Landslide warning system integrated with ensemble rainfall forecasts
Journal
Journal of Taiwan Agricultural Engineering
Journal Volume
63
Journal Issue
4
Pages
79
Date Issued
2017-12-01
Author(s)
Abstract
© 2018, Taiwan Agricultural Engineers Society. All rights reserved. Taiwan is prone to hillslope disasters in the mountain area because of its special topographical, geological, and hydrological conditions. During typhoons and rainstorms, severe shallow landslides frequently occur. To mitigate the impact of shallow landslides, not only the structural measures are necessary, but also adequate warning systems and contingency measures must be executed. Hence, precise precipitation forecasts and landslide prediction are the most important measures in practice. To account for inherent weather uncertainties precipitation forecasts based on ensemble model predictions was adopted in this project instead of using a single model output. A shallow landslide prediction model based on infinite-slope model and TOPMODEL was developed. In considering detail topographic characteristics of the subcatchment, the proposed model can estimate the change of saturated water level during rainstorms, and then link with the slope instability analysis to clarify whether shallow landslides can occur in the subcatchment. The subcatchment on No. 9A Highway at 10.2 K was selected as the test sites for landslide predictions with a lead time of 6 hours. Hydrological data and landslide observed records from 10 typhoons events were used to verify the applicability of the model. Four indexes including the probability of detection (POD), false alarm ratio (FAR), and threat score (TS) were adopted to assess the performance of the model. The results indicated that the POD for the landslide prediction by using the proposed model was higher than 0.73, the FAR was lower than 0.33, and the TS was higher than 0.53. It is promising to apply the proposed model for landslide early warnings to reduce the loss of life and property.
Subjects
Changes in saturated water levels | Ensemble rainfall forecasts | Landslide warning system
SDGs
Type
journal article