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Torres et al. (2025) Desinformación y catástrofes naturales. El caso de la Dana de Valencia en 2024
This study analyzes disinformation surrounding the 2024 DANA floods in Valencia, Spain, revealing that false narratives peaked immediately after the catastrophe, primarily spread via social media by influential accounts, targeting institutional management and fostering mistrust and polarization. The research highlights the critical need for media literacy and coordinated responses from authorities and platforms to counter such disinformation during emergencies.
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Vo et al. (2025) Trends in Cloud Covers across CONUS (1980–2020)
This study utilizes a high-resolution, 40-year reanalysis dataset to analyze cloud frequency trends over the Continental United States (CONUS), finding an overall decline in cloudiness that is most pronounced during the day and in historically sunny regions.
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Nurkholis et al. (2025) Evaluating Richards Equation and Infiltration Capacity Approaches in Mesoscale Hydrologic Modeling
This study compares the 1D Richards Equation (RE) and the Infiltration Capacity (IC) scheme for modeling soil moisture in the mHM model, finding that while both predict streamflow similarly, the RE approach better captures deep soil moisture dynamics.
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Battula et al. (2025) Characteristics and Predictability of Extreme Precipitation Related to Atmospheric Rivers, Mesoscale Convective Systems, and Tropical Cyclones in the U.S. Southeast
This study evaluates how different synoptic patterns and storm types (atmospheric rivers, mesoscale convective systems, and tropical cyclones) influence the predictability of extreme quantitative precipitation forecasts (QPF) in the Southeastern United States. The findings indicate that events associated with atmospheric rivers (ARs) exhibit higher QPF skill than those driven by isolated mesoscale convective systems (MCSs).
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Su et al. (2025) Improving National Water Model Flood Forecast Skill over Coastal Western U.S. River Basins
This study compares the flood forecasting accuracy of WRF-Hydro (the core of the National Water Model) against traditional NWS River Forecast Center methods across seven Pacific Coast watersheds. The results indicate that while WRF-Hydro performs comparably in northern basins, it is inferior in southern basins and tends to predict flood peaks too early.
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Canziani et al. (2025) A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
This study analyzes over 150 years of monthly precipitation at four Argentine locations to evaluate long-term trends and the influence of large-scale climate drivers. The results indicate generally null long-term trends but significant decadal variability and a disconnect between monthly precipitation rankings and severe daily events.
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Ahmadi et al. (2025) Coupling SWAT+ and SWMM Models to Quantify Streamflow in Mixed Rural–Urban Watersheds
The study develops an Integrated Environmental Modelling (IEM) approach by coupling SWMM and SWAT+ to improve streamflow simulation in mixed urban-rural transitional watersheds. The integrated model significantly outperforms standalone models in predicting runoff during both dry and wet periods.
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Vonk (2025) SPEI: A Python package for calculating and visualizing drought indices
The paper introduces `SPEI`, a Python package designed to streamline the calculation and visualization of various meteorological, hydrological, and agricultural drought indices from time series data.
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Yavaşlı (2025) Spatio‐Temporal Trends in Precipitation Indices Over Mediterranean Using ERA5 ‐Land Data (1950–2024)
This study analyzes long-term precipitation trends in the Mediterranean region from 1950 to 2024 using ERA5-Land data, revealing significant regional variations in precipitation frequency and intensity.
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Arya et al. (2025) Comprehending the Synergistic Roles of Cloud Properties and Dynamics on Extreme Rainfall Events During the Indian Summer Monsoon of 2019
This study analyzes the 2019 Indian monsoon to determine how cloud microphysics and atmospheric dynamics differ between extreme and non-extreme rainfall events. It finds that extreme events are characterized by significantly higher cloud ice/liquid mass, higher specific humidity, and enhanced deep convection.
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Wang et al. (2025) The transformation mechanism for accommodating forecast uncertainty of reservoir
This study explores how reservoirs accommodate forecast uncertainty during flood water resource utilization and proposes a risk-based method to optimize water use without increasing flood risk.
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Xue et al. (2025) Characteristics and Mechanisms of Non‐Stationary Turbulence in a Megacity Area
This study analyzes turbulent non-stationarity in Beijing, finding that it occurs in 52.41% of observations and is primarily driven by submeso motions that reduce turbulent transport efficiency.
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Chen et al. (2025) Spatiotemporal variation of forest water conservation based on dual-variable calibration of runoff and evapotranspiration with SWAT model
The study introduces a dual-variable calibration approach for the SWAT model, combining observed runoff and corrected evapotranspiration (ET) products to more accurately quantify forest water conservation in the Shanmei Reservoir Watershed.
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Dougherty et al. (2025) Historical Warming and Drying in Colorado and Their Impact on Cool-Season Precipitation and Snow
This study evaluates thermodynamic changes in Colorado and the Gunnison River basin from 1981 to 2021, finding that warming and drying have led to decreased snowfall and accelerated snowmelt.
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Jia et al. (2025) Fusing SAR image and CYGNSS data for monitoring river water level changes by machine learning
The study proposes a machine learning-based fusion of Sentinel-1 SAR imagery and CYGNSS GNSS-R data to improve the accuracy and temporal resolution of river water level estimation. The fusion approach significantly reduced estimation errors compared to using single-source data.
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Kim et al. (2025) At-Site Versus Regional Frequency Analysis of Sub-Hourly Rainfall for Urban Hydrology Applications During Recent Extreme Events
This study compares at-site and regional frequency analyses for sub-hourly rainfall quantile estimation in Seoul, concluding that regional analysis significantly improves reliability for long-term return periods.
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XUE et al. (2025) The Linkage between the Extreme Cold Air Outbreaks and Rossby Wave Breaking over East Asia
This study diagnostically investigates the relationship between Rossby wave breaking (RWB) and extreme East Asian cold air outbreaks (CAOs), revealing that western and eastern CAOs are driven by distinct wave evolution patterns and regional RWB activities.
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Chen et al. (2025) Noise Mitigation of the SMOS L1C Multi-Angle Brightness Temperature Based on the Lookup Table
The paper proposes a noise mitigation method for SMOS L1C multi-angle brightness temperature (TB) data using a lookup table to map multi-angle measurements to a single angle. This approach reduces system noise to levels comparable to the SMAP satellite and improves salinity retrieval accuracy.
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Halifa‐Marín et al. (2025) Beyond the NAO : The East Atlantic Pattern's Role in Early 20th‐Century Meteorological Droughts in Western Europe
This study identifies the East Atlantic (EA) pattern, rather than the North Atlantic Oscillation (NAO), as the primary driver of winter atmospheric variability and precipitation in Western Europe and the Iberian Peninsula during the early 20th century.
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Page et al. (2025) The proliferation of tiny irrigation tanks observed by remote sensing is in phase with groundwater depletion in Morocco
The study utilizes satellite remote sensing to quantify the proliferation of small irrigation tanks in four Moroccan aquifers, finding that the increase in these reservoirs serves as an indirect proxy for groundwater depletion.
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Thomas et al. (2025) The Role of Internal Variability in Seasonal Hindcast Trend Errors
The study demonstrates that seasonal hindcast models exhibit a wide range of multidecadal trends due to short-term variability, indicating that benchmarking against observations using only the ensemble mean can lead to a misdiagnosis of model trend errors.
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Yao et al. (2025) Spatiotemporal Characteristics and Associated Circulation Features of Summer Extreme Precipitation in the Yellow River Basin
This study analyzes summer extreme precipitation in China's Yellow River Basin from 1981 to 2020, identifying spatial distribution patterns and their drivers related to atmospheric circulation and sea surface temperatures.
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Serra et al. (2025) Evolution of Rainfall Characteristics in Catalonia, Spain, Using a Moving-Window Approach (1950–2022)
This study analyzes rainfall trends in Catalonia, NE Spain, from 1950 to 2022, finding a significant 10% decrease in annual precipitation and strong correlations between long-term oscillations and the NAO and AMO indices.
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Liang et al. (2025) CSAN: A Channel–Spatial Attention-Based Network for Meteorological Satellite Image Super-Resolution
The paper introduces CSAN, a channel-spatial attention-based network designed to super-resolve low-resolution spectral bands of meteorological satellite imagery to the highest available resolution.
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Aryal et al. (2025) Spatio-temporal heterogeneities in hydrologic dynamics across the Asian Water Tower
This study employs high-resolution hydrological-hydrodynamic modeling to analyze hydrologic changes across the Asian Water Tower (AWT) from 1979 to 2018, revealing significant spatio-temporal heterogeneity in flood risks and water storage components.
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Xing et al. (2025) Propagation patterns of different degree meteorological droughts across the Yangtze River Basin: a three-dimensional drought feature identification approach with Copula modeling
The study proposes a framework combining a three-dimensional drought feature identification method and Copula modeling to quantify and analyze the spatio-temporal propagation patterns of different degrees of meteorological droughts in the Yangtze River Basin (YRB).
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Sun et al. (2025) Seasonal Prediction of Spring Drought over Northeast China
The study develops a seasonal prediction model for spring droughts in Northeast China (NEC) using the Standardized Precipitation Evapotranspiration Index (SPEI) and EOF analysis, achieving high correlation between predicted and observed drought patterns.
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Chen et al. (2025) Vegetation growth carryover and lagged climatic effect at Juniperus seravschanica different scales: From tree rings to remote sensing data
This study examines the impacts of vegetation growth carryover (VGC) and lagged climate effects (LCE) on *Juniperus seravschanica* in Tajikistan. The results indicate that both VGC and LCE are more pronounced in tree-ring width than in remote sensing indices and that these two mechanisms operate independently.
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Akter et al. (2025) Comparing the Accuracy of Soil Moisture Estimates Derived from Bulk and Energy-Resolved Gamma Radiation Measurements
This study compares the accuracy of soil moisture (SM) estimation using bulk environmental gamma radiation (EGR) from a Geiger-Mueller counter against specific $^{40}\text{K}$ radiation measurements. The results demonstrate that $^{40}\text{K}$ measurements provide significantly higher accuracy because they are less susceptible to interference from radon and biomass.
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Methaprayun et al. (2025) Enhancing the accuracy of weather radar heavy rainfall estimates in mountainous regions using combined radar quality indices
The study introduces a novel relative radar quality index (QI) and an improved mean field bias adjustment technique to reduce rainfall estimation errors caused by beam blockage in the mountainous regions of Thailand.
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Wang et al. (2025) Integrating hypsography for large-scale lake analysis
The article discusses a new framework for large-scale limnological analysis that aggregates individual lake hypsographies to identify broad spatial patterns.
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Glaude et al. (2025) Innovative use of passive and active distributed temperature sensing for estimating infiltration rates in a managed aquifer recharge framework
This study evaluates the use of combined passive and active Distributed Temperature Sensing (DTS) via fiber optic cables to estimate and map infiltration rates in a Managed Aquifer Recharge (MAR) pilot site situated in loess sediments.
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Li et al. (2025) CloudRuler: Rule-based transformer for cloud removal in Landsat images
The study proposes CloudRuler, a rule-based transformer network that integrates a cloud physical model and domain-specific rules to effectively remove thin clouds from Landsat 8 and 9 imagery.
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Li et al. (2025) Investigating the Regulation Effects of Vegetation Restoration on Precipitation Patterns Over the Loess Plateau, China
This study examines the impact of large-scale vegetation restoration on the Loess Plateau's precipitation from 1982 to 2018, finding that restoration initially increased precipitation via enhanced evapotranspiration, though this effect began to diminish after 2015.
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Zhang et al. (2025) Winter Precipitation Predictions in the Contiguous United States: Challenges for Two Seasonal Forecast Models, SEAS5 and CFSv2
This study evaluates the ability of two operational seasonal forecast models (SEAS5 and CFSv2) to predict large-scale circulation modes that modulate winter precipitation in the contiguous United States via atmospheric rivers, finding that the "West mode" is particularly difficult to forecast due to its internal dynamical origins.
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Ouyang et al. (2025) Research Hotspots and Trends in Soil Infiltration at the Watershed Scale Using the SWAT Model: A Bibliometric Analysis
This bibliometric study analyzes 141 peer-reviewed articles to identify the key themes, influential contributors, and evolving trends in the application of the SWAT model for watershed-scale soil infiltration research.
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Zhao et al. (2025) Water Flow Forecasting Model Based on Bidirectional Long- and Short-Term Memory and Attention Mechanism
The study proposes the AT-BiLSTM model, which integrates a bidirectional LSTM layer and an attention mechanism, to improve the accuracy of river water flow forecasting.
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Fiallos-Salguero et al. (2025) A deep learning pipeline for rainfall estimation from surveillance audio
The study develops a deep learning pipeline that utilizes audio captured by surveillance cameras to estimate rainfall intensity, employing a two-stage network for noise suppression and intensity prediction.
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Wang et al. (2025) Understanding Overland Satellite-Based Precipitation Errors in IMERG Products as a Function of Input Sources
This study evaluates the performance of the IMERG V07B precipitation product against its predecessor V06B over the conterminous United States. The results demonstrate that V07B provides superior precipitation detection and reduced systematic bias across all seasons, particularly in winter.
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Xue et al. (2025) Comprehensive risk assessment of urban flood process based on dynamic weights and lumped impact parameters
The study proposes a dynamic urban flood risk assessment method using lumped impact parameters and dynamic weights to more accurately identify high-risk areas compared to traditional static weighting approaches.
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Zhang et al. (2025) Deriving reservoir operating rules of spillway gates based on deep reinforcement learning
The study proposes a deep reinforcement learning approach to derive operating rules for spillway gates rather than general reservoir outflow, aiming to optimize flood control and reduce operational frequency.
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Chen et al. (2025) Adjustment of Springtime Thermal Anomaly Modes over the Tibetan Plateau Altered Its Interdecadal Relationship with East Asian Summer Monsoon during the Early 2000s
This study identifies a regime shift around 2004 in the relationship between springtime surface sensible heat (SH) flux over the Tibetan Plateau and the East Asian summer monsoon (EASM), driven by changes in the spatial heating patterns of the central-eastern Tibetan Plateau.
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Huang et al. (2025) A three-dimensional Copula-based standardized temperature precipitation evapotranspiration water storage index for comprehensive drought monitoring
The study develops a Multivariate Drought Index (MDI) using a three-dimensional Copula model to integrate temperature, precipitation-evapotranspiration, and water storage data for comprehensive drought monitoring in the Yangtze River Basin.
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Xiaoqin et al. (2025) Spatial multiple variables and single variable updating via hydrologic system differential response method in real-time flood forecasting
The study develops and evaluates three spatial updating approaches based on the Hydrologic System Differential Response (HSDR) method to correct errors in real-time flood forecasting using the Xinanjiang model.
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Liang et al. (2025) Assessment of Aerosol Optical Depth, Cloud Fraction, and Liquid Water Path in CMIP6 Models Using Satellite Observations
This study evaluates the ability of CMIP6 models to simulate aerosol optical depth (AOD), cloud fraction (CF), and liquid water path (LWP) against satellite observations. The results indicate that while spatial patterns are generally captured, models tend to underestimate CF and LWP, with performance being higher in the Northern Hemisphere than in the Southern Hemisphere.
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Neftissov et al. (2025) An Advanced Ensemble Machine Learning Framework for Estimating Long-Term Average Discharge at Hydrological Stations Using Global Metadata
This study develops a machine learning framework, utilizing a weighted Meta Ensemble model, to accurately estimate long-term average (LTA) discharge using global hydrological station metadata.
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Forster et al. (2025) Global Validation of the Version F Geophysical Data Records from the TOPEX/POSEIDON Altimetry Satellite Mission
This study validates the version F Geophysical Data Records (GDR-F) for the TOPEX/POSEIDON satellite mission, demonstrating significant improvements in accuracy and consistency over the previous MGDR-B version.
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Granata et al. (2025) Hydrological extremes in the Mediterranean basin: interactions, impacts, and adaptation in the face of climate change
This review synthesizes current knowledge on hydrological extremes (droughts, intense rainfall, floods) in the Mediterranean basin, analyzing their characteristics, trends, interactions, and climate change impacts, while identifying knowledge gaps and recommending integrated adaptation strategies.
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Melnyk et al. (2025) Seasonal and Long-Term Water Regime Trends of Cheremsky Wetland: Analysis Based on Sentinel-2 Spectral Indices and Composite Indicator Development
This study analyzes long-term seasonal water surface trends in the Cheremsky Nature Reserve (Ukraine) using Sentinel-2 data to develop a composite index (CI) for integrated wetland monitoring.
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Shu (2025) Short-term ensemble prediction of convective cells using data-driven methods
This thesis develops an ensemble nowcasting framework that combines an analogue-based approach with machine learning to predict the evolution of convective rainfall cell properties.
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Badapalli (2025) Integrating multi-temporal remote sensing and advanced drought modeling to assess desertification dynamics in semi-arid Andhra Pradesh, India: A framework for sustainable Land management
The study develops a framework integrating multi-temporal remote sensing and drought modeling to assess desertification in semi-arid Andhra Pradesh, India, finding a significant increase in degraded and desertified land between 1990 and 2020.
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Liu et al. (2025) Heterogeneity Impacts Urban Roughness for Earth System Modeling
The study proposes a physics-based aerodynamic parameterization (RUR) using multi-layer division and a drag-force approach to account for urban heterogeneities, significantly improving the estimation of roughness length and surface fluxes.
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Roy et al. (2025) Smartphone-based image analysis and interpretable machine learning for soil moisture estimation across diverse Indian soils
The study developed a low-cost, non-destructive method for estimating soil moisture content (SMC) using smartphone imagery and interpretable machine learning across diverse Indian soil types.
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Ding et al. (2025) Estimating cropland evapotranspiration based on remote sensing models: A global meta-analysis
This study presents a global meta-analysis of 690 published articles to evaluate the performance, accuracy, and applicability of various remote sensing (RS) models used to estimate cropland evapotranspiration (ETc).
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Zhu et al. (2025) The Frequency and Intensity of Extreme Dust Events and Related Driving Factors in Major Dust Sources Based on MERRA-2 Aerosol Reanalysis
This study analyzes the frequency, intensity, and drivers of spring extreme dust events (EDEs) from 2000 to 2023, finding that EDEs in North Africa and the Middle East are driven by the East Atlantic/West Russia teleconnection rather than the North Atlantic Oscillation.
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Zhang et al. (2025) A comprehensive review of recent progress on the drought-flood abrupt alternation
This review synthesizes recent scientific progress regarding Drought-Flood Abrupt Alternation (DFAA) events, emphasizing the lack of a unified definition and the role of climate change in increasing their frequency and severity.
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Ellur et al. (2025) Prediction and Mapping of Soil Texture at High Spatial Resolution in a Canal Irrigated Region Using Machine Learning
This study mapped the spatial distribution of soil texture (sand, silt, and clay) in the Cauvery command area of southern Karnataka, India, using Random Forest and Sentinel-2 data, identifying clay loam as the predominant soil type.
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Payares et al. (2025) Assessing Plant Water Status and Physiological Behaviour Using Multispectral Images from UAV in Merlot Vineyards in Central Spain
This study evaluates the efficacy of UAV-acquired high-resolution multispectral imagery in estimating vine water status in a Merlot vineyard. The results demonstrate that midday measurements using NDVI and combined red/NIR bands can effectively predict stem water potential.
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ebrahimzadeh et al. (2025) A multi-indicator approach for assessing the hydrological health and drought resilience of Khanmirza watershed, Iran
This study evaluates the hydrological health and drought resilience of the Khanmirza watershed in Iran using an integrated multi-indicator approach. The results indicate that while surface water and climatic conditions are stable, groundwater resources are in an unhealthy state due to over-extraction.
