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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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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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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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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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Ibáñez et al. (2025) Evaluación de un modelo de estimación de evapotranspiración en una cuenca seca
This study evaluates and compares two global climate datasets (CPC and CFSR) and three evapotranspiration estimation methods (Turc, Papadakis, Thornthwaite) for hydrological balance in the Napostá Grande basin, recommending CPC data and Papadakis/Turc methods for accurate hydrological modeling.
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Llano (2025) Classic and innovative trend analysis of long term annual precipitation in Argentina
This study analyzed long-term annual precipitation trends across 49 stations in Argentina (1959-2020) using Mann-Kendall and Innovative Trend Analysis (ITA), finding an overall increase in precipitation and demonstrating ITA's superior ability to detect significant trends, especially in extreme values.
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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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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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Song et al. (2025) Analysis of Flash Drought Occurrence Characteristics in Gangwon Region Considering Meteorological Factors
This study analyzed the occurrence characteristics of flash droughts and general droughts in the Gangwon-do region of Korea from 2015 to 2024 using the Standardized Precipitation Evapotranspiration Index (SPEI), finding that flash droughts constitute approximately 41% of all droughts and are strongly correlated with general droughts, occurring more frequently in inland areas.
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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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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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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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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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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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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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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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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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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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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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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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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.
