GIS-models with fuzzy logic for Susceptibility Maps of debris flow using multiple types of parameters: A Case Study in Pinggu District of Beijing, China
- 1College of Construction Engineering, Jilin University, Changchun 130026, China
- 2ChinaWater Northeastern Investigation, Design and Research Co., Ltd, Changchun, Jilin 130026, China
- 3North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Changchun, Jilin 130000, China
- 4Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, China
- 5University of Chinese Academy of Sciences
- 6Innovation Academy for Earth Science, Chinese Academy of Sciences, China
- 7Department of Earth Sciences and Engineering, Taiyuan University of Technology, Taiyuan 030024, China
- 8Beijing institute of geological and prospecting engineering, Beijing 100020, China
- 1College of Construction Engineering, Jilin University, Changchun 130026, China
- 2ChinaWater Northeastern Investigation, Design and Research Co., Ltd, Changchun, Jilin 130026, China
- 3North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Changchun, Jilin 130000, China
- 4Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, China
- 5University of Chinese Academy of Sciences
- 6Innovation Academy for Earth Science, Chinese Academy of Sciences, China
- 7Department of Earth Sciences and Engineering, Taiyuan University of Technology, Taiyuan 030024, China
- 8Beijing institute of geological and prospecting engineering, Beijing 100020, China
Abstract. Debris flow is one of the main causes of life loss and infrastructure damage in mountainous areas, so these hazards must be recognized in the early stage of land development planning. According to field investigation and expert experience, a scientific and effective quantitative susceptibility assessment model was established in Pinggu District of Beijing. This model is based on Geographic Information System (GIS), combining with grey relational method, data-driven and fuzzy logic methods. The inherent influence factors, which are divided into two categories, are selected in the model consistent with the system characteristics of debris flow gully and some new factors are proposed. The results of the 17 models are verified by the results published by the authority, and validated by the other two indexes as well as Area Under Curve (AUC). Through the comparison and analysis of the results, the method to optimize is proposed, including reasonable application of field investigation and expert experience, simplification of factors and scientific classification. Finally, the final optimal susceptibility map with full discussion has the potential to help in determining regional-scale land use planning and debris flow hazard mitigation for decision makers, with full use of insufficient data, scientific calculation, and reliable results. The model has advantages in economically backward areas with insufficient data in mountainous areas.
Yiwei Zhang et al.
Status: closed
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RC1: 'Comment on nhess-2021-254', Anonymous Referee #1, 27 Oct 2021
The paper entitled "Regional-scale GIS-models with fuzzy logic for Susceptibility Maps of debris flow: A Case Study in Pinggu District of Beijing, China", focused on the debris flow susceptibility map computation of a series of drainage basins of the Pinggu District of Beijing. The authors proposed a methodology based on GIS-models, combining diverse methods: grey relational method, data-driven and fuzzy logic methods. The manuscript deals with the application of susceptibility analysis on debris flow. The topic is interesting and is suitable for the journal. The model used in the manuscript not only considers the scientificity and accuracy, but also considers the application in engineering practice. I think the article can be acceptable after some revisions are made.
I have two main questions for the authors to explain:
- In ArcGIS, the watershed algorithm is to obtain the sub watershed units of the whole Pinggu region. How can the author select these specific watersheds in the article? How are other unqualified units excluded?
- How to explain the similarities and differences between models R6-R17?
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Specific comments are listed as follows:
- The introduction needs a section concerning susceptibility methods.
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- The Results and Discussion needs to be more detailed and organized.
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-The language in this article should be polished by a native speaker. The English is in some cases not good enough for the reviewer to understand the points the authors are trying to make, or follow their descriptions of the research.
Â
-Line 26 by the results → by results
Â
-Line 26 validated by the other two → validated by two other
Â
-Line 27 the method to → a method to
Â
-Line 47 significance to establishing → significance to establish
Â
Line 76 disaster chain and that the geomorphic → disaster chain and the geomorphic
Â
Line 76 rather than simple data fitting → rather than simply data fitting
Â
Line 80 account for → accounts for
Â
Line 90 1. Data and Methodology → 3 Data and Methodology
Â
Line 99 watershed characteristics factors → watershed characteristic factors
Â
Line 103 our primary assumption here are → our primary assumptions here are
Â
Line 103 First → Firstly
Â
Line 105 Second → Secondly
Â
Line 114Â by professional team--- by professional teams
Â
Line 138 factors (Type B) factors → factors (Type B)
Â
Line 159 a effective method → an effective method
Â
Line 169 3.4 fuzzy memberships → 3.4 Fuzzy memberships
Â
Line 217 can be used to derived their fuzzy →  can be used to derive their fuzzy
Â
Line 238 order to use properly → order to use it properly
Â
Line 247 Compared with other four fuzzy operator → Compared with other four fuzzy operators
Â
Line 247 Fuzzy Gamma (Eq.6) → Eq.5
Â
Line 261 seventeen results were compared (Table.6) → Table.5
Â
Line 278 the results is not comprehensive → the results are not as comprehensive
Â
Line 282 there are total 135 basin → there are total 135 basins
Â
Line 306  uncertain factor compared with factors compared → uncertain factors compared
Â
Line 309Â bedrock fracture flow; and root strength--- bedrock fracture flow, and root strength
Â
Line 334Â in which all factors as a single---in which all factors are considered as a single
Â
Line 362 nonlinear methods is consistent → nonlinear method is consistent
Â
Line 377 clear and the data easy to obtain → clear and the data is easy to obtain
- AC1: 'Reply on RC1', Jianping Chen, 20 Dec 2021
-
RC2: 'Comment on nhess-2021-254', Anonymous Referee #2, 15 Nov 2021
I have only partially revised the manuscript "GIS-models with fuzzy logic for Susceptibility Maps of debris flow using multiple types of parameters: A Case Study in Pinggu District of Beijing, China". The manuscript deals with the application of susceptibility analysis on debris flow and could be interesting for the journal. Unfortunately, the manuscript is not written in a good English and many statements and descriptions are very difficult to understand. I revised only up to line 203 (3.4.2 Data-driven method in susceptibility modelling). I recommend the authors to submit a revised version of the manuscript after the revision of an English-speaking person. Few comments are throughout the text.
- AC2: 'Reply on RC2', Jianping Chen, 20 Dec 2021
Status: closed
-
RC1: 'Comment on nhess-2021-254', Anonymous Referee #1, 27 Oct 2021
The paper entitled "Regional-scale GIS-models with fuzzy logic for Susceptibility Maps of debris flow: A Case Study in Pinggu District of Beijing, China", focused on the debris flow susceptibility map computation of a series of drainage basins of the Pinggu District of Beijing. The authors proposed a methodology based on GIS-models, combining diverse methods: grey relational method, data-driven and fuzzy logic methods. The manuscript deals with the application of susceptibility analysis on debris flow. The topic is interesting and is suitable for the journal. The model used in the manuscript not only considers the scientificity and accuracy, but also considers the application in engineering practice. I think the article can be acceptable after some revisions are made.
I have two main questions for the authors to explain:
- In ArcGIS, the watershed algorithm is to obtain the sub watershed units of the whole Pinggu region. How can the author select these specific watersheds in the article? How are other unqualified units excluded?
- How to explain the similarities and differences between models R6-R17?
Â
Specific comments are listed as follows:
- The introduction needs a section concerning susceptibility methods.
Â
- The Results and Discussion needs to be more detailed and organized.
Â
-The language in this article should be polished by a native speaker. The English is in some cases not good enough for the reviewer to understand the points the authors are trying to make, or follow their descriptions of the research.
Â
-Line 26 by the results → by results
Â
-Line 26 validated by the other two → validated by two other
Â
-Line 27 the method to → a method to
Â
-Line 47 significance to establishing → significance to establish
Â
Line 76 disaster chain and that the geomorphic → disaster chain and the geomorphic
Â
Line 76 rather than simple data fitting → rather than simply data fitting
Â
Line 80 account for → accounts for
Â
Line 90 1. Data and Methodology → 3 Data and Methodology
Â
Line 99 watershed characteristics factors → watershed characteristic factors
Â
Line 103 our primary assumption here are → our primary assumptions here are
Â
Line 103 First → Firstly
Â
Line 105 Second → Secondly
Â
Line 114Â by professional team--- by professional teams
Â
Line 138 factors (Type B) factors → factors (Type B)
Â
Line 159 a effective method → an effective method
Â
Line 169 3.4 fuzzy memberships → 3.4 Fuzzy memberships
Â
Line 217 can be used to derived their fuzzy →  can be used to derive their fuzzy
Â
Line 238 order to use properly → order to use it properly
Â
Line 247 Compared with other four fuzzy operator → Compared with other four fuzzy operators
Â
Line 247 Fuzzy Gamma (Eq.6) → Eq.5
Â
Line 261 seventeen results were compared (Table.6) → Table.5
Â
Line 278 the results is not comprehensive → the results are not as comprehensive
Â
Line 282 there are total 135 basin → there are total 135 basins
Â
Line 306  uncertain factor compared with factors compared → uncertain factors compared
Â
Line 309Â bedrock fracture flow; and root strength--- bedrock fracture flow, and root strength
Â
Line 334Â in which all factors as a single---in which all factors are considered as a single
Â
Line 362 nonlinear methods is consistent → nonlinear method is consistent
Â
Line 377 clear and the data easy to obtain → clear and the data is easy to obtain
- AC1: 'Reply on RC1', Jianping Chen, 20 Dec 2021
-
RC2: 'Comment on nhess-2021-254', Anonymous Referee #2, 15 Nov 2021
I have only partially revised the manuscript "GIS-models with fuzzy logic for Susceptibility Maps of debris flow using multiple types of parameters: A Case Study in Pinggu District of Beijing, China". The manuscript deals with the application of susceptibility analysis on debris flow and could be interesting for the journal. Unfortunately, the manuscript is not written in a good English and many statements and descriptions are very difficult to understand. I revised only up to line 203 (3.4.2 Data-driven method in susceptibility modelling). I recommend the authors to submit a revised version of the manuscript after the revision of an English-speaking person. Few comments are throughout the text.
- AC2: 'Reply on RC2', Jianping Chen, 20 Dec 2021
Yiwei Zhang et al.
Yiwei Zhang et al.
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