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2025 Vol. 52, No. 1
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ZHANG Yun, ZI Feng, GUO Jiehua, CAO Yunjiang, DUAN Jiuling, GUO Zhigang, TANG Long. Geological disaster risk assessment based on ecological niche model: A case study of Longhui County, Shaoyang City[J]. Hydrogeology & Engineering Geology, 2025, 52(1): 190-201. doi: 10.16030/j.cnki.issn.1000-3665.202308054
Citation: ZHANG Yun, ZI Feng, GUO Jiehua, CAO Yunjiang, DUAN Jiuling, GUO Zhigang, TANG Long. Geological disaster risk assessment based on ecological niche model: A case study of Longhui County, Shaoyang City[J]. Hydrogeology & Engineering Geology, 2025, 52(1): 190-201. doi: 10.16030/j.cnki.issn.1000-3665.202308054
shu

Geological disaster risk assessment based on ecological niche model: A case study of Longhui County, Shaoyang City

  • 1.

    School of Earth Sciences and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan, Hunan　411201, China

  • 2.

    Sichuan Institute of Geological Engineering Investigation Group Co. Ltd., Chengdu, Sichuan　610072, China

  • 3.

    Hunan Province Nature Resources Investigation Institute, Changsha, Hunan　410007, China

More Information
Received Date:  28 August 2023
Revised Date:  19 January 2024
Accepted Date:  26 January 2024
Publish Date:  15 January 2025
    Abstract

  • Geological disaster risk assessment is crucial for the prevention and control of geological disasters. This study focuses on the significant number of geological disasters induced by urbanization construction in Longhui County, aiming to propose effective preventive and control measures. The study considered various disaster-inducing factors and selected 13 assessment criteria from topography and geomorphology, geological structure, engineering geology of geotechnical bodies, and human engineering activities. The MaxEnt model is employed to establish the geological disaster hazard assessment model, while 7 assessment factors are selected from population distribution, economic background, environmental resources development, disaster prevention, and mitigation capacity. The systematic cluster analysis model was then utilized to establish a geological disaster vulnerability assessment model. The results of both assessments were integrated to construct a comprehensive geological disaster risk assessment model for the region, classifying areas into extremely low risk, low risk, medium risk, high risk, and extremely high risk. The result show that the AUC value of the MaxEnt model in the hazard assessment is 0.918, indicating its strong applicability in predicting the geological disaster hazard risk in the study area. Steep canyon, average annual rainfall, slope, and geotechnical construction are identified as the main factors influencing the development of geological disasters in the study area. The area classified as extremely high to high risk covers is 194.70 km², accounting for 6.80% of the total area. Under existing disaster reduction capacity, the area with extremely high to high risk has been reduced by 30.38%, reflecting a positive impact on disaster reduction. This study introduces a novel method for the risk assessment of geological disasters in Longhui County and provides a theoretical basis for the government’s risk management strategy.

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