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1 This article was downloaded by: [Professor Aminuddin Ab Ghani] On: 23 March 2012, At: 15:57 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: Registered office: Mortimer House, Mortimer Street, London W1T 3JH, UK Urban Water Journal Publication details, including instructions for authors and subscription information: Performance of a dry detention pond: case study of Kota Damansara, Selangor, Malaysia Y.S. Liew a, Z. Selamat a, A. Ab. Ghani b & N.A. Zakaria b a River Research Centre, National Hydraulic Research Institute of Malaysia (NAHRIM), Selangor, Malaysia b River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia, Penang, Malaysia Available online: 30 Jan 2012 To cite this article: Y.S. Liew, Z. Selamat, A. Ab. Ghani & N.A. Zakaria (2012): Performance of a dry detention pond: case study of Kota Damansara, Selangor, Malaysia, Urban Water Journal, 9:2, To link to this article: PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

2 Urban Water Journal Vol. 9, No. 2, April 2012, CASE STUDY Performance of a dry detention pond: case study of Kota Damansara, Selangor, Malaysia Y.S. Liew a *, Z. Selamat a, A. Ab. Ghani b and N.A. Zakaria b a River Research Centre, National Hydraulic Research Institute of Malaysia (NAHRIM), Selangor, Malaysia; b River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia, Penang, Malaysia (Received 28 April 2011; final version received 22 November 2011) The Urban Stormwater Management Manual for Malaysia (MSMA) was published in 2001 by the Department of Irrigation and Drainage (DID), which promotes Best Management Practices (BMPs) aimed at stormwater management at the source. The construction of detention ponds has been strongly encouraged for water quantity control for new housing developments. This study focuses on the evaluation, using the InfoWorks Collection Systems (CS) model, of the effectiveness of a constructed dry detention pond built in 1996 located at Kota Damansara, Selangor. Hydrological and hydraulic data were collected for model calibration and verification. The study indicates that the dry detention pond can achieve its design goals, catering the flow from a 100-year Average Recurrence Interval or ARI storm and complies with the design requirement in the MSMA for major urban stormwater systems. Keywords: dry detention pond; Urban Stormwater Management Manual for Malaysia (MSMA); InfoWorks CS, Best Management Practices (BMPs) Introduction Due to rapid housing development, water quantity and water quality issues have increasingly occurred. Flooding is among the major issues, and the scenario could worsen if improper drainage systems are implemented. In urban areas like Kuala Lumpur and Penang, improper urban stormwater drainage has been highlighted as one of the causes of flash floods. The drainage systems in some housing areas have been in place for 10 to 20 years with no improvements. Inattentiveness to water drainage issues will increase the possibility of more severe flooding, which could lead to more property damage and loss of lives. In 2001, the Department of Irrigation and Drainage (2000) officially published the Urban Stormwater Management Manual for Malaysia (MSMA) that aimed to promote best management practices (BMPs) for stormwater management at the source and within the catchment and to steer drainage development in the country. Many have broached the question over whether detention ponds are effective at controlling the water quantity from development areas and if there are any better drainage systems to address the flooding problems (Semadeni-Davies et al. 2007, Ahmad Nasir 2008). It is also difficult to justify the huge investment for the construction if experience suggested that those measures would be ineffective. The majority of the studies on detention ponds, such as Walker (1998), Larm (2000), Somes et al. (2000), Krishnappan and Marselek (2002), Liu et al. (2007), Xu et al. (2007), Sperling et al. (2010) and Yi et al. (2010) have focused on water quality aspects. The construction of detention ponds has been strongly encouraged in the MSMA for water quantity control for new housing developments. Thus, after nine years of MSMA implementation, there is a need to evaluate the performance of the dry detention ponds that were built before MSMA was implemented. The present study covers only the performance of the dry detention pond on water quantity by using a numerical modelling approach through InfoWorks Collection System (CS) software. The main objectives of the study (Liew 2009) were to determine the hydrological and hydraulic parameters of the catchment, to analyse the performance of the existing dry detention pond and to assess the compliances of design requirement in the MSMA. Methods Study area The research site, shown in Figure 1, is located at Kota Damansara, Petaling District, Selangor, Malaysia *Corresponding author. ysliew@nahrim.gov.my ISSN X print/issn online Ó 2012 Taylor & Francis

3 130 Y.S. Liew et al. Figure 1. Location of the study site. which is about 10 km from Sungai Buloh, North-South Highway toll. Tambul River, a tributary of the Damansara River is the main stream flowing into the dry detention pond and is 3.5 km in length. The dry detention pond is an on-line pond which was built in 1996 with an area of 6.55 hectares (1.5% of the catchment area), as shown in Figure 2, and is situated in Section 6, Kota Damansara, Selangor. The total catchment area contributing to the dry detention pond is comprised of areas in Sections 5, 6, 7, 10 and 11 and covers a total of approximately 428 hectares. The catchment area is further divided into 177 sub-catchments to study the rainfall-runoff relationship at the catchment and calculate the inflow to the pond. The land use within the catchment area was divided into four main categories, namely bungalow or schools (7.3%), impervious (housing or shops) (43.2%), fields (landscape or open space) (12.3%) and pervious (forest or ponds) (37.2%), where almost 50% are housing or shops, which is typical of a moderately developed housing scheme. The hydrologic soil groups (HSG) within the catchment are a combination of Groups A, B and C. Hydrologic soil groups are classified by soil texture (Northern Virginia Planning District Commission and Engineers and Surveyors Institute 1992). The topography of the project area is hilly (21.67%) to undulating (78.33%). The project area rises from m above the mean sea level (MSL) with an average slope of hilly area (0.16) and the rest of entire catchment (0.027). The nearest road, as shown in Figure 2, is Cecawi 6/27 Road on the left bank of dry detention pond, with a ground level of 28 m above mean sea level. Data collection The necessary data for model development are shown in Figure 3. They are comprised of catchment hydrological parameters, which include the amount of rainfall, catchment characteristics, contour (elevation), land use, hydrologic soil groups, soil type, and catchment hydraulic parameters, such as river crosssections, water level, discharge and Manning s n coefficient. Rainfall and water level data were obtained from MyTelelogger (WL-18) wireless Short Messaging Services telemetry system with raingauge and an ultrasonic water level instrument (4 20 ma output, 10 m range) installed at site. The measured rainfall is set at 0.5 mm per tipping and measured water level is at 0.01 m accuracy. Data such as river cross-sections and drainage system layout were obtained from Pembangunan Kemajuan Negeri Selangor (PKNS), the developer of Kota Damansara housing scheme and further

4 Urban Water Journal 131 Figure 2. Figure 3. Locaton of the dry detention pond. Data requirements. ascertained by field surveys at site. The land use maps and hydrologic soil groups map were purchased from Department of Agriculture, Malaysia while QuickBird and LiDAR images were purchased from Malaysian Remote Sensing Agency. The subcatchments were digitised using contour maps generated from LiDAR images. Hassan (2005) explained the appropriateness of digitising a catchment manually when the catchment is basically a flat terrain within a developed area and it is therefore quite difficult to delineate automatically through GIS software. QuickBird Images captured using Remote Sensing techniques with the resolution of 0.6 m were used as the base to develop the Geographical Information System (GIS) database for land use classification within the study area. Other data such as sub-catchments, hydrologic soil groups, soil type and contour are stored, processed, managed and displayed in GIS environment. In addition, the weighted curve number (CN) was determined using the remote sensing and GIS method recommended by Mishra and Babu (2008). Derived weighted CN from CN suggested by Chow et al. (1988) were applied to each sub-catchments and ranged from to for Antecedent Moisture Content (AMC) I (Dry condition), 25 to 95 for AMC II (Normal moisture

5 132 Y.S. Liew et al. Table 1. Summary of sensitivity test. Parameters Tested case Comments Soil Antecedent Moisture Content (AMC) CN for landuse and Hydrologic Soil Groups (HSG) Hydrologic Loss Model Rainfall Intensity Interval Drainage property (Manning s n) Culvert Inlet Properties (Concrete Rectangular Conduits) AMC I (Dry), AMC II (Normal) and AMC III (Wet) HSG A, HSG B, HSG C and Combination of HSG B with A and C Horton Method, SCS Method and Green-Ampt Method condition) and to for AMC III (Wet condition). Info Works CS model development InfoWorks Collection System (CS) version 8.5 together with GIS applications were used to develop a 1- dimensional hydrodynamic model of the Kota Damansara urban drainage system. The software can support up to four different system types (wastewater, stormwater, combined or other) within any one model. It can also support the import and export of data and results (either water level, flow or volume) to specific layers to be displayed in ArcView GIS, ArcInfo or MapInfo application (Wallingford Software 2008). The model development involved the creation of a constructed drainage network containing all the information needed to describe the drainage system. Basically, the overall drainage system is a combination of closed rectangular or circular conduits and open rectangular channels (both with measured geometry) which flow into the dry detention pond and formed a natural river systems. each network was modelled as a collection of subcatchment areas contributing to nodes, which represent the manhole or sump, joined by links, which represent the conduits or channels according to the surveyed data. For each of the nodes at the end of each networks, it is linked to the nearest river cross-sections which represents the dry detention pond before directing the flow to the pond outlet structures (Manning s n of with free flow condition). There were a total of 177 sub-catchments (i) It proves the theory stated if there was rainfall occurred during 5 days prior the event tested, AMC III should be applied. (ii) Water level is increasing if the soil condition is wet. (i) Combination of HSG B, A and C gives best fitted results (i) Green-Ampt Method gives the best results and fitted better in term of shape and the peak value 5 min and 15 min interval (i) Small rainfall interval should be applied (ii) 5 min gives better results 0.011, (i) Applying Manning s n ¼ gives better and results (ii) Water depth is decreasing if the condition is Headwall and wingwalls at 308 to 708 to barrel/ square edge and Headwall and wingwalls at 158 to barrel/square edge rougher (i) Changes of culvert inlet properties is not significant as observed only small range of differences for both water depth and flow comparison generated, which contributed flow into 152 drainage nodes, 143 links (117 closed conduits and 26 open rectangular channels), and 10 natural river crosssections from CH 500 to CH 0 (50 m interval). The United States Soil Conservation Service (SCS) curve number method or SCS model was chosen as the rainfall-runoff model. It was suggested that the SCS model could produce fast results and could be easily updated as the land use or land cover changes (Tsheko 2006, Mishra and Babu 2008, Leow et al. 2008). The SCS model was also well tested and proven in general runoff predictions for ungauged catchments (Yip 2002, Tsheko 2006, Kannan et al. 2006, Leow et al. 2008). Koehn et al. (2011) also applied the SCS CN method to quantify stormwater runoff in an urban catchment. Info Works CS model calibration and verification Methods et al. (2003) stated that any hydraulic model should be calibrated to the greatest degree of accuracy possible and verification step should follow. The verified model can then be applied to further simulation and analyses. The model was divided into a hydrological model and a hydraulic model for the calibration process. The hydrological parameters calibrated were the soil AMC, CN for land use, HSG, hydrology loss model and rainfall intensity interval. The hydraulic parameters calibrated were drainage properties on Manning s n coefficient and the culvert property. The sensitivity test that the CN for land use based on HSG, AMC, hydrology loss model, rainfall intensity intervals, and

6 Urban Water Journal 133 Table 2. Results of model calibration and verification. 3 /s) Peak water level (m) r 2 Difference time to peak (min) r 2 Peak flow (m Observed Simulated Differences Observed Simulated Differences Observed Simulated Differences Event (7.1%) (11.35%) :19 16: February 2006 (Calibration) (3.5%) (12.78%) :25 16: October 2007 (Calibration) (1.1%) (28.15%) :32 18: November 2007 (Calibration) (4.5%) (36.1%) :03 05: February 2006 (Verification) (0.7%) (26.4%) :54 16: September 2006 (Verification) (3.8%) (21.3%) :39 3: October 2007 (Verification) (9.4%) (10.5%) :15 16: March 2008 (Verification) drainage properties, particularly Manning s n coefficient, were sensitive parameters compared to culvert properties. The measurements were calibrated by comparing the simulated and observed water level at the site. The summary of the sensitivity test is shown in Table 1. Three rainfall events, on 17 February 2006 (9- month ARI), 20 October 2007 (8-year ARI) and 29 November 2007 (2-year ARI), were selected for model calibration, and four rainfall events, on 26 February 2006 (25-year ARI), 9 September 2006 (4-year ARI), 22 October 2007 (18-month ARI) and 19 March 2008 (1-month ARI), were used for model verification. The verification processes covered all possibilities, including the highest, medium and lowest rainfall events captured within the catchment, and all models were verified with acceptable errors. The results are shown in Table 2. Statistical analyses using two sample t-tests and regression analysis within the MINITAB software were performed based on methods discussed by Mann (2005). The differences were in the range of % for peak water level and % for flow. The indication of more than 10% up to 36% of difference in flow is due to the observed flow calculation from the rating curve generated which covered only maximum of observed water level up to 2 m only. Anyway, all storm events still fit the 95% confident interval. The comparison between the observed and simulated scenarios for both calibrated and verified models also showed good agreement and satisfactory mean square errors (r 2 ) of more than 0.9 as shown in Table 2. Figures 4 and 5 show an example of the observed and simulated water levels for the 20 October 2007 (calibration) and 26 February 2006 (verification) events, respectively. Results and discussion The simulation and analysis results show that the peak water depth for all design rainfalls occurs after 60 min of rainfall. Therefore, to evaluate the performance of the existing pond, 60 min of rainfall for the 2-, 10-, 50- and 100-year ARIs were tested, and the resulting water depths were compared. The simulation results are shown in Table 3. From the survey, the highest water level simulation for the 50- year ARI is m and m for the 100-year ARI, both showing water levels below the ground level of the Cecawi 6/27 Road (28 m) and no flooding was observed. It was found that the existing dry detention pond designed by Ganendra, Ahmad and Associates in 1996 managed to cater for the flow up to the 100-year ARI of the design without flooding. It complied with the requirement in the MSMA by using 100-year floods as

7 134 Y.S. Liew et al. Figure 4. Observed vs. simulated water levels for 20 October 2007 (model calibration). Figure 5. Table 3. Results of simulations of water depth and flow for various ARIs. Comparison of peak Observed vs. simulated water levels for 26 February 2006 (model verification). ARI (year) Water depth (m) Water level (m) Flow (m 3 /s) the design storm ARIs for major urban stormwater system. As shown in Table 3, the maximum flow simulated for the 2-year ARI to the 100-year ARI ranges from m 3 /s. The dry detention pond also serves to attenuate flow and delay the time to peak downstream of the pond. Figures 6 and 7 show the flow attenuation and different times to peak flow from CH500 (Tambul River upstream) to the pond outlet/culvert inlet (Tambul River Downstream) of the dry detention pond as shown in Figure 2 for the 50-year and 100-year ARIs, respectively. The dry detention influences the shape of the hydrograph and decreases the peak flow noticeably. The results indicate that the dry detention pond could attenuate flow at 40 m 3 /s and increase the time to peak by 40 min for the 50-year ARI. For the 100-year ARI, the detention pond could attenuate flow at 42 m 3 /s and increase the time to peak by 45 min. The present study confirms the ability of detention ponds to attenuate peak flow up to a 100 years storm, as discussed by Ahmad Nasir (2008). Table 4 shows a comparison of the outflow for 60 min of rainfall under the 100-year ARI stated in a previous design specification (Ganendra, Ahmad and Associates 1996) with the current capacity of the dry detention pond. The results demonstrate only minimal differences of 1.0% and 1.8% in water level and flow, respectively, on the capacity of existing dry detention pond compared to the previous design specification. The difference was due to the application of a different method for flow computation. The modified rational

8 Urban Water Journal 135 Figure 6. Peak flow attenuation from CH500 (Tambul River upstream) to the pond outlet/culvert inlet (Tambul River downstream) in the dry detention pond for the 50-year ARI. Figure 7. Flow attenuation from CH500 (Tambul River upstream) to the pond outlet/culvert inlet (Tambul River downstream) in the dry detention pond for the 100-year ARI. Table 4. Comparison of water depth and flow for 60 min-of rainfall at the100-year ARI on design specification and the current capacity of the dry detention pond. Design Specification Current ConditionCapacity Differences Difference (%) Water level (m) Flow (m 3 /s) method was used by the consultant, whereas this research applied the SCS curve number method using a hydrodynamic approach for the simulation, which gave more detailed information. The minimal differences in the comparison above indicates that the existing detention pond, designed and built before the implementation of MSMA, is able to store the total volume of water for the 100-year ARI. Apart from that, the result also strengthens the claim that the urban drainage model provides reasonable results and could be applied for further model simulations. Conclusions The existing dry detention pond manages to cater for flows up to the 100-year ARI design rainfall without

9 136 Y.S. Liew et al. flooding under the design by Ganendra, Ahmad and Associates (1996). It complied with the requirement in MSMA by using a 100-year flood as the design flood level for major urban stormwater systems, such as detention ponds, to be protected against flooding. It also demonstrated the necessity of detention ponds and justified the costly investment required for the benefit of the local communities against flooding. Acknowledgements The research reported herein was funded by the Government of Malaysia under NAHRIM. The first author would like to acknowledge Ir. Hj. Ahmad Jamalluddin Shaaban, Director- General of NAHRIM, and all of the staff from NAHRIM and REDAC for their guidance and support throughout the study. References Ahmad Nasir, B., Peak flow attenuation using dry pond for existing housing schemes. Thesis (Master). Universiti Sains Malaysia. Chow, V.T., Maidment, D.R., and Mays, L.W., Applied hydrology. Singapore: McGraw-Hill. 2 3, 108, , and Department of Irrigation and Drainage Malaysia (DID), Urban Stormwater Management Manual for Malaysia or MSMA. Kuala Lumpur, Malaysia: Pencetakan National Malaysia Berhad (PNMB). Ganendra, Ahmad and Associates, Computation of total runoff for the proposed sungai rumput and sungai tambul channel and flood routing for proposed flood detention ponds. Consultant Report. Selangor, Malaysia: Ganendra, Ahmad and Associates. Hassan, J., River and floodplain modelling for the development of flood risk map: a case study of Sungai Selangor. Thesis (Master). Universiti Sains Malaysia. Kannan, N., et al., Hydrological modeling of a small catchment using SWAT Ensuring correct flow partitioning for contaminant modeling. Journal of Hydrology, 334 (1 2), Koehn, L., Brye, K.R., and Scarlat, C., Quantification of stormwater runoff using a combined GIS and curve number approach: a case study for an urban watershed in the Ozark Highlands, USA. Urban Water Journal, 8 (4), Krishnappan, B.G. and Marselek, J., Modelling of flocculation and transport of cohesive sediment from an on-stream stormwater detention pond. Water Research, 36 (15), Larm, T., Stormwater quantity and quality in a multiple pond-wetland system: Flemingsbergsviken case study. Ecological Engineering, 15 (1 2), Leow, C.S., et al., Modelling urban river catchment: a case study in Malaysia. Water Management, 162 (1), Liew, Y.S., Performance of urban stormwater drainage system through dry detention pond (case study: Kota Damansara, Selangor). Thesis (Master). Universiti Sains Malaysia. Liu, X.B., et al., A coupled model of hydrodynamics and water quality for Yuqiao reservoir in Haihe river basin. Journal of Hydrodynamics, 20 (5), Mann, P.S., Introductory statistics: using technology. Hoboken, NJ: John Wiley & Sons. Methods, H., et al., Floodplain modeling using HEC- RAS. Waterbury, US: Haestad Press. Mishra, P. and Babu, R.R., Hydrological modelling of Gayapaharinala watershed in Chotanagpur Plateau. Journal of Water Management, 16 (1), Northern Virginia Planning District Commission and Engineers and Surveyors Institute, Northern Virginia BMP handbook: a guide to planning and designing best management practices in Northern Virginia. Annandale, Virginia: Northern Virginia Planning District Commission. Semadeni-Davies, A., et al., The impacts of climate change and urbanisation on drainage in Helsingborg, Sweden: suburban stormwater. Journal of Hydrology, 350 (1 2), Somes, N.L.G., Fabian, J., and Wong, T.H.F., Tracking pollutant detention in constructed stormwater wetlands. Urban Water, 2 (1), Sperling, M.V., et al., Comparison between polishing (maturation) ponds and subsurface flow constructed wetlands (planted and unplanted) for the post-treatment of the effluent from UASB reactors. Water Science & Technology, 61 (5), Tsheko, R., Comparison between the United States Soil Conservation Service (SCS) and the two models commonly used for estimating rainfall-runoff in southeastern Botswana. Water Research Commission, South Africa, 32, Walker, D.J., Modelling residence time in stormwater ponds. Ecological Engineering, 10 (3), Wallingford Software, InfoWorks CS (collection systems) technical review. Wallingford, UK: Wallingford Software Ltd. Xu, Z.Y., Godrej, A.N., and Grizzard, T.J., The hydrological calibration and validation of a complexlylinked watershed-reservoir model for the Occoquan Watershed, Virginia. Journal of Hydrology, 347 (3 4), Yi, Q.T., et al., Characteristics of nutrient retention in a stormwater wetland during dry and wet days. Water Science & Technology, 61 (6), Yip, H.W., Flood runoff estimation of ungauged river catchments using soil conservation service method. Thesis (Master). Universiti Sains Malaysia.