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Maines et al. (2026) Recent and future variability in 1-day precipitation extremes in Trentino – South Tyrol (Eastern Italian Alps) based on observations (1956-2023) and climate model projections
This study comprehensively assesses 1-day precipitation extremes in Trentino – South Tyrol (eastern Italian Alps) using observations (1956-2023) and climate model projections, finding increasing intensity and frequency in both past observations (especially in the north, summer/autumn) and future projections, with rarer events becoming more probable under higher warming levels.
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Phommavong et al. (2026) Integrated Approach to Modelling and Forecasting Water Balance under Climate Change in Southern Laos Using Hydrological Model
This study investigates the water balance dynamics in southern Laos from 2018 to 2022, revealing a high infiltration capacity (63.5%) due to sandy loam soils, significant runoff (30%) during monsoons, and low evapotranspiration (6.4%), providing crucial insights for regional water management.
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Chuphal et al. (2026) Development of Gridded Root-Zone Soil Moisture Product for India, 1981–2024
This study developed a high-resolution (0.05°), long-term (1981–2024) daily root-zone soil moisture dataset for India using a hybrid modeling and machine learning approach, providing a crucial resource for drought monitoring and agricultural planning.
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Small et al. (2026) The 1957–1976 Summertime Drought Gap in the Southeastern United States
This paper examined drought frequency in the Southeastern United States from 1931–2024, identifying an exceptional 20-year drought-free period (1957–1976) concurrent with below-average temperatures and a negative Atlantic Multidecadal Oscillation phase, suggesting a rare climatological event unlikely to reoccur.
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Bani et al. (2026) Application of artificial intelligence-based modelling to investigate spring streamflow predictability under ENSO and IOD forcing
This study developed Artificial Neural Network (ANN) models, driven by lagged El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) indices, to forecast spring streamflow in Victoria, Australia. The ANN models consistently and substantially outperformed traditional Multiple Linear Regression (MLR) across diverse catchments, demonstrating enhanced predictive accuracy and better representation of nonlinear climate-streamflow interactions.
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Leščešen et al. (2026) Unraveling Hydrological Dynamics: Investigating the Frequency and Occurrence Rate of Minimum Discharges in Bosnia and Herzegovina
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Kant et al. (2026) Climate change-driven hydroclimatic shifts and energy prospects: Insights from a snow-fed river basin in Western Himalaya
This study assesses the hydrological response and hydropower potential in the data-scarce Upper Beas River basin in the Western Himalaya under future climate change scenarios, finding increasing trends in precipitation, streamflow, and hydropower potential throughout the 21st century, alongside a shift in snowmelt contribution.
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Dehimi et al. (2026) A hybrid methodological framework for flood risk assessment in data-scarce semi-arid basins: Integrating fuzzy AHP and climate scenarios in the Hodna Basin, Algeria
This study developed a hybrid framework integrating Fuzzy AHP and CMIP6 climate scenarios to assess current and future flood risk in Algeria's data-scarce Great Hodna Basin, providing an operational tool for climate-resilient land-use planning.
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Cremaschi et al. (2026) Karst record of Holocene climate and human-induced changes in surface processes in the northern Apennines of Italy
This study reconstructs Holocene environmental changes in the northern Apennines of Italy using clastic and speleothem sediments from Tana della Mussina Cave, revealing the interplay between natural climatic variability and human-induced land use changes, particularly deforestation and pastoralism, in shaping the Earth's Critical Zone dynamics.
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Saini et al. (2026) Understanding glacier dynamics since the Little Ice Age in the sub-basins of Chandrabhaga Basin, Lahaul Himalaya, India
This study quantifies glacier changes in the Chandrabhaga Basin, Lahaul Himalaya, since the Little Ice Age (LIA) to 2023, revealing a 26.27% glacier area retreat and significant fragmentation, driven by regional warming and reduced precipitation, which also caused an upward shift in the Equilibrium Line Altitude (ELA).
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Luintel et al. (2026) Cross-comparison of national drought monitoring products in Central Europe using a new drought impact database
This study evaluated six national drought monitoring products in Central Europe using a novel, high-resolution drought impact database derived from national newspaper reports (2000–2023). It found varying effectiveness in detecting impact occurrence and capturing impact severity across countries and indices, highlighting the need for multi-index approaches and improved impact data for operational drought management.
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Çelik (2026) Shifting aridity patterns in Türkiye: a comparative assessment of De Martonne, UNEP, Erinç and Budyko Dryness indexes
This study comparatively assessed shifting aridity patterns in Türkiye using four dryness indexes and high-resolution climate data for two climate normal periods. It found a consistent expansion of semi-arid areas, primarily driven by increasing potential evapotranspiration rather than precipitation variability, with aridity changes concentrated in semi-arid transition zones.
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Batool et al. (2026) Development of co-integrated standardized procedure for the joint monitoring, forecasting and probabilistic characterization of climate extremes under global climate models
This research develops the Adaptive Joint Standardized Drought and Heatwave Index (AJSDHI) for joint monitoring, forecasting, and probabilistic characterization of climate extremes using multi-model ensembles from CMIP6 GCMs. The study finds K-Component Gaussian Mixture Distribution (K-CGMD) to be the most suitable fitting approach and shows that machine learning models (ELM, MLP) generally outperform ARIMA for forecasting, with moderate wet and cold events having higher long-term probabilities than moderate dry and hot events in the Tibetan Plateau.
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Tang et al. (2026) Fast response of satellite fluorescence-derived plant physiology to drought stress
This study globally disentangles the sequence and drivers of vegetation physiological and structural responses to drought using satellite data. It reveals that satellite fluorescence-derived plant physiology responds to drought within approximately 3 days, significantly faster than structural changes which emerge after approximately 12 days.
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Trullenque‐Blanco et al. (2026) Projected Evolution of Climatic Aridity in Spain: Robust Signals and Model Uncertainties
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Kucheruk et al. (2026) Flash Drought Climatology Over Southeastern South America: Sensitivity to Index and Reanalysis Selection, and Potential Causes
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Comia (2026) Drought analysis in Pemba district, northern Mozambique (1991 – 2023) using the Standardized Precipitation Index (SPI)
This study provides the first comprehensive characterization of drought patterns in the Pemba district, northern Mozambique, using the Standardized Precipitation Index (SPI) derived from satellite precipitation data, revealing 12 distinct drought episodes over 33 years with significant inter-annual variability.
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Vichot‐Llano et al. (2026) Projected 21st Century Changes in Precipitation and Temperature Over Italy Using CMIP6 CMCC ‐ CM2 ‐ SR5 Model and COSMO ‐ CLM Dynamical Downscaling
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Zhang et al. (2026) Multi-source precipitation fusion for hydrological models: Correction and metrics importance analysis
This study developed a lightweight Absolute Distance Inverse Weighting (ADIW) framework to merge eight precipitation datasets, evaluating the merged product's performance and bias-corrected versions through hydrological simulations using HYPE and VIC models in the Ganjiang River Basin. The ADIW+Linear Regression (LR) approach demonstrated optimal hydrological performance, with Relative Bias (RB) and Mean Absolute Error (MAE) identified as key metrics controlling hydrological reliability.
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Abuzarov et al. (2026) Vegetation Health Indicators of Groundwater Discharge: Integration of Sentinel-2 Remote Sensing and Meteorological Time Series in the Northern Apennines (Italy)
This study evaluates the capability of Sentinel-2 derived vegetation indices to indicate groundwater discharge in forested mountainous areas. It found that during droughts, vegetation near springs exhibits significantly higher Normalized Difference Vegetation Index (NDVI), demonstrating groundwater-supported resilience and serving as a reliable indicator for discharge likelihood.
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BAYAZIT et al. (2026) Climate-Induced Vegetation Stress Detected Through Remote Sensing of Hydroclimatic Indicators
This study investigated the effects of hydroclimatic variability and long-term trends on vegetation response in Türkiye's Meriç-Ergene Basin. Findings reveal that vegetation dynamics are increasingly driven by temperature anomalies, leading to heightened evapotranspiration and expedited phenological processes, underscoring the basin's vulnerability to warming and drying.
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Ma et al. (2026) Divergent response of vegetation structure to land-atmosphere droughts across aridity gradients in the Northern Hemisphere
This study used machine learning to investigate the relative contributions of soil moisture (SM) and vapor pressure deficit (VPD) to leaf area index (LAI) across aridity gradients in the Northern Hemisphere, revealing a "seesaw effect" where SM's contribution decreases and VPD's increases with aridity.
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Huang et al. (2026) Unravelling Groundwater–Precipitation Interactions in Karst Aquifers Under the Dual Pressures of Climate Variability and Human Disturbance
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Ultee et al. (2026) CMIP6 climate model spread outweighs glacier model spread in 21st-century drought buffering projections
This study quantifies 21st-century glacial drought buffering across 75 major river basins using an ensemble of three global glacier models forced by 11 CMIP6 climate models, finding that climate model uncertainty significantly outweighs glacier model uncertainty in projections.
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Selek et al. (2026) Multi-Index evaluation of meteorological drought across Türkiye: a temporal and seasonal perspective
This study evaluates the temporal and seasonal dynamics of meteorological drought across Türkiye using SPI, SPEI, and PNI from 1972-2023, revealing an increasing frequency and severity of temperature-driven droughts, particularly in summer and autumn, with a significant intensification after 2000.
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Wang et al. (2026) Evolution characteristics and driving mechanisms of ecological drought from a terrestrial ecosystem perspective
This study systematically investigated the spatiotemporal evolution patterns and driving mechanisms of ecological drought in the Yellow River Basin (YRB) from 1982 to 2022 using a novel Standardized Ecological Water Deficit Index (SEWDI). It found a significant basin-wide drying trend with westward migration of drought centers, primarily driven by evapotranspiration (ET) and the Atlantic Multidecadal Oscillation (AMO).
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Ali et al. (2026) Regional drought assessment using multi-site probabilistically integrated precipitation by Bayesian network
This study proposes a Regional Standardized Precipitation Drought Index (RSPDI) for regional drought assessment by integrating precipitation dynamics from multiple stations using Bayesian Network (BN) theory. Application to two regions in Pakistan showed strong agreement between RSPDI and SPI, demonstrating enhanced spatial coherence and robust probabilistic consistency for regional drought monitoring.
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Rizzoli et al. (2026) Water Resource Management in Wetland: Developing a Predictive Model for Climate Resilience in the Pantanello Natural Park, Italy
This paper describes a hydrological model for the Pantanello Natural Park to identify effective water-resource management strategies. The model demonstrates that a targeted water supply of 0.01 m³/s from April to September significantly reduces dry conditions in the wetland system from 53% to 10%.
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Sánchez-Dávila et al. (2026) Recent water cycle changes in Spanish forests are driven by stand structure more than climatic changes
This study modeled the Spanish forest water cycle from 1990 to 2020 to assess the relative impacts of climate change and forest stand structure on green and blue water. It found that changes in stand structure, particularly leaf area index growth, had a stronger influence on the water cycle than climatic changes, leading to increased green water and decreased blue water.
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Rastipishe et al. (2026) Water-Driven Soil Erosion in Iran’s Agricultural Lands: A Nationwide Synthesis of Drivers, Impacts and Management
This systematic review synthesizes evidence from 399 peer-reviewed studies to evaluate the drivers, impacts, assessment, and management of water-driven soil erosion across Iran's agricultural lands. It reveals a mean annual soil erosion rate of 16.5 t ha⁻¹ yr⁻¹ nationwide, underscoring the critical need for integrated, climate-resilient management strategies.
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Moussaid et al. (2026) K-means clustering applied to vegetation indices for mapping cultivated areas using high-resolution Moroccan Mohammed VI satellite imagery
This study developed a pixel-based unsupervised classification method combining K-means clustering with vegetation indices (NDVI, MNDWI) and the Near-Infrared band to accurately map cultivated areas using high-resolution Moroccan Mohammed VI satellite imagery. The method achieved a low relative error of 1.41%, demonstrating its superior performance compared to traditional approaches for field-scale agricultural mapping.
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Pokhrel et al. (2026) Upstream hydrology and the importance of snowmelt in buffering droughts in the Karnali basin in Nepal
This study quantifies the water balance and drought buffering capacity in Nepal's Karnali basin using a distributed hydrological model, revealing that snowmelt contributes 24% of total discharge and significantly buffers hydrological droughts for up to 6 months.
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Dommange et al. (2026) Climatology of long-term extreme precipitation using rain gauges data over France
This study presents a comprehensive analysis of extreme precipitation events (EPs) across France from 1950 to 2023 using 352 quality-controlled rain gauges, revealing significant intensification of extreme precipitation in southern regions, particularly the Cévennes, alongside a national decrease in the frequency of rainy days, and identifies large-scale atmospheric drivers.
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Tuğrul (2026) A performance comparison of machine learning algorithms for drought forecasting based on SPEI in Norway
This study compares the performance of five machine learning algorithms for forecasting drought based on the Standardized Precipitation Evapotranspiration Index (SPEI) in Bodo, Oslo, and Tromso, Norway. The research identifies the most effective models and input structures for each region, with SVM-M04 demonstrating the best overall performance across Oslo and Tromso, and LSTM-M01 for Bodo.
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Castaldo et al. (2026) Evaluating SEAS5 ECMWF seasonal forecasts for Sicily Mediterranean Island: Retrospective analysis and bias correction
This study evaluates ECMWF SEAS5 seasonal forecasts for temperature and precipitation over Sicily, comparing traditional and Artificial Neural Network (ANN) bias correction methods. It finds that raw forecasts have systematic biases, and the ANN with Individual Member Separated Monthly (IMSM) correction significantly improves forecast accuracy, especially for precipitation, reducing Root Mean Square Error (RMSE) by up to 45 %.
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Lee et al. (2026) A novel approach for soil moisture retrieval from Sentinel-1 SAR via temporal stability-based backscatter analysis
This study developed a novel temporal stability analysis (TSA)-based masking method for Sentinel-1 SAR to improve high-resolution soil moisture retrieval by effectively filtering noisy pixels. The TSA method significantly enhanced correlations and reduced errors compared to existing methods across diverse monitoring networks.
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Islam et al. (2026) Modeling evapotranspiration in diverse climatic zones of Pakistan using Surface Energy Balance Algorithm for Land (SEBAL) through geospatial technologies
This study utilized the SEBAL model with Landsat imagery and meteorological data to estimate actual evapotranspiration (ET) and assess its spatiotemporal variations across Pakistan's diverse climatic zones, revealing significant environmental degradation and increased climatic stress linked to urbanization.
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Wang et al. (2026) Improved estimation of evapotranspiration and gross primary productivity by incorporating soil moisture feedbacks into a coupled ecosystem model
This study developed a fully coupled ecosystem model that explicitly incorporates dynamic soil moisture feedbacks to improve the consistent estimation of gross primary productivity (GPP) and evapotranspiration (ET). The model demonstrated robust performance across 32 diverse sites, significantly enhancing GPP and ET predictions, especially under dry soil conditions, compared to non-coupled approaches.
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Pei et al. (2026) Flooding algorithm combining hydrology and dynamic seed growth
This study develops and validates an improved GIS-based seed propagation algorithm for rapid and accurate flood inundation simulation in data-scarce small and medium-sized river basins, demonstrating superior spatial accuracy (F1 score of 0.76) compared to HEC-RAS models.
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Chen et al. (2026) Enhancement of Global Flood Risk Due To Greater Flood Magnitude and Variability Under Anthropogenic Activities
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Fatma et al. (2026) Analysis of precipitation and temperature trends in the gomti river basin, India (1980–2023)
This study analyzed long-term precipitation and temperature trends in the Gomti River Basin, India (1980–2023), revealing a significant decrease in annual and monsoon rainfall and a slight, seasonally varied increase in mean annual temperature, with implications for water resources and agriculture.
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Debnath et al. (2026) Impacts of Climate Change and Demographic Growth on Future Water Supply and Demand Gap in a River Basin
This study developed a Water Evaluation And Planning (WEAP) model for the Kesinga Sub Catchment of the Mahanadi River basin in India to assess future water supply-demand gaps under climate change and demographic growth, finding significant unmet domestic water demand (up to 20%) in specific demand sites by the 2030s, particularly during lean periods.
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Rahimi et al. (2026) Integrating geospatial intelligence and machine learning for flood susceptibility mapping
This study evaluated five machine learning algorithms and an ensemble voting model for flood susceptibility mapping, demonstrating that the ensemble approach significantly improves accuracy and reliability in identifying flood-prone areas.
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Akaffou et al. (2026) Comparing bias adjustment methods for CMIP6 extreme precipitation projections in the San-Pédro River Basin (Côte d’Ivoire, West Africa)
This study evaluates four bias adjustment methods for CMIP6 extreme precipitation projections in the San-Pédro River Basin, Côte d’Ivoire, identifying CDFt SSR as the most robust for accurately reproducing observed distributions and projecting increased extreme precipitation, which heightens flood risks.
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Rico-Bordera et al. (2026) Emerging Links between Droughts, Heatwaves and Extreme Precipitation in a Western Mediterranean Hotspot: Evidence of Intensifying Compound and Sequential Hazards
This study analyzes the increasing occurrence and impacts of compound and sequential climate events (heatwaves, droughts, forest fires, and extreme precipitation) in the Western Mediterranean Valencian Community from 1979 to 2021, revealing a rising frequency of concurrent hazard days and an increasing influence of Mediterranean Sea warming on autumn flood risks.
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Kalvāne et al. (2026) More frequent warm and dry spells along persistent cold and wet spells in the Baltics
This study analyzed the temporal and spatial variability of warm, cold, wet, and dry spells in the Baltics (Estonia, Latvia, and Lithuania) from 1961 to 2020 using ERA5-Land reanalysis data. The findings reveal a significant increase in the frequency and duration of warm and dry spells, while cold and wet spells moderately decreased, indicating an amplification of extreme weather conditions in the region.
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Lyu et al. (2026) Warming overwhelms CO2-driven drought mitigation in alpine vegetation on the Qinghai-Tibetan Plateau
This study investigates the combined effects of rising atmospheric carbon dioxide (CO₂) and warming on alpine vegetation drought responses on the Qinghai-Tibetan Plateau. It finds that while CO₂ rise alone mitigated drought-induced productivity losses by 5.7%, concurrent warming reversed this benefit, intensifying drought stress by 5.2% due to increased plant water demand.
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Song et al. (2026) Decoupling of gross primary productivity and transpiration revealed through a daily remote sensing modelling approach in arid irrigated farmland
This study investigated the relationship between gross primary productivity (GPP) and transpiration (T) in arid, irrigated farmlands, revealing a weak coupling and significant decoupling where transpiration rates were disproportionately high relative to photosynthesis, especially during the middle to late growing season.
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Türk et al. (2026) Catchment transit time variability with different SAS function parameterizations for the unsaturated zone and groundwater
This study investigated whether stable water isotope (δ2H) measurements in streamflow can effectively represent preferential flow in the unsaturated zone and groundwater using StorAge Selection (SAS) functions. It found that δ2H data are sensitive to preferential flow in the unsaturated zone but insufficient to constrain groundwater preferential flow due to the damping effect of large passive groundwater storage.
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Pinto et al. (2026) User‐Relevant Climate Indices and Associated Uncertainties From Transient Convection‐Permitting Climate Model Projections
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Abidi et al. (2026) Long-term streamflow reconstruction of The Medjerda River, Tunisia, from tree rings
This study presents the first tree-ring-based reconstruction of Medjerda River discharge in Tunisia, extending the natural flow record from 1876 to 2009 CE using seven *Pinus halepensis* chronologies and a hydrological model. The reconstruction explains 54 % of discharge variability and provides crucial long-term context for hydroclimatic extremes, aiding water resource management in this semi-arid region.
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Rahman et al. (2026) Characterization of drought in the Arabian Peninsula: A multi-index approach
This study characterizes drought in the Arabian Peninsula (AP) from 1975 to 2024 using a multi-index approach (SPI, SPEI, EDDI) and ERA5 reanalysis data, revealing a marked increase in drought frequency and severity, particularly in the Southeast and Southwest zones, primarily driven by dewpoint temperature, precipitation, and maximum temperature.
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Évin et al. (2026) Uncertainty sources in a large ensemble of hydrological projections: Regional Climate Models and Internal Variability matter
This study quantifies uncertainty sources in a large ensemble of hydrological projections for Metropolitan France using the QUALYPSO method. It finds that low flows are projected to decrease in southern France, with emission scenarios and regional climate models being dominant uncertainty sources, and highlights that internal variability is often as significant as climate change response uncertainty.
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Kim et al. (2026) Comparative Simulation of Hillslope Runoff Using Two Infiltration Equations
This study compared the performance of Horton and Green-Ampt infiltration equations, coupled with a physically-based overland flow model explicitly accounting for rill-interrill microtopography, in simulating hillslope runoff against field data. It found the Green-Ampt equation superior in validation due to its consideration of antecedent soil moisture, and highlighted that runoff is more sensitive to infiltration parameters than to surface friction.
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Zhao et al. (2026) Quantifying the drivers of river thermal regimes in the Hanjiang River Basin under climate change and reservoir construction
This study developed an integrated SWAT-HHO-LSTM modeling framework to disentangle the impacts of climate change and dam-heightening on river water temperature in the Hanjiang River Basin, revealing a spatial transition from dam-dominated cooling upstream to climate-driven warming downstream.
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Hamel et al. (2026) River temperature response to atmospheric heatwaves is modulated by discharge and meltwater
This study investigates how river water temperature in Alpine regions responds to atmospheric heatwaves, revealing that only 47% of atmospheric heatwaves lead to riverine heatwaves, with discharge and meltwater anomalies significantly modulating this response.
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Boras et al. (2026) Changes in compound dry–hot extremes in Croatia: Spatio-temporal features and the dominant role of temperature
This study investigates the spatio-temporal characteristics and intensity of compound dry and hot (DH) extreme events in Croatia during summer (June-August). It finds a significant increase in the frequency and intensity of these events across all regions of Croatia, primarily driven by rising temperatures, with distinct regional patterns in how temperature contributes to event intensity.
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Zhou et al. (2026) A high-resolution dataset revealing the dynamical variations of the relative humidity in China
This study developed a high-resolution (1 km × 1 km) daily relative humidity dataset for China (1951–2020) using Random Forest interpolation and analyzed its spatiotemporal variations, revealing a significant downward trend of −0.26% per decade from 1956 to 2020.
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Yan et al. (2026) Determination of irrigation water use from multiple soil moisture observations at a fine spatial resolution: Preferred model optimization and fusion strategy
This study proposes a framework to determine high-resolution irrigation water use (IWU) across China using multiple soil moisture (SM) observations, identifying the optimal SM depth and an effective data fusion strategy for improved estimation. The framework demonstrates that surface SM (0–10 cm) combined with an optimal fusion strategy yields the most accurate IWU estimates at a 1 km resolution.
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Oloniyo et al. (2026) Assessment of Heat Stress Hazards in Africa Using CMIP6 and NEX-GDDP Datasets
This study assesses the ability of CMIP6 and NEX-GDDP datasets to reproduce heat stress characteristics across Africa, focusing on heat stress hazard. It finds that while CMIP6 simulations exhibit substantial biases, the NEX-GDDP dataset significantly improves the representation of heat stress hazards by correcting many of these biases, though some overcorrection occurs.
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Chan et al. (2026) UK Hydrological Outlook using Historic Weather Analogues
This study assesses the skill of a new Historic Weather Analogues (HWA) method for seasonal hydrological forecasts across 314 UK catchments, benchmarking it against the standard Ensemble Streamflow Prediction (ESP) and climatology. The HWA method significantly improves winter river flow forecasts nationally, especially in upland, fast-responding catchments, while maintaining comparable skill to ESP in other regions and seasons.
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Chowdhury et al. (2026) Repository of HydroSMADE: Hydropower Site-level Monthly Availability Data Ensemble for 1950-2100 at Existing and Potential Global Sites
This repository introduces HydroSMADE, an open dataset providing monthly hydropower availability for over 125,000 global sites from 1950 to 2100, generated under 30 future climate scenarios using a global hydrologic model.
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Bhattarai et al. (2026) Rainfall relief or humidity havoc? The boon and curse of precipitation during heatwaves
This study investigates the complex interaction between heat, humidity, and precipitation during heatwaves across the contiguous United States from 1980 to 2020. It reveals that while precipitation can terminate heatwaves, it often leads to increased humidity, paradoxically exacerbating heat stress, particularly in vulnerable regions.
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Sanchez et al. (2026) Hotspots and hot moments of metal mobilization: dynamic connectivity in legacy mine waters
This study reveals that metal(loid) mobilization in abandoned underground mines is governed by episodic shifts in subsurface hydrological connectivity, particularly during low-flow and pre-flush periods, leading to disproportionate contaminant release from localized storage zones that are often overlooked by conventional monitoring.
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Roux et al. (2026) Hydrological regime shifts in Sahelian watersheds: an investigation with a simple dynamical model driven by annual precipitation
This study investigates hydrological regime shifts in Sahelian watersheds using a simple dynamical model driven by annual precipitation. It finds that four studied watersheds (Gorouol, Nakanbé, Dargol, Sirba) experienced regime shifts during the droughts of the 1970s–1980s, transitioning from a low to a high runoff coefficient regime.
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Calvo‐Sancho et al. (2026) Human-induced climate change amplification on storm dynamics in Valencia’s 2024 catastrophic flash flood
This study uses a kilometer-scale pseudo-global warming storyline approach to attribute the catastrophic October 2024 Valencia flash flood to anthropogenic climate change, finding that present-day conditions significantly amplified rainfall intensity and the event's overall severity through enhanced moisture and convective processes.
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Fowé et al. (2026) Assessing the Future of Droughts Using Relative Standardized Indices: Insights from the Nakanbé River Basin, West Africa
This study assesses future meteorological and hydrological droughts in the Nakanbé River Basin, Burkina Faso, using relative standardized drought indices and CMIP6 projections. It reveals robust warming and increased evaporative demand will lead to longer, more severe, and more frequent droughts by 2100, particularly under high-emission scenarios, despite uncertain rainfall changes.
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Wu et al. (2026) Linear time-lag effects and nonlinear interactions of global drought-flood abrupt alternation in responses to multiple factors
This study investigated the linear time-lag effects and nonlinear interactions of multiple factors, including surface energy fluxes, on global drought-flood abrupt alternation (DFAA) events. It found that accounting for time-lag effects significantly increased the explanatory power of these factors on DFAA from 33.03% to 70.05%, revealing complex spatial heterogeneity and nonlinear threshold regulations.
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Godet et al. (2026) Quantifying the added value of impact-based warnings for flash flood monitoring using innovative multi-source impact data
This study quantifies the added value of impact-based warnings (IBW) over traditional hazard-based warnings (HBW) for flash flood monitoring in the French Mediterranean region. Using multi-source impact data over a 13-year period, it demonstrates that IBW significantly reduce false alarms and improve the prioritization of affected areas, especially at finer spatial scales.
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Popat et al. (2026) Quantifying groundwater drought hazards with the groundwater level deficit anomaly index (GLDAI)
This study introduces the Groundwater Level Deficit Anomaly Index (GLDAI), a novel metric that integrates both groundwater anomalies and their associated deficits to provide a more accurate characterization of groundwater drought severity. Using 25 years of data from 1,847 monitoring wells across Germany, GLDAI successfully identifies major droughts while reducing the overestimation of severity compared to anomaly-only indices.
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Pary et al. (2026) Trends of rainfed and irrigated crop yield influenced more by increased cultivated area than drought in Iran
This study quantifies the drivers of wheat and barley yield trends in Iran from 1995 to 2022, revealing that the expansion of cultivated area had a significantly larger influence (71–87%) on total production than drought (12–29%). While irrigation provided a buffer, rainfed systems—particularly wheat—remained highly vulnerable to climatic stressors.
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Jagdhuber et al. (2026) Assessing the Spatial Similarity of Soil Moisture Patterns and Their Environmental and Observational Drivers from Remote Sensing and Earth System Modeling Across Europe
This study investigates the spatial similarity of soil moisture patterns between the SMAP passive microwave remote sensing product and the ECMWF IFS Earth system model across Europe. It finds that despite differences in their underlying drivers and methodologies, the two products exhibit significant spatial pattern similarities from local to continental scales.
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Tarpanelli et al. (2026) The Potential of EO Data for Enhanced Flood Monitoring and Forecasting: A Consortium Assessment
This paper provides a consortium assessment reviewing the capabilities of Earth Observation (EO) data to enhance riverine flood monitoring and forecasting systems, evaluating their accuracy, lead time, and reliability while addressing key challenges and outlining future advancements. It concludes that despite significant scientific progress, EO data remain largely under-exploited in operational flood forecasting, particularly in data-scarce regions.
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Sakellariou et al. (2026) Spatiotemporal Drought Assessment Projections for Climate-Resilient Planning in Distinct Mediterranean Agroecosystems
This study provides long-term projections of drought and wetness conditions for three representative Mediterranean agroecosystems (Spain, Tunisia, Lebanon) to support climate-resilient planning. It reveals significant spatial variability in future drought and wetness extremes, with differing timings and intensities of driest and wettest hydrological years across regions, emphasizing the need for spatially targeted adaptation strategies.
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Wu et al. (2026) Modeling runoff with incomplete data: a comparison of hydrological, deep learning, and hybrid approaches
This study systematically evaluates hydrological, deep learning, and hybrid runoff models under various data scarcity scenarios across forty catchments. It finds process-based models more reliable in data-scarce conditions, while hybrid models effectively combine physical knowledge with data-driven flexibility, underscoring the importance of model selection based on data availability.
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Soares et al. (2026) River intermittency: mapping and upscaling of water occurrence using unmanned aerial vehicle, Random Forest and remote sensing landscape attributes
This study maps and models the spatio-temporal dynamics of an intermittent river using UAV surveys to classify water occurrence and Random Forest models with landscape attributes, dam presence, and satellite indices. Model (a), incorporating Sentinel MNDWI, proved most successful in simulating intermittency both temporally and spatially with approximately 80% accuracy.
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Ma et al. (2026) A composite ecological drought index integrating multi-source water and heat stress with time-lag effects: Insights from the Yellow River Basin
This study proposes a Composite Ecological Drought Index (CEDI) using a trivariate copula framework to integrate multi-source water and heat stress with time-lag effects. Applied to the Yellow River Basin, CEDI effectively characterizes ecological drought and vegetation resistance, revealing a general weakening of drought over the past two decades despite regional vulnerabilities.
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K et al. (2026) Forecasting land-use and land-cover change for groundwater sustainability in the Muvattupuzha basin using CA-Markov (2033–2050)
This study integrates satellite-based land-use analysis with machine learning to demonstrate that built-up areas in the Muvattupuzha basin increased from 12.3% to 44.4% between 2003 and 2023. Using CA-Markov modeling, the research forecasts continued urbanization through 2050 and identifies magnesium, calcium, and alkalinity as the primary drivers of groundwater nitrate contamination.
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Jasrotia et al. (2026) Predictive modeling of streamflow in the Chenab basin under anthropogenic and natural forcings
This study projects future streamflow in the Chenab basin under climate change (RCP 4.5 and 8.5) and land use changes using VIC and SWAT models, revealing an overall declining trend in streamflow, with sharper reductions projected under RCP 4.5.
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Ben-Salem et al. (2026) The role of secondary data in estimating groundwater levels in the Iberian Peninsula
This study maps long-term average groundwater levels across the Iberian Peninsula by exploring the value of incorporating various secondary data with cokriging to overcome the scarcity of direct measurements, finding that hydrogeological context significantly improves the reliability of these maps.
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Hamdouni et al. (2026) Evaluation of CMIP6-based climate projections in Northern Morocco: A bias corrected assessment of temperature and precipitation trends in three mediterranean watersheds
This study evaluates historical and future climate trends in three Northern Moroccan watersheds using bias-corrected CMIP6 models, projecting a significant temperature increase (2.5–3.5 °C by 2100) and a substantial precipitation decline (up to 30%) under high-emission scenarios, with the Oued Laou watershed identified as most vulnerable to aridification.
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Ji et al. (2026) Contrasting feedback mechanisms drive basin-scale vegetation vulnerability to drought in cold-arid northern China
This study developed a basin-scale framework using the Standardized Precipitation Evapotranspiration Index (SPEI) and a Composite Vegetation Index (CVI) to assess vegetation vulnerability to drought in cold-arid northern China, revealing spatially differentiated vulnerability driven by contrasting negative and positive feedback mechanisms.
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Gnann et al. (2026) Uncertainty, temporal variability, and influencing factors of empirical streamflow sensitivities
This study systematically evaluates empirical methods for estimating streamflow sensitivities to precipitation and potential evaporation, revealing high uncertainties, particularly for potential evaporation. It demonstrates that these sensitivities are not static but decrease significantly over time (15 %–70 % over 50 years) as aridity increases, urging caution in their use for climate change impact assessments.
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Hu et al. (2026) Advancing hydrological prediction in South Africa with differentiable multi-source meteorological data fusion
This study developed a differentiable multi-source meteorological data fusion framework for regional runoff prediction in 188 South African basins, which significantly outperformed non-fusion baselines by adaptively weighting precipitation sources without relying on ground observations. The framework achieved a median Nash–Sutcliffe efficiency of 0.38, representing a greater than 52 % improvement over single-source models and a 23 % increase over direct splicing.
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Liu et al. (2026) Assessing the impact of drought on water use efficiency among ecosystems on the Mongolian Plateau
This study investigated the responses of precipitation use efficiency (PUE), soil water use efficiency (SWUE), and groundwater use efficiency (GWUE) to meteorological, soil, and groundwater drought conditions on the Mongolian Plateau from 2000 to 2020. Findings reveal that while WUE indicators generally increased, their responses to drought varied significantly by region and vegetation type, exhibiting lagged effects ranging from 2.4 to 4.4 months, with groundwater drought often reducing GWUE, particularly in grasslands.
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She et al. (2026) Copula–information gain-based identification of GPP response thresholds under multiscale agricultural drought
This study develops a Copula–Information Gain (Copula–IG) framework to objectively identify Gross Primary Productivity (GPP) drought response thresholds across multiple temporal scales in China. It reveals pronounced spatiotemporal heterogeneity and scale dependence in GPP responses, with model performance improving and thresholds becoming more stable at longer drought durations.
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Unknown (2026) Tree rings and salt lakes give clues about ancient rainfall
This historical study aimed to accurately reconstruct ancient rainfall using tree rings, finding that variations in salt lake levels provided a crucial independent control, leading to a confident rainfall curve for the past four millennia in the Great Basin.
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Yanqun et al. (2026) Harnessing satellite-driven insights for dynamic soil moisture tracking in smart farming systems
This study developed and validated an integrated framework using Landsat 8 satellite data and IoT-enabled ground sensors to dynamically track soil moisture variability in the Angreb Watershed, Ethiopia, demonstrating its high accuracy and applicability for precision irrigation and smart farming.
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Meng et al. (2026) Similarity-based classification of groundwater hydrographs to reveal regional groundwater dynamics patterns in a semi-arid agricultural area
This study develops a similarity-based classification of groundwater hydrographs in the North China Plain to reveal regional groundwater dynamics patterns, identifying six distinct clusters primarily driven by crop-related irrigation demands and the long-term cumulative water balance.
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Zhou et al. (2026) Integrating distributed hydrologic simulation with low-flow resilience: a spatiotemporal perspective
This study utilizes a fully distributed watershed hydrologic model to investigate low-flow resilience in a poorly gauged basin, revealing distinct spatiotemporal patterns where low flow emerges after approximately 120 days of minimal rainfall, and downstream reaches exhibit higher resilience compared to upstream areas.
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Homtong et al. (2026) Mapping spatiotemporal agricultural droughts from 2019 to 2024 in Northeast Thailand using multi-temporal and multiple sensor data together with random forest algorithm
This study mapped spatiotemporal agricultural droughts in Northeast Thailand from 2019 to 2024 using multi-temporal Sentinel-2 imagery and a Random Forest Regression algorithm, with a Soil Moisture Index (SMI) derived from Landsat 8 as reference data. The models achieved high accuracy (R > 0.65), revealing consistent severe drought events between March and May annually, with irrigated areas showing lower severity.
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Shokri et al. (2026) Better continental-scale streamflow predictions for Australia: LSTM as a land surface model post-processor and standalone hydrological model
This study evaluates two Long Short-Term Memory (LSTM)-based models (standalone and hybrid with AWRA-L) for continental-scale streamflow prediction in Australia, demonstrating their superior performance over traditional land surface and conceptual hydrological models across various validation scenarios. The findings highlight the potential of deep learning to enhance water resource management and climate adaptation strategies.
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Gao et al. (2026) Nonlinear characteristics and driving factors of vegetation-soil moisture feedback at fine scale in Northeast China
This study investigated the nonlinear, bidirectional feedback mechanisms between vegetation gross primary productivity (GPP) and soil moisture (SM) at fine spatial scales (1 km) and different depths (0–100 cm) in Northeast China from 2000 to 2022. It revealed predominant synergistic growth and bidirectional causality, with SM's influence on GPP generally stronger, a 2–3 month lagged response, and regulation by climatic and geographical factors.
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Wang et al. (2026) The impact of 75 years of climate change on Mediterranean glacier mass balance
This study investigates the impact of 75 years of climate change on Mediterranean glacier mass balance and snowpack dynamics, revealing a dominant control by rising summer temperatures and a limited influence of the North Atlantic Oscillation (NAO). It highlights that local topoclimatic factors, such as avalanching snow, are critical for the survival of the region's remaining small, warm-wet glaciers.
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Kumari et al. (2026) Spatio-temporal analysis of rainfall extremes and drought variability in the Tel basin, Odisha, India, under changing climate
This study analyzed spatio-temporal rainfall trends, extreme climatic indices, and drought variability in India's Tel Basin (1981-2021), revealing increasing monsoon rainfall and heavy rainfall events, declining pre-monsoon rainfall and wet days, and an intensified drying trend driven by rising temperatures, highlighting the urgent need for adaptive water management.
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Wang et al. (2026) Long‐Term Trends of Multiple Drought Types and Their Characteristics From ERA5 Since 1940 in the Yangtze River Basin
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Macdonald et al. (2026) Future Climate Change Assessment in Flood Risk Management: A Synthesis of Practices in Germany and the BeNeLux Countries
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Tian et al. (2026) Characteristics of drought evolution and response relationships on the Northern Slope of the Tianshan Mountains
This study investigated the spatiotemporal evolution and response relationships of meteorological, hydrological, and agricultural droughts on the Northern Slope of the Tianshan Mountains from 1980 to 2019, revealing an overall alleviation of drought conditions but complex propagation mechanisms influenced by climatic and anthropogenic factors.
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Montiel et al. (2026) Evaluation of satellite precipitation products across climatic and topographic gradients in a basin in Northern South America
This study evaluates the performance of five gridded precipitation satellite products (GPPs) across climatic and topographic gradients in the Ranchería river basin, northern Colombia. The findings indicate that CHIRPSv3 exhibits the best overall performance and inter-scale consistency, with all products showing improved reliability with temporal aggregation but degraded performance at higher elevations.
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Hou et al. (2026) Global rainfall simulator studies: review, challenges and perspectives
This review paper comprehensively examines the technological progression, types, applications, limitations, and future prospects of global rainfall simulators, emphasizing the critical need for standardization to enhance their reliability and comparability in soil erosion and hydrological research.
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Li et al. (2026) An Interpretable Index-Based Analysis and Scenario-Based Spatial Simulation of Vegetation Drought in the Yellow River Water Conservation Area
This study developed a Temperature–Vegetation–Precipitation Drought Index (TVPDI) to characterize vegetation drought dynamics in the Yellow River Water Conservation Area (YRWC) and analyzed the nonlinear responses of key factors, finding that precipitation is the primary driver and high-emission scenarios significantly exacerbate future drought severity.
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Yu et al. (2026) Future Climate Change Increases Streamflow and Risks of Hydrological Hazards in the Pearl River Basin
This study projects future runoff in the Pearl River Basin (PRB) under various Shared Socioeconomic Pathway (SSP) scenarios, revealing a significant increase in overall runoff, heightened flood risks during wet seasons, and potential drought risks in specific sub-basins during dry seasons, necessitating adaptive water resource management.
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Xu et al. (2026) Drought as a risk amplifier: The intensifying regime of compound dry-hot events in China
This study investigates the spatiotemporal changes and risk amplification of compound dry-hot (CDH) events in China from 1962 to 2022, revealing a significant increase in their frequency, duration, and severity, with drought amplifying concurrent heatwave risks by 3-7 times.
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Ogle et al. (2026) Image-based classification of stream stage to support ephemeral stream monitoring
This study develops a low-cost, image-based machine learning method to classify relative stream stage (no, low, or high water levels) in ephemeral streams using field camera imagery from 2017-2023 in the upper Russian River watershed, California, demonstrating its utility for monitoring and quality control in data-scarce intermittent river systems.
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Howard et al. (2026) The Vulnerability and Resilience of Drinking Water Systems to Extreme Weather Events and Future Climate Change
This review synthesizes current evidence on the climate resilience of the drinking water sector, examining how climate hazards are changing, how resilience is measured, and what interventions are being used. It concludes that climate change poses a major and increasing threat to drinking water supplies, but current actions to improve resilience are insufficient, and measurement methodologies remain fragmented.
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Zotta et al. (2026) Improving AMSR2 vegetation optical depth retrievals via land parameter retrieval model parameter optimisation
This study improves Vegetation Optical Depth (VOD) estimates from AMSR2 X-band observations by optimising key Land Parameter Retrieval Model (LPRM) parameters (surface roughness, effective temperature, single scattering albedo) through minimising brightness temperature residuals, demonstrating enhanced VOD-LAI seasonal agreement, especially in forests, but revealing trade-offs with soil moisture retrieval skill.
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Polls et al. (2026) Observed Effects of Near-Surface Relative Humidity on Rainfall Microphysics During the LIAISE Field Campaign
This study investigates how near-surface relative humidity influences early-stage rainfall characteristics, finding that dry conditions lead to longer precipitation descent times, fewer small drops, and higher surface radar reflectivity compared to moist conditions, despite similar surface rainfall amounts.
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Zhang et al. (2026) A framework for identifying discriminative model, key factors, and precipitation blocking threshold on triggering drought propagation in the Xijiang River Basin (XRB)
This study developed a GANs-enhanced machine learning framework to identify key factors and precipitation thresholds for meteorological-to-agricultural drought propagation in the Xijiang River Basin, finding that non-effective precipitation days, drought duration, and spatial complexity are critical, and daily precipitation exceeding 3 mm can mitigate propagation.
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Bonacci et al. (2026) Assessing Drought Intensification with SPEI and NDI in Pazin, Istria (Northern Adriatic, Croatia)
This study investigated drought intensification in the continental Istrian peninsula using the Standardized Precipitation Evapotranspiration Index (SPEI) and the New Drought Index (NDI), revealing a significant increase in mean annual air temperatures since the late 1990s and intensified drought conditions after 1985, with NDI showing higher sensitivity to temperature-driven processes.
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Mitze et al. (2026) Validation of analog sensor measurements in hydrometeorological participatory monitoring in various tropical countries
This study validates a participatory monitoring approach using analog low-cost sensors for hydrometeorological data collection in tropical mountain regions, finding that analog thermometers and water level gauges provide reliable data, while hygrometers require correction and small rain gauges are inadequate for heavy rainfall.
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Zhou et al. (2026) An impact-based drought classification method using real-world agricultural drought records and explainable automated machine learning
This study introduces a novel impact-based framework combining causal inference with explainable Automated Machine Learning (AutoML) to classify drought severity and identify its primary drivers in China. The framework, leveraging real-world impact records, outperforms conventional methods, revealing that non-climatic factors (latitude, geopotential height) and climatic factors (soil moisture, evaporation) are key drivers, and indicating a significant intensification of drought severity across China from 1980 to 2024.
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Zuo et al. (2026) Decoding surface and root-zone soil moisture dynamics for agricultural drought assessment using multi-source climate records (1990–2019)
This study investigates the dynamics of surface and root-zone soil moisture using 30 years of ESA-CCI data to assess agricultural drought characteristics in three US states and develops a novel knowledge-guided machine learning model for improved drought prediction. It reveals distinct soil moisture responses to precipitation during prolonged versus short-duration droughts and demonstrates an 8% improvement in root-zone soil moisture prediction accuracy with the new model.
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Chaves et al. (2026) When physics gets in the way: an entropy-based evaluation of conceptual constraints in hybrid hydrological models
This study introduces an information theory-based metric to quantitatively evaluate the relative contributions of physics-based conceptual constraints and data-driven components in hybrid hydrological models. It finds that performance predominantly relies on the data-driven component, which often compensates for or even overwrites physics-based constraints, challenging the assumption that integrating physics inherently enhances model performance or interpretability.
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Wu et al. (2026) Propagation patterns of hydrological droughts in the source region of Yellow River: Insights from standardized versus threshold‐based approaches
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Bian et al. (2026) Intercomparison and sensitivity analysis of WRF parameterization schemes for convection-permitting modeling of precipitation distribution along the Yarlung Zangbo River
This study systematically intercompares fifteen 3-kilometer WRF simulations to assess how parameterization choices influence precipitation characteristics in the Yarlung Zangbo River basin. It finds that convection-permitting models improve precipitation estimation by mitigating drizzle bias and that cloud microphysics and planetary boundary layer schemes are most influential for precipitation intensity, duration, diurnal cycles, and frequency.
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Li et al. (2026) Investigating the spatiotemporal behavior of VIC model parameters over the Tibetan plateau via global sensitivity analysis and machine learning
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González-Leiva et al. (2026) When will meteorological droughts become the new normal climatic condition in Central-Southern Chile?
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Kim et al. (2026) Quantitative risk assessment for the compound drought-wildfire disaster
This study develops a novel methodology for the quantitative risk assessment of compound drought-wildfire (CDW) disasters in South Korea, demonstrating that drought conditions can amplify wildfire risk by approximately three times compared to normal conditions.
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Liang et al. (2026) Anthropogenically-driven escalating impact of soil-based compound dry-hot extremes on vegetation productivity
This study reveals that soil-based compound dry-hot extremes (CDHEs) have more severe adverse impacts on vegetation productivity in China than meteorological CDHEs. Their frequency and coverage area significantly increased from 1980-2017 primarily due to anthropogenic soil warming, and are projected to escalate further under high-emission scenarios, threatening terrestrial carbon sinks.
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Raja et al. (2026) Integrated drought monitoring using remote sensing and meteorological indices in arid western Rajasthan
This study assessed the efficacy of remote sensing and meteorological drought indices for monitoring agricultural droughts in western Rajasthan, India. It found that the Standardized Vegetation Index (SVI) strongly correlates with meteorological indices and crop yield, making it a reliable tool for agricultural drought assessment in arid environments.
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Yao et al. (2026) Persisting Modulation of Interdecadal Pacific Oscillation on Near‐Future Winter Precipitation Projections in Northern Europe
## Identification - **Journal:** Geophysical Research Letters - **Year:** 2026...
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Guliyeva et al. (2026) Geospatial Technologies for Flood and Drought Management: A Review of Earth Observation Data, Procedures, and their Operational Effectiveness
This review synthesizes the current state of Earth Observation (EO) data and procedures for operational flood and drought management, introducing the Operational EO Integration Framework (OEI-F) to systematically align EO data types, integration approaches, spatial scales, and response substages. It highlights the pivotal role of EO in strengthening climate adaptation and multi-hazard resilience while identifying persistent challenges and offering strategic recommendations.
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Arnáez et al. (2026) Hydrological Challenges and Competing Demands in the Mediterranean Region
This review examines the severe hydrological challenges in the Mediterranean region, highlighting the growing conflicts between declining water resources in mountainous headwaters (due to climate change and revegetation) and increasing water demand in lowlands (driven by agriculture, tourism, and urban expansion), which leads to environmental and social tensions.
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Othman et al. (2026) A comparative analysis of long-term spatiotemporal variability in precipitation 85 year-long reanalysis and observation data from 150 stations over arid MENA-T region
This study comprehensively analyzed long-term spatiotemporal precipitation variability and trends across the MENA-T region using 85 years of in-situ and ERA5 reanalysis data, revealing a distinct north-south hydroclimatic dipole with increasing aridity in the south and intensifying extremes in the north.
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Yang et al. (2026) Trigger thresholds and drivers of meteorological to agricultural drought propagation in the Hanjiang basin under climate change
This study quantifies how climate change alters meteorological drought trigger thresholds for agricultural drought in the Hanjiang basin, finding that milder meteorological deficits will increasingly trigger agricultural drought by 2100, with temperature dominating annual shifts and precipitation/evaporation driving seasonal changes.
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Neuhauser et al. (2026) Seasonal hazard-vulnerability patterns between drought and wildfire in New Caledonia derived from remote sensing products
This study analyzed seasonal and directional temporal relationships between vegetation drought and wildfire activity in New Caledonia using remote sensing and in-situ data from 2000-2024, revealing distinct seasonal patterns where vegetation stress precedes fires in the early dry season, and fires are followed by altered vegetation conditions later.
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Mohajane et al. (2026) Machine Learning-Based Flood Susceptibility Mapping Using Geoenvironmental Factors in Central Morocco
This study evaluates and compares three machine learning models (CART, SVM, XGBoost) for flood susceptibility mapping in the Tensift Watershed, Central Morocco, identifying Classification and Regression Trees (CART) as the most accurate model with an Area Under the Curve (AUC) of 0.882.
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Verma et al. (2026) CTRIP‐HyDAS: A Global‐Scale Data Assimilation Framework for SWOT‐Derived Discharge Using Synthetic Observations at High Resolution (1/12°)
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Malcheva et al. (2026) Analysis of Precipitation and Regionalization of Torrential Rainfall in Bulgaria
This study comprehensively analyzes precipitation regimes and their links to atmospheric circulation in Bulgaria (1991–2020) and proposes a regionalization of torrential rainfall, finding it primarily associated with low-pressure systems, easterly/northeasterly flows, and weak-gradient pressure fields.
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Güler et al. (2026) Influence of teleconnection patterns on daily extreme precipitation in Turkey
This study investigates the relationship between four major teleconnection patterns (NAO, AO, NCP, EA) and the frequency and intensity of daily extreme precipitation across Turkey from 1950 to 2023. It finds that the North Atlantic Oscillation (NAO) is the dominant influence, particularly in western Turkey during winter and autumn, with distinct responses for extreme precipitation frequency versus intensity.
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Shi et al. (2026) Spatiotemporal drought variability in Gansu Province based on reconstructed land surface temperature
This study developed a novel framework integrating reconstructed Land Surface Temperature (LST)-derived Temperature Vegetation Drought Index (TVDI) with the Standardized Precipitation Index (SPI) to analyze spatiotemporal drought variability in Gansu Province from 2003 to 2022, revealing a "south mild, northwest severe" drought pattern with overall intensification since 2008.
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Oduor et al. (2026) Future of Water Security in Mediterranean Reservoirs: Advancing SWAT + Modeling of Hydrological Response To Climate Change in Central Spain
This study applied the SWAT+ model with an innovative multi-criteria calibration to simulate hydrological behavior and assess climate change impacts in two reservoir catchments in central Spain. Projections indicate significant declines in precipitation and water availability, coupled with increased potential evapotranspiration, leading to an accelerating transition towards an arid hydrological regime by the end of the century.
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Li et al. (2026) ELM‐MOSART‐DOC: A Large‐Scale Riverine Dissolved Organic Carbon Model and Its Application Over the United States
## Identification - **Journal:** Journal of Advances in Modeling Earth Systems - **Year:** 2026...
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Said et al. (2026) Water Demand and Surface Water Supply Dynamics in the Changing Climate of Semi-Arid Basins
This paper quantifies the short- and long-term impacts of climate change on potential evapotranspiration (PET) and surface water flow (Q) in the ungauged, semi-arid Kherbet Qanafar sub-basin (Lebanon), projecting significant declines in water supply (Q) by 38–52 % in the short term and up to 60 % in the long term, while PET changes are nominal.
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Harris et al. (2026) Weather News
## Identification - **Journal:** Weather - **Year:** 2026...
