Optimizing Cropping Pattern and Water Allocation using Stackelberg and Meta-heuristic Techniques in Sistan Region

Document Type : Complete scientific research article


1 Corresponding Author, Assistant Prof., Dept. of Agricultural Economics, Agriculture Institute, Research Institute of Zabol, Zabol, Iran.

2 Associate Professor of Agriculture Economics, Faculty of Management and Economic, University of Sistan and Baluchestan, Zahedan, Iran.

3 Assistant Prof., Dept. of Agronomy and Plant Breeding, Agriculture Institute, Research Institute of Zabol, Zabol, Iran.


Background and objective: Water is a critical input for agricultural production and plays an important role in the sustainable development of the agricultural sector and the economic development of other sectors. Water shortage is one of the major challenges that most countries in the world are struggling with. The great importance of determining the optimal cropping pattern of crops and irrigation allocation planning in the water shortage conditions prevailing in Iran's watersheds is not hidden from anyone. This study aimed to optimize water allocation and determine the optimal cropping pattern of crops in five cities of the Sistan region under different management scenarios.
Materials and methods: In this study, a model with a two-level planning approach, the Stackelberg game framework, and a genetic algorithm, was developed to optimize the water allocation between irrigated areas and crops, as well as to determine the optimal cropping area in 5 cities of Sistan region (including Hamon, Hirmand, Zahak, Nimroz and Zabol) to confront different water conditions. Selected products include wheat, barley, onion, melon, watermelon and alfalfa. The problem was solved in the form of nine scenarios, including three scenarios of irrigation efficiency, three scenarios of climatic conditions, and three scenarios of low irrigation conditions, and compared with the baseline scenario.
Results: For water allocation among the studied regions in the baseline scenario, the most and least water was allocated to Zahak and Hirmand areas, respectively. Among the studied crops, the most water was allocated to the melon due to its low water requirement and high economic value compared to other crops, and the least amount of water was allocated to the alfalfa due to its high water requirement; also the melon with 13503.5 ha had the highest cropping area and alfalfa with 4.85 ha had the lowest cropping area in a total of five cities. The total cropping area obtained by the model was 18240.32 ha. The value of the Gini coefficient was 0.0053, which is small and close to zero, indicating that the water allocation between the regions was fair. The total interest rate obtained in the baseline scenario was 5.06 ×1013, which by applying irrigation efficiency scenarios of 50 and 70 percent, the amount of profit has increased by 12% and 34%, respectively, and the cultivated area by 27% and 47% compared to the baseline scenario. And in normal and wetyear conditions, the amount of total profit has increased by 28% and 54%, respectively, and the cultivated area by 40% and 65% compared to the baseline scenario. By applying the low irrigation scenario, the interest rate decreases compared to the baseline scenario, associated with the saving of a large volume of irrigation water, which leads to an increase in the cropping area of crops with higher economic efficiency. Therefore, by applying various scenarios, the cropping pattern moves towards crops with less water requirement and higher economic value.
Conclusion: According to the results, more water has been allocated to crops with higher economic value and less water requirement. Therefore, if crops with less interest rate compared to their water use and crops with high water requirement are removed from the cropping pattern and crops with higher economic efficiency and less water requirement are replaced in the cropping pattern, it can be a good solution to confront water shortage conditions. The increase in irrigation efficiency increased the total interest, thus it is recommended to save water used by plants through the improvement of irrigation technology and increase irrigation efficiency. The proposed model in this study can be employed for correct and efficient planning for agriculture and water resource management in various conditions.


Main Subjects

1.Rafiee, V., Shourian, M., and Attari, J. 2017. Optimum Crop Patterning by Integrating SWAT and the Harmony Search Optimization Algorithm, Iran - Water Resources Research. 13: 3. 73-88. (In Persian)
2.Li, M., Cao, X., Liu, D., Fu, Q., Li, T., and Shang, R. 2022. Sustainable management of agricultural water and land resources under changing climate and socio-economic conditions: A multi-dimensional optimization approach, Agricultural Water Management. 259:107235.
3.Asadi, E., Shirzadi Laskukalayeh, S., and Mehrjou, A. 2021. The Application of Asymmetric Nash Solution in Optimal Allocation of Water Resources (Case study: Qarehsou basin), J. of Water and Soil Conservation, 28: 2. 43-62. (In Persian)
4.Zeng, Y., Li, J., Cai, Y., Tan, Q., and Dai, C. 2019. A hybrid game theory and mathematical programming model for solving trans-boundary water conflicts, Journal of Hydrology. 570: 666-681.
5.Pereira, L.S. 2017. Water, agriculture and food: challenges and issues, Water Resources Management. 31: 10. 2985-2999.
6.Lalehzari, R., Nasab, B., Moazed, H., and Haghighi, A. 2015. Multiobjective management of water allocation to sustainable irrigation planning and optimal cropping pattern, J. Irrig. Drain. Eng. 142: 1. 1-10.
7.Abdulbaki, D., Al-Hindi, M., Yassine, A., and Abou Najm, M. 2017. An optimization model for the allocation of water resources, Journal of Cleaner Production. 164: 994-1006.
8.Al-Jawad, J.Y., Alsaffar, H.M., Bertram, D., and Kalin, R.M. 2019. A comprehensive optimum integrated water resources management approach for multidisciplinary water resources management problems, Journal of environmental management. 239: 211-224.
9.Martinsen, G., Liu, S., Mo, X., and Bauer-Gottwein, P. 2019. Joint optimization of water allocation and water quality management in Haihe River basin, Science of the total environment. 654: 72-84.
10.Milan, S.G., Roozbahani, A., and Banihabib, M.E. 2018. Fuzzy optimization model and fuzzy inference system for conjunctive use of surface and groundwater resources, Journal of hydrology. 566: 421-434.
11.Ye, Q., Li, Y., Zhuo, L., Zhang, W., Xiong, W., Wang, C., and Wang, P. 2018. Optimal allocation of physical water resources integrated with virtual water trade in water scarce regions: A case study for Beijing, China, Water research. 129: 264-276.
12.Nori, S., Shahraki, J., and Sardar Shahraki, A. 2019. Optimal allocation of water resources in Sistan Chah-Nime reservoirs under the water and soil management scenario, J. of Water and Soil Conservation, 25: 6. 25-46. (In Persian)
13.Li, M., Fu, Q., Singh, V.P., Liu, D., Li, T., and Zhou, Y. 2020. Managing agricultural water and land resources with tradeoff between economic, environmental, and social considerations: A multi-objective non-linear optimization model under uncertainty, Agricultural systems. 178: 102685.
14.Ren, C.F., Li, Z.H., and Zhang, H.B. 2019. Integrated multi-objective stochastic fuzzy pro-gramming and AHP method for agricultural water and land optimization allocation under multiple uncertainties, J. Clean. Prod. 210: 12-14.
15.Regulwar, D.G., and Gurav, J.B. 2011. Irrigation planning under uncertainty-a multi objective fuzzy linear programming approach, Water Resour. Manage. 25: 1387-1416.
16.Mosleh, Z., Salehi, M.H., Fasakhodi, A.A., Jafari, A., Mehnatkesh, A., and Borujeni, I.E. 2017. Sustainable allocation of agricultural lands and water resources using suitability analysis and mathematical multi-objective programming, Geoderma. 303: 52-59.
17.Amanat Behbahani, L., Moghaddasi, M., Ebrahimi, H., and Babazadeh, H. 2020. Optimal water allocation and distribution management in irrigation networks under uncertainty by multi‐stage stochastic case study: Irrigation and drainage networks of Maroon, Irrigation and Drainage. 69: 4. 531-545.
18.Linker, R. 2020. Unified framework for model-based optimal allocation of crop areas and water, Agricultural Water Management. 228: 105859.
19.Li, M., Li, J., Singh, P., Fu, Q., Liu, D., and Yang, G. 2019. Efficient allocation of agricultural land and water resources for soil environment protection using a mixed optimization-simulation approach under uncertainty, Geoderma. 353: 55-69.
20.Xie, Y. L., Xia, D. X., Ji, L., and Huang, G. H. 2018. An inexact stochastic-fuzzy optimization model for agricultural water allocation and land resources utilization management under considering effective rainfall, Ecological indicators. 92: 301-311.
21.Hao, L., Su, X., and Singh, V.P. 2018. Cropping pattern optimization considering uncertainty of water availability and water saving potential, International Journal of Agriculture and Biological Engineering. 11: 1. 178-186.
22.Valizadegan, E., and Dindarsooha, A. 2021. Model of optimal allocation of water and land to agricultural crops in deterministic and stochastic conditions, Water and soil resources conservation. 10: 3. 31-46. (In Persian)
23.Emamifar, S., Mohammadian, F., Mohammadi, R., Abadi, A., and AliMadadi, M. 2021. Investigation of Optimum Cropping Pattern Proportional to Allocable Water and Balancing Aquifer (Case Study of Qom-Kahak Study Area), Water and soil resources conservation. 9: 4. 35-55. (In Persian)
24.Meftah Halaghi, M., Ghorbani, KH., Keramatzadeh, A., and Salarijazi, M. 2021. Application of Game Theory to Determining Optimal Harvesting of Water Resources and Determination of Optimal cropp pattern (Case study: Gharesu basin), J. of Water and Soil Conservation, 27: 5. 69-87. (In Persian)
25.Siasar, H., and Honar, T. 2017. Optimization of Water Allocation Pattern crops using a Genetic Algorithm. 3rd. International Conference on Agricultural Engineering and Natural Resources. July. (In Persian)
26.Reports of Iran Meteorological Organization, Climatology Research Institute of the country, 2014. (In Persian)
27.Sardar Shahraki, A. 2016. Optimal Allocation of Water Resources of Hirmand Basin by Application of Game Theory and Evaluating the Managerial Scenarios. PhD Thesis in agricultural economic university of Sistan and Baluchestan. (In Persian)
28.Agricultural Statistics. 2016. Ministry of Agricultural Jihad, Deputy Planning and Economic Department, Tehran, first volume. (In Persian)
29.Mas-Colell, A., Whinston, M.D., and Green, J.R. 1995. Microeconomic theory. Appendix J. Harvard University. 199p.
30.Ankur, S., Malo, P., Frantsev, A., and Deb, K. 2014. Finding optimal strategies in a multi-period multi-leader–follower Stackelberg game using an evolutionary algorithm, Computers & Operations Research. 41: 374-385.
31.Safari, N. Optimal Surface Water Resources Allocation by Public and Market-Based Mechanisms with the Approach of Cooperative Game; Case Studies. Ph.D. Thesis university of Tabriz. (In Persian)
32.Gibbons, R. 1997. An Introduction to Applicable Game Theory, Journal of Economic Perspective. 11: 1. 127-149.
33.Hu, Z., Wei, C., Yao, L., Li, C., and Zeng, Z. 2016. Integrating equality and stability to resolve water allocation issues with a multiobjective bilevel programming model, J. Water Resour Plann. Manage. 142: 7. 1-12.
34.Xu, Z., Yao, L., Zhou, X, Moudi, M., and Zhang, L. 2019. Optimal irrigation for sustainable development considering water rights transaction: A Stackelberg-Nash-Cournot equilibrium model, Journal of Hydrology. 575: 628-637.
35.Ghaffari Moghadam, Z., Moradi, E., Hashemitabar, M., and Sardarshahraki, A. 2022. Optimal Allocation of Water Resources in the Agricultural Sector by Using the Stackelberg-Nash-Cournot Modeland emphasis on water market (Case Study: Sistan Plain Pipe Water Transfer Project), Ecohydrology. 9: 1. 273-289.
36.Ghaffari Moghadam, Z., Moradi, E., Hashemi Tabar, M., and Sardar Shahraki, A. 2022. Developing a Bi-level programming model for water allocation based on Nerlove’s supply response theory and water market, Environment, Development and Sustainability. https://doi.org/10.1007/ s10668-022-02658-z.
37.Ministry of Energy. 2011. River Water Resources Planning Report and Well Reservoirs in Sistan, Volume II, Regional water Company of Sistan and Baluchistan Province, Zabol.
38.Kalbali, E., Sabouhi, M., and Ahmadpour, M. 2017. Strategies of Voshmgir Dam Water Allocation Using Two-Stage Stochastic Programming, Journal of water and soil. 30: 6. 1832-1847. (In Persian)
39.Akbari, M., Najafi Alamdarlo, H., and Mossavi, S.H. 2019. Impacts of Climate Change and Drought on Income Risk and Crop Pattern in Qazvin Plain Irrigation Network, Journal of water Research in agriculture. 33: 2. 265-281. (In Persian)
40.Parhizkari, A., Sabouhi, M., Ahmadpour, M., and Badie Barzin, H. 2016. Assessment of the Effects of Deficit Irrigation and Decrease in Water Allocation on Agricultural Sector Production in Qazvin Province, Journal of water Research in agriculture. 30: 2. 173-185. (In Persian)