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.