Most large watersheds and river basins contain areas of urban land use. Estimates of the quantity and quality of runoff in urban areas are required for comprehensive management analysis. SWAT+ calculates runoff from urban areas with the SCS curve number method or the Green & Ampt equation. Loadings of sediment and nutrients are determined using one of two options. The first is a set of linear regression equations developed by the USGS (Driver and Tasker, 1988) for estimating storm runoff volumes and constituent loads. The other option is to simulate the buildup and washoff mechanisms, similar to SWMM - Storm Water Management Model (Huber and Dickinson, 1988).

In an impervious area, dust, dirt and other constituents are built up on street surfaces in periods of dry weather preceding a storm. Build up may be a function of time, traffic flow, dry fallout and street sweeping. During a storm runoff event, the material is then washed off into the drainage system. Although the build up/wash off option is conceptually appealing, the reliability and credibility of the simulation may be difficult to establish without local data for calibration and validation (Huber and Dickinson, 1988).

When the build up/wash off option is used in SWAT+, the urban hydrologic response unit (HRU) is divided into pervious and impervious areas. Management operations other than sweep operations are performed in the pervious portion of the HRU. Sweep operations impact build up of solids in the impervious portion of the HRU. For the pervious portion of the HRU, sediment and nutrient loadings are calculated using the methodology summarized in Chapters 4:1 and 4:2. The impervious portion of the HRU uses the build up/wash off algorithm to determine sediment and nutrient loadings.

The build up/wash off algorithm calculates the build up and wash off of solids. The solids are assumed to possess a constant concentration of organic and mineral nitrogen and phosphorus where the concentrations are a function of the urban land type.

Build up of solids is simulated on dry days with a Michaelis-Menton equation:

$SED=\frac{SED_{mx}*td}{(t_{half}+td)}$ 6:3.4.1

where $SED$ is the solid build up (kg/curb km) $td$ days after the last occurrence of $SED=0$ kg/curb km, $SED_{mx}$ is the maximum accumulation of solids possible for the urban land type (kg/curb km), and $t_{half}$ is the length of time needed for solid build up to increase from 0 kg/curb km to $\frac{1}{2} SED_{mx}$(days). A dry day is defined as a day with surface runoff less than 0.1 mm. An example build-up curve is shown in Figure 6:3-1. As can be seen from the plot, the Michaelis-Menton function will initially rise steeply and then approach the asymptote slowly.

Wash off is the process of erosion or solution of constituents from an impervious surface during a runoff event. An exponential relationship is used to simulate the wash off process (Huber and Dickinson, 1988):

To convert the sediment loading from units of kg/curb km to kg/ha, the amount of sediment removed by wash off is multiplied by the curb length density. The curb length density is a function of the urban land type. Nitrogen and phosphorus loadings from the impervious portion of the urban land area are calculated by multiplying the concentration of nutrient by the sediment loading.

In urban areas, surface runoff is calculated separately for the directly connected impervious area and the disconnected impervious/pervious area. For directly connected impervious areas, a curve number of 98 is always used. For disconnected impervious/pervious areas, a composite curve number is calculated and used in the surface runoff calculations. The equations used to calculate the composite curve number for disconnected impervious/pervious areas are (Soil Conservation Service Engineering Division, 1986):

$CN_c=CN_p+imp_{tot}*(CN_{imp}-CN_p)*(1-\frac{imp_{dcon}}{2*imp_{tot}})$ if $imp_{tot}<0.30$ 6:3.2.1

$CN_c=CN_p+imp_{tot}*(CN_{imp}-CN_p)$ if $imp_{tot}>0.30$ 6:3.2.2

where $CN_c$ is the composite moisture condition II curve number, $CN_p$ is the pervious moisture condition II curve number, $CN_{imp}$ is the impervious moisture condition II curve number, $imp_{tot}$ is the fraction of the HRU area that is impervious (both directly connected and disconnected), and $imp_{dcon}$ is the fraction of the HRU area that is impervious but not hydraulically connected to the drainage system.

The fraction of the HRU area that is impervious but not hydraulically connected to the drainage system, $imp_{dcon}$, is calculated

$imp_{dcon}=imp_{tot}-imp_{con}$ 6:3.2.3

where $imp_{tot}$ is the fraction of the HRU area that is impervious (both directly connected and disconnected), and $imp_{con}$ is the fraction of the HRU area that is impervious and hydraulically connected to the drainage system.

Table 6:3-2: SWAT+ input variables that pertain to surface runoff calculations in urban areas.

Urban areas differ from rural areas in the fraction of total area that is impervious. Construction of buildings, parking lots and paved roads increases the impervious cover in a watershed and reduces infiltration. With development, the spatial flow pattern of water is altered and the hydraulic efficiency of flow is increased through artificial channels, curbing, and storm drainage and collection systems. The net effect of these changes is an increase in the volume and velocity of runoff and larger peak flood discharges.

Impervious areas can be differentiated into two groups: the area that is hydraulically connected to the drainage system and the area that is not directly connected. As an example, assume there is a house surrounded by a yard where runoff from the roof flows into the yard and is able to infiltrate into the soil. The rooftop is impervious but it is not hydraulically connected to the drainage system. In contrast, a parking lot whose runoff enters a storm water drain is hydraulically connected. Table 6:3-1 lists typical values for impervious and directly connected impervious fractions in different urban land types.

During dry periods, dust, dirt and other pollutants build up on the impervious areas. When precipitation events occur and runoff from the impervious areas is generated, the runoff will carry the pollutants as it moves through the drainage system and enters the channel network of the watershed.

The linear regression models incorporated into SWAT+ are those described by Driver and Tasker (1988). The regression models were developed from a national urban water quality database that related storm runoff loads to urban physical, land use, and climatic characteristics. USGS developed these equations to predict loadings in ungaged urban watersheds.

The regression models calculate loadings as a function of total storm rainfall, drainage area and impervious area. The general equation is

$Y=\frac{\beta_0*(R_{day}/25.4)^{\beta_1}*(DA*imp_{tot}/2.59)^{\beta_2}*(imp_{tot}*100+1)^{\beta_3}*\beta_4}{2.205}$ 6:3.3.1

where $Y$ is the total constituent load (kg), $R_{day}$ is precipitation on a given day (mm H$_2$O), $DA$ is the HRU drainage area (km$^2$), $imp_{tot}$ is the fraction of the total area that is impervious, and the $\beta$ variables are regression coefficients. The regression equations were developed in English units, so conversion factors were incorporated to adapt the equations to metric units: 25.4 mm/inch, 2.59 km2/mi2, and 2.205 lb/kg.

USGS derived three different sets of regression coefficients that are based on annual precipitation. Category I coefficients are used in watersheds with less than 508 mm of annual precipitation. Category II coefficients are used in watersheds with annual precipitation between 508 and 1016 mm. Category III coefficients are used in watersheds with annual precipitation greater than 1016 mm. SWAT+ determines the annual precipitation category for each subbasin by summing the monthly precipitation totals provided in the weather generator input file.

Regression coefficients were derived to estimate suspended solid load, total nitrogen load, total phosphorus load and carbonaceous oxygen demand (COD). SWAT+ calculates suspended solid, total nitrogen, and total phosphorus loadings (the carbonaceous oxygen demand is not currently calculated). Regression coefficients for these constituents are listed in Table 6:3-3.

Once total nitrogen and phosphorus loads are calculated, they are partitioned into organic and mineral forms using the following relationships from Northern Virginia Planning District Commission (1979). Total nitrogen loads consist of 70 percent organic nitrogen and 30 percent mineral (nitrate). Total phosphorus loads are divided into 75 percent organic phosphorus and 25 percent orthophosphate.

Table 6:3-4: SWAT+ input variables that pertain to urban modeling with regression equations.

Street cleaning is performed in urban areas to control buildup of solids and trash. While it has long been thought that street cleaning has a beneficial effect on the quality of urban runoff, studies by EPA have found that street sweeping has little impact on runoff quality unless it is performed every day (U.S. Environmental Protection Agency, 1983).

SWAT+ performs street sweeping operations only when the build up/wash off algorithm is specified for urban loading calculations. Street sweeping is performed only on dry days, where a dry day is defined as a day with less than 0.1 mm of surface runoff. The sweeping removal equation (Huber and Dickinson, 1988) is:

$SED=SED_0*(1-fr_{av}*reff)$ 6:3.4.4

where $SED$ is amount of solids remaining after sweeping (kg/curb km), $SED_0$ is the amount of solids present prior to sweeping (kg/curb km), $fr_{av}$ is the fraction of the curb length available for sweeping (the availability factor), and $reff$ is the removal efficiency of the sweeping equipment. The availability factor and removal efficiency are specified by the user.

The availability factor, $fr_{av}$, is the fraction of the curb length that is sweepable. The entire curb length is often not available for sweeping due to the presence of cars and other obstacles.

The removal efficiency of street sweeping is a function of the type of sweeper, whether flushing is a part of the street cleaning process, the quantity of total solids, the frequency of rainfall events and the constituents considered. Removal efficiency can vary depending on the constituent being considered, with efficiencies being greater for particulate constituents. The removal efficiencies for nitrogen and phosphorus are typically less than the solid removal efficiency (Pitt, 1979). Because SWAT+ assumes a set concentration of nutrient constituents in the solids, the same removal efficiency is in effect used for all constituents. Table 6:3-5 provides removal efficiencies for various street cleaning programs.

Table 6:3-6: SWAT+ input variables that pertain to build up/wash off.