Hostname: page-component-76fb5796d-x4r87 Total loading time: 0 Render date: 2024-04-26T13:06:01.516Z Has data issue: false hasContentIssue false
  • English
  • Français

Watershed-Scale Economic and Environmental Tradeoffs Incorporating Risks: A Target MOTAD Approach

Published online by Cambridge University Press:  15 September 2016

Zeyuan Qiu ,
Tony Prato  and
Michael Kaylen
Zeyuan Qiu
Affiliation:
Department of Agricultural Economics, University of Missouri-Columbia
Tony Prato
Affiliation:
Department of Agricultural Economics, University of Missouri-Columbia
Michael Kaylen
Affiliation:
Department of Agricultural Economics, University of Missouri-Columbia
Get access

Abstract

This paper evaluates the economic and environmental tradeoffs at watershed scale by incorporating both economic and environmental risks in agricultural production. The Target MOTAD model is modified by imposing a probability-constrained objective function to capture the yield uncertainty caused by random allocation of farming systems to soil types and by introducing environmental targets to incorporate environmental risk due to random storm events. This framework is used to determine the tradeoff frontier between watershed net return and sediment yield and nitrogen concentration in runoff in Goodwater Creek watershed, Missouri. The frontier is significantly affected by environmental risk preference.

Type
Articles
Information
Agricultural and Resource Economics Review , Volume 27 , Issue 2 , October 1998 , pp. 231 - 240
Copyright
Copyright © 1998 Northeastern Agricultural and Resource Economics Association 

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

Brooke, A., Kendrick, D., and Meeraus, A. 1992. GAMS: A User Guide. Release 2.25. Danvers, Mass.: Boyd & Fraser Publishing Company.Google Scholar
Charnes, A., and Cooper, W.W. 1963. “Deterministic Equivalents for Optimizing and Satisfying under Chance Constraints.” Operations Research 11(1): 18–39.Google Scholar
Environmental Protection Agency (EPA), Office of Water. 1994. National Water Quality Inventory: 1992 Report to Congress. EPA 841-R-94-001. Washington D.C.Google Scholar
Ethridge, B.J., and Olson, R.K. 1993. “Research and Information Needs Related to Nonpoint Source Pollution and Wetlands in the Watershed: An EPA Perspective.” In Created and Natural Wetlands for Controlling Nonpoint Source Pollution, ed. Olson, R.K., Boca Raton, Fla.: C.K. Smoley.Google Scholar
Haimes, Y.Y., and Hall, W.A. 1974. “Multiobjectives in Water Resource Systems Analysis: The Surrogate Worth Trade Off Method.” Water Resources Research 10(4): 615–24.CrossRefGoogle Scholar
Ma, J.C. 1993. “Integrated Economic and Environmental Assessment of Alternative Agricultural Systems.” Ph.D. diss., University of Missouri, Columbia.Google Scholar
Milon, J.W. 1987. “Optimizing Nonpoint Source Controls in Water Quality Regulation.” Water Resources Bulletin 23(3): 387–96.Google Scholar
Missouri MSEA Management Team. 1995. “The Missouri Management Systems Evaluation Area Research and Education Report: 1990–1995.” Columbia: University of Missouri.Google Scholar
Tauer, L.W. 1983. “Target MOTAD.” American Journal of Agricultural Economics 65(3) 606–10.Google Scholar
Teague, M.L., Bernardo, D.J., and Mapp, H.P. 1995. “Farm-Level Economic Analysis Incorporating Stochastic Environmental Risk Assessment.” American Journal of Agricultural Economics 77(1): 8–19.Google Scholar
U.S. Department of Agriculture (USDA). Soil Conservation Service. 1988. Cost and Returns Estimator: User Manual. Lino Lakes, Minn. Midwest Agricultural Research Associates, Inc. Google Scholar
U.S. Department of Agriculture (USDA). Soil Conservation Service. Natural Resources Conservation Service (NRCS). 1995. Soil Survey of Audrain County, Missouri. 387-974/00537/SCS. U.S. Government Printing Office.Google Scholar
Van Kooten, G.C., Weisensel, W.P., and Chinthammit, D. 1990. “Valuing Trade-offs between Net Returns and Stewardship Practices: The Case of Soil Conservation in Saskatchewan.” American Journal of Agricultural Economics 72(1): 104–13.Google Scholar
Water Environment Federation. 1992. A National Water Agenda for the 21st Century. Alexandria, Va.: Water Environmental Federation Water Quality 2000.Google Scholar
Wu, S. 1994. “Economic and Water Quality Impacts of Alternative Farming systems in Goodwater Creek Watershed: A Stochastic Programming Analysis.” Ph.D. diss., University of Missouri, Columbia.Google Scholar
Xu, F., Prato, T., and Zhu, M. 1996. “Effects of Distribution Assumptions for SYs on Farm Returns in a Chance-Constrained Programming Model.” Review of Agricultural Economics 18(1): 53–64.Google Scholar
Young, R.A., Onstad, C.A., Bosch, D.D., and Anderson, W.P. 1987. AGNPS, Agricultural Non-Point-Source Pollution Model: A Watershed Analysis Tool. Conservation Research Report. Washington, D.C.: USDA ARS.Google Scholar
Zhu, M., Taylor, D.B., and Sarin, S.C. 1993. “A Multi-Objective Dynamic Programming Model for Evaluation of Agricultural Management Systems in Richmond County, Virginia.” Agricultural Systems 42: 127–52.Google Scholar