Debris-Flow Risk Assessment and Land Management at Municipal Scale

Murgese, Davide; Fontan, Dario; Pirulli, Marina; Scavia, Claudio; Oria, Paolo

doi:10.1007/978-3-642-31319-6_53

Cited by 1 publication

(1 citation statement)

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“…However, the inherent uncertainties in various facets of geological disasters render assessments, from spatial characteristics to disaster progression and consequences, highly uncertain [13]. With the continuous progress in risk management research, efforts in geological disaster prevention and mitigation have been further advanced [14][15][16]. Scholars such as Wu [17] and Zhang [18] conducted in-depth research on the theory and process of geological disaster risk assessment, leading to a substantial reduction in casualties resulting from geological disasters.…”

Section: Introductionmentioning

confidence: 99%

Preliminary Risk Assessment of Geological Disasters in Qinglong Gorge Scenic Area of Taihang Mountain with GIS Based on Analytic Hierarchy Process and Logistic Regression Model

Ma,

Lyu,

Chen

et al. 2023

Sustainability

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Qinglong Gorge Scenic Area (QGSA) boasts stunning natural landscapes, characterized by towering peaks and extensive cliffs. Nevertheless, the intricate geological backdrop and distinctive topographical conditions of this area give rise to various geological disasters, posing a substantial safety concern for tourists and presenting ongoing operational and safety management challenges for the scenic area. In light of these challenges, this study placed its focus on the geological disasters within QGSA and sought to assess risks across various scales. The assessment was accomplished through a combination of methods, including field surveys conducted in 2022, remote sensing interpretation, and comprehensive data collection and organization. For the geological disaster risk assessment of the scenic area, this research selected seven key indicators, encompassing terrain factors, geological elements, structural characteristics, and other relevant factors. The assessment utilized a logistic regression model, which yielded satisfactory results with an AUC value of 0.8338. Furthermore, a model was constructed incorporating seven indicators, encompassing factors such as population vulnerability, material susceptibility, and the vulnerability of tourism resources. To assess vulnerability to geological disasters, the Analytic Hierarchy Process (AHP) was employed, resulting in a CR of 0, thus ensuring the reliability of the findings. The outcomes of the risk assessment indicate that the low-risk area covers a substantial expanse of 5.45 km2, representing 53.66% of the total area. The moderate-risk area extends over 3.59 km2, constituting 35.43%, while the high-risk area encompasses 0.72 km2, accounting for 7.14%. Additionally, the very high-risk area encompasses 0.38 km2, making up 3.77% of the total area. Consequently, building upon the findings of the risk assessment, this paper introduces a risk classification and control prevention system. This system provides invaluable insights for disaster prevention and control in mountainous and canyon-type scenic areas.

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