystems, demonstrating superior accuracy compared to MOD16A2 products.
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Vogel et al. (2025) Do Observations Support Ideas Behind Common Mass Flux Closures?
This study evaluates two common cloud-base mass flux closure models using EUREC4A campaign data, concluding that Turbulence Kinetic Energy (TKE) is the primary driver of mass flux variability.
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Sousa et al. (2025) Evaluating Distributed Hydrologic Modeling to Assess Coastal Highway Vulnerability to High Water Tables
This study evaluates the suitability of the GSSHA model for simulating groundwater dynamics in coastal roads in Alabama, demonstrating its effectiveness in predicting saturation during extreme precipitation events.
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Drift et al. (2025) Dependence of Convective Precipitation Extremes on Near-Surface Relative Humidity
This study uses convection-resolving simulations to demonstrate that reducing near-surface relative humidity (RH) weakens convective precipitation extremes through thermodynamic, dynamic, and precipitation efficiency mechanisms.
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Niu et al. (2025) Machine‐Learning (ML)‐Physics Fusion Model Accelerates the Paradigm Shift in Typhoon Forecasting With a CNOP‐Based Assimilation Framework
The study develops a hybrid forecasting system integrating the FuXi machine-learning model with the physics-based Shanghai Typhoon Model (SHTM) to improve short-term predictions of typhoon track, intensity, and precipitation.
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Zhou et al. (2025) Groundwater Level Estimation Using Improved Transformer Model: A Case Study of the Yellow River Basin
This study compares an enhanced Transformer deep learning model with an LSTM model to estimate long-term groundwater levels in the Yellow River Basin, demonstrating that the Transformer model significantly improves estimation accuracy.
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Chen et al. (2025) Alternative Interpretation of MJO Teleconnection via Dynamical Mode Decomposition
This study employs Dynamical Mode Decomposition (DMD) to analyze Madden–Julian oscillation (MJO) teleconnections, interpreting them as a spatiotemporal resonance between MJO forcing and the atmosphere's internal unforced dynamics.
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Franch-Pardo et al. (2025) Geospatial Technologies in Crisis Response: Analyzing the 2024 Floods in Valencia, Spain
This study systematically reviews and critically analyzes the application of geospatial technologies in forecasting, documenting, and managing the catastrophic October 2024 floods in Valencia, Spain, demonstrating their crucial role as the primary reliable information source post-disaster while exposing significant institutional failures in territorial planning and vulnerability protection.
