Problem statement: Design of storm water best management practices to control runoff and water pollution can be achieved if a prior knowledge of the distribution of rainfall characteristics is known. Rainfall intensity, particularly in tropical climate, plays a major role in the design of runoff conveyance and erosion control systems. This study is aimed to explore the statistical distribution of rainfall intensity for Peninsular Malaysia using hourly rainfall data. Approach: Hourly rainfall data were collected from twelve stations spread across the Peninsular. Six hour separation time was used to divide the data into individual rainfall events and four probability distributions namely, Generalized Pareto (GP), Exponential (EXP), Beta (BT) and Gamma (GM) distributions were used to model the distribution of the hourly rainfall intensity. Kolmogorov-Sminov anderson-Darling and Chi-squared goodness-of-fit tests were used to evaluate the best fit. Results: The rainfall frequency, based on 6 h minimum inter-event time, ranges from 115-198 events. The distribution of the rainfall frequency and that of the highest intensity observed, over the recorded period, across the peninsular, is however irregular. The mean rainfall intensity ranges from 2.32-3.88 mm h −1. Kuala-Lumpur and Penang received the highest, while Segamat and Kedah received the lowest. Conversely, over the period of record, Segamat recorded the highest CV, skewness and kurtosis while Pahang has the least value for these parameters. Goodness-of-fit tests at 5% level of significance indicate that all the models can be used to model the distribution of rainfall intensity in Peninsular Malaysia. However, GP is found to be the most suitable model among the four probability distributions tested. Conclusion: Basic statistics of hourly rain intensity were obtained and probability distributions compared. It was found that GP is the most suitable model. Results can be useful, particularly, to agricultural and storm water management planning.
Urban stormwater is known to cause a myriad of problems, ranging from flooding to water quality degradations. This paper provides an extensive review of analytical probabilistic model (APMs) used in the design of urban runoff control systems. APMs are closed-form mathematical expressions representing a long-term system’s output performance derived from the probability distribution of the system’s input variables. Once derived, the APMs are easy to handle, allow for sensitive analysis, and can be co-opted into optimization frameworks. The implementation of APM in the planning and design of runoff control systems will not only help address the runoff quantity and quality problems of urban stormwater, but will also go a long way in optimizing the benefits derived from the systems. This paper reviews studies that document the negative impacts of urbanization on runoff quantity and quality, and the best management practices (BMPs) used to mitigate the impacts. Three design methodologies used in urban stormwater control systems were reviewed. A detailed review of research on the development and use of APMs in urban stormwater management in various runoff control systems is presented, and recommendations are proffered.
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