1. The Effect of Land Use and Stormwater Control Measures in the Jordan Lake Watershed
Celia Jackson, Drew Hoag, Maddie Omeltchenko, Aditya Shetty, Naomi Lahiri

2. Agenda Background of the problem Hypotheses Research methods Results
Implications

3. Background 1

4. Jordan Lake Insert image

5. 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

6. Here is the JL watershed, it spans a large region with different land uses and municipalities. One of the biggest changes in the watershed in the last couple of decades has been the increase in urbanization.

7. Test SNAP (Stormwater Nitrogen and Phosphorous) v.4.0.
Research Goals
Gain insight on the impacts of land use and stormwater control measures on nutrient loading.
Test SNAP (Stormwater Nitrogen and Phosphorous) v.4.0.

8. Hypotheses 2

9. 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.

10. 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

11. Methods 3

12. Site Selection
Four stream sites chosen for urban gradient and use of SCMs
Watershed Area (ft2)
% ISC
Parcel Density
% Area Paved Road TY
47.26%
2.729
10.20% TB
42.68%
2.313
6.99% BG
14.58%
0.910
4.38%
MLK
24.45%
0.967
3.62% CS
13.38%
0.903
4.47%
Nested sites-Burlage and MLK

13. Mention that burlage - MLK is cole springs

14. Data Collection Synoptic sampling
Collection period: October 6 – November 13
NC Jordan Lake Nutrient Study continuous sampling
Synoptic sampling to create paired data, can be more easily tested for significance

15. Marsh McBirney for flow velocity, depth
YSI multisensor probe for specific conductivity (metric for contaminant loading)

16. NC JLNS HOBO water level at 3 sites, TB couldn’t have sensor
HOBO conductivity sensor at Burlage and Tanyard
S::can spectro:lyser at Burlage (Nitrate)

17. 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

18. 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
*Be more concise about snap
-don’t list off individual values, just give background

19. 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
Tanbark through the city of carboro and MLK through Sallie Hoyt at facility services

20. Results 4

21. Peak Flows BG
MLK TY
All BMPs at MLK are reducing storm flows

22. Hydrographs

23. Predictor Variables for Nitrate Load
% ISC and % Canopy Cover- Multiple Linear Regression
                               Estimate     Std. Error    t value     Pr(>|t|)   
(Intercept)                      15.21         131.4        **
X..ISC                           26.46                **
X..Canopy.Cover           21.19               **
---
Signif. codes:  0 ‘***’ ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 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:
Single Variable Models
% ISC
% Canopy
p-value
0.626
0.733
Single variable run with % Canopy as a predictor for % ISC
p-value=
Using nutrient load...more important for Jordan Lake Watershed overall

24. Nutrient Concentration vs. Impervious Surface Cover

25. Implications 5

26. Surface Cover Tanyard Burlage Neither had any BMPs Highest %ISC
Highest nitrate concentration
Burlage
Lowest %ISC
Lowest nitrate concentration
Neither had any BMPs
-ISC seems directly related to nitrate concentration
-lack of hydraulic conductivity on impervious surfaces allows for increased runoff into watershed
-No BMPs to counteract this

27. 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

28. 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

29. 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

30. Sources
(n.d.). Background. Retrieved November 26, 2017, from
Brett, M. (2005). Non-Point Source Impacts on Stream Nutrient Concentrations Along A Forest to Urban Gradient. Environmental Management, 35(3).
(n.d.). Development of the Jordan Lake Nutrient Strategy. Retrieved November 26, 2017, from fe b9&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 User’s Manual. Retrieved November 2017, from
Shields, C. et al. (2008). Streamflow distribution of non–point 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