Articles | Volume 22, issue 7
https://doi.org/10.5194/nhess-22-2239-2022
https://doi.org/10.5194/nhess-22-2239-2022
Research article
 | 
11 Jul 2022
Research article |  | 11 Jul 2022

Geographic information system models with fuzzy logic for susceptibility maps of debris flow using multiple types of parameters: a case study in Pinggu District of Beijing, China

Yiwei Zhang, Jianping Chen, Qing Wang, Chun Tan, Yongchao Li, Xiaohui Sun, and Yang Li

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Cited articles

Akbar, T. A. and Ha, S. R.: Landslide hazard zoning along Himalayan Kaghan Valley of Pakistan – by integration of GPS, GIS, and remote sensing technology, Landslides, 8, 527–540, https://doi.org/10.1007/s10346-011-0260-1, 2011. 
Beijing Municipal Commission of Planning and Natural Resources: The distribution map of potential geological hazard points and susceptibility map in pinggu district, http://ghzrzyw.beijing.gov.cn/zhengwuxinxi/zxzt/dzzhfzzt/zzzhdcpg/202008/t20200807_1976436.html, last access: 25 June 2022. 
Benda, L. E. and Dunne, T.: Sediment routing by debris flow, in: Erosion and sedimentation in the Pacific Rim, edited by: Beschta, R. L., Blinn, T., Grant, G. E., Swanson, F. J., and Ice, G. G., IAHS P., 213–223, https://doi.org/10.1111/j.1753-4887.1977.tb06503.x, 1987. 
Borrelli, L., Cofone, G., Coscarelli, R., and Gullà, G.: Shallow landslides triggered by consecutive rainfall events at Catanzaro strait (Calabria–Southern Italy), J. Maps, 11, 730–744, https://doi.org/10.1080/17445647.2014.943814, 2014. 
Bovis, M. and Dagg, B.: Debris flow triggering by impulsive loading - mechanical modeling and case-studies, Can. Geotech. J., 29, 345–352, https://doi.org/10.1139/t92-040, 1992. 
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Short summary
The disaster prevention and mitigation of debris flow is a very important scientific problem. Our model is based on geographic information system (GIS), combined with grey relational, data-driven and fuzzy logic methods. Through our results, we believe that the streamlining of factors and scientific classification should attract attention from other researchers to optimize a model. We also propose a good perspective to make better use of the watershed feature parameters.
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