Sains Malaysiana 42(3)(2013): 325–332

Development of Analytical Probabilistic Model Parameters for Urban Stormwater Management

(Pembangunan Parameter Kebarangkalian Analisis untuk Pengurusan Air Ribut di Bandar)

Salisu Dan’azumi*

Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia

Supiah Shamsudin

Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia

54100, Kuala Lumpur, Malaysia

Azmi Aris

Institute of Environmental and Water Resource Management, Faculty of Civil Engineering

Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia

Diserahkan: 13 Julai 2011/Diterima: 1 September 2012

ABSTRACT

Analytical probabilistic models (APM) are closed form mathematical expressions for long term system’s output performance derived from the probability distribution of the system’s input variables. In order to apply the APM for urban stormwater control systems’ design, APM parameters have to be made known. These input parameters include APM parameters which are derived from the meteorological rainfall characteristics; storm depth, duration, intensity and inter-event time. This study is aimed to develop meteorological APM parameters that can be used for detention pond design in Peninsular Malaysia. Hourly rainfall data covering 10 to 40 years period were analyzed from 13 different locations spread across the Peninsular. The data were analyzed to obtain the APM parameters at different values of minimum storm separation time (MSST). The APM parameter of rainfall duration (λ) was found to range from a mean value of 0.260 h-1 for 2 h MSST to 0.04 h-1 for 24 h MSST. The APM parameter of rainfall volume (ζ) ranges from a mean value of 0.091 mm-1 for 2 h MSST to 0.038 mm-1 for 24 h MSST. Similarly, the APM parameter of rainfall intensity (β) ranges from a mean value of 0.355 h/mm for 2 h MSST to 0.504 h/mm for 24 h MSST. Finally, the APM parameter of inter-event time (ψ) ranges from a mean value of 0.025 h-1 for 2 h MSST to 0.012 h-1 for 24 h MSST. Once the APM parameters are determined for a particular area, the long term stormwater control systems’ performance can easily be determined.

Keywords: Analytical probabilistic models (APM); detention pond; meteorological characteristics; stormwater management

ABSTRAK

Model kebarangkalian analisis (APM) adalah ungkapan matematik berbentuk tertutup bagi prestasi keluaran sistem jangka panjang diterbitkan daripada taburan kebarangkalian pemboleh ubah input sistem. Untuk menggunakan aplikasi APM dalam reka bentuk sistem kawalan air-ribut bandar, parameter APM perlu diketahui. Parameter input ini termasuk parameter APM yang diterbitkan daripada ciri hujan meteorologi; kedalaman ribut, tempoh, keamatan dan masa antara-peristiwa. Kajian ini bertujuan untuk menghasilkan parameter APM meteorologi yang boleh digunakan untuk reka bentuk kolam tahanan di Semenanjung Malaysia. Data hujan setiap jam yang merangkumi 10 hingga 40 tahun telah dianalisis dari 13 lokasi berlainan di seluruh Semenanjung. Data dianalisis untuk mendapatkan parameter APM pada nilai masa pengasingan ribut minimum (MSST) yang berbeza. Parameter APM tempoh hujan (λ) adalah bernilai purata 0.260 jam-1 untuk 2 jam MSST ke 0.04 jam-1 untuk MSST 24 jam. Parameter APM isi padu hujan (ζ) bernilai purata antara 0.091 mm-1 untuk 2 jam MSST ke 0.038 mm-1 untuk MSST 24 jam. Begitu juga, parameter APM keamatan hujan (β) adalah antara nilai purata 0.355 jam/mm untuk 2 jam MSST ke 0.504 jam/mm untuk MSST 24 jam. Akhirnya, parameter APM antara peristiwa masa (ψ) bernilai purata 0.025 jam-1 untuk 2 jam MSST ke 0.012 jam-1 untuk 24 jam MSST. Apabila parameter APM telah ditentukan bagi kawasan tertentu, prestasi sistem kawalan air-ribut jangka panjang dapat ditentukan dengan mudah.

Kata kunci: Ciri meteorologi; model kebarangkalian analitis; penahanan kolam; pengurusan air- rebut

REFERENCES

Adams, B.J. & Papa, F. 2000. Urban Stormwater Management Planning with Analytical Probabilistic Models. New York: John Wiley & Sons.

Behera, P.K., Adams, B.J. & Li, J.Y. 2006. Runoff quality analysis of urban catchments with analytical probabilistic models. Journal of Water Resources Planning and Management, ASCE 132: 4-14.

Burgueno, A., Codina, B., Redafio, A. & Lorente, J. 1994. Basic statistical characteristics of hourly rainfall amounts in Barcelona (Spain). Theor. Appl. Climatol. 49: 175-181.

Chen, J. & Adams, B.J. 2005a. Analysis of storage facilities for urban stormwater quantity control. Advances in Water Resources 28: 377-392.

Chen, J. & Adams, B.J. 2005b. Urban storm water control evaluation with analytical probabilistic models. Journal of Water Res. Planning and Management, ASCE 131: 362-374.

Chen, J. & Adams, B. J. 2006a. Analytical urban storm water quality models based on pollutant buildup and washoff processes. Journal of Environmental Engineering, ASCE 132: 1314-1330.

Chen, J. & Adams, B.J. 2006b. Urban stormwater quality control analysis with detention ponds. Water Env. Res. 78: 744-753.

Chen, J. & Adams, B.J. 2007a. A derived probability distribution approach to stormwater quality modeling. Advances in Water Resources 30: 80-100.

Chen, J. & Adams, B.J. 2007b. Development of analytical models for estimation of urban stormwater runoff. Journal of Hydrology 336: 458-469.

DID. 2000. Urban Stormwater Management Manual for Malaysia. Department of Irrigation and Drainage, Malaysia.

Dunkerley, D. 2008. Identifying individual rain events from Pluviograph records: A review with analysis of data from an Australian Dryland Site. Hydrol. Process 22: 5024-5036.

Guo, J.C.Y. 2002. Overflow risk analysis for stormwater quality control basins. Journal of Hydrologic Engineering 7: 428-434.

Guo, Y. & Adams, B.J. 1998a. Hydrologic analysis of urban catchment with event based probabilistic models, 2. Peak discharge rate. Water Resource Research 34: 3433-3443.

Guo, Y. & Adams, B.J. 1998b. Hydrologic analysis of urban catchment with event based probabilistic models, runoff volume. Water Resource Research 34: 3421-3432.

Guo, Y. & Adams, B.J. 1999a. Analysis of detention ponds for storm water quality control. Water Resources Research 35(8): 2447-2456.

Guo, Y. & Adams, B.J. 1999b. An analytical probabilistic approach to sizing flood control detention facilities. Water Resource Research 35: 2457-2468.

Li, J.Y. & Adams, B.J. 2000. Probabilistic models for analysis of urban runoff control systems. Journal of Environmental Engineering, ASCE 126: 217-224.

Restro-Posada, P.J. & Eagleson, P.S. 1982. Identification of independent rainstorms. Journal of Hydrology 55: 303-319.

Shammaa, Y., Zhu, D.Z., Gyürék, L.L. & Labatiuk, C.W. 2002. Effectiveness of dry ponds for stormwater total suspended solids removal. Can. J. Civ. Eng. 29: 316-324.

Supiah, S., Dan’azumi, S. & Aris, A. 2010. Effect of storm separation time on rainfall characteristics: A case study of Johor, Malaysia. European Journal of Scientific Research 45: 162-167.

*Pengarang untuk surat-menyurat; email: sdanazumi@gmail.com