The values in this table come from the “Design and Construction of Urban Stormwater Management Systems” manual (ASCE, 1992). Figure 1: Depression Storage (Image Source)If you search “depression storage” through the PCSWMM online help, you will see a summary table of suggested values for the parameters. Dstore perv corresponds to the depth of depression storage over pervious surfaces. Dstore Imperv is the depth of depression storage over impervious surfaces, such as the parking lot shown below. PCSWMM has two parameters for depression storage: Dstore Imperv and Dstore Perv. The amount of water that accumulates on a surface before overland flow occurs is known as depression storage. As it rains over this parking lot, water fills in the pits and depressions before it flows into an adjacent, lower elevation area. For instance, take a look at the uneven surface depicted in Figure 1 below. Depression Storage: Real-world surfaces are not completely level they are filled with imperfections. You will be provided with suggestions from the literature on how to specify these values, enabling you to select an appropriate value based on your knowledge of the watershed area and how SWMM simulates the rainfall-runoff process. In this section, you will learn about a few of the SWMM model parameters that you will need to specify in your model. However, we often do not have enough data to determine the true value of these parameters, so we must rely on the infamous 'engineering judgment' to select appropriate values.

Therefore, the parameters values you choose should represent the true physical characteristics of your watershed if you would like your hydrograph to accurately portray the watershed response to a rainfall event.

The data you provide and the values of the parameters you specify will impact the magnitude and shape of your runoff hydrograph. Then the model will calculate the state variables, one of which is runoff (Q) and is of primary interest to design engineers. To run a hydrologic model in PCSWMM, you will need to provide the input data and specify values for the parameters. ContextIn the previous section, you were introduced to the SWMM model formulation and you were shown some examples of input variables, state variables and model parameters.

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