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Development of Community-Based Early Warning System (CBEWS) in enhancing community preparedness for dam-related disasters in Malaysia

Series of catastrophic oods that we have witnessed over the last decade in Malaysia have necessitated the adoption of reliable early warning system. Ultimate concern during any event of natural or manmade disaster would be information dissemination to lessen the disaster impact on lives and property...

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Main Authors: Ghazali A., Thiruchelvam S., Muda R.S., Mustapha K.N., Kadir A.K., Norkhairi F.F., Yahya N., Hakimie H., Isa A.A.M., Mamat A.F., Hasini H., Sahari K.S.M., Muda Z.C., Jin N.Y.
Other Authors: 36441299400
Format: Article
Published: Akademi Sains Malaysia 2023
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spelling my.uniten.dspace-241642023-05-29T14:56:18Z Development of Community-Based Early Warning System (CBEWS) in enhancing community preparedness for dam-related disasters in Malaysia Ghazali A. Thiruchelvam S. Muda R.S. Mustapha K.N. Kadir A.K. Norkhairi F.F. Yahya N. Hakimie H. Isa A.A.M. Mamat A.F. Hasini H. Sahari K.S.M. Muda Z.C. Jin N.Y. 36441299400 55812442400 55812851400 26032672000 54401122000 57204332702 57204323509 16021651800 57189232808 57203788816 6507435998 57218170038 55812444000 57314441300 Series of catastrophic oods that we have witnessed over the last decade in Malaysia have necessitated the adoption of reliable early warning system. Ultimate concern during any event of natural or manmade disaster would be information dissemination to lessen the disaster impact on lives and property. The Bertam Valley incident in the wee hours of 23rd October 2013 has been considered as the game changer of how we view the role of vulnerable communities in facing dam-related disasters. Empowerment of local communities has been considered as vital in disaster management, as they are often the first responders to disaster. Local Community-Based Early Warning System (CBEWS) is a smart mechanism operated by the communities. This study revolves around the actual implementation of such system in Cameron Highlands in the effort of increasing human resilience towards damrelated disasters. While establishing the system, the Bertam Valley community has received support from different individuals and organisations. It is paramount that the community develops and maintains close coordination and strong links with these stakeholders. The performance of early warning systems can be evaluated via key parameters such as timeliness, accuracy, reliability, user friendliness, exibility, and costs & benefits. � 2018, Akademi Sains Malaysia. Final 2023-05-29T06:56:18Z 2023-05-29T06:56:18Z 2018 Article 2-s2.0-85055212308 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055212308&partnerID=40&md5=ea03b3c4cd9ae6b104f97e0071aba54a https://irepository.uniten.edu.my/handle/123456789/24164 11 2 117 123 Akademi Sains Malaysia Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Series of catastrophic oods that we have witnessed over the last decade in Malaysia have necessitated the adoption of reliable early warning system. Ultimate concern during any event of natural or manmade disaster would be information dissemination to lessen the disaster impact on lives and property. The Bertam Valley incident in the wee hours of 23rd October 2013 has been considered as the game changer of how we view the role of vulnerable communities in facing dam-related disasters. Empowerment of local communities has been considered as vital in disaster management, as they are often the first responders to disaster. Local Community-Based Early Warning System (CBEWS) is a smart mechanism operated by the communities. This study revolves around the actual implementation of such system in Cameron Highlands in the effort of increasing human resilience towards damrelated disasters. While establishing the system, the Bertam Valley community has received support from different individuals and organisations. It is paramount that the community develops and maintains close coordination and strong links with these stakeholders. The performance of early warning systems can be evaluated via key parameters such as timeliness, accuracy, reliability, user friendliness, exibility, and costs & benefits. � 2018, Akademi Sains Malaysia.
author2 36441299400
author_facet 36441299400
Ghazali A.
Thiruchelvam S.
Muda R.S.
Mustapha K.N.
Kadir A.K.
Norkhairi F.F.
Yahya N.
Hakimie H.
Isa A.A.M.
Mamat A.F.
Hasini H.
Sahari K.S.M.
Muda Z.C.
Jin N.Y.
format Article
author Ghazali A.
Thiruchelvam S.
Muda R.S.
Mustapha K.N.
Kadir A.K.
Norkhairi F.F.
Yahya N.
Hakimie H.
Isa A.A.M.
Mamat A.F.
Hasini H.
Sahari K.S.M.
Muda Z.C.
Jin N.Y.
spellingShingle Ghazali A.
Thiruchelvam S.
Muda R.S.
Mustapha K.N.
Kadir A.K.
Norkhairi F.F.
Yahya N.
Hakimie H.
Isa A.A.M.
Mamat A.F.
Hasini H.
Sahari K.S.M.
Muda Z.C.
Jin N.Y.
Development of Community-Based Early Warning System (CBEWS) in enhancing community preparedness for dam-related disasters in Malaysia
author_sort Ghazali A.
title Development of Community-Based Early Warning System (CBEWS) in enhancing community preparedness for dam-related disasters in Malaysia
title_short Development of Community-Based Early Warning System (CBEWS) in enhancing community preparedness for dam-related disasters in Malaysia
title_full Development of Community-Based Early Warning System (CBEWS) in enhancing community preparedness for dam-related disasters in Malaysia
title_fullStr Development of Community-Based Early Warning System (CBEWS) in enhancing community preparedness for dam-related disasters in Malaysia
title_full_unstemmed Development of Community-Based Early Warning System (CBEWS) in enhancing community preparedness for dam-related disasters in Malaysia
title_sort development of community-based early warning system (cbews) in enhancing community preparedness for dam-related disasters in malaysia
publisher Akademi Sains Malaysia
publishDate 2023
_version_ 1806427960272486400
score 13.222552

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