DOI: https://doi.org/10.15368/theses.2018.137
Available at: https://digitalcommons.calpoly.edu/theses/1977
Date of Award
12-2018
Degree Name
MS in Civil and Environmental Engineering
Department/Program
Civil and Environmental Engineering
Advisor
Misgana Kebede Muleta
Abstract
Developments that have been taking place on Cal Poly campus over the years have altered the natural hydrology of the area. Stormwater management practices could help reduce the impacts of these developments. Computer models can help to design effective and economical stormwater management solutions at a watershed scale. As such, the objective of this study was to develop a stormwater management model for Cal Poly campus. The model was developed based on the utility data obtained from the university and other watershed data available from open sources. Field surveys were conducted to address some anomalies in the utility data, and streamflow monitoring was performed. The model was calibrated using the streamflow data measured during this study. The calibration effort significantly improved the prediction accuracy of the model. The calibrated model was then used to analyze the hydrologic performance of implementing LID systems for two projects that Cal Poly plans to build. Permeable Pavements (PPs) and Bioretention Cells (BRCs) were the LID types examined. The LIDs were evaluated based on peak flow and runoff volume reductions they would achieve. The potential reductions were compared for current conditions and the proposed project if LIDs were implemented, and for inflows to the LIDs and outflows from the LIDs. The results indicate that implementing a PP system for the proposed student apartment at the current H-1 and R-1 parking lots and a BRC system for the proposed engineering project facilities at the current H-2 parking lots will significantly reduce peak flow and runoff volume. Overall, the developed model will help the university with the traditional stormwater management practices such as flood control and to identify effective LID practices for future developments. Limitations of the current model and recommendations on how to improve the model are also discussed.