A systematic review of real-time urban flood forecasting model in Malaysia and Indonesia - current modelling and challenge
Several metropolitan areas in tropical Southeast Asia, mainly in Malaysia and Indonesia have lately been witnessing unprecedentedly severe flash floods owing to unexpected climate change. The fast water flooding has caused extraordinarily serious harm to urban populations and social facilities....
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| Format: | Article |
| Language: | English |
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Pusat Studi Planologi Universitas Islam Sultan Agung Semarang, in collaboration with Asosiasi Sekolah Perencanaan Indonesia
2023
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| Online Access: | http://irep.iium.edu.my/108748/7/108748_A%20systematic%20review%20of%20real-time%20urban%20flood%20forecasting%20model.pdf http://irep.iium.edu.my/108748/ http://jurnal.unissula.ac.id/index.php/psa https://doi.org/10.30659/jpsa.v20i2.30765 |
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| Institution: | Universiti Islam Antarabangsa Malaysia |
| Language: | English |
| Summary: | Several metropolitan areas in tropical Southeast Asia, mainly in Malaysia and Indonesia have lately been
witnessing unprecedentedly severe flash floods owing to unexpected climate change. The fast water flooding has
caused extraordinarily serious harm to urban populations and social facilities. In addition, urban Southeast Asia
generally has insufficient capacity in drainage systems, complex land use patterns, and a large susceptible
population in confined urban regions. To lower the urban flood risk and strengthen the resilience of vulnerable
urban populations, it has been of fundamental relevance to create real-time urban flood forecasting systems for
flood disaster prevention agencies and the urban public. This review examined the state-of-the-art models of real�time forecasting systems for urban flash floods in Malaysia and Indonesia. The real-time system primarily
comprises of the following subsystems, i.e., rainfall forecasting, drainage system modelling, and inundation area
mapping. This review described the current urban flood forecasting modelling for rainfall forecasting, physical�process-based hydraulic models for flood inundation prediction, and data-driven artificial intelligence (AI) models
for the real-time forecasting system. The analysis found that urban flood forecasting modelling based on data�driven AI models is the most applied in in many metropolitan locations in Malaysia and Indonesia. The analysis
also evaluated the existing potential of data-driven AI models for real-time forecasting systems as well as the
challenging towards it. |
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