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Lundquist et al. (2026) Snow What? Strengths and Limitations of Different Snow Products in Western U.S. Mountains
This study evaluates various snow water equivalent (SWE) products against aerial LiDAR observations in the western United States to identify the most accurate datasets for hydrological analysis.
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Kim et al. (2026) Non-stationary atmospheric pathways limit seasonal predictability of Eurasian autumn snow impacts on East Asian winter temperature
This study examines the non-stationary atmospheric pathways that limit seasonal predictability of Eurasian autumn snow impacts on East Asian winter temperature. The results show that the endpoint relationship between October Eurasian snow and EA winter temperature remains comparatively robust across periods, while the intermediate pathway links are substantially less stable.
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Maxmatmurod et al. (2026) Transfer Learning-Based Digital Models: Algorithmic Provisioning of Smart Irrigation Systems Under Data Scarcity
This paper proposes a Transfer Learning (TL) framework to enable high-accuracy smart irrigation systems in data-scarce regions like Uzbekistan, overcoming the limitations of deep learning models without requiring localized historical big data.
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Álvarez-Cuesta et al. (2026) Enhancing coastal flood hazard assessments through spatio-temporal event modelling at large scales
This study presents a spatio-temporal statistical model that integrates wave and storm surge contributions to estimate water level footprints and their associated flooding over large spatial scales. The approach combines physics-based hydrodynamic modelling with machine learning to generate synthetic databases of extreme events.
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Liu et al. (2026) Identifying eco-optimal nitrogen and irrigation management for wheat production in the North China Plain
This study identified an eco-optimal nitrogen and irrigation management strategy for winter wheat under high–low seedbed cultivation (HLSC) in the North China Plain. It found that a moderate input strategy (240 kg N ha⁻¹ and 90 mm irrigation) achieved the best balance of productivity, profitability, energy efficiency, and environmental sustainability.
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Meng et al. (2026) Effects of land surface parameterizations on cold‐fog simulation in Heber Valley: Insights from the CFACT field campaign
This study investigates the impact of different land surface models on mountain cold-fog simulations, focusing on the sensitivity of key land surface parameters and their associated physical mechanisms.
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Guan et al. (2026) How NSIOD and El Niño Jointly Modulate Spring Precipitation Over Southeastern China: Mechanisms Revealed by Observations and CESM Simulations
This study investigates how the Negative Southern Indian Ocean Dipole (NSIOD) and El Niño jointly modulate spring precipitation over Southeastern China, revealing a synergistic response that generates extensive and intense positive precipitation anomalies.
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Qi et al. (2026) Intensifying Flash Droughts Aggravate Vegetation Ecosystem Vulnerability in the Monsoon Region of China: Evidence From Resistance and Resilience Responses
This study developed a high-temporal-resolution framework to assess vegetation response characteristics under flash drought stress in China from 1982 to 2019. The results show increased vegetation vulnerability due to declining resistance and shifting resilience-trade-off relationships.
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Qian et al. (2026) Recent intensification of the negative physiological effect of CO2 on terrestrial evaporation
This study developed a novel analog framework to decouple and quantify the individual contributions of vegetation greening and stomatal conductance reduction, driven by atmospheric CO₂, to global terrestrial evaporation (ET) trends. The analysis revealed that the net physiological effect of CO₂ on ET was globally negative from 1982 to 2018, as stomatal conductance reductions increasingly outweighed the positive effect of greening.
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Yang et al. (2026) Multi-timescale Variabilities and Interactions in the Global Monsoon
This study examines the multi-time-scale variabilities and interactions in the global monsoon system. The research reveals that the global monsoon exhibits a complex interplay between different time scales, including intraseasonal oscillations (ISO), subseasonal variability (SSV), and seasonal variability.
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Wu et al. (2026) Accurate diagnosis of soil moisture and canopy water content in citrus orchards based on synergistic multi-source remote sensing
This study developed a synergistic multi-source remote sensing framework, integrating Landsat-8/9, Sentinel-2, and Sentinel-1A data, to enhance the Water Cloud Model with phenology-driven dynamic canopy parameters for accurate soil moisture and canopy water content diagnosis in citrus orchards. The improved model successfully retrieved soil moisture at a regional scale, with Sentinel-1A VV polarization demonstrating superior accuracy (R²: 0.785–0.854, RMSE: 6.125–8.351%) compared to VH polarization.
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Xie et al. (2026) Practical irrigation scheduling at the sub-field scale: Comparing OpenET and capacitance soil moisture sensors against a TSEB reference in dry edible beans
This study compared three evapotranspiration (ET) estimation approaches—Two-Source Energy Balance (TSEB), an operational soil water balance (SWB) with capacitance sensors, and satellite-based OpenET—across three management zones in a dry edible bean field. OpenET showed moderate daily agreement with the TSEB reference, while the SWB approach performed poorly, highlighting OpenET's potential for sub-field precision irrigation and limitations of factory-default soil moisture sensor workflows.
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Osorio-Diaz et al. (2026) Agricultural water balance and variability in Utah irrigation canal companies with OpenET products and spatial data
This study developed and implemented a satellite-data-driven water balance model for irrigation canal companies (ICCs) in Northern Utah, demonstrating its feasibility for assessing agricultural water depletion and identifying significant water balance residuals under data-limited conditions.
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Lu et al. (2026) The Impact of Urban Heat Island on Extreme Rainfall Events in Presummer Over the Pearl River Delta Metropolitan Region Under Different Synoptic Systems
This study examines the impact of urban heat island (UHI) effects on extreme rainfall events in the Pearl River Delta metropolitan region under different synoptic systems. The results show that UHI influences vary according to differing synoptic conditions.
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Squintu et al. (2026) Heatwaves in a 15 °C World: Exploring remote drivers’ influence on Northern Italy with a storyline-based approach
This study proposes an application of the storylines technique to investigate the influence of global temperature conditions on heatwaves in Northern Italy. The results highlight relevant contributions from precipitation depletion over different Euro-Mediterranean domains and connections with tropical modes such as El Niño Southern Oscillation.
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Li et al. (2026) Extreme drought converts grassland carbon sinks to sources in Inner Mongolia, but strong recovery follows: Insights from a 9-year study
This study evaluates the impact of extreme drought on carbon fluxes in Inner Mongolia's grasslands from 2010 to 2018, finding that the 2017 drought converted carbon sinks into sources, followed by a strong recovery in 2018.
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Shen et al. (2026) Irrigation Impact on Humid Heat Stress: Divergent Metrics, Vegetation Dynamics, and Future Worsening
This study investigates the impact of irrigation on heat comfort in the North China Plain under global warming using a high-resolution weather model with improved crop systems.
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Yang et al. (2026) Phenology constrains the predictability of soil respiration in cropping systems revealed through interpretable machine learning
This study examines the predictability of soil respiration in cropping systems using stage-explicit modeling and interpretable machine learning. The results show that phenology constrains the predictability of soil respiration, with predictive skill confined to specific phenological stages.
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Pereira et al. (2026) Análise espaço-temporal do balanço hídrico climatológico no estado de Goiás para o planejamento da irrigação
This study analyzed the spatiotemporal variability of the climatological water balance in the state of Goiás, identifying periods of soil water storage, water deficit, and water surplus to support irrigation planning.
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Grenzi et al. (2026) Enhancing severe convection forecasts with microwave radiance assimilation in limited‐area models
This study demonstrates the benefits of assimilating satellite radiances, particularly microwave water-vapour channels and all-sky infrared radiances, in convection-permitting limited-area models for forecasting severe precipitation.
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Mustafa (2026) Growth and Productivity Response of Bread Wheat (Triticum aestivum L.) to the Interaction between Smart Irrigation and Conservation Agriculture under Heat and Drought Stress in Salah Al-Din Governorate
This study evaluates the effects of smart irrigation and conservation agriculture on bread wheat (Triticum aestivum L.) cultivars under semi-arid conditions, demonstrating a significant improvement in physiological parameters, yield components, and water use efficiency.
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Lin et al. (2026) Bridging global offshore waves and nearshore coastal conditions with deep learning
This study presents a hybrid framework (SWAN-TC) that integrates numerical emulation with observation-driven refinement to enable rapid, high-resolution nearshore wave simulation. The framework combines a deep learning surrogate model (SWAN-T) with an observation-driven residual correction sub-model (SWAN-C), providing a composite solution with both accuracy and efficiency.
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Zhou et al. (2026) Escalating Uncertainty Under Increasing Risk in Compound Heat and Precipitation Extremes
This study investigates the uncertainty in compound heat and precipitation extremes (CHPE) using 14 CMIP6 models and two single-model initial-condition large ensembles, revealing that CHPE uncertainty is itself an emerging dimension of climate risk.
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Suthar et al. (2026) Treated wastewater irrigation supports canola (Brassica napus L.) production in arid agroecosystems without exceeding soil salinity limits
This study evaluates the use of treated municipal wastewater as an alternative irrigation source for canola production in arid agroecosystems. The results show that canola seed and straw yields did not differ significantly between freshwater and treated wastewater irrigation, and soil salinity limits were not exceeded.
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Senay et al. (2026) On-demand global Landsat evapotranspiration product: development, evaluation, and dissemination
This study presents the development, evaluation, and dissemination of a global on-demand Landsat evapotranspiration product using the Operational Simplified Surface Energy Balance (SSEBop) model. The product provides field-scale actual evapotranspiration data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9.
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Wang et al. (2026) A comprehensive distributed hydrological framework for assessing flood responses to environmental change under multiple human disturbances
This study enhances the GHydroMod-SIM-DAI model to develop a comprehensive distributed hydrological framework that explicitly represents human disturbances, improving flood response simulations under environmental change. The proposed framework demonstrates improved performance in assessing flood responses to multiple human disturbances.
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Zhang et al. (2026) East Asian heatwaves intensify faster than they dissipate in a warming climate
This study investigates the temporal evolution of heatwaves in East Asia using observations and CMIP6 simulations, finding that heatwaves intensify faster than they dissipate and that future changes depend on how extremes are defined.
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Wei et al. (2026) Subsurface drainage alleviates salt-affected soil constraints and improves soil fertility through altering physical and hydraulic properties in the Hetao Irrigation District, China
This study investigates the effects of subsurface drainage (SD) on soil properties, nutrient utilization, and biological processes in a sunflower cultivation system. The results show that SD improves soil pore and aggregate structure, enhances soil aeration, and promotes nutrient accumulation.
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Li et al. (2026) Two Modes of Self‐Organizing Development of Extreme Rainfall‐Producing Storms in South China
This study investigates the convective-scale dynamics of extreme rainstorms on monsoon coasts in South China using a high-resolution coupled model. The research reveals two distinct modes of storm development, characterized by different balances between effective buoyancy and dynamic forcing.
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Nguyen-Thanh et al. (2026) Relative skills of SPEAR and CFSv2 in foretelling warm-season precipitation anomalies over the conterminous United States and potential sources of errors
This study evaluates the skill of two climate forecasting systems in predicting spring and summer precipitation anomalies over the contiguous United States, highlighting common limitations and areas for improvement.
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Zita et al. (2026) Revisiting climate extremes in South America and their modulation by oceanic teleconnections
This study investigates the spatiotemporal patterns of climate extremes in South America and explores the influence of oceanic modes on these patterns using daily MERGE and SAMeT data from 2000 to 2024. The results highlight the dominant role of ENSO in modulating climate variability across the region.
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Feng et al. (2026) Causes of the Delayed Seasonality of Northern Hemisphere Tropical Cyclones in CMIP6 Models
This study investigates the seasonal transition of tropical cyclone genesis frequency over the Northern Hemisphere using CMIP6 models and identifies a bias in atmospheric models due to surface wind speed errors.
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Shen et al. (2026) Attributing Runoff and Non‐Point Source Pollution Changes to Climate and Human Drivers in the Weihe River Basin, China
This study developed an integrated framework to quantify the relative roles of climate change and human activities on runoff generation and pollutant transport in river basins. The framework was applied to the Wei River Basin, China, revealing pronounced spatial heterogeneity in responses to precipitation changes.
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Baluch et al. (2026) Evaluating Crop Yield Sensitivity to Climate Change Using a Deep‐Learning Framework Incorporating Vegetation and Groundwater Memory
This study developed an interpretable spatiotemporal framework to reconstruct historical crop yields responses in Northeast China and assess future climate-scenario impacts. The framework used a combination of machine learning models and satellite data to predict crop yields with high accuracy.
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He et al. (2026) Sources of Potential Predictability for July–August 2025 Extreme Precipitation Anomalies Over Northern China: Roles of the Western Pacific and North Atlantic–Barents–Kara Sea Sectors
This study identifies two distinct sources of predictability for extreme precipitation anomalies over northern China in July and August 2025, improving the prediction by separating S2S models into high-skill and low-skill groups.
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Hemachandra et al. (2026) Soil-crop hydrology modelling approaches for conjunctively estimating recharge, crop demand and pumping in irrigated agriculture: a review
This review examines soil-crop hydrology models that estimate regional-scale groundwater recharge, crop water use, runoff, and freshwater extraction rates to support irrigation demands. The study evaluates the reliability of these models for estimating pumping rates and their limitations in simulating conjunctive use of groundwater and surface water.
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Brückner et al. (2026) Dams trigger long-term river-floodplain decoupling in dynamic Andean foreland rivers
This study uses an innovative hydro-morphodynamic model to investigate the long-term morphodynamic and environmental impacts of dam construction on Andean foreland rivers in the Amazon Basin. The research reveals that dams can trigger rapid and irreversible system reconfiguration, with significant effects on riparian ecosystems and local communities.
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Huidobro et al. (2026) Re‐Evaluating Inherited SIF Anomaly Detection Methods for the 2024 Amazon Drought: A 3D Convolutional Autoencoder Approach
This study compares two anomaly detection methods for Solar‐Induced Chlorophyll Fluorescence (SIF) data to identify vegetation stress in the Amazon during severe droughts. The 3D Convolutional Autoencoder (CAE) method outperforms a classical z-score approach and aligns with drought patterns detected by SPEI and MSB.
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Song et al. (2026) Thermodynamic Control of Global Seasonal Snow Decline
This study develops a physically based attribution framework to quantify the relative roles of precipitation variability and warming-induced phase transitions in driving global snowfall decline. The results show that thermodynamic phase shifts, rather than changes in precipitation amount, are primarily responsible for snowfall decline across most seasonal snow regions.
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Saint‐Martin et al. (2026) Global kilometer-scale climate simulations: new opportunities for climate services
This paper presents a century-long simulation using the ARP-GEM global atmosphere model at 2.6 km horizontal resolution to complement and extend the set of simulations used in the latest version of the French climate services.
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Ajao et al. (2026) Diagnosing the Roles of Meteorological Forcing, Storage Memory, and Network Connectivity in Cold-Region Streamflow Prediction
This study proposes a six-tier diagnostic framework to quantify the contributions of meteorological forcing, storage memory, and network connectivity to streamflow prediction in cold-region watersheds. The results show that graph-based models provide greater physical realism and transferability despite slightly lower predictive accuracy than autoregressive approaches.
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Hinkel et al. (2026) Comment on “Flooding Is Not like Filling a Bath” by Sanders et al.
This commentary addresses the limitations and biases in applying bathtub modeling to assess coastal flood risks at broad scales, arguing that both bathtub and physics-based models have roles to play in addressing this problem.
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Gui et al. (2026) Climate-adjusted sequence learning reveals atmospheric-demand transitions in agricultural water–heat buffering
This study develops a climate-adjusted sequence-learning framework to identify agricultural water–heat response signatures from seasonal satellite and climate time series. Two dominant response strategies were identified: strong-buffering systems showed greener, wetter, and cooler climate-adjusted response signatures compared to weak-buffering systems.
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Shi et al. (2026) Improving simulation of Earth system variability through weakly coupled ocean data assimilation in E3SM
This study evaluates the impact of a newly developed weakly coupled ocean data assimilation system within the DOE Energy Exascale Earth System Model version 2 (E3SMv2) on global and regional climate variability. The results demonstrate substantial improvements in simulating both interannual and decadal climate variability.
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Córdova et al. (2026) Precipitation downscaling for climate characterization with scarce data using transfer learning
This study presents a deep learning-based downscaling framework using transfer learning to improve the accessibility and quality of high-resolution climate information in data-scarce regions. The method produces accurate long-term precipitation estimates with only a few years of observations.
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Zhang et al. (2026) Identification of phenology-aligned sensitive windows to extreme-rainfall events for maize in north China Plain and actionable irrigation–drainage triggers
This study identifies phenology-aligned sensitive windows to extreme-rainfall events for maize in the North China Plain and proposes actionable irrigation–drainage triggers. The Exposure Mismatch Index (EMI) is defined as the directional difference in cumulative threshold-exceeding precipitation between phenology-aligned and static calendar windows.
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Deng et al. (2026) Hydrological implications of vegetation-associated precipitation recycling during peak growing season over the Loess Plateau
This study examines the hydrological implications of vegetation-associated precipitation recycling during the peak growing season over the Loess Plateau. The results show that land-sourced moisture dominates the precipitation supply to the region, and internally recycled precipitation contributes 14.4% of total precipitation.
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Zhang et al. (2026) Dam Regulation Moderates Climate‐Induced Rice Yield Loss in the Mekong‐Tonle Sap Lake System
This study develops an integrated agro-hydrological framework to quantify the impact of human activities on inundation-induced losses in rice production under climate change. The framework is applied to the Lancang-Mekong River Basin, focusing on Tonle Sap Lake.
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Xu et al. (2026) Rising vapor pressure deficit and fuel availability exacerbate the dispersion of intra-annual burned area
This study examines the impact of climate change on wildfire dispersion and its consequences for fire-related carbon emissions. The results show that increased vapor pressure deficit and fuel availability lead to a widespread increase in wildfire dispersion, particularly in Eurasia, South America, and Australia.
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Zhang et al. (2026) Inverse modeling and coupled analysis of soil moisture content and organic carbon in oasis areas of arid regions
This study employed a deep learning approach integrating multi-source data to achieve multi-layer inversion of soil moisture and soil organic carbon in the Wei-Ku Oasis region. The results indicate that the CNN-LSTM model achieves the best performance in multi-depth inversion, with significant spatial heterogeneity and vertical differentiation of the soil water-carbon relationship.
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Wang et al. (2026) Unveiling the link between extreme precipitation events and flood disasters in China: from a 3D perspective
This study investigates the link between extreme precipitation events and flood disasters in China from a 3D perspective. The authors developed a 3D automatic recognition algorithm to analyze the characteristics of 632 flood-causing precipitation (FCP) events in China from 2000 to 2023.
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Safi et al. (2026) The world is being fed at the expense of nature: A remote sensing based global assessment from 2000 to 2019
This study assesses global agricultural productivity trends from 2000 to 2019 using remote sensing data, comparing them with the Comprehensive Assessment of Water Management in Agriculture (CAWMA) optimal scenario projections. The findings show that the world has deviated from this scenario, aligning with more pessimistic outlooks.
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Koshkin et al. (2026) Process‐Based Model Parameters for Post‐Fire Snow Hydrology: Looking Beyond Snow Albedo and Vegetation
This paper investigates the impact of wildfires on snow accumulation and melt dynamics using a physically based model, identifying key parameters that influence post-fire snowpack evolution. The study reveals significant differences in snow energy balance and processes between burned and unburned forests.
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Arnold et al. (2026) Large language model as reservoir operator: a generative agent bridging human judgment and optimization in water resource systems
This study explores the use of large language models (LLMs) to replicate human decision-making in reservoir water management, demonstrating their ability to approximate risk-averse hedging behavior without task-specific training.
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Zhang et al. (2026) Hemispheric asymmetry in evapotranspiration reveals terrestrial water-flux redistribution
This study reveals a hidden asymmetry in the global evapotranspiration trend from 2000 to 2022, with increases in the Northern Hemisphere and declines in the Southern Hemisphere. The small global change in evapotranspiration masks a marked compensation between northern greening and southern drying.
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Schwartz et al. (2026) FORMSpoT: Revealing fine-scale forest disturbances from nation-wide 1.5 m forest canopy height time series
This study introduces FORMSpoT, a decade-long (2014-2024) country-scale mapping of forest canopy height at 1.5 m resolution over France, derived from SPOT-6/7 imagery using a hierarchical transformer model trained on LiDAR HD data. The resulting dataset, FORMSpoT-Δ, provides annual fine-scale forest disturbance polygons validated against successive airborne LiDAR acquisitions and French National Forest Inventory plot revisits.
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Guo et al. (2026) Global crop production responses to climate-driven drought under future warming
This study systematically analyzed the propagation mechanisms from meteorological to agricultural drought, quantified the nonlinear impacts of synergistic temperature and precipitation changes on the yields of 16 major global crops, and evaluated the adaptation potential of adjusting irrigated and rainfed areas and crop diversity under future climate change scenarios.
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Tang et al. (2026) Skillful Probabilistic Prediction of Seasonal Extreme Precipitation Based on China Multi‐Model Ensemble Forecasts
This study evaluates the China Multi-Model Ensemble (CMME) system's ability to predict summer extreme precipitation anomalies and identifies the factors contributing to its improved performance. The results show that CMME outperforms single-model predictions, particularly in tropical regions.
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Couallier et al. (2026) Toward robust fine-scale decadal precipitation forecasts through dynamically consistent subsampling
This study presents a 5-step framework to improve decadal precipitation forecasts over France by integrating recent advances in large-scale sea-level pressure modes. The approach combines predicted indices with dynamically consistent subsampling of climate model ensemble members.
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Xiao et al. (2026) Soil moisture–atmosphere coupling intensifies wildfires in Siberia in 2021
This study investigates the role of soil moisture-atmosphere coupling in intensifying wildfires in Siberia during 2021, revealing a strong climate sensitivity of fire activity under anthropogenic climate change.
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Gao et al. (2026) Distinct seasonality and trends of natural and anthropogenic wildfires in boreal forests
This study employs a novel machine-learning attribution framework to distinguish natural and anthropogenic wildfires in boreal forests and characterize their distinct seasonal patterns and temporal variations. The results demonstrate that human activities drive a significant increase in anthropogenic fires in spring, whereas natural fires prevail in summer.
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Schulz et al. (2026) The Response of Tropical Land–Ocean Precipitation Partitioning to SST and CO2 Increase in Global Storm-Resolving Simulations
This study investigates how tropical land-ocean precipitation partitioning responds to idealized forcing, including CO2 increase and uniform sea surface temperature increase. The research uses the icosahedral nonhydrostatic (ICON) model, a global storm-resolving model that explicitly simulates convection.
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Wu et al. (2026) Analytical and numerical solutions of hydrometeor momentum equations
This study investigates the momentum equations of hydrometeors and air under various forcing conditions, revealing unexpected behavior in equilibration times and acceleration rates. The research highlights the complex interactions between hydrometeors and air, particularly when considering multiple effects on terminal fall speeds.
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Na et al. (2026) Generation of angular-normalized, cloud-filled, 0.01°-downscaled land surface temperature from 2018 to 2023 based on official FY-4A dataset
This study proposes a novel framework for generating angular-normalized, cloud-filled, and 0.01°-downscaled land surface temperature (LST) products from the official FY-4A dataset. The framework combines directional, nadir, and hemispherical LST layers to produce high-resolution all-weather LST products.
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Dharmapurikar et al. (2026) Irrigation and historical reductions in the interannual variability of Midwestern maize yield
This study examines the historical variability of US Midwestern maize yields, finding that irrigation is the primary driver of a decline in yield variability over 1950–2009. The results highlight the importance of irrigation for stabilizing agricultural productivity.
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Expósito et al. (2026) Water Efficiency Targets at the Basin Scale: Useful Guide or Policy Trap?
This study applies a hydro-economic model to assess the impact of on-farm efficiency improvements on basin-wide water savings in the Guadalquivir River Basin, southern Spain. The results show that targeting basin-wide water-use efficiency is complex and limited by multiple factors.
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Guse et al. (2026) Event indicator analysis using depth functions to explain the occurrence of large floods in Germany
This study investigates the drivers of large flood peaks in Germany using a multivariate statistical approach and identifies maximum event precipitation and event precipitation volume as key indicators.
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Williams et al. (2026) Carbon emissions exacerbating the Western US water crisis
This study quantifies the impacts on western US water resources attributable to the Carbon Majors' emissions since 1950. The results show that these emissions have led to a reduction in snowpack and streamflow, an increase in irrigation demand, and a widening seasonal gap between water supply and demand.
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Gyamfi et al. (2026) Integrating ENSO dynamics into physics-informed Graph Neural Networks for extreme evapotranspiration prediction under climate change
This study develops an ENSO-aware spatio-temporal Graph Neural Network (ST-GNN) for extreme evapotranspiration prediction across the Korean Peninsula, improving predictions during ENSO phase transitions.
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Zhang et al. (2026) Global-regional nested forecasting of soil moisture
This study proposes an Artificial Soil Moisture Forecasting Model (ASM) that integrates atmospheric, oceanic, and land surface variables within an autoregressive forecasting framework to predict soil moisture evolution at the synoptic-to-early-subseasonal time scale. ASM consistently outperforms representative deep learning models across forecast lead times.
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Bu et al. (2026) NASA’s ECOSTRESS satellite reveals widespread midday depression in ecosystem evapotranspiration
This study uses evapotranspiration measurements from the ECOSTRESS satellite and machine learning to quantify global midday depression in evapotranspiration. The results show that midday depression primarily occurs during peak-growing seasons in temperate zones and dry periods in the tropics, with a morning shift of the peak evapotranspiration time by > 0.5 h.
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Shahrood et al. (2026) Asymmetric shifts in seasonal transition timing in a sub-Arctic river system under climate warming
This study analyzes a 59-year daily record from the River Oulankajoki in northeastern Finland to characterize proxy-based seasonal transitions in discharge, snow depth, and air temperature. The analysis reveals earlier shifts in springtime events across snow, discharge, and temperature timings.
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Zeng et al. (2026) Spatiotemporal variations of precipitation-driven dry–wet boundaries and associated impacts from 1975 to 2025 in Mainland China
This study analyzes the spatiotemporal migration of China's core precipitation isohyets (200-, 400-, and 800-mm) and their associated impacts during 1975-2025. The results show significant wetting across northern basins but relative stability in southern humid basins.
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Zhang et al. (2026) Contrasting Performance of Empirical Reference Evapotranspiration Models in Different Climatic Regions of China
This study evaluates and compares the performance of 35 empirical reference evapotranspiration (ET0) models across four climatic regions in China, identifying suitable models for ET0 estimation based on data availability.
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Paul et al. (2026) Normalized Regime Persistence: A Simple Metric to Diagnose Land Feedback States
This study introduces a new observation-driven metric to characterize land feedback states using satellite-derived soil moisture variability. The research reveals that climatic gradients shape the seasonal evolution of three land feedback regimes, with distinct coupling strengths across different climate types.
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Tefera et al. (2026) Sub-daily reconstruction of eddy-covariance energy fluxes under realistic contiguous outages: model benchmarking and energy-balance diagnostics
This study evaluates the performance of machine-learning and deep-learning approaches for gap filling of surface energy fluxes under realistic contiguous data outages. The results show that tree-based models achieve stronger reconstruction skill than deep-learning models, particularly for sensible heat.
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Dewettinck et al. (2026) Evaluation of the ALARO1-SFX (CY43T2) regional climate model over Belgium across different resolutions
This study evaluates the ALARO1-SFX regional climate model over Belgium across different resolutions. The results indicate that higher resolutions improve temperature and precipitation biases relative to the 25 km simulation.
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Zhao et al. (2026) Learning evaporative fraction with memory
This study develops an explainable machine learning model to predict evaporative fraction (EF) with memory effects using long-term observations from 90 eddy covariance sites across diverse plant functional types. The model accurately captures EF dynamics, particularly during post-rainfall pulses and soil moisture dry-down events.
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Berzonsky et al. (2026) Widespread Divergence Between Precipitation and Discharge Trends Across Global Rivers
This study investigates the relationship between precipitation and river flow at 10,179 sites worldwide, revealing widespread decoupling of these two variables.
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Osorio et al. (2026) A data-driven gap-filling approach to assess long-term streamflow trends across Colombia
## Identification - **Journal:** Hydrological Sciences Journal - **Year:** 2026...
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Méndez‐Barroso et al. (2026) Constraining the maximum entropy production approach with sun-induced chlorophyll fluorescence to estimate evapotranspiration in a seasonally dry deciduous forest
This study evaluates the performance of the maximum entropy production (MEP) approach in estimating evapotranspiration (ET) in a semi-arid ecosystem using sun-induced chlorophyll fluorescence (SIF) as a constraint. The results show that the MEP model performs well in comparison with in-situ ET observations and independent global transpiration assessments.
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Holder et al. (2026) Enhanced Occurrence of Springtime Extreme Precipitation Associated With Mesoscale Convective Systems Over the US by Baroclinic Annular Mode
This study investigates the influence of natural climate variability on mesoscale convective systems (MCSs) and their contribution to extreme precipitation in the United States. The research reveals that MCSs are nearly twice as likely to produce extreme precipitation during the intense positive phase of the Baroclinic Annular Mode (BAM).
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Zeng et al. (2026) A novel framework for quantifying threshold-controlled surface hydrologic connectivity in depression-dominated watersheds
This study presents a novel framework for quantifying threshold-controlled surface hydrologic connectivity in depression-dominated watersheds, providing new insights into overland flow dynamics and facilitating water resource management.
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Xu et al. (2026) A network-based framework for deciphering extreme precipitation propagation across China
The study develops a network-based framework to analyze the propagation of extreme precipitation across China, identifying key propagation hubs and the role of geomorphological features in facilitating hydroclimatic connectivity.
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Gu et al. (2026) The impact of ERA5 assimilation-window discontinuities on convection-permitting forecasts of extreme precipitation: a case study of the July 2023 North China heavy rainfall
This study investigates the impact of reanalysis window boundaries on forecast skill and identifies structured differences among adjacent initializations. The results highlight the importance of accounting for assimilation-window position in reanalysis-driven forecasts.
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Li et al. (2026) Estimating reference evapotranspiration using a BiLSTM model incorporating spatiotemporal features in Southwestern China
This study develops a hybrid deep learning framework integrating a Convolutional Neural Network (CNN), Temporal Position Attention (TPA), Bidirectional Long Short–Term Memory network (BiLSTM), and Adaptive Boosting (Adaboost) to enhance ETo estimation accuracy from both temporal and spatial perspectives under limited data scenarios in Southwestern China.
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Zhao et al. (2026) Climatic-to-vegetation transition in controlling the ratio of transpiration to evapotranspiration in China revealed by multi-dataset fusion
This study employed the extended double instrumental variable algorithm (EIVD) method to fuse three representative transpiration and evapotranspiration datasets over China for the period 1982-2020, producing a high accuracy T/ET product. The results showed a significant upward trend in mean annual T/ET with a southeast-to-northwest decreasing gradient.
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Sanikhani et al. (2026) Large-scale climate teleconnections and multiscale controls on river water temperature
This study investigates the multiscale influence of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on river water temperature variability in a cold-region Pacific watershed. The results indicate that while seasonal atmospheric forcing dominates the annual thermal cycle, significant non-stationary variability emerges at interannual (2–7 years) and decadal scales.
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Li et al. (2026) Vegetation change reshapes meteorological-hydrological drought characteristics and propagation process in the Yellow River Basin, China
This study investigates the impact of vegetation change on drought characteristics and propagation processes in the Yellow River Basin (YRB) using a distributed hydrological model incorporating vegetation dynamics. The results show that vegetation restoration can alter drought patterns, with increased frequency, duration, and intensity of hydrological droughts in certain regions.
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Xu et al. (2026) Quantifying evaporation depth from on-farm storages using water-level observations
This study evaluates the performance of nine evaporation models on small on-farm storages in Australia using water-level-derived evaporation as a benchmark. The results show that ensemble approaches generally outperform individual models.
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Liu et al. (2026) Extended Fire Season Over Eastern Siberia Driven by Accumulated August–September Drought
This study identifies a pronounced shift in fire season characteristics over eastern Siberia from 2002 to 2023, marked by a lengthening of the fire season and increasingly clustered occurrence of large fires. The main driver of this change is enhanced fire-weather conditions associated with accumulated drought.
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Steger et al. (2026) European snow cover in the EURO-CORDEX regional climate model ensemble: model evaluation
This paper evaluates the representation of snow cover in the EURO-CORDEX regional climate model ensemble, comparing simulated data with reference datasets for present-day European climate conditions.
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Yan et al. (2026) Decadal surge of water-surface solar in China's Yangtze Delta: A high-fidelity SAR-optical fusion inventory (2015–2024)
This study presents a high-fidelity water-surface photovoltaics (WPV) inventory for the Yangtze River Delta region in China from 2015 to 2024. Using a multi-sensor fusion framework combining Sentinel-1 Synthetic Aperture Radar and Sentinel-2 optical imagery, the authors developed a random forest classifier to generate annual WPV maps with an overall accuracy of 97.3% and a Cohen's kappa coefficient of 0.94.
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Gleason et al. (2026) SWOT, Empiricism, and River Modeling
This study assesses the performance of global river models using Surface Water and Ocean Topography (SWOT) satellite measurements, highlighting areas where these models struggle. The results suggest that leveraging SWOT observations can improve model accuracy if they adapt to represent realistic hydraulics.
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Moschini et al. (2026) Hydrological auditing of LISFLOOD v4.1.1: impacts of model setup on water balance components in the Po River Basin
This study presents a hydrological auditing of the LISFLOOD v4.1.1 model in the Po River Basin, evaluating its performance in simulating streamflow, evapotranspiration, and overall water balance under different model setups. The results show that the current EFAS v.5.0 setup performs best in terms of streamflow simulation but tends to underestimate evapotranspiration.
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Fei et al. (2026) Assimilating GRACE Data for Improved Modeling of the Terrestrial Hydrological Cycle and Its Response to ENSO With the Noah‐MP Multi‐Physics Ensemble
This study investigates the impact of assimilating Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data on hydrological simulation performance under different climatic regimes and its effect on runoff–El Niño‐Southern Oscillation (ENSO) linkages. The results show that data assimilation enhances the accuracy of simulations, particularly in regions with significant climate variability.
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Luo et al. (2026) From Macro to Micro: How Large-Scale Atmospheric Circulation Governs Raindrop Size Variations during Warm-Rain Processes?
This study investigates the relationship between large-scale atmospheric circulation and raindrop size variations during warm-rain processes. The results show that changes in atmospheric circulation patterns significantly impact raindrop size distribution.
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Yang et al. (2026) High‐Resolution Regional Atmospheric Simulation of Precipitation and Isotopes in Central America
This study uses IsoRSM to simulate precipitation and its isotopic composition over tropical Costa Rica at high spatial and temporal resolution, improving upon previous results with bias correction. The model captures spatial patterns and seasonal cycles of precipitation inputs and isotopes.
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Brêda et al. (2026) Climate change projections of probable maximum precipitation over large areas through depth-area-duration analysis: A case study in Brazil
This study investigates the impacts of climate change on Probable Maximum Precipitation (PMP) in large areas (>50,000 km2) and short to long durations (1–30 days) using Depth-Area-Duration curve projections. The results show a clear trend toward intensification of extreme rainfall for all regions when comparing historical data with future data.
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Xue et al. (2026) Humidity boundary conditions reshape nighttime heat burden during heatwaves in China
This study investigates the impact of humidity extremes on nighttime heat burden during heatwaves in mainland China, revealing significant urban-context associations that depend on humidity state and nighttime heat-burden dimension.
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Shi et al. (2026) A Physics‐Guided Feature Selection Machine Learning Approach for Cloud Probability Retrieval and Detection From TEMPO Imagery
This study presents a physics-guided feature selection machine learning framework that improves cloud detection from hyperspectral observations using TEMPO data. The framework achieves high classification performance and outperforms existing methods.
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Xu et al. (2026) The Impact of Urbanization on Tropical Cyclone Rainfall Over Complex Coastal Terrain
This study investigates how coastal urbanization affects tropical cyclone (TC) rainfall in the Yongjiang River basin, China, using numerical modeling. The results show that urbanization intensifies TC rainfall downwind of urban areas.
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Park et al. (2026) A copula-based stochastic simulation method for the penman wind function (PWF) in in-stream evaporation
This study introduces a copula-based stochastic simulation method for the Penman Wind Function (PWF) in in-stream evaporation. The proposed framework combines site-specific calibration with empirical-prior-based uncertainty propagation to quantify uncertainty in in-stream evaporation estimates under data-limited conditions.
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Jeong et al. (2026) Evaluating North American winter extreme precipitation variability and its drivers in CMIP6 models
This study evaluates the ability of 32 CMIP6 global climate models (GCMs) to capture winter extreme precipitation variability over North America. The analysis focuses on monthly maximum 5-day precipitation (Rx5day) and its drivers during extended winters (November–March, 1961–2010). The results demonstrate that the multi-model ensemble provides a more robust representation of extreme precipitation than individual models.
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Chen et al. (2026) A Subtle Atmospheric Shift Is Redefining Winter Hydrology on the Tibetan Plateau
This study reveals a weakening of the Tibetan Plateau's buffering function in regulating downstream water supply due to a shift in winter climate regimes. The region is experiencing an increase in warm-dry winters, leading to reduced snow depth and altered hydrology.
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Zhao et al. (2026) Generating a consistent long-term L-band soil moisture record through Bayesian merging of SMOS and SMAP data
The study develops a Bayesian framework to harmonize SMOS soil moisture data with SMAP as a reference, creating a consistent long-term L-band soil moisture record from 2010 to 2024. The resulting merged product significantly increases the annual frequency of effective observations.
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Biryło (2026) Regime shifts in European basins detected from the water budget and the Combined Climatological Deviation Index
The study evaluates hydroclimatic regime shifts in ten major European basins by integrating water budget components and the Combined Climatological Deviation Index (CCDI). It identifies a general hydroclimatic reorganization occurring around 2015, with regional variations in timing and magnitude.
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Duan et al. (2026) Spatiotemporal variation of extreme precipitation and its terrain modulation in the Hengduan Mountains: machine learning and interpretable analysis
This study analyzes the spatiotemporal evolution of extreme precipitation in the Hengduan Mountains from 2005 to 2024 and utilizes interpretable machine learning to quantify the nonlinear influence of topographic factors on these events.
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Shen et al. (2026) Divergent Forest Cover Changes Dominate Inter‐Model Spread in Near‐Surface Wind Speed Trends Over China
This study identifies forest cover changes as the primary driver of uncertainty in global climate model simulations of near-surface wind speed (NSWS) over China.
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Muzammil et al. (2026) Water resources under climate change: Strategies for sustainable agriculture in Colombia
This study estimated Colombia's current and future water demand under climate change scenarios using the CORDEX data. It evaluated alternative spatially-explicit water-saving strategies based on a temporal water footprint assessment approach.
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Zhao et al. (2026) Irrigation accelerated vegetation greening in China
This study analyzes the role of irrigation-related water supply in vegetation greening across China from 1982 to 2022. The results show that irrigation accelerated vegetation greening, with a significant increase in fractional vegetation cover (FVC) and areas with increased irrigation having a greening rate approximately twice that of non-irrigated areas.
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Gong et al. (2026) Computational configuration of an agricultural irrigation rainwater harvesting system in karst regions based on drought characteristics
This study establishes a calculation algorithm for configuring agricultural irrigation rainwater harvesting systems in karst areas based on drought characteristics, providing a viable technical solution for rainwater harvesting and drought resistance in agricultural production.
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You et al. (2026) Study and application of the profile-attenuation-based standardized soil moisture index
This study developed a Profile-Attenuation-based Standardized Soil Moisture Index (PASSMI) to improve the monitoring of spring agricultural drought in cold-region dryland agriculture. PASSMI was shown to be more sensitive than the conventional SSMI in identifying drought events and exhibited stronger consistency with actual agricultural drought impacts.
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Xu et al. (2026) Moderate substitution with organic fertilizer and crushed straw increases maize yield and water productivity by improving soil water-nitrogen coordination
This study evaluates the effects of moderate substitution with organic fertilizer and crushed straw on maize yield and water productivity in newly reclaimed farmland. Results show that combining organic fertilizer and crushed straw (FS1) increases soil water content and nitrate nitrogen content by 3.38–6.61% and 2.13–10.48%, respectively, compared to chemical fertilizer only.
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Liu et al. (2026) Modeling maize productivity and N2O emissions under surface and subsurface drip fertigation in current and future climates
This study evaluates the performance of the DeNitrification-DeComposition model (DNDCv.CAN) in simulating maize yield and N2O emissions under different drip fertigation systems and N sources in Mediterranean conditions. The model is then used to project future climate scenarios and identify potential drivers of yield loss and N2O increase.
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Feng et al. (2026) Divergent vegetation recovery shaped by drought, heat and compound extremes
This study assesses the impacts of compound drought and heat extremes (CDHEs) on vegetation recovery at the basin scale. The results show that CDHEs have increased globally since 1982, with a notable shift from wet-cold to dry-heat conditions. Vegetation generally exhibits lower resistance, slower recovery rates, and longer recovery times following drought than following CDHEs or heat events.
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Vorobeva et al. (2026) On the reliability of seasonal snow forecasts
This study evaluates the reliability of seasonal snow forecasts produced by the ECMWF, a state-of-the-art ensemble dynamical prediction system. The reliability assessment is performed using two independent SWE datasets: ERA5-Land and ESA Snow-CCI v4.
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Lei et al. (2026) Process diagnostics of snowmelt runoff in global hydrological and land surface models – Part 1: A systematic evaluation across basins of increasing complexity
This study evaluates the performance of 15 state-of-the-art large-scale runoff models and data products in simulating snowmelt runoff across 1455 snow-dominated basins worldwide. The results reveal that most models exhibit underestimated total volume and peak flow, and predict centroid timing too early.
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Zheng (2026) Origin of underestimated Indian Ocean Dipole teleconnections to Australia in CMIP6 models
This study investigates the Indian Ocean Dipole's (IOD) impact on the Australian climate and identifies biases in current climate models that overestimate IOD amplitude and underestimate remote effects. The research reveals that correcting spatial biases in tropical diabatic heating is crucial for reliable regional climate predictions.
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Lin et al. (2026) Hydroclimatic Regime Shift Weakens Snowmelt Regulation of Summer Heat Extremes in Northern China
This study investigates the impact of hydroclimatic changes on summer heat extremes in northern China, revealing a weakened regulation of land-surface moisture buffering by cumulative spring snowmelt.
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Mu et al. (2026) Convection‐Permitting Projections of Low‐Level Jets and Mesoscale Convective Systems in South America
This study examines the impact of climate change on low-level jets (LLJs) and mesoscale convective systems (MCSs) in South America, revealing a transition toward complex hydrometeorological hazards. The results highlight thermodynamic intensification of MCS precipitation and dynamic bifurcations between the tropics and subtropics.
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Xie et al. (2026) Warming-driven rise in soil moisture entropy signals growing instability risk in the Asian Water Tower
This study applies an entropy-based framework to quantify the structural organization of soil moisture (SM) over the Tibetan Plateau (TP), revealing a long-term decline in entropy under wetting conditions. The results suggest that while current wetting provides a stabilizing buffer, continued warming is projected to amplify spatial heterogeneity and elevate instability risk.
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Decayeux et al. (2026) Representation of the nitrogen cycle and its coupling with the carbon cycle in ISBA (SURFEX v9) the land surface model: evaluation using two Free-Air CO 2 Enrichment experiment sites
This study presents the implementation of an explicit nitrogen cycle in the ISBA land surface model. The new version, called CN, is evaluated using data from two Free-Air CO2 Enrichment (FACE) experiment sites: Duke and Oak Ridge.
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Zhang et al. (2026) Large‐Scale Extreme Precipitation Events Increasingly Drive River Discharge Extremes in the Yangtze River Basin
This study analyzes the evolution of extreme precipitation events (EPEs) of varying spatial scales in the Yangtze River Basin from 1960 to 2024, finding that larger-scale events are increasing in frequency and intensity, thereby driving higher hydrological flood risks.
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Yang et al. (2026) Improvement of riming process parameterization in the WRF model and its advantages in simulating precipitation over the Tibetan Plateau
This study improves the riming parameterization within the WRF Morrison scheme by adopting constant reduction coefficients and introducing a diagnostic mixing homogeneity parameter χ for snow and graupel. The modified scheme shows superior performance in simulating precipitation over the Tibetan Plateau.
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Mulangwa et al. (2026) Lake Victoria to the Sudd Wetland: flood wave timing, connectivity and wetland buffering across the White Nile
This study quantifies system-scale flood-wave transit time from Lake Victoria to the Sudd Wetland in the White Nile Basin. The results show that flood waves take approximately 17 months to travel through the system, much longer than previously thought.
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DAI et al. (2026) Drought-flood abrupt alternation in the Haihe Plain: Synoptic circulation patterns and yield impacts on summer maize
This study investigates the characteristics and impacts of drought-flood abrupt alternation (DFAA) events on summer maize yield in the Haihe Plain. The results show that DFAA events occur frequently during the summer maize growing season, with a significant increase in frequency and duration over the past decade.
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Oveisgharan et al. (2026) Using LIDAR and SNOTEL data for evaluating the performance of snow water equivalent retrieval using Sentinel-1 repeat-pass interferometry
This study evaluates the performance of Sentinel-1 repeat-pass interferometry for snow water equivalent (SWE) retrieval using airborne LIDAR snow depth data and in situ SNOTEL SWE observations across diverse snow climates in the western United States.
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Peña-Arancibia et al. (2026) Integrating Landsat-based irrigation mapping and actual evapotranspiration estimates with hydrological modelling to assess regional irrigation dynamics in a large basin experiencing extreme climate variability: Towards a national operational irrigation water accounting system
This research developed a multi-decadal (1987–2024), high-resolution (approximately 30 m) remote sensing framework to quantify irrigation water-use (IWU) dynamics across Australia's Murray-Darling Basin. The framework successfully produced maps of irrigated extent, phenology, and net IWU, revealing distinct regional responses to climate variability and policy changes.
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Cui et al. (2026) Runoff thresholds, runoff generation mechanisms, and catchment characteristics: a global synthesis
This study synthesizes reported storm-runoff thresholds from 138 experimental catchments worldwide, linking threshold indicators, dominant runoff generation mechanisms, wetness-dependent mechanism transitions, and soil–geology–hydrogeology contexts within a common analytical framework.
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Wang et al. (2026) A synergetic framework for land-atmosphere coupling-based remote sensing inversion of evapotranspiration, surface resistance, and aerodynamic resistance
This study proposes a remote sensing-based ET coupling estimation framework (ETC framework) that simultaneously estimates evapotranspiration (ET), surface resistance (rs), and aerodynamic resistance (rae) with the land-atmosphere coupling coefficient (Ω) clarifying their coupling relationships. The ETC framework demonstrates high accuracy in ET estimation, outperforming conventional products at various spatial scales.
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Casas et al. (2026) Using machine learning for the prediction of flood-related 112 calls
This study proposes an ML methodology for predicting flood-related impacts using emergency calls as the target variable. The model combines rainfall-related weather data, information on recent emergencies, and static vulnerability-exposure layers to predict flood-related impacts at a municipal and hourly resolution.
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Patil et al. (2026) Phase Transitions in Climate Network Unravel the Large-Scale Onset and Withdrawal of Indian Monsoon
This study proposes a novel transdisciplinary approach to define the onset and withdrawal of the Indian monsoon at every location by tracking the largest cluster of rainfall onsets in a climate network. The research establishes monsoon as a phase transition in the framework of climate networks.
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Yu et al. (2026) A Pure Data‐Driven Fully Distributed Model for Spatially Consistent Streamflow Prediction
This study presents a purely machine learning-based model for fully distributed streamflow prediction, demonstrating its potential in ungauged basins with high spatial consistency. The model outperforms benchmark models with routing modules.
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Chintala et al. (2026) From leaf, canopy to ecosystem: Multi-scale dynamics and drivers of maize water use efficiency in semi-arid tropics
This study investigates the dynamics and drivers of water use efficiency in maize crops under alternate furrow irrigation and conventional furrow irrigation across monsoon and winter seasons at leaf, canopy, and ecosystem scales.
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Gao et al. (2026) Physical continuous-simulation SWAT + framework to develop flow duration curves within the contiguous United States
This study implements a SWAT+ framework to predict Flow Duration Curves (FDCs) across the contiguous United States (CONUS), providing a tool to characterize streamflow regimes and watershed performance.
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Nguyen et al. (2026) The CMIP6-downscaled CORDEX-Southeast Asia (SEA) ensemble: evaluation and benchmarking for megacities of SEA
This study evaluates the performance of a 21-member ensemble of regional climate simulations for Southeast Asia (SEA) generated by dynamically downscaling Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs). The ensemble captures the spatial and seasonal rainfall distribution reasonably well but tends to substantially overestimate observed rainfall.
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Mamani et al. (2026) The role of global warming trend and tropical interannual variability as drivers of South America’s 2022–2024 climate extremes
This study decomposes regional climate anomalies in South America from 1998 to 2024 into Global Warming Trend and Tropical Interannual Variability components, highlighting their contributions to extreme events. The findings reveal that Tropical Interannual Variability played a significant role in precipitation variability associated with climate extremes across the continent.
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Sun et al. (2026) Progressive groundwater decoupling may drive a shift toward shallower and faster terrestrial water cycling
This study investigates the impact of sustained increases in evapotranspiration (ET) demand on groundwater connectivity and terrestrial water cycling. The results suggest that progressive groundwater decoupling drives a shift toward shallower and faster pathways.
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Li et al. (2026) UAV-based multispectral inversion models for soil moisture content across the whole growth cycle of mung bean using SHAP interpretation
This study proposes a synergistic optimization strategy for soil moisture monitoring in mung bean using UAV multispectral imagery at different flight altitudes and machine learning algorithms. The results show that the optimal model varies across growth stages and soil layers.
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Lecacheux et al. (2026) Investigating metamodeling capability to predict sea levels and marine flooding maps for early-warning systems: application on the Arcachon Lagoon (France)
This study investigates the capability of metamodeling to predict sea levels and marine flooding maps for early-warning systems. Three data-driven methodologies are compared: analog-based research from offshore metocean conditions, machine learning type metamodels to predict total water levels at the coast, and deep-learning techniques to predict marine flooding maps.
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Prakash et al. (2026) Locally relevant streamflow reanalysis using ensemble data assimilation and a gauge-based adaptive localization scheme
This study presents a novel streamflow Data Assimilation (DA) framework that combines Ensemble Kalman Filter (EnKF) with gauge-based covariance localization and targeted covariance inflation to improve high-resolution streamflow estimates in the Indian subcontinent.
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Wargo et al. (2026) Observed Decreases in Seasonal Drought across the Northeastern United States
This study examines observed decreases in seasonal drought across the Northeastern United States. The research reveals a decline in drought severity and frequency over the past few decades.
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Goddard et al. (2026) The Influence of Atmospheric River Seasonality and Orientation on Pacific Northwest Surface Temperatures
This study investigates the impact of atmospheric rivers on Pacific Northwest surface temperatures during summer and winter seasons, revealing that AR orientation influences temperature anomalies.
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Jin et al. (2026) Global escalation of more frequent and intense compound heatwave-extreme precipitation events
This study examines the changes in compound heatwave-extreme precipitation (CHWEP) events and their corresponding single extremes from 1980 to 2100 using climate observations and projections under SSP2-4.5 and SSP5-8.5 scenarios.
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Zhou et al. (2026) Boundary‐Aware Physical Constraints Refine Satellite Precipitation Occurrence Over the Qinghai‐Tibet Plateau
This study develops a physical-constraint framework to improve hourly satellite precipitation occurrence estimates over complex terrain by learning rainfall onset and cessation probabilities from environmental contrasts.
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Liu et al. (2026) Exploring Satellite Visible Band Observations for Quantitative Precipitation Estimation
This study presents a quantitative precipitation estimation framework that utilizes 2-km visible-band observations from the Himawari-8 geostationary satellite to improve high-resolution precipitation information. The results show improved precipitation-area delineation and false-alarm control compared to conventional single-time or single-band visible configurations.
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Nikta et al. (2026) Lagged global relationships between teleconnection indices and hydrological drought: a continental-scale analysis using ERA5-Land runoff data
This study evaluates the lagged correlation between five teleconnection indices and hydrological drought globally to identify optimal lag times for early drought detection. It finds that optimal lags are generally shorter at continental scales than at the global scale.
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Liu et al. (2026) A river-augmented highly parameterized linear inverse method for enhanced water table estimation across China
The study develops a river-augmented highly parameterized linear inverse method (HPLIMRG) that utilizes river-stage observations to improve the accuracy and reduce the uncertainty of water table mapping in regions where monitoring wells are scarce.
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Li et al. (2026) Physical Constraints on Future Tibetan Plateau Summer Precipitation: Emergent Relationships and Pareto Optimal Ensembles
This study utilizes emergent constraints and Pareto optimal ensemble selection on CMIP6 models to reduce uncertainty in summer precipitation projections for the Tibetan Plateau for the period 2051–2100.
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Mather et al. (2026) Where has all the energy gone? Quantifying advective energy fluxes with a dense tower network
The study investigates whether a high-density tower network can quantify advective energy fluxes to resolve the systematic energy imbalance observed in eddy covariance measurements.
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Khozani et al. (2026) Advancing River Water Level Prediction: A Comparative Machine Learning and Deep Learning Approach
This study developed four standalone machine learning models and a hybrid model to predict weekly water levels in the Rhine River, achieving remarkable accuracy with the hybrid LSTM-RF model outperforming standalone models.
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Aslan et al. (2026) Winter warming alters snow drought regimes and hydrological conditions: a case study from Türkiye
This study investigates the impact of climate change on global water resources by analyzing the effects of increasing temperatures and changing precipitation patterns on river discharge. The research reveals that climate change will lead to significant changes in river flow regimes worldwide.
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Zhang et al. (2026) Coupling reservoir supply potential with load allocation: A framework to enhance water supply security in multi-reservoir systems
This study presents a framework that links reservoir water-supply potential (RWSP) with reservoir water-supply load allocation (RWSLA) in multi-reservoir systems, providing a pre-operational load-configuration complement to conventional operation simulation. The framework is applied to five medium and small reservoirs in northeastern Chongqing, China.
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Karakiraz et al. (2026) Streamflow forecasting in the Eastern Black Sea Basin using a contrastive PSO-optimized transformer-LSTM framework
This study investigates the impact of climate change on global precipitation patterns using a high-resolution climate model. The research reveals significant changes in precipitation extremes over the 21st century, with increased frequency and severity of droughts and floods.
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Shirafkan et al. (2026) Improving water pixel detection in SWOT Pixel Cloud (PIXC) data over small reservoirs using machine learning methods
This study presents a machine learning-based framework to improve water pixel detection in SWOT Pixel Cloud (PIXC) data for reservoir monitoring applications by reducing false positive and false negative classifications.
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Han et al. (2026) Decoupling dry and wet heat contributions: a station-based index for detecting regional compound heat extremes
This study introduces the dynamic weather-climate index (DWCI), a novel framework that decomposes temperature, moisture-loading, and dry-evaporative-demand anomaly pathways to attribute contributions during compound heat events. DWCI is applied to identify 68,417 regional compound heat extremes globally from 1973-2024.
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Phuong et al. (2026) Development of localized climate projections for Vietnam’s Mekong Delta using univariate and multivariate bias corrections of CMIP6 simulations
This study applied bias correction methods to raw climate model simulations to develop localized climate projections for Vietnam's Mekong Delta, providing valuable insights for climate-sensitive planning and decision-making.
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Cai et al. (2026) CO 2 -altered evapotranspiration moderates future global dryland expansion under climate change
This study maps the global distribution of drylands, quantifies historical and future changes in dryland extent, and identifies drying and wetting hotspots under different emission scenarios using a CO 2 -modified PET framework. The results indicate that accounting for rising CO 2 effects moderates projected dryland expansion and alters the spatial pattern of drying and wetting hotspots.
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Krogh et al. (2026) The Major June 2023 Flood Event in Central Chile: Hydrometeorological Characterization and Rain-on-Snow Contribution
This study investigates the hydrometeorological characterization of the Major June 2023 Flood Event in Central Chile, with a focus on the contribution of rain-on-snow processes to the flood magnitude. The research reveals that the event was influenced by a combination of atmospheric and terrestrial factors.
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Liu et al. (2026) Global estimation of bankfull river discharge reveals distinct flood recurrences across climate zones
This study estimates global bankfull river discharge at ~1 km resolution using machine learning approaches and a recently developed hydrography. The results reveal distinct flood recurrences across climate zones, with median return periods ranging from 1.5 years in tropical regions to 4.3 years in arid regions.
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Nagavciuc et al. (2026) From Rare to Recurrent: Intensifying Hot–Dry Extremes Across Romania
This study quantifies the historical evolution and future projections of compound hot-dry months in Romania, revealing a significant increase in frequency and spatial extent, particularly in lowland regions, accelerating since the 1990s.
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Wu et al. (2026) Spatio-temporal variations in the sensitivity of forests to seasonal precipitation across Europe
This study utilizes long-term satellite data and machine learning to analyze the sensitivity of European forests to seasonal precipitation over two decades, finding that warming and increased vapor pressure deficit (VPD) amplify these sensitivities, particularly during summer and in low-elevation, warm-dry regions.
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Saraceni et al. (2026) Estimating Medicane Precipitation Hazard
This study aims to estimate the precipitation hazard of Medicane events in the Mediterranean region using a combination of numerical modeling and statistical analysis. The main finding is that the frequency and intensity of Medicane-related precipitation are expected to increase under future climate change scenarios.
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Zan et al. (2026) Assessment of agricultural water-saving potential in arid regions based on an integrated sustainable management framework
This study developed an integrated sustainable management framework to enhance water utilization coefficient while controlling soil salinity in arid regions. The framework couples a water-salt process simulation model with a multi-objective optimization algorithm (NSGA-II) to optimize agricultural water resource management.
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North et al. (2026) Hydrologic model parameter estimation in snow-dominated headwater catchments using multiple observation datasets
This study investigates the impact of alternative observations on hydrologic model parameter estimation in snow-dominated headwater catchments. The authors use a multi-observational sensitivity and uncertainty analysis to evaluate the effect of different observation datasets on model performance.
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Latos et al. (2026) Subseasonal forecasts of the MJO and convectively coupled equatorial waves in ACCESS‐S2 and GraphCast: A multi‐year analysis
This study evaluates the predictive skill of two contrasting approaches, ACCESS-S2 and GraphCast, in forecasting Madden–Julian Oscillation (MJO) and convectively coupled equatorial waves at subseasonal-to-seasonal time-scales. The results reveal distinct complementary capabilities between the two models.
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Zhong et al. (2026) Object-Based Analysis of Droughts and Flash Droughts as a Continuum
This study examines the continuum between droughts and flash droughts using an object-based analysis approach. The results show that flash droughts are a distinct category of droughts with unique characteristics, including rapid onset and short duration.
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Ma et al. (2026) Yield–water trade-offs of deficit irrigation in wheat in China: A meta-analysis across irrigation-reduction intensities and production levels
This study conducted a meta-analysis to evaluate the effects of deficit irrigation on wheat grain yield, actual crop evapotranspiration (ETc act), water productivity (WP), and yield components in China. The results showed that deficit irrigation significantly reduced grain yield, ETc act, spike number (SN), grain number per spike (GNPS), and thousand-grain weight (TGW), while WP was not significantly affected.
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Li et al. (2026) Domain-knowledge-guided deep learning for probabilistic precipitation downscaling over southeastern Tibetan Plateau
This study proposes a deep learning-based downscaling method, P-HPDNet, to predict probabilistic precipitation over the southeastern Tibetan Plateau. P-HPDNet incorporates domain knowledge and outperforms baseline models in capturing spatial and temporal dependencies.
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Singh et al. (2026) Comprehensive inter-comparison of generative AI models for super-resolution precipitation downscaling across hydroclimatic regimes
This study presents a comprehensive intercomparison of three deep-learning architectures for precipitation super-resolution downscaling: U-NET, WGAN, and DDPM. The models are evaluated using a perfect-model experimental design based on ERA5-Land precipitation fields over distinct hydroclimatic regimes in the United States.
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Xu et al. (2026) A Bellman equation-based unified framework for evaluating and optimizing reservoir hedging rules: Incorporating inflow temporal dependence and non-stationary environments
This study develops a unified framework for evaluating and optimizing reservoir hedging rules by incorporating inflow temporal dependence and non-stationary environments using the Bellman equation. The framework supports both the evaluation and optimization of hedging rules.
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Cai et al. (2026) Optimizing irrigation strategies for wheat–maize rotation in the North China Plain under future climate Scenarios: Balancing water use, yield, and carbon intensity
This study employed the APSIM model to simulate crop yields, water consumption (ET), and global warming potential (GWP) of a wheat–maize rotation system in the North China Plain from 1980 to 2060 under Shared Socioeconomic Pathways 2–4.5 (SSP245) and Shared Socioeconomic Pathways 5–8.5 (SSP585) scenarios, identifying optimal irrigation strategies that balance crop yields, water use, and carbon emissions.
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Dušek et al. (2026) Effect tracking and flux tracking to quantify preferential flow responses at the hillslope scale
This study combines effect tracking and flux tracking with a two-dimensional dual-continuum model to investigate hillslope runoff generation and water age composition under preferential flow conditions. The results show that stormflow responds rapidly during large rainfall events through activation of preferential flow paths, while smaller events produce weaker and delayed responses.
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Yang et al. (2026) Momentum Decoupling Drives Low‐Wind Events During Heatwaves in China: A Hybrid Explainable Machine Learning and Dynamical Modeling Approach
This study investigates the physical drivers of compound heatwave and low-wind (HW-LW) events in China using explainable machine learning and dynamical simulations. The results show that momentum decoupling is the primary cause of wind suppression during HW-LW events.
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Mekonnen et al. (2026) Multi-scale assessment of irrigation water use and supply in the Amibara Irrigation Scheme, Ethiopia using Landsat-derived evapotranspiration and field data
This study applied a remote sensing-based approach to quantify irrigation water use and supply in the Amibara Irrigation Scheme, Ethiopia. The findings support the development of targeted interventions to improve irrigation performance.
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Wang et al. (2026) Staged water–wetland dynamics in Yangtze-connected Poyang Lake driven by cross-basin compound disasters (1992–2024)
## Identification - **Journal:** Hydrological Sciences Journal - **Year:** 2026...
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Hussain et al. (2026) Climate Change Intensifies Cropland Drought Exposure in the Indus River Basin During the 21st Century
This study evaluates current and future cropland exposure to drought in the Indus River Basin (IRB), finding that exposure increases significantly over time, driven initially by climate change and subsequently by cropland expansion.
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Bandar et al. (2026) Long‐Term Changes in the Relative Contribution of Mediterranean Cyclones and Sudanese Lows to Precipitation Over Iraq (1954–2023)
This study examines the long-term trends in precipitation variability over Iraq driven by Mediterranean cyclone days and Sudanese low days, revealing a significant decrease in frequency and precipitation contributions of Mediterranean cyclones.
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Sugahara et al. (2026) Slope-weighted cost distance for modeling flood dynamics: a physics-informed random forest approach
This study proposes a novel physics-informed random forest framework that incorporates slope-weighted cost-distance features to model flood dynamics. The framework significantly outperforms static baselines and demonstrates reliable performance for hydrographs withheld from training.
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Islam et al. (2026) Assessment of urbanization's impact on 2020 extreme and prolonged heatwave episodes over Northwest Indian cities
This study analyzed a prolonged heatwave event in northwest Indian cities using in-situ observations, reanalysis data, and high-resolution WRF model products. The findings highlight the role of urbanization in exacerbating extreme heat conditions.
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Meng et al. (2026) Synergistic Effects of the Westerly and Asian Monsoon on Summer Rainfall in the Tarim Basin of Northwest China Under Different Climate Backgrounds
This study investigates the synergistic effects of the westerly and Asian monsoon on summer rainfall in the Tarim Basin, Northwest China, using 55-year reanalysis data from JRA-55 and monthly rainfall observations from 28 meteorological stations.
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Fabian et al. (2026) Climate-informed streamflow forecasting based on a Bayesian autoregressive exogenous stochastic volatility model and its use for hydrological drought forecasting
This study presents a Bayesian autoregressive exogenous stochastic volatility model for season-ahead streamflow forecasting in the context of South Korea's Soyang Dam. The proposed approach incorporates large-scale climate predictors and explicitly models time-varying variance through stochastic volatility.
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Cao et al. (2026) Hydraulic connectivity regulates the evaporation paradox and salinization in a semi-arid lake–groundwater system
This study investigates the role of hydraulic connectivity in regulating water and solute exchange between a semi-arid lake and groundwater system. The research reveals that high hydraulic connectivity can limit salinization despite strong evaporative forcing.
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Liu et al. (2026) An integrated framework for characterizing spatiotemporal dynamics of water footprints, water scarcities, water quantity–quality interdependences and coupled risks in a semiarid river basin
This study develops an integrated framework to characterize spatiotemporal dynamics of water footprints, water scarcities, water quantity-quality interdependences, and coupled risks in a semiarid river basin. The framework reveals clear differences among water scarcity types and their spatial-temporal patterns.
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Brendel (2026) Climate Transitions in the Argentine Pampas Exceed Global Rates and Reshape Crop Exposure: A Multi‐Period Köppen–Geiger Analysis (1901–2020)
This study analyzes Köppen–Geiger climate zone transitions in the Argentine Pampas from 1901 to 2020, revealing that the region is a mid-latitude climate change hotspot driven primarily by shifts in precipitation seasonality and the development of winter droughts.
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Wang et al. (2026) Skillful and interpretable ENSO prediction via a glass-box dynamical-deep learning model
This study presents a novel approach to ENSO prediction using a dynamical-deep learning model that achieves skillful predictions up to 19 months ahead while rendering all model terms explicit.
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Poudel et al. (2026) An argument for parsimony in differentiable hydrologic models
This study compares static and dynamic differentiable hydrologic models to evaluate their performance in predicting streamflow. The results show that static models can achieve comparable performance to dynamic models while being simpler and more interpretable.
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Guo et al. (2026) Atmospheric Blocking Pattern as the Primary Driver of Subseasonal Greenland Ice Sheet Summer Melt Variability
This study provides a systematic quantitative assessment of the contribution of subseasonal circulation processes to summer melting of the Greenland Ice Sheet, highlighting the dominance of blocking within this framework.
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Wan et al. (2026) Elevation-dependent hydrological vulnerability of lakes and reservoirs to evaporation loss in the Yarlung Zangbo River Basin, Tibetan Plateau
This study investigates the elevation-dependent hydrological vulnerability of lakes and reservoirs to evaporation loss in the Yarlung Zangbo River Basin, Tibetan Plateau. The results reveal that natural lakes exhibit a strong positive correlation with elevation, while artificial reservoirs show a negative altitudinal evaporative gradient.
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Dong et al. (2026) Rotational canal scheduling in two oasis irrigation districts using a weighted composite objective and a sigmoid-adaptive genetic algorithm
This study developed a constrained rotational scheduling framework that combines modeled canal seepage loss and trunk-canal discharge variance within a weighted composite objective. The framework was tested in the Zhangye and Shihezi oasis irrigation districts.
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Zhao et al. (2026) Event‐Based Detection and Attribution‐Oriented Diagnosis of Compound Hot–Drought Extremes in a Typical Region of Central North China
This study develops an event-based framework to detect and attribute warm-season compound hot-drought events in Central North China, revealing intensified risk in recent decades.
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Wen et al. (2026) Ecological water replenishment improves water quality and environmental capacity in a tributary of the Yellow River: insights from MIKE 21 coupled modeling
This study developed a coupled hydrodynamic-water quality model based on MIKE 21 to quantify the effects of ecological water replenishment scenarios on water quality and environmental capacity in the Yi River, a key tributary of the Yellow River Basin.
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Jiang et al. (2026) Legume-grass mixture synergistically boosts production, water use, and resilience in water-stressed artificial grasslands
This study investigates the synergistic effects of legume-grass mixture combined with mild deficit irrigation on forage productivity, quality, and water use efficiency in artificial grasslands. The results show that the mixture can buffer moisture fluctuations, promote soil organic matter accumulation, and improve forage yield and quality under water stress conditions.
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Gagliano et al. (2026) A global high-resolution dataset of snowmelt runoff onset timing from Sentinel-1 SAR, 2015–2024
This study presents a global high-resolution dataset of snowmelt runoff onset timing from Sentinel-1 SAR observations for the period 2015–2024. The dataset provides unprecedented detail for studying snowmelt runoff onset across snow-covered regions.
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Tan et al. (2026) Hydroclimatic extremes shift GPP–ET response structures despite rising water-use efficiency in woody and herbaceous ecosystems on the Qinghai–Tibet Plateau
This study examines the effects of hydroclimatic extremes on water-use efficiency (WUE) in woody and herbaceous ecosystems on the Qinghai–Tibet Plateau using remote-sensing and reanalysis data. The results show that WUE trends are influenced by changes in gross primary productivity (GPP) and evapotranspiration (ET), but do not necessarily indicate stronger carbon-water coupling or reduced sensitivity to hydroclimatic extremes.
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Guo et al. (2026) Changes in the tropical rainfall seasonal cycle dominated by mesoscale convective systems
This study investigates the impact of global warming on tropical rainfall seasonality using a high-resolution Earth system model coupled to a multiscale modeling framework. The results show that mesoscale convective systems (MCSs) dominate the future changes in both the amplitude and phase of tropical precipitation seasonal cycle.
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Boardman et al. (2026) Groundwater hysteresis increasingly decouples flowing network length from streamflow as snow shifts to rain
This study investigates the relationship between groundwater hysteresis and flowing stream network length (L) in response to climate change. The authors use a new version of the Distributed Hydrology Soil Vegetation Model (DHSVM) to simulate the effects of snow-to-rain transition on L-Q dynamics.
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Johnson (2026) Calibrated spatial uncertainty for Earth observation foundation models via Matérn-motivated latent stochastic regularization
This study introduces a Matérn-motivated latent stochastic regularization layer for frozen foundation model embeddings to quantify spatial uncertainty and improve prediction interval calibration in Earth observation foundation models.
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Hulkkonen et al. (2026) Europe’s extreme temperatures and rainfall in finer detail: strengths and limits of climate model downscaling
This study evaluates the accuracy and reliability of downscaled climate model outputs in Europe for extreme temperatures and rainfall. The results show that downscaling can add details to and increase the accuracy of modelled climate variables in Europe, but their reliability is variable- and region-dependent.
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Vorobevskii et al. (2026) The role of multivariate time-series consistency in micrometeorological forcing data for climate impact modelling
This study assesses the impact of dataset versioning and gap-filled micrometeorological forcing data on process-based climate impact models. The analysis focuses on the subdaily version of the physically based one-dimensional soil-plant-atmosphere model BROOK90, applied to the ICOS ecosystem site DE-Tha in Tharandt, Germany.
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Chen et al. (2026) Changes of Precipitation Extremes and Persistence Over the Tibetan Plateau Projected by a Convection‐Permitting Model
This study investigates the future changes in precipitation extremes and persistence over the Tibetan Plateau using a high-resolution convection-permitting model, finding consistent signals with coarser-resolution CMIP6 models but with significant differences in magnitude.
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Roque et al. (2026) Intercomparison of a Regional Climate Model Ensemble for Selected European Catchments
This study presents a coordinated intercomparison of ICON and TSMP1 regional climate model simulations over Europe (1990–2020) to analyze water cycle processes, revealing systematic biases and demonstrating that ICON generally outperforms TSMP1, with higher-resolution forcing and irrigation improving specific model performances.
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Han et al. (2026) Revealing Upstream Dam Operations under Information Asymmetry for Integrated Water Resources Management
This study develops a framework to infer upstream dam operations—including water levels, inflows, and releases—using only multi-source satellite observations and hydrological modeling to reduce information asymmetry in data-restricted transboundary basins.
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Bo et al. (2026) Physically Consistent Reconstruction of Sparse Scatterometer Ocean Surface Wind Fields Based on Physics‐Guided Generative Learning
The study develops a physics-guided generative learning network to reconstruct sea surface wind vector fields from sparse scatterometer data, ensuring physical consistency and high accuracy.
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Frehner et al. (2026) Revisiting energetic limits on crop coefficients in heterogeneous canopies
The paper challenges the widely accepted theoretical upper limit of the crop coefficient ($K_c$) of 1.2–1.3, arguing that this limit ignores the effects of advection and canopy heterogeneity on evapotranspiration (ET).
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Kim et al. (2026) SDMBCv2 (v1.0): correcting systematic biases in RCM inputs for future projection
This study evaluates the effectiveness of pre-downscaling bias correction in Regional Climate Models (RCMs) using a calibration/validation framework. The results show significant error reduction during the validation period compared to uncorrected Global Climate Model (GCM) data.
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Chang et al. (2026) Rapid Increases in Heat‐Driven Extreme Moisture Demand in the Southern Amazon
This study investigates the rapid increase in extreme vapor pressure deficit (EVPD) over the Southern Amazon during the dry season, attributing 93% and 64% of the increases to anthropogenic forcings. Climate models project a significant rise in EVPD intensities by the end of the century.
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Peeples et al. (2026) A hybrid machine learning and physics-based approach to model high-resolution inundation
This study proposes a hybrid machine learning and physics-based approach to model high-resolution inundation. The method combines coarse-resolution hydrologic modeling with machine learning downscaling to produce accurate 100 m resolution hourly binary inundation status at a significantly lower computational cost.
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Lunel et al. (2026) Systematic overestimation of evapotranspiration over irrigated areas by an offline land surface model
This study quantifies the systematic overestimation of evapotranspiration by offline Land Surface Models (LSMs) over irrigated areas due to their neglect of atmospheric feedback from irrigation, finding an average overestimation of 25%. It details the underlying physical processes and the dependence of this bias on LSM configuration and crop water stress.
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Chen et al. (2026) Predicting cotton yield and optimizing irrigation scheduling from coupled soil water–salinity dynamics
This study developed a numerical model to estimate crop yield by coupling soil water flow and salt transport simulations with an integrated plant water deficit index (PWDI) and a daily water deficit sensitivity index. The model was tested against a five-year cotton field experiment in Xinjiang, China, and a simulation-optimization framework was built to jointly optimize PWDI thresholds and irrigation quotas for triggering timely irrigation.
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Budamala et al. (2026) Hierarchical prediction of streamflow and organic carbon at event scale using a physics-guided AI hybrid framework
This study presents a physics-guided spatial-temporal hybrid framework (PhyST-HC) for hierarchical prediction of streamflow and organic carbon at event scale in agricultural watersheds. The framework integrates uncalibrated SWAT-C simulations with Graph Neural Networks (GNNs) and Transformer-based attention mechanisms.
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Wang et al. (2026) Soil water depletion intensifies ecosystem vulnerability in China’s drylands
This study develops a multidimensional framework to evaluate ecosystem vulnerability in China's drylands, integrating pressure, sensitivity, and resilience components. The research reveals that soil moisture depletion is the primary driver of increased ecosystem vulnerability.
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Caro et al. (2026) Comparative assessment of actual evapotranspiration partitioning models over an irrigated citrus orchard using remote sensing, agrometeorological, and micrometeorological data
This study compares the performance of different approaches for estimating actual evapotranspiration partitioning into soil evaporation and plant transpiration in an irrigated citrus orchard. The methods include a Soil Water Balance (SWB) model, a Surface Energy Balance (SEB) model, and an Eddy Covariance (EC)-based partitioning method.
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Wang et al. (2026) Rising dominance of vapor pressure deficit and carbon dioxide in vegetation drought on the Loess plateau
This study explores the drivers of vegetation drought on the Loess Plateau using a Standardized Vegetation Water Deficit Index (SVWDI) and machine learning-based attribution. The results show that precipitation-dominated vegetation drought in the early stage of the Grain for Green Project shifted to vapor pressure deficit (VPD) and carbon dioxide (CO2)-driven drought in recent years.
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Liu et al. (2026) Geospatial Foundation Embeddings as Transferable Catchment Descriptors
This study evaluates the use of geospatial foundation model embeddings as transferable catchment descriptors for rainfall-runoff modeling, achieving comparable performance to traditional attributes in a global prediction scenario.
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Yang et al. (2026) Contrasting roles of transpiration and interception evaporation in the evolution of interannual evapotranspiration variability across the Yangtze River Basin
This study investigates the evolution of interannual evapotranspiration variability across the Yangtze River Basin, focusing on the roles of transpiration and interception evaporation. The results reveal a basin-wide intensification of interannual ET variability driven primarily by enhanced variability in vegetation transpiration.
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Arouf et al. (2026) Observed Sc and Cu Cloud Variability and Feedback and Their Dependency to Environmental Factors
This study assesses the contributions of stratocumulus and cumulus clouds to low-cloud feedback on a global scale using observations and reanalyses. The results show that near-global low-cloud feedback is primarily controlled by surface warming and temperature inversions, driven by stratocumulus clouds.
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Liu et al. (2026) Evaluating flood responses with and without a reservoir module using the distributed Liuxihe hydrological model
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, leading to both droughts and floods.
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Zhao et al. (2026) Identification of key growth stages for cotton yield formation and SPAD response to irrigation thresholds using UAV multispectral data
This study utilized UAV multispectral data to identify growth stages associated with cotton yield variation and evaluated the response of SPAD values to different lower-limit irrigation thresholds. The results indicate that a flowering-boll lower irrigation threshold range of 60–70% FC may provide a practical reference for balancing canopy physiological status, yield formation, and water-management performance.
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Konold et al. (2026) BiasCast: learning and adjusting real time biases from meteorological forecasts to enhance runoff predictions
This study investigates training strategies and Long Short-Term Memory network architectures to mitigate meteorological forecast-induced bias in maximum daily discharge predictions. The results show that domain shifts between reanalysis and forecast data lead to substantial skill loss, with median Nash–Sutcliffe Efficiency decreasing from 0.58 to 0.33.
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Saminathan et al. (2026) A data driven approach for reference evapotranspiration forecasting: merging weather forecasts with persistence based Approaches
A data-driven approach is proposed to forecast reference evapotranspiration (ETo) by merging weather forecasts with persistence-based approaches, resulting in improved ETo forecasts compared to traditional Numerical Weather Prediction (NWP) models.
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Zou et al. (2026) A process-informed framework linking temperature-rainfall projections and urban flood modeling
This study presents a process-informed framework linking temperature-rainfall projections and urban flood modeling. The framework is designed to project future changes in regional storm and flood statistics under climate warming conditions.
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Rahimi et al. (2026) Bias Correction Can Strongly Shape California's Projected Megaflood Risk
This study investigates the impact of bias correction on dynamical downscaling simulations of California's megaflood risk under climate change, highlighting its crucial role in projecting rare, high-impact events.
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Paul et al. (2026) Can aerosols improve urban flood forecasting? A case study of 2015 Chennai extreme event
This study investigates the impact of aerosols on urban flood forecasting using a case study of the 2015 Chennai extreme event. The results show that explicit aerosol representation can improve the space-time simulation of rainfall and flooding for the EPF in Chennai and potentially for similar coastal megacities.
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You et al. (2026) Winter wheat yield responses to extreme heat in the North China Plain: GGCMI-AgMIP model evaluation and a heat-stress phenology improvement in JULES-crop
This study evaluates the performance of crop models in simulating winter wheat yield responses to climatic variability and extremes in the North China Plain. The analysis focuses on three growing-season climatic drivers: mean temperature, precipitation, and extreme heat days (𝐸𝐻𝐷). The results show that most GGCMI models fail to reproduce the observed negative linear yield response to 𝐸𝐻𝐷 in the central NCP. However, incorporating heat-stress effects into phenological development improves the simulated response of winter wheat yield to extreme heat.
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Xu et al. (2026) Dependence of subseasonal to seasonal precipitation prediction on atmospheric and land initial conditions in the Energy Exascale Earth System Model
This study investigates the impact of atmospheric and land initial conditions on Madden-Julian Oscillation (MJO) and subseasonal to seasonal (S2S) precipitation predictions using coupled atmosphere-land simulations in the Energy Exascale Earth System Model (E3SM). The results show that reanalysis-based initial conditions improve S2S precipitation simulations.
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Parra et al. (2026) Tackling water scarcity through treated wastewater in Patagonian steppe: Carbon assimilation, water use and fruit traits in olive trees
This study investigates the impact of using treated wastewater on the physiological performance and fruit characteristics in olive trees in southeast Patagonia. The results show that wastewater irrigation significantly enhances carbon assimilation, growth rates, and fruit traits compared to freshwater irrigation.
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Pavesi et al. (2026) The Portrait of Flood Risk in Italy: Past, Present and Future, From 1870 to 2100
This study assesses the impact of climate change and urbanization on flood risk in Italy over 230 years, from 1870 to 2100. The results indicate that while historical flood risk was driven by population growth and migration, future projections suggest climate change will dominate.
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Li et al. (2026) Precipitation amount versus precipitation phase: a threshold in precipitation-amount change governs the shift in their relative influence on snowmelt dynamics
This study investigates the relative importance of precipitation amount and temperature-driven precipitation phase transitions on snowmelt dynamics in Mongolia. The results show that a threshold of ±23 mm/decade in precipitation amount change governs the shift in dominant control on snowmelt variability.
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Semenova et al. (2026) Spatiotemporal Characteristics and Synoptic Patterns of Dry‐Hot Winds ( Sukhoviys ) in Ukraine
This study characterizes "sukhoviys" (dry-hot winds) in Ukraine from 1973 to 2025, identifying a predominance of short-duration events and an increasing trend in high-temperature episodes since 2007.
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Zhang et al. (2026) Why Does a Shallow Land Model Underestimate the Dryland Drying Trends?
This study improves the representation of terrestrial water storage declines in global drylands by incorporating deeper soils into a land surface model, leading to more accurate simulations and highlighting potential biases in groundwater assessments based on GRACE data.
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Wang et al. (2026) Watershed-scale sustainable groundwater management using an agent-based modeling approach to policy interventions and stakeholder dynamics
This study investigates sustainable water management strategies in a groundwater-dominant irrigated watershed using an agent-based modeling approach. The research evaluates the interactions among key stakeholders to support improved water resource management.
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Zonato et al. (2026) GLIDE-SOL: a GPU-accelerated global lightweight infrastructure for diagnostic environmental modeling with SOLWEIG
This paper introduces GLIDE-SOL, a GPU-accelerated global lightweight infrastructure for diagnostic environmental modeling with SOLWEIG. GLIDE-SOL operationalizes SOLWEIG for rapid and repeatable thermal-comfort mapping across diverse urban environments.
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Sakib et al. (2026) Machine learning in urban stormwater management: A review
This study presents a structured synthesis of machine learning (ML) approaches for urban stormwater modeling, focusing on their ability to address limitations in traditional models. The review highlights the potential of ML in predicting water quality, flow and discharge, infrastructure inspection, and real-time control.
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Wilson et al. (2026) Projections of Earth's Hottest Surface Temperatures in CMIP6
This study evaluates historical and future extreme heat events using CMIP6 simulations, comparing them with Berkeley Earth data, and projects changes under different scenarios.
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Noyelle et al. (2026) Does Oceanic Variability Explain the Intensity of Megadroughts and Megapluvials in the CESM2 Climate Model?
This study investigates the role of oceanic variability in explaining the intensity of megadroughts and megapluvials in the CESM2 climate model. The authors find that natural variability in the atmosphere is the primary driver of these events outside ENSO-influenced regions.
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Yap et al. (2026) Retrieving root-zone soil moisture from land surface modelling and GRACE/-FO and validating its dynamics with in-situ data over West Africa
This study investigates root-zone soil moisture (RZSM) dynamics across West Africa from 2003 to 2019 using multiple satellite-derived and model-based datasets. The results indicate that ESA CCI exhibits the strongest temporal and spatial alignment with ground measurements.
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Harshitha (2026) Satellite Imaging for Crop Yield Forecasting Using AI
This paper proposes an AI-based crop yield forecasting framework that utilizes satellite imagery and deep-learning techniques to improve accuracy, scalability, and timeliness in agricultural planning. The framework integrates multispectral and hyperspectral satellite image analysis with predictive analytics to estimate crop yields across large regions.
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Kokko et al. (2026) High resolution modelling of temporal and spatial dynamics in soil conditions in subarctic Finland using HydroBlocks model
This study configures the HydroBlocks model in subarctic and arctic Finland to estimate soil temperature and soil ice content at different depths with high spatial and temporal resolution. The results show that using local soil data from the Geological Survey of Finland improves the modeling accuracy.
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Coates et al. (2026) Evaluation of IMERG and CMORPH Satellite Precipitation Products with Respect to Extreme Precipitation from Subdaily to Multiday Accumulation Scales Against In Situ Reference Network
This study evaluates the accuracy of satellite precipitation products (SPPs) from CMORPH and IMERG against in-situ gauge measurements at various accumulation scales. The results show that both SPPs perform better at longer accumulation scales (>12 hours), but tend to underestimate extreme precipitation events.
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Fernández‐Alvarez et al. (2026) Brief communication: Atmospheric moisture and near-surface temperature anomalies: key drivers in the 2022 European mega-drought
This study reveals the dynamics driving the 2022 European mega-drought using an integrated Lagrangian moisture and temperature diagnostic framework. The research highlights a marked decoupling between atmospheric moisture availability and precipitation formation, with persistent anticyclonic circulation and large-scale subsidence suppressing precipitation contributions from Atlantic and Mediterranean sources.
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Fang et al. (2026) Optimizing Precipitation Gauge Networks for Hydrological Modeling Using High-Quality Reanalysis Data: A Spatial Pattern–Based Approach
This study presents a spatial pattern-based approach to optimize precipitation gauge networks using high-quality reanalysis data. The method aims to improve the accuracy of hydrological modeling by identifying the most informative locations for rain gauges.
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Feng et al. (2026) Global‐Regional AI Weather Forecasting on a Stretched Cubed Sphere
This study develops and evaluates two novel numerical weather prediction models, StretchCast, on a stretched cubed sphere mesh to improve regional weather forecasting. The results show improved forecast quality and continuity across face boundaries.
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Wang et al. (2026) Increasing Climate Constraint on Vegetation Productivity Under Rising CO 2 in Northeast Asia
This study investigates the future changes in gross primary productivity (GPP) over Northeast Asia under continued CO2 rise using CMIP6 Earth system models. The results show that GPP is projected to increase throughout the twenty-first century but its sensitivity to rising CO2 weakens markedly from early to late century.
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Liu et al. (2026) Biome-dependent forest GPP responses to compound drought and heat from 2001 to 2023
This study examines the joint response of forest gross primary production (GPP) to compound drought and heat events from 2001 to 2023 across five forest biomes. The results show that the interaction between drought and heat can lead to a more negative GPP anomaly than expected from their individual effects.
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Gou et al. (2026) Global Flash Drought Prediction Through Evaporative Stress Forecasting
This study presents a novel subseasonal global framework that integrates weather forecasts with a hybrid evaporation model to predict flash drought onset and termination up to 10 days in advance. The framework shows high skill in predicting persistence and termination, especially in semiarid regions.
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Derin et al. (2026) Environment-Conditioned Error Characterization of IMERG over Mountainous Terrain using Radar Networks
This study evaluates the performance of IMERG V07B Final Run (IM-F) over six mountain ranges using high-resolution radar-gauge precipitation data and environmental reanalysis parameters. The results show that environmental conditions strongly control precipitation distributions and satellite retrieval biases.
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Wang et al. (2026) FKDM: a frequency-guided Koopman dynamics model with heterogeneous mixture-of-experts for robust daily runoff forecasting under non-stationarity
This study proposes a novel end-to-end forecasting framework, the Frequency-guided Koopman Dynamics Model (FKDM), for robust daily runoff forecasting under non-stationarity. The FKDM exhibits superior performance compared to benchmark models.
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Cappellato et al. (2026) Where drought matters most: A crop calendar-aware index for prioritizing irrigated agricultural drought hotspots in Italy
This study introduces PRIME (PRiority Index for crop-season drought ManagemEnt), a crop calendar-aware index designed to rank irrigated agricultural areas according to their drought management priority. The index combines drought frequency derived from the Standardized Precipitation Evapotranspiration Index (SPEI) with irrigated crop distribution and gross production value.
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Kabakchieva et al. (2026) Digital Twin-Based Energy Management and Irrigation Optimization of PV-Powered Smart Agriculture Systems Using IoT Soil Monitoring
This study proposes a digital twin-based framework for energy management and irrigation optimization in photovoltaic-powered smart agriculture systems using IoT soil monitoring. The framework demonstrates high accuracy in synchronizing virtual models with physical system measurements.
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Deka et al. (2026) A Multi‐Model Ensemble Reveals a Diverging Hydrological Cycle in the Upper and Lower Transboundary Brahmaputra River Basin
This study uses a multi-model ensemble to assess the long-term trends and variability in the water budget components of the Brahmaputra basin from 1981 to 2020, revealing spatial divergence in the hydrological cycle.
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Wang et al. (2026) Declining Sensitivity and Increasing Resistance Time of Ecosystem Water Use Efficiency to Meteorological Drought
This study investigates the spatiotemporal patterns of the water-use efficiency (WUE) - meteorological drought coupling relationship across global terrestrial ecosystems from 1982 to 2018. The results indicate a weakening of the coupling between WUE and meteorological drought, with decreasing sensitivity of WUE to drought and increasing resistance time.
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Feng et al. (2026) Artificial intelligence-based response surface stochastic dynamic programming for long-term operation rule derivation of cascade hydropower reservoirs
This study presents a response surface-based stochastic dynamic programming (RSSDP) algorithm for long-term optimal power generation operation of hydropower reservoirs. The RSSDP method significantly improves computational efficiency while maintaining scheduling accuracy comparable to traditional stochastic dynamic programming.
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Saleh et al. (2026) Consistent relationships between model parameters and catchment attributes for multiple water balance models: a regionalization framework
## Identification - **Journal:** Hydrological Sciences Journal - **Year:** 2026...
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Xie et al. (2026) Topographic aspect shapes temperature lapse rates and land–atmosphere energy exchange in global mountains
This study investigates the influence of topographic aspect on temperature lapse rates (LRT) in global mountain regions using high-resolution satellite-derived land surface temperature observations. The results reveal pronounced spatial, seasonal, and diurnal variations of LRT across global mountain regions, with aspect-induced LRT variability being most pronounced during summer daytime.
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Wang et al. (2026) Unveiling the propagation and driving mechanisms of socioeconomic drought in the Aral Sea Basin: A vine copula and system dynamics ensemble simulation framework
This study develops a novel framework to simulate the propagation of socioeconomic drought in the Aral Sea Basin using vine copula and system dynamics ensemble simulation. The framework excels at simulating social water supply and demand, estimating drought propagation risks under various scenarios, and quantifying the impacts of human activities and climate change on drought propagation.
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Mun et al. (2026) Lag-aware integrated agricultural drought index using satellite precipitation products
This study proposes the integrated agricultural drought index (IADI), a lag-aware framework for spatially continuous agricultural drought assessment using satellite-based precipitation data over South Korea. The IADI combines drought event characteristics derived from run theory, objective weighting methods, and the quantified time-lag relationship between drought indices and observed agricultural drought occurrences.
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Li et al. (2026) Deep learning-based precipitation nowcasting integrating radar echoes and rain gauge data
This study presents a deep learning-based precipitation nowcasting model integrating radar echoes and rain gauge data to improve the accuracy of short-term heavy rainfall forecasts.
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Yurtseven et al. (2026) A Comprehensive Assessment of Drought Dynamics in Türkiye: An Integrated Spatiotemporal Analysis of Trends, Variability and Persistence
This study assesses drought dynamics in Türkiye from 1980 to 2022 using the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI), revealing a systematic divergence between SPI and SPEI series. The results indicate that precipitation-only drought assessment may be incomplete, highlighting the importance of incorporating evaporative demand.
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Tan et al. (2026) Balancing segmentation accuracy and hydrological plausibility in multi-source remote sensing flood inundation mapping with adaptive terrain-constrained learning
This study proposes an adaptive terrain-constrained learning framework to balance segmentation accuracy with hydrological plausibility in multi-source remote sensing flood inundation mapping.
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Hosseini et al. (2026) Equivalent Subsurface Thermal Characteristics for Heterogeneous Surfaces
This study presents a new formulation for estimating equivalent thermal properties of horizontally heterogeneous land surfaces, improving predictions of land-atmosphere exchanges in urban environments.
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Liu et al. (2026) Depth-dependent lag, persistence, and hydro-thermal coupling of soil moisture in a basin of Northern China
This study investigates the depth-dependent lag, persistence, and hydro-thermal coupling of soil moisture in a basin of Northern China using multi-site observations at five depths. The results show that SM persistence increases with depth, accompanied by stronger spatial heterogeneity.
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Song et al. (2026) Urban vegetation modulates compound hot-dry events across Chinese cities
This study investigates the role of urban greening in modulating compound hot-dry events (CHDEs) across Chinese cities from 2000 to 2024. The results show that urban vegetation has a significant negative association with CHDE frequency and intensity, particularly in central China.
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Yeşilköy et al. (2026) Projected changes in water demand and potential water savings for US grown rice under alternate wetting and drying practice
This study evaluates the water-use implications of alternate wetting and drying (AWD) irrigation compared with conventional continuous flooding in US rice production. The results show that AWD has the potential to reduce water use while sustaining high yields.
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Afzal et al. (2026) Projected depletion of high mountain Asia glaciers by 2100: linking mass loss to asynchronous peak runoff
This study projects the depletion of High Mountain Asia glaciers by 2100, linking mass loss to asynchronous peak runoff. The results show that glacier mass declines by 70.7 ± 9.6% by 2100 and total GR falls by 10 ± 6.5% between the early (2001–2020) and late (2081–2100) century periods.
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Li et al. (2026) A weakly supervised, wetness-based dynamic framework for wetland delineation across globally distributed sites
This study presents a weakly supervised, wetness-driven framework using earth observation data streams to improve wetland monitoring across regions represented by reference datasets. The framework achieved moderate spatial delineation accuracy and delivered the highest temporal accuracy.
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Dai et al. (2026) Stratospheric impacts on Eurasian soil moisture on subseasonal timescales
This study investigates the impact of sudden stratospheric warmings (SSWs) on Eurasian soil moisture on subseasonal timescales. The results show a robust dipolar soil moisture response to SSWs, characterized by wetter conditions over the Iberian Peninsula and drier conditions over Iran-Pak-NI.
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Kawase et al. (2026) Impact of global warming and anomalously high sea surface temperatures around Japan during a week-long heavy snowfall in February 2025
This study investigates the impacts of global warming and anomalously high sea surface temperatures on heavy snowfall in Japan during February 2025. The results show that past global warming increases precipitation by 7.8% and decreases snowfall by 2.0% over land areas below 100 m along the Sea of Japan coast, while high SST anomalies enhance precipitation and snowfall by 21.8% and 17.5%, respectively.
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Tshayu et al. (2026) Remote sensing–based assessment of seasonal agricultural drought dynamics using the integration of soil moisture and vegetation health index in Waghimra Zone, Ethiopia
This study integrates soil moisture and vegetation health indicators to assess agricultural drought dynamics in the Waghimra Zone, Ethiopia. The results reveal a strong seasonal relationship between soil moisture and vegetation health.
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Jahanshahi (2026) Hybrid modelling for forecasting daily river streamflow in Iran
This study investigates the impact of climate change on water resources in a semi-arid region using a high-resolution hydrological model. The results show that climate change will lead to a significant decrease in water availability by 2050.
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Wu et al. (2026) Hierarchical multi-objective management of cascade reservoirs: coordinating long-term strategy and daily operation under hydrological variability
This study proposes a Multi-scale Socio-Economic-Environmental Reservoir Management framework to address the scale dilemma in large-scale cascade reservoir operation. The framework restores long-neglected ecological functions while enhancing economic benefits.
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Gleason et al. (2026) SWOT, empiricism, and river modelling
This study assesses the performance of global river models using Surface Water and Ocean Topography (SWOT) satellite measurements, highlighting areas where these models struggle and suggesting improvements.
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Basirifard et al. (2026) A hyperparameter tuning strategy for an LSTM model to simulate reservoir outflows: large-scale evaluation across 441 dams in the CONUS
This study presents a hyperparameter tuning strategy for an LSTM model to simulate reservoir outflows across 441 dams in the CONUS. The proposed method improves the accuracy of reservoir outflow simulations.
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Ramos‐Esteban et al. (2026) CMIP6 Historical Evaluation and Future Changes of Climate Extreme Indices at Regional Scale From the US ‐Mexico Border Region to Central America
This study evaluates seven climate extreme indices and assesses their potential changes in 15 regions of the CORDEX-CAM domain, projecting significant increases in temperature and precipitation extremes by 2080–2099.
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Dong et al. (2026) Convectively Coupled Kelvin Waves over the Congo Basin: Modulation by Land Characteristics
This study investigates the modulation of convectively coupled Kelvin waves over the Congo Basin by land characteristics. The research reveals that land surface properties significantly impact the propagation and intensity of these waves.
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Zhou et al. (2026) Global patterns and declines of precipitation persistence over the past six decades
This study examines global patterns and declines in precipitation persistence over the past six decades. The authors found a significant decline in precipitation persistence globally.
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Matiu et al. (2026) Statistical Downscaling of Daily Temperature and Precipitation From Regional Climate Models in Complex Mountain Terrain
This study presents a novel downscaling method based on principal components analysis (PCA) and evaluates its performance in capturing high-resolution climate information in mountainous regions. The results show that the PCA-based downscaling method performs well, especially for precipitation.
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Caroline et al. (2026) Water productivity and irrigation water management practices: A study of the Arkansas Irrigation Yield 'Most Crop per Drop' Contest
This study evaluates the impact of Irrigation Water Management (IWM) practices on water productivity in corn, soybean, and rice fields under producer-managed conditions. The results show that some IWM practices are associated with higher water productivity, driven primarily by yield gains rather than reductions in applied irrigation water.
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Liu et al. (2026) Increasing synchronized hourly heavy rainfall over South China reflects enhanced multi-cluster and multi-regional coactivity
This study examines the increasing synchronized hourly heavy rainfall over South China during the 1981-2020 pre-summer rainy season. The results show a significant increase in synchronized heavy-rain hours, equivalent to about +16.7% of the 40-year mean per decade.
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McGrath et al. (2026) Gamma Rays Signal the Vulnerability of Forest to Extreme Drought
This study demonstrates that airborne gamma-ray spectrometry (GRS) of potassium (40K) effectively predicts forest die-off during extreme drought-heat events by serving as a proxy for subsurface water storage capacity, enabling regional-scale vulnerability mapping.
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Nayak et al. (2026) Attention‐Based Stochastic Simulation of Climate‐Informed Spatiotemporal Flood Risk for Multisite Insurance Portfolios
This study introduces a multisite flood simulation framework that combines attention-based analog retrieval with stochastic generation to produce spatiotemporally coherent flood portfolios. The framework provides plausible out-of-sample flood risk catalogs for interannual-to-decadal insurance risk assessment and financial planning.
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Campos-Caba et al. (2026) Storm surge dynamics in the northern Adriatic Sea: comparing AI emulators with high-resolution numerical simulations
This study compares the performance of machine learning (ML) emulators with a high-resolution numerical simulation for storm surge prediction in the northern Adriatic Sea. The results show that even simple models like Multivariate Linear Regression (MLR), when trained with the corrected Mean Absolute Deviation squared (MADc2) loss function, can achieve comparable performance to advanced neural networks while remaining orders of magnitude faster.
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Hu et al. (2026) Drivers of flash flood frequency and intensity in the United States: a quantitative analysis of hydrometeorological interactions
This study investigates the drivers of flash flood frequency and intensity in the United States using a quantitative analysis of hydrometeorological interactions. The results reveal that land cover changes have remained stable over the past four decades, while precipitation emerges as the primary driver of streamflow changes.
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Liaqat et al. (2026) Beyond GRACE: Evaluating the benefits of NGGM and MAGIC for precipitation estimation over Europe
This study evaluates the benefits of Next Generation Gravity Mission (NGGM) and Mass Change And Geosciences International Constellation (MAGIC) for precipitation estimation over Europe. The results show that SM2RAIN algorithm exhibits satisfactory performance at a daily temporal resolution, with a mean correlation coefficient of 0.86.
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Sneddon et al. (2026) Atmospheric River Climatology for the South Atlantic Basin Using an Image Processing‐Based Methodology
This study introduces a new detection method for Atmospheric Rivers (ARs) in the South Atlantic, using an image-processing algorithm applied to ERA5 data. The research reveals that ARs occur all year round, with an average of 161 systems per year.
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Decharme et al. (2026) A process-based modeling of soil organic matter physical properties for land surface models – Part 2: Global land surface simulations and mineral soil compactness adjustment
This study evaluates the impact of a process-based framework for representing soil organic matter (SOM) physical properties on global land surface simulations using the ISBA-CTRIP modeling system. The framework improves the internal consistency of SOM representation in land surface models without requiring additional inputs or calibration.
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Kong et al. (2026) Integrating deep-learning detection and hydrological monitoring for driftwood flux estimation in a steep tropical watershed during a typhoon-driven flood
This study integrates deep-learning detection with hydrological monitoring to estimate driftwood flux in a steep tropical watershed during a typhoon-driven flood.
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Li et al. (2026) Predominant vegetation control on baseflow index variations across China’s climatic basins
This study investigates the spatiotemporal dynamics of baseflow index (BFI) across China's climatic basins and identifies vegetation greening as a dominant driver of BFI variability.
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He et al. (2026) The spatial distribution of farmland shelterbelts in desert oasis areas under water resource constraints: A study based on the SWAT model and scenario analysis
This study develops a multi-constraint spatial layout framework for afforestation in arid regions by integrating water surplus, habitat suitability, and suitable density constraints. The results show that the afforestation potential of Populus alba var. pyramidalis decreases gradually from the central irrigation zones toward the peripheries under two irrigation scenarios.
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Li et al. (2026) Cascade-reservoir impoundment reshapes event-scale flood–sediment responses upstream of the Three Gorges Reservoir: evidence from rainfall patterns and driver attribution
This study investigates the impact of cascade-reservoir impoundment on event-scale flood-sediment responses in the Three Gorges Reservoir (TGR) inflow region. The research reveals a decoupling between flood and sediment dynamics, with rainfall magnitude governing floods and spatial organization of rainfall and reservoir-induced sediment-supply limitation controlling sediment delivery.
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Tolley-Mann et al. (2026) Flowing cold and shallow: snowmelt controls on spring temperature and resilience to climate change
This study used a multi-tracer framework combining stable water isotopes, noble gases, and thermal budgeting to reconstruct recharge elevations, temperatures, and flow path depths of six major springs in Northern California's Cascade region. The results indicate that recharge occurs at high elevations (1800-2900 m) with cold recharge temperatures (1.5-7.0 °C), suggesting a significant warming of spring water as it flows through the subsurface.
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Sun et al. (2026) BiGRU-dXAJ: A hybrid hydrologic model enabling differentiable parameter learning for runoff simulation
This paper introduces BiGRU-dXAJ, a novel hybrid hydrologic model that integrates deep learning with a conceptual model, enabling differentiable parameter learning for enhanced runoff simulation.
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Qi et al. (2026) From temperature to VPD: shifting drivers of flash droughts amplify ecosystem risks in high-latitude cold climates
This study investigates the evolving drivers of flash droughts globally, revealing a fundamental shift from temperature to vapor pressure deficit (VPD) as the dominant trigger in high-latitude cold zones, amplifying ecosystem risks.
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Ananda et al. (2026) Emitter depth variation in the sub-surface drip irrigation system based on emitters with flannel cloth on the growth quality of spinach (Amaranthus sp.)
This study investigates the effects of subsurface drip irrigation on soil moisture, water use efficiency, and plant growth in spinach (Amaranthus sp.). The results show that a 6 cm emitter depth is optimal for maintaining stable soil moisture and supporting optimal plant growth.
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Cao et al. (2026) A Driver‐Aware Machine Learning Approach for Predicting the Severity of Decadal‐Scale Extreme Climate Events
The study proposes an integrated framework combining driver analysis and machine learning methods to predict extreme climate event severities at the basin scale. The results show that long-term signals of global warming, AMO, PDO, SOI, and other climate drivers significantly influence extreme wet and dry events in the Yellow River Basin.
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Thomas et al. (2026) Technical note: Temperature dependence of precipitation tail heaviness in the TENAX model
This study investigates the temperature dependence of precipitation tail heaviness in the TENAX model using hourly data from thousands of rain gauges in Germany, Japan, the UK, and the USA. The results show a significant dependence on temperature in many locations, with the majority of stations having negative b values indicating that rarer extremes tend to intensify faster than milder ones.
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Krishnan et al. (2026) Soil vertical heterogeneity reduces rootzone soil moisture bias in hyper-resolution land surface model over smallholder agricultural systems
This study evaluates the impact of incorporating vertically heterogeneous soil properties into a hyper-resolution land surface model (HydroBlocks) on rootzone soil moisture simulations in smallholder agricultural systems. The results show that representing soil texture as vertically heterogeneous reduces systematic bias in rootzone soil moisture simulations compared to the homogeneous assumption.
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Perez et al. (2026) How changes in river geometry impact flood hazard in Brazil
This study investigates the impact of climate change on global water resources using a high-resolution hydrological model. The main finding is that future warming will lead to significant changes in precipitation patterns and river discharge, with potential consequences for water scarcity and flooding.
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Yu et al. (2026) Resolving effects of leaf pigmentation changes and plant residue on the energy balance of winter wheat cultivation in the ORCHIDEE-CROP model
This study improves the representation of albedo dynamics in the ORCHIDEE-CROP model by incorporating time-varying albedo from crop pigmentation during foliar yellowing and post-harvest crop residue soil cover. The results show that incorporating these processes can increase surface albedo by 0.07 ± 0.03 and induce surface cooling by −1.55 ± 0.93 °C.
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Wu et al. (2026) UAV multispectral data and mixed-pixel segmentation for citrus water deficit diagnosis: Integrating spectral–texture features with machine learning for precision irrigation management
This study developed a novel citrus water status monitoring strategy by integrating UAV multispectral imagery and Gaussian mixture model based mixed-pixel segmentation algorithm. The results demonstrated that the Random Forest model achieved the highest prediction accuracy for estimating citrus water content during four critical growth stages.
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Li et al. (2026) Harnessing multimodal UAV data and ensemble learning to improve estimation accuracy of winter wheat water content
This study employed multimodal UAV data and ensemble learning to improve the estimation accuracy of winter wheat water content. The results demonstrated that multimodal data fusion significantly enhanced the accuracy of PWC estimation.
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Wang et al. (2026) Precipitation Changes and Possible Mechanisms in the Global Arid Regions during the Last 40 Years
This study investigates precipitation changes in global arid regions over the last 40 years, analyzing possible mechanisms behind these trends. The research reveals a significant increase in precipitation extremes in dry regions.
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Sen et al. (2026) Benchmarking farmers’ irrigation decisions using farm competition data and a crop growth model
This study benchmarks actual farmer irrigation practices against optimal amounts for maize production in Nebraska using the DSSAT CERES-Maize model to quantify water management efficiency.
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Migliavacca et al. (2026) Monitoring Europe’s forests in a changing climate
This article discusses the application of remote sensing to monitor accelerating biomass loss in European forests, emphasizing the ability to distinguish between harvesting and natural disturbances to inform climate policy.
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Karlshöfer et al. (2026) Drivers of spectro-temporal variability in multi-spectral soil reflectance measured from space: A continental-scale analysis
This study investigates the drivers of spectro-temporal variability in multi-spectral soil reflectance measured from space at a continental scale. It analyzes seven-year time series of surface reflectance satellite imagery of Landsat 8 and Sentinel-2 at 27,819 LUCAS sites distributed across Europe.
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Geoffroy et al. (2026) Global Kilometer-Scale Simulations with ARP-GEM2: Effect of Parameterized Convection and Calibration
This study documents version 2 of the global atmospheric model ARP-GEM and its calibration at kilometer-scale resolution. The results indicate that parameterized convection still plays a significant role in representing the mean state at high resolutions.
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Viazzo et al. (2026) Characterizing individual and compound wind and precipitation extremes over southeastern South America: spatial variability, seasonality and weather types
This study characterizes compound wind and precipitation extremes over southeastern South America, assessing spatial and seasonal variability, seasonality, and weather types. The results show that CWPEs are frequent in eastern SESA, with more than 40% of PEs being CWPEs.
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Vogelbacher et al. (2026) Groundwater Variability Is Strongly Linked to Soil Temperature Across Global Aquifers
This study investigates the global relationship between groundwater table depth fluctuations and various land-surface processes, revealing significant correlations with soil temperature, evaporation, heatwave frequency, and soil moisture.
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Ojo et al. (2026) Machine Learning‐Based Correction of Reanalysis Surface Radiation Fluxes Using Ground‐Measured Data in the Southern Brazilian Pampa Biome
This study evaluates the performance of ERA-5 and MERRA-2 surface radiation products against hourly observations in Southern Brazilian Pampa, demonstrating that ERA-5 outperforms MERRA-2 for all radiation components. A regression model was developed for gap-filling using reanalysis predictors and refined with machine learning models.
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Ranjbar et al. (2026) Near real-time estimation of daytime and nighttime evapotranspiration using GOES-R observations and machine learning models
This study introduces a near real-time estimation framework for daytime and nighttime evapotranspiration using geostationary satellite observations from the GOES-R Advanced Baseline Imager (ABI) and machine learning models. The framework, called ALIVE ET, leverages high-frequency data to estimate sub-daily ET dynamics under both clear and cloudy conditions.
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Ramaswamy et al. (2026) Opportunities for bioenergy crops to support transitions from irrigated agriculture and conserve the U.S. High Plains Aquifer
This study investigates potential economic and groundwater-driven transitions from irrigated maize production to alternative crops such as sorghum and switchgrass in the U.S. High Plains Aquifer region. The results indicate significant regional variability in the future economic viability of irrigated agriculture, driven by differences in aquifer recharge rates, groundwater availability, and market conditions.
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Song et al. (2026) Why does El Niño develop slowly but decay rapidly
This study investigates the phase asymmetry between El Niño development and decay phases. The authors develop a mixed-layer heat budget framework to diagnose the thermodynamic and dynamical contributions to this asymmetry.
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Safre et al. (2026) Calibration and validation of the safer evapotranspiration model using Landsat 8 and eddy covariance data in vineyards
This study locally calibrated and validated the SAFER model for estimating actual evapotranspiration (ET a ) in California vineyards using Landsat 8 imagery and eddy covariance measurements. The results show that SAFER provides reliable estimates of daily ET a when locally calibrated.
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Li et al. (2026) Layer‐Dependent Diurnal Moist Static Energy Biases in the Unified Forecast System During the MJO Preconditioning Stage: A DYNAMO Case Study
This study applies a hierarchical modeling and evaluation approach to diagnose the vertical structure and diurnal evolution of moist static energy (MSE) in the Unified Forecast System (UFS), focusing on two Madden-Julian Oscillation (MJO) events from the DYNAMO field campaign. The results reveal a coherent, layer-dependent loop of interconnected physics deficiencies contributing to MSE biases.
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Franke et al. (2026) Drought propagation and ecosystem resilience in a peri-urban catchment of Berlin-Brandenburg
This study investigates drought dynamics and their effects on surface water, groundwater, and vegetation across the Tegeler Fliess catchment in Berlin/Brandenburg from November 2008 to April 2021. The analysis identifies station-specific drought events and their propagation across different parts of the hydrological system.
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Jin et al. (2026) Early hyperspectral diagnosis of canopy water content for productivity-risk and water-management screening in rainfed winter oilseed rape
This study developed a hyperspectral framework to estimate canopy water-related traits and assess the management relevance of canopy water content (CWC) under mulching and nitrogen treatments in rainfed winter oilseed rape. The framework showed that CWC was strongly associated with measured EWT and final SY and WP, suggesting its potential as a candidate canopy-scale proxy for productivity-risk screening.
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Li et al. (2026) Field-scale soil moisture retrieval from drone-based L-band radiometry with optical and thermal infrared priors
This study develops an uncertainty-aware Bayesian joint retrieval framework that integrates UAV L-band radiometry with RGB and thermal infrared information to improve field-scale soil moisture estimation under heterogeneous land-surface conditions.
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Li et al. (2026) A spectral-constrained HVCE framework for adaptive optical-SAR fusion to enhance soil moisture retrieval
This study proposes a spectral-constrained Helmert variance component estimation (HVCE) adaptive fusion framework for enhancing soil moisture retrieval from Sentinel-1 SAR and Sentinel-2 optical data. The framework outperforms conventional methods by preserving spatial-spectral fidelity while enhancing task-oriented information.
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Bäthke et al. (2026) Hysteresis between groundwater and surface water levels indicates the states of hydrological turnover affecting solute transport and redox processes
This study examines the relationship between hydrological turnover (HT) and stream-stage-groundwater-level hysteresis patterns under various system states in a third-order tributary of the River Mosel in Trier, Germany. The results reveal distinct seasonal dynamics in groundwater-surface water exchange, with counterclockwise hysteresis prevalent during summer and drought conditions.
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Gan et al. (2026) Spatially refined modeling for agricultural groundwater management in Northwestern China
This study proposes a spatially refined coupled surface water-groundwater (SW-GW) flow model to capture the spatiotemporal dynamics of groundwater response to surface irrigation at the farm-grid scale in the Qingtongxia Irrigation District. The model outperformed a coarse-resolution model in groundwater level simulation, reducing RMSE by 0.37 m during calibration and 0.24 m during validation.
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Guedes et al. (2026) Quantifying runoff contribution using wavelet–harmonic decomposition in an Amazonian tide-dominated estuary
This study investigates the impact of climate change on global precipitation patterns using a high-resolution atmospheric model. The main finding is that the model simulates an increase in extreme precipitation events worldwide.
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Luo et al. (2026) Gray‐Zone Simulation of the Dry Convective Boundary Layer Using Fourier Neural Operator
This study develops three-dimensional Fourier neural operator (FNO) models to simulate the dry convective boundary layer at 800-m grid spacing, outperforming traditional gray-zone simulations in predicting flow statistics and instantaneous structures.
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Zhao et al. (2026) Vertical Coherence Dominates Decadal Land Water Storage Change Despite Hydroclimatic Extremes and Groundwater Pumping
This study assesses the vertical organization of land water change across 78 million km² using satellite observations, finding that vertical coherence dominates but can be weakened by climatic and anthropogenic pressures.
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Wagener et al. (2026) Metrics that matter: objective functions and their impact on signature representation in conceptual hydrological models
This study systematically investigates the impact of objective function choice on the representation of various streamflow characteristics across 47 conceptual models and 10 hydro-climatically diverse catchments. The results show that objective function selection is often more influential than model structure choice in determining signature representation.
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Acosta et al. (2026) Exploring graph neural networks for flood modeling: Challenges, opportunities, and future prospects
This review synthesizes 49 peer-reviewed studies on Graph Neural Networks (GNNs) applications in flood modeling, identifying key gaps in physics incorporation, scalability, and cross-domain generalization. It outlines strategies to overcome these limitations and highlights the potential of GNNs as next-generation flood models.
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Gaudin et al. (2026) New classes of climate model emulators to improve paleoclimate reconstructions
This study proposes a new class of climate model emulators that integrate autoencoder-based dimensionality reduction with nonlinear prediction architectures to improve paleoclimate reconstructions. The proposed emulators are evaluated using a comprehensive experimental protocol applied to the IPSL-CM6A-LR model and 52 CMIP6 models, showing improved representation of El Niño Southern Oscillation and Atlantic Multidecadal Variability.
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Zheng et al. (2026) Underestimated climate contributions: Dynamic attribution of vegetation changes in China incorporating soil moisture and vapor pressure deficit
This study reassesses the contributions of climate change and human activities on vegetation dynamics in China by integrating vapor pressure deficit (VPD) and soil moisture (SM) into an attribution framework. The results show that incorporating VPD and SM significantly refines climate attribution, increasing climate-dominated areas from 21% to 53%.
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Manatsa et al. (2026) Multiscale ENSO and Indian Ocean Dipole Controls on Drought Across Mainland SADC : A Meridional Teleconnection Dipole, Its Seasonal and Sectoral Structure and a Domain‐Gated Readiness Index
This study evaluates the influence of the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on drought in the SADC mainland, identifying a meridional teleconnection dipole dominated by ENSO.
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Weng et al. (2026) Hydrological regimes and drainage systems of aerial rivers across South America
This study analyzes the drainage patterns of aerial rivers across South America and develops a mathematical method to identify turning points in moisture drainage curves. The research reveals four distinct drainage types, each characterized by a specific range of turning point thresholds, and provides insights into the management of aerial rivers for regional water resources.
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McJannet et al. (2026) Modelling a decade of daily open water evaporation for existing and planned water storages: A spatially explicit analysis for the Pilbara region of north-western Australia
This study models daily open water evaporation over a decade for existing and planned water storages in the Pilbara region of north-western Australia, providing spatially explicit analysis.
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Ho et al. (2026) Forecast-based operation of repurposed small reservoirs for floods, farms, and (low) flows
This study investigates the potential benefits of repurposing small flood reservoirs for drought protection when operating under forecasts, particularly under the constraint that the reservoir's flood protection function should not be compromised. The results show that many small flood reservoirs can maintain benefits above 40% even when optimized to operate under forecasts.
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Wen et al. (2026) Intensifying Short‐Interval Heatwave‐To‐Rainfall Compound Extremes and Associated Exposure in the Indus Basin
This study examines the frequency and characteristics of short-interval heat-to-rainfall sequences in the Indus Basin, projecting an increase in such events under future climate scenarios. The results highlight the potential impacts on irrigation-dependent basins and populations.
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Kumar et al. (2026) Integrated assessment of climate-induced variability in precipitation extremes in a tropical river basin
## Identification - **Journal:** Hydrological Sciences Journal - **Year:** 2026...
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Barroll et al. (2026) Teleconnections and Topography: How Snowpack Prediction Using Sea Surface Temperature Varies within the Colorado Rocky Mountains
This study investigates the relationship between sea surface temperature (SST) and snowpack prediction in the Colorado Rocky Mountains. The authors found that SST anomalies in the Pacific Ocean can predict snowpack accumulation in the region with high accuracy.
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Awasthi et al. (2026) Conditional simulation for max-stable processes (CoSim-MSP): A framework for flood prediction at ungauged basins
This study proposes a new framework called Conditional Simulation of Max-Stable Process (CoSim-MSP) to predict floods at ungauged basins based on observed extremes at neighboring gauges. The framework utilizes max-stable models that can produce unconditional simulations for a group of basins in a region and resamples conditional simulations from them, preserving spatial dependence structure.
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Liu et al. (2026) Precipitation nowcasting based on convolutional LSTM with spatio-temporal information transformation using multi-meteorological factors
This study proposes a novel dual encoder-decoder neural network (STI-DEDN) that enables the approximation of Spatio-Temporal Information Transformation (STI) equations and robust nonlinear mapping of high-dimensional meteorological and VIL precipitation variables. The model achieves superior predictive accuracy and reduced error rates in hourly multi-step forecasting compared to state-of-the-art deep learning benchmarks.
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Wang et al. (2026) Causal inference of nonlinear vegetation response to earlier seasonal thaw in a semi-arid mountain permafrost region
This study investigates the causal effects of permafrost thaw timing on vegetation growth in the Altai Mountains using a double machine learning framework with multi-source remote sensing data. The results indicate that mid-May acts as a critical phenological tipping point.
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Sharma et al. (2026) Kilometer‐Scale (1‐km) Convection‐Permitting Simulations Over the Hindu Kush‐Himalayan Region: Processes of Winter Precipitation
This study evaluates a kilometer-scale simulation initialized from ECMWF IFS analysis for winter precipitation over the Hindu Kush Himalayas region, highlighting its high fidelity to observed station-based precipitation magnitudes and spatial distribution.
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Zhou et al. (2026) Diverging hydrometeorological drivers of flashier floods in a warming climate
This study investigates the impact of climate warming on the drivers of flashier floods, revealing diverging hydrometeorological factors contributing to increased flood frequency and severity.
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Ullah et al. (2026) Regional Temperature Trends and Future Warming Risks in Pakistan Using Bias‐Corrected CMIP6 Ensembles and Machine Learning Techniques
This study enhances regional temperature projections for Pakistan by integrating CMIP6 models with Fuzzy C-Means clustering, statistical bias correction, and machine learning to provide localized climate insights.
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Hu et al. (2026) Beyond prediction accuracy: using differentiable hybrid models as a tool for hydrological knowledge discovery
This study introduces a closed "diagnosis-extraction-improvement" framework that repurposes differentiable hybrids to identify, correct, and theoretically advance structural deficiencies in traditional process-based hydrological models. The framework successfully identified the temperature- and daylength-based Hamon potential evapotranspiration (PET) formulation as the dominant structural bottleneck at the continental scale.
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Carruthers et al. (2026) Representation of Long‐Term Observed UK Winter Precipitation Trends and Variability in UKCP18 Global Climate Models
This study assesses the representation of long-term precipitation trends in UK winter mean precipitation, focusing on the separation of dynamical and non-dynamical components using a dynamical adjustment methodology. The results highlight limitations in the UKCP18 GCMs' ability to capture observed precipitation variability and change.
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Cordeiro et al. (2026) Assessing SWOT's capability for surface water extent mapping: An evaluation of Level-2 High-Rate Raster water fraction
This study assesses the Surface Water and Ocean Topography (SWOT) mission's capability for surface water extent mapping using Level-2 High-Rate Raster water fraction data. The results show a systematic positive bias in water fraction analysis and highlight limitations of the KaRIn sensor.
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Li et al. (2026) Sustained transpiration masks weakened canopy cooling and emerging carbon constraints during heatwaves in a riparian poplar plantation
This study investigates the responses of a riparian poplar plantation to heatwaves, focusing on transpiration, canopy cooling, and carbon uptake. The results show that sustained transpiration during heatwave conditions does not fully maintain canopy thermal buffering.
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Chen et al. (2026) Intensifying dry-to-wet extremes across Europe: long-term evolution and contrasting impacts on vegetation dynamics
This study presents a pan-European assessment of dry-to-wet extremes (DTWEs) and their impacts on terrestrial ecosystems. The analysis reveals a pronounced intensification of DTWEs across Europe, characterized by increasing spatial extent, frequency, and intensity.
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Liu et al. (2026) Differential response of floods to climate change and human activities in the Yalu River over the past two millennia: insights from hydrological modeling
This study reconstructs annual peak flow in the Yalu River over the past 2000 years using a hydrological model (HYDROTREND) and quantifies the differential impacts of climate change and human activities on floods of varying intensities.
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Liu et al. (2026) Land Surface Feedbacks Regulate Atmospheric Water Demand and Maintain Global Drying Stability
The study resolves the "aridity paradox" by revising the potential evaporation (PE) formulation to treat vapor pressure deficit (VPD) as a dynamic feedback rather than an external driver. This new approach indicates that global aridity will remain relatively stable under climate warming, contradicting previous projections of intensification.
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Mei et al. (2026) Diagnosing Cryospheric Runoff Dynamics: A Distributed Differentiable Hydrological Model With Global Transfer Learning
The study introduces dCREST, a differentiable physics-informed hydrological model, to improve runoff predictions in alpine regions by optimizing soil structure and utilizing global transfer learning to overcome local data scarcity.
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Bolsée et al. (2026) Corrigendum to “Wind flow dynamics over a photovoltaic power plant: Comparison with a vegetated canopy” [Agricultural and Forest Meteorology 388 (2026) 111306]
This document is a corrigendum that corrects a specific parameter value (transition scale $\lambda_c$) in a study comparing wind flow dynamics over a photovoltaic power plant and a vegetated canopy.
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Ragno et al. (2026) The Role of Structural and Transient Compoundness in Advancing Compound Event Characterization
The paper introduces the concepts of "structural compoundness" and "transient compoundness" to quantify the contributions of individual drivers to compound events, moving beyond a sole focus on statistical dependence.
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Ji et al. (2026) Reassessing Alpine Permafrost Thermal State by Accounting for Ground Ice
The study introduces an enthalpy-based metric ($\Delta H'$) to assess permafrost thermal state, demonstrating that it is superior to Mean Annual Ground Temperature (MAGT) because it accounts for the thermodynamic influence of ground ice.
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Pan et al. (2026) Estimating daily evapotranspiration from remotely sensed instantaneous observations with surface flux equilibrium (SFE) theory and maximum entropy production (MEP) principle
The study proposes a method to estimate daily evapotranspiration by utilizing instantaneous remote sensing observations through the application of surface flux equilibrium (SFE) theory and the maximum entropy production (MEP) principle.
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Vegad et al. (2026) Reconstructing Long‐Term Reservoir Storage in India Using Hydrological Modeling and Machine Learning
The study reconstructs long-term daily live storage for major reservoirs in India using a hybrid approach of hydrological modeling and machine learning, finding that normalized storage has moderately declined due to increased water withdrawals.
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Kang et al. (2026) Observations‐Driven Spatial‐Attention LSTM for Multi‐Depth Soil Moisture Prediction and Dynamic Soil Hydrological Process Connectivity Quantification
This study develops a Long Short-Term Memory model with time-varying spatial attention to predict multi-depth soil moisture and quantify vertical hydrological connectivity. The proposed framework outperforms existing models in deeper layers, providing novel insights into subsurface hydrology.
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Hövel et al. (2026) Spatiotemporal Drivers of Runoff Event Timescales: An Event‐Based Clustering Approach Applied to 388 Catchments in the Contiguous United States
This study investigates how hydro-meteorological event conditions and physical catchment attributes influence runoff event timescales in 388 snow-free catchments across the contiguous US, with a focus on contrasting climate types.
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Lyne et al. (2026) Automated Adaptive Baseflow Separation Across Australia's Catchments Using AutoVL
This study evaluates an automated self-calibrating baseflow-separation algorithm, AutoVL, to improve the estimation of streamflow components in diverse hydroclimatic regimes. The results demonstrate the method's capacity to adapt to differing streamflow dynamics.
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Chen et al. (2026) Overland Flow Dynamics on a Cracked Soil Slope Under Drying‐Wetting Cycles: An Integrated Hydrological and Infrared Thermographic Study
This study investigates the impact of desiccation cracking on overland flow and sediment transport in a laboratory setting. The results show that drying-wetting cycles accelerate moisture loss, promote crack development, and influence runoff generation and sediment yield.
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Parra et al. (2026) Validation of GRACE, ERA5-Land and MODIS remote sensing products for groundwater monitoring in semiarid regions: A multi-basin study in Chile’s Coquimbo region
This study validates the use of GRACE, ERA5-land and MODIS remote sensing products for groundwater monitoring in semiarid regions through a multi-basin analysis in Chile's Coquimbo region. The results show that these products can be used as reliable tools for groundwater management.
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Dallan et al. (2026) Climatology of Storm Characteristics for Sub‐Daily Heavy Precipitation in the Greater Alpine Region
This study develops a detailed climatology of precipitation and temperature time series for storms producing heavy rainfall across the Greater Alpine Region, highlighting systematic variations in storm characteristics with duration and geography.
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Voss et al. (2026) Winter Type, Mediated by Land‐Surface Processes, Controls Seasonal Discharge Variability in Culturally Critical Ecosystems in the US 's Upper Midwest
This study investigates the impact of winter snowpack on springtime discharge in the Upper Midwest, highlighting its crucial role in maintaining culturally important ecosystems, such as those supporting Manoomin (Wild Rice).
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Gomez-Tunque et al. (2026) Forecasting Coastal ENSO Warming in the Niño 1+2 Region Using ConvLSTM: Toward Improved Early Warning in Peru and Ecuador
This study develops a spatiotemporal Convolutional Long Short-Term Memory (ConvLSTM) model to forecast sea surface temperature anomalies (SSTA) at lead times of up to 6 months over the tropical Pacific, with a focus on the Niño 1+2 and Niño 3.4 regions.
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Banad et al. (2026) Effects of Climate Change on Ecologically Sensitive Flows in the Goulburn River Basin, Australia
This study evaluates the impact of projected climate change on ecologically sensitive flow characteristics in the Goulburn River, Australia, using a calibrated Soil and Water Assessment Tool (SWAT) model. The results indicate increasing risks to habitat persistence and ecological processes under both RCP4.5 and RCP8.5 scenarios.
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Facchinetti et al. (2026) Modelling High‐Alpine Karst Runoff With Coupled Snow Models of Different Complexity Levels at Mount Zugspitze
This study compares two model configurations for simulating discharge in a high-alpine karst catchment, highlighting the advantages of combining snow and routing models for improved process-level understanding.
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Cristea et al. (2026) Sensitivity of Spatial Snowmelt Simulations to Radiative Forcing and Model Top Layer Thickness
This study investigates the importance of energy balance considerations in snow modeling by examining the impact of model parameters on simulated snowmelt initiation and rate. The results highlight the significance of incorporating multiple validation data sources, including snow surface temperature.
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Solanki et al. (2026) One to Three‐Day Lead Streamflow Forecast Using Multi‐Head Attention With Long Short‐Term Memory in Reservoir Regulated Catchment
This study proposes a novel sequential LSTM with Multi-Head Attention (SeqLSTM-MHA) model to improve 1–3 day ahead flood forecasts by explicitly using historical hydrometeorological and upstream hydrological observations.
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Çelik et al. (2026) Snowmelt‐Associated Inundation Dynamics in a Semi‐Arid Floodplain: Evidence From Multi‐Temporal Sentinel‐1 Observations in the Aras Basin, Eastern Türkiye
This study investigates the relative contributions of snowmelt and rainfall to flood generation in semi-arid basins surrounded by seasonally snow-covered mountains in eastern Anatolia. The results show that inundation is more closely associated with seasonal snow accumulation and melting than with rainfall.
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Tian et al. (2026) Quantifying Ecohydrological Responses to Large‐Scale Vegetation Restoration by Incorporating Dynamic Root Processes
This study investigates the effects of vegetation restoration on ecohydrological processes in water-limited regions using a dynamic vegetation scheme and a prognostic root module. The results highlight trade-offs between ecological benefits and water availability.
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Sun et al. (2026) A novel approach for predicting soil water storage in agricultural areas: An optimized stacked ensemble model based on variational mode decomposition and empirical wavelet transform
This study developed a novel approach to predict soil water storage in agricultural areas using an optimized stacked ensemble model based on variational mode decomposition and empirical wavelet transform. The model was applied to the Songnen Plain in Northeast China from 1982-2024 and showed high accuracy in predicting spatiotemporal evolution of soil reservoirs.
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Nath et al. (2026) Replacing Tunable Parameters in Weather and Climate Models With State‐Dependent Functions Using Reinforcement Learning
This study presents a framework that uses reinforcement learning to learn components of parametrization schemes online as a function of the evolving model state, achieving skillful and stable convergence in idealized testbeds.
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Keppler et al. (2026) Learning 2D Shallow Water Equations With Physics‐Informed Neural Operator Networks
This study explores the application of Physics-Informed Neural Operators (PINOs) for solving 2D shallow water equations in flood modeling, demonstrating improved computational efficiency and accuracy compared to traditional numerical solvers.
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Roy et al. (2026) Applying Transfer Learning for Street‐Scale Nuisance Flood Forecasting in Coastal‐Urban Environments
This study investigates the use of Transfer Learning (TL) for street-scale nuisance flood forecasting by exploring whether an ML model trained on one set of streets can effectively forecast flooding for another set of streets in the same city. The results show that TL is most effective when target data is limited.
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Ghimire (2026) Root System Architecture That Improves Water Use Efficiency and Yield of Cotton
This study identified beneficial root traits associated with water use efficiency (WUE) in upland cotton and highlighted the importance of adaptive root system architecture for drought resilience.
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Silwimba et al. (2026) Efficient Emulation, Uncertainty Quantification, and Sensitivity Analysis for a Land Surface Model Using Evidential Deep Learning
This study presents an evidential deep neural network (EDNN) emulator that efficiently reproduces leaf area index (LAI) variability and uncertainties from a large ensemble of Community Land Model version 5 (CLM5) simulations. The EDNN captures seasonal cycles, interannual variability, and dominant controls on LAI variability.
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Bischof et al. (2026) Scaling and Uncertainty in Soil Moisture Modelling: A Probabilistic Deep Learning Perspective
This study applies a probabilistic deep learning framework to model soil moisture dynamics and uncertainty across the contiguous United States, revealing systematic biases in absolute volumetric water content and coherent spatial organization controlled by physiography and soil texture.
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Hosseini et al. (2026) Food, Energy, and Health Implications of Agrivoltaic Farms
This study introduces a multiphysics model to design and optimize agrivoltaics (AV) systems for specific crop types, micro-environments, and panel configurations. The model predicts various benefits of AV, including reduced daytime panel temperature, increased thermal energy recovery, and decreased transpiration losses.
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Gupta et al. (2026) Soil Hydraulic Properties of Europe at 500 m Resolution for Topsoil Using EUPTFv2 and LUCAS Soil Data
This study presents a spatial dataset of soil hydraulic properties for Europe, developed using harmonised soil property maps and improved pedotransfer functions.
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Brus et al. (2026) A Subgrid Correction Scheme for Accurate km‐Scale Coastal Inundation in the Energy Exascale Earth System Model
This study introduces subgrid scale corrections into a 2-D barotropic ocean model to improve the representation of coastal exchanges and flooding. The results show that these corrections can lead to significant speedup in simulations while maintaining accuracy.
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Luna‐Niño et al. (2026) Tropical Pacific teleconnection to Southwestern US precipitation in the historical observations and climate change projections
This study evaluates the representation of the ENSO-SWUS precipitation teleconnection in CMIP6 models and explores its future variability under climate change. The results show that while models reproduce a wide range of teleconnection strengths, most overrepresent the canonical ENSO influence on SWUS precipitation.
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Ouyang et al. (2026) A Hierarchical Deep Learning Framework for Runoff Prediction Using Raster‐Based Spatial Representations
This study develops a hierarchical deep learning framework to investigate the effect of increasingly explicit spatial encoding on temporal generalization and spatial transferability in large-sample runoff prediction models. The results show that incorporating intermediate spatial structure via fixed-grid encoding provides the clearest benefits, but this advantage weakens under spatial holdout.
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Fukuda et al. (2026) Attribution of Future Water Stress in a Two‐Way Coupled Socioeconomic–Hydrological Framework
This study developed a two-way coupled socioeconomic-hydrological framework to capture dynamic feedbacks between water demand and hydrological processes. The framework was used to decompose future changes in water stress into socioeconomic and hydrological contributions.
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Yu et al. (2026) Optimizing the Rainwater Harvesting and Roof Sprinkling System to Adapt to Urban Extreme Heat
This study proposes an adaptation strategy integrating rainwater harvesting tanks with roof sprinkling to enhance urban heat resilience and evaluates its efficacy using a new module in the Community Land Model Urban (CLMU). The results show that the optimal strategies can reduce cooling energy demand, lower extreme temperatures, and decrease heatwave days.
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Xu et al. (2026) Singapore Water Budget: The Past, the Present, and the Future
This study uses a distributed mechanistic ecohydrological model to quantify the impact of urbanization and climate change on hydrological budget components in Singapore. The results show that urbanization has significant effects on sensible heat flux, latent heat flux, total transpiration, and runoff.
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Jilong et al. (2026) Trend and attribution of runoff in upper reaches of Heihe River
This study quantitatively analyzed the response of runoff variation to climatic factors and human activities in the upper Heihe River Basin, finding an increasing trend in annual runoff from 1971 to 2022, predominantly driven by precipitation.
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Raza (2026) Deep CNN-Based Intelligent Framework for Soil Moisture Prediction and Smart Irrigation Across Diverse Soil Types
This study presents a Deep Convolutional Neural Network (Deep CNN)-based framework for soil moisture prediction and adaptive smart irrigation across diverse soil types. The proposed framework enhances water efficiency and contributes toward scalable precision agriculture solutions.
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Trnka et al. (2026) Climate‐Induced Severe Water Scarcity Events as Harbingers of Global Wheat Price
This study investigates the relationship between severe water scarcity events and global food prices, focusing on wheat as a case study. The results show that increasing greenhouse gas emissions lead to rising wheat prices due to expanding areas under severe water scarcity conditions.
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Ferguglia et al. (2026) A historical and future view of elevation-dependent precipitation change in CMIP6 models
This study assesses the ability of current-generation global climate models to capture elevation-dependent precipitation change (EDPC) in five mountain regions. The results show significant inter-model variability and region-specific EDPC patterns.
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Fu et al. (2026) Hot Droughts Increase the Likelihood and Impacts of Abrupt Drought‐to‐Pluvial Transitions Worldwide
This study investigates the impact of hot droughts on abrupt drought-to-pluvial transitions and their downstream effects, revealing a thermodynamic pathway through which hot droughts increase the likelihood and impacts of these events worldwide.
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Dror et al. (2026) Deforestation Triggers State‐Dependent Cloud Regimes in the Amazon
This study investigates the impact of deforestation on low-level cloudiness in the Amazon region during the dry season, revealing a state-dependent enhancement in cloudiness that varies with background atmospheric conditions.
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Alavi (2026) Development of an Automation System for Site-Specific Irrigation and Nitrogen Application Using a Center Pivot Irrigation System
This study developed an automated irrigation-fertigation system for large-scale cotton production, integrating sensor data acquisition, spatial and temporal variability analysis, and variable-rate N injection. The system was evaluated at a field scale and simulated county-wide to compare Variable-Rate Irrigation (VRI) and Fixed-Rate Irrigation (FRI) strategies.
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Xue et al. (2026) Characterization of aridity-humidity in farming-pastoral ecotone in Northern China from 1965 to 2020 based on SPEI
This study analyzed moisture evolution patterns in Northern China's farming-pastoral ecotone from 1965-2020, revealing a progressive humidification trend that supports vegetation enhancement, while also identifying specific seasonal and spatial drought risks.
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Pfleiderer et al. (2026) Heat Extremes Within Hot Summer Seasons Intensify More Than in Average Summers Under Global Warming
This study investigates changes in the persistence and intensity of temperature anomalies beyond summer mean temperature change, finding that these have increased considerably in 100-year summers due to small changes in soil moisture and land-atmosphere energy fluxes.
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Seubert et al. (2026) Global River Discharge Projections From a Large Multi‐Model Ensemble of CMIP6 and ISIMIP3b Simulations
This study assesses global changes in river flow under anthropogenic warming using a multi-model ensemble approach, combining online and offline simulations. The results show that annual mean and extreme river discharge are projected to decrease in some regions and increase in others.
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Sun et al. (2026) Synergistic Optimization of Real‐Time Control and Spatial Layout Can Enhance the Global Benefits of Urban Stormwater Storage Systems
This study presents a synergistic optimization framework for coordinating stormwater storage system designs with their operational intelligence to improve flood control performance under extreme rainfalls. The framework integrates predictive target flow allocation-based global control with the optimization of storage capacity distribution.
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Aich et al. (2026) Generating realistic global precipitation fields from modelled atmospheric circulation
This study presents a novel approach to generating accurate, high-resolution global daily precipitation fields using generative machine learning. The method combines a conditional diffusion model with a regression model and leverages interactions between global prognostic variables.
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Heijden et al. (2026) A Roadmap for Identifying and Interpreting Physical Processes and National Water Model Prediction Bias Associated With Baseflow Index Regimes Across the Contiguous United States
This study presents a framework linking observed baseflow dynamics to continental-scale hydrologic model performance, highlighting systematic biases in simulated low flow contributions across different watershed regimes.
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Fu et al. (2026) Grain Expansion in China's Drylands Secures Food but Intensifies Environmental Trade‐Offs
This study assessed the expansion of maize, wheat, and rice cultivation in China's drylands from 2000 to 2019, revealing that competitive yields were maintained through elevated inputs, potentially leading to a "high-yield trap."
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Bhardwaj (2026) Hydroclimatic Variability and Drought Driven Changes in Water Availability in the Southeastern United States
This dissertation investigates drought-driven changes in water availability across multiple spatial scales through a comprehensive analysis of climate models, hydrological modeling, and explainable machine learning. The study highlights the importance of considering interacting climatic, physiographic, land-surface, and model-structural controls when assessing drought risk and water availability.
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Williamson et al. (2026) Variability in the Vineyard: A Multi‐Method Approach in Determining Grapevine Evapotranspiration Across Different Varietal Blocks
This study investigates the variability of evapotranspiration (ET) in vineyards using a multi-method approach, combining atmometer ET gauges and the FAO-56 dual crop coefficient procedure. The research reveals significant differences in ET among various cultivars and sites.
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Hobeichi et al. (2026) Climate‐Mode Precursors and the Predictability of Amazon Hot and Dry Extremes
This study investigates the relationship between large-scale climate modes and Amazon climate extremes, identifying potential early warning signals for compound hot-dry events. The research reveals that certain climate indices can predict these events with skillful forecasts up to 7 months in advance.
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Neto et al. (2026) From Situation to Decision: A Transferable Graphical Decision-Support Framework for Water Allocation in Arid and Semiarid Reservoir Systems
This study proposes a decision-support framework that integrates hydrological data and reservoir morphometry to support water allocation under uncertainty in arid and semiarid regions. The framework generates graphical allocation abaci that relate initial storage, demand, and planning horizon.
