A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam

The early-warning model for flash floods is based on a hydrological and geomorphological concept connected to the river basin, with the principle that flash floods will only occur where there is a high potential risk and when rainfall exceeds the threshold. In the model used to build flash-floods ri...

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Main Authors: Thanh Van Hoang, Tien Yin Chou, Ngoc Thach Nguyen, Yao Min Fang, Mei Ling Yeh, Quoc Huy Nguyen, Xuan Linh Nguyen
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:https://www.mdpi.com/2220-9964/8/5/228
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spelling doaj-3b8625ba616b480b82271c56c36917a12020-11-24T21:29:03ZengMDPI AGISPRS International Journal of Geo-Information2220-99642019-05-018522810.3390/ijgi8050228ijgi8050228A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in VietnamThanh Van Hoang0Tien Yin Chou1Ngoc Thach Nguyen2Yao Min Fang3Mei Ling Yeh4Quoc Huy Nguyen5Xuan Linh Nguyen6Geographic Information Systems Research Center, Feng Chia University, Taichung 40724, TaiwanGeographic Information Systems Research Center, Feng Chia University, Taichung 40724, TaiwanVNU, University of Science, Faculty of Geography, VietnamGeographic Information Systems Research Center, Feng Chia University, Taichung 40724, TaiwanGeographic Information Systems Research Center, Feng Chia University, Taichung 40724, TaiwanPhD program of Civil and Hydraulic Engineering, College of Construction and Development, Feng Chia University, Taichung 40724, TaiwanPhD program of Civil and Hydraulic Engineering, College of Construction and Development, Feng Chia University, Taichung 40724, TaiwanThe early-warning model for flash floods is based on a hydrological and geomorphological concept connected to the river basin, with the principle that flash floods will only occur where there is a high potential risk and when rainfall exceeds the threshold. In the model used to build flash-floods risk maps, the parameters of the basin are analyzed and evaluated and the weight is determined using Thomas Saaty’s analytic hierarchy process (AHP). The flash-floods early-warning software is built using open source programming tools. With the spatial module and online processing, a predicted precipitation of one to six days in advance for iMETOS (AgriMedia—Vietnam) automatic meteorological stations is interpolated and then processed with the potential risk maps (iMETOS is a weather-environment monitoring system comprising a wide range of equipment and an online platform and can be used in various fields such as agriculture, tourism and services). The results determine the locations of flash floods at several risk levels corresponding to the predicted rainfall values at the meteorological stations. The system was constructed and applied to flash floods disaster early warning for Thuan Chau in Son La province when the rainfall exceeded the 150 mm/d threshold. The system initially supported positive decision-making to prevent and minimize damage caused by flash floods.https://www.mdpi.com/2220-9964/8/5/228early warningfloodflash floodsanalytic hierarchy processthresholddisaster management
collection DOAJ
language English
format Article
sources DOAJ
author Thanh Van Hoang
Tien Yin Chou
Ngoc Thach Nguyen
Yao Min Fang
Mei Ling Yeh
Quoc Huy Nguyen
Xuan Linh Nguyen
spellingShingle Thanh Van Hoang
Tien Yin Chou
Ngoc Thach Nguyen
Yao Min Fang
Mei Ling Yeh
Quoc Huy Nguyen
Xuan Linh Nguyen
A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam
ISPRS International Journal of Geo-Information
early warning
flood
flash floods
analytic hierarchy process
threshold
disaster management
author_facet Thanh Van Hoang
Tien Yin Chou
Ngoc Thach Nguyen
Yao Min Fang
Mei Ling Yeh
Quoc Huy Nguyen
Xuan Linh Nguyen
author_sort Thanh Van Hoang
title A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam
title_short A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam
title_full A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam
title_fullStr A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam
title_full_unstemmed A Robust Early Warning System for Preventing Flash Floods in Mountainous Area in Vietnam
title_sort robust early warning system for preventing flash floods in mountainous area in vietnam
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2019-05-01
description The early-warning model for flash floods is based on a hydrological and geomorphological concept connected to the river basin, with the principle that flash floods will only occur where there is a high potential risk and when rainfall exceeds the threshold. In the model used to build flash-floods risk maps, the parameters of the basin are analyzed and evaluated and the weight is determined using Thomas Saaty’s analytic hierarchy process (AHP). The flash-floods early-warning software is built using open source programming tools. With the spatial module and online processing, a predicted precipitation of one to six days in advance for iMETOS (AgriMedia—Vietnam) automatic meteorological stations is interpolated and then processed with the potential risk maps (iMETOS is a weather-environment monitoring system comprising a wide range of equipment and an online platform and can be used in various fields such as agriculture, tourism and services). The results determine the locations of flash floods at several risk levels corresponding to the predicted rainfall values at the meteorological stations. The system was constructed and applied to flash floods disaster early warning for Thuan Chau in Son La province when the rainfall exceeded the 150 mm/d threshold. The system initially supported positive decision-making to prevent and minimize damage caused by flash floods.
topic early warning
flood
flash floods
analytic hierarchy process
threshold
disaster management
url https://www.mdpi.com/2220-9964/8/5/228
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