Abstract

Rainfall thresholds for slope failures are essential information for establishing early-warning systems and for disaster risk reduction. Studies on the thresholds for rainfall-induced landslides of different scales have been undertaken in recent decades. This study attempts to establish a warning threshold for large-scale landslides (LSLs), which are defined as landslides with a disturbed area more massive than 0.1 km2. The numerous landslides and extensive rainfall records make Taiwan an appropriate area to investigate the rainfall conditions that can result in LSLs. We used landslide information from multiple sources and rainfall data captured by 594 rain gauges to create a database of 83 rainfall events associated with LSLs in Taiwan between 2001 and 2016. The corresponding rainfall duration, cumulative event rainfall, and rainfall intensity for triggering LSLs were determined. This study adopted the tank model to estimate conceptual water depths (S1, S2, S3) in three-layer tanks and calculated the soil water index (SWI) by summing up the water depths in the three tanks. The empirical SWI and duration (SWI–D) threshold for triggering LSLs occurring during 2001–2013 in Taiwan is determined as SWI = 155.20 − 1.56D and D ≥ 24 h. The SWI–D threshold for LSLs is higher than that for small-scale landslides (SSLs), those with a disturbed area smaller than 0.1 km2. The LSLs that occurred during 2015–2016 support this finding. It is notable that when the SWI and S3 reached high values, the potential of LSLs increased significantly. The rainfall conditions for triggering LSLs gradually descend with increases in antecedent SWI. Unlike the rainfall conditions for triggering SSLs, those for triggering LSLs are related to the long duration–high intensity type of rainfall event.

Highlights

  • In the past two decades, the frequency of occurrence of extreme rainfall events and large-scale natural hazards has increased significantly worldwide [1,2,3,4,5,6], causing substantial economic losses and human casualties

  • To define the rainfall threshold for landslide initiation, a detailed analysis of the rainfall conditions for the 83 landslides considered in the study was performed

  • The duration (D) analysis showed that 63 of the LSLs occurred when the rainfall duration was longer than 48 h, and only one case had a duration time of less than 24 h

Read more

Summary

Introduction

In the past two decades, the frequency of occurrence of extreme rainfall events and large-scale natural hazards has increased significantly worldwide [1,2,3,4,5,6], causing substantial economic losses and human casualties. The rainfall conditions that induce LSLs must be determined and used to define a rainfall threshold as a criterion of early-warning for the prevention and mitigation of disasters. Et al [27] first proposed the SWI–D curve as an empirical rainfall threshold for shallow landslides in Taiwan They noted that the SWI can be used as the indicator of the antecedent rainfall condition and recommended establishing a suitable warning system in Taiwan. SWI and rainfall duration can be used to determine the critical threshold for triggering LSLs. this study attempts to construct a multi-threshold model different from the single threshold for shallow landslides constructed in the past to provide a new landslide warning model, which can be used at different stages or for landslides of different scales. The threshold will provide invaluable information for helping disaster management authorities to alert the general public and prepare for prevention and disaster mitigation

Study Area
Landslide Data
Rainfall Data
Soil Water Index
Rainfall Conditions and SWI for Triggering Large-Scale Landslides
Comparison with Small-Scale Landslides
Effect of Antecedent SWI
Conclusions

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.