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Liu et al. (2025) Transformer-based soil moisture simulation for understanding future drying trend globally
This study introduces TSMSNet, a Transformer-based deep learning model designed to simulate global soil moisture (SM) from 2016 to 2099 under various climate scenarios. The research identifies a significant global drying trend that intensifies with higher greenhouse gas emission pathways, particularly affecting habitable regions and agricultural lands.
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Wang et al. (2025) Estimating soil moisture at farm scale with high spatial resolution: integrating remote sensing data, and machine learning
This study develops a machine learning-based downscaling framework that integrates evapotranspiration and groundwater depth to estimate surface soil moisture at a 30 m resolution from 9 km coarse data. The approach significantly improves soil moisture monitoring in complex agricultural environments by accounting for both upper and lower boundary conditions.
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Sabea et al. (2025) AI for Sustainable Development Goals: Leveraging Machine Learning for Climate-Resilient Wheat Production in Wasit, Iraq
This study develops an integrated machine-learning decision-support system to enhance wheat production resilience in the semi-arid Wasit Governorate of Iraq. By combining multi-temporal satellite data and meteorological reanalysis, the system optimizes irrigation and provides early-season yield forecasts, resulting in significant water savings and improved yield stability.
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Yan et al. (2025) Soil moisture dynamics and rainfall infiltration across vegetation types in subtropical ecosystems in Southwest China
This study investigated soil moisture dynamics and rainfall infiltration across four vegetation types in subtropical Southwest China, revealing that primary evergreen broadleaf forests maintain higher soil moisture and slower infiltration rates, which is crucial for regional drought resistance.
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Qi et al. (2025) MODIS-Landsat fusion reveals two-decade 8-day lake dynamics with critical intra-annual regime shifts
The study reconstructs 8-day resolution dynamics for lakes and reservoirs in southern China from 2001 to 2020 using MODIS-Landsat data fusion. It reveals that high-frequency intra-annual variations are critical for accurate carbon budget estimates, often offsetting or equaling the impact of long-term interannual trends.
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Jain et al. (2025) Deriving hydrological inferences from a machine learning model to understand the physical drivers of flow duration curves
This study utilizes Random Forest regression and SHapley Additive exPlanations (SHAP) to predict Flow Duration Curves (FDCs) across 991 watersheds in the contiguous United States. The research demonstrates that while climate attributes primarily determine the scale of FDCs, the baseflow index and geological features are the critical drivers of FDC shape and low-flow regimes.
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Weng et al. (2025) Evolution and impact of rainfall infiltration in global alpine water towers
This study develops a temperature-mediated infiltration model to quantify rainfall infiltration across 78 global Water Tower Units (WTUs) from 1980 to 2023. The findings reveal that climate warming and freeze-thaw cycles are significantly altering infiltration characteristics, threatening the stability of downstream water supplies and ecological buffering.
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Khan et al. (2025) Remote sensing-based cropping pattern identification and its impact on groundwater use in canal command areas of an irrigated agriculture region in Pakistan
This study integrates Sentinel-2 satellite imagery and Random Forest algorithms to map seasonal cropping patterns across eight Canal Command Areas in Pakistan's Bari Doab from 2018 to 2023. The findings quantify a rising dependency on groundwater for irrigation, driven by water-intensive crops and urbanization, leading to significant regional aquifer depletion.
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Fan et al. (2025) Considering parameter seasonal variation to enhance process-based ecosystem model performance, evidence from the SWH model
This study demonstrates that incorporating seasonal variation into empirical parameters significantly enhances the performance of the SWH evapotranspiration (ET) partitioning model. A novel Monte Carlo-based calibration scheme with adaptive time windows achieved a 95% success rate and substantially improved R² values compared to traditional methods, approaching the accuracy of Extended Kalman Filtering.
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Mo et al. (2025) Time-lag effects of vegetation gross primary production response to the hydro-climate changes in humid and semi-humid areas of China
This study investigated the relationship between vegetation gross primary production (GPP) and hydro-climate factors (precipitation, temperature, basin water storage) in the humid and semi-humid Hanjiang River Basin, China. It revealed significant time-lag effects of hydrological factors on GPP (4 months for basin water storage, 5 months for precipitation), highlighting their long-term influence compared to the immediate response to temperature.
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Daiman et al. (2025) Assessing the link between changes in landscape and desertification in the chambal river basin using machine learning and remote sensing
This study analyzed the linkage between landscape changes and desertification in the Chambal River Basin (India) from 1990 to 2020 using machine learning and remote sensing. It found that anthropogenic land alterations, particularly the conversion of vegetation and agricultural lands, amplified the region's vulnerability to drought and desertification.
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Choubin et al. (2025) Discover the world of drought and water scarcity indices: insights for a sustainable future
This chapter synthesizes the critical role of drought and water scarcity indices as essential tools for monitoring, predicting, and managing water resources, emphasizing their importance for sustainable water management and policy-making in the face of global environmental challenges.
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Alamdarloo et al. (2025) Remote sensing for assessing ecosystem drought impact
This chapter introduces the multifaceted nature of drought, its various classifications, and its devastating impacts on ecosystems, agriculture, and water resources, setting the context for the application of remote sensing in assessing these impacts.
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Turki et al. (2025) On the use of SWOT altimetry data for monitoring coastal hydrodynamics
This study evaluates the accuracy of the Surface Water and Ocean Topography (SWOT) mission in retrieving coastal Sea Surface Heights (SSH) and Significant Wave Heights (SWH) in the English Channel. The findings demonstrate that SWOT provides high-resolution, reliable hydrodynamic data even within 3–4 km of the shoreline, significantly outperforming conventional satellite altimetry in complex nearshore environments.
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Yin et al. (2025) A shift in drought propagation trend in the Yellow River Basin during 1980–2020 linked to climate change and vegetation greening
This study investigates the propagation of meteorological drought to soil moisture drought in the Yellow River Basin from 1980 to 2020, identifying a significant shift around the year 2000 where drought propagation time began to prolong and duration extension began to decrease due to vegetation greening.
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Damaneh et al. (2025) Climatic influences on vegetation degradation and soil moisture
This paper aims to investigate the influences of climatic factors, particularly drought, on vegetation degradation and soil moisture dynamics, highlighting the increasing global challenges posed by climate change.
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Chucuya et al. (2025) Reconstructing aquifer dynamics with machine learning: Linking irrigation expansion to groundwater decline in a data-scarce hyper-arid region
This study utilizes machine learning (BPNN) to reconstruct fragmented groundwater records in the hyper-arid Caplina aquifer, revealing a 0.6 m/yr water table decline driven by a 400% expansion of irrigated agriculture over three decades. The research highlights the critical role of seawater intrusion in maintaining stable water levels near the coast while severely degrading water quality.
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Olson et al. (2025) Long‐Term Stream Chemistry Patterns in a Boreal Watershed Underlain With Discontinuous Permafrost
This study investigated over 20 years of stream chemistry and climate trends in boreal catchments with varying permafrost extents to understand how altered flowpaths and climate change affect solute transport. It found significant declines in dissolved organic carbon (DOC) and partial pressure of carbon dioxide (pCO₂) in sub-catchments with higher permafrost extent, with moisture and discharge being key abiotic drivers.
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Patra et al. (2025) Long-term projections of global groundwater storage under future climate change scenarios using deep learning
This study utilizes a deep learning model to project global groundwater storage (GWS) variations until 2100 under CMIP6 climate scenarios, identifying maximum temperature as the primary driver of depletion. The findings indicate that over 50% of the global population will reside in regions facing GWS decline by the end of the century, with tropical and temperate zones being the most vulnerable.
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Karimzadeh et al. (2025) Climate change has increased global evaporative demand except in South Asia
Climate change has increased global evaporative demand, but this study reveals a significant decline in South Asia due to widespread irrigation, which has increased local moisture, cloud cover, and reduced solar radiation. These contrasting trends highlight how human water use can locally reshape the climate's influence on the water cycle.
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Weynants et al. (2025) Dheed: an ERA5 based global database of compound dry and hot extreme events from 1950 to 2023
This study introduces Dheed, a novel global database of compound dry and hot (CDH) extreme events from 1950 to 2023, derived from ERA5 reanalysis data, and confirms a significant increase in the frequency and spatial extent of these events over recent decades.
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Dangare et al. (2025) Estimating transpiration dynamics of a low-density litchi orchard using crop coefficients derived from a variable leaf conductance model, canopy cover, and tree height in Northeastern South Africa
This study improved the estimation of litchi orchard transpiration in semi-arid South Africa by modifying the Allen and Pereira (A&P) crop coefficient approach to incorporate a variable leaf resistance model and a litchi-specific typical leaf resistance, achieving significantly higher accuracy compared to the original fixed-value method.
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Debnath et al. (2025) Identifying groundwater artificial recharge options using conventional water sources: A way towards genetic resource development
This chapter outlines methods for identifying and implementing artificial groundwater recharge using conventional water sources, aiming to enhance water productivity and contribute to genetic resource development. It details various conventional sources, recharge techniques, and necessary observational data for successful project implementation.
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Zeroualı et al. (2025) Linking the North Atlantic Oscillation to rainfall variability and dynamics in Algeria through GIS and wavelet theory
This study regionally analyzes the relationship between the North Atlantic Oscillation (NAO) and rainfall in northeastern Algeria using wavelet theory and GIS, revealing a strong and consistent NAO influence in the north that diminishes southward, offering potential for improved rainfall forecasting.
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Talebi et al. (2025) Advanced Hybrid Machine Learning for Precise Short-Term Drought Prediction: A Comparative Study of SPI and SPEI Indices in Iran's Arid and Semi-Arid Regions
This study developed and compared twelve hybrid machine learning models for precise short-term drought prediction using SPI and SPEI indices in Iran's arid and semi-arid regions. It found that Tuned Q-factor Wavelet Transform (TQWT)-based models excelled in 1-month forecasts, while Empirical Wavelet Transform (EWT)-Adaptive Neuro-Fuzzy Inference System (ANFIS) was most robust for 3- and 6-month predictions.
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Ercan et al. (2025) Rethinking standardized drought indices for critical drought evaluation
This study investigates the differences between classical and dynamic Standardized Precipitation Index (SPI) models, revealing that dynamic models produce significantly longer drought durations, particularly at short and medium timescales, highlighting the importance of model choice for accurate drought assessment.
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Goebel et al. (2025) NUTS2 Level Land Use and Land Cover Quantifications under the Shared Socio-Economic Pathways, 2020-2050
This paper presents a dataset providing consistent projections of land use and land cover (LULC) for European NUTS2 regions under five Shared Socio-Economic Pathways (SSPs) from 2020 to 2050, generated using the G-RDEM computable general equilibrium model. The dataset offers high spatial and temporal resolution LULC dynamics, directly simulated at the NUTS2 level without post-model downscaling.
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Christian et al. (2025) A bi-level spatiotemporal clustering approach and its application to drought extraction
This paper introduces a novel bi-level spatiotemporal clustering algorithm, combining a modified space-time k-means and DBSCAN, to extract events based on their intensity and spatiotemporal structures. Applied to the Standardized Vapor Pressure Deficit Drought Index (SVDI) over the continental United States from 1980–2021, the algorithm successfully captures historical drought events and reveals long-term shifts in drought patterns.
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Banjoko et al. (2025) Methodological survey for the estimation of groundwater artificial recharge
This paper provides a comprehensive methodological survey for the estimation of artificial groundwater recharge, detailing its objectives, impacts, effective parameters, water sources, influencing factors, planning considerations, and various estimation techniques. It serves as a foundational resource for understanding and implementing artificial recharge schemes.
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Cho et al. (2025) Disentangling geomorphic equifinality in sediment and hydrologic connectivity through the analyses of landscape drivers of hysteresis
## Identification - **Journal:** Earth Surface Processes and Landforms - **Year:** 2025...
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Prasad et al. (2025) Traditional groundwater recharge techniques in India
This paper provides a comprehensive overview and detailed description of 30 traditional groundwater recharge and water harvesting techniques practiced across various regions of India, highlighting their historical significance and diverse methodologies.
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Lemus‐Canovas et al. (2025) More intense heatwaves under drier conditions: a compound event analysis in the Adige River basin (Eastern Italian Alps)
This study analyzes a severe compound drought and heatwave (CDHW) event in the Adige River basin (Eastern Italian Alps) in May 2022, revealing that similar events are now significantly hotter (by 1–4 °C) and drier (with pronounced precipitation deficits) due to climate change, exacerbating water stress and shifting streamflow seasonality. It also highlights the inability of many regional climate models (EURO-CORDEX) to accurately reproduce these observed changes in both magnitude and sign.
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Coulibaly et al. (2025) Estimation of Current Agricultural Drought in the District des Savanes (Northern Côte d’Ivoire)
This study investigated the spatio-temporal variability of soil moisture to estimate agricultural drought in the District des Savanes, Côte d’Ivoire, from 1981 to 2022, revealing a predominant intensification of agricultural drought since 1991, despite intermittent recoveries.
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Ramirez et al. (2025) Hydrological response to thinning in forest stands: analysis of soil volumetric water content and soil water flux
This study investigates the impact of masticator thinning on soil moisture dynamics in a semiarid mixed conifer forest. The findings indicate that thinning increases soil water storage at the soil-bedrock interface and induces upward water flux during dry periods, potentially enhancing forest resilience to drought.
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Papalexiou et al. (2025) Machine unlearning: bias correction in neural network downscaled storms
This study evaluates four machine learning models for downscaling precipitation using synthetic benchmark storms, demonstrating that combining machine learning with post-processing bias correction ("machine unlearning") is crucial for reliable outputs, especially for Wasserstein Generative Adversarial Networks (WGANs). It finds that raw neural network outputs struggle to reproduce key statistical properties and wet/dry boundaries, necessitating systematic bias correction for operational use.
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Lari et al. (2025) Quantifying sediment yield and discharge fluctuations using the GeoWEPP in response to soil and water conservation practices
This study evaluated and calibrated the GeoWEPP model to predict runoff and sediment yield in the mountainous Amameh watershed, Iran, incorporating snowmelt dynamics and high-resolution spatial data. It assessed eight biological conservation scenarios, demonstrating that enhanced canopy cover can reduce runoff by up to 44% and sediment yield by up to 47%.
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Sugita et al. (2025) Ship's Motion and Eddy Correlation Measurements of Surface Fluxes on the Small Research Ship NIES ' 94 in Lake Kasumigaura, Japan
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Tunca et al. (2025) Integration of UAV images and ensemble learning for root zone soil moisture estimation in sorghum
This study developed and evaluated a methodology to estimate root-zone soil moisture in sorghum using high-resolution unmanned aerial vehicle (UAV) multispectral and thermal imagery combined with machine learning. An ensemble model integrating XGBoost, Light Gradient Boosting Machine, and K-Nearest Neighbors achieved the highest accuracy (R² = 0.85, RMSE = 11.124 mm/90 cm, MAE = 8.775 mm/90 cm) for field-scale monitoring.
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Jaafarzadeh et al. (2025) Future trends in groundwater artificial recharge with conventional water
This paper reviews various methods of artificial groundwater recharge using conventional water sources, explores their roles and effectiveness, and identifies key challenges for their implementation, particularly within Iran.
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Rapella (2025) Modélisation et évaluation de la solution agrivoltaïque au nexus climat-eau-énergie-alimentation dans le contexte du changement climatique dans la région euro-méditerranéenne
This study integrates a photovoltaic module into the ORCHIDEE land surface model to assess the regional impact of agrivoltaics across the Euro-Mediterranean. The findings reveal that agrivoltaics significantly improve crop yields and resource efficiency in arid southern regions like the Iberian Peninsula, while providing limited or negative impacts in wetter northern regions like the Netherlands.
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Wang et al. (2025) Spatiotemporal evolution characteristics of multi-type drought propagation processes in the Yellow River Basin, China
This study systematically investigates the spatiotemporal characteristics and propagation mechanisms of meteorological drought to hydrological, agricultural, and ecological droughts in the Yellow River Basin (YRB) from 1982 to 2018, revealing distinct propagation patterns and regional disparities.
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Hirschi et al. (2025) Data accompanying "Quantifying the Rapid Propagation of Rainfall and Evapotranspiration Signals into Soils"
The study quantifies the velocity and dynamics of rainfall and evapotranspiration signal transmission through soil profiles. It utilizes high-resolution in-situ data to characterize how quickly surface hydro-meteorological changes propagate to deeper soil layers.
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Kahne et al. (2025) MEWAC-Verbundprojekt: GRaCCE - Grundwasserneubildung und Klimaänderungen - Quantifizierung der Resilienz von Karstgrundwasserressourcen für Dürre, Teilprojekt 3
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Abdelrahim et al. (2025) A Self‐Supervised Seasonal Anomaly Embedding ViT for Label‐Free Drought Mapping in the Horn of Africa
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Peng et al. (2025) Analysis of Spatiotemporal Changes in NDVI-Derived Vegetation Index and Its Influencing Factors in Kunming City (2000 to 2020)
This study analyzed the spatiotemporal changes and driving factors of vegetation cover in Kunming City from 2000 to 2020 using MODIS NDVI and climate/socioeconomic data, finding an overall increase in vegetation cover primarily influenced by precipitation, with urbanized areas showing lower vegetation.
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Mohanty et al. (2025) Water Saving Strategies in Field-based Agriculture: A Review of Traditional and Modern Approaches Across Agro-ecological Contexts in India
This meta-analytic review evaluates various agricultural water conservation techniques (WCTs) across different agroecological zones, demonstrating that their effectiveness is highly context-dependent and highlighting the superior water use efficiency of modern methods like drip irrigation and conservation tillage.
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El-Bouhali et al. (2025) Performance Evaluation of IMERG Satellite-Based Precipitation Estimates Against Rain Gauge Records in the Sebou Watershed, Morocco
This study evaluates the performance of IMERG-F V06 satellite-based precipitation estimates against ground-based rain gauge records in the Sebou watershed, Morocco, revealing that IMERG-F accuracy is strongly influenced by topography, climatic conditions, and rainfall intensity, with general overestimation in low altitudes and underestimation in high altitudes.
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Goudiaby et al. (2025) Hydrological evaluation of gridded rainfall products for streamflow simulation in West Africa
This study evaluates the hydrological performance of 23 gridded precipitation products for streamflow simulation in eight West African river basins using GR2M and GR4J models, finding that multi-source products like IMERGDF, MSWEP, GPCP, and TAMSAT are the most reliable alternatives in data-scarce regions.
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Preimesberger et al. (2025) ESA CCI SM GAPFILLED Long-term Climate Data Record of Surface Soil Moisture from merged multi-satellite observations
This study presents a global, gap-free long-term climate data record (CDR) of surface soil moisture spanning 1979 to 2024, derived from 19 different satellite sensors. The dataset utilizes a modified Discrete Cosine Transform Penalized Least Squares (DCT-PLS) algorithm to provide daily, spatially continuous estimates without relying on ancillary model-based variables.
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Tügel et al. (2025) Extreme precipitation and flooding in Berlin under climate change and effects of selected grey and blue-green measures
This study quantifies the projected increase in extreme precipitation in Berlin under climate change (RCP8.5) and its impact on urban flooding, demonstrating that a 46 % increase in 1 h 100-year rainfall leads to a 51 % increase in maximum water depth. It further assesses the effectiveness of grey infrastructure, infiltration, and retention roofs in mitigating these impacts, highlighting the non-linear relationship between rainfall and flooding and the need for combined adaptation strategies.
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Marrocu et al. (2025) Integrating deficit irrigation, crop modelling and Water–Energy–Food nexus to enhance durum wheat resilience in Mediterranean climate conditions
This study evaluates the impact of deficit irrigation on durum wheat yield and quality in southern Sardinia over two cropping seasons and two soil types, integrating agronomic monitoring, remote sensing, and crop modeling within a Water–Energy–Food (WEF) nexus framework. It found that moderate deficit irrigation (50% of plant water requirement) significantly improved grain yield and was comparable to full irrigation in efficiency, offering a sustainable strategy for food security in drought-prone Mediterranean regions.
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Tafesa et al. (2025) Assessing groundwater and climate susceptibility in Masgeredo-Bulal catchment, Ethiopia
This study assesses groundwater potential and climate change impacts in Southern Ethiopia's Masgeredo-Bulal catchment using GIS, remote sensing, and climate modeling, revealing that 51.6% of the catchment has good groundwater potential while future projections indicate increased temperature and decreased precipitation.
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Weng et al. (2025) Spatially coherent changes in Chinese annual flood peaks revealed by a consensus-based machine learning framework for regionalization
This study develops a consensus-based machine learning framework to identify homogeneous flood regions across China, revealing predominant trends of decreasing annual flood peak magnitudes and delayed occurrences in most regions, primarily driven by climate factors.
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Huimin et al. (2025) The response of meteorological drought to extreme climate in the water-receiving area of the Tao river diversion project in China
This study analyzed the spatiotemporal variations, interrelationships, and driving factors of meteorological drought and extreme climate events in the water-receiving area of the Tao River Diversion Project, China. It found a persistent drying trend since 1988, primarily driven by annual total precipitation, cold days, and summer days, with most extreme climate factors exhibiting complex nonlinear influences and critical thresholds on drought.
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Shah et al. (2025) Global patterns of reservoir fullness and fluctuations during droughts
This study assesses the storage conditions and fluctuations of 6634 global reservoirs during major river basin-scale droughts from 1999 to 2018, revealing significant regional, functional, and socio-economic disparities in reservoir resilience and a strong link to large-scale climate variability.
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Holwerda et al. (2025) A comparison of drought indices for crop yield loss detection: The role of green-up onset alignment and spatial resolution
This study compares six drought indices for detecting rainfed crop yield loss in the Central Plateau of Mexico, finding that aligning indices to satellite-derived green-up onset improves performance, with ALEXI-based Evaporative Stress Index and MODIS NDVI anomaly showing the strongest relationships with yield anomalies.
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Singh et al. (2025) Integrated trend analysis and meteorological drought forecasting using ANN in the adjacent semi-arid and arid regions
This study integrated trend analysis and meteorological drought forecasting using an Artificial Neural Network (ANN) model in adjacent semi-arid and arid regions of Rajasthan, India, finding increasing precipitation trends in several periods and a decrease in drought severity with longer time scales.
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Kulkarni et al. (2025) Near-global Agro-climatological Drought Monitoring Dataset
This study introduces the Near-global Combined Drought Monitoring (NEC-DROMO) dataset, integrating soil moisture, vegetation water content, rainfall, and temperature at a 0.25-degree monthly resolution from 2002-2021, demonstrating superior reliability in capturing global drought patterns compared to traditional indices.
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İpek et al. (2025) Integrating Spatio-Probabilistic mapping and remote sensing for comprehensive drought risk assessment
This study developed a Spatio-Probabilistic Drought Mapping (SPDM) framework by integrating multiple drought indices with remote sensing and land cover analysis to assess drought dynamics and environmental impacts in the Küçük Menderes Water Basin. The research identified western regions as high-risk areas and quantified severe impacts on vegetation, agriculture, and forest fires during major drought episodes.
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Dasari et al. (2025) A regionalization based machine learning framework for bias correction and downscaling of ESACCI soil moisture in data limited region: A case study over India
This study developed a regionalization-based machine learning framework for bias correction and downscaling of ESACCI soil moisture data in data-limited regions like India, demonstrating significant bias reduction (over 90%) and effective downscaling with high containment ratios (over 89%).
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Cañizares et al. (2025) Los problemas estructurales del Trasvase Tajo-Segura y sus efectos en las superficies cultivables del sureste español
This study identifies structural planning errors in the Tagus-Segura Transfer (ATS) and utilizes high-resolution GIS mapping to demonstrate that actual cultivated land in the Vega Baja del Segura is significantly lower than official estimates. The findings suggest that current water deficits can be managed through non-conventional resources and realistic land-use planning rather than relying on obsolete transfer projections.
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Xu et al. (2025) The applicability of statistical post-processing techniques for quantitative precipitation forecast in the Huaihe River Basin
This study evaluates seven post-processing methods for quantitative precipitation forecasts in the Huaihe River Basin, demonstrating that spatiotemporal deep learning models (specifically ConvLSTM) significantly outperform traditional statistical and time-series methods, particularly during flood seasons and in complex terrains.
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Alifujiang et al. (2025) Spatiotemporal patterns and trends of meteorological drought in the Kaidu-Kongque River Basin
This study analyzed the spatiotemporal patterns and trends of meteorological drought in the Kaidu-Kongque River Basin from 1960 to 2023 using SPI, SPEI, Pettitt test, and Modified Innovative Trend Analysis (MITA). It revealed a significant "dry west and wet east" spatial divergence, increased drought persistence, and a critical shift in drought drivers from precipitation-dominated to water-heat coupling-dominated around 1999.
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Pimentel et al. (2025) Asymmetry in snow-water nexus in mountain areas mainly governed by meteorological seasonal changes
This study analyzes 548 mountain catchments globally to quantify the nexus between snow cover and streamflow, revealing that only 5% of catchments show simultaneous significant trends in both variables. The findings highlight an asymmetric relationship where seasonal meteorological drivers, such as summer temperature increases or winter precipitation shifts, often decouple snow cover changes from annual water yield.
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Mathbout et al. (2025) Europe’s Double Threat: Evolving patterns of compound heatwaves and droughts
This study quantifies the spatiotemporal evolution of Compound Hot and Dry Events (CHDEs) across Europe from 1980 to 2023, revealing a significant post-2000 intensification and northward/eastward expansion, primarily driven by heatwaves, with urban areas showing disproportionately higher increases.
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Yuan et al. (2025) A global drought dataset for Multivariate Composite Drought Index (MCDI) and its constituent drought indices
This study developed and validated a global, high-resolution (0.1°, monthly, 1980-2019) drought dataset based on the Multivariate Composite Drought Index (MCDI) and its constituent indices, demonstrating its effectiveness in characterizing comprehensive drought dynamics and ecosystem responses by accounting for time lag and cumulative effects.
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Sinore et al. (2025) Agricultural and meteorological drought variability assessment over the Rift Valley Lake Basin of Ethiopia
This study assessed the spatiotemporal variability of meteorological and agricultural droughts in Ethiopia's Rift Valley Lake Basin using multi-source remote sensing data and advanced statistical models. It revealed significant drought severity variations, with specific major events, and highlighted the compounded effects of thermal and moisture stress on vegetation.
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Park et al. (2025) Climate change paradox: worsening droughts amidst increasing average precipitation across South Korea
This study reveals a climate change paradox in South Korea, demonstrating that droughts have worsened in frequency and intensity over the past century despite an overall increase in average precipitation, driven by enhanced meteorological variability and temperature-driven evapotranspiration, with strong implications for water resources.
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Yonaba et al. (2025) Hydrological evaluation of top-down and bottom-up rainfall products in West Africa: Model performance, parameter range and uncertainty propagation
This study evaluated the hydrological performance of four top-down and three bottom-up satellite rainfall products in three West African Sahelian river basins using the SWAT model. It found that model skill varied across basins, with some gridded products outperforming gauge observations, and demonstrated that carefully selected rainfall products can significantly enhance hydrological modeling and water resource planning in the region.
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Flaounas et al. (2025) Dynamics, predictability, impacts and climate change considerations of the catastrophic Mediterranean Storm Daniel (2023)
This study provides a comprehensive, interdisciplinary assessment of the catastrophic Mediterranean Storm Daniel (2023), linking its atmospheric dynamics, predictability, and impacts in Greece and Libya to climate change considerations. It highlights distinct predictability challenges for the storm's cyclogenesis versus its mature medicane phase and evaluates the capacity of numerical models to forecast such extreme events.
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Yu et al. (2025) Impacts of the mega cascade reservoirs on riverine hydrothermal regimes based on deep learning
This study investigates the impacts of four mega cascade reservoirs on the Lower Jinsha River's downstream hydrological and water temperature regimes using an LSTM-based hydro-thermal model, revealing significant alterations in flow, temperature, and their coupling, with implications for ecological risks.
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Guzzon et al. (2025) Improving extreme precipitation forecasts in Catalonia (NE Iberian Peninsula) using analog methods: A comparison with the GFS model
This study evaluates novel analog-based methods (AMs) to enhance 24-hour extreme precipitation forecasts in Catalonia, aiming to support flood risk management. The findings demonstrate that AMs integrating Seasonal Standardization and the Perfect Prognosis framework significantly improve forecasts compared to the operational Global Forecast System (GFS), particularly in reproducing the intensity and spatial distribution of extreme events.
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Luo et al. (2025) Surface Soil Moisture Retrieval over Winter Wheat Fields Based on Fused Multispectral and L-Band MiniSAR Data
This study proposes a high-accuracy surface soil moisture (SSM) retrieval method for winter wheat fields by fusing Sentinel-2 satellite and UAV multispectral data with L-band MiniSAR observations. The results demonstrate that multi-platform data fusion combined with machine learning significantly outperforms single-satellite approaches, particularly at shallow soil depths.
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Martí et al. (2025) Revisiting Stability Functions of Surface Heat Fluxes in Semi-arid Environments
This study evaluates the accuracy of standard Businger-Dyer stability functions for estimating heat fluxes in semi-arid regions, finding they significantly fail under wet-surface conditions and high Bowen ratios. The research proposes new, Bowen-ratio-dependent stability functions and demonstrates that mixing efficiencies for heat and moisture are rarely equal in these environments.
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Zhang et al. (2025) Influence of drought identification methods on analyzing and assessing responses of water quality to droughts
This study compares fixed (FDT) and variable (VDT) drought identification methods to assess their influence on water quality responses in the Harp Lake catchment, Ontario. Findings reveal that the choice of drought identification method significantly impacts the assessment of water quality parameters (dissolved organic carbon, total nitrogen, total phosphorus) and their dynamics during drought events.
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González-Ramón et al. (2025) Integration of 3d geological models and groundwater flow models for the improvement of the management of complex multilayer aquifers under intensive exploitation. The case of the Loma de Úbeda (Southern Spain)
This study integrates 3D geological and numerical groundwater flow models to improve the management of the complex, intensively exploited multilayer aquifer system of Loma de Úbeda, Southern Spain. The research successfully corroborates the conceptual hydrogeological model and provides a validated tool for sustainable water resource management, highlighting the shift in water storage and flow dynamics due to prolonged pumping.
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Wittmann et al. (2025) Model data underlying the publication: Drought mitigation as a driver of flood risk: Assessing the trade-offs induced by Natural Water Retention Measures
This study provides a comprehensive model dataset to assess the trade-offs of Natural Water Retention Measures (NWRM) on flood risk in shallow groundwater environments by simulating design storm events using a sequentially coupled subsurface-surface hydrological model.
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Ferdinand et al. (2025) Spatio-temporal variability of flooded areas in the Ouémé floodplain (Benin, West Africa) from 2015 to 2023
This study assessed the spatio-temporal variability of flooded areas in the Ou´em´e floodplain (Benin) from 2015 to 2023 using remote sensing and in-situ data, revealing a significant upward trend in flood extent driven by cumulative rainfall and river water surface elevation thresholds.
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Melón-Nava (2025) Patterns of snow cover distribution in the Cantabrian Mountains (NW Spain)
The study evaluates the performance of the ISBA land surface model and the mHM hydrological model across metropolitan France to improve the national hydrometeorological reanalysis. It demonstrates that while mHM excels in river discharge simulation due to its multiscale parameterization, ISBA provides a more comprehensive representation of surface energy fluxes.
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Wang et al. (2025) Does the reduction of precipitation always suppress vegetation productivity?
This study developed a new approach combining percentile and standard deviation methods with the SWH model to assess vegetation sensitivity to water deficit across 77 global sites. It found that soil water content (SWC) is a more critical determinant than precipitation (PPT), revealing contrasting responses and an unexpected increase in gross primary productivity (GPP) under SWC deficit due to active transpiration regulation.
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Chakraborty et al. (2025) The mirage of the silver bullet: Exploring the limitations of high-resolution data in flood model validation
This study explores the limitations of high-resolution data in flood model validation, demonstrating that while beneficial, it does not resolve all discrepancies, which often stem from a complex interplay of observed data limitations, model uncertainties, and structural differences between datasets.
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Liu et al. (2025) Global warming intensifies extreme day-to-day temperature changes in mid–low latitudes
Global warming is intensifying extreme day-to-day temperature changes (DTDTs) in mid-low latitudes, a distinct and largely ignored extreme weather event, posing substantial risks to human health and ecosystems, with climate models projecting further amplification by 2100.
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Silber-Coats et al. (2025) Beyond scarcity: Science-based solutions for water and agriculture in the Western United States
This editorial synthesizes 14 research contributions focusing on science-based demand management strategies for sustainable agriculture in the water-scarce Western United States, demonstrating that agricultural productivity, environmental sustainability, and economic resilience are mutually compatible goals.
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Sharma et al. (2025) Quantifying potential forestation-induced variability in land surface temperature across India: a percentile-based and class-specific assessment
This study investigated forestation-induced changes in daytime land surface temperature (LST) across 14 major forest classes in India, revealing that the effects vary significantly by forest class and elevation, with low-elevation forests generally causing cooling and high-altitude forests tending towards warming.
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Bourbour et al. (2025) Pre-harvest forecasting of rainfed wheat yield in Iran using multi-source remote sensing and machine learning
This study developed and compared machine learning models integrating multi-source remote sensing and meteorological data to forecast rainfed wheat yield across 22 Iranian provinces from 2001 to 2021. The XGBoost algorithm achieved superior accuracy (R²=0.64, MAE=0.25 t/ha) two months pre-harvest, outperforming Random Forest and Support Vector Regression.
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Shitu et al. (2025) A systematic review of advances in estimating irrigation potential in Ethiopia using GIS and remote sensing with future outlook
This systematic review synthesizes advances in irrigation potential estimation in Ethiopia using Geographic Information Systems (GIS) and Remote Sensing (RS), identifying significant progress while highlighting critical research gaps and future directions for sustainable water and land resource management.
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Quintanilla-Albornoz et al. (2025) Almond yield prediction at orchard scale using satellite-derived biophysical traits and crop evapotranspiration combined with machine learning
This study develops a machine learning framework to predict almond yield at the orchard scale across Spain using Sentinel-2 biophysical traits and Sentinel-3 derived evapotranspiration. The results demonstrate that remote sensing-based models achieve predictive accuracy comparable to ground-truth data, with the best model reaching a Root Mean Square Error (RMSE) of 399.1 kg ha⁻¹.
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Wang et al. (2025) Recent south-central Andes water crisis driven by Antarctic amplification is unprecedented over the last eight centuries
This study reconstructs 827 years of Negro River streamflow in northern Patagonia using tree-ring records, revealing an unprecedented decline in recent decades. This decline is primarily driven by Antarctic amplification, which exacerbates temperature rise and disrupts circulation patterns, intensifying regional aridity.
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Kabe et al. (2025) Impact of hydrogeological regime changes on the Bakhtegan-Tashk lake system under groundwater overextraction
This study investigated the impact of human-induced hydrogeological regime changes on the desiccation of the Bakhtegan-Tashk Lake (BTL) system in southern Iran. It revealed a reversal in the natural groundwater-surface water flow, with the lake now losing approximately 10.5 million cubic meters of water annually to overexploited adjacent aquifers, accelerating its desiccation.
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Huang et al. (2025) Differential sensitivities of three types of compound drought and heatwave events to human-induced climate change across the globe
This study quantifies the differential influences of human-induced climate change on three types of compound drought and heatwave (CDHW) events (precipitation-based, runoff-based, and soil-moisture-based) using CMIP6 simulations, revealing greenhouse gas forcing as the dominant driver of global CDHW intensification, particularly for soil-moisture-based events, and projecting significant future severity growth and population exposure under high-emission pathways.
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Leivadiotis et al. (2025) Understanding Flash Droughts in Greece: Implications for Sustainable Water and Agricultural Management
This study investigates the spatiotemporal variability of flash droughts in Greece from 1990 to 2024 using ERA5-Land root-zone soil moisture data. It reveals distinct regional patterns in flash drought characteristics, including frequency, duration, and recovery, providing a data-driven framework for water management and adaptation strategies in Mediterranean agriculture.
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Shahab et al. (2025) Spatiotemporal Evolution of Water Bodies in the Tarbela Dam Region: Drought Impact and Propagation Mechanisms Using Google Earth Engine
This study investigated the spatiotemporal dynamics of water bodies in the Tarbela Dam region using remote sensing and Google Earth Engine, revealing significant losses of permanent water bodies, emergence of new seasonal features, and transitions between water body types, primarily driven by climate change, sedimentation, and anthropogenic factors.
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Li et al. (2025) Societal and environmental interconnections: future directions for flood inundation models
This review synthesizes the evolution of flood inundation models from 1970 to 2023, highlighting the transition toward large-scale simulations and identifying eight interdisciplinary frontiers for future research.
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Robelin et al. (2025) RECHARGE, a model of potential recharge of aquifers applied to mainland France
The study introduces the RECHARGE model, a simplified soil water balance approach designed to estimate potential groundwater recharge across mainland France by correlating effective precipitation with a cartographic infiltration index (IDPR). The model provides a robust, large-scale estimation of renewable groundwater resources, validated against observed river flows and the physically-based SURFEX model.
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Jalilvand et al. (2025) Characterization of irrigation timing using thermal satellite observations, a data-driven approach
This study presents a data-driven framework using thermal satellite observations and change point detection to estimate irrigation timing and individual events. By comparing cropland land surface temperature (LST) with nearby natural vegetation, the method accurately identifies irrigation schedules in diverse agricultural regions.
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Cherie et al. (2025) Agricultural drought dynamics in East Gojjam: Insights on soil moisture, drought indices, and crop sustainability
This study investigates agricultural drought dynamics in East Gojjam, Ethiopia, from 2013 to 2024 by integrating remote sensing indices (NDVI_Max, SWDI, SMA, SPEI) and rainfall data with machine learning models. It found significant interannual drought variability, identifying 2022 as a critical year, and highlighted Soil Water Deficit Index (SWDI) and Normalized Difference Vegetation Index (NDVI_Max) as the most influential predictors of vegetation response.
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Deng et al. (2025) Enhanced water stress on vegetation productivity with climate warming over the Northern Hemisphere
This study investigates the inter-annual changes in gross primary productivity (GPP) in the Northern Hemisphere from 1982 to 2018, revealing that GPP trends stalled after 1998 due to enhanced atmospheric dryness (vapor pressure deficit, VPD) and that dynamic global vegetation models (DGVMs) fail to accurately capture these changes.
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Cenobio-Cruz et al. (2025) Uncertainty propagation from gridded precipitation datasets to streamflow simulations: application to the Reno River basin (Italy)
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Pellicone et al. (2025) Assessment of Multiple Satellite Precipitation Products over Italy
This study evaluated five satellite precipitation products (CHIRPS, GPM, HSAF, PDIRNOW, SM2RAIN) against high-resolution ground data in Italy to address rainfall estimation uncertainties. It found that no single product performs optimally across all metrics, with GPM showing the most balanced performance, and product suitability depending on the intended hydrological application.
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Liang et al. (2025) Quantifying anthropogenic drivers of water storage decline to support sustainable water management in a coal-mining semi-arid region
This study quantifies the anthropogenic drivers of terrestrial and groundwater storage decline in China's Mu Us Sandyland from 2003 to 2020 using a water balance framework, finding that ecological restoration and irrigation are the primary drivers, with coal mining also significant in energy-intensive areas, and proposes spatially differentiated management strategies for future sustainability.
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Majid et al. (2025) Virtual water gauge from the Synthetic Aperture Radar (SAR) altimeters for small reservoirs in tropical regions
This study evaluates the effectiveness of Sentinel-3 SAR altimetry for monitoring water surface elevation in small tropical reservoirs in Malaysia. The research demonstrates that SAR altimetry can achieve high correlations (>0.95) with in-situ gauges, providing a viable "virtual gauge" for complex tropical landscapes.
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Çelik et al. (2025) Spatio-Temporal Analysis of Observed Drought Events in the Tigris–Euphrates Basin during the 1960–2023 Period Via SPI and SPEI Drought Indices
This study analyzed spatio-temporal drought patterns in the Tigris-Euphrates Basin from 1960 to 2023 using SPI and SPEI, finding a significant increase in drought frequency and severity, especially after 1990, driven by rising temperatures and evapotranspiration.
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Chen et al. (2025) A global long-term (2002–2022) C-band vegetation optical depth record retrieved after merging AMSR-E, AMSR2 and WindSat
This study developed a global, long-term (2002–2022) C-band Vegetation Optical Depth (C-VOD) dataset by merging observations from AMSR-E, AMSR2, and WindSat sensors using a combined inter-calibration method. The resulting merged C-VOD exhibited substantially improved temporal consistency across sensors, reducing global discrepancies between AMSR-E and AMSR2 from 6.20 % to 0.34 %.
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Банщикова et al. (2025) Особенности формирования зажоров и заторов льда на реке Вага
This study investigates the conditions and long-term variability of ice jam and ice dam formation on the Vaga River, revealing that these phenomena are annual occurrences with consistent formation locations, and while ice dams are short-lived, ice jams can persist for months and sometimes cause dangerous water level rises.
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Yaseen et al. (2025) Quantitative assessment of best management practices for soil and water conservation: A case study from the Tarquinia plain
This study utilized the Soil and Water Assessment Tool (SWAT) to quantitatively evaluate individual and combined Best Management Practices (BMPs) in the Tarquinia plain, Italy, demonstrating that combined BMPs significantly reduce river sediment load by up to 33.9 %, total nitrogen by 27 %, and total phosphorus by 27.5 %.
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Cruz et al. (2025) Long-term basin trends confirm a record 2022–2024 hydrological drought and water-storage losses in western Amazonia
This study quantifies long-term hydrological trends (1981-2024) in Western Amazonia and diagnoses the unprecedented 2022-2024 hydrological drought, revealing significant delays in high-runoff season onset, decreased low-flow discharge, and record-low terrestrial water storage. The findings underscore the region's increasing vulnerability and the urgent need for adaptive water resource management.
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García‐García et al. (2025) Intercomparison of Earth Observation products for hyper-resolution hydrological modelling over Europe
This study comprehensively evaluated high-resolution Earth Observation (EO) products for precipitation, snow cover area, surface soil moisture, and evapotranspiration over Europe against observational references. It identified specific merged precipitation, MODIS/Sentinel-2 snow, and NSIDC SMAP soil moisture products as best performing for hyper-resolution hydrological modeling, while evapotranspiration products showed similar overall performance.
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Liu et al. (2025) Agricultural rapid-onset droughts in southern China’s grain-producing regions: Spatiotemporal evolution and potential drought-crop risks
This study investigated the spatiotemporal evolution and seasonal characteristics of agricultural rapid-onset droughts and their coupling with critical crop growth stages across southern China's major grain-producing regions from 1950 to 2022. It revealed significant spatial heterogeneity in drought characteristics and identified critical crop-drought coupling risks during specific phenological windows, emphasizing the need for phenology-aligned drought management.
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Hameed et al. (2025) Groundwater storage changes in the United States using baseflow recession method: Comparison with GRACE and well observations
This study quantifies long-term groundwater storage changes in over 1000 minimally disturbed watersheds across the contiguous United States using a novel event-based baseflow recession algorithm, demonstrating its reliability by comparing estimates with GRACE-DA and well observations.
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Zareian et al. (2025) Adapting to dryness: Two decades of agricultural transformation in Iran’s arid zone through the water-energy-food-carbon lens
This study analyzed agricultural transformations in Iran's Isfahan Province (2004–2023) using the Water-Energy-Food-Carbon (WEFC) Nexus framework, revealing that declining groundwater availability, rather than meteorological drought, drove shifts towards water-efficient, high-value crops, improving water productivity and reducing environmental footprints despite a decrease in total cultivated area.
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Mostafazadeh et al. (2025) Spatio-Temporal Pattern and Hotspots of River Flow Discharge Variability and Seasonality in Northwestern Iran
This study evaluates the spatio-temporal seasonality of river discharge across 32 stations in Ardabil Province, Iran, using the Markham Seasonal Index (MSI) over a 40-year period. The research identifies distinct hydrological clusters and spatial hotspots of flow variability, providing a scientific basis for localized flood and drought risk mitigation.
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Madaula et al. (2025) Hypersaline recharge in Mediterranean coastal aquifers: The role of aquifer–lagoon connectivity
This study investigates seasonal salinity variations in the shallow aquifer of the La Pletera salt marsh using time-lapse electrical resistivity tomography (ERT) and continuous monitoring. It reveals that hypersaline lagoons are a primary source of aquifer salinization, particularly after rainfall events, often exceeding the influence of seawater intrusion.
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Abubakar et al. (2025) Evaluation of temporal convolutional networks and ensemble machine learning models for meteorological drought prediction in the Nigerian Sudano–Sahelian zone
This study predicted and characterized meteorological drought in the Sudano–Sahelian region of Nigeria (SSRN) using temporal convolutional networks (TCNs) and ensemble machine learning models. It revealed severe droughts in the 1970s and 1980s, identified dominant drought cycles linked to large-scale climatic oscillations, and demonstrated the high predictive power and generalization consistency of TCNs for drought forecasting.
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Ioniță et al. (2025) Multi-Indicator Drought Variability in Europe (1766–2018)
This study compares three long-term European drought reconstructions (PDSI, SPEI, and SMI) from 1766 to 2018, finding that the identification of "extreme" drought years and decades varies significantly depending on the indicator used. While the 2015–2018 event was exceptional in several metrics, its "unprecedented" status is indicator- and region-dependent, though all indicators consistently link drought to large-scale atmospheric blocking.
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Soltani et al. (2025) Enhancing Flood Forecasting with Machine Learning Informed by Integrated ParFlow-CLM Hydrological Modeling
This study integrates a fully coupled hydrological model (ParFlow/CLM) with a Gated Recurrent Unit (GRU) Convolutional machine learning model to enhance flood forecasting. It demonstrates that incorporating physically-derived soil water content (SWC) significantly improves the accuracy of river discharge predictions, outperforming standalone AI and hydrological models.
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Rosso et al. (2025) Drought hazard assessment across Sweden's diverse hydro-climatic regimes
This study assesses meteorological, agricultural, and hydrological drought hazard across Sweden using multiple standardized indicators and hydrological model simulations. It reveals distinct regional drought patterns, with central-eastern and south-eastern Sweden experiencing increasing dry conditions, while northern and western Sweden show wetting trends.
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Lopez et al. (2025) Evaluating a Simple Algorithm for an Evapotranspiration Retrieval Energy Balance Model in Mediterranean Citrus Orchards
This study evaluates the SAFER (Simple Algorithm for Evapotranspiration Retrieving) model's ability to estimate actual evapotranspiration in a Mediterranean citrus orchard using Sentinel-2 imagery and Eddy Covariance data. The findings indicate that while the model is highly accurate during wet seasons, its performance declines during dry periods due to its limited sensitivity to plant physiological water stress.
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Janicka-Kubiak (2025) Hydrological drought trends and seasonality in selected Polish catchments between 1993 and 2022 using a threshold based approach
This study investigates long-term trends and seasonality of hydrological droughts in selected Polish lowland catchments from 1993 to 2022, revealing a significant increase in summer and autumn low-flow events and a strong correlation between drought intensification and land use changes, particularly urbanisation.
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P. et al. (2025) Integration of Soil Moisture and Meteorological Data Using Deep Learning for Flash Drought Detection in Northeastern Brazil
This study developed and validated a deep learning U-Net model to integrate meteorological and satellite-derived soil moisture data for detecting flash drought events in Northeastern Brazil (NEB) from 2015–2023. The model accurately reproduced flash drought frequency and duration, demonstrating its potential for high-resolution monitoring and improving early-warning systems in data-scarce regions.
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Huang et al. (2025) Simulating precipitation-induced karst-stream interactions using a coupled Darcy–Brinkman–Stokes model
This study developed a coupled Darcy–Brinkman–Stokes model to simulate precipitation-induced karst-stream interactions, integrating water-air two-phase flow and variably saturated conditions. It found that rainfall intensity is the dominant driver, leading to complex multi-media interactions and shifting discharge contributions, with groundwater stored in porous media significantly influencing subsequent stream levels.
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Bouregaa (2025) Comparative evaluation of machine learning models for regional agricultural drought prediction in Algeria using SHAP analysis
This study comparatively evaluated eight machine learning models for regional agricultural drought prediction in Algeria, finding that optimal model performance is highly dependent on region and timescale, and that efficient feature selection can maintain accuracy while SHAP analysis reveals key climate drivers.
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Nguyen‐Duy et al. (2025) Performance and added value of a high-resolution (2 km) rainfall product based on WRF-downscaled ERA5 for Ho Chi Minh City, Vietnam
This study dynamically downscaled ERA5 reanalysis data using the WRF model and applied bias correction to generate a 2-km resolution rainfall product for Ho Chi Minh City, Vietnam. The bias-corrected product (WRFC-HCM) significantly improved daily rainfall accuracy and representation of extreme events compared to original reanalysis datasets, despite limited improvement at the monthly scale.
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Yan et al. (2025) Improved Near-Real-Time Precipitation Estimation From Himawari-8 Data and Gauge Observations in the Xiangjiang River Basin Using a Three-Stage Machine Learning Framework
This paper aims to improve near-real-time precipitation estimation in the Xiangjiang River Basin by developing a three-stage machine learning framework that integrates Himawari-8 satellite data with ground-based gauge observations.
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Aryal et al. (2025) Dynamics of Meteorological and Agricultural Drought in the Karnali River Basin, Nepal
This study provides a multidimensional drought analysis for the Karnali River Basin (Nepal) using 30 years of observational and satellite data, revealing a long-term greening trend despite a significant increase in meteorological drought severity, highlighting the complex interplay of climatic and anthropogenic factors.
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Dorthe et al. (2025) The thermal future of a regulated river: spatiotemporal dynamics of stream temperature under climate change in a peri-Alpine catchment
This study investigates the future thermal regime of a peri-Alpine regulated river under climate change using a high-resolution process-based model. Projections indicate mean annual water temperatures may rise by up to 4 °C by 2080–2090 under RCP 8.5, with river regulation introducing distinct spatial and seasonal warming patterns, particularly in autumn and winter due to reservoir thermal inertia.
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Xu et al. (2025) Objectivization of an expert assessment framework for drought monitoring
The study develops a Comprehensive Drought Monitoring Model (CDMM) that objectivizes the expert-based U.S. Drought Monitor (USDM) framework using the Random Forest algorithm. The model successfully reproduces USDM drought categories and demonstrates high transferability by effectively capturing regional drought dynamics across China.
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Zhu et al. (2025) Drought identification using standardized evaporative fraction: Perspective from surface energy partitioning
This study introduces the Standardized Evaporative Fraction (SEF) as a new drought index, derived from surface energy partitioning, to better incorporate land-atmosphere interactions in drought identification. The SEF is shown to be effective globally from 1960–2022, demonstrating good consistency with existing indices and revealing increasing drought trends in several global hotspots.
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Zhou et al. (2025) A novel Hankel spectrum analysis filtering for reducing North-South stripes in GRACE gravity solutions
This study introduces the Hankel Spectrum Analysis Filtering (HSAF) framework to effectively reduce North-South striping noise in GRACE-derived terrestrial water storage anomalies. HSAF significantly improves the accuracy of water storage estimates by preserving hydrological signals and outperforming conventional filters across global and basin scales.
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Wu et al. (2025) Cascading effects of cross-year droughts on flow-sediment dynamics across distinct drought types
This study investigates the cascading effects of cross-year meteorological and hydrological droughts on flow-sediment dynamics in seven Loess Plateau tributaries. It reveals that hydrological droughts induce significantly greater reductions in sediment transport rates and larger post-drought surges compared to meteorological droughts, with afforestation further reducing sediment supply efficiency.
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Wang et al. (2025) Hidden deep soil moisture droughts
Anthropogenic climate change exacerbates global soil moisture droughts, which are now revealed to also occur in deeper layers, and are projected to become longer lasting and more severe in a warming climate.
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Al-Taher et al. (2025) Optimizing cotton green water footprint prediction using hybrid machine learning algorithms: a case study of Al-Gezira state, Sudan
This study optimizes cotton green water footprint (GWFP) prediction in Al-Gezira state, Sudan, using hybrid machine learning algorithms (RF, XGBoost, SVR) with climatic and remote sensing data from 2001-2020, demonstrating that hybrid models significantly outperform single models in accuracy and error reduction.
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Unknown (2025) Scatterometers in cryospheric applications
This section explores diverse applications of scatterometer data for cryospheric monitoring, including tracking seasonal snow cover melt, analyzing polar ice shelf dynamics, mapping Antarctic sea ice with machine learning, and enhancing cryosphere analysis resolution through pan-sharpening techniques.
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Zheng et al. (2025) Corrigendum to “Coupling differentiable tau-omega model with Kolmogorov–Arnold network for soil moisture estimation over the Tibetan Plateau” [J. Hydrol. 662(Part B) (2025) 133940]
This corrigendum rectifies an error in the author affiliation order for the original article titled "Coupling differentiable tau-omega model with Kolmogorov–Arnold network for soil moisture estimation over the Tibetan Plateau."
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Conway (2025) InSAR Observations of Ground Deformation in Permafrost and Agricultural Regions of an Arid River Basin
This study applies Sentinel-1 InSAR time series analysis to map ground deformation in China's Shiyang River Basin, revealing rapid subsidence in agricultural areas due to groundwater extraction and widespread, variable subsidence in permafrost regions linked to climate-driven thaw.
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Sun et al. (2025) Development of a Coupled Model for Simulating Multiple Processes of Subunit Hydraulics, Soil Water/Salt Transport, and Crop Growth in a Drip Irrigation System
This study develops and validates a coupled model integrating drip hydraulics, soil water/solute transport, and crop growth to simulate drip irrigation systems. The model accurately predicts system performance, soil conditions, and crop yield, demonstrating how hydraulic nonuniformity propagates through the system and can be mitigated by increased irrigation depth.
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Ha et al. (2025) Geographic Extent of Flash Droughts Across the Seven Climatic Sub-regions of Vietnam
This study analyzed the spatio-temporal characteristics and geographic extent of flash droughts across seven climatic sub-regions of Vietnam using ERA5 soil moisture data at three depths. It revealed significant regional and depth-dependent variations, with shallow soil layers being most sensitive, and identified specific northern and southern regions where flash droughts frequently occur during the rainy season, often on a broad spatial scale.
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Tripathy et al. (2025) Lagged Soil Moisture Controls on the Persistence of Drought and Heatwaves in the United States
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Wendt et al. (2025) Controls on the southwest USA hydroclimate over the last six glacial-interglacial cycles
This study uses an absolute-dated speleothem record from Devils Hole cave 2 and Earth system simulations to identify the primary drivers of hydroclimate and vegetation changes in the southwest USA over the last 580,000 years, finding that temperature-related mechanisms primarily control δ18O variability, with secondary influences from North American ice sheets, while vegetation density is forced by Northern Hemisphere summer intensity.
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Guan et al. (2025) Anthropogenic enhancement of subsurface soil moisture droughts
This study introduces a Lagrangian four-dimensional tracking framework to identify "deep droughts" (more extensive moisture deficits in deep than surface soils) and reveals their increasing duration and intensity globally over the past four decades due to anthropogenic climate change, with projections for further exacerbation under higher-emission scenarios.
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Survey et al. (2025) Global temperate drylands climate change vulnerability
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Mouassom et al. (2025) Hydrodynamics of rainfall peaks in homogeneous regions clustered using the K-means algorithm in Central Africa
This study identifies three homogeneous rainfall subregions in Central Africa using K-means clustering on 1984–2023 daily reanalysis data, revealing distinct rainfall peak patterns and their underlying hydrodynamic and thermodynamic mechanisms.
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Wei et al. (2025) Characteristics of spatio-temporal changes in flash droughts based on the CMIP6 Model
This study identifies flash droughts (FDs) using the standardized evaporative stress ratio (SESR) in CMIP6 historical and future Shared Socio-economic Pathway (SSP) scenarios, analyzing their frequency, duration, and intensity across different arid regions globally. The findings reveal significant regional differences in FD characteristics, with higher frequency and intensity in humid regions, leading to the classification of Governance, Concern, and Prevention Areas to inform regionally varied drought management strategies.
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Marín-Martín et al. (2025) A five-century tree-ring record from Spain reveals recent intensification of western Mediterranean precipitation extremes
This study reconstructs 520 years of quantitative precipitation in the Iberian Range, eastern Spain, using tree-ring data, revealing an unprecedented intensification in the frequency and intensity of hydroclimatic extremes during the late 20th and early 21st centuries compared to previous centuries.
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Survey et al. (2025) Global temperate drylands climate change vulnerability
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Liu et al. (2025) High-resolution remote sensing-driven water management in semi-arid basins: A CNN-Attention-SWAT fusion framework for the Fen River
This study proposes a physics-embedded deep learning (PIDL) framework with bidirectional coupling between the SWAT hydrological model and a CNN-Attention-BiLSTM deep learning model to enhance water management in the semi-arid Fen River Basin. The framework demonstrates superior predictive accuracy for runoff and pollution loads, enabling robust, multi-objective optimized strategies for water allocation, pollution control, and ecological restoration.
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Elias et al. (2025) Drought feature assessment unravels how temperature increase has enhanced earlier and more severe drought in Lebanon over the last 60 years
This study investigated how climate change from 1960 to 2020 affected various drought facets in Lebanon using the DFEAT tool, which analyzes daily soil moisture. It revealed a significant shift towards drier conditions, characterized by an earlier drought onset (up to 17 days) and a delayed offset (up to 5 days), primarily driven by rising temperatures despite stable annual precipitation.
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Veness et al. (2025) User priorities for hydrological monitoring infrastructures supporting research and innovation
This study identifies end-user priorities for the UK’s new GBP 38 million Floods and Droughts Research Infrastructure (FDRI), revealing that value is maximized when infrastructures move beyond simple data provision to actively enable decentralized data collection and foster collaborative research communities.
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Jääskeläinen et al. (2025) High-resolution soil moisture mapping in northern boreal forests using SMAP data and downscaling techniques
This study develops a machine-learning-based downscaling model to estimate soil moisture at 1 km and 250 m spatial resolutions across northern boreal forests. By integrating SMAP satellite data with vegetation and weather parameters, the model improves soil moisture prediction accuracy over forested sites compared to original coarse-resolution products.
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Biella et al. (2025) The 2022 drought needs to be a turning point for European drought risk management
This study analyzes the 2022 European drought by linking climate indices with a continent-wide survey of 481 water managers to evaluate sectoral impacts and management effectiveness. The findings reveal that while drought risk is perceived to be increasing across Europe, current management remains largely reactive and fragmented, prompting a call for a legally binding European Drought Directive.
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Samuel et al. (2025) Assessment of Historical and Future Mean and Extreme Precipitation Over Sub‐Saharan Africa Using NEX ‐ GDDP ‐ CMIP6 : Part II —Future Changes
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Abdulahi et al. (2025) Impact of Climate Change on Drought Dynamics in the Ganale Dawa River Basin, Ethiopia
This study assessed the impact of climate change on agricultural and hydrological drought dynamics in Ethiopia's Ganale Dawa Basin using machine learning-enhanced CMIP6 projections and satellite-based indices. Findings reveal increasing variability in agricultural drought and continued recurrence of hydrological drought, especially under high-emission scenarios.
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Yasin et al. (2025) Spatially integrated standardized relative humidity index: A principal component analysis-based approach for regional drought assessment
This study introduces the Multivariate Standardized Relative Humidity Index (MSRHI), a novel drought assessment tool that integrates relative humidity data from multiple stations using Principal Component Analysis (PCA). The index provides a more stable and spatially coherent representation of regional drought conditions across Pakistan's diverse climatic zones compared to traditional station-based univariate indices.
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Iglesias Vázquez (2025) Proof of Concept: JUNON Digital Twin (v1.4d)
This study presents a proof-of-concept (PoC) for the JUNON Digital Twin, a modular software architecture designed to monitor and manage continental environments in the Centre-Val de Loire region. The system integrates real-time aquifer and meteorological data to provide visualization, forecasting, and spatial analysis services for natural resource management.
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Patil et al. (2025) Over 100 global climate sensitive rivers are experiencing large and severe changes in streamflow volume and timing
This study analyzed streamflow volume and timing changes in 812 climate-sensitive rivers globally from 1950 to 2022, finding increasing streamflow and earlier timing in over half of the sites, largely driven by precipitation changes, with significant implications for river health and water management.
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Wang et al. (2025) The effect of rainfall variability on Nitrogen dynamics in a small agricultural catchment
This study investigates the effect of inter-annual and intra-annual rainfall variability on nitrogen (N) dynamics and water quality in a small agricultural catchment in central Germany using a coupled hydrological and N transport model driven by a stochastic rainfall generator. It finds that higher annual precipitation enhances N transformation and transport, while lower annual precipitation promotes N retention, with vegetation health critically influencing N dynamics during extreme droughts and rewetting periods.
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Zhi-jie et al. (2025) Nonstationary Spatiotemporal Projection of Drought Across Seven Climate Regions of China in the 21st Century Based on a Novel Drought Index
This study projects the spatiotemporal evolution of drought across seven climate regions of China in the 21st century using a novel CO2-aware standardized moisture anomaly index (SZI[CO2]) and nonstationary Copula-based approaches. It finds a wetting trend in Northern and Western China, while Central and Southern China are projected to experience drying, with drought characteristics exhibiting strong nonstationarity and higher joint probabilities under high-emission scenarios.
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Huang et al. (2025) Hydropower vulnerability to drought-flood abrupt alternation under climate change
This study quantifies the global impact of drought-flood abrupt alternation (DFAA) events on hydropower, revealing that these rapid transitions significantly reduce generation and that high reservoir regulation capacity is a key factor in mitigating these losses.
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Disasa et al. (2025) Comprehensive review of drought characteristics and intensification under climate change: implications for agriculture and water resources
This review synthesizes the intensification of drought characteristics across meteorological, hydrological, and agricultural sectors under climate change. It highlights how global warming alters drought frequency and severity, leading to significant risks for water resources and crop yields.
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Tucker et al. (2025) Modeling soil water dynamics to optimize blueberry irrigation in sandy soils
This study optimized drip irrigation system design and management for blueberry plants in sandy soils using the HYDRUS-2D model, finding that a single drip line with 0.45 m or 0.60 m emitter spacing, 1800 seconds (0.5 hour) irrigation duration, and a flow rate of 5.250 x 10⁻⁷ m³/s (1.89 L/h) maximized water use efficiency and minimized leaching.
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Zhang et al. (2025) Coupled surface water-groundwater-crop model considering the impact of irrigation using different calibration targets
This study developed a coupled VIC-EPIC-HYDRUS (VEH) model to improve the simulation accuracy of hydrological processes on agricultural land, considering irrigation impacts, and demonstrated its superior performance through multi-objective parameter optimization and validation.
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Anoop et al. (2025) Atmospheric aridity perturbs critical soil moisture thresholds of plant water stress over Indian biomes
This study quantifies critical soil moisture thresholds (θcrit) for Indian biomes using satellite data and two independent methodologies, revealing that atmospheric aridity (VPD) significantly perturbs θcrit, leading to seasonal and hydrological forcing-driven variations. The covariance-based method (Cov(GPP-VPD)-SM) is found to be more sensitive for assessing these dynamics.
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Sindarov et al. (2025) Application of the AquaCrop model for cotton production under water scarce arid conditions
This study calibrated and validated the AquaCrop model for cotton production under arid conditions in Uzbekistan, identifying an optimal irrigation regime (FC 70-70-65%) that maximized yield and water productivity with high model accuracy.
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Gaiolini et al. (2025) Salt migration and export via subsurface irrigation in a saline reclaimed landscape of the Po River lowland (Italy)
This study investigates the causes and quantifies the sources of dissolved salts in a saline reclaimed landscape of the Po River lowland, Italy, focusing on the impact of subsurface irrigation via tile drains. It reveals that sub-irrigation significantly accelerates salinization and salt export, with peaty lenses and decomposing halophytes acting as major salt sources, leading to high surface water salinity.
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Janoski et al. (2025) The Physical Mechanisms of Hurricane Ida’s Extreme Rainfall in New York City: Insights from the Warn-on-Forecast System
This study investigates the atmospheric processes across multiple spatial scales responsible for the record-breaking hourly rainfall in New York City during the remnants of Hurricane Ida. It finds that low-topped supercells, influenced by synoptic circulation, low-level jet strength, and warm front position, produced the highest rainfall rates.
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Povsheniuk (2025) Automation of Agricultural Data Processing Using Computer Vision and IoT Technologies: An Experimental Study
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Blango et al. (2025) Enhancing Water Productivity in Inland Valley Swamps: Sustainable Strategies and Practices
This paper synthesizes sustainable strategies to enhance water productivity in Sierra Leone's Inland Valley Swamps (IVS) for improved food security, demonstrating how integrating small earth dams, floating rice, and water-saving techniques like Alternate Wetting and Drying (AWD) and Aerobic Rice Systems (ARS) can increase rice yields and optimize water use, while also considering climate change impacts on water resources.
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Zhang et al. (2025) From Depletion to Recovery: Tracking Water Storage Changes in the Semiarid Region of Inner Mongolia, China
This study evaluated spatiotemporal variations in terrestrial water storage (TWS) and groundwater storage (GWS) in semiarid Inner Mongolia from April 2002 to January 2025, revealing a long-term TWS and GWS depletion that notably reversed after 2022 due to policy interventions and precipitation changes, with significant regional differences in driving factors.
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Koralegedara et al. (2025) Springtime soil moisture variability and its changing environmental drivers: a CMIP6 multi-model ensemble analysis for the subtropical East Asian region
This study projects springtime soil moisture changes in the subtropical East Asian region (STEA) using a 14-model CMIP6 ensemble and machine learning, revealing a critical shift from rainfall/runoff dominance to near-surface temperature dominance as the primary environmental driver of soil moisture depletion under future warming. This reorganization leads to progressive drought vulnerability, with surface soil moisture decreasing by 9.1% and total soil moisture by 5.7% by the far-future.
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Kanno et al. (2025) Deep sowing accelerates rice emergence under water deficit: field experiments and model development
This study investigated the potential of deep sowing to accelerate rice emergence under water deficit, finding that sowing at 4 cm or deeper significantly advanced emergence in field experiments under drought. A novel process-based model was developed and validated, accurately predicting emergence dates based on sowing depth, soil temperature, and moisture, and suggesting optimal deep sowing depths to mitigate drought risk.
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Sebastian et al. (2025) Incorporating varying vegetation characteristics driven by Hydrometeorology in the land surface modeling by variable Infiltration Capacity model
This study demonstrates the critical role of dynamic vegetation in hydrological modeling, particularly for evapotranspiration in India, by integrating a machine learning model (LSTM) to simulate vegetation variability within the Variable Infiltration Capacity (VIC) model, revealing an 18% increase in annual evapotranspiration compared to static vegetation approaches.
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Anderson et al. (2025) What is a drought-to-flood transition? Pitfalls and recommendations for defining consecutive hydrological extreme events
This study assesses the suitability and differences of various threshold-level methods for defining drought-to-flood transitions using eight case study catchments, revealing that methodological choices significantly alter detected event characteristics and often fail to capture historically impactful transitions.
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Gouahi et al. (2025) Assessment of groundwater drought risk in arid regions using standardized indices and reliability analysis
This study evaluates groundwater drought risk in the Souss-Massa basin, Morocco, by integrating standardized drought indices with probabilistic reliability analysis. The findings reveal that groundwater drought in this arid region is primarily driven by anthropogenic overexploitation rather than meteorological deficits alone, with the Massa basin identified as a high-risk zone.
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Gillo et al. (2025) Integrated assessment of meteorological, hydrological and agricultural drought in Abaya Chamo sub Basin, Ethiopia
This study comprehensively assessed meteorological, hydrological, and agricultural drought characteristics in Ethiopia's Abaya Chamo sub-basin from 1981-2021 using SPEI, SSI, and SSMI, revealing increasing aridity and severe to extreme drought intensities that varied spatially across catchments.
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Manikandan et al. (2025) Agricultural drought propagation across major sorghum growing districts in Tamil Nadu, India
This study quantified the spatial variations in meteorological and agricultural drought frequency and their propagation time at a weekly scale across major sorghum-growing districts in Tamil Nadu, India, revealing significant regional differences in drought response times.
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Gesualdo et al. (2025) Beyond one-size-fits-all: a path toward region-specific flash drought monitoring and management
This study compares six flash drought indicators across contiguous US catchments over a 40-year period, revealing significant inconsistencies and limited agreement among them, and concludes that effective monitoring requires region- and sector-specific approaches rather than a universal definition.
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Ali (2025) Machine learning approaches for soil moisture prediction: enhancing agricultural water management with integrated data
This study evaluates the effectiveness of nine machine learning algorithms for predicting soil moisture at two depths in New South Wales, Australia, using integrated climate, soil, and vegetation data. The results demonstrate that ensemble models, particularly Random Forest and XGBoost, significantly outperform traditional linear models, providing a robust framework for precision irrigation management.
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Adounkpe et al. (2025) Deep Learning at Two Timescales: Dual Neural Networks for Predicting Fast Urban and Slow Karst Floods
This study develops and evaluates dual artificial neural networks (ANNs) for predicting fast urban and slow karst flash floods in the Las River, France, demonstrating that combining specialized ANNs offers the most robust and generalizable flood forecasting performance across both hydrological regimes.
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Sandoval et al. (2025) Towards water resilience: A multi-stage calibration framework for large-scale integrated surface–subsurface hydrological models
This study presents a multi-stage calibration framework for large-scale, high-fidelity integrated surface water–groundwater models using sensitivity analysis and Gaussian Process Regression surrogates. The approach resulted in the first robustly calibrated integrated model of the Po River District (87,000 km²), effectively capturing complex 3D subsurface dynamics and river discharge.
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Guillory et al. (2025) Soil-to-river Cesium-137 transfer in a catchment coupling the SWAT model and a mass balance equation
This study developed a novel coupled SWAT and mass balance model to simulate Cesium-137 (137Cs) transfer from soils to the river outlet in the Ardèche watershed (2138 km2, France), revealing that 83 % of annual 137Cs transport occurs in the particulate phase, predominantly during high-flow events.
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Khan et al. (2025) Deep learning approach for vertical soil moisture profile estimation using hydrometeorological data
This study presents the evaluation of the eartH2Observe Tier-1 dataset, a global ensemble of ten hydrological and land surface models forced by a consistent atmospheric dataset. The research demonstrates that the ensemble mean generally provides a more reliable estimation of global water fluxes and storage than any individual model.
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Bushra et al. (2025) CAMELS-NZ: hydrometeorological time series and landscape attributes for New Zealand
This paper introduces CAMELS-NZ, the first large-sample catchment hydrology dataset for New Zealand, providing hourly hydrometeorological time series and comprehensive landscape attributes for 369 catchments from 1972 to 2024. The dataset fills a critical gap in global hydrology by representing a Pacific Island environment with complex hydrological processes, supporting diverse research applications.
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Anand et al. (2025) Balancing Productivity and Climate Impact: A Framework to Assess Climate‐Smart Irrigation
## Identification - **Journal:** Earth s Future - **Year:** 2025...
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Manteaux et al. (2025) Evaluation of SWAT‐RIVE's Ability to Represent the Hydrobiogeochemical Dynamics in the Vienne Watershed
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Fiorese et al. (2025) Understanding the influence of Malta litho‐structural features on the dynamics of nitrate transport in the vadose zone
This study evaluates and compares the performance of the ISBA land surface model and the mHM hydrological model in simulating river discharge across 560 basins in France. The results demonstrate that mHM significantly outperforms ISBA in discharge simulation accuracy, while ISBA provides a more comprehensive representation of surface energy balance.
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Eiras‐Barca et al. (2025) Revisiting the Impact of Moisture Transport Deficit on Droughts: Prospective Climate Change Analysis and Emerging Hypotheses
This comprehensive review systematically examines the pivotal role of moisture transport deficits in the genesis and progression of droughts under climate change, confirming that these deficiencies amplify drought severity by reducing precipitation or intensifying evaporative demand.
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Lin et al. (2025) Quantifying the Lifespan of 3D Flood Structures: Unlocking the Potential of Flood Detention Areas for Enhanced Flood Control in China
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Pénot et al. (2025) Combining Landsat optical/thermal and LiDAR High Definition data to estimate turbulent fluxes over Mediterranean forests
This study addresses the challenge of estimating sensible (H) and latent (LE) heat fluxes over semi-arid forests by integrating LiDAR-derived canopy height (hc) into a classical thermal-based contextual method. By normalizing Landsat Land Surface Temperature (LST) for hc effects and constraining the dry edge with an energy balance model, the proposed approach significantly improves the accuracy and consistency of turbulent flux estimates across Mediterranean forest sites.
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Alegría et al. (2025) Reuse of wastewater and desalination for urban uses
This paper explores the viability of wastewater reuse and desalination as sustainable alternatives to enhance urban water system resilience, particularly for the Bilbao metropolitan area on the Cantabrian coast, by analyzing existing technologies, regulations, and real-world examples from Spanish cities. It concludes that while both technologies are advanced, their economic optimality for urban-only use varies significantly with climatic factors like rainfall.
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Hong et al. (2025) Quantifying Impacts of Precipitation and Evapotranspiration on Future Runoff in the Han River Basin Using the Budyko Framework
This study quantifies the relative impacts of precipitation and potential evapotranspiration on future runoff in the Han River basin using the Budyko framework. The findings reveal that precipitation is the dominant driver of projected runoff increases, contributing between 67% and 84% to the total change.
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Bernard et al. (2025) Process‐Level Evaluation of the Land‐Atmosphere Interactions Within CNRM‐CM6‐1 Single‐Column Model Configuration
## Identification - **Journal:** Journal of Advances in Modeling Earth Systems - **Year:** 2025...
