Geological and Geomorphological Tsunami Hazard Analysis for the Maldives Using an Integrated WE Method and a LR Model

Mahmood Riyaz, Anawat Suppasri

Research output: Contribution to journalArticle

Abstract

This study presents a tsunami hazard analysis for the Maldives using integrated statistical approaches, such as the WE (weight of evidence) method and a LR (logistic regression) model, using historical flooding records from the Maldives following the 2004 Indian Ocean Tsunami. The data with respect to the geological and geomorphological parameters of the islands and reefs, which were collected from 202 inhabited islands and seven resorts in the Maldives, were weighted by the presence/absence of evidence from the impacted islands. The tsunami hazard and risk were evaluated using spatial weights calculated for each variable. The predicted tsunami risk was compared with the impact of the 2004 Indian Ocean Tsunami. The results show that for the three cases, the success rate of the estimated hazard and risk prediction ranged between 74% and 90% for the low and high impact islands, respectively. However, the predictability for medium impact islands in the three cases was within the range of 52-58%. The results of this study can be applied to hazard and risk assessments, are useful for tsunami behavior model development for coral islands and can be used to identify islands that are naturally protected, sheltered or resilient against natural disasters, such as tsunamis.

Original languageEnglish
Article number1650003
JournalJournal of Earthquake and Tsunami
Volume10
Issue number1
DOIs
Publication statusPublished - 2016 Mar 1

Keywords

  • Reef islands
  • reef morphology
  • risk assessment
  • the Maldives
  • tsunami hazard

ASJC Scopus subject areas

  • Oceanography
  • Geotechnical Engineering and Engineering Geology
  • Geophysics

Fingerprint Dive into the research topics of 'Geological and Geomorphological Tsunami Hazard Analysis for the Maldives Using an Integrated WE Method and a LR Model'. Together they form a unique fingerprint.

  • Cite this