The Effect of Land Use and Stormwater Control Measures in the ...

The Effect of Land Use and Stormwater Control Measures in the Jordan Lake Watershed Celia Jackson, Drew Hoag, Maddie Omeltchenko, Aditya Shetty, N Lahiri Agenda 1) Background of the problem 2) Hypotheses 3) Research methods

4) Results 5) Implications Background 1 Jordan Lake Insert image

Causes of Eutrophication Eutrophication has been linked to increased nutrient loading Increased urbanization and development Increased impervious surface cover (ISC) More effectively routes nutrients to waterways Decreases soil and vegetation nutrient sinks Attributes of development add to the problem Increased fertilizer use Erosion from construction

Pollution from industry Research Goals Gain insight on the impacts Test SNAP (Stormwater of land use and stormwater Nitrogen and Phosphorous)

control measures on v.4.0. nutrient loading. Hypotheses 2

H1 Nutrients will be lower in urban streams with SCMs integrated into their watersheds than those without SCMs for similar levels of impervious surface cover, canopy cover, road density, and parcel density. H2 When looking at geologically similar urban watersheds, there is a: Positive correlation between metrics of urban development

and nutrient loading Negative correlation between metrics of vegetation density and nutrient loading Methods 3 Site Selection Four stream sites chosen for urban gradient and use of SCMs

Watershed Area (ft ) % ISC Parcel Density % Area Paved Road TY 9154499

47.26% 2.729 10.20% TB 5342414

42.68% 2.313 6.99% BG 16256360 14.58%

0.910 4.38% MLK 1714763 24.45%

0.967 3.62% CS 14541597 13.38% 0.903

4.47% 2 Data Collection Synoptic sampling Collection period: October 6 November 13 NC Jordan Lake Nutrient Study continuous sampling NC JLNS

GIS Data Collection Methods ArcMAP 10.5 Watersheds delineated for all four sites Important variables calculated for each watershed: Watershed Areas

ISC paved roads, parking lots, driveways, rooftops, swimming pools Parcel Density and Average Area Canopy Cover Area - 30m resolution NLCD, Orthographic Imagery classification SNAP v.4.0 Methods Important Required Information includes land use metrics: Area: watershed, roof,

paved road, paved parking lot, paved driveway Custom land use of pervious (airport) and impervious (swimming pools) surfaces SNAP v.4.0 Methods SCM Only those designed to affect nitrogen, phosphorus or peak flow events

were chosen Tanbark and MLK (X # SCMs chosen from each) Catchment areas for and actual areas of each BMP were calculated in ArcMAP 10.5 Default settings for SCMs lacking information Results 4 Peak Flows

BG MLK TY Hydrographs Predictor Variables for Nitrate Load % ISC and % Canopy Cover- Multiple Linear Regression Estimate Std. Error t value Pr(>|t|) (Intercept)

1997.46 15.21 131.4 0.00485 ** X..ISC -3104.14 26.46 -117.3 0.00543 ** X..Canopy.Cover -2393.19 21.19

-112.9 0.00564 ** --Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 Residual standard error: 4.277 on 1 degrees of freedom Multiple R-squared: 0.9999, Adjusted R-squared: 0.9998 F-statistic: 7411 on 2 and 1 DF, p-value: 0.008213 Single Variable Models p-value

% ISC % Canopy 0.626 0.733 Single variable run with % Canopy as a predictor for % ISC p-value= 0.2060

Nutrient Concentration vs. Impervious Surface Cover Implications 5 Surface Cover Tanyard

Highest %ISC Highest nitrate concentration Burlage Lowest %ISC Lowest nitrate concentration Neither had any BMPs Potential Errors/Pitfalls

Limited sampling timeframe Few rainfall/storm events contributed to low flow rates Missing a hydrograph for Tanbark site Load calculations with generally low flow rates yielded a few anomalous values on one day with significantly higher flow rate Inability to extrapolate for annual range Low variety of sampling sites/ISC SNAP model associated with inaccuracies with less urban development

Further testing is needed SNAP: Stormwater Nitrogen and Phosphorus Expected error in SCM watershed calculations DEMs do not account for anthropogenic manipulation of landscape Lack of specifics in Tanbark BMPs Numbers for sites with less ISC significantly less reliable Acknowledgements

Sally Hoyt and Jamie Smedsmo: data provided on MLK at UNC Facility Services GIS data for BMPs NCDEQ Nonpoint Source Division: Jim Hawhee, Rich Gannon, Patrick Beggs Sources (n.d.). Background. Retrieved November 26, 2017, from http:// portal.ncdenr.org/web/jordanlake/background Brett, M. (2005). Non-Point Source Impacts on Stream Nutrient Concentrations Along A Forest to Urban Gradient. Environmental Management, 35(3). https://doi.org/10.1007/s00267-003-0311-z

(n.d.). Development of the Jordan Lake Nutrient Strategy. Retrieved November 26, 2017, from http ://www.jordanlake.org/c/document_library/get_file?uuid=b777ca95-0332-45d0-aaeffe28088293b9&groupId=235275 Duan, S., Kaushal, S., Groffman, P., Band, L., Belt, K. (2012). Phosphorus export across an urban to rural gradient in the Chesapeake Bay watershed. Journal of Geophysical Research, 117(G01025). Groffman, P. et al. (2004). Nitrogen Fluxes and Retention in Urban Watershed Ecosystems. Ecosystems, 7. Kaye, J. et al. (2006). A distinct urban biogeochemistry? Trends in Ecology and Evolution, 21(4). Law, N.L., Band, L. E., Grove, J. M., & Robarge, W. P. (2004). Nitrogen Input from Residential Lawn Care Practices in Suburban Watersheds in Baltimore County, MD. Journal of Environmental Planning and

Management, 47(5). NCDEQ. (2017). Stormwater Nitrogen and Phosphorous (SNAP) v4.0 Accounting Tool Users Manual. Retrieved November 2017, from http:// www.orangecountync.gov/departments/tax/download_gis_data.php. Shields, C. et al. (2008). Streamflow distribution of nonpoint source nitrogen export from urban-rural catchments in the Chesapeake Bay watershed. Water Resources Research, 44(W09416). (2009). Urban Stormwater Management in the United States. National Academies Press. Retrieved from http://nap.edu/12465