An assessment of stream health within the Chesapeake Bay Basin can be made using the Stream Health and Runoff Potential (SHARP) model, which is based solely on the relationship between land cover and stream constituents: Total phosphorus (TP), total nitrogen (TN), and total suspended sediment (TSS). While not intended to compete with more complex models that utilize a range of specific input data, SHARP’s advantage is that it requires little input, is easily applied, and can show whether a stream or watershed is likely to be impacted (impaired). The model allows the user to define a watershed boundary on screen within which a stream health index (SHI), concentrations of TP, TN and TSS, percentages of five land cover types, a color-coded land cover snapshot, impervious surface area and fractional vegetation cover are output. The paper describes SHARP, its output and an overview of how it can be used.
References
[1]
S. D. Preston, R. A. Smith, G. E. Schwartz, R. R. Alexander and J. W. Brakebill, “Spatially Referenced Regression Modeling of Nutrient Loading in the Chesapeake Bay Watershed,” Proceedings of the First Federal Interagency Hydrologic Modeling Conference, April 1998, Las Vagas, Vol. 1, pp. 143-150.
[2]
D. A. Haith and L. L. Shoemaker, “Generalized watershed Loading Functions for Stream Flow Nutrients,” Water Resources Bulletin, Vol. 23, No. 3, 1987, pp. 471478.
[3]
B. M. Evans, D. W. Lehning, K. J. Corradini, G. W. Petersen, E. Nizeyimana, J. M. Hamlett, P. D. Robillard and R. L. Day, “A Comprehensive GIS-Based Modeling Approach for Predicting Nutrient Loads in Watersheds,” Journal of Spatial Hydrology, Vol. 2, No. 2, 2002, pp. 1-18. www.spatialhydrology.com
[4]
S. A. Sheeder and B. M. Evans, “Estimating Nutrient and Sediment Threshold Criteria for Biological Impairment in Pennsylvania Watersheds,” JAWRA Journal of the American Water Resources Association, Vol. 40, No. 4, 2004, pp. 881-888. Hdoi:10.1111/j.1752-1688.2004.tb01052.x
[5]
B. M. Evans, “Private Communication,” 2002.
[6]
Pennsylvania State University Spatial Data Access (PASDA), 2005. http://www.pasda.psu.edu
[7]
T. N. Carlson and D. A. J Ripley, “On the Relationship between NDVI, Fractional Vegetation Cover, and Leaf Area Index,” Remote Sensing of Environment, Vol. 62, No. 3, 1997, pp. 241-252.
Hdoi:10.1016/S0034-4257(97)00104-1
[8]
S. Prince, “Private Communication,” 2005.
[9]
H. Chang, “Spatial Variations of Nutrient Concentrations in Pennsylvania Watersheds,” Journal of the Korean Geographical Society, Vol. 27, 2002, pp. 535-550.
[10]
H. A. Panofsky and G. W. Brier, “Some Applications of Statistics to Meteorology,” Mineral Industries Extension Services, Penn State University, Pennsylvania, 1958.
[11]
USGS Report, “Yields and Trends of the Nutrients and Total Suspended Solids in Non-Tidal Areas of the Chesapeake Bay Basin, 1985 1995,” Water Resources Investigation Report 98-4192, US Geological Survey, US Department of the Interior, 1998.
[12]
J. W. Brakebill, S. D. Preston and S. Martucci, “Digital Data Used to Relate Nutrient Inputs to Water Quality in the Chesapeake Bay Watershed, Version 2.0,” 2001.
http://md.water.usgs.gov/publications/ofr-01-251/sparrow.htm
[13]
M. A. Roland and M. H. Stuckey, “Regression Equations for Estimating Flood Flows at Selected Recurrence Intervals for Ungaged Streams in Pennsylvania,” US Geological Survey Scientific Investigations Report 2008 5102, 2008, 57 p.
