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Bharthisha et al. (2026) Integrated Remote Sensing and GIS Approaches for Mapping Soil Salinity and Waterlogging in Arid and Semi-Arid Environments: A Systematic Review of Statistical and Hydrological Models
This narrative review synthesizes the use of Remote Sensing (RS) and GIS technologies, integrated with machine learning, to provide a cost-effective and large-scale alternative to traditional field monitoring for soil salinity and waterlogging.
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Blöschl (2026) Five principles for hydrology in the era of managed waters
This perspective article proposes five guiding principles for the field of hydrology to adapt to the "era of managed waters," arguing that the discipline must shift toward learning from patterns to understand processes across multiple scales.
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Daide et al. (2026) Spatio-Temporal Dynamics of Vegetation and Water Stress in the Trichonida Basin Using Remote Sensing and Climatic Drought Indicators
This study evaluates drought variability and ecosystem responses in Greece's Trichonida basin by integrating climatic indices with satellite-derived vegetation and temperature data. The findings reveal increasing drought persistence and significant seasonal water stress affecting vegetation and high-conservation-value habitats.
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Sarkar et al. (2026) A hybrid Granger TCN framework for generating climate analogues and determining the future of agricultural practices
The study proposes a hybrid framework combining Granger Causality and Temporal Convolution Networks (TCN) to identify future climate analogues for maximum temperature in Kashmir based on historical data from other Indian cities to support agricultural planning.
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Chu et al. (2026) Spatial Evolution Characteristics and Driving Factors of Compound Droughts in Karst Regions of Southwest China: A Copula-Based Study
This study analyzes the spatial-temporal distribution and driving factors of different drought types in China's Southwest Karst Area (1979–2023) using Copula-based indices and random forest analysis.
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Cui et al. (2026) Airflow-Transport-Pathway Dependence of Raindrop Size Distributions and Radar Z–R Relationships During the Rainy Season in the Liupan Mountains: Warm-Moist Monsoon vs. Dry-Cold Continental
This study analyzes how two distinct airflow transport pathways—warm-moist monsoon (C1) and dry-cold continental (C2)—influence raindrop size distributions (DSD) in the Liupan Mountains. It concludes that C1 produces smaller drops with maritime characteristics, while C2 produces larger drops due to low-level evaporation and orographic lifting.
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Ma et al. (2026) Flash Drought Assessment in the Black Soil Region of Northeast China Using FDHI
The study developed a daily-scale Flash Drought Hazard Index (FDHI) to evaluate the spatiotemporal patterns and hydroclimatic drivers of flash droughts in the Black Soil Region of Northeast China from 2000 to 2020.
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Duan et al. (2026) Quantifying the Synergistic Effects of Environmental Drivers and Irrigation on Evapotranspiration in Shijin Irrigation District Using Projection Pursuit
This study investigates the synergistic effects of meteorological factors, Leaf Area Index (LAI), and irrigation on actual evapotranspiration in the Shijin irrigation district. The results highlight that LAI and irrigation are the dominant drivers, with irrigation acting synergistically with crop growth to increase evapotranspiration.
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Monachese et al. (2026) Evaluating SUDS Efficiency in Urban Environments: A Dual-Scale Methodology Applied to the City of Madrid
This study evaluates the hydrological and economic performance of Sustainable Urban Drainage Systems (SUDS) in Madrid, Spain, under two climate scenarios. The findings indicate that while partial-coverage configurations optimize water retention, economic viability is only achieved at very low retention levels.
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Zheng et al. (2026) Extreme Precipitation in China (1960–2020): Spatiotemporal Evolution and Atmosphere–Ocean Circulation Drivers
This study analyzes eight extreme precipitation indices across six climatic sub-regions of China from 1960 to 2020, finding general upward trends and identifying key atmosphere-ocean teleconnection combinations that drive regional variability.
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Zhang et al. (2026) The Impact of Drought Events on Cropland Phenology and Vegetation Productivity in Northeast China (2001–2020)
This study evaluates the impact of drought frequency and severity on cropland phenology and productivity in Northeast China from 2001 to 2020, revealing that these effects are spatially heterogeneous and strongly dependent on the season.
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Yan et al. (2026) Projected Changes in Dry and Wet Conditions in the Henan Section of the Yellow River Based on the CMIP6 Multi-Model Ensemble
This study analyzes historical drought and pluvial trends in the Henan section of the Yellow River (1970–2014) and projects future conditions up to 2100 using CMIP6 models. The findings reveal a historical drying trend and suggest that future hydroclimatic risks will vary by SSP scenario, generally becoming more severe and persistent.
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Kohli et al. (2026) Beyond Helium-3: Instruments for Cosmic-Ray Neutron Sensing Based on Boron-10 Neutron Detectors
The paper presents a modular family of Cosmic-Ray Neutron Sensing (CRNS) instruments based on boron-10-lined proportional counters designed for autonomous, low-power soil moisture monitoring.
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Nazhmudinova (2026) Modern conditions of humidification in the North of Ukraine
This study analyzes precipitation trends in Northern Ukraine, finding a general shift toward aridity during the summer and specific winter months, contrasted by increased precipitation in May and October.
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Khrystiuk et al. (2026) Decomposition, modeling and forecasting of the time series of discharge of the Desna river using the “bsts” package of the R programming language
The study evaluates the use of the `bsts` R package to model and forecast daily discharges of the Desna River at Litky village, identifying a student local linear trend model as the most effective for short-term predictions.
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Zhao et al. (2026) Assessing Cropland Water Deficit and Productivity-Loss Risk Through the Standardized Crop Water Deficit Index and Copula Analysis in the Huang–Huai–Hai Plain, China
The study developed a crop-oriented framework using a Standardized Crop Water Deficit Index (SCWDI) to quantify drought events and their impact on the Gross Primary Productivity (GPP) of winter wheat and summer maize in China's Huang–Huai–Hai Plain.
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Huang et al. (2026) Classification and mechanisms of summer drought types in Eastern Northwest China
This study classifies summer droughts in Eastern Northwest China (ENC) into persistent and episodic types based on SPEI-3 evolution, revealing that they are driven by distinct atmospheric circulations and oceanic precursors.
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Saipriya et al. (2026) Space-time variability of rainfall attributes across urban agglomerations of Peninsular India and implications for sustainable growth
This study evaluates rainfall dynamics across 63 urban agglomerations in Peninsular India to identify spatio-temporal variability and provide a scientific basis for sustainable urban growth.
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Si et al. (2026) Differential Effects of Soil Moisture and Air Temperature on Vegetation Dynamics in Northwest China’s Warming and Wetting Region: An LSTM Modeling Approach
The study employs a bivariate LSTM model to simulate Leaf Area Index (LAI) in Northwest China, revealing that while hydrothermal drivers explain seasonal phenology and grassland variability, they are insufficient to capture long-term forest greening.
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Wu et al. (2026) Wind stilling shapes grassland water use efficiency by enhancing soil moisture retention
This study demonstrates that declining wind speeds enhance the ecosystem water use efficiency ($\text{WUE}_{\text{eco}}$) of global grasslands by reducing evaporative water loss and increasing carbon uptake.
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Khan et al. (2026) Projected hydrological responses to climate change in a high-mountain river basin based on RCM simulations
This study uses the SWAT model and CORDEX regional climate simulations to project hydrological changes in the Chitral River Basin, finding that climate warming will likely shift peak streamflow timing to June-July.
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Yunue et al. (2026) Multiscale Meteorological Drought Spatial Reconstruction in North-Central Urban Core of Mexico City: An Explainable Deep Learning Approach
The study developed an explainable deep learning framework using LSTM networks to spatially reconstruct three drought indices (SPI, SPEI, and RDI) across various temporal scales in Mexico City.
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Green et al. (2026) Vegetation responses to air dryness amplify future land surface warming
The study finds that canopy temperature is projected to increase significantly more than air temperature over the 21st century due to rising air dryness, implying that current Earth System Models (ESMs) underestimate future constraints on vegetation growth and the land carbon sink.
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Wang et al. (2026) A thermodynamics-integrated physics-guided neural network for soil temperature forecasting
The study develops a Thermodynamic-Enhanced Physics-Informed Neural Network (TE-PINN) that integrates thermodynamic priors into an LSTM framework to improve the accuracy and physical consistency of soil temperature forecasting. The model effectively reduces error accumulation in long-term predictions and enhances spatial generalization across different latitudes.
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Qiu et al. (2026) Visual recognition algorithm for weakly labeled multi-source data fusion of remote sensing images
The study proposes a multi-source data fusion algorithm for remote sensing image recognition that leverages weakly labeled data and multimodal features to improve fine-grained classification and cross-domain generalization.
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Lee et al. (2026) Global patterns of urban heat shaped by climate and morphology
The study quantifies the joint influence of urban morphology and background climate on the urban heat island (UHI) effect across 2,213 cities globally, revealing that while denser structures universally increase heat, the climatic drivers vary by region.
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Bhardwaj et al. (2026) Future changes to meteorological drought in Australia: insights from the Australian Climate Service’s drought and changes in aridity team
This study uses downscaled CMIP6 projections to analyze future drought trends in Australia, identifying significant increases in drought frequency and duration in southern and south-western regions.
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Chancay et al. (2026) Enhancing GEOGLOWS River Forecast System with a High-Resolution Pre-Processing Approach for Runoff Bias Correction
This study evaluates a pre-routing, grid-scale runoff bias-correction framework for the GEOGLOWS River Forecast System to improve streamflow simulations in ungauged basins. The approach improves global median KGE from 0.16 to 0.22, with the most significant gains occurring in data-limited regions like South America and Africa.
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Rangel (2026) A machine learning-Monte Carlo simulation framework to determine the probability of flood flowrates in hydrographic basins
The study proposes a framework combining machine learning and Monte Carlo simulations to estimate the probability of flood flowrates within hydrographic basins.
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Wang et al. (2026) Research data for Effects of envelope materials on the drainage performance of subsurface pipe drainage and on farmland water-salt regulation
This study evaluates how different envelope materials influence the drainage performance of subsurface pipe systems and their effectiveness in regulating water and salt levels in agricultural land.
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Bin et al. (2026) Water-saving and economic benefits of a soil moisture threshold-based irrigation strategy for cotton in Xinjiang under climate change
The study develops a soil moisture threshold-based irrigation strategy (SMTIS) for cotton in Xinjiang, China, using the AquaCrop model and a nonlinear optimization framework. The results demonstrate that SMTIS significantly reduces irrigation water use and increases water productivity and economic benefits under both historical and future climate change scenarios.
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Yang et al. (2026) Efficient spectral-temporal reconstruction of long-term satellite time series via temporal segments and mask-informed embedding
The paper proposes the Mask-informed Spectral-temporal Transformer (MISTR), a framework designed to reconstruct missing values in long-term satellite time series (STS) by utilizing mask-informed embeddings and adaptive spectral-temporal blocks.
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Zhang et al. (2026) Interpretable machine learning framework for urban flood susceptibility assessment: a multi-model comparison with spatial heterogeneity analysis in Yancheng
This study develops an interpretable machine learning framework to assess urban flood susceptibility in Yancheng, China, demonstrating that XGBoost provides the highest predictive accuracy and that flood drivers vary significantly across different geomorphic zones.
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Lu et al. (2026) Divergent Trends and Driving Factors in Meteorological Flash Droughts Across China's Humid and Arid Regions
This study analyzes the spatiotemporal patterns and drivers of meteorological flash droughts (MFDs) in China from 1980 to 2024, revealing that humid regions are experiencing increasing frequency and accelerated onset despite an overall national decline in MFD frequency.
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Lv et al. (2026) Watershed Water Supply Security Reliability Assessment and Risk Node Identification in Mountain Piedmont Transition Zones Under Extreme Drought Stress: A Case Study from the Feng River Basin
This study developed a node-based water supply security assessment framework for the Feng River Basin, demonstrating that while basin-wide reliability remains stable, engineering-based water allocation can redistribute and concentrate risks at specific intake nodes during extreme droughts.
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Bo et al. (2026) Spatially explicit estimation of high-resolution irrigation water use across China using earth observation data and deep learning
The study developed a physically guided deep learning framework integrating Earth observation data and water balance modeling to estimate high-resolution (500 m) irrigation water use (IWU) across China from 2004 to 2019.
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Nair et al. (2026) Assessing climate change effects on streamflow and paddy production in the Bharathapuzha Basin Kerala
This study evaluates the impact of climate change on streamflow and paddy yields in the Bharathapuzha Basin, Kerala, using SWAT and CMIP6 models, predicting significant declines in crop production and altered hydrological regimes by 2100.
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Zhou et al. (2026) Global solar-induced chlorophyll fluorescence reconstruction crossing three platforms
The study develops a harmonized global daily solar-induced chlorophyll fluorescence (SIF) product (HSIF) for the period 2003–2023 by integrating data from three satellite platforms using CDF matching and machine learning.
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Singh et al. (2026) Emerging Trends and Challenges in Remote Sensing for Irrigation of Horticultural Crops
This study evaluates the application of remote sensing and AI in irrigation management for fruit and vegetable crops. The findings indicate that these technologies can enhance water use efficiency by 15–22%.
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Vijaybhai et al. (2026) Advancing Smart Irrigation Practices in Small-Scale Agriculture by Combining Hyperspectral Remote Sensing with IoT Solutions
The study proposes an integrated precision irrigation system combining hyperspectral remote sensing and IoT technology to optimize water management for small-scale farmers in India.
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Sarvari et al. (2026) Quantifying Drought Impacts on Wetlands in Arid Regions Using a Change-Based Drought Severity Index (WCDI) and Sentinel-1/2 Data Fusion within Google Earth Engine: Evidence from Two Wetlands in Central Iran
The study develops and applies a Change-Based Drought Severity Index (WCDI) using fused Sentinel-1 and Sentinel-2 satellite data within Google Earth Engine to quantify drought impacts on two wetlands in Central Iran.
