Extensive research has been undertaken to improve the robustness of runoff quantity predictions for urban catchments. However, equally robust predictions for runoff quality have yet to be attained. Past studies addressing this issue have typically been confined to the use of simple conceptual or empirical models which forgo the tedious steps of providing a physical representation of the actual system to be modelled. Consequently, even if the modelling results for the test catchments are satisfactory, the reliability and applicability of these models for other catchments remain uncertain. It is deemed that by employing process-based, deterministic models, many of these uncertainties can be eliminated. A lack of understanding of the hydrological processes occurring during storm events and the absence of good calibration data, however, hamper the advancement of such models and limit their use in the field. This research proposes that the development of a hydrologic model based on the kinematic wave equations linked to an advection-dispersion model that simulates pollutant detachment and transport will improve both runoff quantity and quality simulations and enhance the robustness of the predictions. At the very worst, a model of this type could still highlight the underlying issues that inhibit models from reproducing the recorded historical hydrographs and pollutographs. In actual fact, this approach has already been applied by various modellers to simulate the entrainment of pollutants from urban catchments. Also, the paradigm shift to using the Water Sensitive Urban Design (WSUD) approach in designing urban stormwater systems has prompted the need to differentiate the various sources of pollutants in urban catchments such as roads, roofs and other impervious surfaces. The primary objective of the study reported herein is to model runoff quantity and quality from small urban catchments, facilitated by the procurement of the necessary field data to calibrate and validate the model via implementation of a comprehensive field exercise based in Sydney. From a water quality perspective, trace metals were selected as the foci. The study outcomes include the formulation of a linkage of models capable of providing accurate and reliable runoff quantity and quality predictions for the study catchments by taking into consideration: - The different availability of pollutants from urban catchments, i.e. roads vs. roofs; - The build-up characteristics of pollutants on the distinct urban surfaces and their spatial distribution; - The contribution of rainwater to urban runoff pollution; - The partitioning of pollutants according to particulate bound and dissolved phases; - The respective role of rainfall and runoff in the detachment and entrainment of pollutants; - The influence of particle properties such as particle size distribution and density on pollutant transport; and - The relationship associating particulate bound metals to suspended solids. The simulation results obtained using the proposed model were found to be suitable for modelling the detachment and transport of pollutants for small urban catchments. Interpretation of these results reveals several key findings which could help to rectify shortcomings of existing modelling approaches. Even though the robustness of the model presented here may not translate into a significant improvement in the overall robustness of model predictions, the physical basis on which this process-based model was developed nevertheless provides the flexibility necessary for implementation at alternative sites. It is also shown that the availability of reliable runoff data is essential for implementation of the model for other similar urban catchments. In conclusion, the proposed model in this study will serve as a worthy tool in future urban catchment management studies.
| Identifer | oai:union.ndltd.org:ADTP/272636 |
| Date | January 2009 |
| Creators | Cheah, Chin Hong, Civil & Environmental Engineering, Faculty of Engineering, UNSW |
| Publisher | Awarded By:University of New South Wales. Civil & Environmental Engineering |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | http://unsworks.unsw.edu.au/copyright, http://unsworks.unsw.edu.au/copyright |
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