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Flood modelling framework for Kuching City, Malaysia

  • Several areas in Southeast Asia are very vulnerable to climate change and unable to take immediate/effective actions on countermeasures due to insufficient capabilities. Malaysia, in particular the east coast of peninsular Malaysia and Sarawak, is known as one of the vulnerable regions to flood disaster. Prolonged and intense rainfall, natural activities and increase in runoff are the main reasons to cause flooding in this area. In addition, topographic conditions also contribute to the occurrence of flood disaster. Kuching city is located in the northwest of Borneo Island and part of Sarawak river catchment. This area is a developing state in Malaysia experiencing rapid urbanization since 2000s, which has caused the insufficient data availability in topography and hydrology. To deal with these challenging issues, this study presents a flood modelling framework using the remote sensing technologies and machine learning techniques to acquire the digital elevation model (DEM) with improved accuracy for the non-surveyed areas.Several areas in Southeast Asia are very vulnerable to climate change and unable to take immediate/effective actions on countermeasures due to insufficient capabilities. Malaysia, in particular the east coast of peninsular Malaysia and Sarawak, is known as one of the vulnerable regions to flood disaster. Prolonged and intense rainfall, natural activities and increase in runoff are the main reasons to cause flooding in this area. In addition, topographic conditions also contribute to the occurrence of flood disaster. Kuching city is located in the northwest of Borneo Island and part of Sarawak river catchment. This area is a developing state in Malaysia experiencing rapid urbanization since 2000s, which has caused the insufficient data availability in topography and hydrology. To deal with these challenging issues, this study presents a flood modelling framework using the remote sensing technologies and machine learning techniques to acquire the digital elevation model (DEM) with improved accuracy for the non-surveyed areas. Intensity–duration–frequency (IDF) curves were derived from climate model for various scenario simulations. The developed flood framework will be beneficial for the planners, policymakers, stakeholders as well as researchers in the field of water resource management in the aspect of providing better ideas/tools in dealing with the flooding issues in the region.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Dongeon Kim, Yabin Sun, Dadiyorto WendiORCiDGND, Ze Jiang, Shie-Yui Liong, Philippe Gourbesville
DOI:https://doi.org/10.1007/978-981-10-7218-5_39
ISBN:978-981-10-7218-5
ISBN:978-981-10-7217-8
ISSN:2364-6934
ISSN:2364-8198
Titel des übergeordneten Werks (Englisch):Advances in Hydroinformatics: SimHydro 2017 - Choosing The Right Model in Applied Hydraulics
Untertitel (Englisch):Overcoming the Lack of Data
Verlag:Springer
Verlagsort:Singapore
Publikationstyp:Sonstiges
Sprache:Englisch
Datum der Erstveröffentlichung:27.02.2018
Erscheinungsjahr:2018
Datum der Freischaltung:24.02.2022
Seitenanzahl:10
Erste Seite:559
Letzte Seite:568
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
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