Hazard regionalization of debris flow disasters along highways based on genetic algorithm and cloud model
(2.State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China 100001)
(3.Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang’an University, Xi’an, Shaanxi, China 710054)
【Abstract】Hazard regionalization of debris flow disasters along highways clarifies the priorities of disaster prevention and protection standards for different parts of China and provides a theoretical basis for macro policy formulation. Hazard sources of debris flow disasters along highways were identified from four aspects of the topography and landscape, precipitation, rock and soil materials, and vegetation. The hazard assessment indexes were extracted using the genetic algorithm according to the survey results of the potential debris flow disasters along highways. The weight of each index was calculated through the AHP algorithm improved by the cloud model. The assessment index maps were rendered and the spatial hazard analysis of debris flow disasters along highways was made with Arc GIS. The hazard regionalization scheme of debris flow disasters along highways in China was worked out mainly based on a hazardous degree. The hazardous degree of debris flow disasters along highways in China is from 1.000 to 7.900. High hazardous areas are the mountainous areas in the southeast of Zhejiang and Fujian Province, the mountain areas of Taiwan, Kunlun Mountains, Tianshan Mountains, Taihang Mountains, Loess Plateau, Hengduan Mountains, and eastern Tibetan Plateau. China is divided into regions of low hazard, moderate hazard, severe hazard, and extremely severe hazard. The extremely severe hazard areas are the Loess Plateau–Qinba mountain areas, Wuyi Mountain–Taiwan mountain areas, Sichuan-Yunnan mountain areas, and Tianshan–Kunlun mountain areas.
【Keywords】 engineering geology; debris flow disaster along highway; assessment index; genetic algorithm; AHP algorithm improved by cloud model;
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