Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-24T17:35:38.488Z Has data issue: false hasContentIssue false

Watershed-scale modeling of the water quality effects of cropland conversion to short-rotation woody crops

Published online by Cambridge University Press:  12 February 2007

Karen Updegraff*
Affiliation:
South Dakota School of Mines and Technology, Institute of Atmospheric Sciences, 501 E. St. Joseph St., Rapid City, SD 57701, USA.
Prasanna Gowda
Affiliation:
University of Minnesota, Department of Soil, Water and Climate, 1991 Upper Buford Circle, St. Paul, MN 55108, USA.
David J. Mulla
Affiliation:
University of Minnesota, Department of Soil, Water and Climate, 1991 Upper Buford Circle, St. Paul, MN 55108, USA.
*
*Corresponding author: [email protected]

Abstract

The conversion of cropland to the production of woody biomass, or short-rotation woody crops (SRWCs), has the potential to provide an economic alternative to Midwestern farmers, while simultaneously offering an environmental dividend in the form of reduced erosion and nutrient pollution of streams. However, notwithstanding a wealth of plot-scale and anecdotal data suggestive of these benefits, there are few watershed-scale integrated analyses on which to base regional policy decisions regarding incentives to convert fields to SRWCs. This study applied a field-scale runoff, sediment and nutrient transport model (Agricultural Drainage and Pesticide Transport, ADAPT) to a simulation of 10, 20 and 30% cropland conversion to SRWCs, grown on a 5-year rotation, in a representative Minnesota River sub-watershed. While the generation of a highly precise simulation would require extensive calibration of the model, its application with parameters previously calibrated to neighboring, similar watersheds provided reasonably robust results that indicated real differences resulting from cropland conversion. At the highest conversion level, mean annual runoff was reduced by up to 9%, sediment loads by 28% and nitrogen (N) loads by 15%, although total phosphorus (P) loads increased by 2% relative to the no-SRWC scenario. However, the relative benefits of conversion at the field level were contingent on soil type, drainage status and the alternative crop. These differences provide useful insights with respect to the targeting of possible conversion incentives.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2004

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1CRPD 2001. Short rotation woody crops: a role for the State of Minnesota. Minnesota State University, Center for Rural Policy and Development, Mankato, Minnesota, USA.Google Scholar
2Vaughan, W., Russell, C., Gianessi, L., and Nielsen, L. 1982. Measuring and predicting water quality in recreation related terms. Journal of Environmental Management 15:363380.Google Scholar
3Ribaudo, M., Young, C., and Epp, D. 1984. Recreation benefits from an improvement in water quality at St. Albans Bay, Vermont (Staff Report AGES 840127). USDA Economic Research Service, Natural Resource Economics Division.Google Scholar
4Henry, R., Ley, R., and Welle, P. 1988. The economic value of water resources: the Lake Bemidji survey. Journal of the Minnesota Academy of Science 53(3): 3744.Google Scholar
5Jacobson, P., Close, T., Anderson, C., and Kelly, T. 1999. Attitudes of Minnesota residents about fisheries issues. Investigational Report 478. Minnesota Department of Natural Resources.Google Scholar
6Feather, P., Hellerstein, D., and Hansen, L. 1999. Economic valuation of environmental benefits and the targeting of conservation programs: the case of CRP. Agricultural Economic Report AER 778. USDA Economic Research Service, Resource Economics Division.Google Scholar
7Ribaudo, M. 1989. Water quality benefits from the Conservation Reserve Program (Agricultural Economic Report AER 606). USDA Economic Research Service.Google Scholar
8Tolbert, V., Thornton, F., Joslin, J., Beck, B., Bandaranayake, W., Tyler, D., Pettry, D., Green, T., Malik, R., Bingham, L., Houston, A., Shires, M., Dewey, J., and Schoenholtz, S. 1998. Soil and water quality aspects of herbaceous and woody energy crop production: lessons form research-scale comparisons with agricultural crops. BioEnergy ’98–-The Eighth National Bioenergy Conference: Expanding Bioenergy Partnerships, 4–8 October 1996, Madison, Wisconsin, USA.Google Scholar
9Malik, R.K., Green, T.H., Brown, G.F. and Mays, D. 2000. Use of cover crops in short rotation hardwood plantations to control erosion. Biomass and Bioenergy 18:479487.CrossRefGoogle Scholar
10Licht, L. 1994. Ecolotree buffers strategically planted on Iowa farms for ecological and commercial value. Working Trees: Farming in the 1990’s. Owatonna, Minnesota, USA.Google Scholar
11Udawata, R., Krstansky, J., Henderson, G., and Garrett, H. 2002. Agroforestry practices, runoff, and nutrient loss: a paired watershed comparison. Journal of Environmental Quality 31:12141225.CrossRefGoogle Scholar
12High Island Watershed Assessment Project. Available at website http://cgee.hamline.edu/rivers/MRN/HIWAP/ (verified 29 February 2004).Google Scholar
13Dalzell, B. 2000. Modeling and evaluation of non point source pollution in the Lower Minnesota River Basin. Master’s thesis, University of Minnesota, St. Paul, Minnesota, USA.Google Scholar
14MPCA 1999. Minnesota River Basin Assessment of Stream Water Quality. Based on the 1998 MN 305(b) Report to Congress of the United States. Minnesota Pollution Control Agency, St. Paul, Minnesota, USA.Google Scholar
15Gowda, P. 1996. An integrated spatial-process model to predict agricultural nonpoint source pollution. PhD thesis, Ohio State University, Columbus, Ohio, USA.Google Scholar
16Leonard, R., Knisel, W., and Still, D. 1987. GLEAMS: groundwater loading effects of agricultural management systems. Transactions of the American Society of Agricultural Engineers 30(5): 14031418.CrossRefGoogle Scholar
17Chung, S., Ward, A., and Shalk, C. 1992. Evaluation of the hydrologic component of the adapt water table management model. Transactions of the American Society of Agricultural Engineers 35(2): 571579.CrossRefGoogle Scholar
18Zucker, L. and Brown, L. 1998. Agricultural drainage–water quality impacts and subsurface drainage studies in the Midwest. Bulletin 871. Ohio State University, Columbus, Ohio, USA.Google Scholar
19Gowda, P., Ward, A., White, D., Baker, D., and Lyon, J. 1999. An approach for using field scale models to predict peak flows on agricultural watersheds. Journal of the American Water Resources Association 35(5): 12231232.CrossRefGoogle Scholar
20Northern States Power Company 1999. NSP signs biomass contracts with St. Paul Cogeneration, EPS/Beck Power. News Release, 8 January.Google Scholar
21Minnesota Agricultural Statistics Service 1994. Minnesota Agricultural Statistics 1994. Annual Report. MASS, St. Paul, Minnesota, USA.Google Scholar
22Minnesota Agricultural Statistics Service 1995. Minnesota Agricultural Statistics 1995. Annual Report. MASS, St. Paul, Minnesota, USA.Google Scholar
23Minnesota Agricultural Statistics Service 1996. Minnesota Agricultural Statistics 1996. Annual Report. MASS, St. Paul, Minnesota, USA.Google Scholar
24Minnesota Agricultural Statistics Service 2000. Minnesota Agricultural Statistics 2000. Annual Report. MASS, St. Paul, Minnesota, USA.Google Scholar
25Isebrands, J., Nelson, N., Dickman, D., and Michael, D. 1983. Yield physiology of short rotation intensively cultured poplars. In Hansen, E.A. (compiler). Intensive Plantation Culture: 12 years Research. USDA Forest Service GTR NC–91. p. 7793.Google Scholar
26Zavitkovski, J. 1983. Projected and actual biomass production of 2- to 10-year-old intensively cultured Populus ‘tristis #1’. In E.A. Hansen (compiler). Intensive Plantation Culture: 12 years Research. USDA Forest Service GTR NC–91. p. 7276.Google Scholar
27Friend, A., Scarascia-Mugnozza, G., Isebrands, J., and Heilman, P. 1991. Quantification of two-year-old hybrid poplar root systems: morphology, biomass and C distribution. Tree Physiology 8:109119.CrossRefGoogle ScholarPubMed
28DeBell, D., Clendenen, G., Harrington, C., and Zasada, J. 1996. Tree growth and stand development in short-rotation Populus plantings: 7-year results for two clones at three spacings. Biomass and Bioenergy 11(4): 253269.CrossRefGoogle Scholar
29Stettler, R., Zsuffa, L., and Wu, R. 1996. The role of hybridization in the genetic manipulation of Populus . In Stettler, R., Bradshaw, J.H.D., Heilman, P., and Hinckley, T. (eds). Biology of Populus and its Implications for Management and Conservation. NRC Research Press, Ottawa, Canada. p. 87112.Google Scholar
30AURI 19971998. Short rotation forestry of hybrid poplars. Ag Innovation News. MN 56716. University of Minnesota, Agricultural Utilization Research Institute. Crookston, Minnesota, USA.Google Scholar
31Ihaka, R. and Gentleman, R. 1996. R: a language for data analysis and graphics. Journal of Computational and Graphical Statistics 5(3): 299314.Google Scholar
32USGS. Available at Web site http://waterdata.usgs.gov/mn/nwis (verified 29 February 2004).Google Scholar
33Available at Web site http://www.crh.noaa.gov/ncrfc/documents/MinnRiver.html (verified 29 February 2004).Google Scholar
34Dalzell, B., Gowda, P., Mulla, D., and Ward, A. 1999. Predicting nonpoint source pollution for a small agricultural watershed in southern Minnesota. 1999 ASAE Annual International Meeting, Paper No. 992215. American Society of Agricultural Engineers, St. Joseph, Michigan, USA.Google Scholar
35Licht, L., Schnoor, J., and Nair, D. 1992. Ecolotree buffers for controlling nonpoint sediment and nitrate. Presented at the 1992 International Winter Meeting of The ASAE. Paper No. 922626. American Society of Agricultural Engineers, St. Joseph, Michigan, USA.Google Scholar
36Perry, C., Miller, R., and Brooks, K. 2001. Impacts of short-rotation hybrid poplar plantations on regional water yield. Forest Ecology and Management 143:143151.CrossRefGoogle Scholar
37MPCA 2001. Draft Minnesota River Basin Plan. 18 June2001. Minnesota Pollution Control Agency. Online Document. Available at http://www.pca.state.mn.us/water/basins/mnriver/mnbasinplan.pdf (verified 29 February 2004).Google Scholar
38Altier, L., Lowrance, R., Williams, R., and Inamdar, S. 1998. The Riparian Ecosystem Management Model: Plant growth component. Proceedings of the First Federal Interagency Hydrologic Modeling Conference, Las Vegas, Nevada, USA, April. p. 1.331.40.Google Scholar
39Todd, R., Fail, J. Jr., Hendrickson, O. Jr, and Asmussn, L. 1984. Riparian forests as nutrient filters in agricultural watersheds. BioScience 34(6): 374377.Google Scholar
40Lowrance, R., Leonard, R., and Sheridan, J. 1985. Managing riparian ecosystems to control nonpoint pollution. Journal of Soil and Water Conservation 40(1): 8791.Google Scholar
41Cooper, J., Gilliam, J., Daniels, R., and Robarge, W. 1987. Riparian areas as filters for agricultural sediment. Soil Science Society of America Journal 51:416420.CrossRefGoogle Scholar