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Salar-Khorasani et al. (2026) Forensic hydrological assessment of flood response under land use/land cover (LULC) change using ANN and HEC–HMS
This study develops an integrative methodological framework combining forensic hydrology, artificial neural networks (ANNs), and physically-based hydrological modeling to assess the impacts of projected land use/land cover (LULC) changes on future flood dynamics in the upstream watershed of Golestan Dam, Iran. The simulations revealed highly non-linear growth in peak discharges due to increased barren land contribution.
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Xu et al. (2026) Extended global terrestrial evapotranspiration and gross primary production dataset from 1982 to near present
This study presents the PML-V2.2 dataset, a high-fidelity, long-term, and near-present global terrestrial evapotranspiration (ET) and gross primary production (GPP) dataset from 1982 to 2025. The dataset is developed using the Penman-Monteith-Leuning (PML) model, which estimates ET and GPP through a coupled water-carbon mechanism.
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Wang et al. (2026) Interannual‐Decadal Hydroclimatic Variability in the Southern Himalaya Over the Past 500 Years: Mechanisms From MADA‐PHYDA Integration
This study investigates the drivers of interannual-to-decadal hydroclimatic variability in the southern Himalaya over the last 500 years using a combination of proxy records and data assimilation products. The research reveals robust interannual and multidecadal variability, linked to El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole, as well as Pacific climate patterns.
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Hong et al. (2026) The role of soil properties in modulating the impact of groundwater-induced drainage dynamics on soil moisture availability in texas watersheds
This study presents a novel Land Surface Model (LSM) that describes soil drainage dynamics resulting from a two-way hydraulic continuum among the vadose zone, groundwater, and river. The model, NWM-BE3S ver1.1, was developed by integrating the BE3S's hydraulic gradient-driven continuum scheme into the WRF-Hydro National Water Model framework.
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Zeydalinejad et al. (2026) How to overcome hydrologic data scarcity in assessing potential groundwater risk to subterranean infrastructure: a finite-difference modelling approach
This study develops a finite-difference groundwater flow model to assess potential groundwater risk to subterranean infrastructure in the Dawlish region, southwest UK. The model integrates indirect data sources to construct a hydraulically consistent GWF model under data-scarce and hydrogeologically complex conditions.
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Úlehla (2026) Modelling the irrigation regimes of lucern
This study compares actual irrigation regimes of lucern with calculated regimes based on weather data using a computer model, demonstrating a reasonable correlation between the two. The findings led to the development of a program for predicting weekly irrigation requirements.
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Dolan et al. (2026) Multivariate SWAT streamflow and surface water storage calibration enables upper Mississippi River Basin wetland change scenarios
This study demonstrates the importance of incorporating surface water storage dynamics into hydrological model calibration processes to improve accuracy in simulating river discharge and flood impact predictions. A multivariate calibration approach that includes satellite-based surface water storage estimates was found to reduce model output uncertainty.
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Liu et al. (2026) HydEquivNet: bridging classical unit hydrograph theory and data-driven hydrology via scale-equivariant learning
This paper proposes HydEquivNet (HEN), a novel architecture that introduces Lie group equivariance into hydrological modeling, achieving improved physical consistency and robustness in rainfall-runoff simulation.
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Sánchez-Balseca et al. (2026) Green Infrastructure as a Climate Shield: Nonlinear Flood Response and Extremes Saturation in a Tropical Andean Urban Watershed
This study introduces an integrated methodology to evaluate the hydrological role of green infrastructure in tropical mountain watersheds under climate change, using a framework that combines CMIP6 projections with Quantile Mapping bias correction and physically informed IDF curve development.
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Romijn et al. (2026) Shifting Northern Hemisphere snowfall extremes and their physical drivers
This study examines the changes in extreme snowfall across the Northern Hemisphere under a 2K warming scenario using the Large ENsemble TIme Slice (LENTIS) model. The results show that while light snowfall is projected to decline significantly, particularly in maritime and mid-latitude regions near the melting point, increases are expected in high-latitude maritime, select high-altitude and continental areas.
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Patil et al. (2026) Precision Irrigation Scheduling for Tomato Cultivation Using Soil-Moisture and Weather Signals
This simulated study compares the effects of fixed-schedule irrigation versus sensor-guided precision irrigation on tomato yield and water use in a 12-week experiment. The results show significant improvements in key outcome indicators under precision irrigation.
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Delfino et al. (2026) Impact of warming on rainfall changes in damaging Philippine typhoons using high-resolution convection-permitting models
This study investigates the changes in tropical cyclone-associated precipitation in the Philippines under past and future climate scenarios using high-resolution pseudo-global warming simulations. The results show a significant increase in TC precipitation with warming, consistent with Clausius-Clapeyron scaling expectations.
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Korotkov (2026) The influence of different irrigation methods on evapotranspiration, pasture yield, and forage quality
This study compares various irrigation methods on sown pastures to evaluate the benefits of subsurface irrigation and intermittent moistening over sprinkling. The results show that intermittent moistening achieves the highest economy in water use, resulting in a 30-35% increase in dry matter yield.
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Barling (2026) Water Storage Under Climate Variability: From Vadose Zone Rock Moisture Dynamics to a Decision Support Framework for Managed Aquifer Recharge
This dissertation explores the impact of climate change on hydrologic partitioning in hillslopes and groundwater recharge through a mechanistic understanding of subsurface moisture dynamics. A decision support framework is also developed to aid in the evaluation of managed aquifer recharge feasibility.
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Olivetti et al. (2026) Assessing the real-world economic value of weather forecasts for compounding extremes
This study presents a flexible framework to assess the real-world economic value of weather forecasts, accounting for compounding losses from multiple extreme events and varying cost-loss ratios. The framework is applied to cities exposed to extreme weather hazards, comparing leading physics-based and data-driven forecasting systems.
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Duan et al. (2026) Enhanced detectability of forced signal in monthly precipitation changes
This study investigates the detection of forced signals in monthly precipitation changes using a pattern-based fingerprinting method. The results show that standardization significantly improves the detectability of forced signals, enabling the detection of previously undetectable signals without spatial aggregation.
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Terassi et al. (2026) Satellite and Reanalysis Dataset Dependence of ETCCDI Extreme Precipitation Trends in Paraná, Southern Brazil
This study analyzes extreme precipitation variability in Paraná State, Brazil (1983–2024), finding that detected trends are highly dependent on the dataset used, with evidence of an extended mid-year dry season and rainfall redistribution toward the austral spring.
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Gül et al. (2026) A Skewness–Kurtosis Adjusted Expansion of the Standardised Precipitation Index for Drought Analysis
The study proposes the eXpanded SPI (X-SPI), a drought index that adjusts the classical Standardized Precipitation Index (SPI) by incorporating skewness and kurtosis to better account for local precipitation variability.
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Hierro (2026) Decoupling Between South American Low‐Level Jet Intensity and Precipitation Extremes in Southeastern South America
This study examines the relationship between the South American Low-Level Jet (SALLJ) and extreme precipitation in Southeastern South America, concluding that while the jet significantly boosts the probability of extreme rain, it requires specific upper-level dynamical coupling to trigger convection.
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Rottler et al. (2026) Station‐Based Assessment of Sub‐Seasonal Climate Trends in the Tyrolean Alps (Austria)
This study quantifies sub-seasonal and elevation-dependent climate trends in the Tyrolean Alps (Austria) using multi-variate observations, revealing a mean warming rate of 0.43°C/decade and shifting precipitation patterns.
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Li et al. (2026) Deep learning tree and forest biomass from sub-meter resolution optical imagery
The study evaluates the ability of Convolutional Neural Networks (CNNs) to directly estimate forest above-ground biomass (AGB) from sub-meter resolution RGB optical imagery. The results demonstrate that CNNs can achieve high predictive performance ($R^2 = 0.71$) without requiring LiDAR-derived tree height data, approaching the accuracy of traditional height-based models.
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Bouchard et al. (2026) Enhancing runoff-infiltration partitioning in the SVS land surface model improves streamflow simulations under frozen soil conditions
This study proposes a new configuration of the Soil, Vegetation, and Snow (SVS) model that enhances frozen soil infiltration by reducing both surface runoff and sub-surface lateral flow. The enhanced configuration significantly improves streamflow simulations under frozen soil conditions.
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Ng et al. (2026) Is Europe Under UNSEEN Risk of Cyclones of Tropical Origin?
This study investigates the impacts and multidecadal variability of cyclones of tropical origin (CTOs) making landfall or passing near Europe, using a novel approach to generate CTO event sets from twentieth-century hindcasts. The results indicate that CTOs pose a significant risk to European regions.
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Singh et al. (2026) How Important Are the Critical Points in Selecting the Optimal Samples for Accurate Estimation of Subsurface Soil Moisture?
This study proposes a novel physics-aware sampling framework to extract informative training instances for predicting subsurface soil moisture from near-surface observations, achieving comparable or superior accuracy compared to the full-training-data baseline model.
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Casirati et al. (2026) Differential impacts of irrigation on precipitation across the United States
This study investigates the impact of irrigation on regional precipitation patterns using a physically based irrigation module in the NASA Goddard Earth Observing System Earth system model. The results show that irrigation redistributes precipitation across regions and seasons.
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Schwind et al. (2026) RIME-X v1.0: combining simple climate models, Earth system models, and climate impact models into a unified statistical emulator for regional climate indicators
This paper presents RIME-X v1.0, a novel probabilistic emulator that combines simple climate models, Earth system models, and climate impact models to generate scenario-dependent, time-evolving probability distributions of regional climate indicators.
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Sultan et al. (2026) Global review of hydrological response time: analysis and synthesis across diverse climates
This study investigates the impact of climate change on global water resources by analyzing the effects of temperature and precipitation changes on river discharge. The research reveals that warming temperatures and altered precipitation patterns will significantly alter river flow regimes worldwide.
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Zhou et al. (2026) Threefold increase in atmospheric–riverine compound heatwaves under climate change
This study examines the increasing trend of atmospheric-riverine compound heatwaves under climate change. The analysis reveals a threefold increase in such events over the past four decades, with significant impacts on river water quality and aquatic ecosystems.
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Basheer et al. (2026) Integrated hydrological and economic assessment of hydropower and irrigation development in Sudan under climate change
This study assesses the biophysical and economy-wide impacts of hydropower and irrigation development in Sudan under climate change. The results indicate a projected increase in naturalized streamflow of the Nile by 2050 due to climate change.
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Yang et al. (2026) GEE-DisALEXI: cloud-based implementation of the DisALEXI model for evapotranspiration monitoring using Google Earth Engine
This paper presents the cloud-based implementation of the Disaggregation of the Atmosphere Land Exchange Inverse (DisALEXI) model on Google Earth Engine (GEE), enabling scalable and high-resolution evapotranspiration (ET) data production. The model exhibits excellent performance in croplands, particularly during the growing season.
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Ren et al. (2026) An enhanced GRACE-based index for nationwide flood-prone region monitoring in China from 2003 to 2022
This study developed the Optimal Flood Potential Index (OFPI) to improve large-scale monitoring of flood-prone regions in China from 2003 to 2022. OFPI showed better detection performance than the existing Flood Potential Index (FPI).
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Tedesco et al. (2026) The Modèle Atmosphérique Régional – Intelligence Artificielle (MAR-IA): surface meltwater over Greenland
This study introduces a machine-learning emulator, MAR-IA, trained on daily surface meltwater production over Greenland and enables attribution of melt drivers. The emulator achieves high test-set skill with R2 = 0.987, low root mean squared error (< 10 mm w.e. d−1), and negligible bias relative to MAR meltwater outputs.
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Manzo et al. (2026) Improved Representation of Surface Emissivity Effects on Longwave Radiation in a Coupled Earth System Model
This study proposes a novel "Full Greybody" method to improve the representation of longwave flux in Earth System Models, reducing bias in atmospheric heating rates and effective temperatures.
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Gupta et al. (2026) MAUSAM: An Observations‐Focused Assessment of Global AI Weather Prediction Models During the South Asian Monsoon
This study evaluates seven leading artificial intelligence-based weather prediction systems during the South Asian Monsoon using ground-based and satellite data, highlighting their skill in predicting large-scale variables but also systematic errors in finer-scale features.
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Li et al. (2026) Mapping complex cropping patterns in China (2018–2021) at 10 m resolution: a data-driven framework based on multi-product integration and Google satellite embedding
This study developed a data-driven crop mapping framework by integrating multiple existing crop products with Google Satellite Embeddings derived from the AlphaEarth foundation model. The framework effectively enhanced the spatial coherence and temporal stability, achieving an overall accuracy of 92.60% and an F1 score of 0.7584.
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Zhao et al. (2026) Greenhouse warming exacerbates El Niño-induced Indian monsoon droughts
This study reveals that greenhouse warming strengthens the inverse relationship between El Niño-Southern Oscillation (ENSO) and Indian summer monsoon rainfall (ISMR), contrary to previous reports. The previously reported weakening was found to be a statistical artefact caused by two unusual events in 1983 and 1997.
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Li et al. (2026) How emergent-constrained precipitation projections reshape watershed hydrology?
This study develops a novel model-selection-based emergent constraint framework to constrain CMIP6 precipitation projections and reduce inter-model spread in watershed hydrology. The constrained projections improve projected precipitation growth rates by 7–84% relative to the raw CMIP6 ensemble.
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Zapata et al. (2026) Soil luminance and thermography support the estimation of whole-field solid-set sprinkler irrigation uniformity
This study proposes novel approaches using ground-sensors and Unmanned Aerial Vehicles (UAV) based remote sensing techniques to evaluate the spatial variability of water application in solid-set sprinkler irrigation across an entire field. The developed methodology effectively explained irrigation depth and variability.
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Tziritis et al. (2026) Nitrate persistence and inland salinisation in an intensively irrigated Mediterranean river basin district: Diagnostic evidence from WFD monitoring data (Thessaly, central Greece)
This study develops a probabilistic diagnostic framework to characterise the spatial extent and temporal persistence of nitrate contamination in the Thessaly River Basin District, central Greece. The framework advances beyond conventional descriptive assessments through three specific analytical contributions: bootstrap exceedance analysis, Shannon entropy-weighted Compound Vulnerability Index, and classification concordance analysis.
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Abbas et al. (2026) Disentangling precipitation forcing and parameter uncertainty in a multi-objective surface–subsurface hydrologic modeling framework
This study investigates the impact of precipitation forcing uncertainty on parameter estimation and predictive performance in coupled surface–subsurface hydrologic models. The authors propose a multi-objective framework to represent precipitation uncertainty during calibration.
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Cappelli et al. (2026) Bridging flexibility and usability: configuring CoSMoS-2s for operational rainfall simulation in the Arno River Basin
## Identification - **Journal:** Hydrological Sciences Journal - **Year:** 2026...
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Shamini (2026) Climate Change Impact on Agricultural Land Suitability: an Interpretable Machine Learningbased Eurasia Case Study
This study presents an interpretable machine learning framework to assess the impact of climate change on agricultural land suitability across Eurasia, leveraging multi-source datasets and advanced algorithms.
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Truong et al. (2026) Spectral nudging impacts on precipitation downscaling in the Conformal Cubic Atmospheric Model, version CCAM-2504: insights from summer 2011
This study evaluates the impacts of spectral nudging on rainfall when dynamically downscaling with the Conformal Cubic Atmospheric Model (CCAM) during the extreme 2010–2011 La Niña event. The results demonstrate that carefully tuned spectral nudging in CCAM preserves large-scale teleconnections associated with La Niña, MJO, and retains mesoscale variability while enhancing the fidelity of both mean and extreme rainfall.
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Li et al. (2026) Climate network-based synchronized structural identification of extreme drought and pluvial events in cross-basin regions
This study uses a complex network to identify the synchronous structure of drought, pluvial, and drought–pluvial dipole events in cross-basin regions. The analysis reveals distinct wet-dry co-variability between the Yangtze and Yellow River Basins.
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Teran et al. (2026) Integrating reservoirs and lakes in the CoSWAT global hydrological model
This study integrates reservoirs and lakes into the CoSWAT global hydrological model, improving its ability to represent basins where these water bodies play a significant hydrological role. The new implementations were applied in selected regions worldwide with sufficient data availability.
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Rehman et al. (2026) Assessment of crop water stress under prevailing irrigation practice in Faisalabad, Pakistan using hyperspectral remote sensing
This study used hyperspectral remote sensing to assess crop water stress under prevailing irrigation practice in Faisalabad, Pakistan. The results showed that maize and spinach yields improved with water application until reaching an optimum level and thereafter improved at higher levels.
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Gauvain et al. (2026) A global high-resolution hydrological model to simulate the dynamics of surface liquid reservoirs: application on Mars
This paper presents a global high-resolution hydrological model to simulate the dynamics of surface liquid reservoirs on Mars. The model uses a pre-computed hydrological database that maps topographic depressions and their hierarchical connections, allowing for efficient simulation of water redistribution between reservoirs.
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Benoît et al. (2026) A non-stationary trans-Gaussian model for daily rainfall over complex topography
This study presents a non-stationary trans-Gaussian model for daily rainfall over complex topography. The model combines the flexibility of a fully non-stationary framework with the ability to capture spatial dependencies through a Matérn covariance function.
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Krasnova et al. (2026) Stand composition modulates water use efficiency in adjacent mature boreal forests
This study investigates the effect of stand composition on water use efficiency in adjacent mature boreal forests. Using six years of eddy covariance data from two sites with contrasting species composition, the results show that mixed forest stands exhibit lower water use efficiency than pine monoculture stands.
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Zhao et al. (2026) Mapping paddy rice distribution and cropping intensity in South and Southeast Asia (1995–2024) at 30 m resolution
This study presents a refined phenology-based algorithm to generate 30âm multi-year composite rice distribution and cropping-intensity products across South and Southeast Asia for four nominal reference years: 1995, 2005, 2015, and 2024.
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Contizanetti et al. (2026) Sensitivity of extreme precipitation to warming in a global storm-resolving model
This study investigates the response of extreme precipitation to global warming using a global storm-resolving model, revealing that the tropics exhibit a weaker response compared to the extratropics.
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Agosta et al. (2026) Structural changes in the interannual variability of extreme autumn precipitation in eastern Spain and the weakening of synoptic forcing
## Identification - **Journal:** Quarterly Journal of the Royal Meteorological Society - **Year:** 2026...
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Sha et al. (2026) Simulating ecosystem water and carbon fluxes by integrating remote sensing indices with multiple machine learning models
This study integrated remote sensing indices with multiple machine learning models to simulate ecosystem water and carbon fluxes. The results showed that incorporating remote sensing data significantly improved the simulation accuracy for carbon fluxes, particularly gross primary production (GPP) and net ecosystem exchange (NEE).
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Zhang et al. (2026) Two Types of Summer Concurrent Heatwaves Across Eurasia and Their Precursor Signals
This study identifies two dominant spatial modes of summer concurrent heatwaves across Eurasia using a hierarchical clustering approach, providing insights into their precursor signals and dynamic drivers.
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Qiao et al. (2026) Flash droughts amplify maize yield losses through intensified atmospheric aridity
This study investigates the impacts of flash droughts on maize yield in the United States, finding that they cause widespread yield losses with a yield sensitivity 27.53% greater than slow-onset droughts due to intensified atmospheric aridity.
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Deng et al. (2026) Assessing the climatic effects and feedback mechanisms of large-scale crop irrigation using the improved WRF model
This study investigates the climatic effects and underlying mechanisms of large-scale crop irrigation (LSCI) in the Huanghe-Huaihe-Haihe River (HHH) basin using the Weather Research and Forecasting (WRF) model. The results show that LSCI significantly modifies surface water and energy balances, leading to a 2.85% increase in evapotranspiration, a 0.19°C reduction in near-surface temperature, and a 5.29 mm increase in precipitation.
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Hedrick et al. (2026) A 40-year high-resolution gridded meteorological dataset derived from station observations in the Reynolds Creek Experimental Watershed
This paper presents a 40-year high-resolution gridded meteorological dataset for the Reynolds Creek Experimental Watershed in southwest Idaho, USA. The dataset includes hourly measurements of air temperature, vapor pressure, precipitation mass and phase, incoming shortwave and longwave radiation, wind speed and direction, and other variables.
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Napoli et al. (2026) Future elevation-dependent changes in meteorological variables across the european alps and their possible links to surface temperature: insights from the EURO-CORDEX ensemble
This study investigates elevation-dependent patterns of change in 18 climate variables across the European Alpine region using a large EURO-CORDEX ensemble, focusing on winter and spring seasons. Strong elevation-dependent patterns are found for minimum temperature, diurnal temperature range, and specific humidity.
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Ao et al. (2026) Station-scale reconstruction of evapotranspiration, climatic water availability, and hydrological extremes exposure since 1700s
This study develops a random forest model to reconstruct monthly evapotranspiration (ET) at 5267 weather stations from 1688 to 2020, providing critical evidence for understanding the impact of climate variability and human influences on the water cycle over the past three centuries.
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Gires et al. (2026) A Universal Multifractals perspective into the link between rainfall variability and temperature
This study investigates the relationship between rainfall variability and temperature across different scales using high-resolution measurement data from Northern France. The results show a positive association between the scale-invariant maximum observable singularity of rainfall extremes and sample-mean surface temperature.
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Yang et al. (2026) Physics‐Informed Spatiotemporal Graph Neural Network for Soil Temperature Forecasting
This study introduces a novel framework for predicting soil temperature using a physics-inspired time-gradient adaptive graph convolutional network (PTAGCN) that outperforms conventional data-driven approaches. The proposed model achieves high accuracy in forecasting 20 cm soil temperature across distinct climate regions in China.
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Xiao et al. (2026) Global comparison of different effective scattering albedo and soil roughness parameterization schemes for SMAP soil moisture and L-VOD retrieval
This study evaluates the performance of soil moisture and L-band vegetation optical depth retrievals using different effective scattering albedo and soil roughness parameterizations, aiming to optimize retrieval algorithms for future microwave remote sensing missions.
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Samouris et al. (2026) Multi‐Timescale Drought Evolution in Greece (1960–2022) From Station‐Based SPI and SPEI
## Identification - **Journal:** International Journal of Climatology - **Year:** 2026...
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Wang et al. (2026) Physics-guided neural network integrating uncertainty evolution for spatiotemporal wind speed prediction
This study presents a physics-guided neural network called PD-WPN that improves the prediction of three-dimensional wind speed fields by learning both data patterns and physical consistency of wind evolution. The model combines information across time, space, and height, and uses physical constraints to guide the learning of wind speed, wind direction, and spatial structure.
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Akor et al. (2026) Integrating Meteorological Forcings and Satellite-Derived Observations to Emulate Snow Water Equivalent in the Colorado Rocky Mountains Using a Spatiotemporal Deep Learning Model
This study develops a deep learning-based emulator to estimate snow water equivalent (SWE) using meteorological forcings and physiographic variables, achieving performance comparable to a numerical model while generating results almost instantly.
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Browne et al. (2026) Coupled observation‐operator approximations in outer‐loop coupling data assimilation
This paper presents a methodology for coupled variational data assimilation that allows the effect of coupled observation operators to be approximated while maintaining separate minimizations across model components, enabling direct constraint of atmosphere, ocean, and sea-ice components from satellite radiances.
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Fan et al. (2026) Sensitivity of NWP Over the Tibetan Plateau to Soil Moisture Uncertainties in Summer
This study investigates the impact of soil moisture (SM) uncertainties on numerical weather prediction (NWP) over the Tibetan Plateau, demonstrating significant sensitivity to SM errors and biases. The research highlights the need for improved accuracy in SM products to enhance NWP performance.
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Mukherjee et al. (2026) When Heat Meets Drought in Maharashtra: Deciphering Compound Extremes Using Copula‐Based Probabilistic Analysis
This study assesses the impact of Compound Drought and Heatwave (CDHW) events on Maharashtra, India, from 1960 to 2025, highlighting a significant increase in frequency and severity post-1990.
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Wang et al. (2026) Seasonal Asymmetry in Extreme Precipitation Intensification Across China's Drylands
This study investigates the seasonal expression and hydrological implications of recent wetting trends in China's drylands, revealing a strong seasonal asymmetry in extreme precipitation intensification. The results highlight the importance of resolving precipitation changes at seasonal scales for understanding dryland hydroclimatic dynamics.
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Qian et al. (2026) Moisture Source Tracking Techniques and Physical Process Analysis Revealing Precipitation Improvement Over North America in CESM2
This study investigates the contributions of updated physical parameterizations versus higher model resolution in simulating global precipitation using CESM2, focusing on North America. The results show that updated physical processes significantly reduce precipitation biases by >45%, surpassing the contribution of higher resolution.
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Sarker et al. (2026) Geographic complexity in Queensland irrigation water pricing: Spatial and temporal dynamics revealed by generalized additive models
This study examines the spatial and temporal dynamics of irrigation water pricing across 16 Queensland water supply schemes over eleven years (2015–2025) using generalized additive models. The results reveal significant non-linear spatial and temporal price patterns, with prices increasing by 115%–164% above 2015 baseline levels through to 2024.
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Luo et al. (2026) Evolution and Prediction of Meteorological Elements in the Luanhe River Basin Based on Machine Learning and CMIP6
This study analyzes the spatiotemporal evolution characteristics of key meteorological elements in the Luanhe River basin from 1980 to 2023 and predicts their trends from 2025 to 2049 using machine learning and CMIP6 data.
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Das et al. (2026) Mesonet‐Based Ground Validation of IMERG‐V07 and GSMaP‐V08 Over a Semi‐Arid Dryland Ecosystem in West Texas
This study evaluates the accuracy of two satellite precipitation products, IMERG-V07 and GSMaP-V08, using ground measurements from 107 sites in West Texas over a four-year period. The results show that both products have biases and limitations, but GSMaP performs better overall.
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Parmar et al. (2026) Evaluation of representation of seasonally frozen ground characteristics in Land Surface Models: JSBACH and CLM
This study evaluates the representation of seasonally frozen ground characteristics in two land surface models (LSMs), JSBACH and CLM, using ERA5 reanalysis data. The results show that JSBACH reproduces frozen ground extent most realistically but simulates reduced snow depth, leading to weaker insulation and deeper seasonal freezing.
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Jiang et al. (2026) Key processes associated with the diurnal cycle of rainfall over East Amazon and their representation in global climate models
This study investigates the impact of increasing model resolution on simulating precipitation patterns in the Amazon Basin and finds that higher resolutions significantly improve the representation of diurnal rain belts.
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Likoya et al. (2026) A Multi-model Perspective of Droughts in Future Climate and Implications for Irrigation in Malawi
This study examines the dynamics of water availability and irrigation water demand in five river basins over Malawi using a suite of bias-corrected Global Climate Models coupled with a Soil Water Assessment Tool. The results highlight the risks associated with droughts and projected increase in irrigation water demand.
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Richardson et al. (2026) Potential Warming‐Induced Changes in Stream Water Sources Between Proglacial and Non‐Glacial Streams, South‐Central Alaska
This study investigates the shift from a glacierized to a deglaciating landscape through the lens of source water contribution in sub-watersheds of the Nellie Juan River watershed on Alaska's Kenai Peninsula.
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Stojanovic et al. (2026) Emerging aridification of the Congo River Basin driven by rainfall decline, moisture-source shifts and rising atmospheric demand
This study reveals a spatially coherent aridification hotspot in the Congo River Basin between 1981–2023, driven by declining precipitation and rising atmospheric evaporative demand. The results demonstrate that oceanic moisture contribution is the primary driver of long-term precipitation decline.
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Rispal et al. (2026) Impact of seasonal snow on the recharge of a mountain karst aquifer under climate change: the Dévoluy case study (Southern Alps, France)
This study investigates the impact of seasonal snow on the recharge of a mountain karst aquifer under climate change using the KarstMod platform. The results show that accounting for snow processes is essential to reproduce observed discharge dynamics in karst environments.
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Hayelom et al. (2026) Introducing IQR–DEMO for precipitation network design optimization
This study introduces an integrated framework that optimizes precipitation network design by combining Information Quality Ratio (IQR) analysis with Dual Entropy Multiobjective Optimization (DEMO), resulting in more spatially representative and information-rich networks.
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Klotz et al. (2026) EARLS: a runoff reconstruction dataset for Europe
This study introduces EARLS: a data-driven daily runoff reconstruction dataset for Europe. The dataset provides streamflow reconstructions for over 10,000 basins in Europe, including uncertainty estimates, covering the period from 1953 to 2023.
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Bayar et al. (2026) Global meta-analysis of irrigation scheduling effects on water use efficiency, fruit quality, and yield in blueberry and strawberry
This study conducted a global meta-analysis to evaluate the impact of irrigation scheduling on water use efficiency (WUE), fruit quality, and yield in blueberry and strawberry under different irrigation regimes. The results showed that moderate deficit irrigation (MDI) can optimize blueberry and strawberry yield while improving WUE under semi-humid climate and loamy soil conditions.
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Xu et al. (2026) Improvement and application of the Green-Ampt model integrating mechanism correction and intelligent parameter prediction
This study presents an integrated infiltration modeling framework that improves the Green-Ampt model by introducing a wetting front suction correction factor and a saturated hydraulic conductivity correction factor, enabling decoupled characterization of gravity-driven, preferential-flow, and capillary-fringe controls. The modified model reduces cumulative infiltration RMSE by an order of magnitude relative to both the classical GA and approximate Richards equation solutions.
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Bercos‐Hickey et al. (2026) Orographic Effects on Precipitation From Hurricane Helene
This study investigates the orographic effects on precipitation from Hurricane Helene using global cloud-resolving simulations, revealing that the Appalachian Mountains redistribute tropical cyclone precipitation and enhance upslope rainfall.
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Kumar et al. (2026) Enhancing urban flood management for ungauged watersheds through adaptive mesh refinement and equation-based flow dynamics
This study investigates the impact of climate change on water scarcity in the western United States by analyzing the effects of projected temperature and precipitation changes on water availability. The main finding is that climate change will exacerbate existing water scarcity issues in the region.
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Bohl et al. (2026) Hybrid models generalize better to warmer climate conditions than process-based and purely data-driven models
This study investigates the generalizability of deep-learning based rainfall-runoff models to warmer climate conditions, comparing their performance with traditional conceptual and hybrid models. The results show that while LSTMs are accurate in historical periods, they have inferior generalizability to warm periods.
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Wang et al. (2026) Predicting emitter irrigation duration for optimized irrigation system operation: An interpretable multi-model ML approach with SHAP
This study develops an interpretable multi-model machine learning framework to predict emitter irrigation duration for optimized irrigation system operation. The proposed framework reveals the underlying physical mechanisms, particularly the interaction between water quality and emitter structure.
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Guo et al. (2026) Anthropogenic Warming Increases Extreme Precipitation in Huaihe River Basin, China in 1961–2020
This study investigates the impact of anthropogenic greenhouse gas emissions on extreme precipitation in the Huaihe River basin (HRB) and explores the underlying causes using observational data and CMIP6 model experiments. The results show that greenhouse gas emissions have led to an increase in extreme precipitation events in the HRB.
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Ding et al. (2026) Long-term increases in tree water-use efficiency across China are associated with CO2 and hydroclimatic variation
This study investigated long-term intrinsic tree water-use efficiency (iWUE) trajectories across China during the 20th century, quantifying the interactive effects of atmospheric CO2 and hydroclimatic variability using tree-ring δ13C data and a novel statistical approach to address CO2-time collinearity. It found significant iWUE increases and strong hydroclimate-dependent responses of iWUE to non-trend CO2 deviations.
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Zheng et al. (2026) Physics-guided urban flood modeling: spatial heterogeneity and diagnostic attribution via CMoE-HDAF
This study develops CMoE-HDAF, a physics-guided surrogate modeling framework, to enable rapid and spatially detailed urban flood forecasting and diagnostic attribution in high-density cities, achieving high accuracy and computational efficiency compared to conventional hydrodynamic models.
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Xiao et al. (2026) Land‐Atmosphere Coupling Is Associated With Severer Vegetation Productivity Losses During Compound Dry‐Hot Events in Drylands
This study investigates the impact of compound dry-hot events on vegetation growth, revealing that land-atmosphere coupling strength regulates CDHE impacts through a 'soil drying—latent heat decreasing—surface warming' feedback loop.
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Xiao et al. (2026) Sentinel-1 SAR time series for forest phenology: multimodal deep learning with meteorological fusion across deciduous broadleaf and evergreen needleleaf forests
This study develops a multimodal deep learning framework that fuses Sentinel-1 time series with meteorological variables to estimate forest phenology in deciduous broadleaf and evergreen needleleaf forests. The results show improved retrievals compared to conventional methods, particularly when integrating meteorological information.
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Li et al. (2026) Hydrological Threshold for Optimizing Wetland Climate Mitigation
This study investigates the relationship between water table depth and greenhouse gas emissions in wetlands, revealing a unimodal pattern that maximizes long-term cooling under future warming conditions.
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Taccari et al. (2026) AIFL: A global daily streamflow forecasting model using deterministic an LSTM pre-trained on ERA5-Land and fine-tuned on IFS
This paper introduces AIFL, an LSTM-based model for global daily streamflow forecasting that outperforms current state-of-the-art systems. The model achieves high predictive skill with a median modified Kling–Gupta Efficiency of 0.66 and a median Nash–Sutcliffe Efficiency of 0.53.
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Xin et al. (2026) Irrigation sequence regulates root-zone water-salt dynamics, growth kinetics, and yield formation of greenhouse tomato under saline-fresh water rotation
This study investigates the effects of saline-fresh water rotation on root-zone water-salt dynamics, growth kinetics, and yield formation in greenhouse tomato. The results suggest that an optimal irrigation sequence can balance saline-water use with root-zone salt control.
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Pan et al. (2026) A refined reservoir evaporation loss estimation approach through improved wind function expression accuracy
The study proposes a weighted wind direction method to refine reservoir evaporation estimates by accounting for reservoir geometry and wind field heterogeneity, applying this approach to 6,853 large reservoirs globally from 1985 to 2021.
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Adibi et al. (2026) Intensity-dependent changes in ENSO frequency and lifecycle characteristics under future climate change
This study investigates the projected changes in the frequency and lifecycle characteristics of El Niño and La Niña events under future warming scenarios using a multi-model ensemble of 13 CMIP6 models. The results show a robust shift toward higher intensity events, particularly under the SSP5−8.5 scenario.
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Wang et al. (2026) Moisture limitation superseding thermal forcing: Elevational divergence in growth and physiological responses of Picea crassifolia to accelerated warming and drying on the Northeastern Tibetan Plateau
This study investigates the impact of accelerated warming and drying on Picea crassifolia growth and physiological responses along an elevational gradient in the northeastern Tibetan Plateau. The results show that moisture limitation supersedes thermal forcing, leading to divergent elevational responses in tree growth and water-use efficiency.
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Sudikdo (2026) Perencanaan Pola Operasi Embung Peniwen Kabupaten Malang
This study analyzed potential discharge inflow and evaluated the reservoir reliability of the Peniwen Small Dam in Indonesia under various cropping patterns. It found that three optimized cropping patterns achieved reservoir reliability levels ranging from 81.00% to 92.08%, all deemed feasible for irrigation and raw water supply.
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Prabaswara (2026) Analisis Komparatif Model Artificial Neural Network (ann) Dan Long Short-Term Memory (lstm) Untuk Prediksi Debit Sungai Dalam Mendukung Pengelolaan Sumber Daya Air Berkelanjutan
This study compares Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) models for daily streamflow prediction in the tropical Welang River, finding that a 7-day look-back ANN model provides the best performance for short-term forecasts due to the watershed's short hydrological memory.
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Li et al. (2026) Rainfall-to-total precipitation proportion increased after bias correction over China from 1961 to 2022
This study corrects wind-induced errors in long-term precipitation records from 2300 meteorological stations across China for the period 1961–2022, revealing new trends in rainfall-to-total precipitation ratios under a changing climate.
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Chen et al. (2026) Future tropical cyclone rainfall constrained by increased atmospheric dryness
This study investigates the impact of atmospheric warming on tropical cyclone rain rates, revealing that increased absolute dryness limits future increases in precipitation efficiency and smaller rain rates.
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Ma et al. (2026) Attribution of the Record‐Breaking June 2024 Eastern Mediterranean Heatwave: Contrasting Roles of Soil Moisture in Anthropogenic Forcing and Natural Variability
This study investigates the relative contributions of anthropogenic forcing and natural variability to a record-breaking June 2024 heatwave in the Eastern Mediterranean, attributing roughly half to greenhouse gas-induced warming and soil drying. Anomalous atmospheric circulation patterns driven by North Atlantic SST anomalies play a significant role.
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Huang et al. (2026) Upwind terrestrial influences on soil moisture variability across South America
This study develops an observation-driven framework to quantify the remote influence of vegetation on soil moisture variability across South America. The framework integrates atmospheric transport trajectories with deep learning to estimate vegetation's contribution to downwind soil moisture, revealing a systematic continent-scale source-sink architecture and non-linear regimes of vegetation influence.
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Sarria-Ospina et al. (2026) Use of nonlinear principal components of CHIRPS precipitation data and ocean–atmospheric variables for streamflow forecasting in an area of scarce data – case study: Tocaría river basin – Orinoquia Colombiana
This study proposes a hybrid forecasting framework that integrates Seasonal Autoregressive Integrated Moving Average models with exogenous inputs (SARIMAX), nonlinear principal components (NLPCs) derived from CHIRPS precipitation data, and large-scale ocean–atmosphere indices to improve streamflow forecasting in data-scarce tropical catchments.
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Dikshit et al. (2026) Co‐Occurring Flash and Standard Droughts Amplify Global Fire Behavior
This study investigates how flash droughts impact wildfire behavior by comparing fires occurring during baseline conditions, standard droughts, and combined drought sequences. The results show that combined drought conditions lead to faster-spreading, longer-lasting, and larger fires.
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Tan et al. (2026) Divergent drivers of canopy and ecosystem water use efficiency in a drip-irrigated citrus orchard of a seasonal arid area in Southwest China
This study analyzed four consecutive years of flux data from a subtropical drip-irrigated citrus orchard in Southwest China to quantify seasonal variations in ecosystem water use efficiency (eWUE) and canopy water use efficiency (cWUE), and identified their environmental controls during the growing and non-growing seasons. Results showed that eWUE exhibited pronounced seasonal dynamics, peaking in winter and declining to a minimum during summer, while cWUE remained relatively stable throughout the year.
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Chen et al. (2026) A database of objectively identified atmospheric rivers based on a multi-method fusion algorithm
This paper proposes a multi-method fusion algorithm for objectively identifying atmospheric rivers (ARs) on a global scale. The algorithm integrates advanced strategies from multiple existing algorithms and introduces a dual-axis test method to enhance the stability of AR identification.
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Zhang et al. (2026) Mapping three decades of urban growth in China: a 30 m annual building height dataset (1990–2019)
This study generates a framework to map annual building height datasets in China from 1990 to 2019 at 30m spatial resolution. The framework integrates multi-source remote sensing data through the eXtreme Gradient Boosting (XGBoost) model.
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Burderi et al. (2026) Regional and weather-type modulation of global warming–driven intensification of Italian precipitation extremes from multi-year storyline simulations
This study investigates changes in precipitation statistics over Italy using multi-year simulations under different climate conditions, revealing robust changes in mean and extreme precipitation that cannot be explained by a single scaling relationship.
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Chen et al. (2026) Democratizing planetary-scale analysis: an ultra-lightweight Earth embedding database for accurate and flexible global land monitoring
This paper presents the Embedded Seamless Data (ESD), an ultra-lightweight Earth embedding database for accurate and flexible global land monitoring. The ESD dataset is designed to overcome the barriers in storage and computational resources required for planetary-scale analysis.
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Bai et al. (2026) Atmospheric Noise Forcing Increases Multiyear El Niño Events
This study investigates the role of atmospheric noise forcing in modulating the frequency of multiyear El Niño events using an Interactive Ensemble coupling strategy. The results reveal a previously underrecognized pathway through which stochastic atmospheric variability influences El Niño persistence.
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Muñoz et al. (2026) Assessing the effect of land cover on ISBA snow water equivalent and land surface temperature simulations over Europe
This study evaluates the impact of updated land cover (LC) representation on snow water equivalent (SWE) and land surface temperature (LST) simulations in the ISBA land surface model over Europe. It finds that integrating the latest ESA CCI LC data reduces ISBA SWE bias by approximately 23%, primarily driven by specific vegetation transitions, while having a limited impact on LST.
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Zhang et al. (2026) Flash drought characteristics based on three identification methods in the North China Plain, China
This study introduces a new identification method called the mean-scaled evaporative stress ratio (MESR) to analyze the spatiotemporal characteristics and hotspots of flash droughts (FD) in the North China Plain from 1981 to 2022.
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Deng et al. (2026) Precipitation water conversion rate variations and driving mechanisms in the Yangtze-Huang-Huai-Hai river basin over the past 60 years
This study investigates the long-term variations and driving mechanisms of precipitation water conversion rate (PWCR) in the Yangtze-Huanghe-Huaihe-Haihe River (YHHH) basin, China, from 1956 to 2024. The results show a significant decline in PWCR under a warming and drying background.
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Chen et al. (2026) Simulation of soil water and nitrogen transport under drip fertigation using a dynamic infiltration boundary in HYDRUS
This study developed a novel numerical approach to simulate soil water and nitrogen transport under drip fertigation by integrating a dynamic surface ponding radius model and parameterizing time-varying infiltration boundaries in HYDRUS-2D. The results demonstrated that the variable infiltration boundary method significantly improved the prediction of soil water content.
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Liu et al. (2026) Enhanced land surface phenology detections in the western U.S. drylands by fusing harmonized Landsat and Sentinel-2 observations with near-surface PhenoCam time series
This study improves land surface phenology detections in western U.S. drylands by fusing harmonized Landsat and Sentinel-2 observations with near-surface PhenoCam time series, generating gap-free temporal observations for 30-m phenology detections.
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Jha et al. (2026) Entrainment‐Based Framework for Understanding Extratropical Moist Heat Extremes
This study investigates the role of dry-air entrainment in intensifying extratropical moist heat extremes using reanalysis data and a global climate model.
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Rampal et al. (2026) Downscaling with AI reveals the large role of internal variability in fine-scale projections of climate extremes
This study introduces a generative-AI approach to enhance the scope of regional downscaling, enabling characterization of fine-scale future climate changes and rare extremes. The research reveals that internal variability dominates uncertainty in projected precipitation extremes.
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Muturi et al. (2026) An integrated satellite remote sensing approach for mapping field-scale irrigation dynamics to support water management in highly regulated semi-arid catchments
This study develops and evaluates a simple thresholding approach using the fraction of reference evapotranspiration (ET0F) and enhanced vegetation index (EVI) to map field-scale irrigation dynamics in the Namoi catchment, Australia, from 2019 to 2025. The method serves as a conservative classifier with moderate accuracy (61.4%) and specificity (79.9%), proving useful as a low-cost screening tool for identifying potential irrigated areas.
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Shen et al. (2026) Radar Reflectivity Assimilation Method Based on Adaptive Hydrometeor Phase Identification Algorithm Using Dual‐Polarization Radar and Its Impacts on Severe Weather Prediction
This study introduces a blended retrieval approach to improve hydrometeor analysis and forecasting accuracy by incorporating dual-polarization radar measurements within the WRFDA framework.
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Yu et al. (2026) Asymmetry of Land Surface Temperature Response to Forest Gain and Loss: The Role of Land Cover Conversions
This study investigates the role of land cover conversions in asymmetric land surface temperature (LST) responses to forest gain and loss, revealing a consistent asymmetry globally.
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Jacobs et al. (2026) Impact of fragmented urbanization on observed precipitation
This study explores an innovative observation-centered method to analyze the impact of fragmented urban areas on downwind precipitation, revealing a decrease in frequency and increase in intensity during summer.
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Potter et al. (2026) Including rainfall sequencing and autocorrelation adjustment as a component of bias correction for hydroclimate projections
This paper presents a new bias correction method called RhoQM that corrects rainfall sequencing and autocorrelation in hydroclimate projections. The method is developed to address the limitations of standard quantile-quantile mapping methods, which can underestimate mean streamflow and high streamflow events due to the lack of consideration of rainfall sequencing.
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Krouma et al. (2026) Ensemble forecasts of isolated and compound wind and precipitation extremes in Europe using HC-SWG (v3.1) and MA-SWG (v1.1) Stochastic Weather Generators
This study presents two forecasting approaches that combine a stochastic weather generator with atmospheric circulation analogs to forecast extreme precipitation and wind speed in Europe. The first approach, HC-SWG, combines ECMWF ensemble reforecasts with the stochastic weather generator to forecast extreme precipitation at different locations in Europe. The second approach, MA-SWG, uses multivariate atmospheric analogs as input to the SWG to forecast extreme 10 m wind speed.
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Bhat et al. (2026) Shifting streamflow patterns in the Upper Jhelum Basin, Western Himalaya: implications for water availability under changing climate
This study investigates the impact of climate change on global ocean acidification, focusing on the role of anthropogenic CO2 emissions. The research reveals a significant increase in ocean acidity over the past century, with severe consequences for marine ecosystems.
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Ocampo-Marulanda et al. (2026) Hourly-scale modeling of storm transitions in Southern Brazil with Markov Chains
This study characterizes the temporal dynamics of storm intensity and persistence at the intraday scale in southern Brazil using a season-resolved Markov chain framework. The results provide actionable inputs for early warning, zoning, and climate risk management.
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Larson et al. (2026) Climate variability introduces uncertainty into future emissions pathways
This study investigates how natural temperature variability influences global emissions trajectories through its impact on societal decision-making using a coupled climate-social model. The research finds that anomalous mid-century warmth accelerates net-zero emissions by several years, while cooling delays it.
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Sweet et al. (2026) A data-driven method for identifying climate drivers of agricultural yield failure from daily weather data
A data-driven method is proposed to identify climate drivers of agricultural yield failure from daily weather data. The approach systematically generates and tests candidate features using machine learning and then selects a set of robust drivers.
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Guendelman et al. (2026) The role of atmospheric fast adjustment in the distinct precipitation response between increase and decrease of CO2 concentrations
This study examines the global mean precipitation response to different CO2 perturbations using idealized climate model experiments. The results show that the apparent hydrological sensitivity is asymmetric when comparing increases (doubling) and decreases (halving) of CO2 concentrations from pre-industrial conditions.
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Sripathi et al. (2026) Early but Anomalous Onset of the 2025 Indian Summer Monsoon
This study investigates the synoptic- and large-scale air–sea processes that triggered the 2025 early onset of the Indian summer monsoon, highlighting key atmospheric and oceanic factors contributing to this event.
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Ding et al. (2026) A heavier tail accelerates the intensification of extreme summer mesoscale convective systems precipitation rate in East Asia during 2000–2024
This study investigates historical changes in mesoscale convective system (MCS) precipitation rate, revealing a nonlinear intensification of extreme MCS events due to tail stretching rather than uniform mean shifts.
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Sarkar et al. (2026) Global changes in precipitable water vapour during 1980–2100 and its spatial, temporal, radiative and causal insights for enhanced climate warming
This study analyzes global and regional trends in precipitable water vapour (TCWV) from 1980 to 2020 using ERA5 data, identifying key drivers and their impact on climate warming.
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Karimi et al. (2026) Improving reference evapotranspiration estimation by attention-enhanced autoencoders and hybrid neural networks under noisy chaotic conditions
This study presents a climate-adaptive Multi-Layer Perceptron-Self Attention (MLP-SA) framework for robust estimation of reference evapotranspiration (ET o ) under noise-distorted conditions. The proposed model outperforms hybrid models in humid regions and demonstrates optimal Lyapunov stability in arid regions.
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Zhao et al. (2026) Westerly induced precipitation increase drives near-surface ground ice gain on the Tibetan Plateau despite warming
This study investigates the anomalous increase in ground ice at the active layer bottom on the Tibetan Plateau despite climate warming, identifying strengthened westerlies as a driving mechanism. The findings highlight that rapid precipitation increase can locally outweigh temperature in driving cryosphere evolution.
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Anderson et al. (2026) Reliance on daily mean streamflow data biases inferred flood seasonality
This study evaluates how the temporal resolution of streamflow data (daily mean versus daily maximum derived from hourly data) affects the characterization of flood seasonality and the identification of extreme flood events.
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Dong et al. (2026) Observed and Simulated Mesoscale Convective Systems over High Mountain Asia. Part II: Past Trend and Future Projection
This study examines the trends and drivers of mesoscale convective system (MCS) characteristics over High Mountain Asia (HMA) using nearly four decades of satellite observations, and projects continued reductions in MCS frequency under warmer conditions.
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Casado-Rodríguez et al. (2026) Benchmarking reservoir operation schemes for large-scale hydrological models
This study evaluates the performance of four reservoir routines in Large-Scale Hydrological Models (LSHMs) using a dataset from 164 reservoirs in the United States. The results show that increased model complexity does not always yield superior results, and calibrating to reservoir storage is more informative than calibrating to outflow.
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Weber et al. (2026) SEAS5-BCSD: a bias-corrected and downscaled global seasonal forecast reference dataset for 1981–2024
This study presents a bias-corrected and downscaled global seasonal forecast reference dataset (SEAS5-BCSD) for precipitation and 2 m temperature from 1981 to 2024. The dataset is generated using the Bias Correction and Spatial Disaggregation (BCSD) method, combining ECMWF SEAS5 seasonal forecasts with ERA5 reanalysis data.
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Yan et al. (2026) Identification of spatiotemporal sensitivity of karst spring discharge to precipitation and evaporation: an LSTM–Transformer Decoder framework
This study develops an LSTM–Transformer Decoders (LSTM–TDs) framework to predict spring discharge in karst systems by linking discharge-difference prediction with attention-based hydroclimatic sensitivity identification. The framework outperformed benchmark models in predicting the Niangziguan Springs' discharge.
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Tu et al. (2026) Toward coordinated water allocation in urban agglomerations under joint supply-demand uncertainty: A distributionally robust bi-level multi-objective framework
This study develops a distributionally robust bi-level multi-objective water allocation framework to facilitate coordination in urban agglomerations under joint supply-demand uncertainty. The framework integrates Wasserstein-based distributional robustness and lexicographic priorities to balance economic cost, environmental load, equity, and systemic coordination.
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Dunkl et al. (2026) European summer drying largely driven by atmospheric circulation changes since the 1980s
This study disentangles the contributions of thermodynamic versus circulation-driven mechanisms to European hydroclimate changes using nudged atmospheric circulation model simulations. The results show that circulation-induced effects play a substantial role in long-term summer drying.
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Amponsah et al. (2026) The application of geospatially-integrated machine learning models for flood prediction: A review
This review analyzed 100 peer-reviewed articles on geospatially integrated machine learning (ML) applications in flood modeling to identify trends and gaps between research activity and flood occurrence. The study highlights the need for capacity building and transferable ML approaches in underrepresented regions.
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Tiwari et al. (2026) How Do Different Sources of Gridded Precipitation Affect Streamflow Prediction? A Case Study Using TC Beryl (2012)
This study evaluates the impact of three gridded precipitation products on surface hydrology during Tropical Cyclone Beryl 2012, finding that satellite-based products provide reasonable streamflow estimates when peak timing is critical.
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Roychoudhury et al. (2026) MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation
This study presents MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year regional hydroclimate-chemical reanalysis for Asia at 12 km resolution. MATCHA couples WRF-Chem with CLM-SNICAR to simulate interactions between atmospheric composition and regional hydroclimate.
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Sigdel et al. (2026) U.S. rivers are transporting more suspended sediment, often in less time
This study integrates high-frequency turbidity sensing with deep learning to reconstruct nearly four decades of daily sediment flux for 175 U.S. rivers, revealing a shift toward greater sediment export and narrower transport windows.
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Tong et al. (2026) Maximum Temperature Forecasts in the Yangtze River Valley Using a Predictor‐Corrector Lightweight Deep Learning
This study introduces a lightweight maximum temperature forecasting framework that combines a ResNet-based predictor with a multilayer-perceptron-based corrector, achieving improved accuracy compared to existing numerical weather prediction methods.
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Cai et al. (2026) Research on Cloud Water Resources in the Bayinbuluke Alpine Basin: Climatic Characteristics and Development Potential
This study evaluates the spatiotemporal distribution and development potential of cloud water resources in the Bayinbuluke alpine basin (BAB) using a high-resolution dataset from 2000 to 2024. The research finds that the developable potential of CWR accounts for 32.8%–50.5% of the total, with an estimated 12.98–19.98 billion tons per year.
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Wang et al. (2026) Drivers, dynamics, and cascading effects of phased drought-flood abrupt alternation on basin water quality
This study investigates the dynamic impacts of drought-flood abrupt alternation (DFAA) events on river water quality in Southern China's Lijiang River Basin using a multiscale multifactor standardized index. The results reveal significant changes in water quality parameters during DFAA events.
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Zhao et al. (2026) Hydrological drought projection in the Lower Songhua River basin under climate and land-use change
This study investigates the impact of climate change on water resources in the southwestern United States. The researchers used a combination of climate models and hydrological simulations to project future changes in precipitation and streamflow.
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Rahparast et al. (2026) Innovative Integrated Sustainability Appraisal Approach for Irrigation Water Distribution Automation: A Combined MCDM-Based Food-Energy-Water Nexus
This study presents a sustainability performance appraisal framework for modernizing irrigation water distribution systems based on the Food-Energy-Water (FEW) nexus. The results show that automation using PI and MPC systems can improve water and energy conservation in normal and water shortage scenarios.
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Detto et al. (2026) Mechanisms and trait controls of canopy thermal regulation across a tropical rainfall gradient
This study investigates the regulation of canopy temperature in three tropical forests along a rainfall gradient on the Panama Isthmus, revealing divergent thermal responses among forests and highlighting the importance of multivariate trait interactions for mitigating warming.
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Kim et al. (2026) Interseasonal Hysteresis and Linearity Among Surface Energy Fluxes and Soil Water Content in Observations, Reanalyses, and Model Simulations
This study examines the representation of surface energy partitioning dynamics with soil water content across CONUS using in situ observations and model-derived products. Large discrepancies emerge in the representation of SWC-EF dynamics, highlighting the need to improve land-atmosphere coupling parameterizations.
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Kukal et al. (2026) Artificial intelligence/machine learning estimation of FAO and ASCE standardized reference ET erodes the physical basis and intended purpose of ET standardization
The paper argues that using artificial intelligence/machine learning to directly estimate FAO and ASCE Standardized Reference Evapotranspiration (ETref) undermines the physical basis and intended purpose of ET standardization. Instead, AI/ML can be used to improve the quality, continuity, and representativeness of meteorological inputs for the FAO/ASCE ETref equation.
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Spence et al. (2026) Ship-Borne Eddy Covariance Systems Identify Turbulent Flux Boundaries on the Laurentian Great Lakes
This study uses ship-borne eddy-covariance-derived turbulent flux measurements to reveal the presence of evaporation zones in large lakes and their implications for estimating evaporation.
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Li et al. (2026) Spatiotemporal Patterns of Drought and Flood Abrupt Alternation and Their Driving Factors in China from 1951 to 2020
This study investigates the spatiotemporal variation and driving mechanisms of drought-to-flood (DTF) and flood-to-drought (FTD) events in China's 218 tertiary river basins from 1951 to 2020 using long-/short-cycle DFAA indices. The results show that regions prone to DTF events have shifted southward, while FTD hotspots have migrated northward.
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Wang et al. (2026) Contrasting hydroclimate variations across inner Asian drylands in a warming climate
This study investigates the contrasting response of surface water availability in East and Central Asian drylands to future climate warming, revealing that non-soil moisture feedbacks dominate this pattern. The results highlight the importance of considering both thermodynamic and dynamic components of the moisture budget in understanding hydroclimate change.
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Feng et al. (2026) Multi-objective optimization of water–sediment-ecology coordinated operation for cascade reservoirs in the Yellow River Basin
This study develops an adaptive multi-objective optimization framework to coordinate the operation of two cascade reservoirs in the Yellow River Basin, balancing hydropower generation, sediment flushing, and downstream ecological protection.
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Feng et al. (2026) A framework for analyzing spatial hydrological drought dependence based on extreme value theory and nonstationary copulas
The study proposes an integrated framework combining event-scale extreme value theory and nonstationary copulas to analyze the spatial dependence and concurrence risk of hydrological droughts within river networks.
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Wan et al. (2026) A self-supervised deep learning method for retrieving historically similar extreme rainfall patterns
This study proposes a novel self-supervised deep learning method for retrieving historically similar extreme rainfall patterns at hourly, daily, and event scales. The method integrates a vision transformer with masked pretraining to learn rainfall representations and demonstrates accurate and efficient retrieval of diverse rainfall patterns.
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Liblab et al. (2026) A dynamic OPTRAM soil moisture constraint for PT-JPL evapotranspiration from Sentinel-2 validated across land covers and climates
This study introduces a dynamic soil moisture constraint for the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) evapotranspiration model, validated across diverse land covers and climates using Sentinel-2 data.
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Ploton et al. (2026) Normalization of Sentinel 2 data over tropical forests to nadir BRDF adjusted reflectance
This study presents a sensor-adapted BRDF correction framework for Sentinel-2 imagery over dense tropical forests, achieving up to 70% reduction in mean relative percent absolute differences compared to uncorrected data.
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Liao et al. (2026) Diurnal sea surface temperature amplification enhances surface extremes during marine heatwaves
This study reveals that diurnal sea surface temperature amplification enhances surface extremes during marine heatwaves. The research shows that the diurnal cycle is systematically amplified under MHW conditions, with enhanced daytime warming and a delayed diurnal phase.
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Liu et al. (2026) Application and Evaluation of a Novel Python‐Based Ensemble Data Assimilation Framework NEDAS in Whole Atmosphere Community Climate Model (WACCM)
This study presents a new Python-based whole-atmosphere ensemble data assimilation framework that integrates NEDAS with WACCM, achieving significant improvements in temperature and wind predictions.
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Mi et al. (2026) Four decades of full-depth profiles reveal layer-resolved drivers of reservoir thermal regimes and episodic hypolimnetic warming
This study developed a novel analytical framework to investigate spatiotemporal temperature dynamics in Rappbode Reservoir over four decades. The framework integrated long-term monitoring and process-based modeling to quantify the contributions of hydro-meteorological and operational drivers on depth-specific temperature changes.
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Vernier et al. (2026) Designing agrivoltaic systems for plant protection
This study investigates the impact of agrivoltaic system design on plant temperature during weather-risk events using a novel numerical approach. The results highlight the importance of tailoring designs to specific stresses to maximize plant protection and agricultural yield.
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Tamoffo et al. (2026) Constraining high-emission future West African monsoon with physics-weighted deep learning ensembles
This study proposes a physics-guided artificial neural network (ANN) approach to constrain regional climate projections by reducing the inter-model spread in West African monsoon rainfall under high-emission scenarios. The method uses sea-level pressure patterns from the Sahelian monsoon ocean-pressure index (SMOPI) as predictors and evaluates the physical realism of learned teleconnections against JRA-55 reanalysis.
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Prashant et al. (2026) Compound droughts as emergent outcomes of cascading drought propagation
This study investigates compound drought as an emergent outcome of cascading drought propagation across Peninsular India using a framework that integrates drought propagation analyses with machine learning emulation.
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Kazemi et al. (2026) Estimating filter head losses caused by reclaimed water based on machine learning approaches
This study applies Gene Expression Programming (GEP) to develop predictive models for head losses in microirrigation filters operating with reclaimed water. The results provide a novel framework for filter head loss estimation when filter-specific training data are unavailable.
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Gupta et al. (2026) Impact of reservoir storage on propagation from meteorological to hydrological drought
This study quantifies how reservoir storage influences the propagation of drought from meteorological to hydrological stages in the Krishna River Basin, demonstrating that reservoirs act as buffers that delay propagation but facilitate the downstream transmission of severe droughts.
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Yong et al. (2026) Spatiotemporal evolution and propagation of GNSS-derived PWV-based meteorological and soil moisture drought: a case study of the contiguous United States (2003–2022)
The study utilizes GNSS-derived precipitable water vapor (PWV) to develop a new meteorological drought index (SPCI) and analyzes its propagation to soil moisture drought (SMD) across the contiguous United States from 2003 to 2022.
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McDermid et al. (2026) Twentieth-century North American reforestation as an historical analogue for examining Natural Climate Solutions
This study investigates the recovery of regional forest carbon stocks in the eastern US over the last ∼150 years, leveraging harmonized land model experimental results to evaluate the impact of reforestation on terrestrial carbon storage.
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Dobson et al. (2026) Evaluating kilometre-scale statistical downscaling of daily climate extremes in Ecuador’s complex terrain: performance, limitations and implications for impact studies
This study evaluates the performance of the ISIMIP3BASD framework for generating high-resolution climate datasets over Ecuador, a region with complex terrain and strong ENSO-driven variability. The results highlight the strengths and limitations of using downscaled climate data for various applications.
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Cunha et al. (2026) EVAonline: An open-source web platform for global reference evapotranspiration estimation via multi-source data fusion
This paper introduces EVAonline, an open-source web platform for global reference evapotranspiration estimation via multi-source data fusion. The platform achieves a Kling-Gupta Efficiency (KGE) of 0.814 in the MATOPIBA region.
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Rinat et al. (2026) The complex effect of climate change and urbanization on streamflow in small–medium eastern Mediterranean catchments
This study examines the impact of climate change and urbanization on streamflow in small to medium-sized eastern Mediterranean catchments. The results show that urbanization leads to a significant increase in mean peak discharge and flood volume, while projected rainfall changes result in decreases in these metrics.
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Bagheri‐Gavkosh et al. (2026) Hydrological effectiveness of multiple natural flood management interventions in rapid responses catchments
This study investigates the hydrological effectiveness of Natural Flood Management (NFM) interventions in small, steep catchments using a systematic monitoring network and statistical analysis. The results show that well-integrated NFMs can deliver measurable flood-risk benefits by reducing peak flows and increasing lag times.
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Montazar et al. (2026) Persistent daily OpenET bias drives seasonal water-use divergence in California avocado orchards
This study evaluates the performance of OpenET, a satellite-based evapotranspiration product, in estimating actual evapotranspiration (ET) in commercial avocado orchards across Southern California. The results show that while OpenET reproduces broad temporal ET variability, it consistently generates higher ET estimates than eddy covariance measurements, leading to substantial cumulative seasonal water-use divergence.
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Merk et al. (2026) The impact of calibration strategies on future evapotranspiration projections: a SWAT-T comparison of three hydrological modeling approaches in West Africa
This study investigates the impact of calibration strategies on future hydrological changes in West Africa, with a focus on actual evapotranspiration (AET) dynamics. The findings show that AET increases under all calibration strategies, and a specific plant growth modeling approach can be used as a proxy to predict AET rates.
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Zwartsenberg et al. (2026) Climate sensitivity of tree growth decreases with site humidity for a tropical tree species
This study investigates how water availability affects tree-ring growth in Toona ciliata across a hydroclimatic gradient in Australia, finding that maximum annual cumulative water deficit is the primary driver of ring width variation.
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Scheftic et al. (2026) Seasonal Predictability of the Land Surface Hydrological Cycle over Two Distinct Regions of the United States within Two Operational Models
This study assesses the predictability of temperature, precipitation, and five additional hydrological variables across two distinct regions in the United States using operational coupled models. The results show that variables with high memory have higher predictability.
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Agustina et al. (2026) The Stage-based waterlogging height optimization in evapotranspiration irrigation system (SIEVAPET) subsurface irrigation for curly lettuce under different soil–sand media
This study optimized stage-based water table depth for lettuce cultivation under subsurface evapotranspiration irrigation, demonstrating improved water use efficiency and productivity. The findings highlight the importance of integrating water table management with crop evapotranspiration-based scheduling.
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Biondi et al. (2026) A decision-theoretic framework for probabilistic flood warnings
This study proposes a decision-theoretic approach to issuing flood warnings in Italy’s Sieve basin by integrating probabilistic precipitation forecasts with a statistical post-processing method to evaluate predictive uncertainty. The proposed framework yields economic benefits and substantial improvements in the Relative Economic Value (REV).
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Marshall et al. (2026) The 2026 western US snow drought was about four times more likely due to climate change
## Identification - **Journal:** Proceedings of the National Academy of Sciences - **Year:** 2026...
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Rong et al. (2026) Stochastic Hydrology Reveals the Controls of Forest Harvesting - Peakflow Causal Relations in Snow-Transient Environment
This study applies a probabilistic framework to nine pairs of control-treatment watersheds in the snow-transient environment of the Pacific Northwest, evaluating the effects of varied forest harvesting practices on peakflow magnitude and frequency.
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Chen et al. (2026) A hydraulic-geometry informed discharge retrieval algorithm for ungauged basins using ICESat-2 and Sentinel-1/2: Application to Qinghai-Tibet Plateau
This study presents a novel algorithm for estimating river discharge in ungauged basins using ICESat-2 altimetry and Sentinel-1/2 data. The Hydraulic-Geometry Informed Discharge Retrieval (HGIDR) algorithm shows substantial improvements over traditional methods, achieving high accuracy in daily discharge estimation.
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Leclerc et al. (2026) Heterogeneous topography and vegetation structure both lead to mosaics of buffered and decoupled microclimates in a Mediterranean massif
This study investigates the spatial variations in microclimates within a Mediterranean landscape in south-eastern France, revealing fine-scale mosaics of contrasting buffering and decoupling effects that vary seasonally. The research highlights the importance of considering heterogeneous landscapes when predicting local ecosystem trajectories under climate change.
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Wang et al. (2026) Estimation of cotton plant moisture content using UAV multimodal data and machine learning
This study developed a cotton plant moisture content (PMC) estimation model based on multimodal UAV remote sensing data. The CatBoost algorithm integrating multimodal data performed best, achieving R² and RMSE values of 0.807 and 0.033%, respectively.
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Molina et al. (2026) Contrasting seasonal and ecohydrological controls on LFMC dynamics and implications for dynamic wildfire risk prediction in Aleppo pine
This study investigates the drivers of live fuel moisture content (LFMC) in a mature Pinus halepensis stand in eastern Spain and explores its relationships with ecohydrological processes. The results show that LFMC is primarily controlled by antecedent atmospheric demand and fine dead-fuel moisture.
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Wei et al. (2026) Unraveling drought impacts on winter wheat yield in the Yellow River Basin: A coupled drought index–crop modeling framework
This study integrates meteorological and soil moisture data to analyze the spatiotemporal evolution of drought in the Yellow River Basin using non-stationary drought indices. The results show a declining trend in both NSPEI and SSI values over the study period, indicating an intensification of drought conditions.
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Bennet et al. (2026) Detection of compound and seesaw hydrometeorological extremes in New Zealand: A copula-based approach
This study demonstrates the use of copula models to understand compound hot and dry and dry-to-wet seesaw events in New Zealand, revealing more frequent and extreme occurrence of these events compared to coincident extremes in separate variables.
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Matland et al. (2026) Required Time Steps for Weather Radar Quantitative Precipitation Estimation
This paper investigates the impact of temporal sampling errors on weather radar observations and provides recommendations for sampling requirements in atmospheric science and hydrometeorology.
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Wang et al. (2026) A deep learning model for runoff prediction via Adaptive Reinforced Feature Mining
This study proposes a deep learning model called DRRA (Deep Learning Model for Runoff Prediction via Adaptive Reinforced Feature Mining) that improves daily runoff prediction accuracy by adaptively extracting global and local features from runoff series.
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Zhang et al. (2026) GPM IMERG V07B and V06B: Evaluation Using Ground‐Based Radar Observations and Application in Global Mesoscale Convective System Tracking
This study evaluates the accuracy of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) Version 07B in tracking Mesoscale convective systems (MCSs) and retrieving precipitation rates, comparing it to its predecessor V06B.
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Choi et al. (2026) Enhanced seasonal soil moisture forecasts by integrating APCC multi-model ensemble predictions into a land surface model framework
This study presents a seasonal soil moisture prediction system that integrates multi-model ensemble information into an LSM framework, yielding substantial improvements in forecast skill and extending the effective lead time for statistically significant predictions.
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Volk et al. (2026) Assessing and correcting bias in gridded reference evapotranspiration over agricultural lands across the contiguous United States
This study assesses and corrects bias in gridded reference evapotranspiration (ETo) over agricultural lands across the contiguous United States. The results show that gridMET ETo systematically overestimates ETo by 10–20% at most cropland sites, while pockets of underestimation appear in some arid western regions.
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Santuy et al. (2026) Enhanced ENSO-driven potential predictability over the Euro-Atlantic under greenhouse warming
This study examines how changes in tropical teleconnections under greenhouse warming reshape potential predictability over the North Atlantic-European region. The results show that ENSO-driven NAE potential predictability is enhanced under greenhouse warming, with implications for climate adaptation in the region.
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Correa et al. (2026) Capturing the extremes: a quasi-comonotonicity-based algorithm for disaggregating daily to hourly rainfall
This study presents a novel algorithm, Q-CODA, that disaggregates daily precipitation data into hourly time scale with improved representation of rainfall extremes and temporal coherence. The approach outperforms state-of-the-art methods in 5-fold cross-validation over 91 Spanish meteorological stations.
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Eebo et al. (2026) Investigating catchment predictors of the fraction of young water variability in streamflow in mesoscale Precambrian Shield catchments in Northeastern Ontario, Canada
This study investigates the streamflow generation processes in Precambrian Shield catchments by estimating the fraction of young water (Fyw) and damping ratios (DR) using isotope records from 16 catchments. The results highlight the importance of wetlands in playing different hydrological roles at a mesoscale.
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Dubinin et al. (2026) Linking plant water status dynamics to yield and fruit cracking in citrus orchards using UAV multi-sensor data and machine learning
This study introduces a dynamic, physiology-based framework that links temporal plant water status (PWS) trajectories during key phenological stages to fruit-cracking risk at the individual-tree scale. The framework integrates UAV-derived multispectral, thermal, and LiDAR observations with field physiological measurements and machine-learning models.
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Hottovy et al. (2026) Analysis of a simple Madden–Julian Oscillation model using a moisture variable with memory
This study investigates the Madden–Julian oscillation (MJO) modeling using simple models with diverse mechanisms and properties. The authors identify two primary mechanisms that can give realistic frequency and decay rates: feedback mechanisms and an additional prognostic "memory" variable.
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Flint et al. (2026) Sensitivity analysis of modeled soil water dynamics within variable rate irrigation zones for winter wheat
This study assesses within-field variability of soil water supply and crop water stress in a winter wheat field managed with variable-rate irrigation (VRI) and validates a water balance model based on the American Society of Civil Engineers (ASCE) standardized Penman-Monteith estimation of reference evapotranspiration.
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Luo et al. (2026) Observation-constrained projections reveal less increase in future global terrestrial evapotranspiration
This study uses water-balance observations in large river basins to constrain future global terrestrial evapotranspiration (ET) trends projected by CMIP6 Earth system models. The results show that the raw CMIP6 ESM ensemble overestimates future global ET trend by 30% under low- and medium-emission scenarios, and by 43% under high-emission scenario.
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Monte et al. (2026) Windows of opportunity in the prediction of dry and wet seasonal climate anomalies: a case study for the Middle East in autumn
This study identifies 'windows of opportunity' for predicting dry and wet events in the Middle East by analyzing the contribution of each autumn to the prediction skill across eight seasonal prediction systems. Strong anomalies in the tropical Pacific or Indian Ocean are found to be key contributors to prediction skill.
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Zhang et al. (2026) Spatially Heterogeneous Impacts of Urbanization in Reshaping the Dry and Hot Extremes Across Chinese Cities
This study investigates how urbanization affects dry and hot extremes in China at various temporal scales, revealing that urbanization intensifies heat extremes by 2%–20% since the 1970s. Urbanization also amplifies precipitation patterns, contributing to reduced light rainfall and exacerbated drought severity.
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Xu et al. (2026) IrriTwin: Integrating reinforcement learning with soil water and crop models toward digital-twin-oriented irrigation scheduling
This study proposes IrriTwin , a digital-twin-oriented irrigation scheduling framework that combines reinforcement learning with mechanistic soil–crop–water models to improve agricultural water-use efficiency under increasing water scarcity.
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Niu et al. (2026) Cascade structure and event-level attribution of three-dimensional compound drought–heat events in China: contrasting meteorological and agricultural systems
This study developed a three-dimensional framework to characterize the evolution and cascade structure of compound drought-heat events in China (1961-2023), revealing their complex spatiotemporal features and distinct drivers for meteorological versus agricultural systems. The findings emphasize treating these events as evolving three-dimensional systems rather than simple temporal overlaps.
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Ren et al. (2026) Machine learning significantly improves the simulation of hourly-to-yearly scale cloud nuclei concentration and radiative forcing in polluted atmosphere
This study develops a machine learning-based model to predict hourly-to-yearly scale cloud condensation nuclei (CCN) number concentrations in the North China Plain. The model significantly improves CCN prediction accuracy compared to the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model, reducing bias from -59% to -31%.
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Palazzoli et al. (2026) The hydrological asymmetric signature of El Niño–Southern Oscillation on global water storage
This study investigates the asymmetric impacts of El Niño–Southern Oscillation (ENSO) on global terrestrial water storage anomalies over the past four decades. The authors identify 81 El Niño-related clusters and 85 La Niña-related clusters covering 105.92 million km², showing that La Niña affects a broader area than El Niño.
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Li et al. (2026) Dynamic Filtering in Lagrangian Model‐Based Moisture Source–Receptor Diagnostics
This study proposes a dynamic filtering method that improves Lagrangian moisture tracking models by using spatiotemporally varying relative humidity and altitude thresholds. The new method enhances the recognition of spatial contrasts in moisture contributions over source regions with complex land–sea distributions.
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Rudlang et al. (2026) Climate and landscape jointly control European streamflow behaviour
This study uses a large dataset of over 7000 catchments in Europe to identify hydrological response types (HRTs) based on 40 hydrological signatures. The results show that climate emerges as the dominant driver of hydrological behavior at the continental scale, but landscape attributes are also important controls on the hydrological response in some environments and at various spatial scales.
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Wang et al. (2026) From Shadow to Fertilizer: Slanted Sunlight in 3D Radiation Enhances Cloud Condensate, Size, and Lifetime of Shallow Cumulus
This study investigates the impact of three-dimensional shortwave radiation on cloud condensate, size, and lifetime using large-eddy simulations coupled to an interactive land surface model. The results show that 3D radiation produces larger and longer-lived clouds compared to one-dimensional radiation.
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Ratshiedana et al. (2026) Evaluation of four remote sensing algorithms in estimating actual evapotranspiration in agricultural environments
This study evaluated the variability and accuracy of four remote sensing-based actual evapotranspiration (ETa) algorithms across an irrigation scheme in South Africa, finding the Vegetation Index (VI)-based algorithm to be the most reliable and computationally efficient for supporting agricultural water management.
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Li et al. (2026) Assessment of Soil Moisture Anomalies in Irrigated and Nonirrigated Soils Combining SMAP Anomaly Data and NASS Crop Soil Moisture Conditions
This study improves the mapping of crop soil moisture conditions by using soil moisture anomalies from SMAP data, providing a more accurate representation of soil moisture adequacy for irrigated croplands.
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Ojha et al. (2026) A comprehensive assessment and comparison of streamflow simulations performance between the national water model versions 3.0 and 2.1 across the continental United States
This study evaluates the performance of National Water Model version 3.0 (NWMv3.0) in simulating streamflow across the continental United States, comparing it to its predecessor NWMv2.1.
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Yao et al. (2026) Long-Term Conjunctive Water Management for Agriculture with Groundwater Salinity
This study employs a novel hydro-economic optimization framework to analyze century-scale water and crop management for a salinizing aquifer in California's western San Joaquin Valley. The results show that groundwater management with accumulating salinity requires fundamentally different strategies than freshwater aquifers.
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Tanarhte et al. (2026) Atmospheric drivers and socioeconomic impacts of precipitation variability in North Africa
This review synthesizes current knowledge on precipitation variability across North Africa from the early Holocene to future climate scenarios, identifying key atmospheric drivers and contrasting regional trends, while highlighting significant socioeconomic impacts and persistent knowledge gaps for climate adaptation.
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Xun et al. (2026) Whole agricultural-year modeling for irrigation strategies and crop responses in seasonally frozen regions
This study developed an enhanced agricultural-year (agr-year) scale model, SHAW-SC, to evaluate the effects of non-crop season irrigation on crop performance and water use in arid, seasonally frozen regions. The improved model was validated against field observations for three major crops (sunflower, spring wheat, and maize) in northwest China.
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Thota et al. (2026) Evolution of Climate Extremes Over the Indian Subcontinent Using a Revised CEI
This study develops a revised India Climate Extremes Index (IndCEI) to assess long-term climate extremes across the country, revealing widespread warming signals and intensifying heat stress.
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Iglesias et al. (2026) Daily sap flow, leaf morphology, and stem xylem characteristics under deficit irrigation and warming during the late winter and spring in young olive trees
This study evaluates the combined effects of moderate deficit irrigation and warming on whole-tree daily sap flow, leaf morphological traits, and stem xylem vessel characteristics in young olive trees. The results show that warming increases tree water use over the short term, but changes in leaf area due to warming may ameliorate such increases.
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Chen et al. (2026) Remote sensing-based mapping of flood irrigation extent and depth during fallow periods in arid irrigation district
This study developed and applied an improved optical trapezoid model (OPTRAM) with Sentinel-2 data to map the extent and estimate the depth of autumn and spring flood irrigation during fallow periods (2016-2023) in the Hetao Irrigation District, China, providing crucial information for water management.
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Li et al. (2026) Classification of paddy field water conditions with unmanned aerial vehicle: A novel method incorporating the short-wave infrared band
This study presents a novel method for classifying paddy field water conditions (PFWC) using unmanned aerial vehicle (UAV) remote sensing data. The proposed approach incorporates the short-wave infrared (SWIR) band and achieves satisfactory classification performance, extending the operational monitoring window compared to traditional thermal infrared (TIR) methods.
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Thoenes et al. (2026) Influence of rainfall event characteristics and antecedent conditions on subsurface stormflow response of two forested hillslopes
This study provides a comprehensive analysis of subsurface stormflow (SSF) event characteristics and antecedent conditions at two forested hillslope sites over a 2-year period. The results show that SSF volume is primarily controlled by total rainfall and antecedent wetness.
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Gopal (2026) Micro Irrigation Systems: a Comprehensive Review on Performance and Adoption in Indian Agriculture
This study evaluates the design principles, performance parameters, economic feasibility, and adoption status of micro irrigation systems in India, with a focus on Madhya Pradesh's agro-climatic conditions. The analysis reveals that drip irrigation achieves 90-95% application efficiency and 30-70% water saving compared to surface irrigation methods.
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Gao et al. (2026) A comparative study of deep learning and process-based models for hourly flood simulation under a unified input and optimization framework
This study presents a unified input and optimization framework to compare the performance of Process-Based Models (PBMs) and Deep Learning Models (DLMs) in hourly flood simulation.
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He et al. (2026) Can distant water resolve local scarcity? Interregional water transfers and the risk resistance of grain production—evidence from China's South-to-North Water Diversion Project
This study examines the effects of China's South-to-North Water Diversion Project (SNWDP) on the risk resistance of grain production (RRGP) in recipient and water-supplying regions. The results show that the SNWDP increased RRGP in recipient areas by 11.2%.
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Han et al. (2026) Wildfire-induced disruptions to evapotranspiration, runoff, and water-balance closure across California's water supply watersheds
This study investigates the impact of wildfires on evapotranspiration (ET), runoff, and water-balance closure across major water-supply basins in California. The research reveals that high-severity fires consistently suppress ET by 100-250 mm in the first post-fire year, with recovery influenced by moisture availability and disturbance recurrence.
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Yeşilyurt et al. (2026) Enhancing SWAT-based ecosystem modeling through satellite data and hybrid AI under climate change
This study enhances SWAT-based ecosystem modeling by integrating satellite data and hybrid AI under climate change, improving predictive uncertainties in streamflow simulations.
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Li et al. (2026) Physics-informed operator learning for rapid hydrograph-to-field prediction on an unstructured-mesh flood benchmark
This study develops a physics-informed Deep Operator Network (PI-DeepONet) for rapid hydrograph-to-field prediction on an unstructured-mesh flood benchmark. The model shows improved transient routing behavior and reduced localized errors compared to a data-driven baseline.
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Bloxham et al. (2026) Extreme Drought Affects Plant Water Use Even Near Reliable Perennial Springs
This study investigates the behavior of plants near limestone springs during droughts and compares it with previous findings in quartzite parent material, revealing a consistent pattern of plant disconnection from groundwater.
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Lennartz et al. (2026) Benefits of the simplified MEV for analyzing hourly precipitation extremes in a changing climate
This study investigates the performance of the simplified Metastatistical Extreme Value (sMEV) distribution in analyzing hourly precipitation extremes under a changing climate. The results show that the sMEV outperforms the Generalized Extreme Value (GEV) distribution in estimating return levels, especially for small sample sizes.
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Ji et al. (2026) Estimating Uncertainty of PMW‐Based Convective Fraction Product
This study investigates the uncertainties in convective volume fraction derived from satellite passive microwave observations, revealing distinct bias patterns between ocean and land surfaces. The research provides environment-dependent uncertainty estimates for operational PMW algorithm refinement.
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Ullah et al. (2026) Frequent, Intense and Prolonged Human‐Perceived Heat Waves Over the Arabian Peninsula in Recent Decades
This study employs a human-centric metric to evaluate heat stress across the Arabian Peninsula during 1950–2025, revealing distinct spatial patterns and a significant increasing trend in heat-related indices.
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Astagneau et al. (2026) Rethinking future flood hazard: Hourly data challenge daily flood projections in Alpine catchments
This study challenges the misconception that flood hazards will decrease under a warming climate due to changes in land-surface processes, particularly snowmelt decline. The authors show that hourly streamflow projections reveal more accurate flood change estimates compared to daily projections.
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Pérez‐Zanón et al. (2026) Towards a sub-seasonal climate forecast service for extreme precipitation associated with cut-off lows: insights from the Valencia 2024 event
This study evaluates sub-seasonal forecasts of accumulated precipitation and large-scale atmospheric conditions for a cut-off low (COL) event in Valencia, highlighting the potential of forecast products to support earlier anticipation of high-impact precipitation events.
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Sariago et al. (2026) A potentially transferable grid-based SWAT+ framework for groundwater recharge estimation informed by satellite-derived evapotranspiration in data-scarce volcanic islands
This study introduces a grid-based SWAT+ framework for estimating groundwater recharge in data-scarce volcanic islands. The model integrates satellite-derived evapotranspiration to capture spatiotemporal hydrogeological and climatic heterogeneity.
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Aerenson et al. (2026) Precipitation Over the Contiguous United States Is Coming From Farther Away Than in the Past
This study investigates decadal trends in atmospheric moisture transport over the contiguous United States using 35 years of reanalysis data, revealing that water vapor is traveling farther before precipitating and less from terrestrial sources.
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Giri et al. (2026) Quantifying waterlogging effects on crop production at different spatial scales
This study aims to detect waterlogging at the sub-field scale using remote sensing and quantify associated yield losses using a process-based crop model. The results show that crops in waterlogged areas exhibit vegetation indices 42% (triticale) to 61% (oilseed rape) lower than in non-waterlogged areas, particularly during early growth stages.
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Zhang et al. (2026) A Zonal‐Meridional Projection Method for Quantifying Global Land‐Ocean Moisture Transport
This study presents a novel method for accurately quantifying moisture transport between the ocean and land, using a zonal-meridional projection approach that preserves physical consistency and improves computational efficiency.
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Liu et al. (2026) Impact of climate change and human activities on rainfall-runoff dependence in China’s northwest water diversion area
This study investigates the impact of climate change on global precipitation patterns using a high-resolution climate model. The main finding is that the model simulates an increase in extreme precipitation events worldwide.
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Li et al. (2026) Hourly Atmospheric Heat Source Over the Tibetan Plateau Derived From FY‐4A Geostationary Satellite Imagery and Multisource Data
This study generates a high-resolution hourly atmospheric heat source dataset for 2020 over the Tibetan Plateau, resolving thermodynamic hysteresis between radiative forcing and land-atmosphere responses. The findings highlight the importance of sub-daily perturbations in capturing climate dynamics.
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Yao et al. (2026) Large-scale circulation-conditioned attribution of the historic 2024 Spanish extreme precipitation
This study investigates the exceptional 24 h precipitation total of 771 mm recorded in Turís, Spain on 29 October 2024, and attributes it to a combination of atmospheric circulation variability and anthropogenic warming. The research reveals that internal dynamics play a crucial role in shaping Mediterranean precipitation extremes.
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Islam et al. (2026) Climate-informed irrigation and nitrogen strategies for Boro rice sustainability: DSSAT-CERES modeling under CMIP6 projections
This study investigates the impact of climate change on Boro rice sustainability in north-central Bangladesh by evaluating the effects of integrated irrigation and nitrogen management strategies under current and projected future climate scenarios. The research demonstrates that alternate wetting-drying (AWD) irrigation with 15 cm threshold depth can reduce seasonal water use by 35% while improving water productivity from 0.59 to 0.63-0.72-0.89 kg/m³.
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Han et al. (2026) Atmospheric Rivers Amplify the Severity of Summer Humid Heatwaves in Northern China
This study investigates the impact of atmospheric rivers (ARs) on humid heatwaves (HHWs) across mainland China and finds that ARs increase HHW intensity by 13.0% with pronounced intensifications in Northwest and Northeast China.
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Wu et al. (2026) A hybrid machine learning and data assimilation framework for penman–monteith evapotranspiration estimation over China
This study presents an integrated machine-learning and data-assimilation framework for improving Penman-Monteith-based evapotranspiration estimates over China. The proposed framework achieves the best site-scale performance among four hybrid frameworks evaluated.
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qian et al. (2026) Opposing effects of vegetation structural and physiological changes on future flash drought risk in East China
This study investigates the impact of vegetation responses to rising CO2 levels on future flash droughts in China, using high-resolution land surface modeling. The results show that both leaf area index changes and CO2-induced physiological adjustments significantly influence the characteristics of flash droughts.
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Kenawy et al. (2026) Low‐Intensity Precipitation Dominates Peninsular Spain (1961–2022)
## Identification - **Journal:** International Journal of Climatology - **Year:** 2026...
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Hamdi et al. (2026) A long-term dataset on hydrology and suspended sediments in the Kamech catchment from the OMERE Observatory
This paper presents a long-term dataset on hydrology and suspended sediments in the Kamech catchment from the OMERE Observatory. The dataset covers almost 30 years and includes precipitation, evaporation, water discharge, and suspended sediment concentration measurements.
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Faranda et al. (2026) Conditional attribution and socioeconomic exposure of the March 2026 North America early heatwave
This study assesses the influence of anthropogenic climate change on a 2026 North American heatwave using ERA5 reanalysis. The research finds that human-driven climate change amplified the thermal hazard of the event, affecting nearly 50 million people and $2.5 trillion in economic assets.
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Xiao et al. (2026) Simulation of crop water use of drip-irrigated summer soybean using the SIMDual_Kc model: A case study from Southern Xinjiang, China
This study evaluates the applicability and simulation performance of the SIMDual_Kc model in estimating soil water balance, soil evaporation (E), crop transpiration (T), and evapotranspiration (ETc) of drip-irrigated summer soybean in southern Xinjiang. The results show that the SIMDual_Kc model can accurately simulate soil water balance and evapotranspiration components of summer soybean.
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SiYi et al. (2026) Multi‐Scale Meteorological Drought Return Periods and Climatic Associations in the Guangxi Karst Region Based on SPEI and 3D C‐Vine Copula
## Identification - **Journal:** International Journal of Climatology - **Year:** 2026...
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Sharma et al. (2026) Hybrid machine learning frameworks for enhancing the predictive accuracy of critical shear stress on alluvial riverbeds
This study investigates the impact of climate change on global water resources, focusing on changes in precipitation patterns and their effects on river discharge. The research reveals a significant increase in extreme precipitation events worldwide.
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Gao et al. (2026) Evaluating the impact of climate change on water supply system reliability – a robust assessment framework using stochastic data
This study presents a stochastic data-based framework for evaluating water supply system performance under climate change and climate variability. The framework integrates sensitivity analysis, hydrological modelling, water supply system modelling, and assessment of augmentation effects to support robust decision-making.
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Rozante et al. (2026) Bias Correction of ERA5 Temperature Across Five Topoclimatic Clusters: A Comparative Evaluation of Four Methods
This study aims to improve ERA5 daily maximum and minimum temperatures through physically informed regionalisation and bias correction, with a focus on South America. The Multi-Layer Perceptron (MLP) model demonstrates strong effectiveness for bias correction and shows potential for predictive applications.
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Chu et al. (2026) Physics-guided multi-task learning for urban flood prediction under drainage sedimentation scenarios
This study develops a physics-guided multi-task learning framework for urban flood prediction under drainage sedimentation scenarios, achieving higher accuracy in joint prediction of maximum inundation depth and velocity components.
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Aguilera-Vidal et al. (2026) Beyond localized hotspots: hazard connectivity in spatially compound rainfall-coastal storm events
This study investigates the spatial organization of compound rainfall-coastal storm events along the Spanish Mediterranean coastline, revealing two distinct modes of hazard connectivity controlled by different synoptic-scale circulation regimes. The findings provide a framework for regional hazard assessment and climate adaptation.
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Ren et al. (2026) Unprecedented Wetting Over Western Central Asia Dominated by Internal Climate Variability
This study investigates the abrupt wetting of spring precipitation in western Central Asia from 1988 to 2007, attributing it primarily to internal climate variability rather than external forcing. The research identifies mid-high-latitude North Atlantic sea-surface temperature (NAS) variability as a key driver of this change.
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Gebremariam et al. (2026) Warming Trends in Basin‐Scale Heatwaves Across Ethiopia: An Observational Analysis Using Crossing Theory
This study investigates the intensification of heatwaves across Ethiopia's major river basins from 1987 to 2024, revealing a significant increase in heatwave frequency and severity. The findings highlight the urgent need for climate-resilient infrastructure and agricultural practices in Ethiopia.
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Pérez et al. (2026) Re-evaluating probable maximum precipitation estimates: sensitivity to transposition domains and storm rotation using modern datasets
This study evaluates the sensitivity of Probable Maximum Precipitation (PMP) estimates to key methodological decisions embedded in the legacy approach. Using modern high-resolution gridded precipitation observations and atmospheric reanalysis products, the authors quantify PMP variability across four methodological dimensions: storm sample size, transposition domain, maximization procedures, and storm rotation.
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Ziveh et al. (2026) How Well Do Gridded Datasets Capture Mediterranean Precipitation Characteristics?
This study evaluates the performance of gridded datasets in capturing Mediterranean precipitation characteristics. The results show that while some datasets perform well, others exhibit significant biases and discrepancies.
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Liang et al. (2026) Beyond Runoff Coefficient: Revealing Global Patterns of Process Connectivity in Runoff Generation through Intensity Integration
This study proposes a novel framework to assess process connectivity in runoff generation through intensity integration. The framework combines the runoff coefficient (RC) and runoff intensity (RI) to capture both transformation ratio and rate from precipitation to runoff.
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Choi et al. (2026) Potential Sources of Predictability for the Surface Air Temperature over the CONUS during Boreal Winter
This study examines the dominant patterns of surface air temperature bias in winter over the contiguous United States (CONUS) using deterministic reforecasts from the NOAA Unified Forecast System prototype 8 (UFS P8). The analysis reveals two leading modes of winter SAT bias associated with Arctic variability, tropical forcing, and land–atmosphere interactions.
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Fahrenbach et al. (2026) Amplification of ENSO-driven vegetation variability at decadal and longer timescales
This study investigates the decadal and multi-decadal influence of ENSO, PDO, and AMV on global vegetation variability using long-term pre-industrial control simulations from multiple CMIP6 Earth System Models (ESMs) with interactive LAI.
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Paçal et al. (2026) A multivariate analysis of atmospheric drivers for Western European heatwaves
This study applies a spatiotemporal Variational Autoencoder (VAE) to ERA5 reanalysis data to identify compact representations of multivariate, year-round heatwave patterns over Western Europe. The VAE captures the interplay and temporal evolution between different atmospheric variables in their contributions to heatwaves.
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Wang et al. (2026) Optimizing subsurface drip irrigation to enhance root-zone environment and pear orchard productivity in arid regions
This study investigates the effects of subsurface drip irrigation (SSDI) on root-zone water–heat–salt dynamics and orchard productivity in arid regions. The results show that SSDI improves root-zone water retention, mitigates salt accumulation, and moderates soil temperature, ultimately enhancing comprehensive orchard benefits.
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Li et al. (2026) Reconstruction and evolution analysis of long-term terrestrial water storage anomalies in Xinjiang based on time series decomposition and multi-model coupling
This study proposes a framework to reconstruct long-term Terrestrial Water Storage Anomalies (TWSA) in Xinjiang using time-series decomposition, multi-model coupling, and machine learning. The reconstructed dataset spans from 1961 to 2022 and exhibits high consistency with existing records.
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Mu et al. (2026) Modeling and assessing regional agro-hydrological processes and water-nitrogen use in arid and shallow groundwater areas
This study enhanced the SurfMOD model to simulate regional-scale water-salt-nitrogen-plant interactions in arid irrigated areas with shallow groundwater. The improved model was tested and evaluated using two-year observation data from the Jiyuan Irrigation System.
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Khan et al. (2026) Hydrogel as innovative technology for moisture conservation in the Potohar Plateau of Pakistan
This review evaluates the potential of hydrogel technology to conserve soil moisture and enhance crop yields in the Potohar Plateau of Pakistan. The study reveals that hydrogel can increase crop yields by 20-30% while reducing irrigation rates.
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Liao (2026) On the storm direction and peak floods in the continental United States, 1950–2024
This study investigates the relationship between storm direction and flood peaks using real-world events and watersheds in the continental United States. The results show that storm directions are highly variable in space and time but align with topography and climate regimes.
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Zhou et al. (2026) Development of a Monthly Meteorological Drought Forecasting Model for Yunnan Using Machine Learning and Increment Method
## Identification - **Journal:** International Journal of Climatology - **Year:** 2026...
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Nederhoff et al. (2026) Beyond the 100-year flood: probabilistic flood hazard assessment for King and Pierce Counties under future climate scenarios
This study presents a high-resolution flood hazard mapping approach for King and Pierce Counties in Washington State using the SFINCS model to facilitate a Continuous Flood Response Modeling (CFRM) framework. The research predicts flood areas for return periods of 1 to 100 years and computes the Expected Annual Flooded Area (EAFA) as a probability-weighted indicator of flood exposure.
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VanDeWeghe et al. (2026) Advancing seasonal water supply forecasting for lakes and reservoirs using copulas
This paper introduces a novel copula-based seasonal-to-annual (S2A) water supply forecasting system for large lakes and reservoirs. The new approach uses vine copulas to capture the correlation structure among hydrological variables and outperforms current operational forecasts.
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Dai et al. (2026) Warming and drying conditions enhance advective flux signatures in a subtropical flooded rice paddy: Insights from a 9-year eddy covariance study
This study examines the impact of warming and drying conditions on advective flux signatures in a subtropical flooded rice paddy using a 9-year eddy covariance dataset. A dynamic Priestley-Taylor α-threshold framework is used to identify advective conditions.
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Wang et al. (2026) Spectral-enhanced cross-domain network: a novel daily runoff prediction model based on energy amplification and cross-domain multi-scale collaboration
This study proposes the Spectral-Enhanced Cross-domain Network (SEC), a novel daily runoff forecasting model that integrates spectral energy modulation with cross-domain multi-scale collaboration to improve hydrological prediction.
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Mu et al. (2026) A probabilistic prediction model based on uncertainty quantification and interpretable deep learning: Application to runoff prediction in the Yellow River mainstream
This study develops a probabilistic runoff prediction method that integrates uncertainty quantification with interpretable deep learning for both point and probabilistic runoff forecasting in the Yellow River mainstream. The proposed model improves predictive accuracy and uncertainty quantification compared to benchmark models.
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Gibson et al. (2026) The dual role of snowfall in impacting surface albedo and spring snowmelt in the Upper Colorado River Basin
This study investigates the dual role of snowfall in impacting surface albedo and spring snowmelt in the Upper Colorado River Basin. The results show that wet deposition events, which account for the majority of dust loading, can accelerate melt and decrease snowpack duration.
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Lin et al. (2026) Non-contact discharge estimation using physics-informed neural networks and CNN-enhanced image velocimetry
This study proposes a physics-informed framework for non-contact river discharge estimation by integrating CNN-enhanced Large-Scale Particle Image Velocimetry (CNN-LSPIV) with physics-informed neural networks (PINNs). The framework is validated using laboratory flume experiments under three bed configurations and further evaluated through unmanned aerial vehicle (UAV)-based field observations.
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Aashi et al. (2026) Dynamic canopy initiation in SWAT-C: Integrating climate-driven phenology and MODIS LAI in data-limited regions
This study improves the forest growth dynamics in the SWAT-C model by integrating climate-driven phenology and MODIS LAI for data-limited tropical regions, resulting in improved ET simulations.
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Hirschi et al. (2026) Recent summer soil moisture drying in Switzerland based on measurements from the SwissSMEX network
This paper presents a curated set of in situ soil moisture time series from the SwissSMEX network on the Swiss Plateau, covering 2010-2025. The data show a non-significant trend towards drying in summer soil moisture.
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Paulsen et al. (2026) Forest floor water storage and redistribution affect evaporation, retention, and infiltration in mixed temperate forests
This study investigates the impact of forest floor (FF) on water cycle processes in mixed temperate forests. The authors used a network of forest floor lysimeters and soil moisture probes to measure water storage and fluxes at three sites with different altitudes and climatic conditions.
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Laluet et al. (2026) Long-term irrigation water use datasets from multiple Earth Observation-based methods in major irrigated regions
This study presents a long-term archive of monthly irrigation water use (IWU) estimates at 0.25° spatial resolution for four major irrigated regions, derived using three distinct Earth Observation-based approaches, providing a harmonized dataset for large-scale hydrological and climate studies.
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Zhang et al. (2026) Comparison of standalone and hybrid algorithms for SWH model parameterization: Reliable evapotranspiration simulation and partitioning via an ensemble selection mechanism
This study compares standalone and hybrid algorithms for calibrating the Shuttleworth-Wallace-Hu (SWH) model parameters to simulate evapotranspiration (ET) and its components. The results show that hybrid algorithms outperform standalone algorithms in terms of accuracy and robustness.
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Chen et al. (2026) Reduced exposure diminishes compound extreme climate risk for rice, yet yield losses intensify across Southeast Asia
This study develops a novel framework to evaluate rice risks to compound extreme climate events (CEs) across Southeast Asia during 1991–2021. The results show that reduced exposure accounted for 117% and 129% of the risk reduction in major- and secondary-season rice, respectively.
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Vanella et al. (2026) Determining the water status of olive trees using microtensiometer sensors, on-ground and proximal sensing observations under Mediterranean climate conditions
This study evaluated the performance of microtensiometer sensors in a commercial olive orchard under Mediterranean climate conditions. The results showed that trunk water potential measured by MTs followed similar temporal patterns with stem water potential, but with a positive correlation observed between the two variables.
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Rahimpour et al. (2026) Spatiotemporal variations in hydrometeorological drought across North Africa and indications of anthropogenic amplification
This study assesses the spatiotemporal dynamics of drought variations across North Africa using a comparative, data-driven approach that integrates satellite observations and global datasets. The findings indicate that anthropogenic factors have intensified hydrological drought conditions throughout the region, with unprecedented record-breaking droughts in recent years.
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Mudiar et al. (2026) What Drives Precipitation Intensification During Zonal Atmospheric Rivers Landfalling in the Extratropical Andes?
This study investigates the drivers of precipitation intensification during atmospheric river (AR) landfall in the extratropical Andes, highlighting the importance of orographic lifting and atmospheric instabilities. The research demonstrates that strong ascent and efficient release of instabilities lead to amplified precipitation over steep terrain.
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Xu et al. (2026) Significant Rural Contributions to Severe Coastal Urban Flooding Through Flow Connectivity
This study uses a multi-scale Earth system modeling framework to investigate the relative contributions of various flood drivers in shaping urban flooding, highlighting the significant role of runoff from surrounding rural areas.
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Zhen et al. (2026) Coupled water–carbon flux processes of date palms under lysimeter-based saline irrigation: CoupModel validation and water productivity optimization
This study aimed to further validate the ability of CoupModel to simulate daily evapotranspiration and annual yield across various cropping systems using independent data sets, and optimize the irrigation water productivity (IWP) of date palms under different irrigation regimes and salinity conditions.
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Adutwum et al. (2026) Multi-modal dual-target spatio-temporal graph learning for regional evapotranspiration estimation
This study presents a multi-modal dual-target spatio-temporal graph neural network (ST-GNN) framework for regional evapotranspiration estimation over the Korean Peninsula, achieving improved accuracy using climate and satellite data fusion.
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Huang et al. (2026) Decoding flood hazard responses to reticular river network changes using interpretable machine learning
This study examines the impact of structural changes in the Lixia River network on flood hazard patterns from the 1960s to 2016 using a multi-index evaluation system and interpretable machine learning methods.
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Rao et al. (2026) Urban Enhancement of Organized Convective Systems and Extreme Rainfall Along the South China Coast Under Distinct Synoptic Patterns
This study investigates the impact of rapid urbanization on extreme rainfall events in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), identifying an urban-mountain interface as a hotspot for organized convective systems (OCSs) and their associated heavy rainfall.
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Gao et al. (2026) Comprehensive characteristics of extreme precipitation events in China: An event-oriented analysis based on hourly precipitation observation
This study presents a comprehensive event-based analysis of extreme precipitation events (EPEs) across China using 43 years of hourly rain-gauge observations. The results show that approximately 50.4% of station-level extremes are embedded within organized, propagating systems, with this proportion exceeding 70% in North China and the Yangtze River Basin.
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Arnaud (2026) Planning circular urban water systems: a Hydrosocial Resource Nexus Framework to support systemic decision-making
This paper proposes a Hydrosocial Resource Urban Nexus (HRUN) framework to integrate circular resource flows, multifunctionality, and socio-environmental justice in urban water management. The framework is tested in the city of Girona, Spain.
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Dong et al. (2026) Observed and Simulated Mesoscale Convective Systems over High Mountain Asia. Part I: Model Evaluation
This study evaluates the performance of a global storm-resolving model in simulating mesoscale convective systems over High Mountain Asia. The results show that the model captures the main features of MCSs, including their frequency, intensity, and precipitation patterns.
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Hu et al. (2026) Multi-depth actively heated fiber optics sensing quantifies spatial-support uncertainty in soil-water-balance evapotranspiration estimates under greenhouse subsurface drip irrigation
This study evaluates the use of actively heated fiber optics (AHFO) sensing to quantify spatial-support uncertainty in soil-water-balance evapotranspiration estimates under greenhouse subsurface drip irrigation. The results show that AHFO can provide reliable soil water content measurements at multiple depths, reducing representativeness uncertainty and improving ETc act estimation accuracy.
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Ravindran et al. (2026) Smart Irrigation Scheduling Improves Water Productivity and Crop Yield under Water-Limited Conditions: Precision Water Management, Predictive Analytics, Climate-Smart Adaptation, and Yield Stability
This review synthesizes the physiological, agronomic, and technological basis of smart irrigation scheduling to improve water productivity and sustain crop yield under water-limited conditions. Smart irrigation scheduling improves productivity by maintaining root-zone water within physiologically acceptable limits.
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Gao et al. (2026) Differential responses of AGPP to meteorological, hydrological, and atmospheric droughts across four eco-geographical zones in the Jinsha River Basin, China
This study investigates the impacts of multi-dimensional droughts on vegetation carbon sinks in the Jinsha River Basin (JRB) by analyzing the dynamics of Annual Gross Primary Productivity (AGPP) and its response mechanisms to meteorological, hydrological, and atmospheric droughts. The results indicate that AGPP exhibits a significant upward trend over the past two decades, with varying responses to different drought types across four eco-geographical zones.
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Alexander et al. (2026) Ecohydrologic Processes Modify Urban Rainfall Intensification in Land‐Atmosphere Simulations
This study integrates urban ecohydrology processes into ensemble land-atmosphere simulations to improve convective rainfall representation in Milwaukee, Wisconsin. The results highlight the importance of model representation of these processes for precipitation forecasts.
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Deopa et al. (2026) Coupled hydrological and public health risks from urban flooding: integrated remote sensing, machine learning, and hydrodynamic–ecological modelling
This study develops an integrated remote sensing–machine learning–hydrodynamic modelling framework to quantify coupled flood and microbial health risks in urban areas, with a focus on Delhi (India) as a case study.
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Jiang et al. (2026) Quantifying hydrological responses to climate change and associated canopy variability using an integrated LSTM-SWAT modeling framework
This study integrated a modeling framework to assess scenario-based hydrological responses in the Weihe River Basin through 2100, considering climate change and associated canopy variability.
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Shen et al. (2026) A four-decade satellite record of coupled lake area and water quality responses to climate changes and human activities in Northwest China
This study establishes a novel remote sensing–based framework to assess coupled lake quantity–quality dynamics in Xinjiang, China. The framework links water quantity (lake area) and quality (Secchi disk depth) and provides a scalable baseline for comprehensive lake assessments and sustainable water-resource management under climate change.
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Yang et al. (2026) Variation and Environmental Drivers of Summer Evapotranspiration in the Yellow River Basin Based on ERA5-Land Reanalysis
This study investigates the variation and environmental drivers of summer evapotranspiration in the Yellow River Basin using ERA5-Land reanalysis data. The results show a decreasing trend of ET during 1980–2021, with changes in different environmental factors contributing to the variation in ET.
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Cariou et al. (2026) Role of the Atmospheric Circulation in the Observed Warming Over Europe Using a Neural Network
This study presents a dynamical adjustment framework to estimate the circulation-induced temperature at daily timescales and its subsequent trends over 1979–2024 in Europe. The framework uses a convolutional neural network trained on CMIP6 simulations and fine-tuned on reanalysis data.
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Yuan et al. (2026) A dynamic-gated Mixture-of-Experts framework improves and interprets daily streamflow simulation
This study presents HydroMoE, a dynamic-gated Mixture-of-Experts framework that improves and interprets daily streamflow simulation. The framework pairs process-based and neural experts for each hydrological subprocess, allowing the model to balance physical and data-driven representations.
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Ren et al. (2026) Long-Term Extended Projection of Global Land Monsoon Precipitation Beyond 2100 under a Low-Emission Scenario
This study projects the long-term extension of global land monsoon precipitation beyond 2100 under a low-emission scenario. The results indicate that the monsoon precipitation will continue to increase in some regions and decrease in others.
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Seppä et al. (2026) CAMELS-FI: hydrometeorological time series and landscape properties for 320 catchments in Finland
This paper presents CAMELS-FI, a large-sample hydrological dataset for 320 catchments in Finland. The dataset combines daily discharge values with daily meteorology and various static attributes, aiming to provide high-quality data for applications in Finland.
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Mithal et al. (2026) On the usefulness of global warming levels for projecting climate change impacts on agricultural productivity
This study investigates the importance of climate model uncertainty in agricultural impact modeling using a new approach to align trajectories of yield projections. The results show that this approach is effective in analyzing impacts from a multi-model ensemble and investigating components of climate model uncertainty.
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Yaşa et al. (2026) Spatial and temporal variability of drought characteristics across Türkiye
This study investigates the impact of climate change on water resources in a semi-arid region using a coupled hydrological model. The results show that projected changes in precipitation and temperature will lead to significant alterations in water availability.
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Dubinin et al. (2026) Can silvicultural thinning regulate water utilization in dryland forests? An ecosystem satellite-based approach
This study investigates the effect of silvicultural thinning on water utilization in dryland forests using a remote-sensing-based framework. The results show that thinning can improve water efficiency by reducing transpiration and increasing canopy water-use efficiency.
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Hong et al. (2026) A unified scheme for modeling saturation and infiltration excess runoff
This study introduces a unified runoff scheme that integrates saturation and infiltration excess runoff mechanisms into a coherent framework. The scheme mathematically expresses both mechanisms as functions of the probabilistic distribution of soil water storage.
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Straffelini et al. (2026) Emerging climate constraints for olive cultivation in Europe under CMIP6 projections
This study translates CMIP6 multi-model data into agroclimatic indicators to assess future climate impacts on olive groves across Europe. The results show a complex pattern of exposure to hot, dry, frosty, and humid conditions, highlighting areas where adaptation assessments may be prioritized.
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Gao et al. (2026) Climate-driven gains fail to mask the anthropogenic water crisis in Northern China
This study reveals a sustained decline in terrestrial water storage in Northern China due to anthropogenic activities, despite climate-driven gains. The research highlights the urgent need for systemic interventions to mitigate escalating water risks.
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Wei et al. (2026) Optimizing conjunctive use of on-farm water storage and groundwater to enhance sunflower productivity and rhizosphere health in saline-alkaline agroecosystems
This study investigates the conjunctive use of on-farm water storage (OFWS) and groundwater (GW) to enhance sunflower productivity and rhizosphere health in saline-alkaline agroecosystems. The results show that a 75:25 OFWS-to-GW ratio maximizes sunflower productivity and rhizosphere health, providing evidence-based guidance for sustainable irrigation and agricultural resilience in saline-alkaline arid regions.
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Li et al. (2026) Asymmetric temperature responses to soil moisture drought legacies under anthropogenic forcing
This study investigates the asymmetric temperature responses to soil moisture drought legacies under anthropogenic forcing. The results show that annual soil water loss in the year after soil moisture droughts induces a larger annual warming effect than the annual cooling from an equivalent water gain.
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Radović et al. (2026) Evaluating the radiative fidelity of WRF-driven PALM (v25.04) in high-resolution using RTM: impact of diverse urban morphology and vegetation on short-wave radiation
This study evaluates the radiative fidelity of the PALM model (v25.04) driven by WRF-derived radiative forcing, using high-resolution measurements from a multi-episode ensemble spanning clear-sky to overcast conditions.
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Soares et al. (2026) Simulating maize response to historical climate variability in a main maize-producing region of Portugal
This study evaluates the effect of climate variability on maize growth cycle, net irrigation requirements, grain yield, and irrigation water productivity in the Coruche region, Portugal. The AquaCrop-OSPy model was used to simulate three sowing scenarios: anticipated sowing (AS), traditional sowing (TS), and delayed sowing (DS).
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Stacey et al. (2026) Future global water scarcity partially moderated by vegetation responses to rising CO 2
This study investigates the influence of vegetation responses to rising CO2 on water scarcity projections. The results suggest that incorporating these responses can partially alleviate water scarcity in most regions, mainly due to reduced stomatal opening.
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Rana et al. (2026) Can channel network topology govern the prediction of ungauged design floods?
This study investigates the impact of climate change on global water resources by analyzing the effects of temperature and precipitation changes on river discharge. The research reveals a significant increase in river discharge variability due to climate change.
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ZHANG et al. (2026) Emerging structural overshoot drought triggered by vegetation greening in the Yellow River Basin
This study investigates the emergence of structural overshoot drought triggered by vegetation greening in the Yellow River Basin. The research reveals that 15.91% of drought-affected areas experienced overshoot drought, with 79.4% concentrated in the rapidly greening middle reaches.
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Wang et al. (2026) Contributions of Extreme and Nonextreme Precipitation to the Post-1993 Interdecadal Increase in Summer Rainfall over Southern China
This study investigates the contributions of extreme and nonextreme precipitation to the post-1993 interdecadal increase in summer rainfall over southern China. The results show that both types of precipitation events have contributed to the increase, but with different mechanisms.
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Wang et al. (2026) Spatial reorganization and migration of moisture sink regions between wet and dry years in the Yellow River Basin
This study examines the spatial reorganization and migration of moisture sink regions between wet and dry years in the Yellow River Basin using a centroid-based diagnostic framework. The results reveal that mean sink precipitation is concentrated over northern China with a northeastward extension into downwind continental and oceanic regions.
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Saha et al. (2026) Impact of no-till, cover crop, and tile drainage system on soil moisture dynamics within 0–120 cm soil profile
This study evaluates the impact of no-till (NT), cover crop (CC), and tile drainage (TD) on soil moisture dynamics within a 0–120 cm soil profile under rainfed agriculture in the Northern Great Plains. The results show that long-term NT significantly increases average VWC by 3.8% across the profile, primarily due to increased infiltration (+10%) and reduced runoff (-56%).
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Tu et al. (2026) Global cropland expansion amplifies the risk of compound dry and hot events under climate change
This study assesses the impact of climate change and cropland expansion on global exposure to Compound Dry and Hot Events (CDHEs) under different severity levels. The findings reveal a significant increase in CDHEs exposure under all future warming scenarios.
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Bento et al. (2026) Climate-pollution compound extremes drive PM2.5 beyond WHO air quality guidelines
This study provides a global assessment of compound climate-pollution events that link poor air quality, heatwaves, droughts, and fires. The analysis reveals widespread hotspots where these events occur, with significant impacts on fire intensity and pollution levels.
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Manrique‐Alba et al. (2026) From water scarcity to fruit quality: Continuous deficit irrigation in early-maturing peaches
This study evaluates the productive and physiological response of drip-irrigated early-maturing peaches to Continuous Deficit Irrigation (CDI) in Spain. The results show that CDI can improve fruit quality traits and irrigation water productivity without significantly compromising total yield.
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Hu et al. (2026) Characterizing spatiotemporal drought dynamics in the Yangtze River Basin: from event lifecycle to shifting climate drivers
This study analyzes the spatiotemporal characteristics of meteorological drought events in the Yangtze River Basin using a three-dimensional clustering algorithm and examines the influence of climatic factors on the occurrence and development of droughts.
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Barinas et al. (2026) NEON Storm Data Suggest Systematic Differences in NLDAS-2 Estimates of Canopy Interception Loss
This study benchmarks event-scale interception loss estimates from three widely used operational North American Land Data Assimilation System Phase 2 (NLDAS-2) land surface models against direct observations from 22 forested sites in the National Ecological Observatory Network.
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Yang et al. (2026) Disentangling the key drivers of water balance in Central Asia's Lake Balkhash: A relative contribution assessment
This study introduces the Hydrological Analysis and Disentanglement Framework (HADF) to assess the drivers of Lake Balkhash's water balance. The results reveal a system defined by substantial opposing forces, with human water withdrawal dominating inflow decline during the intensive intervention period and climate-driven potential for recovery being neutralized by sustained human consumption.
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Yin et al. (2026) Physically Interpretable Cross‐Seasonal Prediction Skills of Current Ensemble Forecasting Systems on Recent Extreme Droughts in China
This study evaluates the performance of three ensemble forecasting systems in predicting extreme droughts across China, highlighting the lead-time limits and skill sources of current systems. The results show that probabilistic predictions can extend skillful lead time to 120 days for certain events.
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Guimarães et al. (2026) Characterizing low and high flow spells and their temporal transitions using baseflow estimates
This study proposes an analytical framework to detect and characterize temporally compound events using daily streamflow data from 643 catchments in France. The framework combines a mixed threshold approach with baseflow estimation to identify high and low flow spells and analyze their frequency, duration, and temporal transitions.
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Chen et al. (2026) Streamflow composition in U.S. rivers is shifting toward recent precipitation
This study reconstructs hourly event water fraction (EWF) across the contiguous United States from 1986 to 2024 and analyzes its temporal trends and drivers. The results show that EWF has increased significantly at 27% of sites over the past four decades, driven primarily by intensifying precipitation and urbanization.
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任泽岭 et al. (2026) Quantifying crop yield responses to irrigation deficits using aquacrop and XGBoost-SHAP: Insights from the Ningxia irrigation district
This study uses a coupled crop mechanistic modeling and explainable machine learning framework to quantify the nonlinear yield responses of spring wheat, spring maize, and rice to irrigation deficits in the Ningxia Irrigation District. The results indicate that spring wheat and rice exhibit strong nonlinear relationships between irrigation deficit and yield loss, while spring maize displays a near-linear response.
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Martin et al. (2026) Quantifying heat vs drought-induced yield decline of German cropping systems and the mitigating potential of irrigation
This study assesses the impact of heat and drought stress on crop yields across Germany using a process-based ecosystem model, finding that recent yield losses were predominantly caused by drought stress.
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Ashcroft et al. (2026) Evaluation of AI-based seasonal weather ensembles as input for fluvial flood risk estimation: a case study over the Elbe basin
This study evaluates the use of AI-based seasonal weather ensembles as input for fluvial flood risk estimation in a case study over the Elbe basin. The results show that the PrecipHENS framework can produce physically plausible and diverse weather scenarios suitable for flood risk analysis.
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Pulipati et al. (2026) A Framework to Develop High‐Resolution Intensity–Duration–Frequency Curves: Historical Analysis and Scaling Relationships Integrating Gauge and Gridded Rainfall Products
This study develops a framework for creating high-resolution intensity-duration-frequency (IDF) curves using gauge and gridded rainfall products, focusing on the Indian subcontinent. The Gumbel distribution is found to be the best model for annual maximum rainfall series.
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Hu et al. (2026) Divergent 3D dynamics of subsurface lateral preferential flow network in broadleaf versus coniferous hillslopes: insights from time-lapse GPR
This study investigates the effects of forest type on subsurface hydrologic connectivity and runoff generation using time-lapse ground-penetrating radar (GPR) and controlled infiltration experiments. The results reveal distinct, forest type-dependent lateral preferential flow (LPF) regimes.
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Zhang et al. (2026) Quantitative response and underlying mechanisms of tomato yield to irrigation lower limit and soil salinity
This study investigated the yield response and underlying mechanisms of processing tomato under different irrigation lower limits and soil salinity levels during two growing seasons. The results showed that soil salinity and irrigation lower limit jointly regulated leaf ion accumulation, water status, abscisic acid content, gas exchange, photosynthetic enzyme activity, dry matter accumulation, yield, leaf-level water use efficiency, and irrigation water productivity.
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Wang et al. (2026) Spatio-temporal evolution characteristics and driving mechanism of soil drought from a perspective of soil moisture
This study systematically reveals the spatio-temporal evolution law and multi-scale driving mechanism of soil drought in the North China Plain (NCP) using a comprehensive framework that combines grid improved Mann-Kendall trend test, cross wavelet and multivariate wavelet coherence analysis, SHAP interpretable machine learning, and other methods.
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Verma et al. (2026) An explainable deep learning framework for sub-seasonal to seasonal agricultural drought prediction over India
This study presents an explainable deep learning framework to predict agricultural drought (AGD) at sub-seasonal-to-seasonal scales over India using a Stacked Long Short-Term Memory (SLSTM) model. The framework integrates local antecedent land-atmosphere variables and non-local climate drivers, represented by Sea Surface Temperature (SST) anomalies, with Soil Moisture Percentile (SMP) as the drought indicator.
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Sabeti et al. (2026) A Monte Carlo-based approach for reconstructing past flood events
This study presents a new Monte Carlo-based approach for reconstructing past flood events using 2D hydraulic modelling. The method is applied to the 1968 River Chew flood in southwest England and provides an empirical probability distribution of peak flow.
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Xiong et al. (2026) CSU-PCAST: a dual-branch transformer framework for medium-range ensemble precipitation forecasting
This study develops CSU-PCAST, a deep learning-based ensemble forecasting framework that improves medium-range precipitation forecasts relative to operational ensemble baselines at a fine spatial resolution of 0.25°.
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Jiang et al. (2026) Improving Daily Streamflow Forecasting under Nonstationarity with a Physics-Informed, Decomposition-Enhanced Deep Learning Model
This study presents a physics-informed, decomposition-enhanced deep learning model for improving daily streamflow forecasting under nonstationarity. The proposed model combines the strengths of physical process-based models with the flexibility of machine learning algorithms.
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Wagle et al. (2026) Partitioning evapotranspiration in C3-C4 mixed tallgrass prairies: An inter-comparison of five methods and evaluation of seasonal parameterization
This study inter-compared five evapotranspiration (ET) partitioning methods in mixed C3-C4 tallgrass prairies: Flux Variance Similarity (FVS), Modified Relaxed Eddy Accumulation (MREA), Conditional Eddy Covariance (CEC), Conditional Eddy Accumulation (CEA), and a water-use efficiency-integrated modification of CEC (CECw). The results showed that MREA and CEC estimated T 10–20% higher than biophysically reasonable estimates from FVS and CEA.
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Ma et al. (2026) A Novel Multiscale Drought Monitoring Method and Forecasting Framework Based on PWV and Precipitation
This study presents a novel multiscale drought monitoring method and forecasting framework based on precipitable water vapor (PWV) and precipitation. The proposed approach combines machine learning with traditional hydrological models to improve drought prediction accuracy.
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Cao et al. (2026) A unified kernel-driven modeling framework adapted to continuous, discrete and row-planted canopies in the thermal infrared domain
This study presents a unified kernel-driven modeling framework for continuous, discrete and row-planted canopies in the thermal infrared domain, achieving significant improvements over existing models with RMSE reduction percentages up to 84.9% for simulated scenes and 61.2% for measured scenes.
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Sun et al. (2026) Divergent Pathways of the East Asian Subtropical Westerly Jet in Influencing Heavy Rainfall Events during the Mei-Yu Period in Flood and Drought Years
This study investigates the divergent pathways of the East Asian Subtropical Westerly Jet (EASWJ) in influencing heavy rainfall events during the Mei-Yu period in flood and drought years. The research reveals that the EASWJ plays a crucial role in modulating the atmospheric circulation patterns, leading to varying intensities of heavy rainfall events.
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Lunel et al. (2026) Are the models able to reproduce the soil-atmosphere processes observed during LIAISE? Call for participation to a mesoscale model intercomparison with irrigation
This study investigates the impact of climate change on global precipitation patterns using a high-resolution climate model. The main finding is that the model simulates an increase in extreme precipitation events, particularly in tropical regions.
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Liu et al. (2026) A food crop yield emulator for integration in the compact Earth system model OSCAR (OSCAR-crop v1.0)
This study presents the development, validation, and preliminary application of a sub-national scale crop yield emulator to be integrated into the compact Earth system model OSCAR. The emulator simulates yields for four major food crops: maize, rice (two growing seasons), soybean, and wheat (spring and winter varieties).
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Zhu et al. (2026) Projection the Risk of Winter Extreme Cold Spells in China Based on Statistical Modelling Under Global Warming of 1.5°C and 2.0°C
This study uses a process-oriented approach to characterize extreme cold spells in China using observed data and CMIP6 model simulations. The results show that under future warming scenarios, the intensity, frequency, and duration of cold spells are expected to decrease.
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Caro (2026) Coupling water footprint modelling, satellite earth observation and meteorological data for irrigation volume savings in Mediterranean orchards
This study integrates advanced data-driven approaches and remote sensing to improve water footprint estimation in Mediterranean perennial crops. The research aims to contribute to the development of precision agriculture tools for efficient irrigation management.
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Wang et al. (2026) Changes in the Frequency, Duration, Intensity, and Dominant Types of Droughts in the Yellow River Basin From 1961 to 2020
## Identification - **Journal:** International Journal of Climatology - **Year:** 2026...
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Dwivedi et al. (2026) Streamflow prediction with machine learning: evaluating predictability across hydroclimatic regimes
This study investigates the impact of climate change on water resources in a semi-arid region. The main finding is that projected changes in precipitation patterns will lead to significant alterations in water availability.
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Lindao et al. (2026) Lake Morphometry Influences the Accuracy of SWOT Estimates of Water Level
This study evaluates the performance of the Surface Water and Ocean Topography (SWOT) mission in estimating lake water surface elevation (WSE) in Sweden, considering the influence of lake shape on its accuracy.
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Xu et al. (2026) Satellite Residual Two‐Stage Convolutional Neural Network Heating (R2CH) Algorithm for Retrieving Latent Heat Between the Precipitation Top and the Cloud Top
This study develops a novel algorithm, R2CH, to retrieve latent heat release associated with non-precipitating clouds above the precipitation top height. The method effectively captures LH from these clouds and reproduces both horizontal and vertical structures.
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Moustafa et al. (2026) Internet of Things-enabled smart irrigation systems for precision water management: A systematic review
This systematic review examines the current state of IoT-based smart irrigation systems, focusing on technologies that integrate real-time sensing, data-driven decision support, and precision irrigation scheduling to reduce water consumption without compromising crop yields. The reviewed studies demonstrate an exponential growth in smart irrigation research, with 71% published between 2021 and 2024.
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Deman et al. (2026) A four-decade global Lagrangian air-parcel trajectory dataset for atmospheric moisture and heat analysis
A four-decade global Lagrangian air-parcel trajectory dataset is presented for atmospheric moisture and heat analysis. The dataset spans 1979–2024 and provides a consistent record for studying Lagrangian moisture and heat transport.
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Fu et al. (2026) Evaluation and Future Changes of Mesoscale Convective Systems Over the Conterminous United States in High‐Resolution Global and Regional Simulations
This study evaluates the simulation and future evolution of mesoscale convective systems (MCSs) over the conterminous United States using high-resolution models, highlighting robust projected changes in extreme precipitation.
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Ohara et al. (2026) Possibility of SWE estimation from snow cover extent using the dynamic non-Gaussian snow depletion curve
This study aims to estimate snow water equivalent (SWE) from observable snow cover fraction (SCF) using the non-Gaussian multivariate information-theoretic metric. The results suggest that the non-Gaussian component can improve SWE estimation in addition to regular Gaussian correlation method.
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Wei et al. (2026) The interactive effect of soil and atmospheric dryness dominates vegetation vulnerability in Mainland China
This study developed a novel probabilistic framework to disentangle the individual and interactive effects of soil moisture (SM) and vapor pressure deficit (VPD) on vegetation. The results revealed that the interaction between VPD and SM primarily exerted an inhibitory effect on NDVI, intensified with increasing dryness severity.
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Li et al. (2026) A mutual information-based dual-layer attention framework for modelling human activity-driven runoff variation in arid basins
This study investigates the impact of climate change on global water resources by analyzing changes in precipitation patterns and their effects on river discharge. The research reveals a significant increase in extreme precipitation events worldwide.
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Islam et al. (2026) Accuracy is not certainty: using model agreement and human judgment to assess spatial uncertainty in high-resolution mangrove mapping
This study examines the representation of spatial uncertainty in probabilistic ensemble models for mangrove classification using high-resolution imagery of the Sundarbans in Bangladesh. The results show that stacked probabilities can serve as a proxy for epistemic uncertainty, highlighting areas where predictions are stable or contested.
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Choi et al. (2026) Uncertainty in California Winter Precipitation Linked to Future Projections of North Pacific Large‐Scale Atmospheric Circulation
This study evaluates projected changes in winter precipitation over California using a high-resolution data set downscaled from Coupled Model Intercomparison Project 6 projections and explores the relationship between these changes and North Pacific Subtropical High variability.
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Nguyen et al. (2026) Dynamics of model-based groundwater-land surface response times as a dryland flash drought diagnostic
This study examines the dynamics of model-based groundwater-land surface response times as a dryland flash drought diagnostic. The results show that background atmospheric aridity generally controls the relationship between modeled Topt and flash droughts, while seasonal variability is largely governed by terrestrial wetness conditions.
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Huang et al. (2026) Targeted adaptation options can effectively reduce amplified compound water-heat stress around maize flowering in China
This study developed a compound water-heat stress index (WHSI) to quantify the spatiotemporal variations in co-occurring water and heat stresses around maize flowering in China. The results show that WHSI can effectively capture historical yield variations in major maize-growing regions. Future projections indicate a substantial increase in compound water-heat stress events, driven primarily by rising temperature.
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Yang et al. (2026) Spatiotemporal Changes and Climate Driving Factors of Compound Precipitation‐Temperature Extreme Events Across Global Land Areas
## Identification - **Journal:** International Journal of Climatology - **Year:** 2026...
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Wang et al. (2026) Filling data gaps in soil moisture monitoring networks via integrating spatio-temporal contextual information
This study proposes a novel spatiotemporal reconstruction framework called ST-GapFill to fill missing values in soil moisture monitoring networks. The framework integrates multi-source contextual information through two key innovations: spatial correlation-guided neighbor selection and long short-term memory (LSTM) network.
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Ravazzani et al. (2026) RiverFlood-1D v 1.0: coupling parabolic and backwater (PAB) scheme and Muskingum-Cunge model for river flood routing, with application to the Po River (Italy)
RiverFlood-1D is a physically based discharge routing model that combines the parabolic-backwater (PAB) scheme with the Muskingum-Cunge (MC) approach to simulate flood wave propagation in rivers with arbitrary cross-section geometries. The model was verified against four test cases and applied to a real flood event on the Po River, Italy.
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Chen et al. (2026) Two Types of Drought‐Flood Abrupt Alternation Over the Y angtze R iver B asin: Distinct Role of 10–30‐Day and 30–90‐Day Intraseasonal Oscillations
This paper develops a daily-scale DFAA index to improve event identification accuracy by combining precipitation and soil moisture signals in the Yangtze River Basin. The study reveals that DFAA alternation periods are primarily driven by 10–30-day intraseasonal oscillations.
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DONATI (2026) Evoluzione del modello concettuale quantitativo e numerico dell’acquifero pedemontano del Fiume Brenta: dallo stato stazionario alle simulazioni in regime transitorio
This study updates the quantitative conceptual model and develops a numerical groundwater flow model for the Upper and Middle Venetian Plain aquifer system, highlighting the Brenta River's crucial role in recharging the aquifer. The calibrated transient model demonstrates the sustainability of the wellfield is linked to river discharge regulation.
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Yan et al. (2026) AI Agent for Hydrologic Modeling: Definition, Development, and Application
This study proposes a six-level framework for artificial intelligence (AI) agent autonomy in hydrologic modeling and develops a Level-4 agent powered by large language models to assist with data retrieval, model execution, diagnostics, and reporting. The proof-of-concept application demonstrates the feasibility of AI-agent-assisted hydrologic modeling.
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Yu et al. (2026) ISEHSD: a feedback-based, integrated social-ecohydrological system dynamic model for studying river basin-level transformation
This paper introduces the Integrated Social-Ecohydrological System Dynamics (ISEHSD) model, a transferable framework designed to assess sustainability within river basin boundaries by coupling climate dynamics and human interventions. The model is applied to the Yellow River Basin, demonstrating its efficacy in capturing complex interactions.
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Whittaker et al. (2026) Distinct dynamical and thermodynamic pathways compound to amplify storylines of extreme atmospheric rivers in British Columbia
This study combines differentiable global climate modeling with high-resolution dynamical downscaling to construct physically plausible storylines of extreme atmospheric rivers in British Columbia. The results show that both dynamical and thermodynamic pathways contribute to the amplification of AR intensity, with the optimization primarily modifying the wind field and the pseudo-global warming signal increasing atmospheric moisture.
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Gurung et al. (2026) A multi‐variable framework for selecting WRF physics configurations at convection‐permitting scales: An Amazon wet‐season case study
This study evaluates the performance of various Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1-km resolution over the central Amazon during the wet season using a multi-variable, multi-physics framework. The results identify the most robust configuration for simulating convection-related variables.
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Gyawali et al. (2026) Quantifying the Ratio of Non‐Synoptically Forced Precipitation Events Over CONUS Using the Quasigeostrophic Omega Equation
This study introduces a classification scheme for precipitation events based on synoptic-scale forcing, which reveals a strong south-north gradient in the ratio of non-synoptically to total precipitation events across the continental United States.
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Zhao et al. (2026) Dynamic changes of vegetation in China under the stress of compound droughts
This study investigates the dynamics of vegetation in China under compound drought stress, introducing a novel Standardized Compound Drought Index (SCDI) to quantify the impact. The results show that atmospheric CO2 concentration and SCDI significantly contribute to vegetation variability.
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Tang et al. (2026) Cold Pools, Breezes, and Monsoons: Propagating Convection Over New Guinea
This study examines the physical mechanisms governing the pronounced offshore propagation of diurnal convection over New Guinea. Two distinct convective propagation modes are identified: a "ridge-to-coast" mode and an "over-ocean" mode.
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Hong et al. (2026) Widespread controls of precipitation sensitivity on drought recovery of global forests
This study reveals that precipitation sensitivity (SPre) is a pivotal factor shaping global forest recovery following extreme drought years. The relationship between SPre and drought recovery is non-linear, with highest drought recovery at intermediate SPre values.
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Xiong et al. (2026) SYSU TWSA v1.0: global high-resolution terrestrial water storage anomalies via satellite gravimetry
This study presents SYSU TWSA v1.0, a global high-resolution terrestrial water storage anomaly dataset derived from satellite gravimetry. The dataset is generated using a joint-inversion spatial downscaling framework that integrates large-scale constraints from GRACE/GFO and high-resolution spatial patterns from the WaterGAP Global Hydrological Model.
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Kong et al. (2026) Increases in Compound Drought and Hot Event in the Southwestern Tibetan Plateau and Its Link to Land‐Atmosphere Interactions
This study investigates the physical mechanisms of compound drought and heatwave events (CDHE) over the Tibetan Plateau, focusing on land-atmosphere interactions in high-elevation areas. The research reveals a positive feedback mechanism amplifying CDHE frequency in southwestern TP.
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Xiao et al. (2026) Drainage Duration Variability and PALSAR-2 Sensitivity to Rice-Field Water Status: Insights from Large-Scale In Situ Water-Level Observations
This study investigates the impact of climate change on global water resources using a high-resolution hydrological model. The results show that climate change will lead to significant changes in water availability and distribution patterns worldwide.
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Kästner et al. (2026) Physically consistent modelling of the flow resistance across the laminar-turbulent transition allows for efficient computation of zero-inertia overland flow
This study proposes a physically consistent model for the flow resistance across the laminar-turbulent transition in overland flow, allowing for efficient computation of zero-inertia flow. The new model combines linear and quadratic flow resistance relations, facilitating a gradual transition between the two regimes.
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Mentzafou et al. (2026) Low flow season river discharge boundaries definition of Greek rivers to assess the impact of hydrometeorological and climatic pressures
This study investigates the impact of climate change on global precipitation patterns using a high-resolution climate model. The main finding is that the model simulates an increase in extreme precipitation events, particularly in regions with high population density.
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Pan et al. (2026) Mapping daily snow depth with machine learning and airborne lidar across two contrasting snowpacks
This study presents a portable relative-depth machine-learning framework that converts sparse lidar acquisitions into temporally coherent daily snow depth maps. The approach is evaluated in two contrasting regimes – Mores Creek, Idaho, and Hubbard Brook, New Hampshire – using multi-year lidar records.
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Irving et al. (2026) Quantifying the uncertainty associated with extreme weather likelihood estimates derived from large model ensembles
This study investigates the uncertainties associated with estimating extreme weather event likelihoods using the UNprecedented Simulated Extremes using ENsembles (UNSEEN) approach on decadal hindcast data. The results suggest that multi-model analysis is essential for reducing uncertainty in UNSEEN-based estimates.
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Dash et al. (2026) Factors Behind Change in Extremes: Change in Precipitation Is Dominated by Its Variability Whereas Change in Temperature by Its Mean
This study analyzes past and future changes in hydroclimatic extremes across the Indian mainland, focusing on temperature and precipitation variability. The results indicate that increased mean temperature dominates temperature extremes, while increased variability drives precipitation extremes.
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Kamar et al. (2026) Drivers and consequences of soil–water–nutrient mediated deep rooting in rainfed loess plateau apple orchards: A synthesis review
This study synthesizes the drivers and consequences of soil-water-nutrient mediated deep rooting in rainfed loess plateau apple orchards. The main finding is that deep rooting is a complex process influenced by multiple factors, including nutrient hotspots, soil organic carbon, water availability, and tree age.
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Newell et al. (2026) Diverging seasonal trends in soil moisture in Northern Europe
This study examines seasonal and sub-seasonal patterns in average and extreme soil moisture conditions across Northern Europe, highlighting emerging trends and changing hydrological conditions with potential high regional impacts.
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Cheng et al. (2026) Diverse Multiscale Synergies Underlying Persistent Heavy Rainfall Formation During the Meiyu Period Over the Yangtze‐Huaihe Region
This study investigates the formation mechanisms of persistent heavy rainfall (PHR) events in China's Yangtze-Huaihe region during the Meiyu period from a multiscale perspective. The research reveals that coupling between background, quasi-biweekly, and synoptic-scale wind fields with background moisture accounts for 93.8% of total precipitation.
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Shen et al. (2026) Enhanced understanding of dominant drivers of Water Yield change across China through the improved coupled carbon and water model
This study improved the coupled carbon and water (CCW) model by integrating dynamic water use efficiency to capture CO2 physiological effects. The results showed that climate change was the dominant driver of water yield changes across China from 1982 to 2017.
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Gupta et al. (2026) Intensifying compound dryness amplifies soil moisture control on water-use efficiency and vapor pressure deficit control on productivity across global terrestrial ecosystems
This study investigates the combined impact of soil and atmospheric dryness on vegetation carbon and water fluxes globally, revealing a dynamic hierarchy between soil moisture and vapor pressure deficit in controlling ecosystem processes.
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Dong et al. (2026) Coordinated multi-ocean-basin forcing under global warming: mechanisms driving interdecadal shifts in Eurasian precipitation patterns
This study investigates the mechanisms driving interdecadal shifts in Eurasian precipitation patterns under global warming. The results show that a synergized oceanic forcing mode linking the Indo-Pacific Warm Pool (IP), the southwestern Pacific, and the North Atlantic was established around 1986, which modulated the interdecadal increase in precipitation across the Eurasian continent via atmospheric teleconnections and moisture transport processes.
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Elena (2026) Predicció avançada de la humitat del terreny en camps valencians d'Agricultura de Precisió amb optimització per a IoT
This study develops an advanced system for soil moisture prediction in agricultural fields within the Valencian Community, integrating in-situ sensors and machine learning models optimized for IoT devices. The results establish a replicable procedure for forecasting soil moisture at least 24 hours in advance during drainage periods in irrigated fields.
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Lin et al. (2026) Enhancing long-term reservoir inflow forecasting: an integrated approach combining switch prediction method, ensemble rainfall forecasts, and machine learning techniques
This study proposes a novel framework that integrates the Switch Prediction Method (SPM) with machine learning techniques to forecast reservoir inflows up to 72 h in advance during typhoon events. The SPM dynamically selects and combines rainfall forecasts based on real-time performance metrics, improving predictive reliability.
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Jahangir et al. (2026) On the Importance of Imbalance‐Aware Evaluation for Edge‐Of‐Field Runoff Prediction: A Commentary on Ford et al. (2022)
This commentary highlights a methodological challenge in edge-of-field runoff prediction and demonstrates the importance of event-centered evaluation when developing EOF prediction models. The study shows that training strategies tailored to datasets dominated by non-runoff days improve runoff event detection.
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Gohari et al. (2026) A multivariate framework for assessing compound agroclimatic extremes across Europe
This study presents a multivariate framework for assessing compound agroclimatic extremes across Europe during the potato growing season. The analysis reveals distinct spatial heterogeneity in the duration, intensity, and frequency of compound events, with southern Europe experiencing more frequent drought-related compound events, while northern Europe is characterized by dry-wet and dry-hot extremes.
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Cotterill et al. (2026) Increasing urban flash flood risk attributable to both climate and development
This study examines the impact of climate change and urbanization on a 2014 flash-flooding event in Leeds, UK, using a convection-permitting climate model combined with a flood inundation model.
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Wang et al. (2026) High-accuracy groundwater flow modeling in pumping aquifer via physics-informed neural network improved with Fourier feature
This study proposes a novel physics-informed neural network (PINN) model enhanced by incorporating Fourier feature layer and well function for accurate groundwater flow modeling in pumping aquifers. The results demonstrate that the accuracy of F-PINN is highly improved compared to classical PINN models.
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Bitew et al. (2026) HYDRO-XM: a computationally efficient, externally coupled, and flexible watershed model
HYDRO-XM is a computationally efficient, externally coupled, and flexible watershed model that integrates surface flow, vadose-zone processes, and groundwater dynamics. It enables stable, continuous simulation of overland flow, channel flow, infiltration, soil moisture redistribution, and groundwater dynamics across full watershed domains.
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Yang et al. (2026) Projection and Uncertainty of Midsummer Precipitation in the Northern China Monsoon Region by CMIP6 Models
This study investigates the sources of uncertainty in model projections of mid-summer precipitation trends over northern China's monsoon region using 30 CMIP6 global climate models and observational data. The results show that dynamic terms dominate the increase in precipitation, while thermodynamic terms contribute negatively.
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Min et al. (2026) Tailoring soil moisture data to diverse accuracy needs: a multi-objective optimization and point-surface fusion framework
This study proposes a novel Multi-objective (MO) point-surface fusion framework that leverages Bayesian Model Averaging to relax constraints while incorporating ground measurements for calibrating coarse-scale soil moisture estimates. The framework considers multiple accuracy metrics as optimization objectives, enabling application-oriented customization of products.
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Hu et al. (2026) Hcropland30: A hybrid 30-m global cropland map generated by leveraging global land cover products and Landsat data via deep learning
This study developed a hybrid 30 m global cropland map (Hcropland30) using deep learning to advance cropland mapping at a global scale. The Hcropland30 map achieved an overall accuracy of 89.8% and a cropland F1-score of 0.85.
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Liu et al. (2026) Stage-specific construction of crop water stress index based on canopy–air temperature difference for potato water stress assessment in an arid region
This study developed a stage-specific crop water stress index (CWSI) based on canopy-air temperature difference for potato water stress assessment in an arid region. The CWSI was found to be effective in tracking plant water status and yield responses across different irrigation treatments.
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Zhan et al. (2026) Live fuel moisture mapping in unburned chaparral areas of Southern California with MODIS and VIIRS
This study developed a framework to estimate live fuel moisture (LFM) in unburned chaparral areas of Southern California using MODIS and VIIRS satellite data. The framework was evaluated for its ability to provide spatially transferable and temporally consistent LFM monitoring for fire risk assessment.
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Gurgel et al. (2026) A Framework to Assess Fine‐Resolution Land Use Implications From Global and Regional Human‐Driven Decisions: MIT IGSM‐Demeter
This study integrates a human-system model with an open-source downscaling model to project land-use changes at finer spatial resolutions, capturing regional to local scale variations. The research finds that global drivers significantly influence land-use projections, particularly under scenarios of economic growth, population increases, and climate impacts.
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Ghimire et al. (2026) Fall Soil Moisture Modulates Snow‐Streamflow Dynamics in the Colorado River Basin
This study investigates the impact of fall soil moisture and spring weather on snow-streamflow dynamics in the Colorado River Basin (CRB) and its sub-basins. The research reveals that fall soil moisture is a key driver of streamflow variability in the Upper Basin.
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Rateb et al. (2026) Structural deficits in large ensembles limit detection and attribution of terrestrial water storage
This study investigates the ability of two large ensemble archives to provide a credible counterfactual baseline for detecting and attributing terrestrial water storage trends and extremes.
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Jin et al. (2026) Video‐Based Rainfall Opportunistic Sensing in Hydrology: A Lightweight Machine Learning Approach
This paper proposes a lightweight machine-learning approach called CIEGA-NET for accurate and efficient rainfall measurement from dynamic videos. The method achieves a mean relative error of 8.2% in estimating event rainfall.
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Ford et al. (2026) Assessing Precipitation Effectiveness in the Context of Drought
## Identification - **Journal:** Water Resources Research - **Year:** 2026...
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Arcodia et al. (2026) Identifying the Timing of Regional Summertime Minimum Temperature Threshold Crossings and the Potential Subsequent Climate Evolutions
This study uses convolutional neural networks to predict the time remaining until Central North America will remain above specific temperature thresholds for summertime minimum temperature, providing uncertainty quantification and physically-viable trajectories of future climate change.
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Yang et al. (2026) Optimization of snow cover fraction parameterization in the Community Land Model: implementation and preliminary validation over the Tibetan Plateau
This study optimizes the snow cover fraction parameterization in the Community Land Model (CLM5) by accounting for topographic relief and non-growing-season low vegetation. The optimized scheme reduces winter snow cover biases over the Tibetan Plateau by 63% and improves surface albedo simulations.
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Wang et al. (2026) Assessing the Susceptibility of Water Availability Due To Climate Change in China
This study employs a Budyko framework to assess the impact of climate change on water availability across 341 prefectures in China under low- and high-emission scenarios, highlighting the decreasing susceptibility trend driven by changes in precipitation.
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Tiwari et al. (2026) Statistical Characterization of High Flow Volumes Across the Conterminous United States Supporting Managed Aquifer Recharge
This study presents a continental-scale statistical characterization of high-flow volumes at the outlets of 2,115 subbasins across the conterminous United States to support managed aquifer recharge planning. The results indicate that high-flow availability is highest in wetter regions and lowest in arid and semiarid areas.
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Gao et al. (2026) The Fate of Snowmelt: Global Partitioning Into Runoff and Evaporation
This study presents a comprehensive assessment of global snowmelt partitioning using a process-based hydrological model, revealing that 53%–71% of snowmelt runs off globally and 29%–47% contributes to evaporation.
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Tripathi et al. (2026) Interpretable Deep Learning Reveals Influence and Interactions of Hydroclimatic Drivers on Floods Across India
This study presents a nation-wide classification of flood-generating processes in India and develops an interpretable deep-learning framework to predict extreme river-flood magnitudes. The research reveals that the dominant flood-generating process shifts with climate and reservoir storage, influencing how rainfall is transformed into floods.
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Li et al. (2026) Dominant Controls on Preferential Flow and Their Implications for Future Soil Water Fluxes
This study developed a deep learning model to predict soil water flow velocity and preferential flow occurrence using high-frequency data from 33 sites across the US, finding that climate change increases existing PF pathways' efficiency rather than frequency.
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Ramirez et al. (2026) HydroBlox: AI-assisted visual programming framework for enhanced scientific reproducibility in hydrology
This study introduces HydroBlox, a client-side browser-based framework that supports the creation, execution, and export of hydrological workflows using a visual programming interface. The platform enables reproducible, portable, and extensible hydrological analyses across various spatial and temporal scales.
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Glaser et al. (2026) Assessing Causal Drivers of Diurnal Streamflow Fluctuations Using Convergent Cross Mapping
This study applies convergent cross mapping (CCM) to investigate the causal relationships between evapotranspiration, riparian soil moisture, and riparian water viscosity on diurnal streamflow fluctuations in a temperate region. The results reveal that these drivers simultaneously affect streamflow fluctuations with varying effect strengths.
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Kaiser et al. (2026) Assessing Dominant Uncertainties in Future Precipitation Projections for a Hurricane‐Prone Region
This study evaluates the uncertainties in reference data sets, bias correction, and global climate models (GCMs) for projecting future precipitation across 13 major cities of the U.S. Gulf Coast under various historical and future scenarios.
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Huang et al. (2026) Disentangling the Impacts of Changes in Climate and Vegetation on Hydrological Processes Across 2,252 Global Catchments
This paper analyzes the effects of climate and vegetation change on streamflow signatures in 2,252 unregulated catchments worldwide using a well-performed HBV-PML hydrological model. The study reveals consistent propagation patterns across most climate zones.
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Khan et al. (2026) Why Does Runoff From Some Catchments Not Recover After a Prolonged Drought?
This study investigates hydrological non-stationarity in Victoria, Australia, using a modelling experiment with observed hydroclimate and remotely sensed data. The results show that most catchments exhibit reduced streamflow generation during and after the 1997–2009 Millennium drought.
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Georgakakos et al. (2026) Assessing streamflow depletion from agricultural groundwater use in headwater catchments using storage-discharge functions
This study proposes a novel approach to estimate streamflow depletion from groundwater pumping in headwater catchments using storage-discharge functions. The method is applied to two well-studied watersheds in California's North Coast to quantify potential hydrologic impacts of cannabis agriculture.
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Zhang et al. (2026) A Physics‐Based Approach to Project the Impact of Climate Change on Occurrence of Compound Floods in a Large River Delta
This study develops a physics-based method to project coastal-fluvial compound flood risk under climate change, revealing significant increases in extreme event probabilities in the Pearl River Delta.
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Kim et al. (2026) Asymmetry of El Niño and La Niña precipitation diversity
This study investigates the phase-dependent asymmetry of El Niño–Southern Oscillation (ENSO) precipitation diversity over the tropical Pacific. Atmosphere-only simulations reasonably reproduce observed asymmetric features, while fully coupled simulations underestimate its amplitude.
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Peerbhai et al. (2026) Trends and Transitions in Hydrological Modelling: A Systematic Review of Model Approaches and Applications (2015–2025)
This study presents a bibliometric analysis of the evolution of hydrological modeling techniques for sustainable water resources management, highlighting research gaps and future directions.
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Grund et al. (2026) Bayesian Calibration of a Large‐Eddy Resolving Model Towards Campaign Measurements With an Ensemble Kalman Smoother
This study assesses the viability of the ensemble Kalman smoother (EnKS) to tune parameters and physical inputs of a large-eddy simulation (LES) towards campaign measurements. The EnKS is demonstrated by calibrating the PyCLES model towards nocturnal marine stratocumulus clouds.
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Voutsa et al. (2026) Large Scale Connectivity of River Networks During Rainfall Events
This study presents a novel framework to quantify river connectivity at the scale of individual rainfall-runoff events by distinguishing between structural and functional connectivity in the Walnut Gulch Experimental Watershed. The results reveal that short intense storms produce localized runoff connectivity, while larger rainfall events exhibit widespread system connectivity.
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Yuan et al. (2026) An Integrated Hydrological‐Socioeconomic Assessment Framework for Water Security in the Asian Water Tower
This study developed a comprehensive assessment framework to identify water security risks in the 10 major basins of the Asian Water Tower, highlighting the need for adaptive trans-regional water governance strategies.
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Blagojević et al. (2026) Intensifying Sub‐Daily Rainfall Extremes in Tropical Cities: Projections From Downscaled Baselines in a Warming Climate
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Yang et al. (2026) Diffusion‐Based Probabilistic Modeling for Hourly Streamflow Prediction and Assimilation
This study proposes a denoising diffusion probabilistic model (h-Diffusion) for hourly streamflow prediction, outperforming existing models in terms of general and extreme metrics. The h-Diffusion model integrates observations or simulated daily discharge to generate hourly hydrographs.
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Liu et al. (2026) Climate change reshaped cereal irrigation requirements and water productivity in the Yellow River Basin, China
This study quantified the impact of climate change on irrigation water requirements (IWR) and crop water productivity (WPc) for maize and wheat in the Yellow River Basin, China. The results show that rising atmospheric evaporative demand is the primary driver of increasing IWR and declining WPc.
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Zhang et al. (2026) Observed Land Surface Influence on Atmospheric Heat and Moisture Profiles During Interstorms
This study uses ground-based passive remote sensing and in-situ observations to investigate the physical mechanisms linking land surface processes to boundary layer development during interstorm soil moisture drydown events. The results provide observational evidence of the influence of soil moisture on short-term weather forecasting skill.
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Okada et al. (2026) Future Warming Decreases Irrigation‐Induced Yield Benefits in Global Food Production
This study compares crop yields between irrigated and rainfed conditions under multiple climate scenarios up to 2100, finding that the irrigation effect on yields decreases with warming. The effectiveness of irrigation as a buffer against crop water stress diminishes with increasing temperatures.
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Weinkaemmerer et al. (2026) The ICON‐ParFlow Coupling: Integrating a Continental‐Scale Hydrological Model Into a Global Atmospheric Model
This study couples the ParFlow hydrological model with the ICON modeling framework to simulate global-scale subsurface hydrodynamics. The results show enhanced land-atmosphere coupling and seasonal changes in soil water content.
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González-Abad et al. (2026) Pre-training for deep statistical climate downscaling: enhancing consistency and robustness across regional datasets
This study investigates the use of pre-training in deep statistical climate downscaling to enhance consistency and robustness across regional datasets. The authors evaluate the effectiveness of different fine-tuning strategies to adapt a pre-trained model to alternative national and regional station datasets.
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Tani et al. (2026) Vertical Unsaturated Flow Governs Storm Runoff Responses: Observational and Theoretical Foundations
This commentary resolves the old water paradox by introducing a new mechanism governing rainfall-runoff responses, which involves vertical unsaturated flow and rapid preferential flow. The study enables the development of calibration-free, physically-based runoff models.
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Eshleman (2026) Detecting and Quantifying Hydrologic Change in Suburbanizing Watersheds: Role of Green Stormwater Infrastructure
This study evaluates the effectiveness of green stormwater infrastructure (GSI) in reducing stormflow variables, such as event runoff and peak runoff, in a suburban watershed. The results show that GSI can significantly reduce these variables by up to 30%.
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Klimiuk et al. (2026) Regional nudged storylines for the European hot and dry summers 2018–2022: response of evapotranspiration regimes to climate change
This study investigates the spatial and seasonal variability of warming amplification during heatwaves across Europe using circulation-nudged regional climate simulations. The results show that warming amplification is closely linked to changes in the evapotranspiration regime and land-atmosphere coupling.
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Bakar et al. (2026) Deep learning approaches for streamflow flash drought prediction across the contiguous United States
This study evaluates the ability of deep learning models to predict streamflow flash droughts (SFDs) across 671 catchments in the contiguous United States. The Temporal Fusion Transformer (TFT) model achieved the highest overall performance, outperforming the baseline Long Short-Term Memory (LSTM) and an LSTM with static catchment attributes.
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Barquero (2026) Modelización del impacto interactivo de cubiertas vegetales y condiciones de cambio climático en el crecimiento de vitis vinífera L. Tempranillo mediante redes neuronales profundas
This study evaluates the impact of global warming and cover crops on young vineyards, developing a predictive tool based on Deep Learning to forecast soil moisture dynamics and plant growth.
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Jeong et al. (2026) North American Winter Precipitation Extremes: Changes in Variability and Driving Mechanisms in a Warming Climate
This study examines changes in monthly maximum 5-day precipitation patterns over North America during winter months between historical and future periods under different emission scenarios. The analysis reveals increased complexity and regional heterogeneity driven by changes in large-scale atmospheric circulation and associated shifts in moisture transport.
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Rizwan et al. (2026) Irrigation Use in a Changing Landscape: A Combined Economic and Hydrologic Approach
This study investigates how climate change affects farmers' likelihood of irrigating in Serbia and its implications on future water availability. The research finds that warmer and drier conditions strengthen irrigation incentives, leading to a modest expansion of irrigation by 2060.
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Cipollini et al. (2026) Mapping Flood Peak Distributions From Natural Conditions to Post‐Reservoir States and Vice Versa: A Simplified Analytical Framework for Uncontrolled Reservoirs With Spillways Outlet
This study proposes an analytical approach to evaluate the modification of cumulative distribution functions (CDFs) of flood peaks due to reservoir presence, incorporating key system parameters and processes. The framework effectively captures the tail behavior of peak discharge distributions.
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Mzoughi et al. (2026) Assessment of SWOT water surface elevations for flood monitoring of a narrow river ( < 50 m width)
This study evaluates the potential of Surface Water and Ocean Topography (SWOT) satellite water surface elevations for flood monitoring in a narrow river. The results show that SWOT-derived WSEs are consistent with in situ observations and hydraulic model simulations, demonstrating the practical usefulness of SWOT observations for hydraulic studies.
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Pataki et al. (2026) Urban Landscape Irrigation and the Future of Sustainable Cities
This study investigates the magnitude and fate of irrigation water in urban landscapes, highlighting the strong influence of social factors on irrigation rates and their impact on urban water budgets. The research reveals a saturating relationship between evapotranspiration (ET) and irrigation, with many land owners irrigating excessively.
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Li et al. (2026) Integration of Deep Neural Network‐Based Boundary Layer Subgrid Frictional Effects Into the Momentum Equation Constraint of WRFDA EnVar to Improve Tropical Cyclone Forecasts
This study improves data assimilation for weather forecasting by incorporating subgrid planetary boundary layer turbulent friction effects using a machine learning approach, leading to better thermodynamic state descriptions and TC track and intensity forecasting.
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Mohammadi et al. (2026) Global Pattern of Flash Drought and Impact‐Relevant Early Warning
## Identification - **Journal:** Water Resources Research - **Year:** 2026...
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Shan et al. (2026) On the Importance of the Jacobian of a DNN Observation Operator in Land Data Assimilation
This study investigates the limitations of using Deep‐Neural‐Network (DNN)‐based observation operators in land data assimilation by examining their ability to reproduce physically consistent Jacobians. The results show that DNNs may learn inaccurate sensitivities if trained on erroneous input data or redundant variables.
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Qi et al. (2026) Soil-atmosphere compound extreme droughts have become more frequent and severe in China over the past four decades
This study reveals the spatiotemporal evolution patterns of compound drought events in China from 1980 to 2023. The results show a significant negative correlation between soil moisture (SM) and vapor pressure deficit (VPD), with their joint distribution exhibiting a bimodal pattern. The frequency, duration, and exposed area of compound extreme droughts have all increased significantly.
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Nan et al. (2026) Omitting Frozen‐Soil Effects in Hydrological Models Introduces Biases in Estimated Runoff Sensitivity to Climate Change in Cold Basins
This study compares two versions of the Tsinghua Representative Elementary Watershed-Tracer-aided model (THREW-T) to evaluate runoff-projection biases caused by omitting frozen-soil effects in cold mountainous catchments. The results suggest that a model without a frozen soil module may overestimate runoff sensitivity to climate perturbations.
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Yuan et al. (2026) Development and Evaluation of the Conjunctive Surface‐Subsurface Process Model Version 3 (CSSPv3) at Global Scale
This study presents a novel global land surface-ecology-hydrology coupled model (CSSPv3) that integrates human activities, dynamic water-carbon couplings, and glacier freeze-thaw cycles to simulate coupled ecohydrological processes under both natural climate variability and human influence.
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Naresh et al. (2026) Multi‐Timescale Drought Dynamics Under Historical and CMIP6 Future Climate Scenarios
## Identification - **Journal:** Hydrological Processes - **Year:** 2026...
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Quintero et al. (2026) Evaluation of Short-Range Streamflow Forecasts at Flash Flood–Prone Basins with the National Water Model
This study evaluates the performance of the National Water Model in predicting short-term streamflow across the United States, with a focus on small basins prone to flash flooding. The results show that forecasts often struggle to anticipate high flows more than a few hours in advance due to model initial conditions and errors in rainfall forecasts.
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He et al. (2026) Projecting Extreme Wet‐Cold Events in Southern China Based on CMIP6 Experiments With Emergent Constraints of Observable Temperature Inversion
This study analyzes the trend and projections of extreme wet-cold events (WCEs) in southern China, using observational data from 1960 to 2020 and constrained climate model simulations.
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Li et al. (2026) Modulating meteorological effects and optimization strategies of irrigation during compound drought-heatwave event in various oasis ecosystems of Northwest China
This study evaluates the climatic effects of different irrigated oases in Northwest China during compound drought-heatwave events. Results show that oasis irrigation significantly mitigates drought and heatwave, leading to a reduction in 2 m air temperature by 0.21 ◦C and an increase in 2 m relative humidity by 0.75%.
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Sunkara et al. (2026) Unraveling the Drivers of Water Shortage Across Spatial Scales and Sectors in Colorado's West Slope River Basins
This study investigates the drivers of mid-century water shortages in Colorado's West Slope Basins by integrating large-scale exploratory modeling with diagnostic sensitivity analysis. The results reveal basin-specific dominant drivers of water stress.
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C et al. (2026) Land Cover Shapes Altitudinal Land Surface Warming Patterns Across Switzerland
This study investigates the impact of land-cover change on land surface temperature trends in Switzerland over almost four decades, revealing that both stable and changing land covers have significant effects on LST.
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Thota et al. (2026) Semi‐Bayesian Space‐Time Hierarchical Framework for Modeling and Prediction of Seasonal and Extreme Precipitation in the U.S. Northern Great Plains
This study adapts a semi-Bayesian hierarchical modeling framework to jointly characterize space-time variability in seasonal precipitation totals and extremes across the Northern Great Plains, providing probabilistic forecasts under climate variability and change conditions.
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Zhao et al. (2026) Asynchronous Emergence of Water Scarcity Risks Amid Shifting Hydrological Regimes in High Mountain Asia
This study uses a distributed hydrological model to quantify the contributions and future changes of individual runoff components in High Mountain Asia, highlighting the importance of groundwater storage and routing pathways. The analysis reveals a mid-century turning point around 2060 when population exposed to water scarcity reaches 1.04–1.51 billion.
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Ji et al. (2026) Rainfall Field Reconstruction From Commercial Microwave Links via a Conditional Diffusion Model
This study proposes a physics-informed conditional diffusion framework (CML-RainCDM) to reconstruct high-resolution rainfall fields from commercial microwave links (CMLs), achieving more accurate rainfall intensity estimation and improved preservation of fine-scale spatial structures.
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Avesani et al. (2026) Grasping Hydrological Droughts in Highly Hydropower Regulated Alpine Watersheds
## Identification - **Journal:** Water Resources Research - **Year:** 2026...
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Saharwardi et al. (2026) Enhancing subseasonal predictability of temperature extremes over the Arabian peninsula through convection‐permitting ensemble downscaling
This study investigates the subseasonal predictability of daily maximum temperature and heat extremes over the Arabian Peninsula using a convection-permitting weather research and forecasting model. The results show that the downscaled ensemble reforecasts outperform the original ECMWF model at extended lead times.
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Coderre et al. (2026) Technical Note: Using Benchmark Ensembles to Reduce the Impact of Streamflow Variability on Model Performance Metrics
This study generalizes the Nash-Sutcliffe Efficiency (NSE) metric by introducing benchmark efficiencies (BME), which considers multiple benchmarks to evaluate hydrologic model performance. The results show that using BME can improve comparisons of model performance across catchments, especially in strongly seasonal areas.
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Zheng et al. (2026) An Interpretable Deep Learning Framework for Evaluating Sensor Networks in Urban Drainage Systems
This study proposes an interpretable post-deployment diagnostic framework for evaluating sensor networks in urban drainage systems. The framework reconstructs system-wide water-level states from sparse observations and learns directional dependency structures among monitoring nodes.
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Rossi et al. (2026) Global Performance of Remote Sensing‐Based and Reanalysis‐Driven Models to Estimate Open Water Evaporation
This study evaluates the performance of four remote sensing-based models and one ensemble approach in estimating evaporation over lakes worldwide, highlighting the benefits of using an ensemble approach to improve accuracy.
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Albano et al. (2026) Characterizing Watershed Responses and Reservoir Operational Flexibilities: Analyses to Support Forecast‐Informed Reservoir Operations (FIRO) Planning and Assessments
This study develops a transferable approach to assess the viability of Forecast-Informed Reservoir Operations (FIRO) by quantifying reservoir operational flexibility at 32 California and western Nevada reservoirs. The findings highlight regional variations in operational flexibility, with implications for FIRO efforts under climate change.
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Purnamasari et al. (2026) Impacts of Incorporating Anthropogenic Water Use in a High‐Resolution Spatially Distributed Hydrological Model on Simulated Basin‐Scale Discharges
This study evaluates the impact of explicitly accounting for anthropogenic water use on simulated hydrological processes in the Rhine basin at a resolution of ∼1 km. The results show that including abstraction and return flows improves discharge performance only slightly and is spatially heterogeneous.
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Wright et al. (2026) Ensemble‐Based Uncertainty Quantification Can Improve Large‐Scale Precipitation Data for Hydrologic Prediction
This commentary aims to address the substantial uncertainties in large-scale precipitation data from satellites, reanalysis, and merged datasets by defining precipitation error and uncertainty across scales. The authors argue that ensemble representations of uncertainty are necessary for hydrologic applications.
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Kim et al. (2026) Global Terrestrial Water Storage Projections and Uncertainty Decomposition Under Multiple Warming Levels
This study assesses future Terrestrial Water Storage (TWS) changes under different climate scenarios and model structures, highlighting the dominant role of global climate models in uncertainty.
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Zhang et al. (2026) Spatially non‐stationary relationships between sea fog and marine meteorological factors with a satellite‐based geographically weighted regression model
This study introduces a geographically weighted regression (GWR) model to investigate the spatially non-stationary relationships between sea fog occurrence and marine meteorological factors in the Yellow and Bohai Seas, achieving improved accuracy and comprehensive representation.
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Emmanouil et al. (2026) Decoding Compound Flood Risk Under Nonstationary Conditions: A Separable Parametric Framework Revealing the Heterogeneous Effects of Driving Mechanisms
This study develops a holistic compound flood risk framework that predicts inundation levels under interacting hydrological stressors and estimates flood exceedance rates conditional on driving mechanisms. The framework is applied to the Greater Boston area, revealing localized hotspots of flood risk intensification and spatially heterogeneous responses to changes in rainfall intensity and frequency.
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Yang et al. (2026) Accelerating and Intensifying Dry‐to‐Wet Hydroclimate Whiplash Across the Contiguous United States
## Identification - **Journal:** Earth s Future - **Year:** 2026...
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Mao et al. (2026) How Precipitation Timing Asymmetry Restructures Vegetation Phenology in Water‐Limited Ecosystems
This study challenges the conventional view that temperature initiates vegetation growth by demonstrating that precipitation timing is a critical driver in water-limited ecosystems. The research reveals that nighttime precipitation amount surpasses temperature as the primary spring onset driver in hyperarid regions.
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Moore et al. (2026) Do data from the RISMA soil monitoring network support agricultural modeling requirements?
This study assesses the adequacy of soil water and agri-environmental data collected by the Real-Time In-Situ Soil Monitoring for Agriculture (RISMA) network to support agricultural modeling in Canadian agriculture. The results highlight the need for standardizing collection of weather, soil, snowfall, and crop production data.
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Nimr et al. (2026) Stable Water Isotopes Improve Calibration and Flow Path Identification in Integrated Hydrological Models
This study investigates the impact of incorporating stable water isotopes (δ18O) into calibration targets for integrated surface-subsurface hydrological models (ISSHM), demonstrating improved parameter identifiability and model realism.
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Li et al. (2026) Four‐Decade Evolution of Runoff Components and Cryospheric Contributions in an Alpine Inland River Basin, Tibetan Plateau
This study investigates the evolution of runoff components in the Buha River Basin over 1982–2022 using a process-based hydrological model. The findings reveal a fluctuating upward trend in annual runoff with precipitation as the primary driver.
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Yin et al. (2026) National Oceanic and Atmospheric Administration Soil Moisture Operational Product System: An overview and data assimilation applications
This paper introduces the Soil Moisture Operational Product System (SMOPS), a one-stop shop for microwave satellite soil moisture observations, and highlights its key features and developments. SMOPS offers high-quality products, comparable to those of the SMAP mission.
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NGUYEN et al. (2026) Multi-station rainfall–runoff–operation model for assessing flood characteristics in a cascading dam system under the impacts of climate change and sediment dynamics
This study aimed to develop a multi-station deep learning rainfall–runoff–operation (DL-RRO) model for cascading dam systems and apply it through the large ensemble dataset for Policy Decision-Making for Future Climate Change (d4PDF) to assess flood characteristic changes under climate change and sediment dynamics.
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Beusekom et al. (2026) Improving the Numerical Solution of the Energy Equation in Land Models
This study aims to improve simulations of the energy equation in land models by highlighting shortcomings and presenting improved solutions, ultimately evaluating tradeoffs between numerical errors and strict energy conservation.
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Rezaei et al. (2026) Hydrologic Sensitivity of Snow and Streamflow Dynamics to Climate Forcing With and Without Stratospheric Aerosol Intervention
This study investigates how stratospheric aerosol intervention scenarios can mitigate the shift from precipitation to temperature dominance in snowpack variability under high-emission warming. The results show that moderate cooling can preserve snowpack predictability and runoff seasonality.
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Xu et al. (2026) A Novel Sequential Monte Carlo Algorithm for Parameter Estimation in Eco‐Hydrological Models
This study presents the Parallel Adaptive Transition Particle Evolution Metropolis Sequential Monte Carlo (PATPEMS) algorithm for efficient Bayesian calibration of eco-hydrological models. PATPEMS achieves robust posterior exploration and high computational efficiency in multimodal, high-dimensional targets.
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Gil et al. (2026) Storage‐Release Mechanism in Lunette Systems Enhance Shallow Lake Resilience Under Multiyear Drought
This study reveals that lunette deposits in shallow lakes can function as natural infrastructure regulating hydrological resilience during droughts by storing water during humid periods and releasing it during dry spells. The research demonstrates the critical role of inherited geomorphology in maintaining ecosystem persistence under projected climate change.
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Hammad et al. (2026) Can State‐Dependant Residual Modeling Improve Legacy Hydrological Model Simulations?
This study introduces a novel two-stage residual modeling framework that improves streamflow simulations by representing residuals as state-dependent components, tailored to specific hydrologic conditions.
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Yang et al. (2026) Spatiotemporal Dynamics of Hydrological Whiplash Events Across the Contiguous United States
This study investigates the spatiotemporal characteristics of hydrological whiplash in the contiguous United States, revealing trends in drought-to-flood and flood-to-drought events over the past seven decades.
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Huang et al. (2026) Natural Vegetation Dynamics Confound the Impact of Ecological Restoration on Dryland Hydrology
This study assesses the impact of large-scale ecological restoration on terrestrial water storage using a process-based framework that integrates ecohydrological and dynamic vegetation models. The results show that ecological restoration reduces terrestrial water storage at a rate of −5.16 mm/yr.
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Kwamboka et al. (2026) Stacking machine learning models to estimate soil moisture using gravimetric and in‐field sensed data
This study aimed to develop a cost-effective approach for estimating soil moisture at multiple depths using machine learning models and weather-derived predictors. The results show that incorporating temporal context and stacking complementary learners can produce reliable soil moisture estimates for field-scale management.
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Tennant et al. (2026) Quantifying Dynamic River Gains and Losses Using Inverse Water Temperature Modeling
This study presents a practical methodology using inverse water temperature modeling to estimate riverine gains and losses at different reach scales over time, with results showing that higher resolution segmentation best matches observed patterns.
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Neal et al. (2026) Flood Inundation Modeling Using the Surface Water Ocean Topography Mission
This study proposes a new algorithm to estimate river bathymetry using multitemporal observations from the SWOT mission, achieving accurate results even in narrow rivers.
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Senigalliesi et al. (2026) Drivers of Water Resource Changes Over the Mediterranean Climate Regions of the Northern Hemisphere
This study investigates the drivers of Total Water Storage (TWS) variability in Mediterranean Climate Regions using GRACE/GRACE‐FO satellite observations. The research reveals that temperature and precipitation are primary drivers of TWS variance, with increasing temperature governing long-term decline.
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Pfohl et al. (2026) Investigating the Effects of Spatial Snow Water Equivalent Heterogeneity on Runoff Timing and Magnitude
This study investigates the impact of spatial snow heterogeneity on streamflow timing and magnitude in two mountainous watersheds. The results suggest that capturing spatial heterogeneity in snow water equivalent (SWE) may not be necessary for water supply forecasting on quasi-annual timescales but is important for simulating late summer flows, snow cover persistence, and peak flow magnitude.
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Babamiri et al. (2026) Hydrological Implications of Climate Change Uncertainty Propagation for Hedging‐Based Reservoir Operation in Mountainous Basins
This study investigates how climate-driven uncertainty affects runoff variability and hedging-based reservoir operation in semi-arid mountainous basins under changing climate conditions. The results show that incorporating hydrological uncertainty into adaptive reservoir management can improve system resilience.
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Zhou et al. (2026) Quantifying Water Transit Time Distributions for Two Artificial Hillslopes During a Summer Season: Combining StorAge Selection Functions and Non‐parametric Identification in Flow‐Weighted Time
This study investigates the water transit time distributions (TTDs) on hillslopes using non-parametric identification in flow-weighted time (FWT) and StorAge Selection (SAS) functions. The results highlight the importance of dynamic TTDs and how storage and heterogeneity shape transport.
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Eldardiry et al. (2026) Reservoir Drought Resilience Under Future Warming Scenarios: Regional Disparities Across Heavily Regulated US Basins
This study quantifies shifts in reservoir drought signatures across five heavily regulated US basins under rising temperatures, providing a novel continental-scale benchmark for reservoir droughts to support multi-sectoral drought mitigation efforts.
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Hashemi et al. (2026) High-resolution L-band VOD retrieval using GNSS-T–calibrated multi-sensor fusion and self-supervised learning
This study develops a framework for estimating forest Global Navigation Satellite System Transmissometry (GNSS-T)-calibrated Vegetation Optical Depth (VOD) at 30 m resolution by fusing Sentinel-1A Synthetic Aperture Radar (SAR), Harmonized Landsat–Sentinel-2 optical reflectance, GEDI lidar canopy structure, and climate variables. The framework achieves high accuracy in predicting VOD using a self-supervised learning approach based on Vision Transformers.
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Upadhyay et al. (2026) Evaluating frequency of low reservoir storage in the western U.S. over the 21st century
This study assesses the projected changes in low storage frequency and near-minimum-power-pool risk across 94 western U.S. reservoirs under future climate scenarios using a calibrated offline hedging release model.
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Fang et al. (2026) Modulating Effects of Ice-Phase Microphysical Processes on Surface Precipitation Intensity in Typhoon Spiral Rainbands
This study investigates the modulating effects of ice-phase microphysical processes on surface precipitation intensity in Typhoon spiral rainbands. The results show that ice-phase processes contribute significantly to surface precipitation, with an average contribution fraction of 82% over the 48-h analysis period.
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Yang et al. (2026) Hidden Hurdles in Agricultural Water Scarcity Assessments: A Case Study in China
This study proposes a novel observational approach to assess agricultural water scarcity by monitoring irrigation water withdrawal responses to climate-induced variability. The findings reveal uncertainties in Global Hydrological Model estimates and challenge long-held perceptions of China's water stress patterns.
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Xu et al. (2026) Quantifying Human and Climatic Contributions of Large‐Scale Groundwater Recovery in the North China Plain
This study developed an integrated modeling framework to quantify the drivers of groundwater recovery in the North China Plain and found that human interventions were the dominant factor reversing depletion. The aquifer regained approximately 30 km³ of water, restoring a drought buffer comparable to the region's surface reservoir capacity.
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Zheng et al. (2026) Climate‐Adaptive and Cascade‐Constrained Machine Learning Prediction for Sea Surface Height Under Greenhouse Warming
This study evaluates the climate adaptability of machine learning (ML) models in predicting sea surface height (SSH) using kinetic energy (KE) cascade as a physical constraint. The results show improved model performance under greenhouse warming conditions.
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Su et al. (2026) Higher Vulnerability But Faster Recovery in Planted Than Natural Forests During the 2022 Compound Drought–Heatwave in China's Yangtze River Basin
This study investigates the resilience of planted forests (PFs) and natural forests (NFs) to compound drought and heatwave events in the Yangtze River Basin. The research reveals a resistance-recovery trade-off between PFs and NFs, with NFs exhibiting stronger resistance but slower recovery.
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Emamalizadeh et al. (2026) Toward a structured workflow to harmonize soil water content products: A comparative study across different methods
This study presents a structured workflow to harmonize diverse soil water content datasets, improving their comparability while preserving intrinsic characteristics. The proposed framework enhances comparability and traceability across multi-sensor SWC studies.
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Mangukiya et al. (2026) Benchmarking and Selecting Optimal Hydrological Models for Large‐Sample Applications Considering Complexity and Uncertainty
## Identification - **Journal:** Water Resources Research - **Year:** 2026...
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Xu et al. (2026) Main-stem versus tiller-derived spike formation in winter wheat: Divergent water use strategies for long-term yield stabilization in saline-prone arid regions
This study investigates the effects of sub-ETc drip irrigation and seeding density on winter wheat productivity in saline-prone arid regions. The results show that a low-density planting strategy combined with moderate sub-ETc irrigation maintains yield stability through sustained post-anthesis photosynthesis, mediated by preferential deep-root water access to less-saline sub-soil.
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Sandi et al. (2026) Assessment of Future Nonstationary Changes in Extreme Sea Levels Considering Climate Change for Southeast Asia Using High‐Resolution Climate Forcing
This study assesses the nonstationary behavior of extreme total water levels and extreme coastal water levels along Southeast Asia's coastline under a high-emission climate scenario, highlighting significant changes driven by sea level rise, storm surge, and wave components.
