Modeling hydrology and water quality in Moore's Mill Creek using the Storm Water Management Model (SWMM)

Abstract

Urban development has long been known to be disruptive of the hydrological cycle and surface water quality. The change from natural vegetation to impervious materials tends to result in larger quantities of stormwater runoff because of lower surface infiltration, leading to flooding and stream bank erosion. Higher pollutant loads are also more likely and can lead to waterbody impairment for drinking water, recreation, and aquatic habitats. One of the most significant pollutants is sediment, which is especially common rapidly developing areas where construction site runoff is a greater issue. One such area is the Moore’s Mill Creek (MMC) watershed in Lee County, Alabama. Population growth in the cities of Auburn and Opelika over the past fifteen years has necessitated a reevaluation of the watershed management plan to address the persistent issue of sedimentation using best management practices (BMPs). Hydrological models are a valuable tool for assessing the effectiveness of BMPs by representing hydrologic and water quality behavior within a watershed. The Storm Water Management Model (SWMM) is one of the oldest and most popular of these models. Though it is ordinarily used for urban stormwater management, SWMM has hydrologic and water quality capabilities that allow it to be applied to a variety of watersheds. Stream flow data and water samples were collected across the northeast portion of the MMC watershed to calibrate hydrographs and total suspended solids pollutographs for several rain events. Sensitivity analyses were conducted to better understand the individual and combined effects of hydrologic and water quality parameters on model results. The results showed the significance of aquifer and surface storage representation to stream hydrograph accuracy and total outflow volume, as well as to pollutograph recession curves. Accounting for groundwater also improved modeled hydrograph recession curves compared to previous research in the watershed.