Hydrology and Climate Change Article Summaries

This study develops a framework to reconcile and evaluate two streamflow permanence datasets (NHDPlus HR and PROSPER model output) for the Pacific Northwest, finding 68% agreement regionally and identifying reliability patterns to inform land and water management decisions.

This study investigates the global co-location of trends towards more intense and less frequent daily precipitation events, finding that fewer, larger events are common and distributed across terrestrial ecosystems, often counteracting increases in annual precipitation totals due to simultaneous decreases in small-to-moderate events.

This study investigates the spatial distribution and differences between compound groundwater droughts and hot extremes (CGDHEs) and compound meteorological droughts and hot extremes (CMDHEs), attributing these differences to hydrological lags. It identifies optimal precipitation timescales to reduce these discrepancies, thereby improving the potential for near-real-time monitoring of CGDHEs.

This review synthesizes the synergistic impacts of climate change and human activities on global agricultural drought, revealing how their interactions form amplifying feedback loops that intensify drought frequency, intensity, duration, and spatial extent, leading to ecological degradation, crop yield loss, and socioeconomic inequality. It proposes a three-dimensional framework integrating mitigation, adaptation, and collaborative governance to address this escalating crisis.

This study developed and evaluated two novel backward hydrological models, an inverted Probability Distributed Model (PDM) and a hybrid Soil Moisture to Rain (SM2RAIN)-Kirchner model, for daily watershed-scale precipitation estimation. The locally calibrated backward models significantly outperformed established Global Gridded Precipitation Products (GGPPs), with the Kirchner model achieving the highest performance (KGE = 0.62) and the inverted PDM proving robust (KGE = 0.55).

This study introduces a novel, interpretable soil moisture retrieval framework by integrating a radiative transfer model (RTM) with a Kolmogorov–Arnold Network (KAN) to derive explicit mathematical expressions from satellite observations, achieving global soil moisture estimates comparable in accuracy to the SMAP Level-3 product.

This study comprehensively assesses historical drought conditions in Iran from 1967 to 2024 and forecasts decadal drought dynamics for 2025–2036 using climate observations and machine learning, revealing a projected significant increase in drier conditions and the disappearance of extreme wet periods.

This study developed a Combined Drought Index (CDI) for the Prom-Choen-Upper Phong River Basin using Principal Component Analysis (PCA) of SPEI, SSFI, and SSDI to assess future drought risk under climate and land use changes. It found that while increased future rainfall may reduce overall drought risk, the SSP585 scenario significantly expands very high-risk drought areas, underscoring the need for the CDI in mitigation strategies.

This study analyzes seasonal and annual patterns and trends of temperature and precipitation, including extreme events, in the Castelporziano Nature Reserve (Italy) from 1980, revealing a significant warming trend, particularly for maximum temperatures and extreme heat indices, influenced by coastal proximity, while precipitation shows no significant trend.

This review synthesizes developments in statistical and stochastic climate downscaling, critically assessing various methods including regression, weather generators, analogs, and machine learning. It highlights the significant, yet underexplored, potential of geostatistical simulation, particularly Multiple-Point Statistics, to provide spatially coherent and uncertainty-aware fine-scale climate information.

This study compares irrigation demand from an agro-hydrological model (WATNEEDS) with irrigation water use from five satellite products across four global irrigation hubs, finding significant correlations (above 0.6 for 3/4 cases) and using discrepancies to identify hydroclimatic and anthropogenic irrigation drivers.

This study developed a computationally efficient, system-scale modeling framework to assess flood risks and evaluate water detention structures for mitigating road washouts in data-scarce Prairie basins. It identified five strategically located detention dams that collectively eliminate road washout risk for floods up to the 100-year return period in the Elgin Creek Basin.

## Identification - **Journal:** International Journal of Climatology - **Year:** 2026...

This study comprehensively assesses projected climate change impacts on temperature and precipitation across the entire Euphrates-Tigris Basin under four RCP scenarios (2.6, 4.5, 6.0, 8.5) for three future periods, revealing a consistent warming trend and significant spatial redistribution of precipitation, with severe implications for downstream water resources.

This study quantified the contributions of climate change and human activities to runoff reduction in the semi-arid Xiliao River Basin from 1980 to 2022 using a Budyko-elasticity framework, revealing an abrupt runoff decline in 2002 with significant spatial heterogeneity: upstream areas are climate-driven, while middle-downstream areas are human-driven, primarily due to agricultural irrigation.

This study evaluates a novel method to improve coastal water level (CWL) predictions by assimilating nadir-only satellite altimetry data from four missions into the ADCIRC hydrodynamic model along the U.S. East Coast, finding that combined assimilation significantly enhances model performance at over 80% of gauge locations.

## Identification - **Journal:** Journal of Geophysical Research Atmospheres - **Year:** 2026...

This study quantifies the scenario-dependent responses of soil conservation service flow (SCSF) to climate change across different karst development degrees (KDDs) in the Pearl River Basin using a coupled Global Climate Model (GCM)-Soil and Water Assessment Tool (SWAT) framework, revealing that SCSF dynamics are significantly influenced by both climate scenarios and karst geomorphology.

This study develops an integrated water footprint accounting framework to diagnose water stress and its drivers across grid (~1 km²), municipal, and sub-basin scales in the Yellow River Basin from 2000 to 2024. It reveals a widening upper-to-lower reach divergence in water stress, driven by coupled socio-hydrological interactions that are often masked by aggregated analyses, providing scale-differentiated management recommendations.

This study quantitatively identified the contributions of climate change and human activities to sediment load variations across the Yellow River Basin from 1961 to 2022, revealing a progressive shift from climate-dominated to human-dominated controls, particularly in midstream and downstream reaches.