Estimating Tsunami Economic Losses of Okinawa Island with Multi-Regional-Input-Output Modeling

Abstract

Understanding the impacts of tsunamis, especially in terms of damage and losses, is important for disaster mitigation and management. The aim of this study is to present our estimations of the potential losses from tsunami damage on Okinawa Island. We combine the use of a tsunami hazard map and our proposed economic loss model to estimate the potential losses that would be sustained by Okinawa Island in the event of a tsunami. First, to produce the tsunami hazard map, we calculated tsunami flow characteristics using the mathematical model TUNAMI-N2 and incorporating 6 earthquake fault scenarios around the study area. The earthquake scenarios are based on historical records along the Ryukyu Trench and the Okinawa. The resulting inundation map is overlaid with economic land use type and topography maps to identify vulnerable regions, which are then employed to compute potential economic losses. Second, we used our proposed economic model for this study area to calculate the potential losses that would be sustained in these vulnerable regions. Our economic model extends the multi-regional-input-output (MRIO) model, where the economic values of industrial sectors are scaled to correlate with land use and topography types (coastal and inland areas) to calculate losses through the Chenery–Moses estimation method. Direct losses can be estimated from the total input of the MRIO table, while indirect losses are computed from the direct losses and interaction parameter of the MRIO table. The interaction parameter is formed by linear programming and calculated using the Leontief methodology. Our results show that the maximum total damaged area under the 6 earthquake scenarios is approximately 30 km2. Inundation ranging from 2.0 to 5.0 m in depth covers the largest area of approximately 10 km2 and is followed by areas with inundation depths of 1.0–2.0 m and >5.0 m. Our findings show that direct losses will occur, while indirect losses are only approximately 56% that of direct losses. This approach could be applied to other areas and tsunami scenarios, which will aid disaster management and adaptation policies.

The near-field tsunami generated by the 15 January 2022 eruption of the Hunga Tonga-Hunga Ha’apai volcano and its impact on Tongatapu, Tonga

“… where is the water level; M and N are discharge fluxes in the (along a parallel of latitude) and (along the longitude cycle) directions, respectively; D is the total depth; g is the gravitational constant; R is the Earth’s radius; n is Manning’s roughness coefficient; h is the static water depth; and is the angular velocity of Earth’s rotation. In this study, the bottom friction is based on Manning’s roughness coefficient of 0.025 28 , 60 , and the finite differential equation is solved at each time step of 0.01 seconds 29 . The Open Multi-Processing (OpenMP) platform was adopted to achieve a faster computation time.…”

Analysis of small microplastics in coastal surface water samples of the subtropical island of Okinawa, Japan

“…This result correlates well with a recent study by Kitahara et al [44], finding small plastics in road dust on Okinawa. Although the population density is highest in Naha and most land use is urban [45,46], plastic particles in the road dust were lower in front of our station S10 [44]. Another reason for finding the second highest plastic pollution at this station is the location outside of a bay.…”

“…In total we have identified 282 particles by employing the OTRS method, of which 48 are sub-micron plastics. The plastic pollution observed for sub-micron plastics follows the population gradient of the island [45,46]. There is a clear distinction between the northern (Figure 1), less populated part of Okinawa, and the southern part with high population density.…”

“…In the central part of the island, the land use shifts from urban areas to more forest cover [45,46]. Traffic density goes down by between one third to about one half that found in the southern part of the island [44].…”

Interdisciplinary Geosciences Perspectives of Tsunami Volume 2

“…Paulik et al (2019) [7] applied the loss model to assess changes in tsunami risk to residential buildings using an example in Omaha Beach, New Zealand, which is another example of tsunami vulnerability research. Pakoksung et al (2019) [8] newly applied an economic model with a tsunami simulation to estimate both the direct and indirect economic losses in the case of tsunami in a well-known tourism area, Okinawa Island, Japan. Tsunami wave forces and debris impact forces are not only the two main causes of damage, but also fires.…”