Ata Amini, Thamer Mohammad Ali, Abdul Halim B. Ghazali, Azlan A. Aziz & Shatirah Mohd. Akib

Impacts of Land-Use Change on Streamflows in the Damansara Watershed, Malaysia Ata Amini, Thamer Mohammad Ali, Abdul Halim B. Ghazali, Azlan A. Aziz & Shatirah Mohd. Akib Arabian Journal for Science and Engineering ISSN 1319-8025 Volume 36 Number 5 Arab J Sci Eng (2011) 36:713-720 DOI 10.1007/s13369-011-0075-3 1 23

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Arab J Sci Eng (2011) 36:713 720 DOI 10.1007/s13369-011-0075-3 RESEARCH ARTICLE - CIVIL ENGINEERING Ata Amini Thamer Mohammad Ali Abdul Halim B. Ghazali Azlan A. Aziz Shatirah Mohd. Akib Impacts of Land-Use Change on Streamflows in the Damansara Watershed, Malaysia Received: 4 December 2009 / Accepted: 25 May 2010 / Published online: 9 August 2011 King Fahd University of Petroleum and Minerals 2011 Abstract Land-use change has significant impacts on hydrologic processes at the watershed level. In this study, hydrologic models and spatial data were used to assess the effects of land-use changes and predict the effects of two future land-use scenarios on the flood regime of the Damansara Watershed. Due to urban growth, the Damansara Watershed has seen increasing streamflows and experienced occasional flooding. The hydrology was modeled using the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model, and land-use changes were quantified with land-use maps. Actual storms were used to calibrate and validate HEC-HMS rainfall-runoff model. The calibrated HEC-HMS model was used to simulate future streamflows and to forecast the impact of land-use changes on downstream peak streamflow. The model also estimated the contribution of individual sub-basins to downstream peak streamflows of the entire watershed. The model predicts that changes in land-use will increase the peak streamflow, and the increase is directly proportional to the rate of urbanization. It was found that the sensitivity of the hydrologic response to land-use change increases as the recurrence interval of rainfall events decreases, and that those impacts are more pronounced in different sub-basins. The results of this study provide support for land-use planning and the management of watersheds. Keywords Land-use change Peak streamflow Hydrologic modeling HEC-HMS Urbanization A. Amini (B) Agricultural and Natural Resources Research Center of Kurdistan, Sanandaj, Iran E-mail: ata_amini@yahoo.com T. M. Ali A. H. B. Ghazali A. A. Aziz Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, 43400 Kuala Lumpur, Malaysia S. Mohd. Akib Department of Civil Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia

714 Arab J Sci Eng (2011) 36:713 720 1 Introduction As development increases, so land-use also changes. These changes progressively affect the local hydrological cycle creating problems with streamflows, water yields, low or high flows, surface runoff and erosion, soil moisture, and evapotranspiration [1]. Precipitation that falls on developed areas quickly flows into streams, increasing storm-water runoff and erosion. A variety of modeling approaches have been used for exploratory analysis of the hydrological effects of land-use change including: statistical trend analysis of recorded flood series, analysis of flood hydrographs, as well as stochastic method that adjust streamflow at urbanized watersheds before and after urbanization [2]. In addition to experimental watersheds or hydrologic models, empirical modeling of documented changes in land cover or land-use patterns have been used to evaluate and predict the hydrologic response to land-use changes [3,4]. Empirical land-use change models and event-scale rainfall-runoff models have also been combined to quantify the impacts of potential land-use change on the storm-runoffgeneration [5]. Aspinall [3]developedan approach to modeling land-usechange that links model selection and multi-model inference with empirical models and spatial data. Saghafian [6]quantifiedpossible effects of land-use changes and identified flood source areas for future flood control planning. The Damansara Watershed is a tropical watershed. Due to rapid economic growth and associated urbanization, over recent decades it has been undergoing intensive land-use change. Previous work on urban growth and runoff estimation and prediction in the Damansara Watershed concluded that land-use change influenced the quantity of runoff. The outlook got worse if adequate drainage systems were not implemented [7]. In Malaysia, the construction of retention ponds as a method of flood control has been encouraged. However, reliable estimations of discharge are required to allow appropriate design of urban drainage systems in the context of land-use change. To achieve this goal, hydrological models under various land-use conditions seem to be appropriate. The objective of this work is to quantitatively assess the change in streamflow in the Damansara Watershed (Malaysia) in response to land-use changes using real storms as test conditions. 2 Methodology The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS, version 3.1.0) was used to develop a hydrologic model for the Damansara Watershed in a distributed modeling scheme. The HEC-HMS is a numerical model that includes a large set of methods to simulate watershed, channel, and water-control structure behavior, thus predicting flow, stage, and timing [8]. The HEC-HMS is a semi-distributed, event scale model, which considers all relevant hydrologic processes, such as evaporation, surface runoff, percolation, and groundwater recharge. The model addresses the spatial distribution of catchment characteristics by subdividing a catchment into sub-catchments that are treated as homogenous in land-use, soil type, etc [5]. The obvious advantage of this program is the ability to optimize parameters [9]. In this work the parameters were prepared with HEC-GeoHMS, in a semi-automated process. A background map file, grid cell parameter file, and distributed basin schematic model file produced by HEC-GeoHMS were used as input files for the

Arab J Sci Eng (2011) 36:713 720 715 HEC-HMS model. Combination of the HEC-GeoHMS and the HEC HMS provide a suite of hydrological modeling options, with a focus on estimation of sub-basin runoff hydrographs and routing the hydrographs through channels to the outlet [10]. Different methods are chosen by different researchers based on existing data and local characteristics. In this study, because new land-use distribution scenarios and associated Curve Number (CN), can be easily developed and hydrologically assessed, the Soil Conservation Service (SCS) Curve Number, which is an empirical approach, was selected to estimate the effective rainfall. For overland routing, the Snyder Unit Hydrograph Method, which was developed to compute the peak flow resulting from unit precipitation, was adopted to incorporate the spatial variability. Additionally, channel flow was determined by the Muskingum routing model; and baseflow was calculated by the exponential recession method. To develop the weights applied to each gauge when calculating the hyetograph for each sub-basin, an area-based weighting scheme, namely the Thiessen Polygon, was used. The Thiessen Polygon is based upon the assumption that the precipitation depth at any point within a watershed is the same as the precipitation depth at the nearest gauge in or near the watershed. It assigns a weight to each gauge in proportion to the area of watershed that is closest to that gauge [8]. Further, the evapotranspiration (ET) losses were considered to be negligible given the intensity of the storm events used, i.e. the ET volume is negligible compared to that of runoff [5,11,12]. The study area was the Damansara Watershed located in Kota Damansara, Selangor, Malaysia. The watershed area is about 20.2 km 2 and is one of the most urbanized watersheds in the area. The topography of the project area is hilly to undulating. The project area rises from 21.72 to 202 m above mean sea level. The watershed is dominated by dense forest, while the major land-use in Kota Damansara is housing and shops; these form the impervious areas (approximately half of the catchment area), while the remaining areas are forest, schools, landscape and fields [7]. The average rainfall is about 2,400 mm, and the highest months (April and November) have precipitations above 250 mm. June has the lowest rainfall, with an average of almost 100 mm. The main river in the catchment is Sungai. Kayu Ara, which is about 7 km long and has a 0.3% slope from North (Kg. Sg. Penchala) to South (Taman Mayang). Within the Damansara Watershed, there are 5 gauging stations (dipping wells) and 16 hourly precipitation gauging stations. The locations of the stations are shown in Fig. 1. However, in this study, gauging station data from only 12 precipitation and 1 water level sites were obtained from the Department of Irrigation and Drainage (DID) Malaysia. The Department of Land and Survey (JUPEM) provided the topographic map. The entire watershed was disaggregated into 8 sub-basins, see Fig. 1. Thedrainagenetworkswere also delineated. The topographic attributes and characteristics for each sub-basin were derived from the topographic maps as shown in Table 1. The soil type and land-use maps were collected from the Department of Agriculture (DOA) Malaysia and were used to calculate the sub-basin characteristics and the initial calculation of hydrology parameters by using equations USACE [8]. The high, intermediate and low precipitation and streamflow events were chosen to calibrate and validate the HEC-HMS hydrologic model under 2005 land-use conditions. Model calibration was performed to minimize the difference between the observed and the simulated hydrograph, with respect to the runoff volume, the peak flow and the time to peak. The results are shown in Fig. 2. In this study, the model was run on a 15 minute time interval. To analyze the hydrologic impact of land-use change, after calibration and verification, the model was executed for two limiting future scenarios: The optimistic scenario (Scenario 1) and pessimistic scenario (Scenario 2). These were used to predict the lower and upper thresholds of the hydrologic response of the watershed. The scenarios were the basis of the sensitivity analysis when using the different hydrologic data in the model. In the optimistic scenario, in line with San [7], it was assumed that the forest area (8.1 km 2 ) upstream of the catchment (Upper TTDI and Sg. Penchala) is converted to paved area (equivalent to 40% urbanization). In the pessimistic scenario it was assumed that the entire watershed becomes an urban area. Scenario 2 is consistent with the trend of land-use changes between 1987 and 2005 for some sub-basins, which were characterized by great increases in urban areas along with great decreases in forest areas. Hence it may be that the second scenario might be the better representation of land-use changes underway in the Damansara Watershed. The 2005 land-use map was considered as the initial condition from which both scenarios were developed, hence in this work the land-use from 2005 is termed current. Impervious change is a characteristic of urban development, thus, to investigate the hydrologic impact of urban development, modeling the Curve Number (CN) is desirable with regard to the surface imperviousness [5,13]. According to the USDA [14] urban land type is directly related to the surface imperviousness. The CN for a watershed can be estimated as a function of land-use, soil type, and antecedent watershed moisture. The CN values range from 100 (for water bodies) to

716 Arab J Sci Eng (2011) 36:713 720 Fig. 1 Catchment area and sub-basins layout at the Damansara Watershed Table 1 The characteristics of the sub-basins of the Damansara Watershed Subbasin Area Slope Subbasin length River length Imperviousness CN Initial abstraction (km 2 ) (%) (km) (km) (%) Sg. Penchala 3.885 0.320 1.51 1.59 6.40 71 20.75 Upper TTDI 4.223 0.120 4.14 3.87 17.40 73 18.79 TTDI 1.647 0.058 2.63 1.51 48.69 85 8.96 Bandar Utama 1.159 0.039 3.09 1.08 67.16 85 8.96 Sg. Kayu Ara 4.645 0.049 7.28 4.92 44.47 85 8.96 Tropicana 2.862 0.073 4.86 2.55 18.25 85 8.96 Damansara Jaya 1.796 0.049 2.03 1.17 64.78 85 8.96 Taman Mayang Megah 0.047 0.038 1.15 1.15 21.96 85 8.96 approximately 30 for permeable soils with high infiltration rates. For a watershed that consists of several soil types and land uses, a composite CN can be calculated. For each scenario, the CN for each sub-catchment was calculated. The peak flow at the Damansara Watershed was calibrated and the results are shown in Fig. 2 and Table 2. To assess the potential land use impacts on storm-runoff, the calibrated HEC HMS model was applied to each of these future land use scenarios using the same storm events which were used in the model validation process. The results of model validation and predicted values under both scenarios in comparison with the data observed on 28th Nov 2004, 6th Dec 2004 and 11th Dec 2004 are shown in Fig. 3. Peak streamflows for each sub-basin were also simulated under Scenario 2. In addition, to identify the effect of the land-use change of each individual sub-basin on streamflow, the model was applied to the entire watershed when only the land use of a selected sub-basin was changed to scenarios conditions.

Arab J Sci Eng (2011) 36:713 720 717 Fig. 2 Comparison of observed and simulated runoff used to calibrate the model. a High rainfall event. b Intermediate rainfall event. c Low rainfall event Table 2 Rainfall and discharge events during the calibration and validation period Type of flow Date Observed peak Computed peak Deviation of runoff Change in time (m 3 /s) (m 3 /s) (%) (min) Calibration High 13 Nov 06 193.38 197.60 2.18 0 Intermediate 01 Dec 04 132.20 127.70 3.39 5 Low 27 May 05 62.90 57.40 8.70 11 Validation High 28 Nov 04 298.94 296.20 0.82 10 Intermediate 06 Dec 04 99.80 95.50 4.40 0 Low 11 Dec 04 63.80 57.80 9.52 15

718 Arab J Sci Eng (2011) 36:713 720 Fig. 3 Comparison of observed and simulated runoff; these were used to validate the model and the simulated discharge under defined scenarios. a High rainfall event. b Intermediate rainfall event. c Low rainfall event 3Results Analysis of the land-use maps show that there has been significant change in land-use between 1987 and 2005 in the Damansara Watershed: the forest has been converted into urban areas. From Table 2, it is apparent that the percentage difference between simulated and observed streamflow is within 10%, which indicates good ground-truthing of the model. However, runoff peaks more quickly with greater land-use change. The maximum difference was found to be 27 minutes for the low storm event under Scenario 2 as shown in Fig. 3c. The deviation of runoff peaks D v is calculated as follows. where Q S and Q O are the simulated and observed peak values. D v = (Q o Q s ) Q o 100 (1)

Arab J Sci Eng (2011) 36:713 720 719 Table 3 Variation of peak streamflow with land use change at Damansara Watershed Type of flow Date Peak flow (m 3 /s) Deviation of peak flow at Scenario 1 (%) Current land use Scenario 1 Scenario 2 High 28 Nov 04 298.94 303.03 340.80 1.37 14.00 Intermediate 06 Dec 04 99.80 102.40 121.05 3.10 21.30 Low 11 Dec 04 63.80 66.54 80.33 4.30 26.70 Deviation of peak flow at Scenario 2 (%) The model was run for the optimistic and pessimistic scenarios, as well as for the 2005 land-use conditions. The changes in peak discharge due to changes of watershed land-use are shown in Table 3. Simulations for both scenarios indicate that there is a visible increase in the peak hydrograph for the Damansara Watershed. In addition, the results shown in Table 3 demonstrate that Scenario 1 resulted in smaller changes than those from Scenario 2 (deviation range from 1.37 to 4.3% for high and low storm events respectively). If land cover goes through a deteriorating trend towards the pessimistic scenario, the flood peak will increase by 14, 21.3 and 26.7% for high, intermediate and low storms respectively. The highest peak discharge of any event occurred under Scenario 2, and was 340.80 m 3 /s. However, due to non-uniform land-use changes across the sub-basins, the flood peak varied across the different sub-basins. The highest increases in peak streamflow were found in the Upper TTDI and Sg. Penchala sub-basins (+31% for low storm under Scenario 2). The smallest change in peak streamflow under Scenario 2 was observed in the Damansara Jaya sub-basin, which mainly consists of residual area, equivalent to a 7.3% increase under the same conditions. In addition, it was found that the higher sub-basins have greater impact on watershed streamflow than the lower sub-basins. 4 Discussion The effect of different land use conditions on the outflow peak discharge has been investigated. The simulation results indicate that land cover deterioration has increased the flood peak. Such an effect on the hydrologic response is more pronounced in some of the sub-basins such as Sg. Penchala and Upper TTDI, which had the highest permeability in the 2005 land-use data. The Damansara Jaya sub-basin was found to have the greatest impervious area, and subjected to minimum increment in peak streamflow. This result supports the finding of Saghafian et al. [8] who related it to the integrated effect of different factors such as river routing, sub-basin location in the entire watershed, topology of river network, spatial distribution of rainfall, and also the sub-basin physical characteristics. As can be concluded from Table 3 and Fig. 3, for both scenarios, the change in peak discharge is less for big storms. This is because the importance of land-use becomes less as the intensity of the storm increases. This finding is consistent with those of other works which link the increasing in peak streamflow and the storm return period [2,6]. Analysis of model results for individual sub-basins show that the upper sub-basins have the greatest effect on the total peak discharge at the watershed outlet. This result is consistent with the finding of Beighley et al. [10] who found that if urban development occurs within the upper portions of a watershed, it tends to result in a larger increase in the peak discharge at the outlet. Hence it is vital to investigate land-use change in the upper sub-basins of a watershed and its impacts on runoff dynamics. The results of this study have important implications for the development of flood control projects and the assessment of flood characteristics of Watersheds undergoing change. 5 Conclusions The purpose of the current study was to assess the effect of land-use change on storm-runoff in Damansara Watershed in Selangor, Malaysia. The following can be drawn from the present study: 1. Major urbanization in the Damansara Watershed has occurred over recent decades. 2. The simulation results indicate that land cover deterioration has increased the flood peak significantly. In this study, it was found that if land cover in Damansara Watershed continues on a deteriorating trend, the flood peak will increase up to 26.7% for smaller storms.

720 Arab J Sci Eng (2011) 36:713 720 3. The difference in the impact of land-use changes on the hydrologic response is more pronounced in some of the sub-basins more than others. Under same conditions, the increase in peak streamflow in the Upper TTDI and Sg. Penchala sub-basins was 31% compared to 7.3% in the Damansara Jaya sub-basin. 4. Under different watershed land-use scenarios, the rate of change of peak streamflow reduces as the return period for the storms increases. The deviation of peak streamflow for a high event (high return period) in comparison with a low event (low return period) were 14 and 26.7% respectively under Scenario 2. 5. The upper sub-basins have the greatest contribution to the total peak discharge at the entire watershed outlet. Future studies focusing on the trend of land use-change in the past, and estimation of future land-use are recommended. References 1. Sikka, A.K.; Sarma, J.S.; Sharda, V.N.; Samraj, P.; Lakshmanam, V.: Low flow and high flow responses to converting natural grassland into Bluegum (Eucalyptus globulus) in Nilgiris Watersheds of South India. J. Hydrol. 270, 12 26 (2003) 2. Amini, A.; Thamer, M.A.; Halim, B.G.; Bujang, K.H.: Adjustment of peak streamflows of a tropical river for urbanization. Am.J.Environ.Sci.5(3), 285 294 (2009) 3. Aspinall, R.: Modelling land use change with generalized linear models a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana. J. Environ. Manag. 72, 91 103 (2004) 4. Shadeed, S.; Shaheen, H.; Jayyousi, A.: GIS-based KW GIUH hydrological model of semiarid catchments: the case of Faria catchment, Palestine. Arab. J. Sci. Eng. 32(1c), 3 16 (2007) 5. Chen, Y.; Xu, Y.; Yin, Y.: Impacts of land use change scenarios on storm-runoff generation in Xitiaoxi Basin, China. Quat. Int. 208, 121 128 (2009) 6. Saghafian, B.; Farazjoo, H.; Bozorgy, B.; Yazdandoost, F.: Flood intensification due to changes in land use. Water Resour. Manag. 22(8), 1051 1067 (2007) 7. San, L.Y., Selamat, Z.; Ghani, A.A.: Urban stormwater drainage system study using numerical modeling. In: International Conference on Water Resources (ICWR 2009), Langkawi, Kedah, Malaysia (2009) 8. USACE (United States Army Corps of Engineers): Hydrologic modeling system-hec HMS. Technical Reference Manual, USACE, Washington, DC (2000) 9. Rahnama, M.B.; Barani, G.A.: Application of Rainfall-Runoff Models to Zard River Catchment s. Am. J. Environ. Sci. 1(1), 86 89 (2005) 10. Beighley, R.E.; Moglen, G.E.: Adjusting measured peak discharges from an urbanizing watershed to re1flect a stationary land use signal. Water Resour. Res. 39(4), 1093 1101 (2003) 11. Knebl, M.R.; Yang, Z.L.; Hutchinson, K.; Maidment, D.R.: Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC HMS/RAS: a case study for the San Antonio River Basin Summer 2002 Storm Event. J. Environ. Manag. 75, 325 336 (2005) 12. McColl, C.; Agget, G.: Land-use forecasting and hydrologic model integration for improved land-use decision support. J. Environ. Manag. 84, 494 512 (2007) 13. Ahn, G.: The effect of urbanization on the hydrologic regime of the big Darby Creek Watershed, Ohio. PhD Thesis, the Ohio State University, Columbus (2007) 14. U.S. Department of Agriculture (USDA): Urban Hydrology for Small Watersheds, TR-55, Washington, DC (1986)