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Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar

Author

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  • Zaw Myo Khaing
  • Ke Zhang
  • Hisaya Sawano
  • Badri Bhakra Shrestha
  • Takahiro Sayama
  • Kazuhiro Nakamura

Abstract

Torrential and long-lasting rainfall often causes long-duration floods in flat and lowland areas in data-scarce Nyaungdon Area of Myanmar, imposing large threats to local people and their livelihoods. As historical hydrological observations and surveys on the impact of floods are very limited, flood hazard assessment and mapping are still lacked in this region, making it hard to design and implement effective flood protection measures. This study mainly focuses on evaluating the predicative capability of a 2D coupled hydrology-inundation model, namely the Rainfall-Runoff-Inundation (RRI) model, using ground observations and satellite remote sensing, and applying the RRI model to produce a flood hazard map for hazard assessment in Nyaungdon Area. Topography, land cover, and precipitation are used to drive the RRI model to simulate the spatial extent of flooding. Satellite images from Moderate Resolution Imaging Spectroradiometer (MODIS) and the Phased Array type L-band Synthetic Aperture Radar-2 onboard Advanced Land Observing Satellite-2 (ALOS-2 ALOS-2/PALSAR-2) are used to validate the modeled potential inundation areas. Model validation through comparisons with the streamflow observations and satellite inundation images shows that the RRI model can realistically capture the flow processes (R2 ≥ 0.87; NSE ≥ 0.60) and associated inundated areas (success index ≥ 0.66) of the historical extreme events. The resultant flood hazard map clearly highlights the areas with high levels of risks and provides a valuable tool for the design and implementation of future flood control and mitigation measures.

Suggested Citation

  • Zaw Myo Khaing & Ke Zhang & Hisaya Sawano & Badri Bhakra Shrestha & Takahiro Sayama & Kazuhiro Nakamura, 2019. "Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-18, November.
  • Handle: RePEc:plo:pone00:0224558
    DOI: 10.1371/journal.pone.0224558
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    1. Alahacoon, Niranga & Matheswaran, Karthikeyan & Pani, Peejush & Amarnath, Giriraj, "undated". "A decadal historical satellite data and rainfall trend analysis (2001–2016) for flood hazard mapping in Sri Lanka," Papers published in Journals (Open Access) H048581, International Water Management Institute.
    2. Bingshun He & Xianlong Huang & Meihong Ma & Qingrui Chang & Yong Tu & Qing Li & Ke Zhang & Yang Hong, 2018. "Analysis of flash flood disaster characteristics in China from 2011 to 2015," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 90(1), pages 407-420, January.
    3. Michael Nones, 2017. "Flood hazard maps in the European context," Water International, Taylor & Francis Journals, vol. 42(3), pages 324-332, April.
    4. Chen Cao & Peihua Xu & Yihong Wang & Jianping Chen & Lianjing Zheng & Cencen Niu, 2016. "Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas," Sustainability, MDPI, vol. 8(9), pages 1-18, September.
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