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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.

Abstract. Flood disaster occurs quite frequently in Malaysia and has been categorized as the most threatening natural disaster compared to landslides, hurricanes, tsunami, haze and others. A study by Department of Irrigation and Drainage (DID) show that 9% of land areas in Malaysia are prone to flood which may affect approximately 4.9 million of the population. 2 Dimensional floods routing modelling demonstrate is turning out to be broadly utilized for flood plain display and is an extremely viable device for evaluating flood. Flood propagations can be better understood by simulating the flow and water level by using hydrodynamic modelling. The hydrodynamic flood routing can be recognized by the spatial complexity of the schematization such as 1D model and 2D model. It was found that most of available hydrological models for flood forecasting are more focus on short duration as compared to long duration hydrological model using the Probabilistic Distribution Moisture Model (PDM). The aim of this paper is to discuss preliminary findings on development of flood forecasting model using Probabilistic Distribution Moisture Model (PDM) for Kelantan river basin. Among the findings discuss in this paper includes preliminary calibrated PDM model, which performed reasonably for the Dec 2014, but underestimated the peak flows. Apart from that, this paper also discusses findings on Soil Moisture Deficit (SMD) and flood plain analysis. Flood forecasting is the complex process that begins with an understanding of the geographical makeup of the catchment and knowledge of the preferential regions of heavy rainfall and flood behaviour for the area of responsibility. Therefore, to decreases the uncertainty in the model output, so it is important to increase the complexity of the model.

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Reservoir inflow forecasting assists dam operator in reservoir operation by providing advance information on lake level. This paper discusses on the application of the physical-based numerical model to simulate one-dimensional channel network using WASH123D Model. The model was developed to simulate streamflow at two locations namely Sg Kejar and Sg Tiang, located in the Temengor catchment. The WASH123D model performed channel routing using shallow water equation. The model input data includes rainfall from 5 rainfall stations, river cross sections and simulated runoff data using SCS Method. Due to unavailable observed data, results comparisons were performed using streamflow results obtained using InfoWorks RS Platform. The peak flow from simulation results at Sg Kejar & Sg Tiang Station is 152.6m3/s and 36.6m3/s. The analysis shows good agreement for both simulations with Nash-Sutcliffe Efficiency of 0.68 for Sg Kejar and 0.99 for Sg Tiang. It is suggested that model recalibration shall be made once there is enough water level data to enable more accurate representation of spatial heterogeneity in the catchment processes.