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Risk models for assessing the derived disasters caused by watershed landslides using environmental indicators

Authors :
Chao-Yuan Lin
Tzu-Ching Chen
Cheng-Yu Lin
Source :
Geomatics, Natural Hazards & Risk, Vol 11, Iss 1, Pp 318-334 (2020)
Publication Year :
2020
Publisher :
Taylor & Francis Group, 2020.

Abstract

Lands reserved for indigenous people in Taiwan are mostly located at junctions between forestry compartments and hillside lands. After heavy rains, sediment disasters can easily occur in such locations. Therefore, identifying primary and derived disaster landslide areas of watersheds in lands reserved for indigenous people is imperative. This study used landslide-prone slopes to correct the vulnerability variable in the model proposed by Lin et al. (), and recalculated the landslide risks of watersheds. In addition, the study used protected objects as study subjects, and considered the likelihood of landslide disaster occurrence and its scale. Risk models for assessing the derived disasters caused by watershed landslides were constructed according to the spatial distribution of sediment delivery ratio. Comparisons between the present model and the original model regarding the relationship between landslide risks and landslide ratios in watershed subdivisions reveal that the corrected model shows significant positive correlation (R2 increased from 0.59 to 0.91). Risk models for assessing the derived disasters caused by watershed landslides indicate that the risk and the disaster ratio of the watershed subdivisions show significant and positive correlation (R2=0.84), indicating that the model developed in this study can effectively estimate the likelihood of protected objects encountering sediment disasters.

Details

Language :
English
ISSN :
19475705 and 19475713
Volume :
11
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Geomatics, Natural Hazards & Risk
Publication Type :
Academic Journal
Accession number :
edsdoj.7a357a2c0dd4449f9b0913c606d2e521
Document Type :
article
Full Text :
https://doi.org/10.1080/19475705.2020.1713913