Statistical spatiotemporal analysis of hydro-morphological processes in China during 1950-2015

doi:10.1007/s00477-021-02007-y

	Statistical spatiotemporal analysis of hydro-morphological processes in China during 1950-2015
	Wang, Nan 5,6; Cheng, Weiming 2,5,6,7; Lombardo, Luigi 1; Xiong, Junnan 3,5; Guo, Liang 4
刊名	STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
	2021-04-19
页码	21
关键词	Hydro-morphological processes Spatiotemporal distribution Periodicity Clustering
ISSN号	1436-3240
DOI	10.1007/s00477-021-02007-y
通讯作者	Cheng, Weiming(chengwm@lreis.ac.cn)
英文摘要	Hydro-morphological processes (HMPs) are some of the most destructive natural disasters. Understanding the spatiotemporal characteristics of HMPs across China is important for enabling better disaster estimation and prevention at the national scale. However, few studies have focused on the spatiotemporal HMP characterization under various geomorphic settings in China, which may shed light on their regional/national evolution. To bridge this research gap, we analysed the longest HMP time series available in China, which including 47,483 HMP records, to detect spatiotemporal patterns. Specifically, we run several tests namely, Mann-Kendall test, wavelet analysis, Monthly Frequency, and Index of Dispersion, with the objective of detecting the temporal evolution, trends, period, and clustering of HMPs in six geomorphological regions (geomorphic-regions): Eastern Plain, South Eastern Mountain (SEM), North Central Plateau, North Western Basin, South Western Mountain (SWM), and Tibetan Plateau. Our results show that in the last decades have been associated with a marked increase in HMPs and this should be accounted for, especially in those areas where we have retrieved high spatiotemporal clustering (e.g., SEM, SWM). Besides, the main periodicity of HMPs is approximately 12-25 years for most of China since the 1980s, which showed analogous patterns with precipitation anomalies. This study provides a preliminary reference for revealing the spatiotemporal characteristics of HMPs in the context of climate change; therefore, the information provided can be crucial to plan engineering applications with specific return period.
资助项目	National Natural Science Foundation of China[41590845] ; China National Flash Flood Disasters Prevention and Control Project[SHZH-IWHR-57] ; China Institute of Water Resources and Hydropower Research (IWHR)
WOS研究方向	Engineering ; Environmental Sciences & Ecology ; Mathematics ; Water Resources
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000641213800002
资助机构	National Natural Science Foundation of China ; China National Flash Flood Disasters Prevention and Control Project ; China Institute of Water Resources and Hydropower Research (IWHR)
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/161754]
专题	中国科学院地理科学与资源研究所
通讯作者	Cheng, Weiming
作者单位	1.Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, POB 217, NL-7500 AE Enschede, Netherlands 2.Collaborat Innovat Ctr South China Sea Studies, Nanjing 210093, Peoples R China 3.Southwest Petr Univ, Sch Civil Engn & Architecture, Chengdu 610500, Peoples R China 4.China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 6.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 7.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China
推荐引用方式 GB/T 7714	Wang, Nan,Cheng, Weiming,Lombardo, Luigi,et al. Statistical spatiotemporal analysis of hydro-morphological processes in China during 1950-2015[J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,2021:21.
APA	Wang, Nan,Cheng, Weiming,Lombardo, Luigi,Xiong, Junnan,&Guo, Liang.(2021).Statistical spatiotemporal analysis of hydro-morphological processes in China during 1950-2015.STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,21.
MLA	Wang, Nan,et al."Statistical spatiotemporal analysis of hydro-morphological processes in China during 1950-2015".STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2021):21.