Journal of Disaster Research
Online ISSN : 1883-8030
Print ISSN : 1881-2473
ISSN-L : 1881-2473
Special Issue on SATREPS Myanmar Project Part 2: Development of a Comprehensive Disaster Resilience System and Collaboration Platform in Myanmar
Characteristics of the 2018 Bago River Flood of Myanmar
Daisuke KomoriAkiyuki KawasakiNanami SakaiNatsumi ShimomuraAkira HaradaKohei OkudaChit Bo Bo WinAye Myat ThuKhin Yadanar TunWai ToeWin Win Zin
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JOURNAL OPEN ACCESS

2020 Volume 15 Issue 3 Pages 256-266

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Abstract

A massive flood in Myanmar struck the Bago river in July, 2018. In this study, because of the limitation of real-time data availability, the satellite-based precipitation was used for clarifying the characteristics of the flood. The total precipitation during 10 days from July 22, when the flood first began at the western Bago city, was estimated approximately 753 mm and 527 mm at the Bago and Zaungts stations in the Bago river watershed. These values were corresponding to 355% and 294% of average of the 10-day total precipitation at the Bago (1967–2015) and Zaungts (1987–2014) stations. Furthermore, not only the 3-day and weekly peak precipitations but also the annual accumulative precipitations during July 22 and August 16 were estimated larger than the largest recorded precipitations at both stations. Although the Zaungts dam stored approximately 140 million m3 during this period, which was an amount equivalent to 40% of inflow volume during July 22 and 28, the resulting flood widely propagated in the Bago city. Based on the flood survey, the 2018 Bago river flood was classified into 4 areas; the right bank of the Bago river, the eastern town, the northern town, and the downstream from the Zaungts Weir and Bago city. These areas were marked as vulnerable areas in the Bago city. The Bago river watershed has experienced many floods in the past, and floods on the same scale as this flood are expected to occur in the future. Therefore, it is essential to understand the characteristics of the 2018 Bago river flood and develop near real-time monitoring of hydrometeorological situation to be prepared for the next flood disaster.

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