Spatiotemporal evolution of drought status and its driving factors attribution in China

被引：0
作者：
机构：
[1] National Key Laboratory of Water Disaster Prevention, Hohai University, Jiangsu, Nanjing
[2] Yangtze Institute for Conservation and Development, Jiangsu, Nanjing
[3] College of Hydrology and Water Resources, Hohai University, Jiangsu, Nanjing
[4] China Meteorological Administration Hydro-Meteorology Key Laboratory, Hohai University, Jiangsu, Nanjing
[5] Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University, Jiangsu, Nanjing
[6] The Fenner School of Environment and Society, The Australian National University (ANU), Canberra, 0200, ACT
[7] School of Civil Engineering, Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai
[8] Department of Civil Engineering, Hydraulics and Geotechnics Section, KU Leuven, Leuven
来源：
Zhang, Ke (kzhang@hhu.edu.cn) | 2025年 / 958卷
关键词：
Drought; Geographical detector; Partial correlation analysis; Principal component analysis; Trend decomposition;
D O I：
10.1016/j.scitotenv.2024.178131
中图分类号：
学科分类号：
摘要：
Drought has intensified in China in recent years, and it is urgent to clarify the characteristics of drought evolutions in different regions and its influencing factors. To this end, we selected six main influencing factors and analyzed their impact on drought patterns. The results show that drought is increasing in 78.4 % of China, and more severe droughts have occurred since 2000. From the perspective of drought change distribution, the wet areas in China are getting wetter, and the dry areas are getting drier. The partial correlation coefficient (PACC) between precipitation and standard precipitation evapotranspiration index (SPEI) is the largest in South China (SC), and the PACC between temperature and SPEI is the largest in Northwest China (NWC). Precipitation and temperature have the greatest correlation with drought, accounting for 45.7 % and 30.8 % of China. In 49.9 % of China, temperature contributes the most to the drought trend changes, and in 16.6 % of China, normalized difference vegetation index (NDVI) contributes the most to the drought trend changes. Geographical detector model (GDM) shows temperature has the greatest driving force on SPEI, followed by surface solar radiation (SSR). Principal component analysis (PCA) shows temperature has the greatest positive impact on drought, while soil moisture has the greatest negative impact on drought. This study is helpful to increase the understanding of the diversities in drought drivers in different regions of China. © 2024
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