Abstract

Climate warming leads to frequent extreme precipitation events, which is a prominent manifestation of the variation of the global water cycle. In this study, data from 1842 meteorological stations in the Huang–Huai–Hai–Yangtze River Basin and 7 climate models of CMIP6 were used to obtain the historical and future precipitation data using the Anusplin interpolation, BMA method, and a non-stationary deviation correction technique. The temporal and spatial variations of extreme precipitation in the four basins were analysed from 1960 to 2100. The correlation between extreme precipitation indices and their relationship with geographical factors was also analysed. The result of the study indicates that: (1) in the historical period, CDD and R99pTOT showed an upward trend, with growth rates of 14.14% and 4.78%, respectively. PRCPTOT showed a downward trend, with a decreasing rate of 9.72%. Other indices showed minimal change. (2) Based on SSP1-2.6, the intensity, frequency, and duration of extreme precipitation changed by approximately 5% at SSP3-7.0 and 10% at SSP5-8.5. The sensitivity to climate change was found to be highest in spring and autumn. The drought risk decreased, while the flood risk increased in spring. The drought risk increased in autumn and winter, and the flood risk increased in the alpine climate area of the plateau in summer. (3) Extreme precipitation index is significantly correlated with PRCPTOT in the future period. Different atmospheric circulation factors significantly affected different extreme precipitation indices of FMB. (4) CDD, CWD, R95pD, R99pD, and PRCPTOT are affected by latitude. On the other hand, RX1day and RX5day are affected by longitude. The extreme precipitation index is significantly correlated with geographical factors, and areas above 3000 m above sea level are more sensitive to climate change.

Details

Title
Spatial–temporal variation of extreme precipitation in the Yellow–Huai–Hai–Yangtze Basin of China
Author
Wang, Lichuan 1 ; Wang, Jianhua 2 ; He, Fan 2 ; Wang, Qingming 2 ; Zhao, Yong 2 ; Lu, Peiyi 2 ; Huang, Ya 3 ; Cui, Hao 4 ; Deng, Haodong 2 ; Jia, Xinran 2 

 Hohai University, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing, China (GRID:grid.257065.3) (ISNI:0000 0004 1760 3465); China Institute of Water Resources and Hydropower Research, State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing, China (GRID:grid.453304.5) (ISNI:0000 0001 0722 2552); Hohai University, College of Hydrology and Water Resources, Nanjing, China (GRID:grid.257065.3) (ISNI:0000 0004 1760 3465) 
 China Institute of Water Resources and Hydropower Research, State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing, China (GRID:grid.453304.5) (ISNI:0000 0001 0722 2552) 
 Hohai University, College of Oceanography, Nanjing, China (GRID:grid.257065.3) (ISNI:0000 0004 1760 3465) 
 Hohai University, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing, China (GRID:grid.257065.3) (ISNI:0000 0004 1760 3465) 
Pages
9312
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2825537703
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.