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  1. 防災科研関係論文

Assessing Flood Risk of the Chao Phraya River Basin Based on Statistical Rainfall Analysis

https://nied-repo.bosai.go.jp/records/3677
https://nied-repo.bosai.go.jp/records/3677
d0945aaf-9595-425d-8fe5-0265701c6e38
Item type researchmap(1)
公開日 2023-04-27
タイトル
言語 en
タイトル Assessing Flood Risk of the Chao Phraya River Basin Based on Statistical Rainfall Analysis
言語
言語 eng
著者 Shakti P. C.

× Shakti P. C.

en Shakti P. C.

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Mamoru Miyamoto

× Mamoru Miyamoto

en Mamoru Miyamoto

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Ryohei Misumi

× Ryohei Misumi

en Ryohei Misumi

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Yousuke Nakamura

× Yousuke Nakamura

en Yousuke Nakamura

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Anurak Sriariyawat

× Anurak Sriariyawat

en Anurak Sriariyawat

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Supattra Visessri

× Supattra Visessri

en Supattra Visessri

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Daiki Kakinuma

× Daiki Kakinuma

en Daiki Kakinuma

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抄録
内容記述タイプ Other
内容記述 The Chao Phraya River Basin is one of the largest in Asia and is highly vulnerable to water-related disasters. Based on rainfall gauge data over 36 years (1981–2016), a frequency analysis was performed for this basin to understand and evaluate its overall flood risk; daily rainfall measurements of 119 rain gauge stations within the basin were considered. Four common probability distributions, i.e., Log-Normal (LOG), Gumbel type-I (GUM), Pearson type-III (PE3), and Log-Pearson type-III (LP3) distributions, were used to calculate the return period of rainfall at each station and at the basin-scale level. Results of each distribution were compared with the graphical Gringorten method to analyze their performance; GUM was found to be the best-fitted distribution among the four. Thereafter, design hyetographs were developed by integrating the return period of rainfall based on three adopted methods at basin and subbasin scales; each method had its pros and cons for hydrological applications. Finally, utilizing a Rainfall-Runoff-Inundation (RRI) model, we estimated the possible flood inundation extent and depth, which was outlined over the Chao Phraya River Basin using the design hyetographs with different return periods. This study can help enhance disaster resilience at industrial complexes in Thailand for sustainable growth.
言語 en
書誌情報 en : Journal of Disaster Research

巻 15, 号 7, p. 1025-1039, 発行日 2020-12-01
出版者
言語 en
出版者 Fuji Technology Press Ltd.
ISSN
収録物識別子タイプ EISSN
収録物識別子 1883-8030
DOI
関連識別子 10.20965/jdr.2020.p1025
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