Drought Driving Factors as Revealed by Geographic Detector Model and Random Forest in Yunnan, China

Forests, Год журнала: 2025, Номер 16(3), С. 505 - 505

Опубликована: Март 12, 2025

Yunnan Province, as a critical ecological security barrier in China, has long been highly susceptible to drought events. Characterizing the spatiotemporal distributions of and identifying its driving factors is crucial. Due complexity occurrence, linear correlation analysis alone insufficient quantify drivers their interactions. This study used Standardized Precipitation Evapotranspiration Index (SPEI) indicator analyze trends across six major river basins. The geographic detector model (GDM) random forest (RF) were utilized impacts meteorological, topographical, soil, human activities on drought, well interactions among these factors. results showed that 63.61% area exhibits significant drying trend (p-value < 0.05), with Jinsha River Basin (JSRB) experiencing highest frequency extreme (PRE), temperature, potential evapotranspiration (PET), vapor pressure deficit (VPD), relative humidity (RH) identified primary controlling factor displaying nonlinear enhancement effects. PRE plays dominant role Yunnan, whereas elevation primarily influenced severity JSRB, Lancang (LCRB), Nujiang (NJRB). RF-based SPEI prediction demonstrated superior performance simulating short-term (SPEI_1, R2 > 0.931, RMSE 0.279), particularly JSRB (R2 = 0.947 0.228). These findings provide scientific basis for regional water resource management applications early warning systems, offering robust framework understanding mitigating ecologically sensitive regions.

Язык: Английский

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Changes in future drought characteristics in the Ili River Basin, China, using the new comprehensive standardized drought index

Ecological Indicators, Год журнала: 2025, Номер 173, С. 113412 - 113412

Опубликована: Апрель 1, 2025

Язык: Английский

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Defining potential pathways for improving the resilience and sustainable development of rangeland grazing systems: Insights from northern Australia

The Science of The Total Environment, Год журнала: 2025, Номер 978, С. 179488 - 179488

Опубликована: Апрель 19, 2025

Язык: Английский

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Exploring the combined effects of drought and drought-flood abrupt alternation on vegetation using interpretable machine learning model and r-vine copula function

Agricultural and Forest Meteorology, Год журнала: 2025, Номер 370, С. 110568 - 110568

Опубликована: Май 8, 2025

Язык: Английский

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Study on the propagation processes and driving mechanisms of meteorological, hydrological, and agricultural droughts on the Mongolian Plateau

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 133511 - 133511

Опубликована: Май 1, 2025

Язык: Английский

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