Environmental Management

, Volume 46, Issue 3, pp 351–366 | Cite as

The Impact of Future Land Use Scenarios on Runoff Volumes in the Muskegon River Watershed

  • Deepak K. Ray
  • Jonah M. Duckles
  • Bryan C. Pijanowski
Article

Abstract

In this article we compared the response of surface water runoff to a storm event for different rates of urbanization, reforestation and riparian buffer setbacks across forty subwatersheds of the Muskegon River Watershed located in Michigan, USA. We also made these comparisons for several forecasted and one historical land use scenarios (over 140 years). Future land use scenarios to 2040 for forest regrowth, urbanization rates and stream setbacks were developed using the Land Transformation Model (LTM). Historical land use information, from 1900 at 5-year time step intervals, was created using a Backcast land use change model configured using artificial neural network and driven by agriculture and housing census information. We show that (1) controlling the rate of development is the most effective policy option to reduce runoff; (2) establishing setbacks along the mainstem are not as effective as controlling urban growth; (3) reforestation can abate some of the runoff effects from urban growth but not all; (4) land use patterns of the 1970s produced the least amount of runoff in most cases in the Muskegon River Watershed when compared to land use maps from 1900 to 2040; and, (5) future land use patterns here not always lead to increased (worse) runoff than the past. We found that while ten of the subwatersheds contained futures that were worse than any past land use configuration, twenty-five (62.5%) of the subwatersheds produced the greatest amount of runoff in 1900, shortly after the entire watershed was clear-cut. One third (14/40) of the subwatersheds contained the minimum amount of runoff in the 1960s and 1970s, a period when forest amounts were greatest and urban amounts relatively small.

Keywords

Land use change modeling Surface water runoff Policy Impacts 

Notes

Acknowledgments

We would like to acknowledge funding from the NSF Water Cycle Program, (Grant #WCR 0233648), the NASA Land Cover/Use Change and Hydrology Program, NSF III-XT Program (Grant #IIS 0705836), the Great Lakes Fishery Trust and the Wege Foundation. Dave Hyndman and Anthony Kendall provided the output from the groundwater travel time model. Kimberly Robinson read an earlier version of the manuscript and provided useful input.

References

  1. Alexander J (2006) The Muskegon: the majesty and tragedy of Michigan’s rarest river. Michigan State University PressGoogle Scholar
  2. Alig RJ, Kline JD, Klein M (2004) Urbanization on the US landscape: looking ahead in the 21st century. Landscape and Urban Planning 69:219–234CrossRefGoogle Scholar
  3. Allan JD (2004) Landscape and riverscapes: the influence of land use on river ecosystems. Annual Reviews of Ecology, Evolution and Systematics 35:257–284CrossRefGoogle Scholar
  4. Antrop M (2005) Why landscapes of the past are important for the future. Landscape and Urban Planning 70:21–34CrossRefGoogle Scholar
  5. Bankes S (1992) Exploratory modeling for policy analysis. Operations Research 41(3):435–449CrossRefGoogle Scholar
  6. Baker JP, Hulse D, Gregory S, White D, Sickle J, Berger P, Dole D, Schumaker N (2004) Alternative futures for the Willamette River Basin, Oregon. Ecological Applications 14(2):313–324CrossRefGoogle Scholar
  7. Bhaduri B, Harbor J, Engel B, Grove M (2000) Assessing watershed-scale, long-term hydrologic impacts of land-use change using a GIS-NPS Model 2000. Environmental Management 26(6):643–658CrossRefGoogle Scholar
  8. Booth D, Karr J, Schauman S, Konrad C, Morley S, Larson M, Burges S (2004) Revising urban streams: land use, hydrology, biology and human behavior. Journal of the American Water Resources Association 40(5):1351CrossRefGoogle Scholar
  9. Boutt DF, Hyndman DW, Pijanowski BC, Long DT (2001) Identifying potential land use-derived solute sources to stream baseflow using ground water models and gis. Ground Water 39(1):24–34CrossRefGoogle Scholar
  10. Bren LJ (1998) The geometry of a constant buffer-loading design method for humid watersheds. Forest Ecology and Management 110(1–3):113–125CrossRefGoogle Scholar
  11. Bren LJ (2000) A case study in the use of threshold measure of hydrologic loading in the design of stream buffer strips. Forest Ecology and Management 132:243–257CrossRefGoogle Scholar
  12. Carpenter S, Caraco N, Correll D, Howarth R, Sharpley A, Smith V (1998) Nonpoint source pollution of surface waters with phosphorus and nitrogen. Ecological Applications 8(3):559–568CrossRefGoogle Scholar
  13. Chaubey I, Maringanti C, Schaffer B, Popp J (2008) Targeting versus optimization: critical evaluation of BMP implementation for watershed management. In: World Environmental and Water Resources Congress 2008Google Scholar
  14. Cifaldi R, Allan JD, Duh J-D, Brown DB (2003) Spatial patterns in land cover in exurbanizing watersheds of southeastern Michigan. Landscape and Urban Planning 66:107–123CrossRefGoogle Scholar
  15. Correll DL (1997) Buffer zones and water quality protection: general principles. In: Haycock N, Burt T, Goulding K, Pinary G (eds) Buffer zones: their processes, potential in water protection. Quest Environmental, Harpenden, UKGoogle Scholar
  16. Diaz RJ, Rosenberg R (2008) Spreading dead zones and consequences for marine ecosystems. Science 321:926–929CrossRefGoogle Scholar
  17. Diebel MW, Maxted JT, Nowak PJ, Vander Zanden MJ (2008) Landscape planning for agricultural nonpoint source pollution reduction I: a geographical allocation framework. Environmental Management 42(5):789–802CrossRefGoogle Scholar
  18. Dosskey M (2002) Toward quantifying water pollution abatement response to installing buffers on crop land. Environmental Management 28(5):577–598CrossRefGoogle Scholar
  19. Duckles JM (2008) Impacts of land use change on runoff in the Muskegon River watershed of Michigan, past, present and future: a stakeholder driven, scenario-based approach. MS Thesis, Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana, p 109Google Scholar
  20. EPA (1972) Clean Water Act, Section 319Google Scholar
  21. Feddema JJ, Oleson KW, Bonan GB, Mearns LO, Buja LE, Meehl GA, Washington WM (2005) The importance of land-cover change in simulating future climates. Science 310:1674–1678CrossRefGoogle Scholar
  22. Fitzpatrick M, Long D, Pijanowski B (2007) Characterizing biogeochemical fingerprints of land use on surface water quality across a regional watershed in the Upper Midwest, USA. Applied Geochemistry 22(8):1825–1840CrossRefGoogle Scholar
  23. Fohrer N, Haverkamp S, Frede H (2005) Assessment of the effects of land use patterns on hydrologic landscape functions: development of sustainable land use concepts for low mountain range areas. Hydrologic Processes 19:659–672CrossRefGoogle Scholar
  24. Foster D (1992) Land-use history (1730–1990) and vegetation dynamics in central New England, USA. Journal of Ecology 80(4):753–771CrossRefGoogle Scholar
  25. Garen DC, Moore DS (2005) Curve number hydrology in water quality modeling: uses, abuses and future directions. Journal of the American Water Resources Association 41(2):377–388CrossRefGoogle Scholar
  26. Groves DG, Lempert RJ (2007) A new analytic method for finding policy-relevant scenarios. Global Environmental Change 17:73–85CrossRefGoogle Scholar
  27. GVSU (2002a) Muskegon River Watershed project: watershed plan, vol I. Annis Water Search Institute, Muskegon, Michigan, p 191Google Scholar
  28. GVSU (2002b) Muskegon River Watershed project: management plan appendices, vol II. Annis Water Search Institute, Muskegon, Michigan, p 31Google Scholar
  29. GVSU (2002c) Muskegon River Watershed project: education plan III. Annis Water Search Institute, Muskegon, Michigan, p 42Google Scholar
  30. Harbor JM (1994) A practical method for estimating the impact of land-use change on surface runoff, groundwater. Journal of the American Planning Association 60(1):95CrossRefGoogle Scholar
  31. Hundecha Y, Bardossy A (2003) Modeling of the effect of land use change on the runoff generation of a river basin through parameter regionalization of a watershed model. Journal of Hydrology 292(1–4):281–295Google Scholar
  32. Johnson NL, Lilja N, Ashby JA (2003) Measuring the impact of user participation in agricultural and natural resource management research. Agricultural Systems 78:287–306CrossRefGoogle Scholar
  33. Koomen E, Stillwell J (2007) Modelling land-use change: theories and methods. GeoJournal Library 90:1–22CrossRefGoogle Scholar
  34. Kim Y, Engel B, Lim K, Larson V, Duncan B (2002) Runoff impacts of land-use change in Indian River Lagoon Watershed. Journal of Hydrologic Engineering 7(3):245–251CrossRefGoogle Scholar
  35. Landis J (1995) Imagining land use futures: applying the California urban futures model. Journal of the American Planning Association 61:438–457CrossRefGoogle Scholar
  36. Lempert R, Popper S, Bankes S (2002) Confronting surprise. Social Science Computer Review 20(4):420–440CrossRefGoogle Scholar
  37. Leopold L (1968) Hydrology for urban land planning—a guidebook on the hydrologic effects of urban land use. USGS Circular 554Google Scholar
  38. Leopold L (1994) A view of the river. Harvard University Press, Cambridge, MA, p 298Google Scholar
  39. Levy D (2001) Michigan land resource project. Technical report. Public Sector Consultants, IncGoogle Scholar
  40. Lowrance R, Altier L, Williams R, Inamdar S, Sheridan J, Bosch D, Hubbard R, Thomas D (2000) REMM: the riparian ecosystem management model. Journal of Soil and Water Conservation 55(1):27–34Google Scholar
  41. Lowrance R (1998) Riparian forest ecosystems as filters for non-point source pollution. In: Pace M, Groffmann P (eds) Chapter 5 in success, limitations, and frontiers in ecosystem science. Springer Publishers, New York, p 499Google Scholar
  42. Macdonald JS, MacIssac E, Herunter H (2003) The effect of variable retention riparian buffer zones on water temperatures in small headwater streams in sub-boreal forest ecosystems of British Columbia. Canadian Journal of Forest Research 33:1371–1382CrossRefGoogle Scholar
  43. Machtans C, Villard M, Hannon S (1996) Use of riparian buffer strips as movement corridors by forest birds. Conservation Biology 10(5):1366–1379CrossRefGoogle Scholar
  44. Mitsch WJ, Gosselink JG (1993) Wetlands. Van Nostrand Reinhold, New YorkGoogle Scholar
  45. Mölders N, Rühaack W (2002) On the impact of explicitly predicted runoff on the simulated atmospheric response to small-scale land-use changes—an integrated modeling approach. Atmospheric Research 63:3–38CrossRefGoogle Scholar
  46. National Research Council (2008) Urban stormwater management in the United States. The National Academies Press, Washington, DC, 529 ppGoogle Scholar
  47. NRCS (2008) US General Soil Map (STATSGO2) Description. http://www.soils.usda.gov/survey/geography/statsgo/description.html
  48. O’Neal R (1997) Muskegon River Watershed assessment. Fisheries Division Special Report No. 19. State of Michigan Department of Natural ResourcesGoogle Scholar
  49. O’Callaghan JO (1996) Land use: the interaction of economics, ecology and hydrology. Chapman and Hall Publishers, LondonGoogle Scholar
  50. Paul M, Meyer J (2001) Streams in the urban landscape. Annual Review of Ecology and Systematics 32:333–365CrossRefGoogle Scholar
  51. Pijanowski B, Ray D, Kendall A, Duckles J, Hyndman D (2007) Using backcast land use change and groundwater travel-time models to generate land use legacy maps for watershed management. Ecology and Society 12(2):25Google Scholar
  52. Pijanowski BC (2006) Afforestation patterns in the Upper Midwest, USA. In: Proceedings of the IUFRO landscape ecology conference, Locorotondo, Bari, Italy, 26–29 Sept 2006Google Scholar
  53. Pijanowski BC, Pithadia S, Shellito BA, Alexandridis K (2005) Calibrating a neural network-based urban change model for two metropolitan areas of the Upper Midwest of the United States. International Journal of Geographical Information Science 19(2):197–215CrossRefGoogle Scholar
  54. Pijanowski BC, Shellito B, Pithadia S (2002a) Using artificial neural networks, geographic information systems and remote sensing to model urban sprawl in coastal watersheds along eastern Lake Michigan. Lakes and Reservoirs 7:271–285CrossRefGoogle Scholar
  55. Pijanowski BC, Brown DG, Shellito BA, Manik GA (2002b) Using neural networks and GIS to forecast land use changes: a land transformation model. Computers, Environment and Urban Systems 26(6):553–575CrossRefGoogle Scholar
  56. Ponce VM, Hawkins RH, ASCE M (1996) Runoff curve number: Has it reached maturity? Journal of Hydrologic Engineering 1:11–19CrossRefGoogle Scholar
  57. Pontius R G Jr, Boersma W, Castella J-C, Clarke K, de Nijs T, Dietzel C, Duan Z, Fotsing E, Goldstein N, Kok K, Koomen E, Lippitt CD, McConnell W, Sood AM, Pijanowski BC, Pithadia S, Sweeney S, Trung TN, Veldkamp AT, Verburg PH (2008) Comparing the input, output, and validation maps for several models of land change. Annals of Regional Science 42(1):11–47CrossRefGoogle Scholar
  58. Ray DK, Welch RM, Lawton RO, Nair US (2006) Dry season clouds and rainfall in northern central America: implications for the Mesoamerican biological corridor. Global and Planetary Change 54:150–162. doi:10.1016/j.gloplacha.2005.09.004 CrossRefGoogle Scholar
  59. Ray DK, Pielke RA Sr, Nair US, Welch RM, Lawton RO (2009) Importance of land use versus atmospheric information verified from cloud simulations from a frontier region in Costa Rica. Journal of Geophysical Research. doi:10.1029/2007JD009565
  60. Ray DK, Pijanowski BC (2010) A backcast land use change model to generate past land use maps for the Muskegon River Watershed of Michigan, USA. Journal of Land Use Science 5:1, 1–29. doi:10.1080/17474230903150799
  61. Ray DK, Pielke R A Sr, Nair US, Niyogi D (2010) Roles of atmospheric and land surface data in dynamic regional downscaling. Journal of Geophysical Research 115:D05102. doi:10.1029/2009JD012218 CrossRefGoogle Scholar
  62. Rodrguez JP, Beard JTD, Bennett EM, Cumming GS, Cork S, Agard J, Dobson AP, Peterson GD (2006) Trade-offs across space, time, and ecosystem services. Ecology and Society 11(1), art28Google Scholar
  63. Searchinger T, Heimlich R, Houghton R, Dong F, Elobeid A, Fabiosa J, Tokgoz S, Hayes D, Yu T (2008) Use of US croplands for biofuels increases greenhouse gases through emissions from land-use change. Science 319:1238–1240CrossRefGoogle Scholar
  64. Shields FD, Bowie AJ, Cooper CM (1995) Control of streambank erosion due to bed degradation with vegetation and structure. Water Research Bulletin 31:475–489Google Scholar
  65. Sokal RR, Rohlf FJ (1995) Biometry, 3rd edn. WH Freeman and Company, 887 pGoogle Scholar
  66. Stevenson RJ, Wiley M, Gage S, Lougheed V, Riseng C, Bonnell P, Burton T, Hough R, Hyndman D, Koches J, Long D, Pijanowski B, Qi J, Steiman A, Uzarski D (2008) Watershed science: essential, complex, multidisciplinary and collaborative. In: Wetland and water resource modeling and assessment: a watershed perspective. Taylor and Francis Publishers, Baca Raton, FloridaGoogle Scholar
  67. Systat Inc (2008) Systat 12, Introduction of linear mixed models, chap 5. Systat Software Inc., San Jose, CA Google Scholar
  68. Tang Z, Engel B, Lim K, Pijanowski B, Harbor J (2005a) Minimizing the impact of urbanization on long-term runoff. Journal of the Water Resources Association 41(6):1347–1359CrossRefGoogle Scholar
  69. Tang Z, Engel BA, Pijanowski BC, Lim KJ (2005b) Forecasting land use change and its environmental impact at a watershed scale. Journal of Environmental Management 76:35–45CrossRefGoogle Scholar
  70. Tomer M, Burkart M (2003) Long-term effects of nitrogen fertilizer user on ground water nitrate in two small watersheds. Journal of Environmental Quality 32:1931–1938CrossRefGoogle Scholar
  71. Tong S, Chen W (2002) Modeling the relationship between land use and surface water quality. Journal of Environmental Management 66(4):377–393CrossRefGoogle Scholar
  72. United States Department of Agriculture (1986) Tr-55: urban hydrology for small watersheds. Technical report. Natural Resource Conservation Service Conservation Engineering DivisionGoogle Scholar
  73. USEPA (1983) Final peport of the nationwide urban runoff program. US Environmental Protection Agency, Water Planning Division, Washington, DCGoogle Scholar
  74. USEPA (2000) Nutrient criteria technical guidance manual: lakes and reservoirs, 1st edn. EPA 8222-B00-001. Washington, DCGoogle Scholar
  75. Walker B, Salt D (2006) Resilience thinking. Island Press, Washington, DCGoogle Scholar
  76. Walter MT, Archibald J, Buchanan B, Dahlke H, Easton Z, Marjerison R, Sharma A, Shaw S (2009) New paradigm for sizing riparian buffers to reduce risks of polluted storm water: practical synthesis. Journal of Irrigation and Drainage Engineering 135(2):200–2009CrossRefGoogle Scholar
  77. Wang L, Lyons J, Kanehl P, Gatti R (1997) Influences of watershed land use on habitat quality and biotic integrity in Wisconsin streams. Fisheries 22(6):6–12CrossRefGoogle Scholar
  78. Wayland KG, Hyndman DW, Boutt D, Pijanowski BC, Long DT (2002) Modelling the impact of historical land uses on surface-water quality using groundwater flow and solute-transport models. Lakes and Reservoirs 7:189–199CrossRefGoogle Scholar
  79. Wayland KG, Long DT, Hyndman DW, Pijanowski BC, Woodhams SM, Haack SK (2003) Identifying relationships between baseflow geochemistry and land use with synoptic sampling and R-mode factor analysis. Journal of Environmental Quality 32(1):180–190CrossRefGoogle Scholar
  80. Whitney GG (1987) An ecological history of the great lakes forest of Michigan. The Journal of Ecology 75(3):667–684CrossRefGoogle Scholar
  81. Wiley M, Pijanowski B, Jan Stevenson R, Seelbach P, Richards P, Riseng C, Hynman D, Koches J (2008)  Integrated modeling of the Muskegon River: tools for ecological risk assessment in a Great Lakes Watershed. In: Ji W (ed) Wetland and water resource modeling and assessment: a watershed perspective, chap 20. Taylor & Francis, LondonGoogle Scholar
  82. Wiley M, Hyndman D, Pijanowski BC, Kendall A, Riseng C, Rutherford E, Cheng S, Carlson M, Tyler J, Stevenson R, Steen P, Richards P, Seelbach P, Koches J (2010) A multi-modeling approach to evaluate impacts of global change on river ecosystems. Hydrobiologia. doi:10.1007/s10750-010-0239-2
  83. Wolter PT, Johnston CA, Niemi GJ (2006) Land use and cover change in the U.S. Great Lakes basin 1992–2001. Journal of Great Lakes Research 32:607–628CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Deepak K. Ray
    • 1
    • 2
  • Jonah M. Duckles
    • 1
  • Bryan C. Pijanowski
    • 1
  1. 1.Department of Forestry and Natural ResourcesPurdue UniversityWest LafayetteUSA
  2. 2.Institute on EnvironmentUniversity of Minnesota-Twin CitiesSaint PaulUSA

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