Hostname: page-component-77c89778f8-swr86 Total loading time: 0 Render date: 2024-07-17T16:10:26.106Z Has data issue: false hasContentIssue false
  • English
  • Français

A Dynamic Analysis of the Impact of Water Quality Policies on Irrigation Investment and Crop Choice Decisions

Published online by Cambridge University Press:  28 April 2015

JunJie Wu ,
Harry P. Mapp  and
Daniel J. Bernardo
JunJie Wu
Affiliation:
Oklahoma State University, Stillwater, Oklahoma
Harry P. Mapp
Affiliation:
Oklahoma State University, Stillwater, Oklahoma
Daniel J. Bernardo
Affiliation:
Oklahoma State University, Stillwater, Oklahoma
Get access Rights & Permissions [Opens in a new window]

Abstract

A dynamic model is developed to analyze farmers' irrigation investment and crop choice decisions under alternative water quality protection policies. The model is applied to an empirical example in the Oklahoma High Plains. The choices of crops and irrigation systems and the resulting levels of irrigation, income, and nitrogen runoff and percolation are simulated over a ten-year period. An effluent tax on nitrogen runoff and percolation is shown to be effective in reducing nitrate pollution. The efficacy of cost sharing in adopting modern irrigation technologies and restrictions on irrigation water use depends on soil type. A tax on nitrogen use is shown to be the least effective policy.

Keywords

crop selectiondynamic optimizationirrigation investmentwater quality
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 26 , Issue 2 , December 1994 , pp. 506 - 525
Copyright
Copyright © Southern Agricultural Economics Association 1994

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

Antie, John M., and Just, Richard E.. “Effects of Commodity Program Structure on Resource and the Environment.” In Commodity and Resource Policy in Agricultural Systems, eds. Bockstael, N. and Just, R.. New York: Springer-Verlog, 1990.Google Scholar
American Petroleum Institute. Basic Petroleum Data Book: Petroleum industry Statistics. Vol. XI, No.2, May, 1991.Google Scholar
Casterline, Gary, Dinar, Ariel, and Zilberman, David. “The Adoption of Modern Irrigation Technologies in the United States.” In Free Trade and Agricultural Diversification: Canada and the United States, ed., Andrew Schmits, Boulder: Westview Press, 1989.Google Scholar
Caswell, M., Lichtenberg, E., and Zilberman, D.. “The Effects of Pricing Policies on Water Conservation and Drainage.” Amer. J. Agr. Econ. 72(1990): 883–890.CrossRefGoogle Scholar
Caswell, M. and Zilberman, D.. “The Effects of Well Depth and Land Quality on the Choice of Irrigation Technology.” Amer. J. Agr. Econ. 68(1986): 798–890.CrossRefGoogle Scholar
Caswell, M. and Zilberman, D.. “The Choices of Irrigation Technologies in California.” Amer. J. Agr. Econ. 67(1985): 224–234.CrossRefGoogle Scholar
Dale, J. F., Bernardo, D. J., Kizer, M. A., and Nelson, J. R.. Capital and Operating Costs for Alternative Irrigation Systems in the Central Ogallala Region. Research Report P-902, Oklahoma Agricultural Experiment Station, Oklahoma State University, Stillwater, Oklahoma, January 1989.Google Scholar
Dinar, A., and Knapp, K.. “A Dynamic Analysis of Optimal Water Use Under Saline Conditions.” West. J. Agr. Econ. 11(1986): 58–66.Google Scholar
Earls, R. C. “An Economic Analysis of Water-Related Technology in The Oklahoma High Plains.” Master Thesis, Oklahoma State University, 1989.Google Scholar
Earls, R.C, and Bernardo, Daniel J.. “An Economic Analysis of Irrigation Investment Alternatives in the Central High Plains.” J. of Amer. Soci, of Farm Managers and Rural Appraisers. 56(1992): 18–26.Google Scholar
Food and Agricultural Policy Research Institute. F APRI 1993 U.S. Agricultural Outlook. Staff Report #1-93, April 1993a.Google Scholar
Food and Agricultural Policy Research Institute. FAPRI Forecast: Macro, Prices Paid Indices and Cost of Production. CNFAP #2-93, January 1993b.Google Scholar
Hexem, R. W., and Heady, E. O.. Water Production Functions for Irrigated Agriculture. Ames IA: Iowa State University Press, 1978.Google Scholar
Kletke, Darrel D., Harris, Thomas R., and Mapp, Harry P.. Irrigation Cost Program Users Reference Manual. Research Report P-770, Oklahoma Agricultural Experiment Station, Oklahoma State University, Stillwater, Oklahoma, May 1978.Google Scholar
Knapp, K. C., Stevens, B. K., and Land, J.Oster, J. D.. “A Dynamic Optimization Model for Irrigation Investment Under Limited Drainage Conditions.” Water Resources Research. 26(1990): 1335–1343.CrossRefGoogle Scholar
Lichtenberg, Erick. “Land Quality, Irrigation Development, and Cropping Patterns in the Northern High Plains.” Amer. J. Agr. Econ. 71(1989): 187–194.CrossRefGoogle Scholar
Lyle, W. M., and Bordovsky, J. P.. “LEPA Irrigation System Evaluation.” Transactions of the ASAE. 26(1983): 761–781.Google Scholar
Mapp, H. P., Bernardo, D. J., Elliott, R. L., Stone, J. F., Sabbagh, G. J., Geleta, S., and Watkins, K. B.. Impacts of Agricultural Production Practices on the Quantity and Quality of Groundwater in the Central High Plains. Final Report, USGS Project No. 14-08-001-Gl750. November 1991.Google Scholar
Matanga, G. B., and Marino, M. A.. “Irrigation Planning, 2, Water Allocation for Leaching and Irrigation Purposes.” Water Resources Research. 15(1979): 679–683.CrossRefGoogle Scholar
Musick, J. T., Pringle, F. B., and Walker, J. D.. “Sprinkler and Furrow Irrigation Trends-Texas High Plains.” Appi. Eng. Agr. 4(1988): 46–52.CrossRefGoogle Scholar
Negri, D. H., and Brooks, D. H.. “Determinants of Irrigation Technology Choice.” West. J. of Agr. Econ. 15(1990): 213–223Google Scholar
Oklahoma State University, Farm Management Extension, Department of Agricultural Economics. Oklahoma Crop and Livestock Budgets. Oklahoma State University, 1992.Google Scholar
Opaluch, J. J., and Segerson, Kathleen. “Aggregate Analysis of Site-Specific Pollution Problems: the Case of Groundwater Contamination From Agricultural Pesticides.” Northeastern Journal of Agricultural and Resource Economics. 20(1991): 83–97.CrossRefGoogle Scholar
Ray, S. C. “A Translog Cost Function Analysis of US Agriculture, 1939-1977.” Amer. J. Agr. Econ. 64(1982): 490–498.CrossRefGoogle Scholar
Sabbagh, G. J., Geleta, S., Elliott, R. L., Williams, J. R., and Griggs, R. H.. “Modification of Epic To Simulate Pesticide Activities: EPIC-PST.” Transactions of the ASAE. Vol 34(4): July-August 1991.CrossRefGoogle Scholar
Segerson, Kathleen, and Wu, JunJie. “Impacts of Government Programs and Land Characteristics on Groundwater Pollution in Wisconsin.” U.S. Department of Agriculture, Economic Research Service, Technical Bulletin, forthcoming.Google Scholar
Shumway, R. C. “Supply, Demand and Technology in a Multiproduct Industry: Texas Fieldcrops.” Amer. J. Agr. Econ. 65(1983): 748–760.CrossRefGoogle Scholar
U.S Department of Agriculture. Agricultural Statistics. Washington, D.C, 1970-1992.Google Scholar