Sensitivity of Stormwater Management Solutions to Spatial Scale

• Main Author: Barich, Jeffrey Michael
• Format: Others
• Published: DigitalCommons@CalPoly 2014
• Subjects: Uncertainty analysis; Watershed modeling; Spatial aggregation scale; Low Impact Development
• Online Access: https://digitalcommons.calpoly.edu/theses/1212; https://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=2288&context=theses

Urbanization has considerably altered natural hydrology of urban watersheds by increasing runoff volume, producing higher and faster peak flows, and reducing water quality. Efforts to minimize or avoid these impacts, for example by implementing low impact development (LID) practices, are gaining momentum. Designing effective and economical stormwater management practices at a watershed scale is challenging; LIDs are commonly designed at site scales, considering local hydrologic conditions (i.e., one LID at a time). A number of empirical studies have documented hydrologic and water quality improvements achieved by LIDs. However, watershed scale effectiveness of LIDs has not been well studied. Considering cost, effort, and practicality, computer modeling is the only viable approach to assess LID performance at a watershed scale. As such, the United States Environmental Protection Agency’s Stormwater Management Model (SWMM) was selected for this study. It is well recognized that model predictions are plagued by uncertainties that arise from the lack of quality data and inadequacy of the model to accurately simulate the watershed. To scrutinize sensitivity of prediction accuracies to spatial resolution, four SWMM models of different spatial detail were developed for the Ballona Creek watershed, a highly urbanized watershed in the Los Angeles Basin, as a case study. Detailed uncertainty analyses were carried out for each model to quantify their prediction uncertainties and to examine if a detailed model improves prediction accuracy. Results show that there is a limit to the prediction accuracy achieved by using detailed models. Three of the four models (i.e., all but the least detailed model) produced comparable prediction accuracy. This implies that devoting substantial resources on collecting very detailed data and building fine resolution watershed models may not be necessary, as models of moderate detail could suffice. If confirmed using other urban watersheds, this result could benefit stormwater managers and modelers. All four SWMM models were then used to evaluate hydrologic effectiveness of implementing bioretention cells at a watershed scale. Event based analyses, 1-year, 2-year, 5-year and 10-year storms of 24-hours were considered, as well as data from October 2005 to March 2010 for a continuous simulation. The runoff volume reductions achieved by implementing bioretention cells were not substantial for the event storms. For the continuous simulation analysis, however, about twenty percent reductions in runoff volume were predicted. These results are in-line with previous studies that have reported ineffectiveness of LIDs to reduce runoff volume and peak for less frequent but high intensity storm events.