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Real Time Impact Based Flood Forecasting (IBF) for Tropical Rivers: A Case Study in Dungun River Basin

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dc.citedby0
dc.contributor.authorAlkareem F.A.en_US
dc.contributor.authorSidek L.M.en_US
dc.contributor.authorSalih G.H.A.en_US
dc.contributor.authorBasri H.en_US
dc.contributor.authorSammen S.S.en_US
dc.contributor.authorid58905982500en_US
dc.contributor.authorid35070506500en_US
dc.contributor.authorid56239664100en_US
dc.contributor.authorid57065823300en_US
dc.contributor.authorid57192093108en_US
dc.date.accessioned2024-10-14T03:19:32Z
dc.date.available2024-10-14T03:19:32Z
dc.date.issued2023
dc.description.abstractSuch catastrophes may be brought on by floods to the impacted populace due to property damage, crop loss and death. Flooding caused significant damage to property and crops due to the high economic value of the property and the extent of the flood. Flood forecasts and warnings are one of the informal measures to provide warnings to affected populations. People living in flood-affected areas will be warned to evacuate their belongings before the flood arrives. This will greatly reduce the loss and damage caused by flooding, especially the loss of human life. This paper presents a comprehensive study of flood assessment and forecasting using Real-Time Flood Forecasting (RTIBFF) to assess the performance of IBF in identifying areas of potential flood risk by increasing the gap between the users and producers of timely information. Synergies are among several elements of an early warning system. Furthermore, in this paper, automated warning messages using color codes are used to initiate risk reduction measures at the local level for vulnerable groups in the Long Strait of Malaysia. RTIBFF collects information on the potential severity and likelihood of climate impacts. RTIBFF is still underutilized in Malaysia despite its extreme weather and potential catastrophe risk reduction benefits. The forecast, user understanding, and confidence are still questionable due to the forecast environment's uncertainty. To improve government-user collaboration, users should incorporate RTIBFF into popular weather forecast methodologies. � The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-981-99-3708-0_62
dc.identifier.epage897
dc.identifier.scopus2-s2.0-85185939426
dc.identifier.spage881
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85185939426&doi=10.1007%2f978-981-99-3708-0_62&partnerID=40&md5=64bcf801d3cc49053f8c49d94486f8c9
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34402
dc.identifier.volumePart F2265
dc.pagecount16
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.sourceScopus
dc.sourcetitleWater Resources Development and Management
dc.subjectClimate change
dc.subjectDungun River Basin
dc.subjectFlood hazard
dc.subjectRisk mitigation
dc.subjectRTIBFF
dc.subjectWarning system
dc.titleReal Time Impact Based Flood Forecasting (IBF) for Tropical Rivers: A Case Study in Dungun River Basinen_US
dc.typeBook chapteren_US
dspace.entity.typePublication
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