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

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...

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Autores principales: Khaing, Zaw Myo, Zhang, Ke, Sawano, Hisaya, Shrestha, Badri Bhakra, Sayama, Takahiro, Nakamura, Kazuhiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6879136/
https://www.ncbi.nlm.nih.gov/pubmed/31770381
http://dx.doi.org/10.1371/journal.pone.0224558
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author Khaing, Zaw Myo
Zhang, Ke
Sawano, Hisaya
Shrestha, Badri Bhakra
Sayama, Takahiro
Nakamura, Kazuhiro
author_facet Khaing, Zaw Myo
Zhang, Ke
Sawano, Hisaya
Shrestha, Badri Bhakra
Sayama, Takahiro
Nakamura, Kazuhiro
author_sort Khaing, Zaw Myo
collection PubMed
description 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 (R(2) ≥ 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.
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spelling pubmed-68791362019-12-08 Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar Khaing, Zaw Myo Zhang, Ke Sawano, Hisaya Shrestha, Badri Bhakra Sayama, Takahiro Nakamura, Kazuhiro PLoS One Research Article 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 (R(2) ≥ 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. Public Library of Science 2019-11-26 /pmc/articles/PMC6879136/ /pubmed/31770381 http://dx.doi.org/10.1371/journal.pone.0224558 Text en © 2019 Khaing et al http://creativecommons.org/licenses/by/4.0/ 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 author and source are credited.
spellingShingle Research Article
Khaing, Zaw Myo
Zhang, Ke
Sawano, Hisaya
Shrestha, Badri Bhakra
Sayama, Takahiro
Nakamura, Kazuhiro
Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar
title Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar
title_full Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar
title_fullStr Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar
title_full_unstemmed Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar
title_short Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar
title_sort flood hazard mapping and assessment in data-scarce nyaungdon area, myanmar
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6879136/
https://www.ncbi.nlm.nih.gov/pubmed/31770381
http://dx.doi.org/10.1371/journal.pone.0224558
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