SWAT vs. RUSLE: Which better predicts benthic habitat condition?

References

1. ↵
   1. Abrahart, R.J., and
   2. S.M. White

   . 2001. Modeling sediment transfer in Malawi: Comparing back propagation neural network solutions against a multiple linear regression benchmark using small datasets. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans, and Atmosphere 26(1):19-24, doi:10.1016/S1464-1909(01)85008-5.

   OpenUrlCrossRefGeoRef
2. ↵
   1. Arnold, J.G.,
   2. D.N. Moriasi,
   3. P.W. Gassman,
   4. K.C. Abbaspour,
   5. M.J. White,
   6. R. Srinivasan,
   7. C. Santhi,
   8. R.D. Harmel,
   9. A. van Griensven,
   10. M.W. Van Liew,
   11. N. Kannan, and
   12. M.K. Jha

   . 2012. SWAT: Model use, calibration, and validation. Transactions of the ASABE 55(4):1491-1508.

   OpenUrl
3. ↵
   1. Bilotta, G., and
   2. R. Brazier

   . 2008. Understanding the influence of suspended solids on water quality and aquatic biota. Water Research 42:2849-2861.

   OpenUrlCrossRefPubMed
4. ↵
   1. Braccia, A., and
   2. J.R. Voshell Jr..

   2006. Benthic macroinvertebrate fauna in small streams used by cattle in the Blue Ridge Mountains, Virginia. Northeastern Naturalist 13(2):269-286, http://dx.doi.org/10.1656/1092-6194(2006)13[269:BMFISS]2.0.CO;2.

   OpenUrl
5. ↵
   1. Brady, N., and
   2. R. Weil

   . 2008. The Nature and Properties of Soils, 14th edition. Columbus, OH: Pearson.
6. ↵
   1. Collins, A.L.,
   2. P.S. Naden,
   3. D.A. Sear,
   4. J.I. Jones,
   5. I.D. Foster, and
   6. K. Morrow

   . 2011. Sediment targets for informing river catchment management: International experience and prospects. Hydrological Processes 25(13). https://doi.org/10.1002/hyp.7965.
7. ↵
   1. ESRI (Environmental Systems Research Institute)

   . 2012. ArcGIS Desktop: Release 10.2. Redlands, CA: Environmental Systems Research Institute.
8. ↵
   1. Griensven, A.V.,
   2. S. Maharjan, and
   3. T. Alemayehu

   . 2014. Improved simulation of evapotranspiration for land use and climate change impact analysis at catchment scale. Proceedings of the International Congress on Environmental Modelling and Software conference, June 15-19, 2014, San Diego, CA.
9. ↵
   1. Hair, J.F.,
   2. W.C. Black,
   3. B.J. Babin, and
   4. R.E. Anderson

   . 1995. Multivariate Data Analysis, 7th edition. New York: Macmillan.
10. ↵
    1. Holl, K.D., and
    2. R.B. Howarth

    . 2001. Paying for restoration. Restoration Ecology 8(3) https://doi.org/10.1046/j.1526-100x.2000.80037.x.
11. ↵
    1. Holmes, T.P.,
    2. J.C. Bergstrom,
    3. E. Huszar,
    4. S.B. Kask, and
    5. F. Orr III.

    2004. Contingent valuation, net marginal benefits, and the scale of riparian ecosystem restoration. Ecological Economics 49(1):19-30.

    OpenUrlCrossRefWeb of Science
12. ↵
    1. Homer, C.G.,
    2. J.A. Dewitz,
    3. L. Yang,
    4. S. Jin,
    5. P. Danielson,
    6. G. Xian,
    7. J. Coulston,
    8. N.D. Herold,
    9. J.D. Wickham, and
    10. K. Megown

    . 2015. Completion of the 2011 National Land Cover Database for the conterminous United States-representing a decade of land cover change information. Photogrammetric Engineering & Remote Sensing 81(5):345-354.

    OpenUrl
13. ↵
    1. Independent Petroleum Association of America

    . 2004. Guidance document: Reasonable and prudent practices for stabilization (RAPPS) of oil and gas construction sites (Appendix A) (Tech.). Washington, DC: Independent Petroleum Association of America.
14. ↵
    1. Jabbar, M.

    2003. Application of GIS to estimate soil erosion using RUSLE. Geospatial Information Science 6(1):34-37.

    OpenUrl
15. ↵
    1. Jack, K.,
    2. B. Leimona, and
    3. P. Ferraro

    . 2008. A revealed preference approach to estimating supply curves for ecosystem services: Use of auctions to set payments for soil erosion control in Indonesia. Conservation Biology 23(2):359-367.

    OpenUrl
16. ↵
    1. Jenkins, R., and
    2. N. Burkhead

    . 1994. Freshwater fishes of Virginia. Bethesda, MD: American Fisheries Society.
17. ↵
    1. Kalcic, M.,
    2. I. Chaubey, and
    3. J. Frankenberger

    . 2015. Defining Soil and Water Assessment Tool (SWAT) hydrologic response units (HRUs) by field boundaries. International Journal for Agricultural and Biological Engineering 8(3): 69-79, doi:10.3965/j.ijabe.20150803.951.

    OpenUrlCrossRef
18. ↵
    1. Kinnell, P.I.

    2000. The effect of slope length on sediment concentrations associated with side-slope erosion. Soil Science Society of America Journal 64(3):1004-1008, doi:10.2136/sssaj2000.6431004x.

    OpenUrlCrossRefWeb of Science
19. ↵
    1. Donald F. Hayes

    1. Langendoen, E.J.,
    2. A. Simon, and
    3. R.E. Thomas

    . 2001. CONCEPTS: A process-based modeling tool to evaluate stream-corridor restoration designs, ed. Donald F. Hayes. Paper presented at the 2001 Wetlands Engineering & River Restoration Conference. Reston, VA: American Society of Civil Engineers.
20. ↵
    1. Lim, K.,
    2. M. Sagong,
    3. B. Engel,
    4. Z. Tang,
    5. J. Choi, and
    6. K. Kim

    . 2005. GIS-based sediment assessment tool. CATENA 64:61-80.

    OpenUrlGeoRef
21. 1. Louis Berger Group Inc.

    2006. Benthic TMDL development for the Roanoke River, Virginia. Washington, DC: The Louis Berger Group Inc.
22. ↵
    1. Mayer, P.M.,
    2. S.K. Reynolds,
    3. M.D. McCutchen, and
    4. T.J. Canfield

    . 2007. Meta-analysis of nitrogen removal in riparian buffers. Journal of Environmental Quality 36(4):1172-1180.

    OpenUrlCrossRefPubMedWeb of Science
23. ↵
    1. Moriasi, D.N.,
    2. J.G. Arnold,
    3. M.W. Van Liew,
    4. R.L. Bingner,
    5. R.D. Harmel, and
    6. T.L. Veith

    . 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE 50(3):885-900.

    OpenUrlCrossRefWeb of Science
24. ↵
    1. NOAA NCDC (National Oceanic and Atmospheric Administration National Climate Data Center)

    . 2016. Daily weather records. Washington, DC: National Oceanic and Atmospheric Administration. https://www.ncdc.noaa.gov/cdo-web/datatools/records.
25. ↵
    1. Novotny, N.

    2003. Water Quality: Diffuse Pollution and Watershed Management. Boston, MA: Wiley.
26. ↵
    1. O’Driscoll, M.A., and
    2. D.R. DeWalle

    . 2006. Stream-air temperature relations to classify stream-groundwater interactions in a karst setting, central Pennsylvania, USA. Journal of Hydrology 329(1-2):140-153, doi:10.1016/j.jhydrol.2006.02.010.

    OpenUrlCrossRefGeoRefWeb of Science
27. ↵
    1. Perry, L.G.,
    2. L.V. Reynolds,
    3. T.J. Beechie,
    4. M.J. Collins, and
    5. P.B. Shafroth

    . 2015. Incorporating climate change projections into riparian restoration planning and design. Ecohydroloy 8(5):863-879.

    OpenUrl
28. ↵
    1. PRISM Climate Group

    . 2014-2015. PRISM datasets for US Monthly Precipitation 2014-15. Corvallis, OR: Oregon State University. http://prism.oregonstate.edu/recent/.
29. ↵
    1. Renard, K.,
    2. G. Foster,
    3. G. Weesies,
    4. D. McCool, and
    5. D. Yoder

    . 1997. Predicting soil erosion by water: A guide to conservation planning with the revised universal soil loss equation (RUSLE). Agriculture Handbook 703. Washington, DC: USDA Agricultural Research Service.
30. ↵
    1. Rosenberger, A., and
    2. P. Angermeier

    . 2003. Ontogenetic shifts in habitat use by the endangered Roanoke logperch (Percina rex). Freshwater Biology 48(9):1563-1577.

    OpenUrl
31. ↵
    1. Scott, L.

    2016. Assessing Statistical Instream Sediment Models as an Approach to Prioritize Riparian Restoration in Two Virginia River Basins. Master’s thesis, Plymouth State University. https://digitalcommons.plymouth.edu/etd/111.
32. ↵
    1. Scott, L.,
    2. A. Villamagna, and
    3. P. Angermeier

    . 2018. A new modeling approach to prioritize riparian restoration to reduce sediment loading in two Virginia river basins. Environmental Management 62(4):721-739, https://doi.org/10.1007/s00267-018-1078-6.

    OpenUrl
33. ↵
    1. Seelbach, P.W.,
    2. L.C. Hinz,
    3. M.J. Wiley, and
    4. A.R. Cooper

    . 2011. Use of multiple linear regression to estimate flow regimes for all rivers across Illinois, Michigan, and Wisconsin (Rep. No. 2095). Lansing, MI: Michigan Department of Natural Resources Fisheries Division.
34. ↵
    1. Soil Survey Staff

    . 2016. USDA Natural Resources Conservation Service, Soil Survey Geographic (SSURGO) Database. Washington, DC: USDA Natural Resources Conservation Service. https://sdmdataaccess.sc.egov.usda.gov.
35. ↵
    1. Trimble, S.W.

    1994. Erosional effects of cattle on streambanks in Tennessee, U.S.A. Earth Surface Processes and Landforms 19(5):451-464, doi:10.1002/esp.3290190506.

    OpenUrlCrossRefGeoRefWeb of Science
36. ↵
    1. USACE (US Army Corps of Engineers)

    . 2016. Philpott Reservoir Outflow Data 2000-2014. Washington, DC: United States Army Corps of Engineers. http://epec.saw.usace.army.mil/phil.htm.
37. ↵
    1. USDA NRCS (Natural Resources Conservation Service)

    . 2010. 30-meter resolution digital elevation model for Virginia. Geospatial Data Gateway. Washington, DC: USDA Natural Resources Conservation Service. https://gdg.sc.egov.usda.gov/.
38. ↵
    1. USGS (US Geological Survey)

    . 2015a. USGS Surface-Water Daily Data for the Nation. Reston, VA: US Geological Survey. https://waterdata.usgs.gov/nwis/dv/?referred_module=sw.
39. ↵
    1. USGS

    . 2015b. Physiographic divisions of the conterminous U.S. Reston, VA: US Geological Survey. https://water.usgs.gov/GIS/metadata/usgswrd/XML/physio.xml.
40. ↵
    1. VA Department of Conservation and Recreation

    . 2004. The Virginia stream restoration and stabilization best management practices guide. Richmond, VA: Virginia Department of Conservation and Recreation. https://www.deq.virginia.gov/Portals/0/DEQ/Water/Publications/BMPGuide.pdf.
41. ↵
    1. VA Department of Mines, Minerals, and Energy

    . 2012. Sinkholes and kart terrain. Big Stone Gap, VA: VA Department of Mines, Minerals, and Energy. https://www.dmme.virginia.gov/dgmr/sinkholes.shtml.
42. ↵
    1. Wischmeier, W.H., and
    2. J.V. Mannering

    . 1969. Relation of soil properties to its erodibility. Soil Science Society of America Journal 33(1):131-137, doi:10.2136/sssaj1969.03615995003300010035x.

    OpenUrlCrossRef
43. ↵
    1. J.E. Parsons,
    2. D.L. Thomas, and
    3. R.L. Huffman

    1. Yoder, D.C.,
    2. G.R. Foster,
    3. G.A. Weesies,
    4. K.G. Renard,
    5. D.K. McCool, and
    6. J.B. Lown

    . 2004. Evaluation of the RUSLE soil erosion model [Editorial]. In Agricultural Non-Point Source Water Quality Models; Their use and Application, eds. J.E. Parsons, D.L. Thomas, and R.L. Huffman. Southern Cooperative Series Bulletin #398, July, 2001. Southern Association of Agricultural Experiment Station Directors.
44. ↵
    1. Young, R.A., and
    2. J.L. Wiersma

    . 1973. The role of rainfall impact in soil detachment and transport. Water Resources Research 9(6). https://doi.org/10.1029/WR009i006p01629.
45. ↵
    1. Zaimes, G.N.,
    2. R.C. Schultz, and
    3. T.M. Isenhart

    . 2006. Riparian land uses and precipitation influences on stream bank erosion in central Iowa. Journal of the American Water Resources Association 42(1):83-97, doi:10.1111/j.1752-1688.2006.tb03825.x.

    OpenUrlCrossRefGeoRef
46. ↵
    1. Zhang, X.,
    2. R. Srinivasan,
    3. J. Arnold,
    4. R.C. Izaurralde, and
    5. D. Bosch

    . 2011. Simultaneous calibration of surface flow and baseflow simulations: A revisit of the SWAT model calibration framework. Hydrological Processes 25(14):2313-2320, doi:10.1002/hyp.8058.

    OpenUrlCrossRef