dc.description.abstract | Urbanization has occurred in Singapore over the recent decades concurrent with the growth of Singapore’s population and economy. The process of urbanization has significantly impacted both the storm runoff volume and the timing and magnitude of the peak runoff rate. Urbanization also increases the variety and amount of pollutants transported to receiving waters, causing surface water quality deterioration. Studies on stormwater quantity and quality are hence vital for planning and managing water resources for catchments subjected to human perturbations. The objective of this study is to develop an approach for estimating long term runoffs and pollutant loadings for the Kranji catchment in Singapore, particularly as functions of land use. he study first established the rainfall-total runoff relationships and total runoff-pollutant loading rate relationships in Kranji Catchment, Singapore. Storm water data were measured and used for calibration and verification of the XP-SWMM model. The calibrated XP-SWMM model was then applied for continuous simulation of catchment runoffs over the 2005-2007 period. The results from XP-SWMM simulations showed that the model is capable of providing good results for continuous flow simulations, and is highly efficient for the estimation of urban storm water direct runoff volumes. he relationship between rainfall and runoff for the gauged period at each study site shows good correlations. The runoff coefficient (total flow/rainfall ratio) is found to be a function of the total rainfall and land use. In comparing gauging stations CP2 with CP4, the average runoff coefficient is about 3 times higher for CP2, which has the largest proportional area which is developed, around 68%, comprising mainly residential land use with high impervious land cover. In contrast, CP4, which has the largest proportional previous areas, has the lowest runoff coefficient of 0.13. his study covered thirteen water quality parameters which are considered relevant for water quality management: ammonium-equivalent nitrogen (NH3-N), dissolved organic carbon (DOC), particulate organic carbon (POC), total nitrogen (TN), total dissolved nitrogen (TDN), nitrate+nitrite (NOx), dissolved organic nitrogen (DON), total phosphate (TP), total dissolved phosphate (TDP), ortho-phosphate (OP), dissolved organic phosphorus (DOP), silica (SiO2), and total suspended solids (TSS). A good knowledge of the relative pollutant load contributions from dry-weather flow (DWF) and wet-weather flow (WWF) could provide useful guides for implementing effective and efficient water quality management measures for the sub-catchments. This study uses a regression approach to estimates the WWF loads, and uses the monitored data to estimate the DWF loads. The annual DWF and WWF pollutant loadings were characterized over the 2005-2007 period. For nearly all the pollutants studied, contributions from WWF are greater than DWF at CP1, CP2, CP6 and CP7. However, almost all quality parameters show larger contributions from DWF than WWF at CP4, except for TP, TDP, DOP, OP and TSS. The results suggest that DWF quality control measures may be important for CP4. On the other hand, WWF quality management may be important for CP1, CP2, CP6 and CP7. he analytical approach developed in this study can be applied to other ungauged watersheds near the study site. The results of this study will provide a better understanding on both the flow and nutrient loading into the reservoir which will aid the overall management objective of nutrient load reduction. | en |
dc.description.tableofcontents | 誌謝 i要 iiBSTRACT iiiIST OF CONTENTS vIST OF FIGURES viiIST OF TABLES ixhapter 1 Introduction 1.1 Background 1.2 Objective and Scope of the Study 2.3 Organization of the Thesis 3hapter 2 Literature Review 5.1 Storm Runoff Modeling 5.2 Impact of Non-Point Source Pollution 11hapter 3 Study Site Description 17.1 Kranji Reservoir 17.2 Kranji Watershed 18.3 Gauging Station 20.3.1 Channel Cross-Section 25.4 Meteorological Condition 27hapter 4 Methodology 29.1 Description of XP-SWMM Model 29.1.1 Overview of XP-SWMM Capabilities 29.1.2 RUNOFF Block Routing Method 32.1.3 Rainfall Abstraction Methods 36.1.4 Routing Methods 36.1.5 Hydrograph Separation 37.1.6 Generation of Baseflow 38.1.7 Sensitivity Analyses 41.1.8 Evaluation Criteria 49.2 Load Estimation Method 50.2.1 Dry-Weather Flow Load Calculation 50.2.2 Wet-Weather Flow Load Calculation 52.2.3 Regression Analysis 53.2.4 Annual Pollutant Loadings 55hapter 5 Results and Discussion 59.1 Calibration and Verification Results for CP1, CP2, CP4, and CP7 59.1.1 Long-Term Runoff Simulation 69.2 Impact of Land Use on Runoff-Loading Rates 74.2.1 Analysis of Event Mean Concentrations 74.2.2 Analysis based on Rating Curve 76.2.3 Analysis based on Simple Method 92hapter 6 Conclusions &Recommendations 95.1 Conclusions 95.2 Recommendations 98EFERENCES 99PPENDIX APPENDIX BPPENDIX CPPENDIX DPPENDIX E | en |