气候变化领域集成服务门户(CCPortal): Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility

CCPortal

DOI	10.1007/s11069-020-04498-4
	Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility
	Sun J.; Qin S.; Qiao S.; Chen Y.; Su G.; Cheng Q.; Zhang Y.; Guo X.
发表日期	2021
ISSN	0921030X
起始页码	881
结束页码	912
卷号	106 期号:1
英文摘要	Regional scale debris flow susceptibility is widely evaluated by statistical methods. However, the initiation mechanism of debris flow is not considered, which leads to the neglect of the microtopographic characteristics. To address this problem, we established three novel combined models by introducing the physical model into statistical methods. The integrating models consists of two parts, the statistical models and the TRIGRS model. The eventual results obtained with the integrating model consider both the prediction result of the statistical method for debris flow susceptibility and the mechanism of debris flow initiation. To test the feasibility of the integrating model, three representative statistical models, the analytic hierarchy process (AHP), Shannon entropy (Entropy) and support vector machine (SVM) were selected to evaluate debris flow susceptibility in Yongji County of Jilin Province, China. The results demonstrate that the performance of the integrated models is significantly better than that of the single statistical model, especially in the local areas. The integrating models (AHP-TR, Entropy-TR, SVM-TR) can generate higher quality debris flow susceptibility maps (DFSMs) than the single model, which clearly reflect the scope and boundaries of the areas which are most prone to debris flow and identify the flat land and valleys between adjacent high-prone areas. It also reduces the overprediction generated by the physical model. In general, combining the statistical methods with the TRIGRS model can maximize the strengths of these models and avoid their weaknesses and obtain the effect of 1 + 1 > 2. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
关键词	Debris flow susceptibility mapping Integrating model Physical model Statistical model Yongji County
英文关键词	debris flow; integrated approach; mapping; microtopography; statistical analysis; China; Jilin
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206588
作者单位	Jilin University, Changchun, China
推荐引用方式 GB/T 7714	Sun J.,Qin S.,Qiao S.,et al. Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility[J],2021,106(1).
APA	Sun J..,Qin S..,Qiao S..,Chen Y..,Su G..,...&Guo X..(2021).Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility.Natural Hazards,106(1).
MLA	Sun J.,et al."Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility".Natural Hazards 106.1(2021).