| Description |
Green Stormwater Infrastructure (GSWI) has emerged as the next-generation stormwater management solution for urban areas and can provide greater flexibility in treatment options, design type, and site locations compared to traditional stormwater management alternatives. While methodologies for simulating GSWI functionality at the individual site level are well established, the complexity of representing GSWI collectively throughout a watershed remains problematic. One reason is the lack of literature comparing methods that represent GSWI networks within urban watershed models. This research addresses this need by evaluating GSWI up-scaling methods and the associated impacts on estimated benefits from varying spatial distribution and subcatchment aggregation. The first component of this research focuses on GSWI up-scaling methods and the impacts to the hydrologic response estimates. Comparisons are drawn from two GSWI models built to meet performance criteria metrics, such as drawdown time and runoff capture volume. One model applies a GSWI design-specific up-scaling approach, while the other model represents the GSWI network as a nonspecific collective unit. Results from an assessment of the hydrologic response output between the models show comparable estimates within 5% for peak discharge, average flow rate, and volume. Therefore, representing GSWI as nonspecific collectives can comparably estimate watershed-scale benefits to those estimated using representations with design-specific details. The second component compares various GSWI spatial distribution and aggregation modeling scenarios and identifies the impacts of each on hydrologic response estimates. Spatial targeting of GSWI is compared to output from uniformly distributed GSWI in all subcatchments. Statistical assessments using t-test methods indicate that spatial targeting does not significantly impact estimates for volume, peak flow rate, or average flow rate estimates. Increasingly aggregated GSWI subcatchments had varied hydrologic response estimates of volume, peak flow rate, and average flow rate for urban areas, though not varied enough to be statistically significant for the Philadelphia model until the subcatchments were aggregated to a single subcatchment. However, the impact at the event level was obvious for peak discharge. Thus, for watershed areas with smaller subcatchment sizes, the greatest impact is to the peak flow rates. For SLC model scenarios, aggregating GSWI subcatchments significantly influenced all flow. |
