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==References== | ==References== | ||
*Acharya, A., and T. Piechota. 2010. [https://www.researchgate.net/publication/267200251_Characterization_of_First_Flush_Phenomenon_in_an_Urban_Stormwater_Runoff_A_Case_Study_of_Flamingo_Tropicana_Watershed_in_Las_Vegas_Valley Characterization of First Flush Phenomenon in an Urban Stormwater Runoff: A Case Study of Flamingo Tropicana Watershed in Las Vegas Valley]. World Environmental and Water Resources Congress 2010: Challenges of Change. American Society of Civil Engineers. p 3365-3375. 10.1061/41114(371)347. | *Acharya, A., and T. Piechota. 2010. [https://www.researchgate.net/publication/267200251_Characterization_of_First_Flush_Phenomenon_in_an_Urban_Stormwater_Runoff_A_Case_Study_of_Flamingo_Tropicana_Watershed_in_Las_Vegas_Valley Characterization of First Flush Phenomenon in an Urban Stormwater Runoff: A Case Study of Flamingo Tropicana Watershed in Las Vegas Valley]. World Environmental and Water Resources Congress 2010: Challenges of Change. American Society of Civil Engineers. p 3365-3375. 10.1061/41114(371)347. | ||
+ | *Baldys III, S., T.H. Raines, B.L. Mansfield, and J.T. Sandlin. 1998. [https://www.semanticscholar.org/paper/Urban-stormwater-quality%2C-event-mean-and-estimates-Baldys-Raines/c8ffa3331750ead92c7ee74c2c46234fbe2572b9 Urban Stormwater Quality, Event-Mean Concentrations, and Estimates of Stormwater Pollutant Loads, Dallas-Fort Worth Area, Texas, 1992–93]. U.S. Geological Survey Water-Resources Investigations Report 98–4158. | ||
+ | *Bannerman, Roger T., Andrew D. Legg, and Steven R. Greb. 1996. [https://pdfs.semanticscholar.org/850e/ccf19feb2157c170ebdada940d30f9426711.pdf Quality Of Wisconsin Stormwater, 1989-94]. U.S. Geological Survey. Open-File Report 96-458. | ||
+ | *Bannerman, R.T., D. W.Owens,R. B.Dodds, and N. J. Hornewer. 1993. [https://www.fws.gov/southwest/es/Documents/R2ES/LitCited/4TX_Sal/Bannerman_1993_Pollutants_in_stormwater.pdf Sources of Pollution in Wisconsin Stormwater]. Wac Sci tech 28:3-5. pp. 241-259. | ||
+ | *Bartley, Rebecca, and William Speirs. 2010. [https://ewater.org.au/uploads/files/Water%20quality%20review_Bartley%20and%20Speirs_Final.pdf A review of sediment and nutrient concentration data from Australia for use in catchment water quality models]. eWater Cooperative Research Centre Technical Report. | ||
+ | *Brezonik PL, Stadelmann TH.. 2002. [https://www.esf.edu/EFB/mitchell/Brezonik&Stadelmann2002.pdf Analysis and predictive models of stormwater runoff volumes, loads, and pollutant concentrations from watersheds in the Twin Cities metropolitan area, Minnesota, USA]. Water Res. Apr;36(7):1743-57. DOI: 10.1016/s0043-1354(01)00375-x | ||
+ | *California Regional Water Quality Control Board. 2014. [https://www.waterboards.ca.gov/losangeles/water_issues/programs/stormwater/municipal/watershed_management/dominguez_channel/DominguezChannel_WP.pdf ENHANCED WATERSHED MANAGEMENT PROGRAM WORK PLAN FOR THE DOMINGUEZ CHANNEL WATERSHED MANAGEMENT AREA GROUP]. | ||
+ | *Capitol Region Watershed District. 2016. [https://issuu.com/capitolregionwd/docs/may_18__2016_board_packet_142422444f549a/256 May 18, 2016 Board Packet]. | ||
+ | *Erickson, A.J., P.T. Weiss, J.S. Gulliver, R.M. Hozalski. [http://stormwaterbook.safl.umn.edu/pollutant-removal/analysis-individual-storm-events Analysis of individual storm events, Stormwater Treatment: Assessment and Maintenance]. Accessed December 31, 2019. | ||
*Gong, Y., X. Liang, X. Li, J. Li, X. Fang, and R. Song. 2016. [https://www.mdpi.com/2073-4441/8/7/278/htm Influence of Rainfall Characteristics on Total Suspended Solids in Urban Runoff: A Case Study in Beijing, China]. Water 2016, 8(7), 278; https://doi.org/10.3390/w8070278 | *Gong, Y., X. Liang, X. Li, J. Li, X. Fang, and R. Song. 2016. [https://www.mdpi.com/2073-4441/8/7/278/htm Influence of Rainfall Characteristics on Total Suspended Solids in Urban Runoff: A Case Study in Beijing, China]. Water 2016, 8(7), 278; https://doi.org/10.3390/w8070278 | ||
+ | *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. | ||
+ | *Jae-Woon Jung, 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. | ||
+ | *Kim, Lee-Hyung. 2003. Determination of event mean concentrations and first flush criteria in urban runoff. Environ. Eng. Res. 8:4:163-176. | ||
+ | *Lee-Hyung Kim. 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 | ||
+ | *Maniquiz, Marla C. , Soyoung Lee, Lee-Hyung Kim. 2010. Multiple linear regression models of urban runoff pollutant load and event mean concentration considering rainfall variables. Jour Environ. Sci. 22:6:946-852. | ||
+ | *Maniquiz, Marla C., Jiyeon Choi, Soyoung Lee, Hye Jin Cho, Lee-Hyung Kim. 2010. [https://pdfs.semanticscholar.org/e24b/670b01617980cf9458bcf868c8feaebded74.pdf Appropriate Methods in Determining the Event Mean Concentration and Pollutant Removal Efficiency of a Best Management Practice]. 15:215-223. | ||
+ | *McKee, Paul W., and Harry C. McWreath. 2001. [https://pubs.usgs.gov/wri/wri01-4253/pdf/wri01-4253.pdf Computed and Estimated Pollutant Loads, West Fork Trinity River, Fort Worth, Texas, 1997]. U.S. GEOLOGICAL SURVEY Water-Resources Investigations Report 01–4253. | ||
+ | *Olson, Chris, Tyler Dell, and Jason Brim. 2017. Nutrient Sources in Urban Areas – A Literature Review. Prepared for the City of Fort Collins, Colorado. | ||
+ | *Rhee, Han-Pil, CG Yoon, S.J. Lee, and JH Choi. 2012. [https://www.researchgate.net/publication/263627021_Analysis_of_Nonpoint_Source_Pollution_Runoff_from_Urban_Land_Uses_in_South_Korea Analysis of Nonpoint Source Pollution Runoff from Urban Land Uses in South Korea]. Environmental Engineering Research 17(1):47-56. DOI: 10.4491/eer.2012.17.1.047. | ||
*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 | ||
+ | *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. 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. | ||
+ | *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. | ||
+ | *University of Wisconsin at Milwaukee. [https://www.mmsd.com/application/files/6214/8192/3796/1103620Phosphorus20Speciation.pdf Phosphorus Speciation and Loads in Stormwater and CSOs of the MMSD Service Area (2000 – 2008) Final Report]: February, 2011 | ||
+ | *Wang, Shumin, Qiang Hea, Hainan Aia, Zhentao Wanga, and Qianqian Zhang. 2013. [https://www.sciencedirect.com/science/article/pii/S1001074211610322 Pollutant concentrations and pollution loads in stormwater runoff from different land uses in Chongqing]. Journal of Environmental Sciences. Volume 25, Issue 3, Pages 502-510. https://doi.org/10.1016/S1001-0742(11)61032-2. | ||
+ | *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 | ||
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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 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 concentration (EMCs) are used in several models for predicting water quality impacts from stormwater runoff and stormwater treatment practices. This page provides summary information that can be used for selecting appropriate EMCs. For a discussion of event mean concentrations, see Stormwater pollutant concentrations and event mean concentrations. For a discussion of event mean concentrations, see Stormwater pollutant concentrations and event mean concentrations.
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). 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.
The following table summarizes results from our literature review. The table includes a range of values observed in the literature. Note this range does not represent a statistically-derived range but instead is based on a combination of data analysis and best professional judgement. For example, we did analyze the data for outliers, but also omitted entire studies if we felt the data were not representative of conditions likely to be encountered in Minnesota. To see the full range of values compiled from the literature, open the Excel spreadsheet containing the data.
Studies from the literature frequently provide concentrations for residential land use or occasionally for different types of 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. We use the following definitions.
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 = (( * 10)/31) + ((10 * )/31) + ((10 * )/31) + ((1 * )/31) = 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. Mean concentrations for Region 1 of the National Stormwater Quality Database are 50% greater than median concentrations for commercial, industrial, and residential land uses, indicating data are skewed 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 the 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.