| تعداد نشریات | 127 |
| تعداد شمارهها | 7,196 |
| تعداد مقالات | 77,227 |
| تعداد مشاهده مقاله | 157,180,516 |
| تعداد دریافت فایل اصل مقاله | 118,386,807 |
استفاده از تئوری بازیها در بازتخصیص آب در میان بهرهبرداران بخش کشاورزی بهمنظور افزایش کارایی مصرف آب | ||
| تحقیقات آب و خاک ایران | ||
| دوره 57، شماره 3، خرداد 1405، صفحه 589-610 اصل مقاله (1.41 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2026.403271.670016 | ||
| نویسندگان | ||
| محمد هاشم صرافها1؛ شیدا کاکاوند1؛ معصومه اسلادات هاشمی2؛ حامد مازندرانی زاده* 3 | ||
| 1دانش آموخته کارشناسی ارشد مدیریت منابع آب، دانشگاه بین المللی امام خمینی(ره)، قزوین، ایران. | ||
| 2دانش آموخته دکتری گروه مهندسی علوم و مهندسی آب، دانشکده فنی مهندسی، دانشگاه بین المللی امام خمینی (ره)، قزوین، ایران. | ||
| 3دانشیار گروه مهندسی آب، دانشگاه بین المللی امام خمینی، قزوین | ||
| چکیده | ||
| در سالهای اخیر، آب اختصاصیافته به شبکه آبیاری دشت قزوین به حدود نصف حقابه مصوب آن کاهشیافته است، بهگونهای که از 250 میلیون مترمکعب در سال، به حدود 120 میلیون مترمکعب کاهشیافته است. بررسی وضعیت فعلی نشان میدهد علاوه بر کاهش 50 درصدی منابع ورودی، الگوی توزیع آب میان بهرهبرداران بدون تغییر باقیمانده است. هدف از این تحقیق، باز توزیع آب میان بهرهبرداران شبکه آبیاری قزوین باهدف رفع اختلاف میان بهرهبرداران است. برای این منظور ابتدا درآمد هر بهرهبردار در شرایط فعلی (عدم همکاری) محاسبه شد. سپس با فرض شکلگیری همکاری کامل، الگوریتم ژنتیک برای توزیع بهینه ۱۲۲ میلیون مترمکعب آب در شبکه بهکار گرفته شد. در ادامه، برای ترغیب بهرهبرداران به مشارکت، سود مازاد حاصل از همکاری با استفاده از تئوری ارزش شپلی میان آنان بازتوزیع گردید. نتایج نشان میدهد درصورتیکه بهرهبرداران با هم در برداشت از آب همکاری نمایند، نهتنها همگی سودی بیش از وضعیت فعلی کسب خواهند نمود، بلکه مجموع سودی که نصیب آنها میشود افزایش چشمگیری داشته و حدود ۱۰۴ درصد (از 902/8 به 233/18 میلیون دلار) بیشتر از وضعیت فعلی خواهد شد. بهکارگیری رویکرد ترکیبی الگوریتم ژنتیک و تئوری ارزش شپلی میتواند در مدیریت تعارضات، افزایش عدالت در توزیع منابع و ارتقای بهرهوری اقتصادی شبکههای آبیاری مؤثر واقع شود. | ||
| کلیدواژهها | ||
| الگوریتم ژنتیک؛ باز تخصیص آب؛ شبکه آبیاری؛ تئوری ارزش شپلی | ||
| مراجع | ||
|
Abdolmanafi Jahromi, N. & Asadi, M. (2024). Review and analysis of macro indicators of the water sector in the last quarter of 1402 (Quarterly Report 4). Monthly magazine of expert reports of the Islamic Consultative Assembly Research Center. 32(1), e19700 doi: 10.22034/report.2024.16749.1698. (In Persian). Abed-Elmdoust, A., Kerachian, R., & Ziari, S. (2016). Evaluating the Relative Power of Water Users in Inter-Basin Water Transfer Systems. Water Resources Management, 30(11), 3863–3885. https://doi.org/10.1007/s11269-016-1407-1 Abedi. S, (2020). Water Governance and Evaluation of its Impacts on Water and Food Security, Journal of Water and Sustainable Development, 7(1), 1-12. (In Persian). Banihashemi, S., Eslamian, S. S., & Nazari, B. (2021). Prediction of Local Alterations in the Relative Amounts of Temperature and Precipitation Caused by Climate Change in Near and Far Future, and Drought Investigation Using SPI and SPEI Indices in Qazvin Plain, Iran. Journal of Hydrology and Soil Science, 25(2), 25–44. https://www.magiran.com/paper/2328026 LK - https://www.magiran.com/paper/2328026 Bi, F., Zhou, H., Zhu, M., & Wang, W. (2022). Economic benefit evaluation of water resources allocation in transboundary basins based on particle swarm optimization algorithm and cooperative game model—A case study of Lancang-Mekong River Basin. PLOS ONE, 17(7), e0265350-. https://doi.org/10.1371/journal.pone.0265350 Boyd, N. T., Gabriel, S. A., Rest, G., & Dumm, T. (2023). Generalized Nash equilibrium models for asymmetric, non-cooperative games on line graphs: Application to water resource systems. Computers & Operations Research, 154, 106194. https://doi.org/https://doi.org/10.1016/j.cor.2023.106194 Bulukazari, S., Babazadeh, H., Ebrahimipak, N., Mousavi-Jahromi, S.-H., & Ramezani Etedali, H. (2022). Optimization of water and land allocation in salinity and deficit- irrigation conditions at farm level in Qazvin plain. PLOS ONE, 17(7), e0269663. https://doi.org/10.1371/journal.pone.0269663 Dastjerdi, S. Z., Sharifi, E., Rahbar, R., & Saghafian, B. (2022). Downscaling WGHM-Based Groundwater Storage Using Random Forest Method: A Regional Study over Qazvin Plain, Iran. Hydrology, 9(10). https://doi.org/10.3390/hydrology9100179 Degefu, D. M., He, W., Yuan, L., & Zhao, J. H. (2016). Water Allocation in Transboundary River Basins under Water Scarcity: a Cooperative Bargaining Approach. Water Resources Management, 30(12), 4451–4466. https://doi.org/10.1007/s11269-016-1431-6 Dinar, A., & Howitt, R. E. (1997). Mechanisms for allocation of environmental control cost: empirical tests of acceptability and stability. Environmental Management, 49(2), 183–203. Fakhar, M. S., & Kaviani, A. (2022). Evaluation of FAO Wapor Product and PYSEBAL Algorithm in Estimating the Amount of Water Consumed. Soil and Water Research, 37(3), 487–502. https://doi.org/10.22067/jsw.2023.81695.1267. (In Persian). FAO. 2014. Water Governance for Agriculture and Food Security, a FAO initiative to minimize its environmental impact and promote greener communications. Other documents can be consulted at www.fao.org. Fisvold, G. B., & Caswell, M. F. (2000). Transboundary water management: game theoretic lessons for projects on the US–Mexico border. Journal of Agricultural Economics 24, 101–111. Fu, J., Zhong, P., Xu, B., Zhu, F., Chen, J., & Li, J. (2021). Comparison of Transboundary Water Resources Allocation Models Based on Game Theory and Multi-Objective Optimization. Water, 13, 1421. https://doi.org/10.3390/w13101421 Ghaffari Moghadam, Z., Moradi, E., Hashemi Tabar, M., & Sardar Shahraki, A. (2023). Developing a Bi-level programming model for water allocation based on Nerlove’s supply response theory and water market. Environment, Development and Sustainability, 25(6), 5663–5689. https://doi.org/10.1007/s10668-022-02658-z Hashemi, S. R., Tabesh, M., & Ataeekia, B. (2024). Multi-objective optimization of water distribution systems using game theory and genetic algorithms. Water Resources Planning and Management, 150(3). https://doi.org/10.1061/JWRMD5.WRENG-5842 Hashemi, V., Taleai, M., & Abolhasani, S. (2024). Enhancing agricultural land valuation in land consolidation projects through cooperative game theory and genetic algorithm optimization. Habitat International, 152, 103157. https://doi.org/10.1016/J.HABITATINT.2024.103157 Hemati, H., & Abrishamchi, A. (2020). Water allocation using game theory under climate change impact (case study: Zarinehrood). Journal of Water and Climate Change, 12(3), 759–771. https://doi.org/10.2166/wcc.2020.153 Hosseini, S. M. and Mazandarani Zadeh, H. (2025). Comparison of the ability of inverse demand function and artificial neural network to predict crop prices (Case Study: Qazvin Plain Irrigation Network). Irrigation Sciences and Engineering, 48(2), 35-47. doi: 10.22055/jise.2024.45614.2109. (In Persian). Imani, S., Niksokhan, M. H., Delavar, M., & Safari Shali, R. (2023). Water allocation sustainability assessment in climate change: a modeling approach using water footprint and just policy. Journal of Water and Climate Change, 14(11), 4261–4272. https://doi.org/10.2166/wcc.2023.534. Jahromi, N. S, & Asadi.M. (2024). Review and Analysis of Macroeconomic Indicators of the Water Sector in the Final Quarter of 1402 (Fourth Quarterly Report). Monthly Expert Reports of the Research Center of the Islamic Consultative Assembly. . (In Persian). Janjua, S., An-Vo, D.-A., Reardon-Smith, K., & Mushtaq, S. (2025). A Three-stage Cooperative Game Model for Water Resource Allocation Under Scarcity Using Bankruptcy Rules, Nash Bargaining Solution and TOPSIS. Water Resources Management. https://doi.org/10.1007/s11269-025-04123-8. Kakavand, S. , Mazandarani zadeh, H. and Ramezani Etedali, H. (2023). Optimal Redistribution of Water among Agricultural Sector Operators Using a Fuzzy Multi-objective Optimization Model. Irrigation Sciences and Engineering, 46(1), 77-93. doi: 10.22055/jise.2021.37122.1966. (In Persian). Kayhomayoon, Z., Milan, S. G., Arya Azar, N., Bettinger, P., Babaian, F., & Jaafari, A. (2022). A Simulation-Optimization Modeling Approach for Conjunctive Water Use Management in a Semi-Arid Region of Iran. In Sustainability (Vol. 14, Issue 5). https://doi.org/10.3390/su14052691 Khorshidi, M. S., Nikoo, M. R., Al-Rawas, G., Bahrami, N., Al-Wardy, M., Talebbeydokhti, N., & Gandomi, A. H. (2024). Integrating agent-based modeling and game theory for optimal water resource allocation within complex hierarchical systems. Journal of Cleaner Production, 482, 144164. https://doi.org/10.1016/J.JCLEPRO.2024.144164 Madani, K. (2010). Game theory and water resources. Journal of Hydrology, 381(3), 225–238. https://doi.org/https://doi.org/10.1016/j.jhydrol.2009.11.045 Mazandarani zadeh, hamed, & Hoseini, M. (2023). Investigating the effect of agricultural product price forecasting on groundwater level using systems dynamics, in order to simultaneously maintain the welfare of farmers and groundwater resources. Iranian Journal of Soil and Water Research, 53(11), 2565–2582. https://doi.org/10.22059/ijswr.2022.345131.669305. (In Persian). Mazandarani zadeh, H. and Hosseini, S. M. (2025). Assessing the Economic Efficiency of Water Distribution in the Agricultural Sector through Crop Pattern Modification (Case Study: Qazvin Plain Irrigation Network). Irrigation Sciences and Engineering, 48(1), 39-57. doi: 10.22055/jise.2023.43268.2061. (In Persian). Mehrparvar, Milad, Ahmadi, Azadeh, & Safavi, Hamid Reza. (2019). Resolving water allocation conflicts using WEAP simulation model and non-cooperative game theory. SIMULATION, 96(1), 17–30. https://doi.org/10.1177/0037549719844827 Mirzaei-Nodoushan, F., Bozorg-Haddad, O., & Loáiciga, H. A. (2022). Evaluation of cooperative and non-cooperative game theoretic approaches for water allocation of transboundary rivers. Scientific Reports, 12(1), 3991. https://doi.org/10.1038/s41598-022-07971-1 Moghaddam, H. K., Javadi, S., Randhir, T. O., & Kavehkar, N. (2022). A Multi-Indicator, Non-Cooperative Game Model to Resolve Conflicts for Aquifer Restoration. Water Resources Management, 36(14), 5521–5543. https://doi.org/10.1007/s11269-022-03310-1 Parrachino, I., Dinar, A., & Patrone, F. (2006). Cooperative game theory and its application to natural, environmental, and water resource issues: 3. Application to water resources. In World Bank Policy Research Working Paper (Issue 4074). Rashidi, M., Talebi, A., Raeisi, A., & Dezfoulian, M. (2022). Application of cooperative game theory in transboundary groundwater resources management. Water and Land Development, 54, 99–108. https://doi.org/10.24425/jwld.2022.141552 Rashidi, M., Zarghami, M., Pishbahar, E., & Fallahi, F. (2022). Assessing coalition in meeting environmental flow based on Shapley value and nash equilibrium: case study Aras River. International Journal of Environmental Science and Technology, 19(7), 6521–6530. https://doi.org/10.1007/s13762-021-03855-5 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. https://doi.org/10.1007/s11269-009-9552-9 Sechi, G. M., & Zucca, R. (2015). Water Costs Allocation in Complex Systems Using a Cooperative Game Theory Approach. Water Resources Management, 29(6), 1781–1796. https://doi.org/10.1007/s11269-015-0910-8 Shapley, L. S. (1953). A Value for n-Person Games. In Contributions to the Theory of Games (pp. 307–317). Princeton University Press. Shokoohi, A., Ramezani Etedali, H., Mojtabavi, S. A., & Singh, V. P. (2016). Using Water Footprint Accounting for Optimizing Crop Patterns Respecting Sustainable Development (Case Study: Qazvin Plain). Iran-Water Resources Research, 12(3), 99–113. https://www.iwrr.ir/article_32628.html Taha, Z., Abdullah, A., & Rashid, T. (2024). Optimizing Feature Selection with Genetic Algorithms: A Review of Methods and Applications. https://doi.org/10.48550/arXiv.2409.14563 Tharwat, A., Sabry, M. M., & El-Khodary, I. (2024). A Cooperative Game Approach for Solving Water Resources Allocation Problem BT - ICT for Engineering & Critical Infrastructures (A. Salman & A. Tharwat (eds.); pp. 23–31). Springer Nature Switzerland. Wanniarachchi, S., & Sarukkalige, R. (2022). A Review on Evapotranspiration Estimation in Agricultural Water Management: Past, Present, and Future. Hydrology, 9(7), 1–12. https://doi.org/10.3390/hydrology9070123 Wu, X., & Whittington, D. (2006). Incentive compatibility and conflict resolution in international river basins: A case study of the Nile Basin. Water Resources Research, 42(2). https://doi.org/10.1029/2005WR004238 Yoosefdoost, I., Abrão, T., & Santos, M. J. (2021). Water Resource Management Aided by Game Theory. In O. Bozorg-Haddad (Ed.), Essential Tools for Water Resources Analysis, Planning, and Management (pp. 217–262). Springer Singapore. https://doi.org/10.1007/978-981-33-4295-8_9 Yoosefdoost, I., Khashei-Siuki, A., Tabari, H., & Mohammadrezapour, O. (2021). Runoff simulation under climate change conditions by using of hybrid bat-based support vector machine neural network. Hydrological Sciences Journa, 66(3), 412–427. https://doi.org/10.1080/02626667.2021.1873343 Zhang, K., Lu, H., & Wang, B. (2024). Benefit Distribution Mechanism of a Cooperative Alliance for Basin Water Resources from the Perspective of Cooperative Game Theory. Sustainability, 16, 6729. https://doi.org/10.3390/su16166729 Zheng, H., Wang, Z., Hu, S., & Wei, Y. (2022). A comparative study of the performance of bankruptcy methods for water allocation in river systems. Water Resources Management, 36(4), 1391–1409. https://doi.org/10.1007/s11269-022-03087-3 Zheng, Y., Sang, X., Liu, Z., Zhang, S., & Liu, P. (2022). Water Allocation Management Under Scarcity: a Bankruptcy Approach. Water Resources Management, 36(9), 2891–2912. https://doi.org/10.1007/s11269-022-03098-0 | ||
|
آمار تعداد مشاهده مقاله: 66 تعداد دریافت فایل اصل مقاله: 73 |
||