Flash Flood Early Warning System in Colima, Mexico.pdf (7.07 MB)
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journal contribution
posted on 2020-09-25, 08:52 authored by José Ibarreche, Raúl Aquino, Robert EdwardsRobert Edwards, Víctor Rangel, Ismael Pérez, Miguel Martínez, Esli Castellanos, Elisa Álvarez, Saul Jimenez, Raúl Rentería, Arthur Edwards, Omar ÁlvarezThis paper presents a system of sensors used in flash flood prediction that offers critical real-time information used to provide early warnings that can provide the minutes needed for persons to evacuate before imminent events. Flooding is one of the most serious natural disasters humans confront in terms of loss of life and results in long-term effects, which often have severely adverse social consequences. However, flash floods are potentially more dangerous to life because there is often little or no forewarning of the impending disaster. The Emergency Water Information Network (EWIN) offers a solution that integrates an early warning system, notifications, and real-time monitoring of flash flood risks. The platform has been implemented in Colima, Mexico covering the Colima and Villa de Alvarez metropolitan area. This platform consists of eight fixed riverside hydrological monitoring stations, eight meteorological stations, nomadic mobile monitoring stations called “drifters” used in the flow, and a sniffer with data muling capability. The results show that this platform effectively compiles and forwards information to decision-makers, government officials, and the general public, potentially providing valuable minutes for people to evacuate dangerous areas.
Funding
Flood Prediction using real time sensing Emergency Water Information Networks over mobile phone networks and WiFi (EWIN)
Engineering and Physical Sciences Research Council
Find out more...History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
SensorsVolume
20Issue
18Pages
5231Publisher
MDPI AGVersion
- VoR (Version of Record)
Rights holder
© The authorsPublisher statement
This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/Acceptance date
2020-09-10Publication date
2020-09-14Copyright date
2020eISSN
1424-8220Publisher version
Language
- en