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New Regional-Specific Urban Runoff Prediction Model of Sungai Kayu Ara Catchment in Malaysia

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ICACE 2019

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 59))

Abstract

Malaysian government agencies adopted curve number (CN) rainfall-runoff model for design use like many other commercial software applications, while most researchers have adopted CN values from its published handbook from USA. However, there is no regional-specific curve numbers handbook in Malaysia for the rainfall-runoff predictive modelling. This study did not refer to any CN value but derived a statistically significant CN value with rainfall-runoff events directly. The derived λ = 0.0002 is statistically significant (α = 0.01), while the optimum CN value of 92.95 represents the rainfall-runoff characteristic at the Sungai Kayu Ara catchment. The runoff predictive model estimated an averaged flood depth of 7.46 cm from 100 mm rainfall event when the drainage infrastructure fails to drain away the runoff volume effectively. It is recommended to limit the upstream development, while rainwater harvesting, storm water retention, and detention facilities should be constructed to curb the urban flash flooding at the Sungai Kayu Ara catchment.

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Acknowledgements

The authors would like to thank Universiti Tunku Abdul Rahman and Brunsfield International Group for their financial support in this study. This study was also supported by Universiti Teknologi Malaysia and Universiti Tenaga Nasional. The authors would also like to acknowledge the guidance from Professor Richard H. Hawkins (University of Arizona, USA) and Professor Ismail Abustan (USM) for sharing his research data.

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Correspondence to Lloyd Ling .

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Ling, L., Chow, M.F., Tan, W.L., Tan, W.J., Tan, C.Y., Yusop, Z. (2020). New Regional-Specific Urban Runoff Prediction Model of Sungai Kayu Ara Catchment in Malaysia. In: Awang, M., Meor M Fared, M. (eds) ICACE 2019. Lecture Notes in Civil Engineering, vol 59. Springer, Singapore. https://doi.org/10.1007/978-981-15-1193-6_18

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  • DOI: https://doi.org/10.1007/978-981-15-1193-6_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1192-9

  • Online ISBN: 978-981-15-1193-6

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