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Palacios-Gutiérrez et al. (2025) Identification of extreme temperature and precipitation patterns in Spain based on multiscale analysis of time series
This study develops a novel multiscale analysis methodology to identify patterns of change in extreme maximum and minimum temperatures and precipitation in Spain from 1951 to 2021, revealing twelve distinct climate zones with varying warming trends, precipitation decreases, and increased drought duration and magnitude.
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Yan et al. (2025) Responses of Typical Riparian Vegetation to Annual Variation of River Flow in a Semi-Arid Climate Region: Case Study of China’s Xiliao River
This study identifies the primary drivers of riparian vegetation changes in a section of the Xiliao River from 1985 to 2020, concluding that river flow indicators—particularly the average flow in May—exert a greater influence than climate factors.
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Majd et al. (2025) Stochastic evaluation of the effect of cross-correlation between precipitation and evapotranspiration on SPEI performance
This study evaluates how the cross-correlation between precipitation and evapotranspiration influences the performance of the Standardized Precipitation Evapotranspiration Index (SPEI) across four different climatic zones compared to the Standardized Precipitation Index (SPI).
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Montzka et al. (2025) AI in soil moisture remote sensing
This paper provides the first structured overview of artificial intelligence (AI) applications for soil moisture retrieval from remote sensing data. It highlights how AI overcomes the limitations of traditional physical models by learning complex non-linear relationships and improving data continuity and resolution.
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Collignan et al. (2025) Identifying and Quantifying the Impact of Climatic and Non‐Climatic Drivers on River Discharge in Europe
This study proposes a novel methodology utilizing a common parsimonious modeling framework to decompose observed river discharge trends into components driven by climate change and those driven by non-climatic (human) factors across Europe, concluding that non-climatic factors dominate discharge changes, particularly in Southern Europe.
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He et al. (2025) SMPD-MERG: A Hybrid Downscaling Model for High-Resolution Daily Precipitation Estimation via Merging Surface Soil Moisture and Multisource Precipitation Data
The study introduces SMPD-MERG, a novel hybrid downscaling model designed to merge surface soil moisture data with multisource precipitation products to generate high-resolution, accurate daily precipitation estimates.
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Lamichhane et al. (2025) Multi‐layer root zone soil moisture estimation using field and remote sensing data fusion with machine learning in semi‐arid croplands
This study developed an Extreme Gradient Boosting model integrating PlanetScope optical data, climate variables, and soil properties to estimate multi-layer soil moisture (SM) down to 1.8 m at 3 m spatial resolution, achieving high accuracy ($R^2$ up to 0.89) and demonstrating that incorporating SM from the adjacent upper layer significantly improves deep SM prediction.
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Liu et al. (2025) AI-Driven GIS Modeling of Future Flood Risk and Susceptibility for Typhoon Krathon under Climate Change
This study develops a Random Forest (RF)-based GIS model to assess flood susceptibility in Keelung City using data from Typhoon Krathon (2024) and projects future risks under IPCC AR5 RCP8.5 climate scenarios.
