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A method for evaluating population and infrastructure exposed to natural hazards: tests and results for two recent Tonga tsunamis.
Thomas, Bruce Enki Oscar; Roger, Jean; Gunnell, Yanni; Ashraf, Salman.
  • Thomas BEO; Institute of Geodesy (GIS), University of Stuttgart, Stuttgart, Germany.
  • Roger J; Earth Structure and Processes, GNS Science, Lower Hutt, New Zealand.
  • Gunnell Y; Université Lumière Lyon 2, CNRS UMR 5600, Bron, France.
  • Ashraf S; Data Science and Geohazards Monitoring, GNS Science, Lower Hutt, New Zealand.
Geoenvironmental Disasters ; 10(1): 4, 2023.
Article in English | MEDLINE | ID: covidwho-2284012
ABSTRACT

Background:

Coastal communities are highly exposed to ocean- and -related hazards but often lack an accurate population and infrastructure database. On January 15, 2022 and for many days thereafter, the Kingdom of Tonga was cut off from the rest of the world by a destructive tsunami associated with the Hunga Tonga Hunga Ha'apai volcanic eruption. This situation was made worse by COVID-19-related lockdowns and no precise idea of the magnitude and pattern of destruction incurred, confirming Tonga's position as second out of 172 countries ranked by the World Risk Index 2018. The occurrence of such events in remote island communities highlights the need for (1) precisely knowing the distribution of buildings, and (2) evaluating what proportion of those would be vulnerable to a tsunami. Methods and

Results:

A GIS-based dasymetric mapping method, previously tested in New Caledonia for assessing and calibrating population distribution at high resolution, is improved and implemented in less than a day to jointly map population clusters and critical elevation contours based on runup scenarios, and is tested against destruction patterns independently recorded in Tonga after the two recent tsunamis of 2009 and 2022. Results show that ~ 62% of the population of Tonga lives in well-defined clusters between sea level and the 15 m elevation contour. The patterns of vulnerability thus obtained for each island of the archipelago allow exposure and potential for cumulative damage to be ranked as a function of tsunami magnitude and source area.

Conclusions:

By relying on low-cost tools and incomplete datasets for rapid implementation in the context of natural disasters, this approach works for all types of natural hazards, is easily transferable to other insular settings, can assist in guiding emergency rescue targets, and can help to elaborate future land-use planning priorities for disaster risk reduction purposes. Supplementary Information The online version contains supplementary material available at 10.1186/s40677-023-00235-8.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Geoenvironmental Disasters Year: 2023 Document Type: Article Affiliation country: S40677-023-00235-8

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Geoenvironmental Disasters Year: 2023 Document Type: Article Affiliation country: S40677-023-00235-8