干旱区生态环境知识资源中心(Arid): The construction of flood loss ratio function in cities lacking loss data based on dynamic proportional substitution and hierarchical Bayesian model

Arid

DOI	10.1016/j.jhydrol.2020.125797
	The construction of flood loss ratio function in cities lacking loss data based on dynamic proportional substitution and hierarchical Bayesian model
	Lv, Hong; Wu, Zening; Guan, Xinjian; Meng, Yu
通讯作者	Meng, Y (corresponding author), Zhengzhou Univ, Sch Water Conservancy & Engn, Zhengzhou 450001, Henan, Peoples R China.
来源期刊	JOURNAL OF HYDROLOGY
ISSN	0022-1694
EISSN	1879-2707
出版年	2021
卷号	592
英文摘要	A reliable flood loss assessment in city is the basis of efficient flood risk management. However, it is difficult to fit empirical functions with typical case data for most of the world's arid or semi-arid cities that lack or even have no historical flood loss data. Under the background of frequent global extreme weather events and high-speed urbanization, urban flood loss assessment has become increasingly important to support urban flood risk management. At present, few researches have focused on the modeling of Flood Loss Ratio Function (FLRF) for cities lacking loss data. Therefore, based on the improved analogy principle, a Dynamic Proportional Substitution (DPS) method in this paper was proposed to transfer large sample data from multiple quoted cities into a sample matrix of loss ratios in the study city to address the lack of data. Then, according to the hierarchical data structure characteristics of the loss ratio matrix, a Hierarchical Bayesian Model (HBM) of FLRF with unknown parameters was constructed based on the prior distribution of parameters. Finally, taking the city lacking data-Zhengzhou, China as the study area, the water depth - loss ratio functions of four land types (industry, commerce, residence, and public utilities) were calculated. The results showed that: 1. The combined feature schemes achieved dynamic selectivity; 2. The parameters gradually converged after a certain number of iterations; 3. The error of FLRF solved by HBM was less than that of the least square method (LSM); 4. The DPS-HBM model had good performance in transplantation verification. This study is expected to provide a reference for the establishment of flood loss functions in cities lacking data.
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000639844900039
WOS关键词	DAMAGE ASSESSMENT ; RISK ; VULNERABILITY ; UNCERTAINTY ; CURVES ; RIVER
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Engineering ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/369073
作者单位	[Lv, Hong; Wu, Zening; Guan, Xinjian; Meng, Yu] Zhengzhou Univ, Sch Water Conservancy & Engn, Zhengzhou 450001, Henan, Peoples R China
推荐引用方式 GB/T 7714	Lv, Hong,Wu, Zening,Guan, Xinjian,et al. The construction of flood loss ratio function in cities lacking loss data based on dynamic proportional substitution and hierarchical Bayesian model[J],2021,592.
APA	Lv, Hong,Wu, Zening,Guan, Xinjian,&Meng, Yu.(2021).The construction of flood loss ratio function in cities lacking loss data based on dynamic proportional substitution and hierarchical Bayesian model.JOURNAL OF HYDROLOGY,592.
MLA	Lv, Hong,et al."The construction of flood loss ratio function in cities lacking loss data based on dynamic proportional substitution and hierarchical Bayesian model".JOURNAL OF HYDROLOGY 592(2021).