Applying rainfall threshold estimates and frequency ratio model for landslide hazard assessment in the coastal mountain setting of South Asia
Akhtar Alam, Bayes Ahmed, Peter Sammonds, A. S. M. Maksud Kamal
Abstract
Landslides pose a serious risk to life and property in the mountainous regions around the globe. Understanding the interplay of landslide conditioning and triggering factors is essential for lessening the impacts caused by the hazard. Cox's Bazar — a coastal mountainous district in Bangladesh is recurrently affected by rainfall-triggered landslides. Based on analysis of 14 experiential landslides and combination of gauged and satellite based rainfall estimates for the period from 2003 to 2019, the present study determines three landslide-triggering rainfall thresholds: 1. Intensity-Duration (ID) threshold derived in this study revealed that any rainfall event with an intensity of ≥4.04 mm/h if prolonging for ≥12h can cause slope failures in the Cox's Bazar District (CBD); 2. Event-Duration (ED) threshold suggested that a rainfall event with normalized cumulative event rainfall (EMAP) of 0.15 for one day is expected to trigger landslides; and 3. threshold calculated using randomly chosen antecedent rainfall expressed best distinction on 30-day rainfall and the equation of the threshold came out as Rth = 64–0.02 Ra30. The incidence probability of expected landslides was determined at various intervals using the derived antecedent rainfall threshold. The recurrence probability of the thresholds was observed as 91% within one year. Moreover, we assess the landslide susceptibility of the district with a coupled use of Frequency Ratio (FR) statistical measure and Geographic Information System (GIS). Based on the combined role of conditioning factors, the landslide susceptibility status of the CBD was quantified and classified into probability intervals. The accuracy of the susceptibility maps was assessed through Relative Landslide Density Index (R-Index) that used field based landslide inventory, comprising well distributed 891 events. Gridded population data was superimposed on the derived susceptibility maps to understand the risk levels of people. The derivation of landslide-triggering rainfall thresholds and spatial susceptibility assessment has been useful to propose a low-cost Landslide Early Warning System (LEWS) which can contribute in alleviating the adverse effects of landslide hazard in the CBD.