Adopting the I3–R24 rainfall index and landslide susceptibility for the establishment of an early warning model for rainfall-induced shallow landslides

Rainfall-induced landslides number among the most devastating natural hazards in the world and early warning models are urgently needed to reduce losses and fatalities. Most landslide early warning systems are based on rainfall thresholds defined on the regional scale, regardless of the different la...

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Bibliographic Details
Published inNatural hazards and earth system sciences Vol. 18; no. 6; pp. 1717 - 1733
Main Authors Lun-Wei, Wei, Chuen-Ming Huang, Chen, Hongey, Lee, Chyi-Tyi, Chun-Chi, Chi, Chen-Lung, Chiu
Format Journal Article
LanguageEnglish
Published Katlenburg-Lindau Copernicus GmbH 20.06.2018
Copernicus Publications
Subjects
Casualties
Duration
Early warning systems
Field investigations
Geology
Landslide warnings
Landslides
Landslides & mudslides
Lithology
Local government
Rain
Rainfall
Rainfall index
Rainfall intensity
Rainfall patterns
Regression analysis
Slopes
Software
Statistical analysis
Studies
Thresholds
Warning systems
Taiwan
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Summary:Rainfall-induced landslides number among the most devastating natural hazards in the world and early warning models are urgently needed to reduce losses and fatalities. Most landslide early warning systems are based on rainfall thresholds defined on the regional scale, regardless of the different landslide susceptibilities of various slopes. Here we divided slope units in southern Taiwan into three categories (high, moderate and low) according to their susceptibility. For each category, we established separate rainfall thresholds so as to provide differentiated thresholds for different degrees of susceptibility. Logistic regression (LR) analysis was performed to evaluate landslide susceptibility by using event-based landslide inventories and predisposing factors. Analysis of rainfall patterns of 941 landslide cases gathered from field investigation led to the recognition that 3 h mean rainfall intensity (I3) is a key rainfall index for rainfall of short duration but high intensity; in contrast, 24 h accumulated rainfall (R24) was recognized as a key rainfall index for rainfall of long duration but low intensity. Thus, the I3–R24 rainfall index was used to establish rainfall thresholds in this study. Finally, an early warning model is proposed by setting alert levels including yellow (advisory), orange (watch) and red (warning) according to a hazard matrix. These differentiated thresholds and alert levels can provide essential information for local governments to use in deciding whether to evacuate residents.
ISSN:1561-8633
1684-9981
DOI:10.5194/nhess-18-1717-2018