Flood forecasting and warning for Muar River: non-structural measures for flood mitigation

Bin Wan Abdul Majid, W. and Brown, E. and Bin Osman, S. and Bin Asan, G. and Bin Osman, A. and Bin Samsudin, R. and Boelee, L. and Ahmad, F. (2017) Flood forecasting and warning for Muar River: non-structural measures for flood mitigation. In: IAHR World Congress 2017, 13 - 18 August 2017, Kuala Lumpur, Malaysia.

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Abstract

The Muar River catchment has repeatedly suffered prolonged, significant flood events which have caused widespread disruption and impacts to residents, businesses and infrastructure; the impacts have been exacerbated by considerable rapid development over the past decade, which has modified the flow regimes and flooding mechanisms. To help prepare for, and mitigate, the effects of future floods, the Malaysian government is implementing a range of flood management projects, which will provide an integrated approach based on structural and non-structural measures. The integrated Flood Forecasting and River Monitoring system (iFFRM) for the river Muar is a key non-structural measure that has been recently implemented. The government’s Department of Irrigation and Drainage (DID) is responsible for providing a flood forecasting and warning service to the public; the iFFRM is a tool designed to enable effective decision support by DID. The iFFRM is a fully automated system that is driven by a combination of live, telemetered gauged data from DID’s own InfoBanjir database, spatial rainfall radar data, and Numerical Weather Prediction (NWP) rainfall forecasts from the Malaysian Meteorological Department. Hourly simulations are carried out automatically, to forecast water levels and flows in the river channels, and to map the flood inundation process within the flood plains. Simulation results are used to warn DID staff so that immediate action can be taken to provide an effective and proactive emergency response. Results are also passed to the project website, and dedicated smartphone application, enabling forecasts to be disseminated more widely. A parallel analytical modelling network can take over the forecasting role should the primary iFFRM system fail. Ongoing structural measures for flood mitigation are captured through a flexible modelling approach that can incorporate model updates to reflect real changes in the catchment, complementing the structural measures being implemented by DID and ensuring a sustainable solution.

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