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Risk models for assessing the derived disasters caused by watershed landslides using environmental indicators.
- Source :
-
Geomatics, Natural Hazards & Risk . Dec2020, Vol. 11 Issue 1, p318-334. 17p. - Publication Year :
- 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. (2017), 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *WATERSHED management
*LANDSLIDES
*GEOGRAPHIC information systems
*SOCIOECONOMICS
Subjects
Details
- Language :
- English
- ISSN :
- 19475705
- Volume :
- 11
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Geomatics, Natural Hazards & Risk
- Publication Type :
- Academic Journal
- Accession number :
- 147676872
- Full Text :
- https://doi.org/10.1080/19475705.2020.1713913