Abstract
The issue of water resource management in the Sistan region has been complicated by water fluctuations of the Hirmand River in recent years. The decrease in the water flowing toward Sistan and followed by continuous droughts has caused a severe water crisis in this region. The critical situation of water resources in the Sistan region has faced a serious problem in the process of sustainable development in this region. Consequently, it has become more imperative to adopt effective approaches for optimal and efficient management of water, especially in the agricultural sector as it is the biggest water consumer in the Sistan region. This research focused on the optimal allocation of water to the agricultural sector with an emphasis on the water market by integrating the Stackelberg–Nash–Cournot equilibrium model and Nerlove’s supply model. The Stackelberg–Nash–Cournot equilibrium game was run with a metaheuristic algorithm composed of a dynamic genetic algorithm and a fuzzy programming method. Also, to cope with the challenges, tackle the future uncertainty, and provide more information for the adjustment of the agricultural irrigation pattern, the scenario-building technique was applied in which two parameters of irrigation coefficient and the amount of water allocated to the agricultural sector were changed. The results showed that the Hirmand 2 region has been allocated with the highest amount of water. The lowest amount of water is allocated to wheat and barley due to their low return, whereas the highest amount of water is allocated to onion and melon production. By creating a water market, the economic profit increases by 20,013 million IRR, and the inequity in water allocation changes by 0.02. The results of modeling the scenario of different irrigation coefficients and water allocated show that the economic profit increases to 695,152 and 6,109,136 million IRR when the irrigation coefficient increases to 50% and 70%, it increases to 474,550 million IRR when the amount of water allocated is increased, and it decreases to 834,946 million IRR when the amount of water allocated is decreased. The comparison of the allocation with and without a water market shows the significance and effectiveness of the water market. Accordingly, the establishment of a regional water market in the Sistan region not only changes the water allocated to the crops in the studied regions and the profit of the cropping pattern but also improves the income of the farmers and contributes to equity in water allocation among the regions. Also, the water market contributes to reducing the amount of water allocated per unit of economic profit. Given the supportive and constructive role of local and regional water markets, it is recommended to lay the ground for establishing this mechanism and optimally using it. In order to overcome the lack of water among crops and gain more economic profit, it is possible to implement the scenario of increasing irrigation efficiency using modern irrigation systems. According to the results of water allocation between regions and agricultural crops, it is suggested that low-yield crops such as wheat and barley have been removed from the cultivation pattern and replaced by high-yield crops such as onions, melons and alfalfa.
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References
AghaKouchak, A., Feldman, D., Hoerling, M., Huxman, T., & Lund, J. (2015). Water and climate: Recognize anthropogenic drought. Nature News, 524(7566), 409.
Agricultural Statistics, Ministry of Jihad Agriculture, Deputy of Planning and Economy, Tehran, Volume 1, 2017.
Alarcón, J., & Juana, L. (2016). The water markets as effective tools of managing water shortages in an irrigation district. Water Resources Management, 30(8), 2611–2625.
Al-Jamal, M. S., Ball, S., & Sammis, T. W. (2001). Comparison of sprinkler, trickle and furrow irrigation efficiencies for onion production. Agricultural Water Management, 46(3), 253–266.
Allan, J. A. (1993). Fortunately there are substitutes for water otherwise our hydro-political futures would be impossible. Priorities for Water Resources Allocation and Management, 13(4), 26.
Bhaduri, A., & Barbier, E. B. (2003). Water Transfer and International River Basin Cooperative Management: The Case of the Ganges. University of Wyoming.
Candler, W., & Townsley, R. (1982). A linear two-level programming problem. Computers & Operations Research, 9(1), 59–76.
Cai, Y., Xiao, J., He, Y., Guo, H., & Xie, Y. (2022). A bi-level multi-objective programming for water resources management under compound uncertainties in Dongjiang River, Greater Bay Area of China. Journal of Contaminant Hydrology, 104020.
Chakraei, I., Safavi, H. R., Dandy, G. C., & Golmohammadi, M. H. (2021). Integrated Simulation-Optimization Framework for Water Allocation Based on Sustainability of Surface Water and Groundwater Resources. Journal of Water Resources Planning and Management, 147(3), 05021001.
Dotaniya, M. L., Meena, V. D., Saha, J. K., Dotaniya, C. K., Mahmoud, A. E. D., Meena, B. L., Meena, M. D., Sanwal, R. C., Meena, R. S., Doutaniya, R. K., & Solanki, P. (2022). Reuse of poor-quality water for sustainable crop production in the changing scenario of climate. Environment, Development and Sustainability, 1–32,. https://doi.org/10.1007/s10668-022-02365-9
Drisya, J., & Sathish Kumar, D. (2022). Evaluation of the drought management measures in a semi-arid agricultural watershed. Environment, Development and Sustainability, 1–23,. https://doi.org/10.1007/s10668-021-02079-4
Elleuch, M. A., Anane, M., Euchi, J., & Frikha, A. (2019). Hybrid fuzzy multi-criteria decision making to solve the irrigation water allocation problem in the Tunisian case. Agricultural Systems, 176, 102644.
Ekhtiari, M., & Zandieh, M. (2022). A multi-objective bi-level stochastic programming for water sustainable supply and allocation problem. Journal of Industrial and Systems Engineering, 14(2), 1–31.
Fang, S., Guo, P., Li, M., & Zhang, L. (2013). Bilevel multiobjective programming applied to water resources allocation. Mathematical Problems in Engineering, 2013.
Feng, J., Tang, Y., Xue, S., & Zhang, K. (2022). Study on cooperative strategies of rural water environment governance PPP project between companies and farmers from the perspective of evolutionary game. Environment, Development and Sustainability, 24(1), 138–155.
Ghaffari Moghadam, Z., Moradi, A., Hashemi Tabar, S., & Sardar Shahraki, A. (2022). Optimal allocation of water resources in the agricultural sector by using the Stackelberg–Nash–Cournot model and emphasis on water market (case study: Sistan plain water transfer project). Ecohydrology, 9(1), 273–289.
Hausmann, C., & Patrick, S. (2013). Contingency Planning: Trade’s Role in Sustainable World Food Security. Aquatic Procedia, 1, 20–29.
Kavinya, P., & Phiri, M. A. R. (2014). Maize hectarage response to price and non-price incentives in Malawi. Scholarly Journal of Agricultural Science, 4(3), 142–151.
Kazemi, M., Bozorg-Haddad, O., Fallah-Mehdipour, E., & Chu, X. (2022). Optimal water resources allocation in transboundary river basins according to hydropolitical consideration. Environment, Development and Sustainability, 24(1), 1188–1206.
Khatibi, S., & Arjjumend, H. (2019). Water crisis in making in Iran. Grassroots Journal of Natural Resources, 2(3), 45–54.
Kosolapova, N. A., Matveeva, L. G., Nikitaeva, A. Y., & Molapisi, L. (2017). Modeling resource basis for social and economic development strategies: Water resource case. Journal of Hydrology, 553, 438–446.
Li, M., Li, J., Singh, V. P., Fu, Q., Liu, D., & 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.
Li, M., Xu, Y., Fu, Q., Singh, V. P., Liu, D., & Li, T. (2020). Efficient irrigation water allocation and its impact on agricultural sustainability and water scarcity under uncertainty. Journal of Hydrology, 586, 124888.
Lin, P., You, J., Gan, H., & Jia, L. (2020). Rule-based object-oriented water resource system simulation model for water allocation. Water Resources Management, 34(10), 3183–3197.
Liu, D., Liu, W., Fu, Q., Zhang, Y., Li, T., Imran, K. M., & Abrar, F. M. (2017). Two-stage multi-water sources allocation model in regional water resources management under uncertainty. Water Resources Management, 31(11), 3607–3625.
Lv, T., Xie, H., Lu, H., Zhang, X., & Yang, L. (2019). A game theory-based approach for exploring water resource exploitation behavior in the Poyang Lake Basin, China. Sustainability, 11(22), 6237.
Mahmoud, A. E. D., Franke, M., Stelter, M., & Braeutigam, P. (2020). Mechanochemical versus chemical routes for graphitic precursors and their performance in micropollutants removal in water. Powder Technology, 366, 629–640.
Nerlove, M. (1956). Estimates of the elasticities of supply of selected agricultural commodities. American Journal of Agricultural Economics, 38(2), 496–509.
Nerlove, M., Grether, D. M., & Carvalho, J. L. (2014). Analysis of economic time series: A synthesis. Academic Press.
Philpot, S. L., Johnson, P. A., & Hipel, K. W. (2017). Analysis of a brownfield management conflict in Canada. Hydrological Research Letters, 11(3), 141–148.
Ren, C., Li, Z., & Zhang, H. (2019). Integrated multi-objective stochastic fuzzy programming and AHP method for agricultural water and land optimization allocation under multiple uncertainties. Journal of Cleaner Production, 210, 12–24.
Sadati, S. K., Speelman, S., Sabouhi, M., Gitizadeh, M., & Ghahraman, B. (2014). Optimal irrigation water allocation using a genetic algorithm under various weather conditions. Water, 6(10), 3068–3084.
Sadegh, M., Mahjouri, N., & Kerachian, R. (2010). Optimal inter-basin water allocation using crisp and fuzzy Shapley games. Water Resources Management, 24(10), 2291–2310.
Sapino, F., Pérez-Blanco, C. D., Gutiérrez-Martín, C., & Frontuto, V. (2020). An ensemble experiment of mathematical programming models to assess socio-economic effects of agricultural water pricing reform in the Piedmont Region, Italy. Journal of Environmental Management, 267, 110645.
Silva, W. D. O., Morais, D. C., & Urtiga, M. M. (2022). An Integrative negotiation model to deal with conflicts toward water resources management: A case study in Brazil. Environment, Development and Sustainability, 24(8), 10443–10469.
Sohrabi, M., Ahani Amineh, Z. B., Niksokhan, M. H., & Zanjanian, H. (2022). A framework for optimal water allocation considering water value, strategic management and conflict resolution. Environment, Development and Sustainability, 1–32,. https://doi.org/10.1007/s10668-022-02110-2
The United Nations. UN agriculture chief calls for stronger water management, improved access for small farmers. 2017.
Tu, Y., Shi, H., Zhou, X., & Lev, B. (2022). Optimal trade-off of integrated river basin water resources allocation considering water market: A bi-level multi-objective model with conditional value-at-risk constraints. Computers & Industrial Engineering, 169, 108160.
Wang, Y., Yang, J., & Chang, J. (2019). Development of a coupled quantity-quality-environment water allocation model applying the optimization-simulation method. Journal of Cleaner Production, 213, 944–955.
Wu, R. S., Liu, J. S., Chang, S. Y., & Hussain, F. (2017). Modeling of mixed crop field water demand and a smart irrigation system. Water, 9(11), 885.
Xu, J., Lv, C., Zhang, M., Yao, L., & Zeng, Z. (2015). Equilibrium strategy-based optimization method for the coal-water conflict: A perspective from China. Journal of Environmental Management, 160, 312–323.
Xu, Z., Yao, L., Zhou, X., Moudi, M., & Zhang, L. (2019). Optimal irrigation for sustainable development considering water rights transaction: A Stackelberg–Nash–Cournot equilibrium model. Journal of Hydrology, 575, 628–637.
Yao, L., Xu, Z., & Chen, X. (2019). Sustainable water allocation strategies under various climate scenarios: A case study in China. Journal of Hydrology, 574, 529–543.
Yue, Q., Zhang, F., Zhang, C., Zhu, H., Tang, Y., & Guo, P. (2020). A full fuzzy-interval credibility-constrained nonlinear programming approach for irrigation water allocation under uncertainty. Agricultural Water Management, 230, 105961.
Zeng, X. T., Li, Y. P., Huang, G. H., & Liu, J. (2016). Modeling water trading under uncertainty for supporting water resources management in an arid region. Journal of Water Resources Planning and Management, 142(2), 04015058.
Zeng, Y., Li, J., Cai, Y., Tan, Q., & Dai, C. (2019). A hybrid game theory and mathematical programming model for solving trans-boundary water conflicts. Journal of Hydrology, 570, 666–681.
Zhang, Z., Lei, X., Tian, Y., Wang, L., Wang, H., & Su, K. (2019). Optimized scheduling of cascade pumping stations in open-channel water transfer systems based on station skipping. Journal of Water Resources Planning and Management, 145(7), 05019011.
Zhang, Y., Lu, Y., Zhou, Q., & Wu, F. (2020). Optimal water allocation scheme based on trade-offs between economic and ecological water demands in the Heihe River Basin of Northwest China. Science of the Total Environment, 703, 134958.
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Ghaffari Moghadam, Z., Moradi, E., Hashemi Tabar, M. et al. Developing a Bi-level programming model for water allocation based on Nerlove’s supply response theory and water market. Environ Dev Sustain 25, 5663–5689 (2023). https://doi.org/10.1007/s10668-022-02658-z
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DOI: https://doi.org/10.1007/s10668-022-02658-z