日本地球惑星科学連合2024年大会

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セッション記号 M (領域外・複数領域) » M-IS ジョイント

[M-IS06] Extreme Weather and Water Related Disasters in Asia

2024年5月31日(金) 13:45 〜 15:15 104 (幕張メッセ国際会議場)

コンビーナ:久保田 尚之(北海道大学)、佐藤 光輝(北海道大学 大学院理学研究院)、Rahayu Pertiwi Rahayu(Institute Technology of Bandung)、Villafuerte II Q. Villafuerte II(Philippine Atmospheric, Geophysical and Astronomical Services Administration)、座長:久保田 尚之(北海道大学)、佐藤 光輝(北海道大学 大学院理学研究院)、Harkunti Pertiwi Rahayu(Institute Technology of Bandung)


14:15 〜 14:30

[MIS06-03] Severe Wind Risk Assessment for Super Typhoon Doksuri (2023) in the Philippines

Jomar A. Layderos1,2、Karlo J. Timbal1、Orlean G. Dela Cruz2、*Marcelino Q. Villafuerte II1 (1.Philippine Atmospheric, Geophysical and Astronomical Services Administration、2.Graduate School, Polytechnic University of the Philippines, Manila)

キーワード:Severe Wind, Risk Assessment, Building Typology, Damage state, Tropical Cyclone Risk Model

This paper presents the estimated severe wind risks associated with Super Typhoon Doksuri (“Egay”) on different building typologies along its path as it traversed the northern part of the Philippines in 2023. The Severe Wind Estimation of Risk Using Vulnerability and Exposure (SWERVE) tool is used to estimate the severity of damage a particular building could suffer due to severe wind. A comprehensive damage state of the building types was obtained and the results were compared with those reported by the National Disaster Risk Reduction and Management Council (NDRRMC). Comparisons revealed that the SWERVE-estimated partially damaged houses are underestimated by 13%, while completely damaged houses were overestimated by about 13.5% relative to the NDRRMC-reported data. Further refinement of the SWERVE tool is needed to closely resemble the observed damaged state of the buildings. Nevertheless, the exposure data (i.e., the total number of buildings/houses) as used in the model simulation and the way the reports were taken might be the main source of discrepancies. Hence, a more extensive validation of datasets is required to further improve the estimated risks.