Flood disaster due to prolonged heavy rainfall had caused millions ringgit of property losses, infrastructure damages and numerous deaths in the east coast region of Peninsular Malaysia. One of the efforts taken to improve disaster preparedness in this region is by enhancing the flood forecasting and warning system (FFWS) using rainfall input from weather radar. Weather radar has the advantage of its ability to provide good spatial and temporal resolution of rainfall estimates but comes with inherent associated errors. In this study, the radar rainfall estimates were improved by climatological calibration of reflectivity-rain (Z-R) relationships for Pahang river basin. The reflectivity data for period of one year from Kuantan radar station and the hourly rainfall depths at 67 rainfall stations located in the basin for the same periods were used. Correlation analysis between radar and gauged rainfall indicates that the further the distance from the radar, the weaker the R2 coefficient value. Two Z-R equations were derived using optimization method for distance (1) 0-100 km and (2) above 100 km from Kuantan radar. The results in the form of Z = 24R1.7 and Z =5R1.6 represents the average relationship for Kuantan radar for distance (1) and (2). The radar rainfall estimates using the newly derived climatological Z-R equations enhanced the FFWS for Pahang river basin.
Flood is without doubt the most devastating natural disasters, striking numerous regions in Malaysia each year. During the last decades, the trend in flood damages has been growing exponentially. This is a consequence of the increasing frequency of heavy rain, changes in upstream land-use and a continuously increasing concentration of population and assets in flood prone areas. Malaysia, periodically, have faced with huge floods since previous years. Kelantan River basin, which located in the Northeast of Peninsular Malaysia, is prone to flood events in Malaysia. Kelantan River is the principal cause of flooding because it is constricted at its lower reaches. The capacity of the river at the downstream coastal area is less than 10,000 m3/s, therefore flood that exceeds this capacity will overspill the banks and discharge overland to the sea. Realizing the seriousness of the problems, it is vital in providing in time useful information for making crucial decisions especially to provide warning for any potential flood occurrence. In this study, stochastic flood forecasting model using stage regression method was applied to Kelantan River basin, in which the regression coefficients and equations was derived from the least square principle. The stochastic model were calibrated and validated which then shows that the equations derived are suitable to predict the hydrograph in Kelantan River basin. In conclusion, establishing a flood forecasting system would enhance the effectiveness of all other mitigation measures by providing time for appropriate actions. This has increased the importance of flood modelling for flood forecasts to issue advance warning in severe storm situations to reduce loss of lives and property damage.
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