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توسعه مدل برنامه‌ریزی چندهدفه فازی در مدیریت آب کشاورزی نواحی خارج از شبکه آبیاری و زهکشی سفیدرود با تعیین بارش موثر | ||
| تحقیقات آب و خاک ایران | ||
| دوره 53، شماره 8، آبان 1401، صفحه 1901-1920 اصل مقاله (1.96 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2022.346546.669331 | ||
| نویسندگان | ||
| یاسمن آورند1؛ سمیه جنت رستمی* 2؛ افشین اشرف زاده1؛ نادر پیرمرادیان3 | ||
| 1گروه مهندسی آب، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران | ||
| 2گروه مهندسی آب، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، گیلان. | ||
| 3گروه مهندسی آب، دانشکده علوم کشاورزی، دانشگاه ایران، رشت، ایران | ||
| چکیده | ||
| در این مطالعه مدل برنامه‌ریزی چندهدفه فازی برای تخصیص بهینه آب آبیاری و کاربری زمین تحت عدم قطعیت چندگانه پیشنهاد شد. در مدل توسعه یافته در این مطالعه، تاثیر میزان بارندگی موثر در تعیین نیاز آبیاری محصولات تحت کشت و همچنین محدودیت منابع آب سطحی و زیرزمینی در محدوده مطالعاتی تالش، خارج از شبکه آبیاری و زهکشی سفیدرود، در نظر گرفته شد. محدوده مطالعاتی تالش به سه ناحیه آبیاری آستارا، تالش و رضوانشهر تقسیم شد. نتایج مدل بهینه در α-cutهای مختلف (صفر، 2/0، 4/0، 6/0، 8/0 و 1) مورد بررسی قرار گرفت. مقادیر تخصیص‌یافته آب سطحی و زیرزمینی نشان داد که بیشترین مقادیر کمبودها در ماه‌های خرداد و تیر و در ناحیه تالش به وقوع می‌پیوندد، به طوری که در حد بالا و پایین α-cut=0.8 به ترتیب 7/1 و 7/2 برابر ناحیه آستارا و 2/1 و 8/1 برابر ناحیه رضوانشهر است. همچنین، نسبت مصرف آب زیرزمینی در سه ناحیه آستارا، تالش و رضوانشهر به ترتیب 4/13، 1/58 و 5/28 درصد در حالت بهینه است و در اکثر ماه‌های خشک سال 100 درصد آب زیرزمینی مجاز مصرف می‌شود که با توجه به عدم دسترسی بسیاری از کشاورزان منطقه به منابع آب سطحی باید به دنبال روش‌هایی برای دسترسی بیشتر کشاورزان به آب سطحی بود. بنابراین نتایج این مطالعه می‌تواند هشداری برای مسئولان و برنامه‌ریزان منطقه باشد که در برنامه‌ریزی‌های آینده برای انتخاب بهترین تصمیم در مورد استفاده از نوع منبع آب آبیاری این مسئله را در نظر بگیرند. | ||
| کلیدواژه‌ها | ||
| بهینه‌سازی؛ آب سطحی؛ آب زیرزمینی؛ نیاز آبیاری | ||
| عنوان مقاله [English] | ||
| Developing Fuzzy Multi-Objective Planning Model for Agricultural Water Management in Areas outside the Sefidrud Irrigation and Drainage Network by Determining Effective Precipitation | ||
| نویسندگان [English] | ||
| Yasaman Avarand1؛ Somaye Janatrostami2؛ Afshin Ashrafzadeh1؛ Nader Pirmoradian3 | ||
| 1Department of Water Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran | ||
| 2Department of Water Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Guilan. | ||
| 3Department of Water Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran | ||
| چکیده [English] | ||
| In this study, a fuzzy multi-objective planning model was used for the optimal allocation of irrigation water and land use under multiple uncertainties. The effect of effective rainfall for determining the irrigation requirement of cultivated crops and also the limitation of surface water and groundwater resources were taken into account in the developed model in the Talash study area, which is located outside the Sefidroud irrigation and drainage network. The study area of Talesh was divided into three irrigation areas: Astara, Talesh, and Rezvanshahr. Then, the results of the optimal model were investigated at different levels of α-cut (0, 0.2, 0.4, 0.6, 0.8, and 1). Allocated amounts of surface water and groundwater showed that maximum shortages occurred in June and July in Talash area, So that the shortage of Talash area in the upper and lower bounds of a-cut=0.8 was 1.7 and 2.7 times more than Astara area as well as 1.2 and 1.8 times more than Rizvanshahr area, respectively. The optimal ratio of groundwater consumption to the total allocated water in Astara, Talesh, and Rezvanshahr areas were 13.4%, 58.1%, and 28.5% respectively. Also, 100% of the allowable groundwater is consumed in most of the dry months of the year. Due to the unavailability of surface water resources to many farmers in this area, proper approaches should be given to the farmers for more access to surface water. Therefore, the results of this study could be a warning for the regional manager and planners to consider this issue in future planning to select the best decision regarding the use of the type of irrigation water resource. | ||
| کلیدواژه‌ها [English] | ||
| Optimization, Surface water, Groundwater, Irrigation requirement | ||
| مراجع | ||
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Allen, R.G., Pereira, L.S., Raes, D. and Smith, M. (1998). Crop Evapotranspiration. Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56, FAO, Rome, Italy. Allen, R.G., Wright, J.L., Pruitt, W.O., Pereira, L.S. and Jensen, M.E. (2007). Water requirements. In G.J. Hoffman, R.G.Evans, M.E. Jensen, D.L. Martin, R.L. Elliot (Eds.), Design and Operation of Farm Irrigation Systems. (pp. 208–288). St Joseph, MI: ASABE. Amin, K. and Mohammad, J.M. (2014). Integrated stepwise approach for optimal water allocation in irrigation canals. Irrigation and Drainage, 63,12-21. Baradaran Sirjani, F., Kohansal, M. and Sabouhi, M. (2015). Application of Two-Stagesmulti-Objective Fuzzy linear Programming Model to develop Optimal Cropping pattern (Case study: Central District of Mashhad). Journal Of Agricultural Economics and Development, 28(4), 368-376. (In Farsi) Bekri, E., Disse, M. and Yannopoulos, P. (2015). Optimizing water allocation under uncertain system conditions in Alfeios River Basin (Greece), Part A: two-stage stochastic programming model with deterministic boundary intervals. Water, 7, 5305-5344. Das, B., Singh, A. and Panda, S.N. (2015). Optimal land and water resources allocation policies for sustainable irrigated agriculture. Land Use Policy, 42, 527-537. Davijani, M.H., Banihabib, M.E. and Anvar, A.N. (2016). Optimization model for the allocation of water resources based on maximization of employment in the agriculture and industry sectors. Hydrology, 533(1), 430-438. Fisher, J.B., Melton, F. and Middleton, E. (2017). The future of evapotranspiration: global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources. Water Resources Research, 53(4), 2618-2626. Garg, N.K. and Dadhich, S.M. (2014). Integrated non-linear model for optimal cropping pattern and irrigation scheduling under deficit irrigation. Agricultural Water Management, 140, 1-13 Khandelwal, S.S. and Dhiman, S.D. (2018). Optimal allocation of land and water resources in a canal command area in the deterministic and stochastic regions. Water Resources Management, 32,1569-1584. Leite, K.N., Martinez-Romero, A. and Tarjuelo, J.M. (2015). Distribution of limited irrigation water based on optimized regulated deficit irrigation and typical meteorological year concepts. Agricultural Water Management, 148,164-176. Leng, Y.K., Lee, J.Y. and Tan, R.R. (2017). Multi-objective optimization for resource network synthesis in eco-industrial parks using an integrated analytic hierarchy process. Journal of Cleaner Production, 143,1268-1283. Li, M. and Guo, P. (2014). A multi-objective optimal allocation model for irrigation water resources under multiple uncertainties. Applied Mathematical Modelling, 38,4897-4911. Li, M. and Guo, P. (2015). A couple random fuzzy two-stage programming model for crop area optimizationda case study of the middle Heihe River basin, China. Agricultural Water Management, 179, 352-365. Li, Y.P. and Huang, G.H. (2011). Planning agricultural water resources system associated with fuzzy and random features. Journal of the American Water Resources Association, 47 (4), 841-860. mazandarani zadeh, H., kakavand, S. and Ramezani Etedali, H. (2021). Optimal redistribution of water among agricultural sector operators using a fuzzy multi-objective optimization model. Irrigation Sciences and Engineering, doi: 10.22055/jise.2021.37122.1966. (In Farsi) Morgan, D.R., Eheart, J.W. and Valocchi, A.J. (1993). Aquifer remediation design under uncertainty using a new chance constrained programming technique. Water Resources Research, 29:551-568. Pirmoradian, N. (2018). Designing and creating the native system of water requirement of agricultural and garden plants in different climates of Iran. Soil and Water Research Institute, Agricultural Research and Training Organization, Ministry of Agriculture. (In Farsi) Pirmoradian, N. and Davatgar, N. (2019). Simulating the effects of climatic fluctuations on rice irrigation water requirement using AquaCrop. Agricultural water management, 213, 97-106. Rastegaripour, F. (2020). Application of Interval Fuzzy Multi-Stage Stochastic Model in water resource management Case study: Latian Dam. Hydrogeology, 5(1), 47-60. (In Farsi) Ren, C., Li, Z. and 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. Ren, C.F., Guo, P. and Li, M. (2013). Optimization of industrial structure considering the uncertainty of water resources. Water Resources Management, 27(11), 3885-3898. Ren, C.F., Guo, P., Tan, Q. and Zhang, L.D. (2017). A multi-objective fuzzy programming model for optimal use of irrigation water and land resources under uncertainty in Gansu Province, China. Journal of Cleaner Production, 164,85-94. Ren, C.F., Li, R.H., Zhang, L.D. and Guo, P. (2016). Multiobjective stochastic fractional goal programming model for water resources optimal allocation among industries. Journal of Water Resources Planning and Management, 142(10), 6036-6040. Singh, A. (2015). Land and water management planning for increasing farm income in irrigated dry areas. Land Use Policy, 42, 244-250. Singh, A. (2017). Optimal allocation of water and land resources for maximizing the farm income and minimizing the irrigation-induced environmental problems. Stochastic Environmental Research and Risk Assessment, 31, 1147-1154. Sun, J., Li, Y.P., Suo, C. and Liu, Y.R. (2019). Impacts of irrigation efficiency on agricultural water-land nexus system management under multiple uncertainties-A case study in Amu Darya River basin, Central Asia. Agricultural Water Management, 216, 76-88. Tenant, D.L. (1976). Instream Flow Regimens for Fish, Wildlife, Recreation and Related Environmental Resources. Fisheries, 1(4),6-10. Wang, C.H., Hou, Y.L. and Xue, Y.J. (2017). Water resources carrying capacity of wetlands in Beijing: analysis of policy optimization for urban wetland water resources management. Journal of Cleaner Production, 161, 1180-1191. Wang, C.X., Li, Y.P. and Zhuang, X.W. (2018). Conjunctive water management under multiple uncertainties: A centroid-based type-2 fuzzy-probabilistic programming approach. Engineering Applications of Artificial Intelligence, 72, 437-448. Wang, H., Jiang, Z.G. and Wang, Y. (2018). A two-stage optimization method for energy-saving flexible job-shop scheduling based on energy dynamic characterization. Journal of Cleaner Production, 188, 575-588. Wang, Z.W., Yang, J. and Deng, X.Z. (2015). Optimal water resources allocation under the constraint of land use in the Heihe River Basin of China. Sustainability, 7(2),1558-1575. Xie, Y.L., Xia, D.X. and Ji, L. (2017). An inexact stochastic-fuzzy optimization model for agricultural water allocation and land resources utilization management under considering effective rainfall. 353, 55-69. Zeng, X.T., Chen, C. and Liu, A.H. (2018). Planning a sustainable regional irrigated production and forest protection under land and water stress with multiple uncertainties. Journal of Cleaner Production, 188, 751-762. | ||
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