Multiscale Quantification of Tsunami Hazard Exposure in a Pacific Small Island Developing State: The Case of Samoa

Abstract

This study presents a scenario-based approach for identifying and comparing tsunami exposure across different sociopolitical scales. In Samoa, a country with a high threat to local tsunamis, we apply scenarios for the 2009 South Pacific tsunami inundation at different grid resolutions (50 and 10 m) to quantify building and road exposure at the national, district and village levels. We show that while the coarser 50 m model is adequate for use in the rapid identification of exposure at the national and district levels, it can overestimate exposure by up to three times more at the village level. Overestimation typically occurs in areas characterized by flat, low-lying, gentle-rising terrain. Overall, a 35% increase in buildings exposed to the 50 m model is observed compared with the 10 m scenario on southeast Upolu island. Similarly, a 31% increase in road exposure is observed for the 50 m scenario. These observations are discussed within the context of tsunami evacuation planning and logistics. Notwithstanding the variability in exposure, a precautionary approach leads us to conclude that while higher-resolution models are recommended where available data and/or financial resources permit, the absence of such datasets should not preclude the use of coarser hazard datasets in risk assessments. Finer-resolution models provide more credence in detailed local-level exposure evaluation. While the results of this study are specific to the Samoan context, the results can be applied to the multiscale assessment of tsunami risk exposure in similar hazard contexts.

Sea-Level Rise Effects on Changing Hazard Exposure to Far-Field Tsunamis in a Volcanic Pacific Island

“…Notwithstanding the focus of this study, the findings imply that SLR will compound the impacts of near-field tsunamis which presently expose large quantities of assets (e.g., [36,42,43]) and can cause destructive damages and losses (e.g., [36,38]). Similar inferences could be made for high-frequency, low-magnitude, coastal inundation hazards, such as king tides and cyclonerelated storm surges (e.g., [44]), whereby RSLR may compound present day exposure and impact levels across the Pacific.…”

Quantifying National-Scale Changes in Agricultural Land Exposure to Fluvial Flooding

“…Exposure mapping was undertaken by using the RiskScape multi-hazard risk model framework [53]. This modular framework is configured to produce exposure and impact data by analyzing hazard data and the characteristics of the assets at risk, and it has been applied in exposure studies in New Zealand and the wider Pacific region [54][55][56][57][58]. The RiskScape engine computes user-defined risk/exposure/vulnerability calculations for these hazards and assets.…”

RiskScape: a flexible multi-hazard risk modelling engine

“…RiskScape is used in several previous modelling studies (e.g. Craig et al 2021;Paulik et al 2021;Williams et al 2021;Woods et al 2021); however, this paper is its first formal description. The RiskScape engine, system architecture and features are presented, with a focus on 'model pipelines' for risk quantification.…”