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*[https://link.springer.com/article/10.1007/s12665-014-3682-y Contribution of surface runoff from forested areas to the chemistry of a through-flow lake]. Forested land use in Poland. | *[https://link.springer.com/article/10.1007/s12665-014-3682-y Contribution of surface runoff from forested areas to the chemistry of a through-flow lake]. Forested land use in Poland. | ||
*[https://www.sciencedirect.com/science/article/pii/S004313540100375X Brezonik and Stadelman], (2002). Analysis and predictive models of stormwater runoff volumes, loads, and pollutant concentrations from watersheds in the Twin Cities metropolitan area, Minnesota, USA. | *[https://www.sciencedirect.com/science/article/pii/S004313540100375X Brezonik and Stadelman], (2002). Analysis and predictive models of stormwater runoff volumes, loads, and pollutant concentrations from watersheds in the Twin Cities metropolitan area, Minnesota, USA. | ||
+ | |||
+ | In addition to the above sources, we compiled water quality monitoring data from 10 storm sewer outfalls in the [https://www.capitolregionwd.org/monitoring-research/ Capitol Region Watershed] in Minnesota. The data period for each outlet varied but generally spanned the period from about 2005 to 2019. The following information was compiled for each monitoring location. | ||
+ | *Date | ||
+ | *Total suspended solids in mg/L. | ||
+ | *Sample type, which included runoff samples during precipitation events, snowmelt samples, and <span title="Baseflow (also called drought flow, groundwater recession flow, low flow, low-water flow, low-water discharge and sustained or fair-weather runoff) is the portion of streamflow delayed shallow subsurface flow".> '''baseflow'''</span> samples for those locations where groundwater contributed to flow. | ||
+ | |||
+ | We also downloaded the [http://www.bmpdatabase.org/nsqd.html 2015 National Stormwater Quality Database]. The dataset includes information from across the U.S. We selected only data from Region 1, which includes Minnesota, for analysis. Four land uses included commercial, industrial, residential, and open space, with the number of samples for each land use varying. | ||
+ | |||
+ | For both of these data sets, we conducted simple statistical analyses. | ||
==Recommended event mean concentrations for total suspended solids== | ==Recommended event mean concentrations for total suspended solids== | ||
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===Commercial land use=== | ===Commercial land use=== | ||
+ | [[File:Commercial land use 1.jpg|300px|thumb|alt=image of commercial land use|<font size=3>Example of commercial land use</font size>]] | ||
+ | |||
"Commercial land use is the use of land for commercial purposes including building offices, shops, resorts and restaurants as opposed to construction of a residential house" ([https://www.reference.com/business-finance/commercial-land-use-d186d8d0a4ae4e72 Reference, accessed December 24, 2019)]. Commercial areas considered in this analysis do not include areas used for commercial crop production. | "Commercial land use is the use of land for commercial purposes including building offices, shops, resorts and restaurants as opposed to construction of a residential house" ([https://www.reference.com/business-finance/commercial-land-use-d186d8d0a4ae4e72 Reference, accessed December 24, 2019)]. Commercial areas considered in this analysis do not include areas used for commercial crop production. | ||
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===Industrial land use=== | ===Industrial land use=== | ||
+ | [[file:Industrial land use 1.jpg|300px|thumb|alt=imageindustrial area|<font size=3>Example of an industrial area</font size>]] | ||
+ | |||
We used the following studies in our analysis. | We used the following studies in our analysis. | ||
*NSWD; n=84; median=70 | *NSWD; n=84; median=70 | ||
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===Open space=== | ===Open space=== | ||
+ | [[File:Undeveloped land use 1.jpg|300px|thumb|alt=image of undeveloped land|<font size=3>Example of open space land use</font size>]] | ||
+ | |||
Open space consists of land that is undeveloped. Typically it will not contain buildings or other built structures. Many open spaces are accessible to the public. Open space generally consists of green space (land that is partly or completely covered with grass, trees, shrubs, or other vegetation). Abandoned parcels lacking structures may be considered open space, but it is generally more accurate to include these areas in the land use that existed prior to the parcel being vacant, or including it in adjacent land use categories. The following references were used to generate a recommended value a TSS emc for open space. | Open space consists of land that is undeveloped. Typically it will not contain buildings or other built structures. Many open spaces are accessible to the public. Open space generally consists of green space (land that is partly or completely covered with grass, trees, shrubs, or other vegetation). Abandoned parcels lacking structures may be considered open space, but it is generally more accurate to include these areas in the land use that existed prior to the parcel being vacant, or including it in adjacent land use categories. The following references were used to generate a recommended value a TSS emc for open space. | ||
*NSQD; n=6; median = 20.5 | *NSQD; n=6; median = 20.5 | ||
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===Transportation corridors, highways, and freeways=== | ===Transportation corridors, highways, and freeways=== | ||
+ | [[File:Transportation land use 1.jpg|300px|thumb|alt=imagetransportation area|<font size=3>Example of transportation land use</font size>]] | ||
+ | |||
This land use includes major transportation corridors where the land use is exclusively transportation. These areas are typically highly impervious and may include only small vegetated areas consisting of swales or medians, and relatively small right-of-way areas. This land use does not include arterial streets in residential, commercial, and industrial areas. The following references were used to generate a recommended value a TSS emc for open space. | This land use includes major transportation corridors where the land use is exclusively transportation. These areas are typically highly impervious and may include only small vegetated areas consisting of swales or medians, and relatively small right-of-way areas. This land use does not include arterial streets in residential, commercial, and industrial areas. The following references were used to generate a recommended value a TSS emc for open space. | ||
*China median=86.72 | *China median=86.72 | ||
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*'''Rainfall intensity and depth, including the maximum intensity and timing of this maximum'''. Most studies show emcs increase with rainfall intensity and depth during the initial period of runoff, but at some intensity emcs begin to decline due to dilution (Gong et al., 2016; Acharya and Piechota, 2010). Other studies show little or no effect of rain intensity (Schiff et al., 2016). During the latter part of a runoff event, TSS emcs and rain intensity are inversely related (Schiff et al., 2016). | *'''Rainfall intensity and depth, including the maximum intensity and timing of this maximum'''. Most studies show emcs increase with rainfall intensity and depth during the initial period of runoff, but at some intensity emcs begin to decline due to dilution (Gong et al., 2016; Acharya and Piechota, 2010). Other studies show little or no effect of rain intensity (Schiff et al., 2016). During the latter part of a runoff event, TSS emcs and rain intensity are inversely related (Schiff et al., 2016). | ||
*'''Interval between runoff events'''. As the number of days between runoff events increases, pollutants build up on impervious surfaces, resulting in greater TSS loading when runoff does occur. The effect on emcs is less certain and appears to vary with climate. This effect appears to be smaller in humid and sub-humid climates compared to arid and semi-arid climates (Gong et al., 2016; Acharya and Piechota, 2010; Li et. al, 2015). | *'''Interval between runoff events'''. As the number of days between runoff events increases, pollutants build up on impervious surfaces, resulting in greater TSS loading when runoff does occur. The effect on emcs is less certain and appears to vary with climate. This effect appears to be smaller in humid and sub-humid climates compared to arid and semi-arid climates (Gong et al., 2016; Acharya and Piechota, 2010; Li et. al, 2015). | ||
− | *'''Length of runoff event'''. Typically, pollutant concentrations decrease after an initial peak associated with <span title="the initial surface runoff of a rainstorm. During this phase, water pollution entering storm drains in areas with high proportions of impervious surfaces is typically more concentrated compared to the remainder of the storm"> '''first flush'''</span>. Studies suggest that, for runoff events lasting roughly 40 minutes or more, depending on intensity, TSS concentrations reach a relatively stable or slowly decreasing concentration that is 25-50% of the peak concentration (Li et. al, 2015; Schiff et al., 2016). | + | *'''Length of runoff event'''. Typically, pollutant concentrations decrease after an initial peak associated with <span title="the initial surface runoff of a rainstorm. During this phase, water pollution entering storm drains in areas with high proportions of impervious surfaces is typically more concentrated compared to the remainder of the storm"> '''first flush'''</span>. Studies suggest that, for runoff events lasting roughly 40 minutes or more, depending on intensity, TSS concentrations reach a relatively stable or slowly decreasing concentration that is 25-50% of the peak concentration (Li et. al, 2015; Schiff et al., 2016; Stenstrom and Kayhanian, 2005). |
*'''Nature of watershed contributing to runoff and impervious connectedness'''. This effect relates to the phenomenon of <span title="the initial surface runoff of a rainstorm. During this phase, water pollution entering storm drains in areas with high proportions of impervious surfaces is typically more concentrated compared to the remainder of the storm"> '''first flush'''</span> in which the greatest pollutant loading occurs in the early stages of runoff (Gong et al., 2016; Acharya and Piechota, 2010). | *'''Nature of watershed contributing to runoff and impervious connectedness'''. This effect relates to the phenomenon of <span title="the initial surface runoff of a rainstorm. During this phase, water pollution entering storm drains in areas with high proportions of impervious surfaces is typically more concentrated compared to the remainder of the storm"> '''first flush'''</span> in which the greatest pollutant loading occurs in the early stages of runoff (Gong et al., 2016; Acharya and Piechota, 2010). | ||
**First flush is more pronounced in smaller watersheds. | **First flush is more pronounced in smaller watersheds. | ||
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==Effect of emc on pollutant loading== | ==Effect of emc on pollutant loading== | ||
− | [[File:Emc sensitivity tss.png|400px|thumb|alt=graph showing TSS sensitivity to changes in emc|<font size=3>TSS loading for 3 different TSS emcs (30, 54.5, and 100 mg/L) | + | [[File:Emc sensitivity tss.png|400px|thumb|alt=graph showing TSS sensitivity to changes in emc|<font size=3>TSS loading, in pounds, for 3 different TSS emcs (30, 54.5, and 100 mg/L) and five land uses (1 acre of impervious with no pervious, and 1 acre of impervious with 1 acre of pervious turf on either HSG A, B, C, or D).</font size>]] |
− | To assess the effect of changing the TSS emc, we ran several scenarios using the [https://stormwater.pca.state.mn.us/index.php?title=MIDS_calculator Minimal Impact Design Standards Calculator]. For each model run we assumed | + | To assess the effect of changing the TSS emc, we ran several scenarios using the [https://stormwater.pca.state.mn.us/index.php?title=MIDS_calculator Minimal Impact Design Standards Calculator]. For each model run we assumed |
+ | 31.9 inches of precipitation annually. We varied the emc as follows | ||
*30 mg/L | *30 mg/L | ||
*54.5 mg/L (MIDS Calculator default) | *54.5 mg/L (MIDS Calculator default) | ||
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We varied land use as follows | We varied land use as follows | ||
*1 acre of impervious | *1 acre of impervious | ||
− | *1 acre of impervious and 1 acre of turf on hydrologic group soil (HSG)A soil | + | *1 acre of impervious and 1 acre of turf on hydrologic group soil (HSG) A soil |
*1 acre of impervious and 1 acre of turf on B soil | *1 acre of impervious and 1 acre of turf on B soil | ||
*1 acre of impervious and 1 acre of turf on C soil | *1 acre of impervious and 1 acre of turf on C soil | ||
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==Accounting for differences in pollutant loading== | ==Accounting for differences in pollutant loading== | ||
− | Pollutant loads are a function of pollutant concentrations in runoff and the volume of runoff. Consequently, when calculating pollutant loads it is necessary to adjust both the emcs and volume of runoff. Volumes are typically calculated using curve numbers or runoff coefficients. The MPCA Simple Estimator, for example, employs a default runoff coefficient of 0.8 for commercial areas, compared to 0.44 for residential areas. The tables below may be used to determine the proper curve number or runoff coefficient. Percent impervious can be converted to a curve number using the following formula. | + | Pollutant loads are a function of pollutant concentrations in runoff and the volume of runoff. Consequently, when calculating pollutant loads it is necessary to adjust both the emcs and volume of runoff. Volumes are typically calculated using <span title="The SCS curve number method is a widely used method for determining the approximate amount of runoff from a rainfall even in a particular area. The curve number is based on the area's hydrologic soil group, land use , treatment and hydrologic condition."> '''curve numbers'''</span> or <span title="The runoff coefficient (C) is a dimensionless coefficient relating the amount of runoff to the amount of precipitation received. It is a larger value for areas with low infiltration and high runoff (pavement, steep gradient), and lower for permeable, well vegetated areas (forest, flat land)."> [https://stormwater.pca.state.mn.us/index.php?title=Runoff_coefficients_for_5_to_10_year_storms '''runoff coefficients''']</span>. The [https://stormwater.pca.state.mn.us/index.php?title=Guidance_and_examples_for_using_the_MPCA_Estimator MPCA Simple Estimator], for example, employs a default runoff coefficient of 0.8 for commercial areas, compared to 0.44 for residential areas. The tables below may be used to determine the proper curve number or runoff coefficient. Percent impervious can be converted to a curve number using the following formula. |
<math> Curve number = (Impervious * 98) + ((1 - impervious) * (open space curve number in good condition for the specific soil)) </math> | <math> Curve number = (Impervious * 98) + ((1 - impervious) * (open space curve number in good condition for the specific soil)) </math> | ||
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*Hallberg, M., G. Renman. 2008. [http://www.pjoes.com/Suspended-Solids-Concentration-in-Highway-r-nRunoff-during-Summer-Conditions,88100,0,2.html Suspended Solids Concentration in Highway Runoff during Summer Conditions]. Pol. J. Environ. Stud. 17(2):237–241. | *Hallberg, M., G. Renman. 2008. [http://www.pjoes.com/Suspended-Solids-Concentration-in-Highway-r-nRunoff-during-Summer-Conditions,88100,0,2.html Suspended Solids Concentration in Highway Runoff during Summer Conditions]. Pol. J. Environ. Stud. 17(2):237–241. | ||
*Jung, Jae-Woon, Ha-Na Park, Kwang-Sik Yoon, Dong-Ho Choi, Byung-Jin Lim. 2013. [https://link.springer.com/article/10.1007/s13765-013-3128-3 Event mean concentrations (EMCs) and first flush characteristics of runoff from a public park in Korea]. Journal of the Korean Society for Applied Biological Chemistry. October 2013, Volume 56, Issue 5, pp 597–604. | *Jung, Jae-Woon, Ha-Na Park, Kwang-Sik Yoon, Dong-Ho Choi, Byung-Jin Lim. 2013. [https://link.springer.com/article/10.1007/s13765-013-3128-3 Event mean concentrations (EMCs) and first flush characteristics of runoff from a public park in Korea]. Journal of the Korean Society for Applied Biological Chemistry. October 2013, Volume 56, Issue 5, pp 597–604. | ||
+ | *Kieser and Associates. 2008. [http://kieser-associates.com/uploaded/pawpaw_urban_buildout_report_063008.pdf Urban and Build-out and Stormwater BMP Analysis in the Paw Paw River Watershed]. For the Southwest Michigan Planning Commission. 36 p. | ||
*Kim, Lee-Hyung. 2003. ''Determination of event mean concentrations and first flush criteria in urban runoff''. Environ. Eng. Res. 8:4:163-176. | *Kim, Lee-Hyung. 2003. ''Determination of event mean concentrations and first flush criteria in urban runoff''. Environ. Eng. Res. 8:4:163-176. | ||
*Li D, Wan J, Ma Y, Wang Y, Huang M, Chen Y. 2015. [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118776 Stormwater Runoff Pollutant Loading Distributions and Their Correlation with Rainfall and Catchment Characteristics in a Rapidly Industrialized City]. PLoS ONE 10(3): e0118776. doi:10.1371/journal.pone.0118776 | *Li D, Wan J, Ma Y, Wang Y, Huang M, Chen Y. 2015. [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118776 Stormwater Runoff Pollutant Loading Distributions and Their Correlation with Rainfall and Catchment Characteristics in a Rapidly Industrialized City]. PLoS ONE 10(3): e0118776. doi:10.1371/journal.pone.0118776 | ||
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*Schiff, Kenneth C., and Liesl L. Tiefenthaler. 2011. [https://onlinelibrary.wiley.com/doi/full/10.1111/j.1752-1688.2010.00497.x Seasonal flushing of pollutant concentrations and loads in urban stormwater]. Jour. Amer. Water Works Assoc. 47:1:136-143 | *Schiff, Kenneth C., and Liesl L. Tiefenthaler. 2011. [https://onlinelibrary.wiley.com/doi/full/10.1111/j.1752-1688.2010.00497.x Seasonal flushing of pollutant concentrations and loads in urban stormwater]. Jour. Amer. Water Works Assoc. 47:1:136-143 | ||
*Schiff, Kenneth C., and Liesl L. Tiefenthaler. 2016. [https://www.mdpi.com/2073-4441/8/8/320 Effects of Rainfall Intensity and Duration on the First Flush from Parking Lots]. Water. 8(8), 320. https://doi.org/10.3390/w8080320 | *Schiff, Kenneth C., and Liesl L. Tiefenthaler. 2016. [https://www.mdpi.com/2073-4441/8/8/320 Effects of Rainfall Intensity and Duration on the First Flush from Parking Lots]. Water. 8(8), 320. https://doi.org/10.3390/w8080320 | ||
+ | *Sharma, D., R. Gupta, R.K. Singh, and A. Kansal. 2012. [https://www.researchgate.net/publication/257799126_Characteristics_of_the_event_mean_concentration_EMCs_from_rainfall_runoff_on_mixed_agricultural_land_use_in_the_shoreline_zone_of_the_Yamuna_River_in_Delhi_India Characteristics of the event mean concentration (EMCs) from rainfall runoff on mixed agricultural land use in the shoreline zone of the Yamuna River in Delhi, India]. Applied Water Science. 2:55-62. | ||
*Smullen, James T., Amy L. Shallcross, Kelly A.Cave. 1999. [https://www.sciencedirect.com/science/article/abs/pii/S0273122399003121 Updating the U.S. Nationwide urban runoff quality data base]. Water Science and Technology. Volume 39, Issue 12, Pages 9-16. https://doi.org/10.1016/S0273-1223(99)00312-1. | *Smullen, James T., Amy L. Shallcross, Kelly A.Cave. 1999. [https://www.sciencedirect.com/science/article/abs/pii/S0273122399003121 Updating the U.S. Nationwide urban runoff quality data base]. Water Science and Technology. Volume 39, Issue 12, Pages 9-16. https://doi.org/10.1016/S0273-1223(99)00312-1. | ||
*Stein, Eric D., Liesl L. Tiefenthaler and Kenneth C. Schiff. 2008. [http://ftp.sccwrp.org/pub/download/DOCUMENTS/AnnualReports/2008AnnualReport/AR08_015_027.pdf Comparison of stormwater pollutant loading by land use type]. Southern California Coastal Water Research Project, AR08-015-027. | *Stein, Eric D., Liesl L. Tiefenthaler and Kenneth C. Schiff. 2008. [http://ftp.sccwrp.org/pub/download/DOCUMENTS/AnnualReports/2008AnnualReport/AR08_015_027.pdf Comparison of stormwater pollutant loading by land use type]. Southern California Coastal Water Research Project, AR08-015-027. | ||
*Stein, Eric D., Liesl L. Tiefenthaler and Kenneth C. Schiff. 2007. [http://ftp.sccwrp.org/pub/download/DOCUMENTS/TechnicalReports/510_pollutant_loading.pdf SOURCES, PATTERNS AND MECHANISMS OF STORM WATER POLLUTANT LOADING FROM WATERSHEDS AND LAND USES OF THE GREATER LOS ANGELES AREA, CALIFORNIA, USA]. Technical Report 510. | *Stein, Eric D., Liesl L. Tiefenthaler and Kenneth C. Schiff. 2007. [http://ftp.sccwrp.org/pub/download/DOCUMENTS/TechnicalReports/510_pollutant_loading.pdf SOURCES, PATTERNS AND MECHANISMS OF STORM WATER POLLUTANT LOADING FROM WATERSHEDS AND LAND USES OF THE GREATER LOS ANGELES AREA, CALIFORNIA, USA]. Technical Report 510. | ||
+ | *Stenstrom, M.K., and M. Kayhanian. 2005. [https://www.researchgate.net/publication/288208061_First_flush_phenomenon_characterization First Flush Phenomenon Characterization]. Prepared for: California Department of Transportation. 81 p. | ||
*U.S. Environmental Protection Agency. 1983. Results of the Nationwide Urban Runoff Program—Executive summary: U.S. Environmental Protection Agency, Water Planning Division, National Technical Information Service PB84–185545, 24 p. | *U.S. Environmental Protection Agency. 1983. Results of the Nationwide Urban Runoff Program—Executive summary: U.S. Environmental Protection Agency, Water Planning Division, National Technical Information Service PB84–185545, 24 p. | ||
*U.S. Environmental Protection Agency. 1983. [https://www3.epa.gov/npdes/pubs/sw_nurp_vol_1_finalreport.pdf Results of the Nationwide Urban Runoff Program: Volume I – Final Report]. National Technical Information Service Number PB84-185552. | *U.S. Environmental Protection Agency. 1983. [https://www3.epa.gov/npdes/pubs/sw_nurp_vol_1_finalreport.pdf Results of the Nationwide Urban Runoff Program: Volume I – Final Report]. National Technical Information Service Number PB84-185552. | ||
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*Washington District Department of the Environment. 2014. [http://dcstormwaterplan.org/wp-content/uploads/AppD_EMCs_FinalCBA_12222014.pdf Selection of Event Mean Concentrations (EMCs)]. | *Washington District Department of the Environment. 2014. [http://dcstormwaterplan.org/wp-content/uploads/AppD_EMCs_FinalCBA_12222014.pdf Selection of Event Mean Concentrations (EMCs)]. | ||
*Yang, Yun-Ya, and Gurpal S. Toor. 2018. [https://www.nature.com/articles/s41598-018-29857-x runoff driven phosphorus transport in an urban residential catchment: Implications for protecting water quality in urban watersheds]. Scientific Reports. 8:1-10 | *Yang, Yun-Ya, and Gurpal S. Toor. 2018. [https://www.nature.com/articles/s41598-018-29857-x runoff driven phosphorus transport in an urban residential catchment: Implications for protecting water quality in urban watersheds]. Scientific Reports. 8:1-10 | ||
+ | |||
+ | <noinclude> | ||
+ | [[category:pollutants]] | ||
+ | </noinclude> |
Land use | Recommended emc TSS (mg/L) |
Commercial | 75 |
Industrial | 93 |
Residential | 73 |
Freeways/transportation | 87 |
Mixed | 76 or calculate |
Open space | 21 |
Conventional roof | < 10 |
|
This page provides information on event mean concentrations of total suspended solids (TSS) in urban stormwater runoff. For a discussion of TSS in stormwater runoff, including information on sources, fate, and water quality impacts, see Total Suspended Solids (TSS) in stormwater.
Event mean concentrations (emcs) are used in models for predicting water quality impacts from stormwater runoff and stormwater treatment practices or pollution prevention practices. Pollutant loads, which are typically used to assess water quality impacts, including establishing total maximum daily loads (TMDLs), are a function of pollutant concentration and volume of runoff. It is therefore important to accurately determine appropriate event mean concentrations when assessing water quality impacts from stormwater runoff.
This page provides summary information that can be used for selecting or calculating appropriate emcs for total suspended solids.
We conducted a review of literature to develop the EMCs shown on this page. Nearly all studies provided summary information; we therefore did not analyze raw data with the exception of data from Capitol Region Watershed District (see discussion below) and the National Stormwater Quality Database. We compiled the summary information into a spreadsheet and conducted simple statistical analysis of the information.
Data from the following studies were used to generate emcs for total suspended solids.
In addition to the above sources, we compiled water quality monitoring data from 10 storm sewer outfalls in the Capitol Region Watershed in Minnesota. The data period for each outlet varied but generally spanned the period from about 2005 to 2019. The following information was compiled for each monitoring location.
We also downloaded the 2015 National Stormwater Quality Database. The dataset includes information from across the U.S. We selected only data from Region 1, which includes Minnesota, for analysis. Four land uses included commercial, industrial, residential, and open space, with the number of samples for each land use varying.
For both of these data sets, we conducted simple statistical analyses.
Emcs for TSS vary by land use. This section provides recommended emcs for different land uses. A discussion of factors affecting emcs and potential adjustments to emcs are provided in separate sections below.
Studies from the literature frequently provide concentrations for residential land use or occasionally for different types of residential land use, typically low-, medium-, or high-density residential. Most studies do not define criteria for dividing residential land use into these subcategories. Various definitions can be found in the literature, including the following.
Note that residential land uses can include other land uses, such as commercial and industrial. Many studies therefore classify land uses as mixed or urban, even though a specific land use may dominate a particular area.
Because of the variable and arbitrary manner in which residential land use is classified, we provide a single recommended value for event mean concentrations in residential land uses. We provide additional discussion below so that users can adjust this recommended value depending on local conditions. We used the following references for generating a recommended value for residential land use.
We chose these studies because they contained large amounts of data and they were located in humid and sub-humid areas of the U.S. The median of the above 7 values is 73 mg/L.
"Commercial land use is the use of land for commercial purposes including building offices, shops, resorts and restaurants as opposed to construction of a residential house" (Reference, accessed December 24, 2019). Commercial areas considered in this analysis do not include areas used for commercial crop production.
We used the following studies in our analysis. Commercial
The median concentration from these studies is 75 mg/L.
We used the following studies in our analysis.
The median TSS concentration from these studies is 93 mg/L. TSS concentrations do not appear to vary much across different industrial land uses, with the primary sources likely being road salt and atmospheric deposition. However, the following may contribute to higher TSS loads in industrial areas.
Open space consists of land that is undeveloped. Typically it will not contain buildings or other built structures. Many open spaces are accessible to the public. Open space generally consists of green space (land that is partly or completely covered with grass, trees, shrubs, or other vegetation). Abandoned parcels lacking structures may be considered open space, but it is generally more accurate to include these areas in the land use that existed prior to the parcel being vacant, or including it in adjacent land use categories. The following references were used to generate a recommended value a TSS emc for open space.
Parks and recreation areas are generally included in open space.
This land use includes major transportation corridors where the land use is exclusively transportation. These areas are typically highly impervious and may include only small vegetated areas consisting of swales or medians, and relatively small right-of-way areas. This land use does not include arterial streets in residential, commercial, and industrial areas. The following references were used to generate a recommended value a TSS emc for open space.
The median value from these studies is 87 mg/L.
TSS concentrations from transportation corridors are highly variable depending on inputs. The primary inputs include road salt, sediment, and vehicle-related wastes, including oil. The recommended value should be adjusted based on vehicle traffic and likely suspended solids sources and inputs.
Overall median = 76 mg/L
An emc can be calculated if the total area of interest (Atotal), the area of each land use in the area of interest, and the emc for each land use in the area of interest are known.
Site emc = Σ1n ((AArea 1 * emcArea 1)/ (Atotal) + ... ((AArea n * emcArea n) / (Atotal)
where A = area in acres.
Example calculation
Overall emc = (73 * 10/31) + (75 * 10/31) + (93 * 10/31) + (1 * 10/31) = 80.5 mg/L
NOTE: To calculate loads for a mixed land use, a curve number or runoff coefficient must be calculated based on the impervious surface for each of the land uses.
Event mean concentrations for total suspended solids.
Link to this table
Land cover/land use | Range (mg/L) | Recommended value (mg/L) | Notes |
---|---|---|---|
Commercial | 42-164 | 75 | If applicable to models being used, adjust curve numbers/runoff coefficients when calculating loads |
Industrial | 70-170 | 93 |
|
Residential | 42-101 | 73 | |
High-density/Multi-family residential | Calculate |
|
|
Medium density residential | Calculate |
|
|
Low density residential | Calculate |
|
|
Freeways/transportation | 50-90 | 87 | |
Mixed | 47-188 | 76 or calculate |
|
Parks and recreation | Use value for open space or calculate |
|
|
Open space | 11-70 | 21 | |
Conventional roof | <20 | ||
Institutional | 17-140 | 80 | |
Forest/shrub/grassland | 26-140 | 72 | Sediment concentrations from forested areas vary widely with factors such as slope and forest condition. Concentrations may be very high, but the annual volume of runoff is typically much less than non-forested areas. |
Open water and wetlands | see Notes (next column) |
|
|
Cropland (row crops) | 50-160 | Literature review was not adequate to recommend an emc | |
Pasture | 75-150 | 84 | Concentrations are a function of intensity of use. |
Concentrations of TSS show considerable variability within land uses. Using data from Region 1 of the National Stormwater Quality Database, mean concentrations are 50% greater than median concentrations for commercial, industrial, and residential land uses, indicating data are skewed toward higher concentrations. The mean for open space was only 7% greater than the median, indicating more uniform TSS concentrations.
Several factors affect concentrations of total suspended solids in stormwater runoff. The following bullet list summarizes some of the most important factors. Note these are general conclusions and not applicable to all local situations.
Several factors affect emcs, as discussed above. Emcs can and should be adjusted when supporting data exist. Local monitoring data should be used to support different emcs than those recommended on this page, but the following guidelines may be used to adjust emcs.
To assess the effect of changing the TSS emc, we ran several scenarios using the Minimal Impact Design Standards Calculator. For each model run we assumed 31.9 inches of precipitation annually. We varied the emc as follows
We varied land use as follows
The results, illustrated in the adjacent graph, indicate a small effect of soil. Changing the emc within a specific land use scenario, however, results in significant changes in loading. The change in loading is linear and equal to the following.
This exercise illustrates the importance of selecting an appropriate emc.
Pollutant loads are a function of pollutant concentrations in runoff and the volume of runoff. Consequently, when calculating pollutant loads it is necessary to adjust both the emcs and volume of runoff. Volumes are typically calculated using curve numbers or runoff coefficients. The MPCA Simple Estimator, for example, employs a default runoff coefficient of 0.8 for commercial areas, compared to 0.44 for residential areas. The tables below may be used to determine the proper curve number or runoff coefficient. Percent impervious can be converted to a curve number using the following formula.
\( Curve number = (Impervious * 98) + ((1 - impervious) * (open space curve number in good condition for the specific soil)) \)
where impervious is given as a fraction (not a percent).
For example, if an area on B soils is 50 percent impervious, the curve number is given as (0.5 * 98) + ((1 - 0.50)(61)) = 79.5.
Curve numbers for urban and agricultural areas. Source: [USDA Urban Hydrology for Small Watersheds - TR-55. USDA Urban Hydrology for Small Watersheds - TR-55].
Link to this table
Cover type and hydrologic condition | Soil Group A | Soil Group B | Soil Group C | Soil Group D |
---|---|---|---|---|
Open space poor condition (<50% cover) | 68 | 79 | 86 | 89 |
Open space average condition (50-75% cover) | 49 | 69 | 79 | 84 |
Open space good condition (>75% cover) | 39 | 61 | 74 | 80 |
Impervious surfaces | 98 | 98 | 98 | 98 |
Commercial (85% impervious) | 89 | 92 | 94 | 95 |
Industrial (72% impervious) | 81 | 88 | 91 | 93 |
Residential (65% impervious) | 77 | 85 | 90 | 92 |
Residential (30% impervious) | 57 | 72 | 81 | 86 |
Residential (12% impervious) | 46 | 65 | 77 | 82 |
Pervious, no vegetation (newly graded) | 77 | 86 | 91 | 94 |
Fallow with residue cover | 74-76 | 83-85 | 88-90 | 90-93 |
Row crop, no residue | 67-72 | 78-81 | 85-88 | 89-91 |
Row crop with residue | 64-71 | 75-80 | 82-87 | 85-90 |
Pasture, good condition | 39 | 61 | 74 | 80 |
Pasture, poor condition | 68 | 79 | 86 | 89 |
Meadow | 30 | 58 | 71 | 78 |
Woods, good condition | 32 | 58 | 72 | 79 |
Woods, poor condition | 57 | 73 | 82 | 86 |
Runoff coefficients for different soil groups and slopes. Coefficients are for recurrence intervals less than 25 years. Source: Hydrologic Analysis and Design (4th Edition) (McCuen, 2017).
Link to this table
Land use | Soil Group A | Soil Group B | Soil Group C | Soil Group D | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
0-2% | 2-6% | >6% | 0-2% | 2-6% | >6% | 0-2% | 2-6% | >6% | 0-2% | 2-6% | >6% | |
Residential (65% impervious) | 0.25 | 0.28 | 0.31 | 0.27 | 0.30 | 0.35 | 0.30 | 0.33 | 0.38 | 0.33 | 0.36 | 0.42 |
Residential (30% impervious) | 0.19 | 0.23 | 0.26 | 0.22 | 0.26 | 0.30 | 0.25 | 0.29 | 0.34 | 0.28 | 0.32 | 0.39 |
Residential (12% impervious) | 0.14 | 0.19 | 0.22 | 0.17 | 0.21 | 0.26 | 0.20 | 0.25 | 0.31 | 0.24 | 0.29 | 0.35 |
Commercial | 0.71 | 0.71 | 0.72 | 0.71 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 |
Industrial | 0.67 | 0.68 | 0.68 | 0.68 | 0.68 | 0.69 | 0.68 | 0.69 | 0.69 | 0.69 | 0.69 | 0.70 |
Streets | 0.70 | 0.71 | 0.72 | 0.71 | 0.72 | 0.74 | 0.72 | 0.73 | 0.76 | 0.73 | 0.75 | 0.78 |
Parking | 0.85 | 0.86 | 0.87 | 0.85 | 0.86 | 0.87 | 0.85 | 0.86 | 0.87 | 0.85 | 0.86 | 0.87 |
Open space | 0.05 | 0.10 | 0.14 | 0.08 | 0.13 | 0.19 | 0.12 | 0.17 | 0.24 | 0.16 | 0.21 | 0.28 |
Cultivated land | 0.08 | 0.13 | 0.16 | 0.11 | 0.15 | 0.21 | 0.14 | 0.19 | 0.26 | 0.18 | 0.23 | 0.31 |
Pasture | 0.12 | 0.20 | 0.30 | 0.18 | 0.28 | 0.37 | 0.24 | 0.34 | 0.44 | 0.30 | 0.40 | 0.50 |
Meadow | 0.10 | 0.16 | 0.25 | 0.14 | 0.22 | 0.30 | 0.20 | 0.28 | 0.36 | 0.24 | 0.30 | 0.40 |
Forest | 0.05 | 0.08 | 0.11 | 0.08 | 0.11 | 0.14 | 0.10 | 0.13 | 0.16 | 0.12 | 0.16 | 0.20 |
There are numerous studies summarizing TSS exports for different land uses. Examples include the following.
The studies illustrate the importance of estimating runoff volume, since loading from commercial areas, for example, is greater than from residential areas even though the emc for commercial areas is lower (0.20 mg/L compared to 0.325 mg/L for residential).
Example MIDS Calculator with and without adjusted emcs | ||||||
Land use | % impervious | Impervious acres | Pervious acres | emc (mg/L) | Total TSS load (lb/yr) | TSS export (lb/ac/yr) |
Residential (>40% canopy) | 30 | 0.90 | 2.1 | 80 | 663.8 | 221.3 |
Residential (<10% canopy) | 30 | 0.6 | 1.4 | 70 | 387.2 | 193.6 |
Commercial | 85 | 0.85 | 0.15 | 75 | 408.8 | 408.8 |
Industrial | 72 | 0.72 | 0.28 | 93 | 447.8 | 447.8 |
Open space | 10 | 0.10 | 0.90 | 21 | 37.6 | 37.6 |
Total suspended solids load with adjusted emcs = 1945.2 pounds/yr | ||||||
MIDS unadjusted | 39.6 | 3.17 | 4.83 | 54.5 | 1410.7 | 176.3 |
The following example illustrates how a variable land use setting may be modeled using the MIDS Calculator.
Site conditions.
EMCs are as follows.
Total load with the variable land uses (1945.2 pounds) is much greater than the default MIDS scenario (1410.7 pounds). This is primarily due to the higher emcs and partly due to the higher impervious acreages in the variable land use scenario. The effect of impervious acreage is shown, for example, by reducing the percent impervious for industrial land use from 72% to 50%. This results in a total load of 348 pounds, or a reduction of about 100 pounds (22.3% reduction for a 22% change in impervious). This example also demonstrates the importance of accurately identifying land use within a modeled area.