Effects of Catchment Modification on the Flow Frequency Curve Modeled Using the EPA-SWMM Model

Urbanization often produces detrimental impacts on receiving stream ecology due to an increased volume and velocity of storm runoff. The hydrologic effects of urbanization, including: increases in bankfull events, increased flooding, increased peak flows, decreased baseflow, stream enlargement, stream incision, severe stream bank erosion, sedimentation, changes in morphology, increased instream sediment load, increased sediment transport, aesthetic degradation, degradation of designated uses, and loss of fish populations. The purpose of this study is to determine how different physical characteristics of a watershed affect the peak discharges of runoff events produced by fifty years of continuously modeled precipitation. The Runoff and Statistical Blocks of the EPA Stormwater Management Model (SWMM4.4h) and rainfall from three climatically different cities were used to generate flow frequency curves that illustrate changes in subcatchment imperviousness, slope, runoff length, and Horton infiltration parameters. Historical rainfall hyetograph information for Fort Collins, Colorado; Atlanta, Georgia; and Seattle, Washington were used to determine the effects of different rainfall patterns in three subcatchments ranging from 6 to 10 Hectares. Results indicate urbanization has the greatest impact on the peak discharge of catchment runoff and caused all flow frequency curves in all three cities modeled to shift upward. While changes in slope, runoff length, and infiltration produced no alteration in runoff magnitude and frequency for some storms (seen through the convergence of the flow frequency curves), the impact of urbanization on the frequency and magnitude of runoff events was apparent in all scenarios run. As the level of urbanization changed, some response was always visible, no matter how the three other variables were altered. Introduction Increases in catchment urbanization create detrimental impacts to the receiving stream ecosystems through alterations in the river’s natural flow regime (Poff et al, 1997). Alterations to the five critical components of the natural flow regime—magnitude, frequency, duration, timing, and rate of change—through human impacts decrease native species’ variation and promote the propagation of non-native Copyright ASCE 2006 World Environmental and Water Resources Congress 2006 2 generalist species. Landuse change, especially urbanization, alters the magnitude and frequencies of high and low flows, causing physiological stress to species adapted to the altered natural conditions (Poff et al., 1997). The EPA-SWMM 4.4 model was used in this investigation to determine the general affects urbanization produces on the magnitude and frequency of discharge from three catchments with three regional patterns of rainfall. The Runoff and Statistics blocks of SWMM were used to determine the affects of catchment urbanization, slope, width, and soil composition on the peak discharge of watershed runoff. Fifty years of historical rainfall data from three cities – Atlanta, Fort Collins, and Seattle – were incorporated to account for climate variations; these data originated from the National Oceanic and Atmospheric Administration (NOAA) website. This was done to determine how alterations in the model catchment affect the runoff flow frequency curves. This is important because the flow frequency curves generated illustrate general trends of how different regions and physical characteristics of a watershed affect peak runoff discharge. It is also valuable because less money and effort can be directed toward obtaining data that does not significantly affect the output of the SWMM model. Methods The effects of catchment modifications on the resulting flow frequency curves were investigated using a single catchment and precipitation data from three different cities. The model catchment was composed of three subcatchments and subjected to recorded rainfall patterns from Atlanta, Georgia; Fort Collins, Colorado; and Seattle, Washington. The general process of this investigation included the following steps. (1) Select catchment parameters were changed in the Runoff input file and read into the Runoff Block of the EPA SWMM model. (2) The interface file output from the Runoff block was then input into the Statistics block of the model. (3) Data output from the Statistics block were used to calculate the return periods and peak discharges of all runoff events. (4) Runoff exceedances and flow frequency curves were produced for the catchment. (5) The flow frequency curves were then analyzed to determine what physical changes in the watershed produced what curve features. Model Catchment The model catchment used was composed of three subcatchments of 6.47, 5.67, and 9.96 Hectares. This catchment was modeled from an existing subwatershed located in the Fossil Creek watershed south of Fort Collins, Colorado. Currently, the land use in the area consists of 12.1 Hectares of low-density residential development and 10.1 Hectares of pasture land (Rohrer, 2004). An illustration of this catchment and its subcatchments appears in Figure 1. Although located in Fort Collins, Colorado, the catchment describe above was used in the Atlanta and Seattle simulations as well. The original areas of the model watershed, its Manning’s roughness, and depression storage were held constant throughout the study. The SWMM model allows two values each for Manning’s roughness and depression storage: one for the pervious areas and one for the impervious areas. The Manning’s value for the pervious areas in this model was 0.25 Copyright ASCE 2006 World Environmental and Water Resources Congress 2006 3 and the value for the impervious areas was 0.016. Values for depression storage were 7.62-mm for the pervious areas and 2.54-mm for the impervious. Channels, pipes and flood control devices were not considered in this study. Figure 1. Model Catchment Catchment Modifications Four types of catchment modifications were evaluated: imperviousness, slope, width, and infiltration. When one of these parameters was altered, the others were retained at their original values. The one exception to this was the percent imperviousness of the catchment. Catchment imperviousness was changed from the original values to 5%, 20%, and 40% to represent the effects of urbanization. These changes in imperviousness were applied to the slope, width, and infiltration scenarios. Modifications in catchment imperviousness were used to simulate urbanization of the watershed. Catchment imperviousness is also known as percent imperviousness and denoted as WW (3) in the SWMM 4.4 Runoff input file. Values of 10, 20, 30, 40, 50, 60, 70, 80, and 90 percent imperviousness were modeled and their affects demonstrated through flow frequency curves. The original percent imperviousness for the subcatchments 1101, 1201, and 1301 were 13.1, 14.0, and 5.0 respectively. Catchment slope is a measurement of the increase or decrease in ground elevation within the catchment. Slopes considered were 0.01, 0.04, 0.08, 0.12, 0.16, 0.20, 0.24, 0.28, and 0.32-m/m. When one of the other four parameters was altered the slopes of the subcatchments were retained at their original values of 0.015 for subcatchment 1101, 0.013 for subcatchment 1201, and 0.019 for subcatchment 1301. The width of the subcatchments refers to the length of the subcatchment side perpendicular to the direction of flow of the runoff (Figure 2). Figure 2. Subcatchment Width Copyright ASCE 2006 World Environmental and Water Resources Congress 2006 4 In SWMM all subcatchments are modeled as rectangles (Huber, 1998). Subcatchment areas were held constant during this part of the simulation and the results are documented based on a width to length ratio of the subcatchment. Width/length ratios considered for each subcatchment were 0.1, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, and 4. The widths entered into the SWMM model were determined from the equation below. This equation was derived from the area of a rectangle and the width to length ratio.