High resolution modeling for water quantity and quality, understanding the role of green infrastructure best management practices in ultra urban environments: connections, feedbacks and interactions

Abstract

Urbanization modifies the land surface and results in increases to stormwater runoff, decreases to infiltration and degraded water quality. Natural system approaches such as green infrastructure use best management practices (BMPs), to mitigate the changes to urban hydrology caused by urbanization. However, patterns of stormwater runoff from urban environments are complex, and it is unclear how efficiently green infrastructure will improve urban runoff. To assess the merits of BMPs in urban environments, hydrologic models are used. These models are used to study pre and post urban development hydrology, including green infrastructure. But many of these models are applied in urban environments with very little formal verification and/or bench marking. This presents challenges for communities to have confidence in implementing BMPs at larger scales. These challenges arise from issues of scale, heterogeneity of the land surface, and the capability of models to correctly account for these complexities. The objective of this dissertation was to assess the effectiveness of distributed green infrastructure best management practices (BMPs) on urban hydrology. Specifically, to evaluate the impacts to water quantity and water quality. This was explored through three studies that evaluated (1) the impacts distributed BMPs have on water quantity using a hyper-resolution model, (2) an inter-comparison between distributed and lumped parameter models to provide better understanding and confidence in the use of both to represent BMPs in urban environments, (3) incorporation of researched biofiltration media into distributed models and the impacts distributed BMPs have on water quality. Results from the first study (Chapter 2) revealed that a nonlinear relationship is seen between the percent of BMP placement and storm intensity. The results indicate that BMP efficiency varies with spatial location and that type and emplacement within the urban watershed may be more important than the total amount of BMPs. A model intercomparison between distributed and lumped parameter models was explored using a set of benchmark problems, and a new urban case (Chapter 3). The intercomparison revealed that the use of key model parameters from the distributed model could be incorporated into the lumped model to improve performance. Finally, evaluation of water quality was performed using a hyper-resolution distributed model based upon the previous analysis for water quantity and the intercomparison (Chapter 4). The analysis revealed that removal of contaminants from the water shed was greatly enhanced by the inclusion of distributed BMPs, but was correlated to the capability of the BMP to capture stormwater runoff. Although not all BMPs performed equally as the removal efficiency of the BMPs depended upon spatial location, and specified biofiltration media. Biochar/Sand-amended BMPs performed slightly greater than those filled with only biochar, but significantly greater than those filled with a sandy-loam. The main outcome of this thesis was the validation of the effectiveness of distributed BMPs in reducing the impacts to stormwater runoff caused by modifications to the land surface.