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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 | ||
| عنوان مقاله [English] | ||
| Application of Game Theory in the Reallocation of Agricultural Water to Improve Water Use Efficiency | ||
| نویسندگان [English] | ||
| Mohammadhashem Sarafha1؛ Sheyda Kakavand1؛ Hashemi Masoumeh2؛ hamed mazandarani zadeh3 | ||
| 1M.Sc. in Water Resource Management, Imam Khomeini International University, Qazvin, Iran. | ||
| 2Ph.D. in Water Resource Management, Imam Khomeini International University, Qazvin, Iran. | ||
| 3associate professor, water eng. group, Imam Khomeini International University، Qazvin | ||
| چکیده [English] | ||
| In recent years the water allocated for the Qazvin irrigation network has reached a staggering level of reduction at half the agreed upon total. Rather than the original allocation of 250 million cubic meters per year, it has dropped below 120 million cubic meters per year. An assessment of the situation shows that in addition to the nearly 50% reduction of water flowing in, the actual distribution pattern of water to the farmers remains unchanged. The objective of this study is to reallocate water among farmers in the Qazvin irrigation network in order to resolve existing disparities among them. To this end, the income of each farmer was first calculated under the current non-cooperative condition. Then, assuming the establishment of full cooperation, a genetic algorithm was employed to optimize the allocation of 122 million cubic meters of water within the network. Subsequently, to encourage participation, the additional benefits generated through cooperation were redistributed among farmers using the Shapley value theory. The results demonstrate that if farmers cooperate in water extraction, not only will all of them earn higher profits compared to the current situation, but the total profit will also increase significantly by about 104% (from 8.902 to 18.233 million USD). The combined application of the genetic algorithm and Shapley value theory can serve as an effective approach in managing conflicts, enhancing equity in resource allocation, and improving the economic efficiency of irrigation networks. | ||
| کلیدواژهها [English] | ||
| game theory, genetic algorithm, irrigation network, water reallocation | ||
| مراجع | ||
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