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{{:Land use event mean concentrations (emcs) for the MPCA Simple Estimator}} | {{:Land use event mean concentrations (emcs) for the MPCA Simple Estimator}} | ||
− | [[Estimator default Figure 1.png|300px|thumb|alt=figure default percent land use|<font size=3>Percent of total land use in specific land use categories for three groups. See text for description of groups.</font size>]] | + | [[file:Estimator default Figure 1.png|300px|thumb|alt=figure default percent land use|<font size=3>Percent of total land use in specific land use categories for three groups. See text for description of groups.</font size>]] |
We divided the selected cities into three groups, as described below. | We divided the selected cities into three groups, as described below. |
Default TSS and TP loads using the MPCA Simple Estimator
The objective of this analysis was to provide estimates of annual loads of total phosphorus (TP) and total suspended solids (TSS), in pounds per acre, from stormwater runoff in Minnesota cities. The results represent estimated loads with no implemented best management practices (BMPs).
We used the MPCA Simple Estimator (Estimator) to calculate average annual loading, in pounds per acre, for total phosphorus (TP) and total suspended solids (TSS). We used the default values in the Estimator for event mean concentration and runoff coefficient and assumed an annual average precipitation of 30.65 inches (Twin Cities Metro Area (TCMA)). These values are discussed in the Minnesota Stormwater Manual, as well as guidance for the MPCA Simple Estimator. Appropriate links include the following.
We gathered land use data for several TCMA cities using Metropolitan Council land use data. The land use categories for the Met Council data do not match those used in the Estimator, so we converted the Met Council data into land uses used in the Estimator. These are summarized in the following table. Because this is subjective, we include a column describing the relative significance of a specific land use to total acres in a city. For example, farmstead was assigned to agricultural land use. Farmsteads may not be associated with typical agricultural practices, but farmstead is a minor land use and therefore has a minor impact on overall pollutant loading.
Met Council and Manual land use categories
Link to this table
Met Council land use data | Land use assigned in the Simple Estimator | Relative contribution of land use to total acres in a city |
---|---|---|
Agriculture | Agriculture | Low to high |
Farmstead | Agriculture | Low |
Golf course | Golf course | Low |
Industrial and utility | Indutrial | Low to moderate |
Institutional | Institutional | Low to moderate |
Major highway | Transportation | Low to moderate |
Airport | Transportation | Low |
Railroad | Transportation | Low |
Mixed use commercial and other | Commercial | Low |
Mixed use industrial | Industrial | Low |
Mixed use residential | Residential | Low |
Multifamily | Residential | Low |
Office | Commercial | Low to moderate |
Open water | Water | Moderate |
Park, recreational, or preserve | Park | High |
Retail and other commercial | Commercial | Low to moderate |
Single family attached | Residential | Low |
Single family detached | Residential | High |
Undeveloped land | Open space | High |
Manufactured housing park | Residential | Low |
Retail and other commercial | Commercial | Low to moderate |
Extractive | Extractive | Low |
The Estimator does not have default emcs and runoff coefficients for golf courses and extractive land use. We conducted a brief literature review to determine values for these two land uses. Default values for Estimator inputs are summarized in the following table.
Land use event mean concentrations (emcs) for the MPCA Simple Estimator
Link to this table
Land use | Phosphorus emc (mg/L) | TSS emc | Annual precipitation (inches) | Runoff coefficient |
---|---|---|---|---|
Commercial | 0.20 | 75 | 30.65 | 0.71 |
Industrial | 0.235 | 93 | 30.65 | 0.68 |
Institutional | 0.25 | 80 | 30.65 | 0.3 |
Open space | 0.19 | 21 | 30.65 | 0.08 |
Residential | 0.325 | 73 | 30.65 | 0.27 |
Park | 0.19 | 21 | 30.65 | 0.08 |
Agriculture | 0.50 | 100 | 30.65 | 0.11 |
Transportation | 0.28 | 87 | 30.65 | 0.80 |
Water | 0 | 0 | 30.65 | 0 |
Extractive | 0.15 | 94 | 30.65 | 0.15 |
Golf course | 0.45 | 49 | 30.65 | 0.27 |
We divided the selected cities into three groups, as described below.
Using the land uses from the Estimator and Met Council, we entered percentages for each land use for each city and converted these to fractions. If the fractions did not add to 1.0, we adjusted the fractions so that the total equaled 1.0. Thus, the data represent land use across one (1) acre within a specific city. We calculated means, standard deviations, and associated coefficients of variation (CV). We selected a sufficient number of cities to ensure the CV was less than 1 for each land use. CVs exceeded tolerance limits for agriculture in Group 1 and extraction in Group 3. Since these land uses make up a very small percent of the total land use for these two groups, we assumed the high variability would not significantly affect the results. The distribution of land uses for the three groups is shown in the following figure. Residential land use decreases in importance from Groups 1 through 3, while open space and agriculture increase in importance. Commercial, industrial, institutional, and transportation decrease as a percent of total acreage from Groups 1 through 3, although these land uses each comprise a relatively small percent of total land use. Parkland is similar across the three groups, while water comprises a greater percent of land use in Group 3 compared to Groups 1 and 2.