Investigating the Effect of Variations in Irrigation Water Price on Cropping Pattern and Gross Margin under Uncertainty (Case Study: Khorasan Razavi)
محورهای موضوعی : Environmental policy and managementMostafa Mardani 1 , Saman Ziaee 2 , Elham Kalbali 3 , Samira Soltani 4
1 - Department of Agricultural Economics, University of Zabol, Bonjar Street, Zabol City, Sistan and Balochestan Province, Iran
2 - Department of Agricultural Economics, University of Zabol, Bonjar Street, Zabol City, Sistan and Balochestan Province, Iran
3 - Department of Agricultural Economics, University of Zabol, Bonjar Street, Zabol City, Sistan and Balochestan Province, Iran
4 - Department of Agricultural Economics, University of Zabol, Bonjar Street, Zabol City, Sistan and Balochestan Province, Iran
کلید واژه: Optimization, uncertainty, Water price, Khorasan Razavi Province,
چکیده مقاله :
Water shortage crisis is an issue that has led to drastic changes in different agricultural policies, especially in arid and semi-arid areas. Uncertainty in the amount of resources, e.g. water, used for agricultural production entails risk for farmers' income and cropping pattern changes. In the present study, the robust optimization model was used for optimal allocation of arable lands of Khorasan Razavi Province under uncertainty. During the allocation, the effect of water input price variations on total gross margin and cropping pattern was considered. It was found that under certain data, both parameters of total gross margin and total acreage are more than uncertain data. Given that water price variations resulted in tangible changes in wheat acreage, it is recommended to adopt appropriate policies to reduce its production risk.
Water shortage crisis is an issue that has led to drasticchanges in different agricultural policies, especially inarid and semi-arid areas. Uncertainty in the amount of resources,e.g. water, used for agricultural production entails risk forfarmers' income and cropping pattern changes. In the presentstudy, the robust optimization model was used for optimal allocationof arable lands of Khorasan Razavi Province underuncertainty. During the allocation, the effect of water inputprice variations on total gross margin and cropping patternwas considered. It was found that under certain data, both parametersof total gross margin and total acreage are more thanuncertain data. Given that water price variations resulted intangible changes in wheat acreage, it is recommended to adoptappropriate policies to reduce its production risk.
1- Jehad-Keshavarzi Organization Office of Statistics and Information Technology unpublished results (2011). Statistical Report of Irrigation Systems. Soil and Water Management Department, Iran.
2-Bagheri, M., & Moazzazi, F. (2010). Determining the optimal cropping pattern: Possibility programming application. Agricultural Economics Research, 1, 81-53.
3- Ben-Tal, A., & Nemirovski, A. (2000). Robust solutions of linear programming problems contaminated with uncertain data. Journal of Mathematical Programming, 88, 411–424.
4- Ben-Tal, A., & Nemirovski, A. (1999). Robust solutions of uncertain linear programs. Journal of Operations Research, Letters, 25, 1–13.
5- Bertsimas D. & Sim M. (2004). The price of robustness. Journal of Operations Research, 52 (1), 35–53.
6- Biswas, A., & Pal, B.B. (2005). Application of fuzzy goal programming technique to land use planning in agricultural system. Journal of Omega, 33(5), 391-398.
7- Chizari, A., Sharzehie, Gh., & Keramat Zadeh, A.( 2005). Determining the economic value of water with ideal programming approach (Case Study: Barez and Shirvan Dam). Economic Research, 71, 66-39.
8- El-Shishiny, H. (1988). A goal programming model for planning the development of newly reclaimed lands. Journal of Agricultural Systems, 26(4), 245-261.
9- Hassan Shahi, M. (2007). Optimal pattern (economic) of crops under risk (application of objective models - MOTAD, Advanced MOTAD, linear programming and quadratic), case study of Arsanjan
city. Economics Research, 43(1), 1-18.
10- Hazell, P.B.R. & Norton R.D. (1986). Mathematical programming for economic analysis in agriculture, Colliei MacMillan publisher, London, U.K., Pp. 387-.
11- Kohansal, M. & Zare, A. (2008). Determining the optimal cropping pattern consistent with sustainable agriculture using fractional fuzzy programming with multiple objectives. A Case Study in Northern Khorasan Province. Agricultural Economics and Development, 62, 33-1.
12- Oliveira, F., Volpi, N.M.P., & Sanquetta, C.R. (2003). Goal programming in a planning problem. Journal of Applied Mathematics and Computation, 140(1), 165-178.
13- Pfeiffer, L., & Lin, C.-Y.C. (2014). The effects of energy prices on groundwater extraction in agriculture in the High Plains Aquifer. American Journal of Agricultural Economics, 4(8), 213-222.
14- Rastgaripoor, F., & Sabouhi, M. (2009). Determining the cropping pattern using gray fuzzy programming (case study of Ghochan County). Journal of Agriculture and Natural Resources Science and Technology, 48, 413-405.
15- Sabouhi, M., & Soltani, Gh. (2008). Optimal cropping patterns in the basin area with emphasis on social benefits and net imports of virtual water: A case study of Khorasan region. Journal of Agriculture and Natural Resources Science and Technology, 43, 313-297.
16- Sharma, D. K., & Jana, R.K.( 2009). Fuzzy goal programming based genetic algorithm approach to nutrient management for rice crop planning. International Journal of Production Economics, 121(1),
224-232.
17- Sharma, D.K., Ghosh, D., & Alade, J.A. (2006).A fuzzy goal programming approach for regional rural development planning. Journal of Applied Mathematics and Computation, 176(1), 141-149.
18- Soltani, Gh., Zibaee, M., & Kahkha, A. (2008). Application of Mathematical programming in agriculture. Research Organization, Agricultural Extension and Education. Tehran.
19- Soyster, A.L. (1973). Convex programming with set-inclusive constraints and applications to inexact linear programming. Journal of Operations Research, 21, 1154–1157.
20- Yeh, C.H., & Labadie, J.W. (2003).Multiobjective planning for agricultural decision: An application. Agricultural Journal of Planning and Management, 23, 336-343.
21- Zeng, X., Kang, S., Li, F., Zhang, L., & Guo, P. (2010). Fuzzy multi-objective linear programming applying to crop area planning. Agricultural Water Management, 7(23), 233-241.
