کاربرد تئوری بازی در تخصیص بهینه منابع آب منطقه سیستان تحت شرایط خشکسالی با راهبرد کمآبیاری
محورهای موضوعی : برگرفته از پایان نامهزهرا غفاری 1 , علی سردارشهرکی 2 , آرش غفاری مقدم 3
1 - استادیار گروه اقتصاد کشاورزی، پژوهشکده کشاورزی، پژوهشگاه زابل، زابل،ایران
2 - دانشیار اقتصاد کشاورزی، دانشگاه سیستان و بلوچستان، زاهدان، ایران
3 - دانش آموخته کارشناسی ارشد مهندسی کامپیوتر، دانشگاه هاتف، زاهدان، ایران
کلید واژه: استاکلبرگ, نیاز آبی, الگوریتم ژنتیک, تخصیص آب, بازار آب ,
چکیده مقاله :
مقدمه: با توجه به خشکسالیهای فراوان، معمولاً امکان افزایش تخصیص آب وجود ندارد و بنابراین عامل محدودکننده حجم آب میباشد. با توجه به محدودیت منابع آب استفاده از تکنیکهای مناسب جهت بهینه سازی تخصیص آب به محصولات مختلف میتواند راهگشا باشد. استفاده از روشهای کمآبیاری راهبردی بهینه جهت مقابله با بحران کمآبی میباشد.
روش: در مطالعه حاضر اثرات کمآبیاری بر تخصیص آب بین محصولات و مناطق، سود سیستم، مبادله آب بین مناطق بررسی شده است. برای این منظور از مدل تعادلی استاکلبرگ- نش- کورنو با هدف تخصیص آب بین مناطق مختلف تحت آبیاری در سطح رهبر و تخصیص آب بین محصولات مختلف در سطح پیرو در شرایطی که بازار آب شکل بگیرد و تاکید بر کمآبیاری انجام شده است. در این مطالعه سه سناریو 5 درصد کمآبیاری، 10 درصد کمآبیاری و 15 درصد کمآبیاری جهت مقابله با شرایط خشکسالی در منطقه سیستان در نظر گرفته شده است.
یافته ها: نتایج حاصل نشان داد در شرایطی که آبیاری کامل انجام شود بیشترین آب به محصول خربزه و کمترین اب به محصول گندم اختصاص یافته است و سود حاصل در این حالت 1011×71/2 ریال میباشد که با اعمال سناریوهای کمآبیاری میزان سود افزایش خواهد یافت. مقدار شاخص نابرابری تخصیص در آب بدست آمده در این سناریو 0334/0میباشد که مقدار این شاخص نزدیک به صفر میباشد و نشان میدهد تخصیص آب بین مناطق عادلانه بوده است. در بین محصولات بیشترین آب به محصول خربزه و کمترین آب به محصول گندم تخصیص داده شده است. با اعمال سناریو کمآبیاری مقدار سود افزایش و مقدار شاخص نابرابری تخصیص در آب کاهش مییابد.
نتیجه گیری: نتایج نشان داد در صورت استفاده از روش کم آبیاری، منفعت حاصل از مقدار آب ذخیره شده جبران کاهش عملکرد محصول را کرده و با استفاده از مقدار آب صرفه جویی میتوان به محصولات پربازده آب بیشتری تخصیص داد و ضرر ناشی از کاهش عملکرد را جبران کرد. همچنین با اعمال سناریو کمآبیاری کاهش در عملکرد نسبی برای محصولات کاهش پیدا میکند. کمآبیاری سبب شده است که نیاز آبی تامین نشده محصولات کاهش یابد و درصد بیشتری از نیاز آبی آنها تامین شود.
Introduction: Due to frequent droughts, it is usually not possible to increase water allocation and therefore it is the limiting factor of water volume. Considering the limitation of water resources, the use of appropriate techniques to optimize the allocation of water to different products can be a solution. Using deficit irrigation methods is an optimal strategy to deal with the water shortage crisis.
Methods: In the current study have been investigated the effects of deficit irrigation on water allocation between crops and regions, system profit, water exchange between regions. For this purpose, the Stackelberg-Nash-Cournot equilibrium model has been used with the aim of allocating water between different irrigated areas at the leader level and allocating water between different crops at the follower level in the condition that the water market is formed and emphasis on deficit irrigation. In this study, three scenarios of 5% deficit irrigation, 10% deficit irrigation and 15% deficit irrigation have been considered to deal with drought conditions in Sistan region.
Findings: The results showed that in the condition that full irrigation is done, the most water is allocated to the melon crop and the least amount of water to the wheat crop, and the profit in this case is 2.71×1011 IRR, which increases the profit by applying deficit irrigation scenarios. The results of this research can be used as assistants for network managers and responsible people for water allocation.
1. Ren C, Li Z, Zhang H. Integrated multi-objective stochastic fuzzy programming and AHP method for agricultural water and land optimization allocation under multiple uncertainties. Journal of Cleaner Production. 2019;210:12-24. https://doi.org/10.1016/j.jclepro.2018.10.348
2. Li M, Fu Q, Singh VP, Ma M, Liu X. An intuitionistic fuzzy multi-objective non-linear programming model for sustainable irrigation water allocation under the combination of dry and wet conditions. Journal of Hydrology. 2017;555:80-94. https://doi.org/10.1016/j.jhydrol.2017.09.055
3. Zhang F, Guo P, Engel BA, Guo S, Zhang C, Tang Y. Planning seasonal irrigation water allocation based on an interval multiobjective multi-stage stochastic programming approach. Agricultural Water Management. 2019;223:105692. https://doi.org/10.1016/j.agwat.2019.105692
4. Wu D, Liu M. Coordinated optimal allocation of water resources and industrial structure in the Beijing–Tianjin–Hebei regions of China. Chinese Journal of Population, Resources and Environment. 2022;20(4):392-401. https://doi.org/10.1016/j.cjpre.2022.11.009
5. Feng J. Optimal allocation of regional water resources based on multi-objective dynamic equilibrium strategy. Applied Mathematical Modelling. 2021;90:1183-203. https://doi.org/10.1016/j.apm.2020.10.027
6. Francesco S, Dionisio, P., Carlos, G., Vito, F. 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. 2020;17(3). Epub 29. https://doi.org/10.1016/j.jenvman.2020.110645
7. Zeng X, Li Y, Huang G, Liu J. Modeling water trading under uncertainty for supporting water resources management in an arid region. Journal of Water Resources Planning and Management. 2016;142(2):04015058. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000593
8. Xu Z, Yao L, Zhou X, Moudi M, Zhang L. Optimal irrigation for sustainable development considering water rights transaction: A Stackelberg-Nash-Cournot equilibrium model. Journal of Hydrology. 2019;575:628-37. https://doi.org/10.1016/j.jhydrol.2019.05.063
9. Yao L, Xu Z, Chen X. Sustainable water allocation strategies under various climate scenarios: A case study in China. Journal of Hydrology. 2019;574:529-43.
10. Alarcón J, Juana L. The Water Markets as Effective Tools of Managing Water Shortages in an Irrigation District. Water Resources Management. 2016;30(8):2611-25. https://doi.org/10.1007/s11269-016-1296-8
11. Yue Q, Zhang F, Zhang C, Zhu H, Tang Y, Guo P. A full fuzzy-interval credibility-constrained nonlinear programming approach for irrigation water allocation under uncertainty. Agricultural Water Management. 2020;230:105961. https://doi.org/10.1016/j.agwat.2019.105961
12. Li M, Xu Y, Fu Q, Singh VP, Liu D, Li T. Efficient irrigation water allocation and its impact on agricultural sustainability and water scarcity under uncertainty. Journal of Hydrology. 2020;586:124888. https://doi.org/10.1016/j.jhydrol.2020.124888
13. Elleuch MA, Anane M, Euchi J, Frikha A. Hybrid fuzzy multi-criteria decision making to solve the irrigation water allocation problem in the Tunisian case. Agricultural systems. 2019;176:102644. https://doi.org/10.1016/j.agsy.2019.102644
14. Wu R-S, Liu J-S, Chang S-Y, Hussain F. Modeling of mixed crop field water demand and a smart irrigation system. Water. 2017;9(11):885. https://doi.org/10.3390/w9110885
15. Lin P, You J, Gan H, Jia L. Rule-based object-oriented water resource system simulation model for water allocation. Water Resources Management. 2020;34:3183-97. https://doi.org/10.1007/s11269-020-02607-3
16. Li M, Li J, Singh VP, Fu Q, Liu D, Yang G. Efficient allocation of agricultural land and water resources for soil environment protection using a mixed optimization-simulation approach under uncertainty. Geoderma. 2019;353:55-69. https://doi.org/10.1016/j.geoderma.2019.06.023
17. Wang Y, Yang J, Chang J. Development of a coupled quantity-quality-environment water allocation model applying the optimization-simulation method. Journal of Cleaner Production.2019;213:944-55. https://doi.org/10.1016/j.jclepro.2018.12.065
18. Chakraei I, Safavi HR, Dandy GC, Golmohammadi MH. Integrated simulation-optimization framework for water allocation based on sustainability of surface water and groundwater resources. Journal of Water Resources Planning and Management. 2021;147(3):05021001. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001339
19. Zeng Y, Li J, Cai Y, Tan Q, Dai C. A hybrid game theory and mathematical programming model for solving trans-boundary water conflicts. Journal of Hydrology. 2019;570:666-81. https://doi.org/10.1016/j.jhydrol.2018.12.053
20. Kosolapova NA, Matveeva LG, Nikitaeva AY, Molapisi L. Modeling resource basis for social and economic development strategies: Water resource case. Journal of Hydrology. 2017;553:438-46. https://doi.org/10.1016/j.jhydrol.2017.08.007
21. Philpot SL, Johnson PA, Hipel KW. Analysis of a brownfield management conflict in Canada. Hydrological Research Letters. 2017;11(3):141-8. https://doi.org/10.3178/hrl.11.141
22. Geerts S, Raes D. Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas. Agricultural Water Management. 2009;96(9):1275-84. https://doi.org/10.1016/j.agwat.2009.04.009
23. Fereres E, Soriano MA. Deficit irrigation for reducing agricultural water use. Journal of experimental botany. 2007;58(2):147-59. https://doi.org/10.1093/jxb/erl165
24. Mahmoudzadeh Varzi M, Trout TJ, DeJonge KC, Oad R. Optimal water allocation under deficit irrigation in the context of Colorado water law. Journal of Irrigation and Drainage Engineering. 2019;145(5):05019003. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001374
25. Trout TJ, Howell, T. A., English, M. J., Martin, D. L. Deficit irrigation strategies for the western US. Transactions of the ASABE. 2020;63(6):12. https://elibrary.asabe.org/abstract.asp?aid=51878
26. English M, Raja SN. Perspectives on deficit irrigation. Agricultural Water Management. 1996;32(1):1-14. https://doi.org/10.1016/S0378-3774(96) 01255-3
27. Englsih M, Music J, Murty V. Deficit irrigation. Management of Farm Irrigation Systems ASAE Monograph, Michigan. 1990:631-63.
28. Salemi H, Soom MAM, Lee TS, Mousavi SF, Ganji A, Yusoff MK. Application of AquaCrop model in deficit irrigation management of Winter wheat in arid region. African Journal of Agricultural Research. 2011;610(1):2204-DOI: 10.5897/AJAR10.1009
29. Shirshahi F, Babazadeh H, Ebrahimipak N, Khaledian M. Determining Optimum major Crops Cultivation Areas in Different Levels of deficit Irrigation in Qazvin Irrigation and drainage district. Water and Soil Science. 2020;30(1):69-81. 20.1001.1.20085133.1399.30.1.6.2
30. Mohammad khani M, karimi m, Gomrokchi a. Optimization of Water Allocation between Different Crops in Water Stress Conditions in Qazvin Irrigation Network. Water and Soil. 2017;31(1):1-10. https://doi.org/10.22067/jsw.v31i1.48682
31. Pande G, Umamahesh N. Optimal Cropping Pattern and Water Allocation Using Ga Under Deficit Irrigation Conditions. 2022. https://doi.org/10.21203/rs.3.rs-1873146/v1
32. Ali S. Optimal Allocation of Water Resources of Hirmand Basin by Application of Game Theory and Evaluating the Managerial Scenarios [thesis]: university of Sistan and Baluchestan. ; 2016.
33. Ghaffari Moghadam Z, SardarShahraki A. Prediction of monthly consumption of drinking water in the Sistan region under climate change impact. Journal of Natural Environmental Hazards. 2023;12(37):75-100. 10.22111/jneh.2023.42994.1912
34. Zapata-Sierra AJ, Manzano-Agugliaro F. Controlled deficit irrigation for orange trees in Mediterranean countries. Journal of Cleaner Production. 2017;162:130-40. https://doi.org/10.1016/j.jclepro.2017.05.208
35. Clarke D, Smith M, El-Askari K, editors. CropWat for Windows: user guide. 2001: IHE Oak Brook, IL, USA. https://www.researchgate.net/publication/312903822_CropWat_for_Windows_User_guide
36. Steduto P, Hsiao TC, Fereres E, Raes D. Crop yield response to water: fao Rome; 2012. https://www.fao.org/4/i2800e/i2800e00.htm
37. Graveline N, Mérel P. Intensive and extensive margin adjustments to water scarcity in France's Cereal Belt. European Review of Agricultural Economics. 2014;41(5):707-43. https://doi.org/10.1093/erae/jbt039
38. Goetz RU, Martínez Y, Xabadia À. Efficiency and acceptance of new water allocation rules-The case of an agricultural water users association. Science of the total environment. 2017;601:614-25. https://doi.org/10.1016/j.scitotenv.2017.05.226
39. Ghaffari Moghadam Z, Moradi E, Hashemi Tabar M, Sardar Shahraki A. Developing a Bi-level programming model for water allocation based on Nerlove’s supply response theory and water market. Environment, Development and Sustainability. 2023;25(6):5663-89. https://doi.org/10.1007/s10668-022-02658-z
40. Georgiou P, Papamichail D, Vougioukas S. Optimal irrigation reservoir operation and simultaneous multi‐crop cultivation area selection using simulated annealing. Irrigation and drainage: the journal of the International Commission on Irrigation and Drainage. 2006;55(2):129-44.
https://doi.org/10.1002/ird.229
