Extreme Rainfall in the Eastern Region of Peninsular Malaysia

Syafrina Abdul Halim, A. Norzaida

Abstract


Modeling of daily rainfall data, particularly rainfall amount, is important not only for hydrological purposes but also for providing input for models of crop growth, design of urban drainage systems, land management systems and other environmental projects. This study tests the performance of Gamma and Weibull that are incorporated in the weather generator in simulating extreme rainfall and extreme dry/wet spell lengths for the eastern region of Peninsular Malaysia. Next, the monthly rainfall and the extreme rainfall are simulated using the best distribution. A weather generator known as Advanced Weather Generator (AWE-GEN) is chosen to model hourly rainfall time series in the eastern region of Peninsular Malaysia. Previously, Gamma distribution is incorporated in AWE-GEN to represent the rainfall intensity. This study proposes Weibull distribution and the performances between Gamma and Weibull distributions in generating rainfall series are compared based on Root Mean Square (RMSE) value error. Minimum RMSE value indicates the best distribution for eastern region. Results have shown that Gamma is the best distribution in simulating hourly rainfall in the east coast as compared to Weibull despite not being able to capture the peak/extreme values at several stations in the east coast of Peninsular Malaysia. The extreme wet spell length is well simulated although the extreme dry spell is under-estimated at all stations. Rainfall in November is contributing most of the annual rainfall followed by December. This study is relevant and very crucial for a tropical country like Malaysia which will benefit the policy makers in executing the strategic management of flooding in urban areas that is predominantly caused by convective activities.


Keywords


Extreme Rainfall, Rainfall Intensity, Gamma Distribution, Weibull Distribution, Weather Generator, Root Mean Square

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DOI: http://dx.doi.org/10.26713%2Fcma.v8i3.654

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