Preprints
https://doi.org/10.5194/nhess-2021-254
https://doi.org/10.5194/nhess-2021-254

  20 Sep 2021

20 Sep 2021

Review status: this preprint is currently under review for the journal NHESS.

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

Yiwei Zhang1, Jianping Chen1, Qing Wang1, Chun Tan2,3, Yongchao Li4,5,6, Xiaohui Sun7, and Yang Li8 Yiwei Zhang et al.
  • 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: open (until 17 Nov 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Yiwei Zhang et al.

Yiwei Zhang et al.

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Short summary
Beijing is the capital, it is important to do research on disaster prevention and reduction. In this paper, the author found that the accuracy of susceptibility assessment model is improved by efficiently using the field survey data rather than data fitting. The study found that effective use of field survey data, reasonable classification and simplification of factors can improve the accuracy of susceptibility assessment method. A new factor-watershed volume is proposed in this paper.
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