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González-Hidalgo et al. (2026) Is daily extreme rainfall increasing in the Mediterranean basin? A critical review of the evidence
This review synthesizes 175 peer-reviewed studies on daily extreme precipitation trends in the Mediterranean basin (1980-2025), revealing no generalized basin-wide intensification but rather substantial spatial and temporal heterogeneity, with localized increases in some areas and stable or decreasing trends elsewhere.
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Li et al. (2026) Quantifying the uncertainty contribution in runoff projection and the time scale effects
This study quantifies the uncertainty contributions of various factors (modeling chain and internal variability) to runoff projections and explores their time scale effects in the Upper Heihe River Basin (UHRB) and Upper Yalong River Basin (UYRB), China. It reveals that internal variability dominates short-term uncertainty (less than 20 years), while the modeling chain becomes the primary source for longer-term projections (over 35 years).
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Hendrickx et al. (2026) Field‐Scale Soil Moisture Predictions in Real Time Using In Situ Sensor Measurements in an Inverse Modeling Framework: SWIM 2
This study introduces **SWIM 2** (Sensor Wielded Inverse Modeling of a Soil Water Irrigation Model), an irrigation decision support system designed as a digital twin. It integrates real-time soil sensor data and periodic soil samples into an FAO-based soil water balance model using the Bayesian inverse modeling algorithm **DREAM (ZS)**. Validated across 18 vegetable cropping cycles in Flanders, Belgium, the system provides robust 7-day soil moisture predictions with uncertainty estimates, even with minimal prior knowledge and biased sensors.
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Ravbar et al. (2026) Integrated multi-scale ecohydrogeological monitoring of spatio-temporal dynamics in karst critical zones
This paper proposes and assesses an integrated multi-scale ecohydrogeological monitoring approach for karst critical zones, demonstrating its effectiveness in capturing spatio-temporal variability and improving data representativeness in a forested karst aquifer in Slovenia. The study highlights the benefits of this interdisciplinary strategy for understanding complex ecohydrological processes in heterogeneous karst environments.
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Golosov et al. (2026) Field Verification of Erosion Models Based on Studies of Five Small Catchments on the Central Russian Upland
This study verified the WaTEM/SEDEM (for rainfall runoff) and a modified State Hydrological Institute (SHI) model (for snowmelt runoff) against field assessments using soil truncation and radiocesium methods across five small arable catchments on the Central Russian Upland. It found good agreement for average long-term soil erosion rates but identified significant discrepancies in sediment redeposition estimates, particularly in uncultivated areas.
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Cao et al. (2026) Assessing the response of terrestrial water storage to climate warming in China by coupling CMIP6 multi-model ensembles, hydrological model, and machine learning algorithms
This study develops a new framework for comprehensive terrestrial water storage (TWS) projection and attribution in China by integrating CMIP6 multi-model ensembles, a hydrological model, and machine learning algorithms. It projects an intensified water cycle and increasing TWS in most of China, but a declining TWS in western China, with Global Climate Model (GCM) uncertainty dominating projections.
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Tidjani et al. (2026) Applicability of the Lumped GR4J Model for Modeling the Hydrology of the Inland Valleys of the Sudanian Zones of Benin
This study evaluates the applicability of the lumped GR4J model for simulating streamflow in three inland valleys of the Sudanian zone of Benin and assesses the reliability of satellite-based rainfall data. The GR4J model effectively simulates daily discharge, with CHIRPS emerging as the most consistent satellite rainfall product for reconstructing historical streamflow, providing valuable insights for water resource management.
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Wilbanks et al. (2026) Evaluation of streamflow trends and the drivers of long-term change for 33 river basins in the southeastern U.S.
This study assessed long-term (1957–2022) streamflow trends and their drivers across 33 river basins in the southeastern U.S., revealing widespread declines in mean annual streamflows, with spatial variability primarily linked to precipitation patterns and drainage area, while regional temperature and population increases were not directly correlated.
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Rastgoo et al. (2026) Integrated Spatio-Temporal Drought Vulnerability and Risk Assessment in Iran
This study comprehensively assessed the spatio-temporal changes in drought risk across Iran from 2000 to 2019 by integrating climatic, socio-economic, and demographic factors. It found that drought risk increased in 57% of Iran, particularly in the northwest, west, and central regions, while declining in 21% of the area, predominantly in the northern and southern regions of the Alborz Mountains.
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Ding et al. (2026) Three-dimensional identification and attribution of flash and slow agricultural droughts in the North China Plain
This study proposes a novel three-dimensional framework integrating DBSCAN spatiotemporal clustering with Local Transfer Entropy (LTE) to identify and attribute flash and slow agricultural droughts in the North China Plain. It reveals that precipitation deficits are the primary driver of drought occurrences, with flash droughts rapidly intensified by water vapor flux divergence and temperature anomalies, while slow droughts are governed by prolonged precipitation deficits.
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Darouich et al. (2026) Towards sustainable water use in intensive and super-intensive olive orchards of Alentejo across multiple scenarios for present and future climate
This study developed guidelines for improving water use and optimizing irrigation scheduling in intensive and super-intensive olive orchards in Alentejo, southern Portugal, under present and future climate scenarios. It found that water-saving irrigation strategies can significantly reduce water consumption with manageable yield impacts, but climate change will increase irrigation requirements, necessitating adaptive management for sustainability.
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Zheng et al. (2026) Vegetation restoration mitigates meteorological drought on the Loess Plateau
This study quantified the net impact of large-scale vegetation restoration on meteorological drought on the Loess Plateau using a counterfactual modelling framework. It found that despite increased evapotranspiration, vegetation restoration substantially mitigated meteorological drought, primarily driven by favorable climate shifts and reinforced by vegetation structural changes.
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Bianco et al. (2026) A framework for generating catalogues of high-impact UNSEEN flood events
This paper introduces a modular framework that combines ensemble reforecast pooling (UNSEEN approach) with probabilistic impact modeling (CLIMADA) to generate catalogues of physically plausible, high-impact, yet unobserved flood events for European river catchments. The framework's utility is demonstrated in the Panaro watershed, Italy, showing its capacity to anticipate record-breaking historical floods and support disaster management.
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Egli et al. (2026) Detecting anthropogenically induced changes in extreme and seasonal evapotranspiration observations
This study investigates anthropogenically induced changes in extreme and seasonal evapotranspiration (ET) using climate models and observational data. It robustly detects increases in high ET extremes and seasonal mean ET in observational products, particularly in the Northern Hemisphere, indicating an increased risk of flash droughts.
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Sun et al. (2026) Nonuniform variations of drought driven by spatially heterogeneous climate changes
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Bazzi et al. (2026) Observing irrigation using SWOT SAR Ka-band data from daily calibration and validation acquisitions
This study investigates the potential of SWOT Ka-band SAR data to detect irrigation events by analyzing its sensitivity to soil moisture variations over an irrigated grassland site. It found that SWOT Ka-band backscatter is sensitive to irrigation, showing an average increase of 4.3 dB on the day of irrigation, and its near-nadir incidence angle allows penetration through dense vegetation.
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Lu et al. (2026) Applicability of Flash Drought Definitions in China: Verification of Identification in Recent Three Years
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Chen et al. (2026) A hybrid Penman-Monteith and machine learning model for simulating evapotranspiration and its components
This study develops Residual Neural Network–Penman–Monteith (RNN-PM), a novel hybrid model that integrates physical processes with machine learning to accurately simulate and partition evapotranspiration (ET) into soil evaporation and vegetation transpiration. Validated at NEON flux sites, RNN-PM reliably reproduces ET and its components, demonstrating superior performance and generalization compared to existing models.
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Polz et al. (2026) Improving transparency in karst spring discharge and water quality forecasts using interpretable machine learning models in the Eastern Alps
This study enhances the transparency of machine learning (ML) models for karst spring discharge and water quality (UV254) forecasts in the Eastern Alps by employing attribution analysis. It demonstrates that the Transformer model provides the best overall performance, and Deep SHAP reveals significant seasonal variations in the contributions of environmental factors, offering valuable insights for drinking water management.
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González-Cao et al. (2026) Impact of dams on river regime and extreme flow events in MIÑO–SIL river basin (NW of the IBERIAN peninsula)
This study evaluates the long-term impacts of dam regulation, precipitation variability, and land-use change on river flow regimes and extreme flood events in the Miño–Sil River Basin (NW Iberian Peninsula) from 1944 to 2023. It concludes that dam regulation is the primary driver of hydrological alterations, reshaping seasonal flows, decoupling streamflow from precipitation, and conditionally attenuating floods based on reservoir storage.
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Latif et al. (2026) El Niño-Southern Oscillation-driven variability in drought severity across the Upper Indus Basin, Pakistan
This study investigates the influence of El Niño-Southern Oscillation (ENSO) phases on drought severity, precipitation extremes, and consecutive dry days across the Upper Indus Basin (UIB) in Pakistan, revealing significant regional and temporal variability in hydroclimatic conditions driven by ENSO.
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Douville (2026) Faster than expected drying in western Europe: mechanisms, attribution and implications
This study investigates the faster-than-expected drying trend in western Europe (1979–2022) compared to climate model projections, attributing the mismatch primarily to systematic errors in the simulated radiative forcing by sulfate aerosols. Using a Bayesian statistical method, the research constrains CMIP6 projections, revealing a more rapid future drying over the region than previously unconstrained models suggest.
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Adarsh et al. (2026) Analysing the Hydro-Meteorological synchronization of reference evapotranspiration across Indian Mainland using cross recurrence approach
This study analyzed the dynamic behavior and hydro-meteorological synchronization of monthly reference evapotranspiration (ET₀) across 14 agro-climatic zones in India (2000–2020) using Recurrence Quantification Analysis (RQA) and Cross Recurrence Quantification Analysis (CRQA), revealing distinct spatial patterns of ET₀ predictability and varying influences of meteorological drivers across zones.
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Neverre et al. (2026) Balancing drinking water security and conservation: A spatial multi-objective optimization framework for regional groundwater management under global change
This study developed a spatially-explicit multi-objective optimization framework, coupling hydro-economic and high-resolution hydrogeological models, to balance drinking water security and environmental conservation in the Roussillon plain under global change. It found that future demand cannot be fully met under drier climates without violating seawater intrusion constraints, necessitating abstraction redistribution and demand-side management.
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Ning et al. (2026) Forty-year data analysis of droughts and drought-flood dynamics: impacts of cascading reservoirs
This study developed an inflow-driven cascading reservoir release framework within SWAT+ to assess the impacts of coordinated reservoir operations on drought propagation and drought-flood dynamics in the Yangtze River Basin from 1980-2020. It found that cascading reservoirs generally aggravated hydrological drought duration and frequency while decreasing intensity, and had mixed effects on drought-flood abrupt alternations across different river sections.
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Jaefar et al. (2026) Numerical Simulation of Water Transfer in Unsaturated Soils: Evaluating the Effects of Temperature and Root Activity in Water Distribution
This study utilizes a finite element numerical model to analyze how soil temperature fluctuations and root activity influence water redistribution in unsaturated soils. The research demonstrates that thermal gradients significantly impact soil moisture levels and enhance root water uptake (RWU) rates.
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Marengo et al. (2026) Characterisation of the Exceptional Heatwave Conditions Observed in Brazil During the Record‐Hot Years of 2024 and 2025
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Reinecke et al. (2026) The ISIMIP groundwater sector: a framework for ensemble modeling of global change impacts on groundwater
This paper introduces the new ISIMIP Groundwater sector, a framework for multi-model ensemble simulations of global change impacts on groundwater. It outlines the sector's protocol and demonstrates significant inter-model differences in simulated water table depth and groundwater recharge, highlighting the need for ensemble assessments.
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Black et al. (2026) Emerging hotspots of agricultural drought under climate change
This study identifies emerging agricultural drought hotspots in Europe, southern Africa, and the Americas by analyzing soil moisture dynamics and evaporative regimes during specific growing seasons. The findings reveal that drought risk is intensifying through increased frequency and severity, even in regions where future precipitation trends remain uncertain.
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Ji et al. (2026) Three generations of NARCliM: future projections of mean and extreme climate over the CORDEX Australasia domain
This study evaluates future changes in mean climate and 10 extremes using three generations of the NARCliM project, which dynamically downscale CMIP3, CMIP5, and CMIP6 models. Projections consistently show statistically significant increases in maximum and minimum temperatures across all NARCliM generations, while precipitation projections exhibit greater variability, emphasizing the robustness of temperature extremes compared to precipitation.
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González et al. (2026) Variability, Prediction, and Simulation of Rainfall Erosivity Risk in the State of Sinaloa, Northwest Mexico
This study models and estimates the spatiotemporal variability of the Observed Rainfall Erosivity Risk (ORE) index for Sinaloa, Mexico, from 1969 to 2018, proposing a new methodology to predict and simulate ORE for agricultural land management.
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Schiavo et al. (2026) Genetic and Iterative Metaheuristics‐Informed Algorithms for Precision Shallow Groundwater Modeling and Drought Inference
This study performs a comprehensive cross-evaluation of the ISBA land surface model and the mHM hydrological model across 800+ French river basins. The results demonstrate that while both models effectively capture hydrological variability, mHM generally provides superior streamflow simulations due to its multiscale parameterization.
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Clerc-Schwarzenbach et al. (2026) Evaluating E-OBS forcing data for large-sample hydrology using model performance diagnostics
This study evaluates the hydrological efficacy of E-OBS meteorological forcing data for 2682 European catchments by comparing it to eight national/regional CAMELS-like datasets using a bucket-type hydrological model. It finds that E-OBS data generally lead to slightly lower, but still good, model performance compared to national datasets, with performance strongly linked to E-OBS station density, making it a reasonable harmonized option for pan-European large-sample hydrological studies.
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Innocenti et al. (2026) Tidal, hydrological and meteorological contributions to high-water level events in the Saint Lawrence River Estuary: Local responses to regional drivers
This study develops a robust statistical framework using non-stationary harmonic regression and event-based analysis to identify, characterize, and attribute high-water level events in the St. Lawrence River Estuary. It reveals distinct spatial patterns of tidal and non-tidal processes, identifying a transition zone where influences shift from coastal to hydrological drivers, with non-stationary dynamics varying across frequency bands and persisting over different spatial scales.
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Konicek et al. (2026) Assessment of Water Balance and Future Runoff in the Nitra River Basin, Slovakia
This study evaluates 90 years of historical water balance (1931–2020) and projects future runoff (2080–2099) for the Nitra River basin using the BILAN model. The findings reveal that rising temperatures drive significant runoff declines through increased evapotranspiration, with projected annual decreases of up to 35.2% under high-emission scenarios.
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Hu et al. (2026) New insights from the bias-corrected simulations of CMIP6 in Northern Hemisphere’s snow drought
This study bias-corrects CMIP6 Snow Water Equivalent (SWE) outputs to robustly project future Northern Hemisphere snow drought characteristics. It reveals a fundamental shift towards more frequent, prolonged, and severe extreme droughts under high-emission scenarios, primarily driven by reduced snowfall.
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Vasala et al. (2026) Spatially explicit and regionalized quantification of blue and green crop water footprints in a water-stressed river basin
This study develops a regionalized remote sensing framework to quantify blue and green water footprints for major crops in the Upper Cauvery Basin, revealing that while most crops rely on green water, summer paddy and rabi ragi exert significant pressure on blue water resources. The research demonstrates that replacing generalized crop coefficients with real-time vegetation coefficients significantly improves the accuracy of agricultural water management data.
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Soto-Escobar et al. (2026) Developing Intensity-Duration-Frequency (IDF) curves using sub-daily gridded and in situ datasets: characterising precipitation extremes in a drying climate
This study investigates the influence of stationary assumptions and data length on annual maximum precipitation intensities (Imax) in continental Chile using sub-daily gridded and in situ datasets. It reveals significant decreasing trends in Imax across Central Chile, with non-stationary models generally yielding slightly lower intensities, though the impact of data length on Imax values is minor.
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Buccellato et al. (2026) Seasonal hindcasts to assess the hazard of meteorological drought over Europe: A multimodel approach
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Poláková et al. (2026) Intensification of Flash and Long‐Term Droughts in the Danube River Basin: A Multi‐Scale Analysis Using Satellite‐Derived Evaporative Stress Index and Soil Water Index
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Ahmad et al. (2026) Hydro-Climate Variability and Its Implications for Water Resource Sustainability in the Sahiwal Region of Pakistan
This study evaluates hydro-climatic variability and its implications for water resource sustainability in the Sahiwal region of Pakistan, analyzing ten years of rainfall data (2014–2023) to identify trends, predict future patterns, and propose climate-adaptive interventions like rainwater harvesting and managed aquifer recharge. It found significant rainfall variability, a slight declining trend, and a shift towards earlier, more intense monsoon peaks, threatening groundwater and agriculture.
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Zou et al. (2026) Seasonal variation of groundwater flow path induced by freeze‒thaw process drives the changes of DOC export and DOM composition in streams in an alpine catchment, Qinghai‒Tibet Plateau
This study investigates how freeze-thaw induced changes in groundwater flow paths in an alpine catchment on the Qinghai-Tibet Plateau influence dissolved organic carbon (DOC) export and dissolved organic matter (DOM) composition in streams. It reveals significant seasonal variations in groundwater flow, DOC concentrations, and DOM characteristics, demonstrating that groundwater contributes substantially to stream DOC flux, especially during specific periods.
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Luo et al. (2026) Spatial Heterogeneity and Land Use Modulation of Soil Moisture–Vapor Pressure Deficit–Solar-Induced Fluorescence Interactions in Henan, China: An Integrated Random Forest–GeoShapley Approach
This study investigated the fine-scale spatial heterogeneity of soil moisture (SM), vapor pressure deficit (VPD), and solar-induced chlorophyll fluorescence (SIF) interactions, and their modulation by land use/cover change (LUCC) in Henan Province, China. It found that VPD and its geographic interactions predominantly control SIF variability, with LUCC-specific thresholds and sensitivities, highlighting croplands' high sensitivity to VPD and natural lands' greater hydraulic resilience.
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Sauter et al. (2026) Glacier-Atmosphere Interactions and Feedbacks in High-Mountain Regions - A Review
This review synthesizes the current understanding of complex glacier-atmosphere interactions in high-mountain regions, highlighting recent advances in observational and numerical modeling, and identifying future research needs to improve glacier change prediction.
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Çelik et al. (2026) North Atlantic Oscillation modulation of drought and vegetation activity in Türkiye
This study investigates the relationships between the North Atlantic Oscillation (NAO), drought, and vegetation activity in Türkiye, revealing a statistically significant positive NAO trend over the last 40 years linked to increased drought, with vegetation responses varying significantly between natural ecosystems and irrigated agricultural areas.
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Colas et al. (2026) Evaluation of snow conditions modelling for various LCZ types
This study evaluates the impact of improved snow parameterizations, including a multilayer snow model and snow removal, within the Town Energy Balance (TEB) urban canopy model across 9 cold urban sites. It finds that these enhancements significantly improve the simulation of town albedo and energy fluxes, particularly in low-density urban areas, while highlighting remaining challenges for dense city centers.
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Zhang et al. (2026) Overestimation of past and future increases in global river flow by Earth system models
This study refines global water partitioning estimates by combining Earth system model outputs with river flow observations using an emergent constraint approach. It reveals that Earth system models significantly overestimate past and future increases in global river flow, providing more accurate historical estimates and strengthening future projections with reduced uncertainty.
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Reggiani et al. (2026) Post‐Processed CMIP6 Climate Projections for Hydro‐Environmental Risk Assessment in the Middle East and Central Asia
This study evaluates the impact of assimilating satellite-derived Surface Soil Moisture (SSM) and Leaf Area Index (LAI) into the ISBA Land Surface Model to improve the representation of terrestrial water and carbon fluxes. The results demonstrate that joint assimilation significantly enhances the accuracy of root-zone soil moisture and vegetation biomass estimates across various climatic regions.
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Devkota (2026) Innovations for Soil Health and Water Management for Climate-Resilient Dryland Agriculture in the CWANA Region
This study evaluates the quantitative impacts of integrated soil and water management innovations on food security and climate resilience in the CWANA region. The findings demonstrate that scaling practices like conservation agriculture, raised-bed planting, and agrivoltaics significantly improves yields, water-use efficiency, and carbon sequestration.
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Klaho et al. (2026) Spatiotemporal analysis of lower tail precipitation events over the Eastern Middle East using the complex network to capture drought patterns
This study investigates the spatiotemporal dynamics of lower tail precipitation events (LTPEs) and drought patterns in the Eastern Middle East, focusing on Iran, using a complex network framework. It identifies specific regions like Saudi Arabia, southeastern Iran, Pakistan, and Turkmenistan as severe drought clusters, hubs for propagation, or critical pathways, revealing complex synchronization and directional spread of drought.
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Lee et al. (2026) Drought resistance of dams based on propagation analysis: A case study of various multipurpose dams in South Korea
This study quantitatively evaluates the drought resistance of nine major multipurpose dams in South Korea by analyzing the propagation of meteorological drought (MD) to hydrological drought in natural (HDn) and dam-adjusted (HDa) states. It found that dams generally mitigate drought duration and intensity, with six out of nine dams showing high resistance, while others exhibited low resistance or even exacerbated drought conditions.
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Kinglo et al. (2026) Are there biases in borehole databases of weathered basement aquifers affecting their reliability to estimate aquifer productivity?
This study uses a novel numerical stochastic modeling approach to reveal systematic biases in borehole databases of weathered basement aquifers (WBAs) caused by drillers' instructions (discharge target, maximum/minimum depth). It finds that insufficient drilling depth leads to significant underestimation of aquifer productivity and fractured-layer thickness, and that traditional data processing methods fail to account for these biases.
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Ma et al. (2026) Quantitative Assessment of Drought Impact on Grassland Productivity in Inner Mongolia Using SPI and Biome-BGC
This study developed and validated a novel hybrid modeling framework to quantify the interactive effects of drought intensity and duration on net primary productivity (NPP) across Inner Mongolia's grasslands. The framework significantly outperforms conventional models, revealing that drought duration is a stronger driver of productivity decline than intensity, with desert grasslands being the most vulnerable.
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Pierrat et al. (2026) Human contributions to evapotranspiration mitigate swings in dry-to-wet year transitions
This study quantifies how human interventions, primarily irrigation, stabilize California's total evapotranspiration during extreme shifts from drought to record rainfall. The findings reveal that while natural evapotranspiration fluctuates with precipitation, human activity maintains high water consumption in managed lands even during exceptionally wet years.
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Nieto-Cañarte et al. (2026) Estimation of the water balance in the Vinces river watershed office automation and geomatic tools
This study estimates the water balance of the Vinces River basin in Ecuador using office automation and geomatic tools to identify water surplus and deficit patterns. The research reveals a significant annual water surplus of 1,322.97 mm and an irrigation potential of over 422,000 hectares, highlighting a major opportunity for optimized agricultural water management.
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Ekpelikpeze et al. (2026) Water Scarcity Risk for Paddy Field Development Projects in Pre-Modern Japan: Case Study of the Kinu River Basin
This study reconstructs pre-modern river flows in the Kinu River Basin to determine if historical irrigation success was due to natural water abundance or management practices. The findings indicate that while natural flows were insufficient for extensive management during droughts, intensive management could successfully prevent water scarcity.
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Kovacs (2026) Targeting Investment in On-farm Surface Water Storage for Groundwater Conservation
This study develops a hydro-economic optimization model to evaluate the cost-effectiveness of subsidies for on-farm surface water storage as a tool for groundwater conservation. The findings indicate that current subsidies generate a positive social net benefit of $12.32 per acre-foot ($0.01 per m³) after 30 years, significantly increasing aquifer thickness in high-intensity rice-growing regions.
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Patil (2026) Impact of photovoltaic irrigation system
This study evaluates the socio-economic, agronomic, and environmental impacts of adopting photovoltaic irrigation systems (PVIS) by comparing 108 adopters and 115 non-adopters in semi-arid Central India. The research identifies key shifts in cropping intensity, water-use efficiency, and carbon emissions resulting from the transition to solar-powered pumping.
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Sperandio et al. (2026) Water Scarcity Footprint and Economic Feasibility of Precision Irrigation in Short Rotation Coppice for Energy in Italy
This study evaluates the economic and environmental sustainability of precision irrigation in a 15-year-old high-density poplar plantation using Life Cycle Costing (LCC) and Life Cycle Assessment (LCA). The findings indicate that while non-irrigated systems are currently the most sustainable, higher irrigation levels (T3 and T4) may become viable if biomass market values increase.
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Patil (2026) Impact of photovoltaic irrigation system
This study evaluates the multi-dimensional impacts of Photovoltaic Irrigation Systems (PVIS) by comparing 108 adopters and 115 non-adopters in central India. The research quantifies how solar-powered irrigation influences cropping intensity, household economics, and environmental indicators such as CO₂ emissions and groundwater extraction.
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Sanz et al. (2026) Anthropogenically-induced saline wetland recharge drives denitrification: Implications for nitrate attenuation in semi-arid aquifer–wetland systems
This study demonstrates that the hydrogeological shift of hypersaline wetlands from discharge to recharge zones, caused by intensive irrigation, triggers density-driven flow that facilitates heterotrophic denitrification. This process acts as a natural buffer, attenuating high nitrate concentrations in semi-arid aquifer systems.
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Wasti (2026) Conservation Agriculture combined with supplemental irrigation enhances resilience and food security in Morocco’s rainfed drylands
This study evaluates the synergistic effects of Conservation Agriculture (CA) and Supplemental Irrigation (SI) on wheat productivity during an exceptionally dry season in Morocco. The findings demonstrate that CA significantly enhances grain yield and water productivity across all water regimes compared to conventional tillage.
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Rajewar et al. (2026) Groundwater depletion in North West India and its response on crustal deformation
The study introduces LDAS-Monde, a global-scale land data assimilation system that integrates satellite-derived soil moisture and leaf area index into the ISBA land surface model. The system significantly improves the monitoring of vegetation dynamics and terrestrial water storage, providing a more accurate representation of the global land surface state.
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Guo et al. (2026) Characteristics of meteorological-hydrological drought propagation in the Yangtze River Basin: dynamic and spatiotemporal variations, 2003–2022
## Identification - **Journal:** Hydrological Sciences Journal - **Year:** 2026...
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Hote et al. (2026) An integrated framework for strengthening local agriculture drought management
This study proposes an integrated framework for agricultural drought management in Balochistan, Pakistan, by combining a district-level socioeconomic vulnerability index with ecohydrological simulations. The findings demonstrate that linking scientific outputs, such as vegetation water content, with socioeconomic data can significantly enhance localized disaster risk reduction and food security planning.
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Yuan et al. (2026) Responses of Vegetation to Atmospheric and Soil Water Constraints Under Increasing Water Stress in China’s Three-North Shelter Forest Program Region
This study systematically assessed the spatiotemporal dynamics of vegetation responses to atmospheric and soil moisture constraints in the Three-North Shelterbelt Forest Program (TNSFP) region of northern China from 2001 to 2022. It revealed a compound water constraint pattern, with increasing vegetation dependence on middle and deep soil moisture, reduced response times to water stress, and a stronger influence of air temperature over precipitation on vegetation–water relationships.
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Lou et al. (2026) Divergent Mechanisms Drive Multi‐Decadal Drought Intensification in South America: A Trend Turning Analysis From 1958 to 2023
This study evaluates and compares the performance of the land surface model **ISBA** and the distributed hydrological model **mHM** in simulating river discharge and soil moisture across major French river basins. The research identifies that while both models effectively capture seasonal discharge cycles, mHM's multiscale parameterization provides superior spatial consistency in runoff generation.
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Xu et al. (2026) SMOTE-BN-FLA: enhanced Bayesian network for rainfall-induced flood loss estimation and mechanism decoding in data-scarce regions
This study proposes SMOTE-BN-FLA, an integrated framework combining the Synthetic Minority Oversampling Technique (SMOTE) with data-driven Bayesian Networks (BN) for rainfall-induced flood loss estimation. The framework addresses data imbalance and opaque disaster mechanisms, demonstrating superior accuracy and interpretability in identifying loss drivers compared to conventional methods.
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Abdelhedi et al. (2026) Machine learning prediction of effective porosity and water content in unsaturated zones: application to the Merguellil Basin in the arid Mediterranean region of central Tunisia
This study developed an innovative methodology combining ultrasonic waves and machine learning to accurately predict effective porosity and water content in the unsaturated zone of the Merguellil Basin, central Tunisia, providing crucial insights for groundwater recharge assessment in arid regions.
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Tian et al. (2026) Deriving groundwater storage anomalies based on GRACE data and drought prediction using deep learning
This study analyzes groundwater storage anomalies (GWSA) in Shaanxi Province from 2002 to 2021 using GRACE satellite and GLDAS data to establish a Standardized Groundwater Index (SGI). The research demonstrates that deep learning models, particularly the CNN-LSTM architecture, can predict groundwater drought indices with an average accuracy exceeding 84%.
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Li et al. (2026) Forest loss intensifies meteorological drought in more than half of Earth’s climate zones
## Identification - **Journal:** Science Advances - **Year:** 2026...
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Rodríguez-Castellanos et al. (2026) Disentangling the hydrological implications of the climate 80s effect and water transfers in a large Mediterranean river
This study disentangles the hydrological impacts of the "climate 80s effect" and water transfers on the Tagus River, revealing that climate change-driven reductions in precipitation and increased temperature, combined with the Tagus-Segura Water Transfer, have led to a 76% decrease in middle Tagus streamflow and severe water quality degradation.
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Li et al. (2026) Spatiotemporal evolution and attribution analysis of groundwater drought in the North China Plain: GGDI constructed based on downscaled GRACE GWSA
This study develops a high-resolution (0.05°) groundwater drought assessment framework for the North China Plain by downscaling GRACE satellite data, revealing a significant storage decline of -17.81 mm/yr and identifying anthropogenic extraction as the primary driver of drought.
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Thakare et al. (2026) Climate Change Impacts on Agriculture for Dhule District, in Maharashtra
This study evaluates the performance of the ISBA and mHM land surface models in simulating river discharge and soil moisture across France. The results demonstrate that mHM’s multiscale parameterization significantly improves discharge simulation and spatial consistency compared to the physics-based ISBA model.
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Wang et al. (2026) Integrated analysis of groundwater storage dynamics and drought migration in the Tarim River Basin
This study quantifies a significant long-term groundwater depletion rate of −8.6 mm/year in the Tarim River Basin from 2002 to 2024. It reveals a 250 km southeastward migration of groundwater drought centers driven by the combined pressures of glacier retreat and intensive agricultural irrigation.
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Li et al. (2026) Dynamic analysis of drought propagation in the context of climate change and watershed characterization: a quantitative study based on GAMLSS and Copula models
This study quantitatively analyzed the dynamic propagation of meteorological to hydrological drought in the Luanhe River Basin under climate change, using GAMLSS and Copula models to assess the influence of climatic factors and watershed characteristics. It found that non-stationary drought indices better capture propagation dynamics, showing increased hydrological drought probability and thresholds, especially in spring and winter, driven by large-scale climate indices and meteorological elements, further modulated by watershed characteristics.
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Paola et al. (2026) The May 2023 flood in Emilia-Romagna and 50-year trends in extreme precipitation based on ERA5-Land
This study analyzes the extreme precipitation events of May 2023 in Emilia-Romagna, Italy, and places them in a multi-decadal context by deriving long-term (1974–2023) precipitation trends from ERA5-Land reanalysis. It finds that while overall wet hours have decreased and precipitation has become more fragmented, the intensity and frequency of the most extreme precipitation events have increased, consistent with thermodynamic expectations.
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Zhang et al. (2026) Changes and driving factors of compound droughts in China based on the soil-atmosphere compound drought index
This study develops the Soil-Atmosphere Compound Drought Index (SACDI) to quantify the concurrent stress of low soil moisture and high vapor pressure deficit across China from 1982 to 2020. The research identifies a transition from drought intensification to alleviation after 2007, driven primarily by temperature fluctuations and atmospheric circulation anomalies.
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Sahu et al. (2026) Evaluation of microphysics and boundary layer schemes for simulating extreme rainfall events over Saudi Arabia using WRF-ARW
This study evaluates 36 combinations of planetary boundary layer (PBL) and cloud microphysics (MP) schemes within the WRF-ARW model to simulate 17 extreme rainfall events (EREs) over the Arabian Peninsula, identifying the Thompson-Yonsei University (MP8_BL1) combination as generally the best performer for rainfall and other meteorological variables.
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Adera et al. (2026) Assessing future hydrologic extremes using an integrated hydrology and river operations model in the Russian River watershed
This paper introduces an integrated hydrology and river operations model for the Russian River watershed to assess future hydrologic extremes. The model projects significantly longer and more severe streamflow droughts, lower seasonal low flows, and higher peak streamflows under future climate and water use scenarios, underscoring the critical role of reservoir operations in mitigating these impacts despite decreased reliability at Lake Mendocino.
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Sun et al. (2026) Interdecadal variability and future persistence of meteorological drought in Yunnan, Southwest China (1961–2021)
This study investigates the interdecadal variability and future persistence of meteorological drought in Yunnan, Southwest China, from 1961 to 2021. It reveals a persistent drying trend with an abrupt shift around 2002, projected to continue for the next three decades, driven by a combination of climatic and anthropogenic factors.
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Houmma et al. (2026) Seasonal forecasting of dam water resources using optimized hybrid models under unprecedented drought conditions
This study developed optimized explainable artificial intelligence (XAI) models for monthly forecasts of water resource variations at the Al Massira dam in Morocco. It found that Bayesian probabilistic Long Short-Term Memory (ProbLSTM) and Generalized Additive Models (GAM) consistently outperform Light Gradient Boosting Machine (LightGBM) for seasonal forecasting, especially under unprecedented drought conditions.
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Panda et al. (2026) Assessing meteorological drought indices for monitoring agricultural drought using SPEI: a remote sensing approach
This study compared seven meteorological drought indices against the Standardised Precipitation Evapotranspiration Index (SPEI) to identify suitable proxies for agricultural drought in a tropical river basin using remote sensing data, finding that SPI and CZI are the most reliable alternatives when evaluated comprehensively.
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Chen et al. (2026) High spatiotemporal resolution monitoring of crop water stress across the contiguous United States using Harmonized Landsat and Sentinel-2 data
This study explored the potential of Harmonized Landsat and Sentinel-2 (HLS) data for near-real-time crop water stress monitoring across the contiguous United States (CONUS). It demonstrated that HLS data can provide timely alerts of crop water stress with an overall accuracy of 74.0% and a mean detection lag of approximately 9 days.
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Krogulec et al. (2026) Spatiotemporal assessment of groundwater drought in a river valley aquifer using standardized indices in central Poland
This study assessed spatiotemporal groundwater drought patterns in central Poland's Kampinos National Park (1999-2020) using Standardized Precipitation Index (SPI), Standardized Groundwater Index (SGI), and cluster analysis, revealing distinct drought responses between dune (prolonged, moderate intensity) and marsh (rapid, high intensity) environments.
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Keivabu et al. (2026) Monsoon weather and food security in Pakistan
This paper investigates how dry monsoon conditions in Pakistan affect self-assessed food security, finding that drier monsoon seasons significantly increase mild to severe food insecurity, primarily by reducing food quality and diversity, with a disproportionate impact on less educated individuals.
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Darand et al. (2026) Long-term spatiotemporal analysis of variation in soil moisture over Iran
This study analyzed the spatiotemporal variations of surface soil moisture (0–7 cm) across Iran from 1979 to 2024 using ERA5-Land data. The findings revealed an overall decreasing trend in soil moisture, averaging 0.0032 m³ m⁻³ per decade, with the most significant reductions occurring during cold and rainy seasons and in the northeastern regions.
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Penna (2026) Controls on runoff processes in forested catchments worldwide
This study synthesizes data from 691 globally distributed forested catchments to identify the main controls on runoff processes, streamflow response, and streamflow prediction, and how these controls vary with climate. The findings corroborate some existing hydrological theories while challenging others, providing new process-based insights into runoff generation in forested catchments worldwide.
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Tiel et al. (2026) Swiss glacier mass loss during the 2022 drought: persistent streamflow contributions amid declining melt water volumes
This study analyzed the role of glaciers in mitigating the severe hydrological drought in Switzerland during the extremely warm and dry year of 2022. It found that while glaciers significantly buffered water deficits, total meltwater volumes have declined compared to past extreme years due to ongoing glacier area loss, despite higher melt rates per unit area.
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Wang et al. (2026) A multivariate framework to quantify propagation characteristics from soil drought to socio-ecological productivity
This study develops a multivariate framework to quantify how soil moisture deficits propagate into vegetation productivity losses and evaluates the resulting exposure of crops, GDP, and population across China under historical and future climate scenarios. The findings reveal that the proportion of vegetation-loss events triggered by soil drought will increase significantly, with distinct regional shifts in ecosystem resistance and socio-economic vulnerability.
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Bhatia et al. (2026) Regional responses to oceanic variability constrain global drought synchrony
This study analyzed global drought synchrony over 120 years (1901–2020), revealing that while rising temperatures exacerbate drought severity, regional precipitation variability, modulated by oceanic oscillations, limits the global extent of synchronized droughts to a maximum of 1.84% to 6.5% of the total land mass.
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Lian et al. (2026) Climate and land use change driving divergent surface water dynamics in the Northern China agro-pastoral ecotone
This study quantifies surface water dynamics in Northern China's agro-pastoral ecotone (APE) from 1986-2020, revealing a net surface water loss and divergent watershed trends where anthropogenic interventions, especially irrigation and revegetation, have become more influential than climatic drivers in reconfiguring water distribution.
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Shan et al. (2026) Spatial-temporal dynamics of meteorological and groundwater drought in Northwest China: Propagation, threshold, recovery time, drivers
This study investigated the spatial-temporal dynamics of meteorological and groundwater drought propagation, thresholds, recovery times, and driving factors in Northwest China from 1960 to 2024. It found that extreme meteorological droughts predominantly trigger groundwater droughts, with climate change and human activities being the strongest drivers, highlighting the need for differentiated groundwater management.
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Posa et al. (2026) A spatiotemporal analysis of hydro-meteorological factors driving floods
This study investigates the spatiotemporal hydro-meteorological drivers of Annual Maximum Floods (AMF) across major Indian river basins, revealing that AMFs are frequently caused by heavy rainfall events smaller than Annual Maximum Rainfall (AMR) and are significantly amplified by antecedent catchment conditions like high baseflow and soil moisture, challenging traditional rainfall-centric flood estimation.
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John et al. (2026) Bottom-up assessment of climate change vulnerability of a large and complex river basin using emulator models
This study conducts a bottom-up climate vulnerability assessment for the Murray-Darling Basin using computationally efficient machine learning-based emulator models. It reveals significant system sensitivities, non-linearities, and a critical threshold of 15% precipitation reduction, beyond which environmental targets are severely compromised.
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Kim et al. (2026) A structural correction to atmospheric evaporative demand narrows the gap between offline aridity diagnostics and Earth system model projections
This study demonstrates that the divergence between offline aridity diagnostics and Earth system model (ESM) projections is primarily due to structural inconsistencies, specifically the violation of precipitation-potential evapotranspiration independence caused by land-atmosphere feedbacks. A thermodynamic correction using the complementary evaporation principle significantly reduces this bias, bringing offline evapotranspiration trends closer to ESM projections.
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Zhao et al. (2026) Assessment of potential drought hazard in Gansu Province under climate change
This study assesses future drought evolution and ecosystem responses in Gansu Province under CMIP6 SSP2-4.5 and SSP5-8.5 scenarios, proposing a novel drought hazard index (DHI) that integrates instantaneous development and recovery speeds (IDS and IRS). Findings indicate intensifying droughts, accelerated IRS, and varied ecosystem sensitivities, with northwestern Gansu facing increased hazard.
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Rouzies et al. (2026) Comparison of ensemble assimilation methods in a hydrological model dedicated to agricultural best management practices
This study compares three ensemble data assimilation methods (EnKF, ES-MDA, iEnKS) for jointly estimating vertical moisture profiles and soil water retention properties within the PESHMELBA hydrological model. Using synthetic surface moisture images from a virtual agricultural catchment, the research aims to reduce model uncertainties and improve water quality management.
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Kurugama et al. (2026) Augmenting observation network design and assimilation frequency in distributed hydrological models: insights from the LISFLOOD-based hydrological data assimilation framework
This study developed a LISFLOOD-based hydrological data assimilation framework (LISFLOOD-HDAF) coupling LISFLOOD with an Ensemble Kalman Filter (EnKF) to evaluate the impact of assimilation frequency and observation network design on streamflow prediction. It found that EnKF consistently improved predictions, with non-monotonic frequency effects and strong dependence on gauge density and placement, enabling cost-effective network design.
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Din et al. (2026) Bayesian geostatistical insights into seasonal variability and spatiotemporal structure of precipitation
This study analyzes the seasonal variability and spatiotemporal structure of precipitation in Punjab, Pakistan, using the Precipitation Concentration Index (PCI) and comparing classical and Bayesian geostatistical methods. It concludes that Bayesian kriging models generally outperform their classical counterparts in spatial modeling of seasonal PCI, with optimal method performance varying by season.
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Abbas et al. (2026) Redundancy‐Resilient Multi‐Criteria Multi‐Model Ensemble Framework for Drought Assessment Under Climate Change
## Identification - **Journal:** International Journal of Climatology - **Year:** 2026...
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Naik et al. (2026) Investigating raindrop size distribution and intensity patterns using disdrometer observations over Pune, India
This study investigates the variability of raindrop size distribution (DSD) and intensity patterns over Pune, India, using disdrometer observations from 2018 to 2022. It reveals that smaller raindrops consistently dominate, with significant annual and monthly variations, and demonstrates that reduced aerosol loading during the COVID-19 pandemic influenced DSD, leading to a higher concentration of larger drops at moderate to high intensities in 2020.
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Zhang et al. (2026) Propagation mechanisms of meteorological to hydrological events in inland river basins of Northwest China: Considering compound climate changes
This study investigated the propagation mechanisms of meteorological to hydrological events in five inland river basins of Northwest China, revealing how compound climate changes modulate drought and flood propagation probabilities and thresholds. It found distinct responses in rainfall-runoff versus snowmelt-runoff dominated basins to climate drying and warming trends over the past six decades.
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Swain et al. (2026) Human-induced temperature rise is driving Africa towards drought-prone climatic conditions
This study identifies human-induced factors as the primary drivers of surface air temperature (SAT) rise and subsequent drought intensification across Africa, attributing a 0.8 to 1.06 °C warming above pre-industrial levels mainly to greenhouse gases and land-use changes, which has shifted the continent towards significantly drier conditions.
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Tian et al. (2026) Freeze-thaw processes induce soil water and salt migration in farmland-ditch systems
This study investigates the two-dimensional migration of water and salt in farmland-ditch systems during seasonal freeze-thaw cycles. It reveals that freezing induces salt recharge from ditches to farmlands, while thawing promotes drainage, characterized by a distinct temporal asymmetry in water-salt exchange.
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Dessers et al. (2026) Hydrological modelling of the 2021 mega-flood in the east of Belgium
This study reconstructs the 2021 mega-flood in Belgium's Vesdre and Amblève catchments using the WOLFHydro platform, demonstrating that models calibrated on historical data significantly underestimate extreme peaks. The research highlights the necessity of flexible modeling frameworks and envelope curves to account for the high uncertainty in "black swan" hydrological events.
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Guo et al. (2026) Global urban vegetation exhibits divergent thermal effects: From cooling to warming as aridity increases
This study performs a comprehensive cross-evaluation of the ISBA land surface model and the mHM multiscale hydrological model to assess their proficiency in simulating river discharge, soil moisture, and terrestrial water storage. The findings highlight that while mHM excels in discharge accuracy due to its spatial parameterization, ISBA provides superior representations of surface-atmosphere energy exchanges.
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Wang et al. (2026) Multidimensional Drought Relationships in the Yangtze River Basin: Causality, Propagation Thresholds, and Drought Resistance Capacity
This study investigates the propagation patterns and thresholds between meteorological, agricultural, and groundwater droughts across the Yangtze River Basin using multi-source data and Copula functions. The findings reveal significant mutual feedback between agricultural and groundwater droughts and identify specific regional thresholds for drought escalation.
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Teku et al. (2026) Optimizing Flood Hazard Zonation and Planning Landscape‐Based Mitigation Measures in Gimba Sub Watersheds, Northeastern Ethiopia: A Comprehensive Approach
This study evaluates and compares the performance of the ISBA land surface model and the mHM hydrological model in simulating water fluxes and energy balances within the hyper-arid Atacama Desert. The research identifies critical model structural differences that impact the quantification of water-related ecosystem services at the terrestrial "dry limit."
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Terekhin et al. (2026) Changes in Climatic Parameters and Moistening Conditions on the South of the East European Plain
This study analyzed long-term climatic changes (late 20th to early 21st century) in the Central Russian Upland, revealing significant warming and a decrease in moistening conditions during the warm season due to contrasting temperature and precipitation trends.
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Guo et al. (2026) Global urban vegetation exhibits divergent thermal effects: From cooling to warming as aridity increases
This study provides the first global assessment of urban vegetation's thermal regulation across 761 megacities, revealing that vegetation can transition from a cooling to a warming agent as aridity increases. In 22% of cities with low annual precipitation, the reduction in albedo and heat storage by vegetation outweighs limited evapotranspiration, leading to net urban warming.
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Kuang et al. (2026) Intelligent diagnosis of winter wheat water stress based on UAV multi-modal remote sensing
This study develops a machine learning-based classification model for winter wheat water stress using UAV-mounted multispectral and thermal infrared sensors. The research demonstrates that fusing vegetation indices with canopy temperature data, particularly using a Support Vector Machine (SVM) algorithm, significantly improves diagnostic accuracy across critical growth stages.
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Karapetyan et al. (2026) Deep vision-based framework for coastal flood prediction under sea level rise and shoreline protection
The study develops a vision-based deep learning framework, featuring a lightweight CNN architecture named CASPIAN, to predict high-resolution coastal flood depths under sea level rise and various shoreline protection scenarios. The framework achieves accuracy comparable to physics-based hydrodynamic models while providing a $10^8$ times increase in inference speed.
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Badaoud et al. (2026) Evaluating the impact of irrigation on groundwater resources using remote sensing: a case study for Saudi Arabia
This study evaluates the impact of assimilating satellite-derived Leaf Area Index (LAI) and Surface Soil Moisture (SSM) into the ISBA-A-gs land surface model to improve the monitoring of vegetation and water variables. The results demonstrate that joint assimilation significantly enhances the representation of biomass and carbon fluxes across various ecosystems.
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Zhang et al. (2026) Spatial Synchronization and Propagation of Soil Moisture Droughts Over China Using Complex Network Theory
This study utilizes complex network theory and random forest models to analyze the spatial synchronization, regional drivers, and propagation pathways of weekly soil moisture droughts across China from 1979 to 2019. The research identifies key drought source and sink regions while quantifying the meteorological and geographical factors influencing drought connectivity.
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Glaser et al. (2026) Partitioning Water Storage in Stream Reaches: Implications for Solute Transport Under Varying Hydrological Conditions
## Identification - **Journal:** Water Resources Research - **Year:** 2026...
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Gopi et al. (2026) Machine Learning (ML)-Based Monthly Streamflow Prediction for a River Basin: A Case Study
This study evaluates five machine learning models for monthly streamflow prediction across three gauge stations in the Godavari River basin, finding that the Long Short-Term Memory (LSTM) model consistently outperforms others with high accuracy.
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Khwairakpam et al. (2026) Enhanced flood quantile estimation and its implications in rainfall–discharge relationship during flood events in Brahmani-Baitarani River basin, India
This study aimed to identify suitable probability distributions for flood quantile estimation and analyze rainfall-discharge relationships in the Brahmani-Baitarani River basin, India. It found that multi-parameter distributions like Wakeby, Log-Pearson 3, and Generalised Extreme Value (GEV) provided the most reliable flood quantile estimates, revealing strong but non-linear rainfall-discharge correlations during flood events.
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Arnaud-Fassetta et al. (2026) When geomorphological field data and systemic analysis help refine the uncertainties of numerical hydrometeorological models in extreme values. Case study: The catastrophic flood event of October 14-15, 2018, in the Aude watershed (southern France)
Anubis is a server-side bot detection and protection system that employs a Proof-of-Work (PoW) scheme, inspired by Hashcash, to deter aggressive AI scraping by increasing the computational cost for mass scrapers while aiming to minimize impact on legitimate users.
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ZAMAN et al. (2026) Flood Frequency and Trend Analysis for Williams River at Tillegra in Hunter Basin New South Wales Australia
This study conducts a flood frequency and trend analysis for the Williams River at Tillegra, Australia, utilizing 93 years of annual maximum flood data to compare various probability distributions and recommend the most reliable for infrastructure design. The findings indicate that Log-Pearson Type III and Generalized Pareto distributions are most reliable for quantile estimation, and no significant long-term trend in flood magnitudes was detected.
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Sguigaa et al. (2026) Retrospective Analysis and Future Projections of Bioclimatic Indices Under Climate Change: The Case of Azilal Province, Morocco
This study analyzes historical (1983-2016) and projected (2015-2100) bioclimatic changes, water balance, and thermal extremes in Azilal Province, Morocco, under CMIP6 SSP2-4.5 and SSP5-8.5 scenarios, revealing significant warming, increasing aridity, and an expansion of "Dry/DTR↑" bioclimatic regimes.
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Elomari et al. (2026) Hydrological Assessment of Climate Change Impacts on the Upper Tassaoute Watershed, Morocco
This study assessed the hydrological impacts of recent climate variability on the Upper Tassaoute Watershed, Morocco, using the HBV model, revealing a significant reduction in streamflow and altered seasonal water availability linked to observed rainfall and temperature changes.
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Andros et al. (2026) Swamp-Eye: a deep learning model for monitoring wetlands change across the globe
This study develops "Swamp-Eye," a deep learning model designed for the rapid and cost-effective monitoring of global wetland extent changes. By training on a diverse, multi-seasonal dataset of coastal and inland systems, the model achieved a 93.7% overall accuracy, providing a generalizable tool for large-scale environmental assessment.
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Wang et al. (2026) Fusing ERA5-Land and SMAP L4 for an improved global soil moisture product (1950–2025)
This study develops a bias-corrected global soil moisture dataset (1950–2025) by fusing ERA5-Land reanalysis with SMAP L4 satellite-based data using a mean-variance rescaling method. The resulting product significantly reduces systematic errors and improves accuracy across diverse climate zones, providing a seamless 75-year record for climate and hydrological research.
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Yoshe (2026) Characterization of Drought Severity Using GRACE and TerraClimate Dataset in the Rift Valley Basin, Ethiopia
This study develops a GRACE-based drought index (GRDI/WSDI) to characterize hydrological drought in the Ethiopian Rift Valley Basin, demonstrating that integrated terrestrial water storage data captures severe deficits and groundwater depletion more effectively than traditional meteorological indices. The findings reveal that droughts in the region have become increasingly frequent and severe, with extreme water storage deficits recorded in 2013 and 2014.
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Cordel (2026) Strategies for enhancing irrigation efficiency on turfgrass areas
This study evaluates the integration of real-time Internet of Things (IoT) sensor networks with the ISBA and mHM hydrological models to enhance the spatial-temporal resolution of soil moisture and streamflow predictions. The findings demonstrate that assimilating high-frequency IoT data significantly reduces predictive uncertainty and improves flood forecasting lead times compared to satellite-only data sources.
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Barmakova et al. (2026) Long-term dynamics of groundwater levels under rice-based irrigation systems in South-East Kazakhstan
This study analyzes over 60 years of hydrogeological monitoring data to characterize the spatiotemporal evolution of groundwater regimes in the Akdala and Karatal rice irrigation massifs. The research identifies a recent trend of declining groundwater levels (0.25–0.45 m per year) driven by water scarcity and reduced rice cultivation, providing a framework for adaptive irrigation management in arid regions.
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Luo et al. (2026) The role of soil moisture on summer atmospheric circulation climatology in the Northern Hemisphere
This study demonstrates that interactive soil moisture significantly alters Northern Hemisphere summer circulation by shifting subtropical jets poleward and amplifying planetary wave amplitudes over land. The findings reveal that soil moisture-atmosphere feedbacks are a primary driver of both mean atmospheric state and temperature extremes.
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Ouikhlef et al. (2026) Impact of climate variability on land use and groundwater resources: A case study of Wadi Fekan, northwest Algeria
This study analyzes 40 years of climatic data in the Wadi Fekan sub-watershed, finding that a shift to a wetter regime after 2000 increased groundwater recharge but failed to offset the hydrologic deficit caused by historical overexploitation.
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Zhao (2026) Data Assimilation and Modeling Frontiers in Soil–Water Systems
This review synthesizes advancements in data assimilation (DA) and coupled modeling for soil–water systems, highlighting the integration of multi-source observations and hybrid physics–ML methods to develop digital twins for sustainable resource management.
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Brito et al. (2026) Climate Resilience Assessment in Regions, Cities, Strategic Services, and Critical Infrastructure: Implementation and Outcomes
The study presents a holistic, web-based resilience assessment framework and platform designed to help metropolitan and rural areas plan for and monitor climate-related hazards using nature-based solutions. Application of the tool in Spain and Austria demonstrated its ability to move regional planning from basic to comprehensive assessment levels.
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Zhang et al. (2026) Warm and wet spring compensated for the reduction in carbon sinks due to an extreme summer heatwave-drought event in 2022 in southern China
This study quantifies the impact of the record-breaking 2022 summer heatwave-drought on carbon sinks in southern China, finding that a warm and wet spring significantly offset summer carbon losses. While the summer event caused a major decline in photosynthesis, the annual carbon sink in the Yangtze River basin remained relatively stable due to this seasonal compensation.
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Jin et al. (2026) Guiding VI selection for phenology monitoring: Differential sensitivity of vegetation indices to temporal dynamics in canopy leaf area and pigment
This study disentangles the influence of canopy structure (leaf area) and leaf biochemistry (pigments) on 21 vegetation indices used for phenology. It identifies that while most indices (e.g., NDII, EVI) track leaf area expansion, a specific subset (e.g., CVI, MTCI) is required to accurately monitor leaf chlorophyll maturation.
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Duvan et al. (2026) Enhancing Drought Prediction in Semi-Arid Climates: A Synthetic Data and Neural Network Approach Applied to Karaman Region, Turkey
This study develops a drought forecasting framework for the semi-arid Karaman region of Turkey by combining synthetic data augmentation (KDE and Cholesky-based reconstruction) with Artificial Neural Networks (ANN). The approach successfully overcomes historical data scarcity, improving prediction accuracy for precipitation and drought intensity by 10–15% compared to traditional statistical models.
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Yang et al. (2026) Knowledge-guided graph machine learning improves corn yield mapping in the U.S. Midwest
The study develops KGML-Graph, a machine learning framework that integrates spatial graph neural networks with temporal deep learning to improve corn yield mapping. By incorporating historical yield correlations as knowledge-guided edge weights, the model significantly outperforms standard temporal models, especially under extreme climatic conditions and in spatial transferability.
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Szanyi et al. (2026) Assessment of Changes in Groundwater Resources Due to Climate Change for the Purpose of Sustainable Water Management in Hungary
This study evaluates the combined impacts of climate change and anthropogenic water extraction on groundwater resources in Hungary's Nyírség region using numerical modeling and remote sensing. The findings indicate that while climate-driven infiltration loss is the primary driver of regional water table decline, managed aquifer recharge (MAR) via subsurface injection offers a viable local mitigation strategy.
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Abbaszadeh et al. (2026) GNSS evaluation of GRACE-assimilated water storage models over 89 river basins worldwide
This study evaluates two global GRACE-assimilated (GA) hydrological models, GLWS2.0 and CLSM-DA, using vertical displacement data from over 9,000 GNSS stations across 89 river basins. The results indicate that CLSM-DA generally provides a more accurate representation of seasonal water storage variations, particularly regarding amplitude in tropical regions and phase timing in mid-latitudes.
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Raji et al. (2026) Coupled land–atmosphere processes exacerbate recent compound drought and heatwaves over Africa
This study identifies a significant intensification of compound drought and heatwave (CDHW) events in equatorial Africa since 2004, driven by a shift toward moisture-limited land–atmosphere coupling and weakened atmospheric vertical motion. The research highlights how self-reinforcing feedback loops between soil moisture depletion and surface warming exacerbate climate extremes in the region.
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Jia et al. (2026) Assessing the Impact of Agrivoltaics on Water, Energy, and Carbon Cycles Using the Community Land Model Version 5
This study develops a process-based agrivoltaic model within the Community Land Model 5 (CLM5) to evaluate how solar panel integration affects water, energy, and carbon cycles. The findings reveal that agrivoltaics can mitigate drought in arid regions by conserving soil moisture, whereas in humid regions, shading significantly reduces crop carbon assimilation.
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Jach et al. (2026) Comparing Temporal Dynamics of Soil Moisture from Remote Sensing, Modeling, and Field Observations Across Europe
This study evaluates the accuracy and temporal variability of ECMWF and SMAP soil moisture products across Europe, finding that while both capture timing well, they consistently overestimate the magnitude of short-term fluctuations.
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Laalaoui et al. (2026) Hybrid Ensemble Learning for TWSA Prediction in Water-Stressed Regions: A Case Study from Casablanca–Settat Region, Morocco
This study develops a hybrid machine learning ensemble to estimate Terrestrial Water Storage Anomalies (TWSA) in Morocco’s Casablanca–Settat region by combining GRACE satellite data with environmental indicators. The framework achieves high predictive accuracy ($R^2 = 0.97$), providing a detailed spatial tool for monitoring groundwater depletion and informing regional water management.
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Savary et al. (2026) Linking European droughts to year-round weather regimes
This study investigates the relationship between North Atlantic weather regimes and European meteorological droughts using a year-round framework. It finds that while atmospheric circulation frequency anomalies significantly drive droughts in Western Europe and during winter, their influence is reduced in Eastern Europe and during summer months.
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Iliopoulou et al. (2026) Complexity of Hydroclimatic Changes in the Mediterranean: Exploring Climate Drivers Using ERA5 Reanalysis
This study analyzes ERA5 reanalysis data (1950–2024) to evaluate Mediterranean hydroclimatic trends, finding significant lower-tropospheric warming and steepening lapse rates while precipitation and evaporation remain primarily governed by wind speed rather than temperature.
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Güiza-Villa et al. (2026) Impacto del riego estimado por satélite en la modelación hidrológica: análisis del balance hídrico y desempeño del modelo TETIS en la cuenca del río Po
This study evaluates the integration of satellite-derived irrigation estimates into the TETIS v9.1 hydrological model for the Po River basin. The research demonstrates that incorporating irrigation data, coupled with model recalibration, significantly improves discharge simulations (particularly low flows) and provides a more realistic representation of the basin's water balance.
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Benito-Verdugo et al. (2026) Impact of flash droughts on cereal crops under Mediterranean conditions
This study characterizes flash droughts (FD) in Mediterranean rainfed cereal regions from 2000 to 2023, demonstrating that these rapid-onset events significantly reduce crop yields by up to 33% and accelerate phenological development. The research highlights that cereals respond to soil moisture deficits within five days, particularly during critical growth stages in spring.
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Karami et al. (2026) Soil moisture estimation at 1-km resolution over croplands and grasslands using sentinel-1/2 and SMOS-IC data: algorithm and validation
This study evaluates the impact of assimilating satellite-derived Leaf Area Index (LAI) and Surface Soil Moisture (SSM) into the ISBA Land Surface Model to improve the representation of vegetation and water cycles. The results demonstrate that joint assimilation significantly enhances the monitoring of biomass production and evapotranspiration across various spatial scales.
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Cairano et al. (2026) Temporal changes in the water quality and ecology of an alluvial aquifer through an agricultural crop cycle
This study investigates the spatial and temporal impacts of an annual cotton cropping cycle on a shallow alluvial aquifer's water quality and biodiversity using eDNA metabarcoding. The findings reveal that irrigation water infiltration alters groundwater chemistry and biotic communities, which exhibit an "ecological memory" of agricultural practices.
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Ankela et al. (2026) Spatiotemporal assessment of maize evapotranspiration and surface energy fluxes under varying irrigation regimes using UAV based METRIC
This study evaluates the effectiveness of the METRIC model adapted for high-resolution UAV imagery to estimate maize evapotranspiration (ET) and surface energy fluxes under different irrigation regimes. The results demonstrate that UAV-based METRIC accurately captures irrigation-induced variability in ET and energy partitioning, showing strong agreement with ground-based validation methods.
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Hill et al. (2026) From reach to catchment-scale impacts: High-resolution hydrodynamic modelling of Nature-based solutions in the Cocker Catchment, UK
This study utilizes a high-resolution, GPU-accelerated 2D hydrodynamic model (HiPIMS) to evaluate the effectiveness of leaky wooden barriers across the 145 km² Cocker catchment. The findings reveal that while Natural Flood Management (NFM) features provide measurable flood attenuation and peak reduction during moderate rainfall events, their impact is significantly diminished during extreme events like Storm Desmond.
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Gambarani et al. (2026) Multi-Year Assessment of Soil Moisture Dynamics Under Nature-Based Vineyard Floor Management in the Oltrepò Pavese (Northern Italy)
This study evaluates the effectiveness of cereal-based rolled cover crops versus mowed spontaneous vegetation in enhancing drought resilience in rainfed vineyards. The findings demonstrate that rolled cover crops improve soil moisture buffering and preserve hydraulic conductivity, though performance is heavily modulated by site-specific soil texture and structure.
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Feng et al. (2026) Optimizing Soil Moisture‐Runoff Coupling Strength With Remotely Sensed Soil Moisture for Improved Hydrological Modeling
The study presents the development and validation of **SIM2**, a high-resolution hydrometeorological reanalysis for metropolitan France covering the period 1958–2022. By integrating the ISBA-CTRIP model with SAFRAN atmospheric forcing, the system provides a significantly improved estimation of river discharge, snowpack dynamics, and soil moisture compared to its predecessor.
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Arivoli et al. (2026) Application of soil moisture probe in optimizing the parameters of a land surface model
This study optimizes the Variable Infiltration Capacity (VIC) land surface model parameters using site-specific volumetric soil moisture probe data in Pantnagar, India, concluding that calibration based on root fraction and Leaf Area Index significantly improves the accuracy of subsurface soil moisture simulation (R up to 0.89, KGE up to 0.80).
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Wang et al. (2026) Optimal groundwater depth thresholds for sunflower in salt-affected farmland: A process-based modeling approach across hydrological years in the Hetao Irrigation District
This study integrates field experiments with the Agro-Hydrological & Chemical (AHC) simulator to determine optimal groundwater depth (GWD) thresholds for sunflower cultivation. The research identifies specific GWD ranges for dry, normal, and wet hydrological years that balance maximum crop yield with effective soil salinity control in the Hetao Irrigation District.
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Vologjanin et al. (2026) Linking intra-annual density fluctuations to early-warning indicators of drought-driven tree mortality in the NE Iberian Peninsula
The study identifies Intra-Annual Density Fluctuations (IADFs) as a superior early-warning signal for drought-driven mortality in *Pinus halepensis* compared to traditional growth metrics. Findings reveal that surviving trees exhibit higher IADF frequency and greater climatic plasticity, allowing them to better adjust to Mediterranean environmental fluctuations.
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Bonet et al. (2026) A user-friendly decision support tool for irrigation scheduling in smallholder olive orchards
This study developed and validated a user-friendly decision support tool (DST) based on the Soil-Atmosphere Adjusted Model (SAAM) to optimize irrigation in smallholder olive orchards. The tool successfully reduced irrigation water use by 11% while maintaining crop yields and physiological health through automated sensor-based feedback.
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Feijoo et al. (2026) Insights into the environmental performance of nature-based wastewater technologies towards water and carbon neutrality
This study performs a comparative Life Cycle Assessment (LCA) of four biological wastewater treatment systems in the Iberian Peninsula to evaluate their environmental performance and progress toward water and carbon neutrality. The results demonstrate that nature-based solutions like constructed wetlands significantly lower the land area required for carbon offsetting compared to energy-intensive membrane-based technologies.
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Slocum et al. (2026) Elevated organic carbon in African Dark Earths is not exclusively attributable to pyrogenic organic matter
This study quantifies the contribution of pyrogenic organic matter to the elevated carbon stocks in West African Dark Earths, finding that pyrogenic carbon accounts for approximately 65% of the carbon increase. The remaining enrichment consists of non-pyrogenic organic matter, suggesting that pyrogenic material promotes the stabilization and persistence of other organic carbon forms.
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Ali et al. (2026) Mitigating nitrous oxide emissions in wastewater treatment with pure oxygen aeration: A full-scale study
This study demonstrates that utilizing pure oxygen aeration instead of conventional air-based systems in industrial wastewater treatment significantly mitigates nitrous oxide ($N_2O$) emissions. Through full-scale field measurements and CFD modeling, the research found that pure oxygen systems can reduce $N_2O$ flux by $67\%$ to over $98\%$ while simultaneously lowering the process energy footprint.
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Varghese et al. (2026) Global compound drought–hot events: insights from a 3D-event based framework, intercontinental synchronization, and the evolving influence of climatic drivers
This study implements a three-dimensional (3D) event-based framework to characterize the spatiotemporal evolution of global compound drought–hot events (CDHEs) from 1951 to 2022. The research identifies a shift in the primary drivers of these events, showing a weakening influence of ENSO and a growing dominance of anthropogenic warming.
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Yu et al. (2026) How much historical data do we need? The role of data recency and training period length in LSTM-based rainfall-runoff modeling
This study investigates the relative importance of training period length and data recency for LSTM-based rainfall-runoff models across 1374 North American watersheds. The findings demonstrate that recent data is more critical for predictive accuracy than long historical records, and the benefits of spatial diversity are significantly enhanced when training on recent observations.
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Rezapour et al. (2026) Enhanced remote sensing of water surface elevation through fusion of Sentinel-3 altimeter data and climate variables using machine learning
This research develops a framework to enhance the monitoring of inland Water Surface Elevation (WSE) by fusing Sentinel-3 satellite altimetry data with climate variables using machine learning. The approach aims to overcome the spatial and temporal limitations of traditional in situ gauging stations for effective water resource management.
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Yan et al. (2026) Advances in coupling machine learning with hydrological simulation: A review
This review systematically synthesizes the evolution of hydrological modeling from traditional physical frameworks to data-driven machine learning (ML) approaches. It establishes that coupling physically-based mechanisms with ML architectures is the most effective pathway to enhance predictive accuracy, computational efficiency, and interpretability.
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Mamassi et al. (2026) Trade-offs associated with achieving food self-sufficiency: The underlying mechanisms
This study synthesizes literature to identify the mechanisms driving trade-offs between food self-sufficiency (FSS) and ten major influencing factors, classifying them into primary (direct) and secondary (indirect) drivers. The findings reveal that FSS challenges are highly context-specific, with resource constraints dominating low-sufficiency regions and sustainability-related trade-offs prevailing in industrialized, export-oriented nations.
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Pérez et al. (2026) Quantifying the Value of Ai-Based Meteorological Postprocessing for Seasonal Hydrological Forecasting in Mediterranean Semi-Arid Basins
This study quantifies the value of AI-based fuzzy rule systems for postprocessing meteorological inputs in seasonal hydrological forecasts in Spain's Jucar River Basin, finding that forecast reliability coverage increased substantially from 41.6% to 73.7% and extending the operational lead time from 1–2 months to 4–5 months ahead.
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Zipper et al. (2026) Lagged streamflow depletion due to pumping-induced stream drying: Incorporation into analytical streamflow depletion estimation methods
This study develops a method to incorporate stream drying and network routing into Analytical Depletion Functions (ADFs), improving their ability to estimate streamflow depletion in non-perennial systems. The findings reveal that stream drying causes a temporal shift, lagging a significant portion of streamflow depletion until the stream network rewets in the fall and winter.
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Xie et al. (2026) Decadal changes and influencing factors of global industrial heat sources
This study develops a deep learning framework to automatically classify six major types of global industrial heat sources using high-resolution satellite imagery and thermal anomaly data. The researchers produced the first annual global dataset of industrial heat sources from 2013 to 2023, revealing decadal shifts in industrial activity and the impacts of the COVID-19 pandemic.
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Aritz et al. (2026) Cropping camelina with flood irrigation under contrasting fertilization sources
This study evaluates the performance of camelina (*Camelina sativa*) under flood irrigation and rainfed conditions in Mediterranean Spain, demonstrating that a single 100 mm irrigation event can stabilize and increase yields to 3000 kg ha⁻¹. The findings suggest camelina is a viable, water-efficient alternative to traditional winter cereals in drought-prone irrigated systems.
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Costabile et al. (2026) A stochastic rain-on-grid framework for handling spatio-temporal rainfall uncertainty in impact-based flood nowcasting
This study introduces a Stochastic Rain-on-Grid framework that couples high-resolution stochastic rainfall generation with 2D hydrodynamic modeling to quantify how rainfall spatio-temporal uncertainty propagates into flood impacts. The findings demonstrate that while hydrological responses are highly sensitive to rainfall structure, street-level hazard classifications are more robust, providing a more stable target for early warning systems.
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Najmi et al. (2026) Evaluation of Precipitation-Based Drought Indices Under Future Climate Change Scenarios: Integration of PERSIANN-CCS-CDR and Dynamically Downscaled Regional Climate Models for the Tensift Watershed
This study evaluates future meteorological drought in the Tensift watershed, Morocco, by integrating PERSIANN-CCS-CDR data with elevation-stratified bias-corrected MED-CORDEX models. Results project a statistically significant, basin-wide shift toward persistent moderate-to-severe drought conditions by the late 21st century under both RCP4.5 and RCP8.5 scenarios.
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Li et al. (2026) Shifting climatic sensitivities of drought-related yield gaps signal potential increases in irrigation reliance in the Yellow River Basin
This study quantifies the evolving sensitivity of the irrigated–rainfed yield gap to climate drivers in the Yellow River Basin, finding that rising atmospheric demand reduces the effectiveness of precipitation in narrowing this gap. The results indicate a projected increase in yield gaps for maize, soybean, and rice, signaling a heightened future reliance on irrigation to stabilize food production.
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He et al. (2026) Flash flood risk governance system in China and its governance effectiveness
This study evaluates the effectiveness of China’s state-led, multi-level flash flood governance system by integrating institutional analysis with a survey of 811 rural households. It finds that while government-led structural measures and emergency relief are the primary drivers of perceived safety, community-level institutions and traditional knowledge play vital supporting roles.
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Yalcin et al. (2026) Assessing Climate Change Vulnerability of Hydropower Production and Water Supply in the Mediterranean Hotspot
The study presents the development and validation of SIM2, a high-resolution (8,000 m) hydrometeorological dataset for metropolitan France covering the period from 1958 to 2018. By coupling the SAFRAN atmospheric reanalysis with the SURFEX/ISBA-CTRIP modeling chain, the authors provide a consistent 60-year reconstruction of the French water cycle.
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Afrasiabikia et al. (2026) A satellite-driven approach to estimating delivered irrigation water via SM-based inversion algorithm: A case study of the Doroodzan irrigation district, Iran
This study utilizes a high-resolution (1 km) soil moisture-based inversion algorithm to estimate irrigation water use in the Doroodzan district, Iran. The findings reveal that actual irrigation efficiency (26–37%) is significantly lower than the 53% reported by local authorities, highlighting substantial conveyance and distribution losses.
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Fabre et al. (2026) Integrated modelling of sediment and organic carbon fluxes in a large catchment: quantifying riverine contributions to the Mediterranean Sea
This study utilizes the SWAT-C model to quantify the integrated fluxes of sediment, particulate organic carbon (POC), and dissolved organic carbon (DOC) from the Rhone River catchment to the Mediterranean Sea between 2002 and 2020. The research identifies the Durance and Isère rivers as primary sediment contributors and characterizes the exported organic carbon as predominantly labile POC and refractory DOC.
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Thomas (2026) Supporting data for 2022-2023 groundwater budget for the Mountain Home area, southern Idaho
This study develops a comprehensive groundwater budget for the Mountain Home area in southern Idaho for the 2023 irrigation year to address concerns regarding declining aquifer levels. The research provides a detailed dataset of irrigation sources, pumping volumes, and percolation estimates essential for regional water resource management.
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Dang et al. (2026) Climate-induced hydrological changes and agricultural implications in the Laurentian Great Lakes region
This study provides the first comprehensive basin-wide assessment of the Laurentian Great Lakes Basin's hydrological response to climate change, projecting significant seasonal shifts and a decline in growing-season soil moisture. The research highlights a critical trade-off between increased overall surface water storage and heightened agricultural water stress due to earlier spring peaks and summer drying.
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Elsadek et al. (2026) Comparing Cotton ET Data from a Satellite Platform, In Situ Sensor, and Soil Water Balance Method in Arizona
This study evaluates the accuracy of six satellite-based OpenET models, their ensemble, and the LI-710 field-based system in estimating evapotranspiration (ET) for late-planted cotton in an arid environment. The results identify eeMETRIC, SIMS, SSEBop, the OpenET Ensemble, and the LI-710 as reliable tools for irrigation management, while other models significantly underestimated ET.
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Bouswir et al. (2026) Irrigation optimization and assessment of deep percolation losses for winter wheat in a semi-arid using the SIMDualKc model
This study utilizes the SIMDualKc model to quantify deep percolation losses in Moroccan wheat cultivation and demonstrates that optimized irrigation scheduling can reduce these losses by 88%. The research highlights a significant opportunity to improve water use efficiency by reducing irrigation volumes by 45% compared to traditional farmer practices.
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Aderdour et al. (2026) Advanced Drought Prediction Using Hybrid Deep Learning Models: A Case Study of the High Atlas and Anti-Atlas Mountains
This study develops a hybrid deep learning framework using Gated Recurrent Units (GRU) to predict the Standardized Precipitation Index (SPI) at a 5 km resolution in the High and Anti-Atlas mountains. The model achieves over 91% accuracy by integrating multi-source remote sensing and climate data, providing a robust early-warning tool for regions with sparse meteorological stations.
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Diop (2026) A Unified Framework for Stochastic Differential Equations Driven by H ö lder Continuous Functions with Applications to Senegalese Groundwater Management
This research establishes a unified mathematical framework for stochastic differential equations (SDEs) driven by Hölder continuous paths, bridging Young integration and rough path theory. The application of this framework to Senegalese hydrology results in a 52% improvement in groundwater level prediction accuracy compared to traditional stochastic models.
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Atiq et al. (2026) Monitoring drought-induced degradation of olive and citrus tree crops in the Tadla plain (Morocco) with multi-sensor remote sensing
This study utilizes multi-sensor satellite data (Sentinel-1 and Sentinel-2) and Support Vector Machine (SVM) classification to monitor the degradation of citrus and olive crops in Morocco's Tadla plain. The findings reveal a significant reduction in crop area and health between 2018 and 2024 due to persistent drought and groundwater overexploitation.
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Wu et al. (2026) Multi-Dimensional Monitoring of Agricultural Drought at the Field Scale
This study develops a high-resolution, field-scale agricultural drought monitoring model for Hebi City using multi-source satellite data and machine learning, identifying XGBoost as the most effective algorithm with 89% accuracy. The research demonstrates that integrating radar, optical, and topographic data significantly improves the detection of rapid-onset, small-scale drought events.
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Ech-Chahdi et al. (2026) Long-term monitoring of surface water dynamics using remote sensing data: A case study of Al Wahda dam, Morocco
This study monitors the spatiotemporal dynamics of the Al Wahda Dam in Morocco using the NDWI index and evaluates the impact of rainfall variability through the SPI. The findings reveal a significant correlation between climatic drought and the contraction of the reservoir's water surface area.
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López et al. (2026) Post-abandonment management strategies influence future soil organic carbon storage and water resources
This study evaluates how three post-abandonment land management strategies—shrub clearing for pasture, secondary succession, and afforestation—affect soil organic carbon (SOC) and water resources in a Mediterranean mountain valley under various IPCC climate scenarios. The findings indicate that while afforestation maximizes carbon sequestration, shrub clearing for agroforestry significantly enhances water yield and provides a balanced socio-economic and environmental outcome.
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Bouswir et al. (2026) Irrigation optimization and assessment of deep percolation losses for winter wheat in a semi-arid using the SIMDualKc model
This study utilizes the SIMDualKc model to quantify deep percolation losses in Moroccan winter wheat, demonstrating that optimized irrigation scheduling can reduce water consumption by up to 70% and drainage losses by over 90% compared to traditional farmer practices.
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Wang et al. (2026) Effects of Ponding Water Depths on Evapotranspiration in Irrigated Rice Paddies
This study evaluates the performance of the ISBA and mHM land surface models in simulating soil moisture and streamflow within the Garonne River basin. The results demonstrate that while both models accurately capture streamflow dynamics, they exhibit significant differences in soil moisture spatial patterns and sensitivity to meteorological forcing.
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Eshetie et al. (2026) High-resolution root-zone soil moisture for agricultural drought assessment using Sentinel-2 and hybrid modeling in the Lake Tana Basin, Ethiopia
This study develops a high-resolution framework for estimating root-zone soil moisture (RZSM) in the Lake Tana Basin by integrating Sentinel-2A data with hybrid modeling. The research identifies significant agricultural drought patterns and contrasting trends between pre-rainy (antecedent) and post-rainy (residual) soil moisture levels from 2016 to 2024.
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Pliemon et al. (2026) Spectral Divergence in Hydroclimate and Temperature Between Models and Reconstructions Over the Common Era
This study compares long-term temperature and hydroclimate variability between the CESM-LME model and the PHYDA reconstruction, finding that the assimilation of proxy data introduces significant low-frequency variability that is otherwise absent in the climate model.
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Terzi et al. (2026) Probabilistic Risk Assessment of Meteorological and Hydrological Droughts with Copula Functions: A Multivariate Framework
This study develops a sequential, copula-based framework to assess meteorological and hydrological drought risk in the Çoruh River Basin, demonstrating that this integrated multivariate approach provides more accurate estimates of drought duration, severity, and joint return periods compared to traditional univariate methods.
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Banda et al. (2026) A Multi-Metric and Multi-Driver Analysis of Long-Term Aridity Change over Africa (1951-2020)
This study analyzed long-term aridity changes across Africa from 1951-2020, revealing widespread drying trends primarily driven by increasing potential evapotranspiration (PET) due to warming temperatures, with precipitation playing a secondary role.
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Afrin et al. (2026) Uncertainty Analysis of Artificial Neural Network based Regional Flood Modelling in New South Wales, Australia
This study conducts an in-depth uncertainty analysis of Artificial Neural Network (ANN)-based Regional Flood Frequency Analysis (RFFA) using data from 88 gauged stations in New South Wales, Australia, finding that ANN performance and uncertainty vary with return period, with mid-range quantiles showing lower uncertainty.
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Montzka et al. (2026) AI in soil moisture remote sensing
This paper provides a comprehensive review and synthesis of the application of Artificial Intelligence (AI) techniques in the field of soil moisture remote sensing, highlighting current advancements, methodologies, and future research directions.
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Akhal (2026) Desertification In Irrigated Areas in Mediterranean Environments, Case of Tadla’s Irrigated Perimeter
This study examines the progression of desertification in Morocco's Tadla irrigated perimeter, identifying climate change and unregulated groundwater extraction as primary drivers of severe piezometric decline and soil salinization. The research highlights a critical disconnect between institutional water management and local farming practices, where 88% of wells operate without legal authorization.
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Aras et al. (2026) Spatiotemporal analysis of temperature rise impact on snow drought in Erzurum, Türkiye
This study aims to conduct a spatiotemporal analysis of the impact of temperature rise on snow drought in Erzurum, Türkiye, highlighting the critical link between climate change and regional water resource vulnerability.
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Jagdhuber et al. (2026) Assessing the Spatial Similarity of Soil Moisture Patterns and Their Environmental and Observational Drivers from Remote Sensing and Earth System Modeling Across Europe
This study investigates the spatial similarity of soil moisture patterns between passive microwave remote sensing (SMAP) and Earth system modeling (ECMWF IFS) across Europe, identifying the environmental and observational drivers behind these patterns. It reveals underlying spatial similarities despite inherent discrepancies between the products and highlights soil texture, precipitation, and temperature as key drivers for model outputs, while SMAP retrievals are driven by brightness temperatures influenced by surface properties.
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Boutelhig et al. (2026) Geospatial Management of Water Supply in Algerian Territory, Based on the Water Stress Indicator Analysis
This study evaluates Algeria's water security by analyzing the Water Stress Indicator (WSI) and Water-Use Efficiency (WUE) across various sectors. The findings reveal a critical water stress level exceeding 80% and highlight a significant lack of agricultural statistics necessary for effective geospatial water management.
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Umair et al. (2026) Implementing a Plant Hydraulics Parameterization in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) v.1.4
This study evaluates the impact of assimilating satellite-derived Leaf Area Index (LAI) and Surface Soil Moisture (SSM) into the ISBA-CTRIP land surface model over the Euro-Mediterranean region. The results demonstrate that joint assimilation significantly improves the representation of vegetation dynamics and river discharge, particularly in water-limited areas.
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GEDİK et al. (2026) Evaluation of groundwater drought in the Konya closed basin by examining hydrological and anthropogenic factors
This study assesses groundwater drought in the Konya Closed Basin from 1967 to 2019 using the Standardized Groundwater Level Index (SGI), finding that intensive agricultural irrigation and a surge in unlicensed wells have caused an average water level decline of 15.9 m. The research identifies the 1990s as a critical turning point where anthropogenic pressures began to systematically override natural recharge cycles, leading to persistent severe and extreme drought conditions.
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Iza‐Wong et al. (2026) Evaluation of Precipitation Observations Across Ecuador
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Webb et al. (2026) Review: The Importance of Lateral Flow Through Snow in Hydrological Processes Globally
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Alzabari (2026) Spatiotemporal variability and climatic determinants of reference evapotranspiration in Saudi Arabia
This study investigated the spatiotemporal variability, long-term trends, and climatic sensitivity of reference evapotranspiration (ET0) across 25 meteorological stations in Saudi Arabia from 2000 to 2024, revealing statistically significant increasing ET0 trends, particularly in summer, primarily driven by mean relative humidity, wind speed, and maximum air temperature.
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Feizi et al. (2026) Streamflow Forecasting Based on PatchTST, LSTM, and Ensemble Learning Approaches
This study evaluates the performance of PatchTST and LSTM deep learning models for daily streamflow forecasting of the Sefidrud River, demonstrating that a Stacking Ensemble approach significantly enhances prediction accuracy compared to individual models.
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Legese et al. (2026) Evaluation of Hydrological Drought Under Climate Change in Hamessa Watershed, Rift Valley Basin, Ethiopia
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Kalura et al. (2026) Enhancing Hydrologic Model Performance in a Data-Scarce Basin Using Satellite-Based Soil Moisture Data
This study evaluates the effectiveness of incorporating satellite-derived soil moisture (SM) into the calibration of the Variable Infiltration Capacity (VIC) model in the data-scarce Wardha River Basin, demonstrating that multivariate calibration with SM significantly improves streamflow predictions, especially low-flow conditions, and enhances internal hydrological state representation.
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Goutard (2026) Simulation outputs
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Evaristo (2026) Left High and Dry: Deep Soil Water Depletion and Ecohydrological Resilience on China's Loess Plateau
This study evaluates and compares the performance of the ISBA land surface model and the mHM hydrological model in simulating the terrestrial water cycle across Europe. The research identifies that while both models effectively capture water storage trends, mHM excels in discharge accuracy while ISBA provides robust surface moisture estimates.
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Goffin et al. (2026) Satellite-Based Fraction of Available Water Reveals Soil Moisture Deficits Preceding Major Wildfires
The study demonstrates that the satellite-derived Fraction of Available Water (FAW) serves as a robust indicator of wildfire risk by identifying critical soil moisture deficits months before ignition. It establishes that major wildfires are consistently preceded by FAW values dropping below a specific threshold, regardless of the geographic region.
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Liu et al. (2026) Spatiotemporal characteristics and onset processes of flash droughts during the growing season in Inner Mongolia, China
This study investigated the spatiotemporal characteristics and onset processes of flash droughts in Inner Mongolia, China, from 1982 to 2022, identifying five hotspot regions and determining that vapor pressure deficit is consistently the most influential meteorological driver.
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Nouri et al. (2026) Global Attribution of Anthropogenic Climate Change to Terrestrial Long-Term Droughts
This study quantitatively attributes anthropogenic climate change (CC) to global terrestrial long-term droughts by comparing factual and counterfactual climate scenarios, revealing that CC has significantly increased drought frequency, multi-year drought occurrences, and shifted drought trends towards drying across substantial portions of the global land, with atmospheric evaporative demand (AED) playing a crucial role.
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Mo et al. (2026) Multi-objective Joint Optimization Operation of Cascade Reservoirs Considering River Hydrological Health Assessment
This study developed a multi-objective optimization framework for cascade reservoir operation in the Haokun-Chengbi River Basin, integrating river hydrological health assessment to balance power generation, water supply, and ecological flow. The research found that optimal strategies vary significantly with hydrological conditions, with dry years showing the most pronounced improvement in river hydrological health (up to 57.35%) after optimization.
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Atiq et al. (2026) Monitoring drought-induced degradation of olive and citrus tree crops in the Tadla plain (Morocco) with multi-sensor remote sensing
This study utilizes multi-sensor satellite integration (Sentinel-1 and Sentinel-2) and Support Vector Machine (SVM) classification to monitor the degradation of perennial crops in Morocco's Tadla plain. The findings reveal a significant reduction in citrus (38%) and olive (32%) cultivation areas between 2019 and 2024 driven by severe drought and groundwater overexploitation.
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Zemzami et al. (2026) Integrating climate models to confront the illusion of certainty in water planning: evidence from Morocco
This study examines the implications of hydroclimatic non-stationarity on water planning in a semi-arid Moroccan basin, revealing that traditional stationary assumptions significantly overestimate water availability and conceal critical system vulnerabilities, necessitating climate-informed adaptive strategies combining reservoirs and desalination.
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Roy et al. (2026) Assessment of Remote Sensing Precipitation Products for Hydrological Analysis in an Ungauged Watershed
This study proposes a novel Monsoon Index (MI) to quantify the temporal distribution and magnitude of monsoon rainfall for selecting suitable Remote Sensing Precipitation Products (RSPPs) in ungauged, high-altitude regions. It found that IMERG most accurately represents observed monsoon characteristics and significantly improves daily runoff estimation in the Ranikhola watershed compared to other RSPPs.
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Bruno et al. (2026) Short to Long Streamflow Droughts: A Process‐Oriented Review
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Otop et al. (2026) Seasonal Changes of Extreme Precipitation in Relation to Circulation Conditions in the Sudetes Mountains
This study examines multiannual (1961–2020) changes in seasonal heavy precipitation in the Polish-Czech Sudetes Mountains and its relationship with atmospheric circulation. It finds that heavy precipitation changes are non-homogeneous and significantly influenced by the chosen indices, seasons, and local geographic factors like slope exposition, particularly under specific circulation types.
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Obayomi et al. (2025) Sustainable agriculture in the face of water scarcity: Opportunities, challenges, and global perspectives
This paper provides a comprehensive synthesis of reclaimed water applications across the global food system, evaluating its potential to mitigate water scarcity through nutrient recycling and circular bioeconomy strategies. It identifies technical, regulatory, and socioeconomic barriers while proposing a multidisciplinary framework that integrates water reuse with precision and controlled-environment agriculture.
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Azedou et al. (2025) Ensemble deep learning towards high-resolution soil-moisture mapping for enhanced water management in California's Central Valley
This study develops an optimized ensemble deep learning framework to downscale NASA SMAP soil moisture data from 9 km to a 30 m spatial resolution across California’s Central Valley. The resulting high-resolution maps for surface and root-zone moisture provide critical data for precision irrigation scheduling and sustainable groundwater management.
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Zhang et al. (2025) Multi-layer grid-scale soil moisture estimation using spatiotemporal deep learning methods with physical constraints
This study develops a physics-guided deep learning (PGDL) model that integrates the Richardson-Richards equation into a CNN-LSTM architecture to estimate multi-layer soil moisture. The approach significantly improves the accuracy and physical consistency of soil moisture predictions across depths of 10 cm to 50 cm compared to standard machine learning methods.
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Sivelle et al. (2025) Investigating hydrological modeling uncertainties in the Mediterranean region by combining precipitation and soil moisture products
This study evaluates the impact of various satellite-derived precipitation and soil moisture products on hydrological modeling performance across five Mediterranean catchments. It demonstrates that while gauge-based data remains superior, merged precipitation products and Sentinel-1 soil moisture data significantly reduce predictive uncertainties, especially when forcing models with satellite-only rainfall.
