江西科学2025，Vol.43Issue(2)：211-219,9.DOI:10.13990/j.issn1001-3679.2025.02.001
基于SPEI的中国气候区干旱特征时空演变研究
Spatiotemporal Evolution of Drought Characteristics in Chinese Climate Zones Based on SPEI
摘要
Abstract
Under the context of global climate change,the ecosystems,the environment,and socio-economic development have been seriously impacted by the occurrence of drought e-vents.A standardized precipitation evapotranspiration index dataset with a spatial resolution of 0.1° was calculated for China from 1990 to 2023,using precipitation and potential evapo-transpiration data.The spatial and temporal evolution of drought in China's climatic zones at multiple time scales was analyzed using the Mann-Kendall trend test method and time sliding window.The results show that the distribution of wet-dry differences over the Chi-nese land is mainly characterized by the trend distribution of dry-wet-dry.Spatially,obvi-ous droughts are observed in the humid subtropical region of central and southern China at a 1-month time scale,the Qinghai-Tibet Plateau at a 3-month time scale,the desert region of northwest China at a 6-month time scale,and the Inner Mongolia grassland region at a 12-month time scale,compared to other climate zones at the same time scale.Tempo-rally,the frequency of drought events shows an increasing trend in the Inner Mongolia grassland area,humid subtropical areas of central and southern China,and the northwestern desert area.Conversely,a downward trend is noted in the number of droughts in the humid to semi-humid temperate areas in northeast China,the humid to semi-humid warm tem-perate areas in northern China,and the Qinghai-Tibetan Plateau.These findings contribute to a deeper understanding of drought evolution in China and provide valuable references for drought prevention and drought relief policies.关键词
SPEI/干旱/时空演变特征/Mann-Kendall趋势检验/时间滑动窗口Key words
SPEI/drought/temporal evolution/Mann-Kendall trend analysis/sliding window分类
地理科学引用本文复制引用
曾思婷,周世健,石现坤,章园..基于SPEI的中国气候区干旱特征时空演变研究[J].江西科学,2025,43(2):211-219,9.基金项目
国家自然科学基金资助项目(42064001). （42064001）
