This study explored the relationship between increased proportions of imperviousness in a watershed on surface water quality and examined the effectiveness of using remote sensing to systematically and accurately determine impervious surfaces. A supervised maximum likelihood algorithm was used to classify the 2008 high resolution National Agriculture Imagery Program (NAIP) imagery into six classifications. A stratified random sampling scheme was conducted to complete an accuracy assessment of the classification. The overall accuracy was 85%, and the kappa coefficient was 0.80. Additionally, field sampling and chemical analysis techniques were used to examine the relationship between impervious surfaces and water quality in a rainfall simulation parking lot study. Results indicated that day since last rain event had the most significant effect on surface water quality. Furthermore, concrete produced higher dissolved organic carbon (DOC), dissolved organic nitrogen (DON), potassium and calcium in runoff concentrations than did asphalt. Finally, a pollutant loading application model was used to estimate pollutant loadings for three watersheds using two scenarios. Results indicated that national data may overestimate annual pollutant loads by approximately 700%. This study employed original techniques and methodology to combine the extraction of impervious surfaces, utilization of local rainfall runoff data and hydrological modeling to increase planners' and scientists' awareness of using local data and remote sensing data to employ predictive hydrological modeling.

Concentrated animal feeding operations (CAFOs) have caused water quality concerns in many rural watersheds, sometimes forcing the State of Texas to conduct Total Maximum Daily Load (TMDL) assessments of stream nutrients such as nitrogen (N) and phosphorus (P). One suggested Best Management Practice (BMP) is the export of phosphorus (P) through turfgrass sod produced with composted dairy manure from an impaired rural watershed to an urban watershed. The manure-grown sod releases P slowly and would not require additional P fertilizer for up to 20 years in the receiving watershed. This would eliminate P application to the sod and improve the water quality of urban streams. The Soil and Water Assessment Tool (SWAT) was used to model a typical suburban watershed that would receive the transplanted sod. The objective of the modeling was to determine the water quality changes due to the import of sod transplanted from turf fields and grown with composted dairy manure. The SWAT model was calibrated to simulate historical flow and sediment and nutrient loading to Mary's Creek. The total P stream loading to Mary's Creek was lower when manure-grown sod was imported instead of commercial sod grown with inorganic fertilizers. Yet, flow, sediment yield, and total N yield increased equally for both cases at the watershed outlet. The SWAT simulations indicate that a turfgrass BMP can be used effectively to import manure P into an urban watershed and reduce in-stream P levels when compared to sod grown with inorganic fertilizers.

The research described in the thesis details the investigation of build-up and wash-off process kinetics of Polycyclic Aromatic Hydrocarbons (PAHs) and heavy metals in urban areas. It also discusses the design and development of a rainfall simulator as an important research tool to ensure homogeneity and reduce the large number of variables that are usually inherent to urban water quality research. The rainfall simulator was used to collect runoff samples from three study areas, each with different land uses. The study areas consisted of sites with typical residential, industrial and commercial characteristics in the region. Build-up and wash-off samples were collected at each of the three sites. The collected samples were analysed for a number of chemical and physico-chemical parameters. In addition to this, eight heavy metal elements and 16 priority listed PAHs were analysed in five different particle size fractions of the build-up and wash-off samples. The data generated from the testing of the samples were evaluated using multivariate analysis, which reduced the complexity involved in determining the relative importance of a single parameter in urban water quality. Consequently, variables and processes influencing loadings and concentrations of PAHs and heavy metals in urban stormwater runoff from paved surfaces at any given time were identified and quantified using Principal Component Analysis (PCA). Furthermore, the process kinetics found were validated using a multivariate modelling approach and Partial Least Square (PLS) regression, which confirmed the transferability of chemical processes in urban water quality. Fine particles were dominant in both the build-up and wash-off samples from the three sites. This was mirrored in the heavy metal and PAH concentrations at the three sites, which were significantly higher in particles between 0.45-75μm than in any other fraction. Thus, the larger surface area and electrostatic charge of fine particles were favourable in sorbing PAHs and heavy metals. However, factors such as soil composition, total organic carbon (TOC), the presence of Fe and Mn-oxides and pH of the stormwater were all found to be important in partitioning of the metals and PAHs into different fractions. Additionally, PAHs were consistently found in concentrations above their aqueous solubility, which was attributed to colloidal organic particles being able to increase the dissolved fraction of PAHs. Hence, chemical and physico-chemical parameters played a significant role in the distribution of PAHs and heavy metals in urban stormwater. More importantly, the research showed the wide range of factors that distribute metals and PAHs in an urban environment. Furthermore, it indicated the need for monitoring these parameters in urban areas to ensure that urban stormwater management measures are effective in improving water quality. The build-up and wash-off process kinetics identified using PCA at the respective land uses were predicted using PLS and it was found that the transferability of the governing processes were high even though the PAHs and metal concentrations and loads were highly influenced by the source strength at each site. The increased transferability of fundamental concepts in urban water quality could have significant implications in urban stormwater management. This is primarily attributed to common urban water quality mitigation strategies relying on studies based on physical concepts and processes derived from water quantity studies, which are difficult to transfer between catchments. Hence, a more holistic approach incorporating chemical processes compared to the current piecemeal solutions could significantly improve the protection of key environmental values in a region. Furthermore, urban water quantity mitigation measures are generally designed to reduce the impacts of high-flow events. This research suggests that fairly frequent occurring rainfall events, such as 1-year design rainfall events, could carry significant heavy metal and PAH concentrations in both particulate and dissolved fractions. Hence, structural measures, designed to decrease quantity and quality impact on receiving waters during 10 or 20-year Average Recurrence Interval (ARI) events could be inefficient in removing the majority of PAHs and heavy metals being washed off during more frequent events. The understanding of physical and chemical processes in urban stormwater management could potentially lead to significant improvements in pollutant removal techniques which in turn could lead to significant socio-economic advantages. This project can serve as a baseline study for urban water quality investigations in terms of adopting new methodology and data analysis.

Accurate and reliable estimations are the most important factors for the development of efficient stormwater pollutant mitigation strategies. Modelling is the primary tool used for such estimations. The general architecture of typical modelling approaches is to replicate pollutant processes along with hydrologic processes on catchment surfaces. However, due to the lack of understanding of these pollutant processes and the underlying physical parameters, the estimations are subjected to gross errors. Furthermore, the essential requirement of model calibration leads to significant data and resource requirements. This underlines the necessity for simplified and robust stormwater pollutant estimation procedures. The research described in this thesis primarily details the extensive knowledge developed on pollutant build-up and wash-off processes. Knowledge on both build-up and wash-off were generated by in-depth field investigations conducted on residential road and roof surfaces. Additionally, the research describes the use of a rainfall simulator as a tool in urban water quality research. The rainfall simulator was used to collect runoff samples from small-plot surfaces. The use of a rainfall simulator reduced the number of variables which are common to pollutant wash-off. Pollutant build-up on road and roof surfaces was found to be rapid during the initial time period and the rate reduced when the antecedent dry days increase becoming asymptote to a constant value. However, build-up on roofs was gradual when compared to road surfaces where the build-up on the first two days was 66% of the total build-up. Though the variations were different, it was possible to develop a common replication equation in the form of a power function for build-up for the two surface types with a as a multiplication coefficient and b as a power coefficient. However, the values for the two build-up equation coefficients, a, and b were different in each case. It was understood that the power coefficient b varies only with the surface type. The multiplication coefficient varies with a range of parameters including land-use and traffic volume. Additionally, the build-up observed on road surfaces was highly dynamic. It was found that pollutant re-distribution occurs with finer particles being removed from the surface thus allowing coarser particles to build up. This process results in changes to the particle size composition of build-up. However, little evidence was noted of re-distribution of pollutants on roof surfaces. Furthermore, the particulate pollutants in both road and roof surfaces were high in adsorption capacity. More than 50% of the road and more than 60% of the roof surface particulates were finer than 100 μm which increases the capacity to adsorb other pollutants such as heavy metals and hydrocarbons. In addition, the samples contained a significant amount of DOC which would enhance the solubility of other pollutants. The wash-off investigations on road and roof surfaces showed a high concentration of solid pollutants during the initial part of events. This confirmed the occurrence of the 'first flush' phenomenon. The observed wash-off patterns for road and roof surfaces were able to be mathematically replicated using an exponential equation. The exponential equation proposed is a modified version of an equation proposed in past research. The modification was primarily in terms of an additional parameter referred to as the 'capacity factor' (CF). CF defines the rainfall's ability to mobilise solid pollutants from a given surface. It was noted that CF varies with rainfall intensity, particle size distribution and surface characteristics. Additional to the mathematical replication of wash-off, analysis further focused on understanding the physical processes governing wash-off. For this, both particle size distribution and physicochemical parameters of wash-off pollutants were analysed. It was noted that there is little variation in the particle size distribution of particulates in wash-off with rainfall intensity and duration. This suggested that particle size is not an influential parameter in wash-off. It is hypothesised that the particulate density and adhesion to road surfaces are the primary criteria that govern wash-off. Additionally, significantly high pollutant contribution from roof surfaces was noted. This justifies the significance of roof surfaces as an urban pollutant source particularly in the case of first flush. This dissertation further describes a procedure to translate the knowledge created on pollutant build-up and wash-off processes using small-plots to urban catchment scale. This leads to a simple and robust urban water quality estimation tool. Due to its basic architecture, the estimation tool is referred to as a 'translation procedure'. It is designed to operate without a calibration process which would require a large amount of data. This is done by using the pollutant nature of the catchment in terms of buildup and wash-off processes as the basis of measurements. Therefore, the translation procedure is an extension of the current estimation techniques which are typically complex and resource consuming. The use of a translation procedure is simple and based on the graphical estimation of parameters and tabular form of calculations. The translation procedure developed is particularly accurate in estimating water quality in the initial part of runoff events.

The River Medlock is a small (22km) urbanised river, and is one of the five main tributaries which forms part of the River Irwell Catchment in Greater Manchester, UK. The river has a legacy of pollution from the 18th century and continues to be affected by anthropogenic factors including point source pollution from waste water treatment works (WwTWs) and combined sewer overflows (CSOs). In order to investigate the impact of CSOs and the WwTWs on the river hydrology, water quality and ecology of the lower largely urbanised reach, data sets were obtained from the Environment Agency and from direct sampling of the river. Load estimations from continuous discharge records from the river's gauging station plus estimates of sub-catchment area indicate the lower sites, classified as a "highly modified water body" and downstream of treatment works had had a higher load of discharge and phosphate-P linked to point sources and episodic discharges. Short term, continuous monitoring revealed that CSOs were active during high velocity, but increased concentrations of nutrients post high velocity indicate WwTW effects and possibly diffuse sources. This project reveals that the WwTW are a major source of phosphate-P and that the impact of CSOs on the river quality is short-lived and depends on the degree of precipitation. Other parameters indicate good water quality although the benthic macroinvertebrate community is degraded as a result of episodic increases in the quantity of water destabilising the river bed. Therefore, pollution from the CSOs, the WwTW and rapid changes in discharge are the reasons for the river's failure to conform to EU's requirements of the Water Framework Directive.