MATEC Web Conf.
Volume 197, 2018The 3rd Annual Applied Science and Engineering Conference (AASEC 2018)
|Number of page(s)||4|
|Published online||12 September 2018|
Development risk analysis method for tsunami disaster
Andalas University, Department of Civil Engineering, Padang, Indonesia
2 Andalas University, Department of Environmental Engineering, Padang, Indonesia
3 Andalas University, Department of Civil Engineering, Padang, Indonesia
* Corresponding author: email@example.com
After tsunami disaster hit Aceh and Mentawai Island, Indonesia Government prepare disaster prevention plan for the areas that could be hit by tsunami disaster. Government has predicted that 19 areas could hit by tsunami disaster if big earthquake occur in that areas. Based on that condition, Regional Disaster Management Agency (BPBD) in several cities has prepared the evacuation facilities to reduce the effect of tsunami if the disaster is occurred. Although, the evacuation facilities have been built, however the risk from the impact of tsunami in that areas are still could not be measured. This paper shows the method to measure tsunami disaster risk, and method to determine the priorities handling tsunami impacts in certain area. This risk analysis method was developed based on risk analysis method developed by Federal Emergency Management Agency (FEMA). The risk of tsunami disaster is determined based on three parameters, i.e: threat of tsunami, vulnerability of people, infrastructure and agriculture, the inundation impact of tsunami. The priorities of tsunami risk handling to the affected areas are determined based on the Risk Prioritisation Index (RPI). The RPI values could be determined from the risk analysis values. The RPI values indicate the risk exposure rank in the tsunami affected areas. From analysis RPI value of each area, Government could determine the area that should be prioritising prevention to facing tsunami disaster because of the high risk level that could be occurred in that area.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.