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Ferreira et al. (2025) Improving ETa Estimation for Cucurbita moschata Using Remote Sensing-Based FAO-56 Crop Coefficients in the Lis Valley, Portugal
This study assessed pumpkin crop water status and evapotranspiration dynamics in the water-scarce Lis Valley, Portugal, by integrating in-situ soil moisture and electrical conductivity measurements with Sentinel-2 derived vegetation indices. It found that this integrated approach enhances precision irrigation strategies and confirmed the applicability of the FAO-56 method for *Cucurbita moschata* under Mediterranean conditions.
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Zhao et al. (2025) Multidimensional Copula-Based Assessment, Propagation, and Prediction of Drought in the Lower Songhua River Basin
This study assesses, propagates, and predicts multidimensional drought (meteorological, hydrological, agricultural) in the lower Songhua River basin under future climate change scenarios using a coupled modeling framework. It reveals a significant increase in multidimensional drought risk, with varying propagation patterns and thresholds across different climate scenarios.
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He et al. (2025) Hydrological response to land use change under low carbon-optimal economic scenario
This study developed a framework integrating land-use simulation (CA Markov) and hydrological modeling (SWAT) with spatiotemporal regression (GTWR) to assess hydrological responses to land-use change under a low-carbon, economic-optimal scenario in the Dongjiang River Basin. It found that by 2035, land-use changes, primarily farmland conversion to forest, grassland, and construction, lead to increased surface runoff and evapotranspiration, decreased soil percolation and groundwater recharge, with significant spatiotemporal heterogeneity and implications for drought and flooding risks.
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Louis et al. (2025) A new approach in monitoring regional water use efficiency in response to climate variability: a case study in Hungary
This study develops and evaluates a novel biomass soil moisture index (NWUESM) as a simpler and less expensive alternative to the standard regional water use efficiency (RWUEEC) indicator, demonstrating its superior accuracy at 60 cm soil depth for monitoring water use efficiency in northeastern Hungary.
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Jiao et al. (2025) Multi-Layer Soil Moisture Profiling Based on BKA-CNN by Integrating Sentinel-1/2 SAR and Multispectral Data
This study developed a BKA-CNN model integrating Sentinel-1 SAR and Sentinel-2 multispectral data to estimate multi-layer soil moisture (SM) in the Shandian River Basin, achieving high accuracy (R² up to 0.799) across depths from 3 cm to 50 cm, with superior performance compared to single-source data and traditional machine learning models, and demonstrating robust generalization.
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Zhang et al. (2025) Multi-stage flood utilization framework to support ecological flow protection and groundwater recovery mechanisms
This study introduces a multi-stage flood utilization framework that integrates ecological flow protection with groundwater recharge to address water scarcity. The framework significantly improves downstream ecological flow protection by eliminating flow interruptions and enhances groundwater recovery in water-scarce regions.
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Lakshmi et al. (2025) Remote Sensing-Based Monitoring of Agricultural Drought and Irrigation Adaptation Strategies in the Antalya Basin, Türkiye
This study assessed agricultural drought dynamics in the Antalya Agricultural Basin, Türkiye, from 2001 to 2023 using multiple remote sensing indices, revealing recurrent moderate summer droughts driven by minimal precipitation and high temperatures, and proposing adaptation strategies for irrigation efficiency aligned with national water management goals.
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Vila et al. (2025) Potential of thermal imaging for yield and soil water content prediction in leafy vegetables
This study developed predictive models for yield and soil water content in lettuce and arugula by integrating thermal images. The models, based on Crop Water Stress Index (CWSI) and normalized temperature difference (ΔT), demonstrated good performance for yield (R² up to 0.82) and soil water content (R² up to 0.92), providing critical thresholds for efficient irrigation management.
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Zhang et al. (2025) Significant Shifts in Continental Precipitation Sources in the 21st Century
## Identification - **Journal:** Water Resources Research - **Year:** 2025...
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Long et al. (2025) Reconstruction of drought propagation pathways: A global analysis of multitype propagation chains and nonlinear mechanisms
This study reconstructs global drought propagation pathways by combining copula functions, a Bayesian framework, and multi-scale drought indices, revealing that abnormal evapotranspiration often initiates drought and quantifying the nonlinear roles of natural and anthropogenic drivers using interpretable machine learning.
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Rabie et al. (2025) Remote Sensing, GIS, and Machine Learning in Water Resources Management for Arid Agricultural Regions: A Review
This study optimized geospatial data pipeline automation for landscape monitoring in Italy using GeoAI and machine learning on Landsat imagery, demonstrating that the Support Vector Machine (SVM) algorithm achieved the highest classification accuracy for detecting land cover changes over a five-year period.
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Sun et al. (2025) High-resolution streamflow simulation, trend and drought analysis in China (1980–2022): A large-scale routing model based on improved geomorphic functions
This study developed improved geomorphic functions for China and integrated them with the Variable Infiltration Capacity (VIC) model to reconstruct high-resolution streamflow across China from 1980 to 2022. The research revealed an overall increasing streamflow trend in eastern regions, declining trends in western regions, and detailed spatiotemporal characteristics of hydrological droughts, including a contraction in drought extent after 2013.
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Xiao et al. (2025) Quantitative identification of drought dominant periods and driving factors in China: integrating from TVDI and pixel-wise EMD
This research quantifies the multi-scale driving mechanisms of drought in China from 2000 to 2022 using the Temperature-Vegetation Drought Index (TVDI) and pixel-wise Empirical Mode Decomposition (EMD), revealing that precipitation drives seasonal drought, potential evapotranspiration dominates interannual drought in arid regions, and maximum temperature is crucial for interdecadal drought, with its influence increasing for longer drought periods.
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Zelalem et al. (2025) Assessment of deep-water wells drawdown: A case study of legedadi deep well field phase I, Addis Ababa, Ethiopia
This study assessed groundwater sustainability and operational performance in the Legedadi Deep Well Field Phase I, Addis Ababa, Ethiopia, revealing significant groundwater drawdown, low pump efficiencies, high energy consumption, and operational inefficiencies exacerbated by SCADA system failure.
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Wang et al. (2025) Spatially synchronized structures of global hydroclimatic extremes
This study develops DOMINO-SEE, a multilayer event-based complex climate network framework, to analyze global synchronizations of meteorological droughts, pluvials, and drought-pluvial 'seesaw' extremes using 67 years of precipitation reanalysis data. It reveals pronounced spatial asymmetries in teleconnected synchronizations, dominated by oceanic regions and southern mid-latitudes, and highlights significant cross-hemisphere seesaw patterns affecting global breadbasket regions.
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Monte et al. (2025) Skilful seasonal predictions of droughts in the Mediterranean region
This study investigates the skill of seasonal prediction systems (SPSs) in forecasting meteorological drought in the Mediterranean region using SPI3 and SPEI3 indices. It demonstrates that optimized multi-model ensembles (MME) significantly enhance drought prediction skill, outperforming individual systems and climatology across most of the region.
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Chang et al. (2025) Historical evolution and future trend of meteorological drought in the upper Yangtze River basin
This study analyzed historical (1961-2018) and projected future (2019-2099) meteorological drought trends in the upper Yangtze River basin using SPI and SPEI and CMIP6 models, finding a historical intensification of droughts post-2000 and a projected transition to significantly drier conditions with more frequent, longer, and more intense droughts after 2040 under higher emission scenarios.
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Fu et al. (2025) Response of dry-wet abrupt alternation to precipitation variation in the Hailar River Basin, northern China
This study investigates dry-wet abrupt alternation (DWAA) events in the Hailar River Basin (1980–2019) using a novel Soil Moisture Concentration Index (SMCI) and the VIC hydrological model. It reveals that DWAA driving mechanisms are spatially heterogeneous, shifting from terrestrial factors upstream to meteorological factors downstream, with an overall increasing intensity of dry-wet transitions.
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Jiang et al. (2025) Crop water origins and hydroclimate vulnerability of global croplands
This study uses satellite-derived water isotope observations and physical models to trace atmospheric moisture origins for global rain-fed crops, revealing that regions heavily dependent on land-originating moisture (fraction of land-originating rainwater, f ≥ 36%) are significantly more vulnerable to hydroclimate stress and drought, impacting major staple crops.
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Khadke et al. (2025) Vapor pressure deficit dominates sap flow variability across forest biomes
This study investigates the causal drivers of sap flow (SAPFlow) across 15 global forest sites using information theory-based process networks and wavelet analysis. It finds that vapor pressure deficit (VPD) is the dominant causal driver of SAPFlow variability across all forest types, forming a coupled system with soil water content (SWC) mediated by land-atmosphere feedback.
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Fashoto et al. (2025) Anticipating drought: enhancing prediction models and assessing environmental impact in Eswatini’s Maguga Basin
This study developed and compared drought prediction models for Eswatini's Maguga Basin, finding that a Genetic Algorithm (GA) optimized Long Short-Term Memory (LSTM) model significantly outperformed the Auto-regressive Integrated Moving Average (ARIMA) model in forecasting the Standardized Precipitation Evapotranspiration Index (SPEI) and Maguga Dam water levels. The research provides a robust tool for early drought warning and water resource management in the region.
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Tripathy et al. (2025) Spatiotemporal dynamics of surface and rootzone soil moisture droughts
This study employed a Complex Network framework and event synchronization to analyze summer surface and root-zone soil moisture droughts across the contiguous United States, identifying the Ohio River Valley as a central drought hub and revealing a west-to-east propagation pattern with stronger spatial coherence in root-zone soil moisture.
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Florea et al. (2025) The Impact of Climate Change on Eastern European Viticulture: A Review of Smart Irrigation and Water Management Strategies
This review synthesizes the impacts of climate change on Eastern European viticulture, highlighting increased water stress and phenological shifts. It emphasizes the critical role of integrating climate adaptation measures with smart irrigation and water management strategies, such as Regulated Deficit Irrigation (RDI) and sensor-based systems, to enhance vineyard resilience and sustainability.
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Lei et al. (2025) Synergizing machine learning and modified physical models for hydrology modeling: A case study of modified SIMHYD and TANK models
This study investigates the effectiveness of hybrid hydrological models (HMs) that combine machine learning with original and modified physical models (SIMHYD, TANK) across 569 catchments in the United States. It finds that HMs with modified physical layers offer superior runoff predictability and improved reasoning ability for evaporation and baseflow compared to those with original physical models.
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Liu et al. (2025) Temporal persistence of postfire flood hazards under present and future climate conditions in southern Arizona, USA
This study investigates the temporal evolution of post-fire hydrologic parameters and quantifies changes in flash flood peak discharges under future climate conditions in a 49.4 km² watershed in southern Arizona. It finds that while soil hydraulic properties recover over three post-fire years, climate change-driven rainfall intensification will significantly increase the magnitude and persistence of post-fire flood hazards, potentially doubling the likelihood of 100-year floods by mid-century under medium emissions scenarios.
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Yang et al. (2025) Probabilistic assessment for drought risk: Integrating drought hazard, ecological sensitivity, economic vulnerability, and their coupling coordination
This study developed a robust drought risk assessment framework integrating Eco-DRR capacity and the coupling coordination of drought risk components. Applied to county-level cities in China's three northeastern provinces (2000-2022), the framework revealed generally low/moderate drought hazards, high ecological sensitivity, low economic vulnerability, and low/moderate overall drought risk, with specific spatial patterns and probabilistic classifications for cities.
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Ma et al. (2025) Comprehensive drought detection, spatiotemporal variations, and attribution across different agricultural climate zones in Eastern China using a copula-based drought index
This study developed a novel Copula-based Multivariate Standardized Drought Index (MSDI) to assess drought spatiotemporal variations and attribution across different agricultural climate zones in Eastern China from 2001–2020. Findings reveal a general worsening of drought conditions characterized by a southward shift and increased frequency, intensity, and severity of short-term events, with dominant drivers varying regionally.
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Martínez-Castro et al. (2025) Impact of Extreme Droughts on the Water Balance in the Peruvian–Ecuadorian Amazon Basin (2003–2024)
This study assesses the impact of extreme droughts on the surface and atmospheric water balance of the Peruvian Amazon basin from 2003 to 2024, identifying four extreme drought years characterized by major precipitation deficits, reduced runoff and total water storage, and significant imbalances in both surface and atmospheric water balances.
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D’Ercole et al. (2025) Using daily vegetation and precipitation products to study drought events in the Horn of Africa
This study assesses the capability of high-frequency daily Earth observations (vegetation and precipitation) to detect and monitor meteorological and agricultural drought events in the Horn of Africa, revealing the benefits of daily resolution for capturing short-term wet-dry spells and identifying optimal precipitation products for the region.
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Li et al. (2025) Assessing the Impact of Land‐Use Types on Historical Dryness/Wetness Trends Over Global Land Areas
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Chivangulula et al. (2025) The Drought Regime in Southern Africa and Recent Climate Change: Long-Term Trends in Climate Elements, Drought Indices and Descriptors
This study assessed long-term climate trends and drought hotspots in Southern Africa (1971-2020) using ERA5 data, revealing widespread increasing temperatures, decreasing precipitation, and expanding drought risk in agriculturally vital regions.
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Yang et al. (2025) Divergent Drought Paradigms and Their Driving Mechanisms in the Yangtze and Yellow River Basins
This study compares drought patterns and their underlying mechanisms in China's Yangtze and Yellow River Basins (1961-2022), revealing the Yangtze experiences high-frequency, short-duration droughts driven by precipitation deficits, while the Yellow River faces low-frequency, long-duration droughts amplified by evaporative demand.
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Çıtakoğlu et al. (2025) Multiscale drought forecasting via temporal–spectral decomposition and machine learning integration
This study developed a novel multiscale drought forecasting framework by integrating temporal–spectral decomposition techniques with machine learning models to predict the Multivariate Standardized Drought Index (MSDI) at 1-, 3-, and 6-month time scales for the Sakarya region, Türkiye, finding the TQWT-GPR hybrid model to be the most accurate.
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Cen et al. (2025) Improving Remote Sensing Ecological Assessment in Arid Regions: Dual-Index Framework for Capturing Heterogeneous Environmental Dynamics in the Tarim Basin
This study introduces ARSEI and CoRSEI to improve ecological assessment in arid regions, demonstrating ARSEI's enhanced sensitivity to desert dynamics and CoRSEI's ability to capture heterogeneous environmental changes and long-term trends in the Tarim Basin from 2000 to 2023. The findings highlight the importance of differentiated ecological modeling for targeted ecosystem management in hyper-arid environments.
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Brigode et al. (2025) Using century-long reanalysis and a rainfall-runoff model to explore multi-decadal variability in catchment hydrology at the European scale
This study evaluates the capacity of century-long global reanalyses (NOAA 20CR, ERA-20C) to simulate multi-decadal catchment hydrology across over 2000 European catchments using a rainfall-runoff model, finding reasonable performance, especially for mean flows, and revealing significant alternating wet and dry periods.
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Lumban-Gaol et al. (2025) Peat subsidence and dynamics in Midden-Delfland, the Netherlands, from time series InSAR analysis and the SPAMS model
This study estimates and analyzes peat subsidence in the Midden-Delfland region, The Netherlands, using Sentinel-1 InSAR data and the SPAMS model. It reveals an average subsidence rate of −5.4 ± 0.7 mm/year, with irreversible subsidence strongly correlated with dry climatic conditions, particularly during drought periods.
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Gonzalez-Mora et al. (2025) A climate-informed statistical framework to indirectly estimate trends in future seasonal high flows in snow-dominated watersheds using short-term climate variability indices
This study developed a climate-informed statistical framework to indirectly estimate future seasonal high flow trends in snow-dominated watersheds using short-term climate variability indices (SCIs). It found that future high flow variability can be anticipated using highly correlated SCIs, with a single SCI explaining at least 50% of the variability.
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Ochege et al. (2025) Enhancing reference crop evapotranspiration prediction in arid regions: A stacking ensemble learning approach for the Amu Darya basin
This study developed a novel stacking ensemble (stkENS) machine learning model, hybridizing Decision Trees, Generalized Linear Models, K-Nearest Neighbours, and Support Vector Regression, to enhance reference crop evapotranspiration (ETo) prediction in the data-limited Amu Darya basin. The stkENS model significantly outperformed individual base learners, achieving high accuracy (R² > 0.96, RMSE: 0.65 mm d⁻¹) with fewer inputs, providing robust ETo estimates crucial for sustainable water management in arid croplands.
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Alvarenga et al. (2025) Meteorological Droughts in the Paraopeba River Basin: Current Scenarios and Future Projections
This study evaluated the performance of CMIP6 climate models in projecting meteorological droughts in the Paraopeba River Basin using SPI and SPEI indices. The findings indicate a significant intensification of droughts throughout the 21st century, particularly under the pessimistic SSP585 scenario, highlighting the critical role of rising temperatures in exacerbating water deficits.
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Ssembajwe et al. (2025) Assessment and Validation of FAPAR, a Satellite-Based Plant Health and Water Stress Indicator, over Uganda
This study assessed and validated satellite-based Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) as a plant health and water stress indicator over Uganda, finding it to be a robust proxy with strong correlations to established drought and water stress indices. The research revealed increasing photosynthetic activity and FAPAR-centered stress across significant portions of the country, influenced by climatic and land use factors.
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Maryam et al. (2025) Nonstationarity impacts on the assessment of drought conditions across diverse climate zones of Pakistan
This study quantifies the impacts of nonstationarity on drought assessment across diverse climate zones of Pakistan using the Reconnaissance Drought Index (RDI). It reveals significant zonal and temporal shifts in drought and wet conditions, with nonstationarity generally increasing drought severity in northern and agricultural plains and decreasing it in western and coastal regions during the later period (1986–2021).
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García et al. (2025) Electrical Resistivity Tomography and 3D Modeling for Groundwater Salinity Assessment in Volcanic Islands: A Case Study in Los Cristianos (Tenerife, Spain)
This study applies Electrical Resistivity Tomography (ERT) and 3D modeling in Los Cristianos, Tenerife, to characterize groundwater salinity and marine intrusion in a volcanic island setting. The methodology effectively delineates saline horizons, providing objective criteria for sustainable borehole siting for desalination purposes.
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Matthews et al. (2025) Dynamic assessment of rainfall erosivity in Europe: evaluation of EURADCLIM ground-radar data
This study evaluates the ground radar-based EURADCLIM dataset for quantifying rainfall erosivity across Europe, finding that it initially overpredicts erosivity due to radar artifacts but significantly improves with an 80 mm h⁻¹ I30 threshold, offering unique spatial detail for soil erosion prediction.
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Qin et al. (2025) Impact of impervious surface spatial morphologies on urban waterlogging: Insights from a cascade modeling chain at catchment scale
This study investigates how the spatial morphology of impervious surfaces influences urban waterlogging using a cascade modeling chain. It reveals distinct hydrological functions for different road morphologies and static obstruction by buildings, proposing an evidence-based intervention hierarchy that prioritizes road modifications for urban flood resilience.
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Fazli et al. (2025) Quantifying single, compound and cascading climate extremes: Implications for agricultural resilience in California
This study quantifies the spatiotemporal dynamics of single, compound, and cascading climate extremes in California's Central Valley from 1951 to 2025, revealing increasing heatwaves and droughts, northward shifting hotspots, and differential vulnerability for almonds and grapes, which informs agricultural resilience strategies.
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Ganjei et al. (2025) Evaluating climate change impacts on reference evapotranspiration using CMIP6 projections and machine learning in the Aras River Basin
This study evaluated future spatio-temporal trends of reference evapotranspiration (ET₀) in the Aras River Basin, Iran, using CMIP6 projections and machine learning, finding a consistent upward trend in ET₀, especially under the high-emission SSP5-8.5 scenario.
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Şerban et al. (2025) Satellite-based assessment of drought evolution and agricultural stress in Dobrogea, Romania using the Normalized Vegetation Soil Water index (NVSWI)
This study utilized a multi-indicator remote sensing approach to assess agrometeorological drought dynamics in Dobrogea, Romania, from 2001 to 2021, revealing an increased drought frequency and severity, with over 70% of the area experiencing extreme drought in 2020.
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Bista et al. (2025) Local-scale flood hazard projections in historically vulnerable communities
This study developed an integrated hydrologic-hydrodynamic modeling framework to project local-scale fluvial flood hazards in Jackson, Mississippi, finding a significant increase in flood risks under future climate change scenarios, disproportionately impacting vulnerable communities and critical infrastructure.
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Ahmed et al. (2025) A Continental-Scale tracking for mobile drought dynamics across Africa using Multivariate drought Index Fusion
This study proposes a novel Multivariate Drought Index Fusion (MDIF) to dynamically track the spatiotemporal trajectory of mobile drought fronts across Africa from 2000 to 2024, revealing persistent drought hotspots and a dominant northeast-to-southwest propagation pathway.
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Lu et al. (2025) A micro–macro coupled approach to assess urban road traffic flood risk at the city scale
This study developed a micro-macro coupled dynamic risk assessment model, integrating hydrodynamic-hydrological, multi-agent, and system dynamics models, to evaluate urban road traffic flood risk and the effectiveness of mitigation strategies at the city scale. The model demonstrated that comprehensive mitigation measures significantly reduce dangerous vehicles and validate preemptive flood prevention strategies.
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Vicente‐Serrano et al. (2025) Developing science-informed maps and climate service for extreme rainfall in Spain
This study develops the first high-resolution hazard probability maps of extreme precipitation for Spain, integrating them into a national climate service. Using a stationary Generalized Pareto Distribution and universal kriging on long-term daily precipitation data, the maps provide reliable estimates of extreme precipitation quantiles, revealing distinct spatial patterns and supporting decision-making through an interactive online platform.
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Silva et al. (2025) Impact of precipitation variability on erosivity, runoff, and soil erosion in a semiarid basin: a case study from Northeast Brazil
This study investigated the impacts of precipitation variability on rainfall erosivity, runoff, and soil erosion in the Apodi–Mossoró River basin, Northeast Brazil, using climate indices and the SWAT model. Findings indicate a decline in extreme precipitation events and significant spatiotemporal variability in precipitation, which directly influences erosivity, runoff, and soil erosion patterns across the semiarid region.
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Liu et al. (2025) The spatiotemporal characteristics of extreme drought events in China from 1961 to 2022 via a copula function
This study systematically analyzed extreme drought events in China from 1961 to 2022 using the Standardized Precipitation Index (SPI) and copula functions, revealing significant spatiotemporal variations in drought trends and severity across different regions. It highlights increased drought severity in Northeast and South China, while Northwest China and the Qinghai–Tibet Plateau experienced increased humidity.
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Rizk et al. (2025) Environmental hazards of wastewater disposal on groundwater at the West Sohag site, Egypt
This study assessed the environmental impact of wastewater disposal at the West Sohag site, Egypt, using remote sensing and geochemical techniques, confirming significant leakage of sewage water and heavy metals (Zn, Cu, Pb, Cd) into the groundwater aquifer due to insufficient land and high soil permeability. The findings highlight severe contamination risks for local water supplies and public health.
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Granata et al. (2025) The anatomy of drought in Italy: statistical signatures, spatiotemporal persistence, and forecasting potential
This study comprehensively analyzes six-month Standardized Precipitation–Evapotranspiration Index (SPEI-6) time series across Italy using advanced statistical, persistence, clustering, and deep learning methods to characterize drought patterns and improve forecasting, revealing a tripartite drought structure and regional forecasting skill.
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Vallés et al. (2025) SERGHEI v2.1: a Lagrangian model for passive particle transport using a two-dimensional shallow water model (SERGHEI-LPT)
This paper introduces SERGHEI v2.1, a new Lagrangian particle transport (LPT) model coupled with a 2D shallow water model, designed to simulate passive particle advection and turbulent diffusion. The study evaluates the accuracy and computational efficiency of various numerical schemes, concluding that the online Euler method offers the best compromise for large-scale applications.
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Dubey et al. (2025) Entropy theory-based performance appraisal of CMIP6 climate models in regional drought simulation over the Indus River basin: a multifactorial investigation
This study assessed the historical performance of 16 CMIP6 climate models in simulating regional drought and associated meteorological variables over the Indian Indus River basin (1979–2014) using an entropy-based approach, identifying MIROC6, MPI-ESM1-2-HR, and NorESM2-LM as the most suitable models for future climate projections.
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Qiu et al. (2025) Spatiotemporal pattern of terrestrial ecological drought based on ecological water deficit in the Yellow River Basin
This study developed a novel ‘Vegetation-Evapotranspiration-Water Balance’ framework to comprehensively assess the spatiotemporal patterns of terrestrial ecological drought (ED) in the Yellow River Basin (YRB) from 1982 to 2020, revealing a predominantly alleviating drought trend despite increasing ecological water requirements and consumption.
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Poudel et al. (2025) Uncertainty in estimating the relative change of design floods under climate change: a stylized experiment with process-based, deep learning, and hybrid models
This study conducts a stylized model-as-truth experiment across 30 Massachusetts basins to evaluate uncertainty in estimating relative changes of design floods under climate change using process-based, deep learning, and hybrid hydrological models. Findings reveal that structural limitations and equifinality dominate uncertainty in change estimates, which are significantly reduced in variance through regional pooling.
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Hamma et al. (2025) Hydrogeochemical assessment of groundwater for agricultural suitability in the Ksour Mountains, Algeria
This study characterized the hydrogeochemical composition and evaluated the suitability of groundwater for agricultural irrigation in the arid Ain-Sefra region, Algeria, finding it generally suitable but requiring salinity control measures, particularly in downstream areas.
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Ellahi et al. (2025) A framework for spatiotemporal drought analysis using proposed multi-regional weighted aggregative SPI and Bayesian inference
This study develops a novel framework for spatiotemporal drought analysis using a proposed multi-regional weighted aggregative standardized precipitation index (MRWASPI) and Bayesian inference, demonstrating its effectiveness in providing insights into drought severity and patterns for homogeneous regions.
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Azhar et al. (2025) Comprehensive portfolio of adaptation measures to safeguard against evolving flood risks in a changing climate
This review compiles and critically analyzes a comprehensive portfolio of 39 flood adaptation measures, classifying them into four groups and evaluating their advantages, disadvantages, co-benefits, and tradeoffs to inform successful, socially just, practically feasible, and technically sound adaptation strategies against evolving flood risks in a changing climate.
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Zuecco et al. (2025) Trees use predominantly summer water in a pre-Alpine catchment
This study utilized a 6-year isotopic dataset in a pre-Alpine catchment to investigate the seasonal origin of water sources for soil and plants, revealing that beech and chestnut trees predominantly use summer precipitation with rapid water turnover, even during dry years.
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Deng et al. (2025) Modeling the propagation time from meteorological to root-zone soil moisture drought: a case study in Jiangxi Province, China
This study utilized the Variable Infiltration Capacity (VIC) model to quantify the propagation time from meteorological to root-zone soil moisture drought in Jiangxi Province, China. It demonstrated that climate change, particularly higher temperatures, has increased drought frequency and altered propagation times in recent decades, providing insights for water resource management in humid agricultural regions.
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Zhang et al. (2025) Climate warming shortens the propagation time from meteorological drought to groundwater drought over 1960–2100
This study investigates how climate warming influences the propagation time from meteorological drought to groundwater drought in the Ganjiang River Basin from 1960 to 2100, revealing that warming shortens the propagation time for drought onset and center, while prolonging it for drought end, primarily due to increased evapotranspiration and groundwater storage anomalies.
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Tran et al. (2025) A Machine Learning Approach for Improving the Accuracy of Gridded Precipitation With Uncertainty Quantification
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Gallois (2025) Projet Aqui-FR - Phase 4 - Plateforme nationale de modélisation AQUI-FR : Calibration de l’application hydrogéologique "Eaudyssée-Loire" sous forçage SURFEX V8F
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Ji et al. (2025) Distinct hydrologic response patterns and trends worldwide revealed by physics-embedded learning
This study introduces a high-resolution, physics-embedded, big-data-trained hydrologic model to accurately capture global hydrologic response patterns and their shifts. The model reveals widespread and significant shifts in green-blue-water partitioning and baseflow ratios worldwide over the past two decades, with critical implications for flood risks, water supply, and aquatic ecosystems.
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Khare et al. (2025) Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities
This study developed the first 10 m resolution Global Surface Water Extents (GSWE) dataset for 2015–2023 using Sentinel-2 Dynamic World products, estimating 2.5 million km² of permanent and 8 million km² of seasonal waters globally, and providing an operational framework for actionable water information.
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Boisier et al. (2025) Increasing water stress in Chile revealed by novel datasets of water availability, land use and water use
This study evaluates past, present, and future water stress in Chile using novel, national-scale datasets of water availability, land use, and water use. It reveals a steady increase in water stress in central Chile, primarily driven by rising water consumption and reduced availability, projecting permanent megadrought-like conditions and extreme water stress in many basins under adverse climate scenarios.
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Nayak et al. (2025) Regional and vertical scaling of water vapor with temperature over Japan during extreme precipitation in a changing climate
This study investigates the regional and vertical scaling of atmospheric water vapor with temperature over Japan during extreme precipitation events in present and future climates. It finds a strong positive relationship between specific humidity and temperature in the lower atmosphere, with a rate of change of 8.3 ± 2.4% per degree Celsius, indicating increased intensity of extreme precipitation in a warming climate.
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Kelley et al. (2025) State of Wildfires 2024–2025
This report systematically tracks global and regional fire activity for the 2024–2025 fire season, analyzing the causes of prominent extreme wildfire events and projecting their likelihood under future climate scenarios. It found that global fire-related carbon emissions totaled 2.2 Pg C (9% above average) despite below-average global burned area, driven by extreme seasons in South America and Canada, with climate change significantly increasing the likelihood of these events.
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S. et al. (2025) Soil infiltration variability across diverse soil reference groups, textures, and landuse types
This study evaluates the variability of soil infiltration parameters, such as saturated hydraulic conductivity (Ks) and final infiltration rate (ic), across diverse soil reference groups, textures, and land-use types using a global database. It finds that World Reference Base (WRB) soil groups, especially when combined with land-use and texture, are significantly more effective in explaining infiltration parameter variability than soil texture or land-use alone, thereby improving upscaling for hydrological modeling.
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Tang et al. (2025) Multi-indicator comparison in characterizing spatiotemporal patterns of water disasters and corresponding agricultural applications in the Middle-and-lower Yangtze River
This study systematically compared five hydrometeorological indicators to characterize spatiotemporal drought and flooding patterns in the Middle-and-lower Yangtze River Region, revealing increasing trends in both disasters and identifying high-risk zones for cotton and rapeseed, with rapeseed facing significantly higher risks.
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Datta et al. (2025) Assessment of climate change impacts on runoff and hydrological drought risk using the VIC-3L model and four-variate D-vine copulas in the Upper Bhima basin, India
This study developed a novel D-vine copula-based framework, integrated with the VIC-3L hydrological model, to assess climate change impacts on runoff and four-variate hydrological drought risk in the Upper Bhima basin, India. It projects significant seasonal shifts in runoff and an increased frequency of both mild and extreme droughts under future climate scenarios.
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Chu et al. (2025) Increasing ecological drought risks with warming climate over Northwestern China
This study characterizes ecological drought in Northwestern China using a novel standardized ecological water shortage index (SEWDI) under CMIP6 SSP2-4.5 and SSP5-8.5 scenarios, revealing a significant increase in ecological drought risk with warming climate, particularly in western and central regions.
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Qi et al. (2025) Monitoring River–Lake Dynamics in the Mid-Lower Reaches of the Yangtze River Using Sentinel-2 Imagery and X-Means Clustering
This study developed a robust Sentinel-2 and X-means clustering-based method to monitor river-lake dynamics in the Mid-Lower Reaches of the Yangtze River (MLRYR) from 2018-2023, finding overall surface water area (SWA) stability but significant declines in major lakes (Poyang, Dongting, Shijiu) and an increase in Danjiangkou Reservoir, with river networks buffering climatic impacts.
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Montero‐Martínez et al. (2025) How does the influence of wind on the fall speed of raindrops change with altitude?
This study investigates how horizontal wind intensity affects raindrop fall speed and its variability at two distinct altitudes in Mexico. It finds that while mean fall speed changes are not statistically significant, wind significantly increases the dispersion of fall speeds, with a more pronounced effect at lower-altitude coastal sites due to higher air density.
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Kalin et al. (2025) Sub-daily rainfall extremes in Croatia: a basis for improved warning thresholds
This study provides the first comprehensive climatology of sub-daily rainfall extremes across Croatia (1961–2020) to establish an improved basis for rainfall warning thresholds. It reveals distinct regional and seasonal patterns of extreme rainfall and proposes new warning thresholds based on stationary Generalized Extreme Value (GEV) return levels.
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Zhang et al. (2025) Synoptic Origins of Extreme Riverine Floods Over the North China Plain With Focus on the Tail Behaviors
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Alharfouch et al. (2025) Ecohydrological and isotopic insight into Mediterranean montane Scots pines water use dynamics under different wetness conditions
This study investigated Scots pine water use dynamics in a Mediterranean montane environment by integrating high-resolution hydrological monitoring with stable water isotope data. It found that Scots pines predominantly sourced water from winter precipitation tightly bound in small soil pores, even after large convective summer precipitation events, highlighting the critical importance of winter precipitation for sustaining hydraulic functioning in drought-prone ecosystems.
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Huang et al. (2025) Drought propagation in china: Uncertainties originate more from dataset choice than drought index selection
This study quantifies the uncertainties in drought propagation time and probability from meteorological to soil moisture drought across China, revealing that dataset choice contributes more to uncertainty than drought index selection, and identifies SPEI as optimal for minimizing these uncertainties.
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Gómez-Gómez et al. (2025) Impact of climate change on droughts and their propagation in an alpine-semiarid basin in Granada, Spain. Does the snow component help to anticipate adaptation strategies?
This study assesses past and projected climate change impacts on various drought types and their propagation in the Alto Genil Basin, an alpine Mediterranean region in southern Spain, with a focus on the role of snow in early adaptation strategies. Results indicate a significant temperature rise and precipitation decrease, leading to more frequent, severe, and prolonged droughts, particularly in snow-reliant areas, and a reduced lead time for operational drought response.
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Liu et al. (2025) Next-Generation Drought Forecasting: Hybrid AI Models for Climate Resilience
This study developed a hybrid machine learning and deep learning framework for drought forecasting in Inner Mongolia, finding that a Long Short-Term Memory (LSTM) network accurately predicts increased drought severity and variability under high-emission climate scenarios.
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Wang et al. (2025) Discriminating the impact of soil moisture and vapor pressure deficit on vegetation greening over multiple time scales
This study investigated the latent time scales and nonlinear characteristics of global vegetation greening from 1982 to 2020, examining the sensitivity and response mechanisms of Leaf Area Index (LAI) to soil moisture (SM), vapor pressure deficit (VPD), and their interactions across multiple time scales. The findings indicate that LAI and its multi-temporal components are more sensitive to SM than to VPD or their interaction, with these influences exhibiting scale dependence.
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Colleoni et al. (2025) smash v1.0: a differentiable and regionalizable high-resolution hydrological modeling and data assimilation framework
This paper introduces smash v1.0, an open-source, differentiable, and regionalizable framework for high-resolution hydrological modeling and data assimilation. It demonstrates the framework's capabilities in local calibration (median Kling–Gupta efficiency > 0.8 at 3 km resolution) and regionalization (Kling–Gupta efficiency > 0.6 and Nash–Sutcliffe efficiency > 0.6 at 500 m resolution) across various scales and model structures.
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Huerta et al. (2025) Enhancing daily precipitation reconstruction: An improved version of the reddPrec R package
This paper introduces an improved version of the reddPrec R package for daily precipitation reconstruction, featuring enhanced quality control, homogenization, and flexible machine learning models with dynamic covariates. Case studies in Switzerland and Spain demonstrate its superior accuracy in gap-filling and grid creation, and its effectiveness in detecting and adjusting data inhomogeneities.
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Kwon et al. (2025) Synoptic systems influence the effectiveness of spectral nudging in high-resolution simulations of extreme precipitation
This study investigates the effectiveness of spectral nudging (SN) in convection-permitting model simulations of warm-season extreme precipitation in South Korea, finding that SN improves simulations by maintaining synoptic circulations consistent with observations, with its effectiveness depending on synoptic conditions, domain size, and the dominant wave scales of the event.
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Amiranipour et al. (2025) Meteorological and agricultural drought assessments using satellite imagery and machine learning models
This study comprehensively assessed meteorological and agricultural droughts and their interrelationship across Iran using satellite imagery and machine learning, demonstrating robust predictive accuracy for drought early warning and management.
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Filippucci et al. (2025) Development of HYPER-P: HYdroclimatic PERformance-enhanced Precipitation at 1 km/daily over the Europe-Mediterranean region from 2007 to 2022
This study introduces HYPER-P, a high-resolution (1 km, daily) precipitation product for Europe and the Mediterranean basin (2007-2022), developed by downscaling and merging remote sensing, reanalysis, and in situ observations. The merged product, particularly the configuration including ERA5-Land, consistently outperforms individual parent datasets and reference products, especially in regions with sparse gauge coverage and complex topography.
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Ali et al. (2025) Development and application of a novel drought index for regional drought assessment: a case study from Pakistan
This study introduces the Inter-Het Regional Drought Index (IHRDI), a novel drought assessment tool for Pakistan that integrates precipitation data interdependence and heterogeneity using Bayesian networks and square deviation. The IHRDI demonstrates superior performance over existing indices in capturing regional drought conditions and reveals increasing drought trends across most regions of Pakistan.
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Villegas-Vega et al. (2025) Optimization of LSTM networks through neuroevolution for drought forecasting in Mexico
This study proposes DeepGA-LSTM, a neuroevolution-based method using genetic algorithms to optimize Long Short-Term Memory (LSTM) networks for drought forecasting in Mexico. The DeepGA-LSTM consistently outperformed baseline LSTM and CNN-LSTM models in two Mexican regions (Chihuahua and Zacatecas) using SPEI and SPI indices, demonstrating its effectiveness in finding optimal network architectures.
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Sutanto et al. (2025) Future intensification of compound and consecutive drought and heatwave risks in Europe
This study projects the future intensification of single and compound/consecutive drought and heatwave events across Europe and their impacts in Germany under climate change scenarios, finding significant increases in event characteristics and impacts across multiple regions.
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Magnini et al. (2025) Informativeness of teleconnections in frequency analysis of rainfall extremes
This study proposes a reproducible framework to assess the informative content of teleconnections for regional frequency analysis of rainfall extremes in North-Central Italy. It identifies significant spatial patterns of correlation between specific climate indices (WeMOI, EA-WR) and rainfall extreme statistics, demonstrating that climate-informed regional models can improve the goodness-of-fit compared to stationary approaches.
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Wang et al. (2025) Saudi Rainfall (SaRa): hourly 0.1° gridded rainfall (1979–present) for Saudi Arabia via machine learning fusion of satellite and model data
This paper introduces Saudi Rainfall (SaRa), a high-resolution, hourly, gridded precipitation product for the Arabian Peninsula developed using machine learning fusion of satellite and model data. SaRa significantly outperforms 19 other state-of-the-art precipitation products in the region across various evaluation metrics.
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Lakatos et al. (2025) Extreme weather risks for European agriculture (1981–2020): A quantitative review using the E3CI
This study provides the first pan-European, multi-hazard assessment of agricultural climate risks during the growing season (1981–2020) using the European Extreme Events Climate Index (E3CI), revealing significant increases in extreme warm events, drought, and wildfire risk, with distinct zonal and meridional spatial patterns across Europe.
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An et al. (2025) Future projections of wet and dry spells in southern Sweden: The impact of climate model resolution
This study evaluates the performance of five Regional Climate Models (RCMs) with resolutions from 44 km to 3 km in reproducing historical wet and dry spells in southern Sweden and projects future changes under RCP8.5. It finds that the convection-permitting model (CPM) AROME (3 km) outperforms coarser RCMs, projecting increases in wet spells and extreme precipitation intensities, while dry spells show more modest, non-monotonic changes in duration.
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Farchouni et al. (2025) Mapping groundwater recharge potential zones in a semi-arid, anthropogenically modified mountainous basin
This study maps groundwater recharge potential zones (GRPZ) in the semi-arid Tensift basin, Morocco, using a multi-factorial approach combining remote sensing, GIS, Analytical Hierarchy Process (AHP), and stable isotopes for validation. It identifies mountains and piedmonts as primary recharge areas, with moderate potential in irrigated plains and low potential in urbanized zones.
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Khanam et al. (2025) Predictive understanding of socioeconomic flood impact in data-scarce regions based on channel properties and storm characteristics: application in High Mountain Asia (HMA)
This study introduces a novel geomorphologically guided machine learning method to predict socioeconomic flood impacts in data-scarce regions. Applied to High Mountain Asia (HMA), the model effectively identifies flood susceptibility hotspots and their evolution from 1980 to 2020, demonstrating its versatility for ungauged areas.
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Pareja-Quispe et al. (2025) Meteorological Droughts in the Peruvian Andes: Characteristics and Relationships with Climate Variability
This study analyzed the characteristics and likely causes of meteorological droughts in the Peruvian Andes over 83 years using SPI and SPEI, revealing that western regions experience more frequent and intense droughts, primarily linked to positive phases of the Atlantic Multidecadal Oscillation (AMO), positive El Niño Southern Oscillation (Niño 4 region), and negative Tropical South Atlantic (TSA) sea surface temperature anomalies.
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Liu et al. (2025) Understanding copula-based multivariate standardized drought indices for characterizing meteorological, hydrological and agricultural droughts across global land areas
This study systematically evaluates the Copula-based Multivariate Standardized Drought Index (CMSDI) for characterizing meteorological, hydrological, and agricultural droughts across global land areas, demonstrating its applicability and reliability in monitoring diverse composite drought conditions using bivariate and vine copulas.
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Bianchi et al. (2025) Synchrony of Wind, Solar and Hydroelectric Resources Over Argentina and Its Climatic Drivers
This study comprehensively analyzes the interannual complementarity of wind, solar, and hydroelectric resources in Argentina over 38 years, assessing the impact of low-frequency ocean-atmosphere variations. It finds limited complementarity with the current spatial distribution of renewable capacity, emphasizing the significant control of climatic drivers and the need for alternative spatial schemes for future energy development.
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Cruz‐Pérez et al. (2025) Climate Projections and Temperature Evolution in the Canary Islands: High Resolution Analysis at Island Scale
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Nguyen‐Duy et al. (2025) Increasing compound heat and precipitation extremes and population exposure in a warming Vietnam
This study projects future changes in compound heat and precipitation extremes (CHPEs) and associated population exposure across Vietnam using high-resolution climate data and population scenarios. It finds a significant increase in CHPEs and population exposure under warmer scenarios, primarily driven by climate change.
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Deng et al. (2025) Economic consequences of cascading drought-flood events: evidence from central Europe
This study empirically compares cascading drought-flood events (CDFEs) with flood-only events (FEs) in Central Europe, revealing that CDFEs are associated with significantly higher streamflow, deeper water depths, and greater economic losses.
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Keshta et al. (2025) Enhancing Climate Modeling over the Upper Blue Nile Basin Using RegCM5-MOLOCH
This study enhances the RegCM5 climate model with the MOLOCH dynamical core to improve precipitation and temperature simulations over the Upper Blue Nile Basin, finding that the MOLOCH-UW configuration is the most reliable for reproducing regional climate variability.
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Wang et al. (2025) Climate drives observational changes in hydrological extremes across most global regions
This study analyzes changes in drought and flood flows and their dominant drivers across 9,531 global hydrological stations from 1980 to 2014, revealing that most regions experience simultaneous increases (28.14%) or decreases (33.36%) in both extremes, with climate primarily influencing the Southern Hemisphere and human activities dominating specific Northern Hemisphere regions.
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Tong et al. (2025) Evolution and prediction of drought-flood abrupt alternation in mainland China using an improved index
This study develops and validates a daily Drought-Flood Abrupt Alternation Index (DFAI) to overcome limitations of monthly indices, revealing increased DFAA frequency and intensity across mainland China from 1961–2022 and projecting intensified events under future climate change scenarios despite stable or decreasing frequency.
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Brunner et al. (2025) Spatially Compounding Drought‐Flood Events Are Favored by Atmospheric Blocking Over Europe
This study investigates the occurrence, seasonality, and large-scale atmospheric drivers of spatially compounding drought-flood events across Europe using streamflow and precipitation observations. It reveals that these events exhibit strong seasonality, occurring most frequently in winter, spring, and June, and are primarily favored by specific blocking and Zonal weather regimes.
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Aminzadeh et al. (2025) Water storage paradox of reservoir expansion and evaporative losses in the MENA region
This study quantifies the storage capacity and evaporative losses of over 133,700 small agricultural reservoirs (< 0.1 km²) in the Middle East and North Africa (MENA) region from 2016 to 2023, revealing a paradox where high evaporation rates, potentially exceeding 2.4 x 10⁹ cubic meters annually, significantly undermine their storage efficiency despite their crucial role in water supply.
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Cao et al. (2025) Runoff changes and influencing factors in the Nyang River Basin in Xizang
This study developed and evaluated a large-scale Variable Infiltration Capacity (VIC) hydrological model for the high-altitude Nyang River Basin, demonstrating its applicability for runoff simulation and identifying key meteorological and geographical factors influencing runoff volume.
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Shi et al. (2025) Improved soil moisture mapping using an integrated cyclic modeling and bias correction approach
This study developed an integrated cyclic modeling and bias correction approach using an XGBoost model to downscale soil moisture, producing a 500 m resolution product with significantly improved accuracy compared to single-shot modeling.
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Feng et al. (2025) Linkages of Multiple Types of Compound Droughts and Hot Events at the Global Scale
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Hissan et al. (2025) Predicting long-term meteorological drought using random forest and multi-scale drought indices
This study assessed meteorological drought patterns in Pakistan from 1960–2023 using SPI and SPEI at multiple timescales and applied a Random Forest model to predict long-term drought, finding that longer-term indices (SPI-12 and SPEI-12) are the most informative for forecasting.
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Ge et al. (2025) Nonlinear behavior of urban flood peaks in the U.S. Mid-Atlantic region
This study analyzes observed flood peaks in 262 U.S. Mid-Atlantic watersheds, revealing a V-shaped nonlinear relationship where flood peaks initially decrease and then increase with urban development, with a shift around 10% developed area, driven by complex interactions of climate and landscape properties.
