Document Type: Original Article

Authors

1 Agricultural Sciences and Natural Resources University of Khuzestan

2 Assistance Professor of agricultural economics University of Zabol

3 Assistance Professor of agricultural economics Research Center for Agriculture and Natural Resources

Abstract

Sustainability in agricultural is determined by aspects like economy, society and environment. Multi-objective programming (MOP) model has been a widely used tool for studying and analyzing the sustainability of agricultural system. However, optimization models in most applications are forced to use data which is uncertain. Recently, robust optimization has been used as an optimization model that incorporates uncertainty. This paper develops a framework for environmental-economic decision making that includes the environmental and economic sustainability criteria for determining an optimal allocation of agricultural areas that cover an irrigation network under uncertain data. The primary uncertain parameter of the robust model was quantity of available water for each season. Application of the proposed model to the case study of the right side of Nekooabad irrigation network in the province of Isfahan, Iran, demonstrates the reliability and flexibility of the model. The results show that that the optimal total gross margin decreases with higher robustness levels. To compensate loss of gross margin of farmers in the robust pattern, efficiency enhancement policies emphasized.

Highlights

  • A mathematical programming model was proposed to optimize the cropping pattern with the economic-environmental objectives.
  • In order to apply the uncertainty conditions, a robust optimization method was used in the proposed model.
  • In order to evaluate the proposed model, the right fringe of irrigation and drainage network of Nekoobad in Isfahan province, Iran was selected as a case study.
  • By increasing the protection of the system against uncertain data, the gross profit of the optimal model decreased.

Keywords

Main Subjects

Bell, S., & Morse, S. (2008). Sustainability indicators: Measuring the immeasurable? London, Earthscan.

Ben-Tal, A., & Nemirovski, A. (1999). Robust solutions to uncertain programs. Operations Research Letters, 25,1-13.

Ben-Tal, A., & Nemirovski, A. (2000). Robust solutions of linear programming problems contaminated with uncertain data. Journal of Mathematical Programming, 88,411-424.

Bertsimas, D., & Sim, M. (2004). The price of robustness. Journal of Operations Research Letters, 52(1), 35–53.

Chang, Y.C., Hung, F.W., & Lee, M.T., (2008). A system dynamic based DSS for sustainable coral reef management in Kenting Coastal Zone, Taiwan. Ecological Modeling, 211 (1), 153–168.

Chen, H., Yang, W. G., Liang, X. Y., & Wang, T. (2010). Multi-scale modeling of land use based on the MAS from field to village: A case study for Mengcha Village of Mizhi County of Shaanxi Province. Geographical Research, 29, 1519–1527.

Chung, G., Lansey, K., & Bayraksan, G. (2009). Reliable water supply system design under uncertainty. Environmental Modelling and Software, 24, 449–462.

Cohon, J.L. (1978). Multi objective programming and planning. Academic Press, New York.

Eshraghi Samani, RE, & Poursaeed, A. (2015). Cropping pattern and comparative advantage of agricultural products in Ilam Province.International Journal of Agricultural Management and Development, 5(3): 235-243.

Department of Regional Planning and Development (2010). District statistical yearbook (Annual time series data from 1986 to 2009), Isfahan, Iran.

Diamond, J.T., & Wright J.R. (1989). Efficient land allocation. Journal of Urban Planning and Development, 115, 81–96.

El-Ghaoui, L., & Lebret, H. (1997). Robust solutions to least-square problems to uncertain data matrices. SIAM Journal on Matrix Analysis and Applications, 18و1035-1064.

El-Ghaoui, L., Oustry, F., & Lebret, H. (1998). Robust solutions to uncertain semidefnite programs. SIAM Journal on Optimization, 9,33-52.

Gibert, K.C., Holmes, D.D., & Rossenthal, R.E. (1985). A multi objective discrete optimization model for land allocation. Management Science, 31, 1509–1552.

Gomez-Limon, A., & Riesgo, L. (2009).  Alternative approaches to the construction of a composite indicator of agricultural sustainability: An application to irrigated agriculture in the Duero basin in Spain. Journal of Environmental Management, 90:3345–3362.

Hafkamp, W., & Nijkamp, P. (1968). Integrated economic-environmental-energy policy and conflict analysis. Journal of Policy Modelling, 8,551-576.

Hansen, J. (1996). Is agricultural sustainability a useful concept? Agricultural systemsSystems, 50(2), 117-143.

Hardaker, J.B., Huirne, R.B.M., Anderson, J.R., & Lien, G. (2004). Coping with risk in agriculture. (2 Ed.), CABI Pulishing, London, UK, p. 332

Iranian Ministry of Energy, Office of Dams and Agricultural Irrigation Networks Control. (2003). Statistical Report of Long-Term Development Strategies for Iran’s Water resources, Unpublished result. Tehran, Iran.

Isfahan Regional Water Organization, Department of Equipment and Development of Agricultural Irrigation Networks. (2008). Selected Water Resources Data, Unpublished result. Isfahan, Iran.

Jihad-e Agriculture Organization, Soil and Water Management Department. (2010). Statistical Report of Irrigation Systems in Esfahan Province, Unpublished result. Isfahan, Iran.

Larimian, T.,  Zarabadi, Z., & Sadeghi, A. (2013).Developing a fuzzy AHP model to evaluate environmental sustainability from the perspective of Secured by Design scheme-A case study. Biological Sciences, 7, 25–36.

Monteith, J.L. (1990). Can sustainability be quantified? Indian Journal of Dry land Research and Development, 5 (1), 1-5.

Morse, S., McNamara, N., Acholo, M., & Oknoli, B. (2000). Visions of Sustainability. Ashgate, Hampshire, UK, pp. 5–45.

Romero, C., & Rehman, T. (2003). Multiple criteria analysis for agricultural decisions. 2th Edition, British Library cataloguing, UK, pp47-61.

Sabouni, M., & Mardani, M. (2013). Application of robust optimization approach for agricultural water resource management under uncertainty. Journal of Irrigation and Drainage Engineering, 139, 571–581.

Sahinidis, N., & Tawarmalani, M. (2005). GAMS/BARON Solver Manual. Arki Consulting Development, Bagsvaerdvej, Denmark, pp.233.

Seppelt, R., & Voinov, A. (2003). Optimization methodology for land use patterns valuation based on multiscale habitat pattern comparison. Ecological Modeling, 168 (3), 217–231.

Soyster, A. L.  (1973). Convex programming with set-inclusive constraints and applications to inexact linear programming. Operations Research, 21,1154–1157.

Stewart, T.J., Janssen, R., & Herwijnen, M. (2004). A genetic algorithm approach to multibjective land use planning. Computers & Operation Research, 31, 2293–2313.

Tiwari , D.N.,  Loof , R., & Paudyal,  G.N. (1999). Environmental-economic decision-making in lowland irrigated agriculture using multi-criteria analysis technique. Agricultural Systems, 60, 99-112.

Ying-bin, H., & Wei-min, C. (2016). Linking a farmer crop selection model (FCS) with an agronomic model (EPIC) to simulate cropping pattern in Northeast China. Journal of Integrative Agriculture, 15(10), 2417-2425.

Yu, Q. Y., Wu, W. B., Tang, H. J., Yang, P., Li,  Z. G., Xia, T., Liu, Z. H., & Zhou, Q. B. (2013). An agent-based model for simulating crop pattern dynamics at a regional scale: Model framework. Scientia Agricultura Sinica, 46, 3266–3276.

Yunlong, C., & Smit, B. (1994). Sustainability in agriculture: A general review. Agricultural Ecosystem and Environment, 49 (2), 299–307.

Zekri, S., & Romero, C. (1993). Public and private compromises in agricultural water management. Journal of Environmental Management, 37, 281-290.