DOI : https://doi.org/10.18517/ijaseit.14.4.19952

Roughness Ecosystem-based Approach to Estimate the Exposure Area of Tsunami on a Coastal City: A Case Study in Bengkulu City, Indonesia

Della Ayu Lestari (1), Yonvitner (2), Ario Damar (3), Fery Kurniawan (4), I Wayan Nurjaya (5)
(1) Department of Geography, Faculty of Social Sciences, Universitas Negeri Jakarta, Jakarta, Indonesia
(2) Centre for Coastal and Marine Resources Studies, IPB University, Bogor, West Java, Indonesia
(3) Centre for Coastal and Marine Resources Studies, IPB University, Bogor, West Java, Indonesia
(4) Centre for Coastal and Marine Resources Studies, IPB University, Bogor, West Java, Indonesia
(5) Department of Marine Science and Technology, Faculty of Fisheries and Marine Sciences, IPB University, Bogor, West Java, Indonesia
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How to cite (IJASEIT) :
Lestari, Della Ayu, et al. “Roughness Ecosystem-Based Approach to Estimate the Exposure Area of Tsunami on a Coastal City: A Case Study in Bengkulu City, Indonesia”. International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 4, Aug. 2024, pp. 1373-82, doi:10.18517/ijaseit.14.4.19952.
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Bengkulu City, as the main activity center in Bengkulu Province, is experiencing significant population growth. However, geographically, the city is vulnerable to tsunami disasters. High population growth outside the line with coastal area management also increases the risk of tsunami disasters in Bengkulu City due to green land conversion into built-up land. This condition is exacerbated by coastal abrasion that threatens the coastline, brings residential settlements closer to the shoreline, and conflicts over spatial utilization of the coastal green belt. Therefore, implementing tsunami mitigation measures, mainly through coastal ecosystem-based strategies, is crucial. This study compares the spatial modeling of tsunami inundation in Bengkulu City with three roughness scenarios of coastal vegetation: coastal forest and mangrove. These scenarios include a scenario without coastal vegetation, a scenario based on existing conditions, and a scenario with optimized coastal vegetation. Spatial modeling was conducted using cost distance analysis modeling to calculate the effectiveness of coastal vegetation in reducing tsunamis. The results showed that coastal forests and mangroves in existing conditions could effectively reduce tsunamis by 3.84% compared to land cover without coastal forests and mangroves. The coastal vegetation optimization scenario has effectively reduced the exposure area by 5.00% compared to that without vegetation. The coastal vegetation optimization scenario also has an effectiveness of 1.20% compared to the existing condition. The findings underscore the critical role of coastal vegetation as a natural barrier against tsunamis and emphasize the potential advantages of optimizing land cover to improve coastal protection.

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