Development of flood hazard map of upstream Johor river
Flooding has become a common occurrence in Malaysia, occurring every year in many states, particularly during the northeast monsoon. From 1926 until 2013, Johor State, in its most southern portion of Peninsular Malaysia, experienced severe floods. The Johor River watershed, on the other hand, was de...
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| Format: | Article |
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Springer Science and Business Media Deutschland GmbH
2022
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| Online Access: | http://eprints.um.edu.my/43581/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133016365&doi=10.1007%2f978-3-030-99979-7_8&partnerID=40&md5=4f6341130d78fe44dd9d6d38ffc5f09f |
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| Summary: | Flooding has become a common occurrence in Malaysia, occurring every year in many states, particularly during the northeast monsoon. From 1926 until 2013, Johor State, in its most southern portion of Peninsular Malaysia, experienced severe floods. The Johor River watershed, on the other hand, was decimated by floods in December 2006 and January 2007. The floods flooded the relatively extensive catchment of the upstream Johor River, resulting in a substantial volume of discharge. The study's goal was to undertake river modelling and create a flood map for the Johor River upstream. The Johor River is 123 kms long and has a catchment area of 2,636 km. It starts from Mount Gemuruh and travels generally north–south before discharging into the Johor Strait. The data required in setting up this model includes the river spatial and geometrical data, hydraulics and hydrological data. The developing of the river model was starting by collecting data and insert the input data then the river model had been setup. The model had been calibrated and the results had been analyzed. The observed and simulated data have showed a reasonable agreement with the model. With a flood depth of 3.73 m and 100 ARI, Rantau Panjang is the most flooded area. The 100 ARI flood depth at Rantau Panjang is similar to the observed flood depth during the Johor River flood occurrences in 2007. The flood map River modelling can be a highly beneficial option because it is always possible to assess and anticipate with enough data. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
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