Abstract

In China, the majority of mountainous regions are characterized by complex topography and a delicate, sensitive geological environment. These areas, which exhibit insufficient infrastructure and widespread irrational human engineering activities, are often susceptible to geological hazards such as slope instability and soil mass movements. These geological hazards pose substantial threats to human lives and property, hindering the progress of mountainous areas. Therefore, conducting research on evaluating the vulnerability of slope rock and soil mass movement geological hazards (hereinafter referred to as geological hazards) is of utmost importance for hazard prevention, emergency management, and economic advancement in these regions. This study focuses on Xuanwei City and selects eight factors for evaluation, including elevation, gradient, slope aspect, normalized vegetation index, stratigraphic lithology, distance from faults, distance from rivers, and distance from roads. These factors are chosen based on a comprehensive analysis of the spatial and temporal distribution of geological hazards and hazard incubation conditions. Two paired models, the deterministic coefficient model + logistic regression model (CF+LR) and the information quantity model + logistic regression model (I+LR), were employed to assess the study area quantitatively. The performance of these models was assessed by employing receiver operating characteristic (ROC) curves and calculating the corresponding area under curve (AUC) values. The results indicate that: (1) The AUC values for the coupled CF+LR and I+LR models are 0.799 and 0.772, respectively. These results indicate that both models provide an objective and reliable assessment of the vulnerability to geological hazards, specifically slope rock and soil mass movements, in the study area. (2) Based on the CF+LR model calculations, the geological hazard susceptibility of Xuanwei City can be categorized into four zones: extremely high susceptibility (6.09%), high susceptibility (31.08%), medium susceptibility (32.26%), and low susceptibility (30.57%). (3) The CF+LR model more accurately represents the evaluation results and offers a strong reference value.

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