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

Abstract

Abstract. Debris flow is one of the main causes of loss of life and infrastructure damage in mountainous areas. This hazard should 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) combined with grey relational, data-driven and fuzzy logic methods. The influence factors, which are divided into two categories and consistent with the system characteristics of a debris flow gully, are selected, but also a new important factor is proposed. The results of the 17 models are verified using data published by the authority and validated by two other indexes, as well as area under curve (AUC). Through the comparison and analysis of the 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. These parameters fit well with the watershed units. With full use of insufficient data, scientific calculation and reliable results, the final optimal susceptibility map could potentially help decision makers in determining regional-scale land use planning and debris flow hazard mitigation. The model has advantages in economically weak areas with insufficient data in mountainous areas because of its simplicity, interpretability and engineering usefulness.

Machine learning approaches to debris flow susceptibility analyses in the Yunnan section of the Nujiang River Basin

“…Raster cells and watershed units in DEM are commonly used for susceptibility assessments ( Zou et al, 2017 ). Raster cells are more convenient for modelling and calculation because of their regular shape and uniform size, while watershed units can represent integrated geomorphological characteristics of hydrological processes, and that helps in obtaining the actual conditions of debris flow ( Liu et al, 2018 ; Qiang et al, 2019 ; Zhang et al, 2022 ). Therefore, we adopted watershed units as the basic evaluation units and used ArcMap’s hydrological analysis tools to categorize the 30 m spatial resolution DEM data of the YNR Basin.…”