Abstract
The GRACE satellite mission provides a new approach for monitoring,tracking,and assessing drought conditions by detecting changes in Earth's gravitational fields and inversing signals of terrestrial water storage anomalies.Existing studies of terrestrial water storage anomalies related droughts paid rare attention to the behind atmospheric physical mechanisms,nor quantified the risk propagation patterns between terrestrial water storage deficits and hydrological or agricultural droughts.In this study,we first extract terrestrial water storage(TWS)droughts,hydrological droughts,and agricultural droughts by using multiple variables including TWS from the GRACE/GRACE-FO satellites,runoff and soil moisture from the ERA5-Land reanalysis dataset.We then identify key atmospheric and oceanic oscillation indices affecting water deficits by employing machine learning technologies.We characterize the joint distributions between drought duration and severity by using the Copula function and quantify the risk propagation of hydrological and agricultural droughts to TWS droughts.The results show that:(1)From 2002 to 2021,there is a significant decrasing trend of TWS in China;the WPIO group atmospheric circulation indices(sea surface temperature index within the Western Pacific and Indian Ocean)contributes the most to TWS.Specifically,the sea surface temperature anomalies within the NINO 3.4 region as well as the Western Pacific Warm Pool area index show significantly positive correlation relationships with TWS in southern China;(2)The northwestern China,the Yangtze River basin,and the downstream of the Pearl River basin are the hotspots of TWS droughts.Besides,the hotspots of hydrological droughts locate in northwestern China and the hotspots of agricultural droughts locate in South China and eastern Tibetan Plateau;(3)The elastic coefficients of hydrological droughts propagating to TWS droughts are higher than those of agricultural droughts,indicating that the TWS droughts are more sensitive to hydrological droughts than to agricultural droughts.
基金项目
National Natural Science Foundation of China(52209020)
Natural Science Foundation of Hubei Province(2023AFB722)
维普
万方数据