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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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-254', Anonymous Referee #1, 27 Oct 2021
    • AC1: 'Reply on RC1', Jianping Chen, 20 Dec 2021
  • RC2: 'Comment on nhess-2021-254', Anonymous Referee #2, 15 Nov 2021
    • AC2: 'Reply on RC2', Jianping Chen, 20 Dec 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (26 Mar 2022) by Heidi Kreibich
AR by Jianping Chen on behalf of the Authors (06 Apr 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (10 Apr 2022) by Heidi Kreibich
RR by Anonymous Referee #1 (18 Apr 2022)
RR by Anonymous Referee #3 (21 May 2022)
ED: Publish subject to minor revisions (review by editor) (21 May 2022) by Heidi Kreibich
AR by Jianping Chen on behalf of the Authors (25 May 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (06 Jun 2022) by Heidi Kreibich
ED: Publish subject to technical corrections (06 Jun 2022) by Heidi Kreibich (Executive editor)
AR by Jianping Chen on behalf of the Authors (10 Jun 2022)  Manuscript 
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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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