摘要
Landslides distribute extensively in Rongxian county, the southeast of Guangxi province, China and pose great threats to this county. At present, hazard management strategy is facing an unprecedented challenge due to lack of a landslide susceptibility map. Therefore, the purpose of this paper was to construct a landslide susceptibility map by adopting three widely used models based on an integrated understanding of landslide’s characteristics.These models include a semi-quantitative method(SQM), information value model(IVM) and logistical regression model(LRM).The primary results show that(1) the county is classified into four susceptive regions, named as very low, low, moderate and high, which covered an area of 13.43%, 32.40%, 31.19% and 22.99% in SQM, 0.86%, 26.82%, 44.11%, and 28.21% in IVM, 9.88%, 17.73%, 46.36% and 26.03% in LRM;(2) landslides are likely to occur within the areas characterized by following obvious aspects: high intensity of human activities, slope angles of 25°～35°, the thickness of weathered soil is larger than 15 m; the lithology is granite, shale and mud rock;(3) the area under the curve of SQM, IVM and LRM is 0.7151, 0.7688 and 0.7362 respectively, and the corresponding success rate is 71.51%, 76.88% and 73.62%. It is concluded that these three models are acceptable because they have an effective capability of susceptibility assessment and can achieve an expected accuracy. In addition, the susceptibility outcome obtained from IVM provides a slightly higher quality than that from SQM, LRM.
Landslides distribute extensively in Rongxian county, the southeast of Guangxi province, China and pose great threats to this county. At present, hazard management strategy is facing an unprecedented challenge due to lack of a landslide susceptibility map. Therefore, the purpose of this paper was to construct a landslide susceptibility map by adopting three widely used models based on an integrated understanding of landslide’s characteristics.These models include a semi-quantitative method(SQM), information value model(IVM) and logistical regression model(LRM).The primary results show that(1) the county is classified into four susceptive regions, named as very low, low, moderate and high, which covered an area of 13.43%, 32.40%, 31.19% and 22.99% in SQM, 0.86%, 26.82%, 44.11%, and 28.21% in IVM, 9.88%, 17.73%, 46.36% and 26.03% in LRM;(2) landslides are likely to occur within the areas characterized by following obvious aspects: high intensity of human activities, slope angles of 25°～35°, the thickness of weathered soil is larger than 15 m; the lithology is granite, shale and mud rock;(3) the area under the curve of SQM, IVM and LRM is 0.7151, 0.7688 and 0.7362 respectively, and the corresponding success rate is 71.51%, 76.88% and 73.62%. It is concluded that these three models are acceptable because they have an effective capability of susceptibility assessment and can achieve an expected accuracy. In addition, the susceptibility outcome obtained from IVM provides a slightly higher quality than that from SQM, LRM.
基金
funded by the National Natural Science Foundation of China (No. 51609041)
the Natural Scientific Project of Guangxi Zhuang Autonomous Region (No. 2018GXNSFAA138187)
the Project of the Education Department of Guangxi Zhuang Autonomous Region (No. 2018KY0027)
the Project of Department of Land and Resources of Guangxi Zhuang Autonomous Region (GXZC2018G3-19302-JGYZ)
the Project of Xi’an Geological survey center of China Geological survey (DD20189270)
