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Testing the Hydrological Landscape Unit Classification System and Other Terrain Analysis Measures for Predicting Low-Flow Nitrate and Chloride in Watersheds

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Abstract

Elevated nitrate concentrations in streamwater are a major environmental management problem. While land use exerts a large control on stream nitrate, hydrology often plays an equally important role. To date, predictions of low-flow nitrate in ungauged watersheds have been poor because of the difficulty in describing the uniqueness of watershed hydrology over large areas. Clearly, hydrologic response varies depending on the states and stocks of water, flow pathways, and residence times. How to capture the dominant hydrological controls that combine with land use to define streamwater nitrate concentration is a major research challenge. This paper tests the new Hydrologic Landscape Regions (HLRs) watershed classification scheme of Wolock and others (Environmental Management 34:S71-S88, 2004) to address the question: Can HLRs be used as a way to predict low-flow nitrate? We also test a number of other indexes including inverse-distance weighting of land use and the well-known topographic index (TI) to address the question: How do other terrain and land use measures compare to HLR in terms of their ability to predict low-flow nitrate concentration? We test this for 76 watersheds in western Oregon using the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program and Regional Environmental Monitoring and Assessment Program data. We found that HLRs did not significantly improve nitrate predictions beyond the standard TI and land-use metrics. Using TI and inverse-distance weighting did not improve nitrate predictions; the best models were the percentage land use—elevation models. We did, however, see an improvement of chloride predictions using HLRs, TI, and inverse-distance weighting; adding HLRs and TI significantly improved model predictions and the best models used inverse-distance weighting and elevation. One interesting result of this study is elevation consistently predicted nitrate better than TI or the hydrologic classification scheme.

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References

  • Arheimer B, Liden R (2000) Nitrogen and phosphorous concentrations from agricultural catchments—influence of spatial and temporal variables. Journal of Hydrology 227:140–159

    Article  CAS  Google Scholar 

  • Baker JP, Landers DH, Lee H, Ringold PL, Sumner RR, Wigington PJ, Bennett RS, Preston EM, Frick WE, Sigleo AC, Specht DT, Young DR (1995) Ecosystem management research in the Pacific Northwest: five-year research strategy. EPA/600/R-95/069. U.S. EPA, Corvallis, OR

    Google Scholar 

  • Baker ME, Wiley MJ, Seelbach PW (2001) GIS-based hydrologic modeling of riparian areas: implications for stream water quality. Journal of the American Water Resources Association 37:1615–1627

    Article  Google Scholar 

  • Beven KJ (2000) Uniqueness of place and process representations in hydrological modeling. Hydrology and Earth System Sciences 4:203–213

    Article  Google Scholar 

  • Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrological Sciences 24:43–69

    Google Scholar 

  • Burnham KP, Anderson DR (1998) Model selection and inference a practical information-theoretic approach. Springer-Verlag, New York

    Google Scholar 

  • Chapman T (1987) Classification of regions. In: Falkenmark M, Chapman T (eds) Comparative hydrology: an ecological approach to land and water resources. Unesco, Stockholm, pp 50–74

    Google Scholar 

  • Christensen S, Simkins S, Teidje JM (1990) Spatial variation of denitrification: dependency of activity centers on the soil environment. Soil Science Society of American Journal 54:1608–1613

    CAS  Google Scholar 

  • Creed IF, Band LE (1998) Export of nitrogen from catchments within a temperate forest: evidence for a unifying mechanism regulated by variable source area dynamics. Water Resources Research 11:3105–3120

    Article  Google Scholar 

  • Dahm CN, Grimm NB, Marmonier P, Valett HM, Vervier P (1998) Nutrient dynamics at the interface between surface waters and groundwaters. Freshwater Biology 40:427–451

    Article  Google Scholar 

  • Heisig PM (2000) Effects of residential and agricultural landuses on the chemical quality of baseflow of small streams in the Croton Watershed, southeastern New York. U.S. Geological Survey Water-Resources Investigations Report 99–4173

  • Herlihy A, Kaufmann P, Reynolds L, Li J, Robison G (1997) Developing indicators of ecological condition in the Willamette Basin: and overview of the Oregon prepilot study for EPA’s EMAP program. In: Laenen A, Dunnette DA (eds) River quality dynamics and restoration. Lewis, CRC Press, Boca Raton, FL, pp 275–282

    Google Scholar 

  • Herlihy AT, Stoddard JL, Johnson CB (1998) The relationship between stream chemistry and watershed land cover data in the Mid-Atlantic Region. U.S. Water, Airand Soil Pollution 105:377–386

    Article  CAS  Google Scholar 

  • Hill AR, Devito KJ, Campagnolo S, Sanmugades K (2000) Subsurface denitrification in a forest riparian zone: interactions between hydrology and supplies of nitrate and organic carbon. Biogeochemistry 51:193–223

    Article  Google Scholar 

  • Hjerdt KN, McDonnell JJ, Seibert J, Rodhe A (2004) A new topographic index to quantify downslope controls on local drainage. Water Resources Research 40(W05602):1–6

    Google Scholar 

  • Hornberger GM, Bencala KE, McKnight DE (1994) Hydrological controls on dissolved organic carbon during snowmelt in the Snake River near Montezuma, Colorado. Biogeochemistry 25:147–165

    Article  CAS  Google Scholar 

  • Howarth RW, Boyer EW, Pabich WJ, Galloway JN (2002) Nitrogen use in the United States from 1961–2000 and potential future trends. Ambio 31:88–96

    Article  Google Scholar 

  • Hulse DW, Gregory SV, Baker JP (2002) Willamette River basin planning atlas: trajectories of environmental and ecological change. Oregon State University Press, Corvallis

    Google Scholar 

  • Hunsaker CT, Levine DA (1995) Hierarchical approaches to the study of water quality in rivers. Bioscience 45:193–203

    Article  Google Scholar 

  • Johnson LB, Richards C, Host GE, Arthur JW (1997) Landscape influences on water chemistry in Midwestern stream ecosystems. Freshwater Biology 37:193–208

    Article  CAS  Google Scholar 

  • Jones KB, Neale AC, Nash MS, Van Remortel RD, Wickham JD, Riitters KH, O’Neill RV (2001) Predicting nutrient and sediment loadings to streams from landscape metrics: a multiple watershed study from the United States Mid-Atlantic Region. Landscape Ecology 16:301–312

    Article  Google Scholar 

  • Jordan TE, Correll DL, Weller DE (1997) Relating nutrient discharges from watersheds to landuse and streamflow variability. Water Resources Research 33:2579–2590

    Article  CAS  Google Scholar 

  • Kehmeier JW (2000) A spatially explicit method for determining the effects of watershed scale landuse on stream conditions. Master’s thesis. Oregon State University

  • King PB, Beikman HM (1974) Geology of the conterminous United States at 1:2,500,000 scale—a digital representation of the 1974. King PB, Beikman HM Map. U.S. Geological Survey Digital Data Series DDS-11

  • King RS, Baker ME, Whigham DF, Weller DE, Jordan TE, Kazyak PF, Hurd MK (2005) Spatial considerations for linking watershed land cover to ecological indicators in streams. Ecological Applications 15:137–153

    Article  Google Scholar 

  • Kirchner JW, Feng X, Neal C (2001) Catchment-scale advection and dispersion as a mechanism for fractal scaling in stream tracer concentrations. Journal of Hydrology 254:82–101

    Article  Google Scholar 

  • Lowrance R, Todd R, Fail J Jr, Hendrickson O Jr, Leonard R (1984) Riparian forests as nutrient filters in agricultural watersheds. Bioscience 34:374–377

    Article  Google Scholar 

  • McClain ME, Boyer ME, Dent CL, Gergel SE, Grimm NB, Groffman PM, Hart SC, Harvey JW, Johnston CA, Mayorga E, McDowell WH, Pinay G (2003) Biogeochemical hot spots and hot moments at the interface of terrestrial and aquatic ecosystems. Ecosystems 6:301–312

    Article  CAS  Google Scholar 

  • McDonnell JJ, Woods R (2004) On the need for catchment classification. Journal of Hydrology 299:2–3

    Google Scholar 

  • McHale MR, McDonnell JJ, Mitchell MJ, Cirmo CP (2002) A field-based study of soil water and groundwater nitrate release in an Andirondack forested watershed. Water Resources Research 38(4):1–17

    Article  Google Scholar 

  • Moser TJ, Wigington PJ, Schuft MJ, Kaufmann PR, Herlihy AT, Van Sickle J, McAllister LS (1997) The effect of riparian areas on the ecological condition of small, perennial stream in agricultural landscapes of Western Oregon. Research Plan, EPA/600/R-97/074. Environmental Protection Agency

  • Neal C, Rosier PTW (1990) Chemical studies of chloride and stable oxygen isotopes in two conifer afforested and moorland sites in the British Uplands. Journal of Hydrology 115:269–283

    Article  CAS  Google Scholar 

  • Norton MM, Fisher TR (2000) The effects of forest on stream water quality in two coastal plain watersheds of the Chesapeake Bay. Ecological Engineering 14:337–362

    Article  Google Scholar 

  • Nyberg L, Rodhe A, Bishop K (1999) Water transit times and flow paths from two line injections of 3H and 36Cl in a microcatchment at Gardsjon, Sweden. Hydrological Processes 13:1557–1575

    Article  Google Scholar 

  • Oetter DR, Cohen WB, Berterretche M, Maiersperger TK, Kennedy RE (2000) Land cover mapping in an agricultural setting using multiseasonal Thematic Mapper data. Remote Sensing of Environment 76:139–155

    Article  Google Scholar 

  • Omernik JM, Griffith GE (1991) Ecological regions versus hydrologic units: frameworks for managing water quality. Journal of Soil and Water Conservation 46:334–340

    Google Scholar 

  • Owens LB, Edwards WM, Keuren RW (1991) Baseflow and stormflow transport of nutrients from mixed agricultural watersheds. Journal of Environmental Quality 20:407–414

    Google Scholar 

  • Peck DV, Averill DK, Herlihy AT, Hughes RM, Kaufmann PR, Klemm DJ, Lazorchack M, McCormick FH, Peterson SA, Cappaert MR, Magee T, Monaco A (2005a) Environmental monitoring and assessment program—surface waters western pilot study: field operations manual for non-wadeable rivers and streams. EPA 600/R-05/XXX. U.S. Environmental Protection Agency, Washington, DC

    Google Scholar 

  • Peck DV, Herlihy AT, Hill BH, Hughes RM, Kaufmann PR, Klemm DJ, Lazorchack JM, McCormick SA, Peterson SA, Ringold PL, Magee T, Cappaert MR (2005b) Environmental monitoring and assessment program—surface waters western pilot study: field operations manual for wadeable streams. EPA 600/R-05/XXX. U.S. Environmental Protection Agency. Office of Research and Development, Washington, DC

    Google Scholar 

  • Peterjohn WT, Correll DL (1984) Nutrient dynamics in an agricultural watershed: observations on the role of a riparian forest. Ecology 65:1466–1475

    Article  CAS  Google Scholar 

  • Petry J, Soulsby C, Malcolm IA, Youngson AF (2002) Hydrological controls on nutrient concentrations and fluxes in agricultural catchments. Science of the Total Environment 294:95–110

    Article  CAS  Google Scholar 

  • Pinay G, Decamps H, Arles C, Lacassin-Seres M (1989) Topographic influence on carbon and nitrogen dynamics in riverine woods. Archive fur Hydrobiologie 114:401–414

    Google Scholar 

  • Pionke HB, Urban JB (1985) Effect of agricultural landuse on ground-water quality in a small Pennsylvania watershed. Ground Water 23:80–98

    Article  Google Scholar 

  • Preston SD (2000) Statistical identification of hydrochemical response units for hydrologic monitoring and regressioning in Maryland. USGS Water-Resources Investigations Report 00-4232. U.S. Geological Service

  • SAS Institute, Inc., (2003) Getting sStarted with SAS. SAS Institute, Inc., Cary, NC

    Google Scholar 

  • Schilling KE (2002) Chemical transport from paired agricultural and restored prairie watersheds. Journal of Environmental Quality 31:1184–1193

    Article  CAS  Google Scholar 

  • Sebilo M, Billen G, Grably M, Mariott A (2003) Isotopic composition of nitrate-nitrogen as a marker of riparian and benthic denitrification at the scale of the whole Seine River system. Biogeochemistry 63:35–51

    Article  CAS  Google Scholar 

  • Smart RP, Soulsby C, Neal C, Wade A, Cresser MS, Billett MF, Langan SJ, Edwards AC, Jarvie HP, Owen R (1998) Factors regulating the spatial and temporal distribution of solute concentrations in a major river system in NE Scotland. Science of the Total Environment 221:93–110

    Article  CAS  Google Scholar 

  • Smith RA, Schwarz GA, Alexander RB (1997) Regional interpretations of water-quality monitoring data. Water Resources Research 33:2781–2798

    Article  CAS  Google Scholar 

  • Stoddard JL, Peck DV, Olsen AR, Larson DP, Van Sickle J, Hawkins CP, Hughes RM, Whittier TR, Lomnicky G, Herlihy AT, Kaufman PR, Peterson SA, Ringold PL, Paulsen SG, Blair R (2005) Environmental Monitoring and Assessment Program (EMAP): Western streams and rivers statistical summary. EPA 620/R-05/XXX. U.S. Environmental Protection Agency, Washington, DC

  • Sylvia DM, Fuhrmann JJ, Hartel PG, Zuberer DA (1998) Principles and applications of soil microbiology. Prentice Hall, Upper Saddle River, NJ

    Google Scholar 

  • Wagener T, Sivapalan M, Troch P, Woods R (2007) Catchment classification and hydrologic similarity. Geography Compass 1:901–931

    Article  Google Scholar 

  • Wickham JD, O’Neill RV, Riitters KH, Smith ER, Wade TG, Jones KB (2002) Geographic targeting of increases in nutrient export due to future urbanization. Ecological Applications 12:93–106

    Article  Google Scholar 

  • Winter TS (2001) The concept of hydrologic landscapes. Journal of the American Water Resources Association 37:335–349

    Article  Google Scholar 

  • Wolock DM, Winter TC, McMahon G (2004) Delineation and evaluation of hydrologic landscape regions in the United States using geographic information system tools and multivariate statistical analyses. Environmental Management 34(Suppl 1):S71–S88

    Article  Google Scholar 

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Acknowledgments

We thank Dan Heggem, Jim Wigington, and John Van Sickle of the Environmental Protection Agency for chemistry and GIS data, Dave Wolock of the United States Geological Survey for hydrologic landscape region maps, and Alan Herlihy, Jim Wigington, and Pete Nelson for useful discussions. Many thanks go to John Van Sickle for reviewing an early version of the manuscript and providing valuable editorial advice. This research was funded by the Environmental Protection Agency cooperative program. TU Delft is thanked for their support of J.J.M. during the final writing stages.

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  1. Department of Civil and Environmental Engineering, Washington State University, 118 Sloan Hall, Pullman, WA, 99164-2910, USA

    Cara J. Poor

  2. Water Resources Section, TU Delft, Delft, The Netherlands

    Jeffrey J. McDonnell

  3. On leave from Department of Forest Engineering, Oregon State University, 204 Peavy Hall, Corvallis, OR, 97331, USA

    Jeffrey J. McDonnell

  4. Department of Bioengineering, Oregon State University, 116 Gilmore Hall, Corvallis, OR, 97331, USA

    John Bolte

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  1. Cara J. Poor
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Correspondence to Cara J. Poor.

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Poor, C.J., McDonnell, J.J. & Bolte, J. Testing the Hydrological Landscape Unit Classification System and Other Terrain Analysis Measures for Predicting Low-Flow Nitrate and Chloride in Watersheds. Environmental Management 42, 877–893 (2008). https://doi.org/10.1007/s00267-008-9168-5

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