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

Natural Hazards Research (Sep 2023)

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

Affiliations

Akhtar Alam: Department of Geography and Disaster Management, University of Kashmir, Srinagar, 190006, India; Institute for Risk and Disaster Reduction, University College London, Gower Street, London, WC1E 6BT, United Kingdom; Corresponding author. Department of Geography and Disaster Management, University of Kashmir, Srinagar, 190006, India.
Bayes Ahmed: Institute for Risk and Disaster Reduction, University College London, Gower Street, London, WC1E 6BT, United Kingdom
Peter Sammonds: Institute for Risk and Disaster Reduction, University College London, Gower Street, London, WC1E 6BT, United Kingdom
A.S.M. Maksud Kamal: Department of Disaster Science and Climate Resilience, University of Dhaka, Dhaka, 1000, Bangladesh

Journal volume & issue: Vol. 3, no. 3
pp. 531 – 545

Abstract

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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 rainfall estimates for the period from 2003 to 2019, the present study determines three landslide-triggering rainfall thresholds for the Cox's Bazar District (CBD): 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; 2. Event-Duration (ED) threshold suggested that a 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 recurrence probability of the derived antecedent rainfall threshold and likely landslides was determined through the Poisson distribution. Moreover, we assess the landslide susceptibility of the district with a coupled use of Frequency Ratio (FR) statistical measure and Geographic Information System (GIS). Considering the combined role of selected 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 the Relative Landslide Density Index (R-Index) that used a field landslide inventory, comprising well distributed 891 events. Moreover, 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.

Published in Natural Hazards Research

ISSN: 2666-5921 (Online)
Publisher: KeAi Communications Co. Ltd.
Country of publisher: China
LCC subjects: Science: Geology; Science: Physics: Geophysics. Cosmic physics
Website: https://www.keaipublishing.com/en/journals/natural-hazards-research/

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