The impact of physiographic factors upon the probability of slides occurrence: a case study from the Kaoping River Basin, Taiwan. (4th July 2018)

• Record Type: Journal Article
• Authors: Fan, Jen-Chen; Chang, Shih-Chun; Liao, Kuo-Wei; Guo, Jia-Jun; Liu, Che-Hsin; Chang, Yu-Cheng; Huang, Chien-Lin; Yang, Chih-Hsiang
• Is Part Of: Journal of the Chinese Institute of Engineers. Volume 41:Number 5(2018)
• Page Start: 419
• Page End: 429
• Publication Date: 2018-07-04
• Subjects: Physiographic factors -- the landslide ratio -- logistic regression -- probability of slide occurrence -- nonparametric statistical test; Technology -- Periodicals; Engineering -- Periodicals; 620.005
• DOI: 10.1080/02533839.2018.1482236
• Languages: English
• ISSNs: 0253-3839

Abstract

ABSTRACT: This study has investigated the influence of physiographic factors upon the probability of slide occurrence in the Kaoping River Basin. According to previous literature, statistical tests, and physical mechanisms, three physiographic factors (slope steepness, the dip slope ratio, and the time-dependent landslide ratio) were significantly related to slide occurrence. These were combined with hydrological factors (cumulative rainfall) to establish an assessment model for estimating the probability of slide occurrence using logistic regression. The model's overall accuracy in the training and validation stages was about 81%. Overall, 20 randomly selected historical rainfall events were employed for verification, including 10 events each with and without slide occurrence. The results showed that the model accuracy was approximately 80%, if the probability threshold Psh is set to be 0.5. This assessment model can assist in prediction of slide occurrence and the proposed subsequent engineering measures or vegetation restoration is often able to reduce the landslide ratio and the probability of slide occurrence. After landform changes, the model's physiographic factors can be updated to adjust the rainfall threshold for slide occurrence. Given an appropriate cumulative rainfall and an acceptable risk of slide occurrence, the model can identify priority regions for slide prevention.