تعیین الگوی کشت مطلوب با تاکید بر مصارف بهینه آب کشاورزی در دشت شهریار تهران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی آب، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی،

2 گروه مهندسی آب، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران

3 دانشکده کشاورزی، واحد کرج، دانشگاه آزاد اسلامی، کرج، ایران

4 استادیار، گروه علوم و مهندسی آب، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران

چکیده

به دلیل فعالیت‌های کشاورزی گسترده و نیاز آبیاری قابل توجه، مصرف آب در بخش کشاورزی افزایش یافته است. بنابراین ارائه راه کارهایی به منظور کاهش مصارف آبی، مسئله‌ای مهم و حائز اهمیت است. به این منظور مدل بهینه‌سازی با استفاده از الگوریتم ژنتیک چندهدفه (NSGA-II) با دو تابع هدف سود خالص و مصرف آب کشاورزی به صورت مجزا برای دشت شهریار تهران و سال آبی 95 محاسبه و ارائه شد. همچنین مقادیر بهینه سود خالص، الگوی کشت، مصارف آبیاری و نیاز ناخالص آبیاری در مدل بهینه‌سازی مورد نظر برآورد شدند. نتایج نشان داد بیشترین سود خالص، مساحت کشت و حجم نیاز آبی بهینه مربوط به ناحیه اسلامشهر بوده سپس ناحیه شهریار و در نهایت رباط‌کریم بیشترین مقادیر مورد نظر را دارد. ناحیه شهریار بیشترین مصرف بهینه آب در بخش کشاورزی را دارد، سپس اسلامشهر و در آخر رباط‌کریم کمترین مقدار بهینه مصرف آب کشاورزی را دارد. بیشترین مقدار نسبت سود خالص به مساحت کشت در حالت بهینه مربوط به ناحیه رباط‌کریم سپس ناحیه شهریار و در انتها ناحیه اسلامشهر بوده است. همچنین با توجه به مساحت کشت و حجم آب مصرفی بهینه محصولات انگور، انار، پیاز، سبزیجات و گلابی در هر ناحیه، سود خالص آن‌ها مناسب و ایده‌آل می‌باشد. و انگور بهترین محصول ممکن در میان آن‌ها می‌باشد. سیاست بهره‌برداری بهینه از منابع آبی منجر به کاهش سطح زیر کشت، حجم آب مصرفی بهینه و حجم نیاز آبی در کل محدوده مورد مطلعه نسبت به حالت فعلی به اندازه 44/20، 71/49 و 35/20 درصد شده است.

کلیدواژه‌ها

عنوان مقاله [English]

Determining the optimal cultivation area and pattern of agricultural water consumption in order to manage multi-objective planning

نویسندگان [English]

  • Nima Salehi Shafa 1
  • Hossein Babazadeh 2
  • Fayaz Aghayari 3
  • Ali Saremi 4
1 Department of Water Science and Engineering, Science and Research Branch, Islamic Azad University
2 Department of Water Science and Engineering, Science and Research Branch, Tehran, Iran
3 Department of Agronomy, Karaj Branch, Islamic Azad University, Karaj, Iran
4 Assistant Professor, Department of Water Science and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
چکیده [English]

Due to extensive agricultural activities and the need for significant irrigation, water consumption in the agricultural sector has increased. Therefore, providing solutions to reduce water consumption is an important issue. For this purpose, the optimization model was calculated and presented separately using the multi-objective genetic algorithm (NSGA-II) with two functions of net profit and agricultural water consumption in the Shahriar plan(Tehran, Iran). Also, the optimal values of net profit, cultivation pattern, irrigation uses and gross irrigation requirement were estimated in the optimization model. The results showed that the highest net profit, cultivation area and the volume of optimal water demand are related to Islamshahr area, then Shahriyar area and finally Robat Karim have the most desired values. Shahriar area has the highest optimal water consumption in the agricultural sector, then Islamshahr and finally Robat Karim has the lowest optimal amount of agricultural water consumption. The highest ratio of net profit to cultivated area in the optimal condition was related to Robat Karim area, then Shahriyar area and finally Islamshahr area. Also, according to the cultivation area and the optimal water consumption of grape, pomegranate, onion, vegetables in each area, their net profit is appropriate and ideal. And grape is the best possible crop among them.The policy of optimal utilization of water resources has led to a reduction in the area under cultivation, the volume of optimal water consumption and the volume of water needs in the whole area compared to the current situation by 20.44, 49.71 and 20.35 percent.

کلیدواژه‌ها [English]

  • Net profit
  • agricultural water consumption
  • Water demand volume
  • net profit to cultivation area ratio
  • optimal exploitation policy

مراجع

Adeyemo, J. and Otieno, F. 2010. Differential evolution algorithm for solving multi-objective crop planning model. Agricultural Water Management. 97(6): 848-856.
Alabdulkader, A. M., Al-Amoud, A. I. and Awad, F. S. 2012. Optimization of the cropping pattern in Saudi Arabia using a mathematical programming sector model. Agricultural Economics. 58(2): 56-60.
Alizadeh, a., Majidi, n., Ghorbani, m. and Mohammadian, f. 2012. Cultivation pattern optimization to balance groundwater resource (case study: Mashhad-Chenaran plain). Iran irrigation and drainage. 6(1): 55- 68.
Asaadi, M. A., Mortazavi, S. A., Zamani, O., Najafi, G. H., Yusaf, T. and Hoseini, S. S. 2019. The impacts of water pricing and non-pricing policies on sustainable water resources management: A case of Ghorveh plain at Kurdistan province, Iran. Energies. 12(14): 2667.
Babel, M. S., Gupta, A. D. and Nayak, D. K. 2005. A model for optimal allocation of water to competing demands. Water resources management. 19(6): 693-712.
Bergez, J. E. 2013. Using a genetic algorithm to define worst-best and best-worst options of a DEXi-type model: Application to the MASC model of cropping-system sustainability. Computers and electronics in agriculture. 90: 93-98.
Birhanu, K., Alamirew, T., Olumana, M. D., Ayalew, S. and Aklog, D. 2015. Optimizing cropping pattern using chance constraint linear programming for koga irrigation dam, Ethiopia. Irrigation & Drainage Systems Engineering. 10(4172): 2168-9768.
Chetty, S., Adewumi, A. O. 2013. Comparison study of swarm intelligence techniques for the annual crop planning problem. IEEE Transactions on Evolutionary Computation. 18(2): 258-268.
Dai, C., Qin, X. S. and Lu, W. T. 2021. A fuzzy fractional programming model for optimizing water footprint of crop planting and trading in the Hai River Basin, China. Journal of Cleaner Production. 278: 123196.
Dai, Z. Y. and Li, Y. P. 2013. A multistage irrigation water allocation model for agricultural land-use planning under uncertainty. Agricultural Water Management. 129: 69-79.
Divakar, L., Babel, M. S., Perret, S. R. and Gupta, A. D. 2011. Optimal allocation of bulk water supplies to competing use sectors based on economic criterion–An application to the Chao Phraya River Basin, Thailand. Journal of Hydrology. 401(1-2): 22-35.
Fasakhodi, A. A., Nouri, S. H. and Amini, M. 2010. Water resources sustainability and optimal cropping pattern in farming systems; a multi-objective fractional goal programming approach. Water resources management. 24(15): 4639-4657.
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.
Garga, S. and Dadhich, M. 2014. Integrated non-linear model for optimal cropping pattern and irrigation scheduling under deficit irrigation. Agricultural Water Management. (140): 1–13.
Georgiou, P. E. and Papamichail, D. M. 2008. Optimization model of an irrigation reservoir for water allocation and crop planning under various weather conditions. Irrigation science. 26(6): 487-504.
Hashemi, M., Zadeh, H. M., Arasteh, P. D. and Zarghami, M. 2019. Economic and environmental impacts of cropping pattern elements using systems dynamics. Civil Engineering Journal. 5(5): 1020-1032.
Honar, T., Ghazali, M. and Nikoo, M. R. 2021. Selecting the Right Crops for Cropping Pattern Optimization Based on Social Choice and Fallback Bargaining Methods Considering Stakeholders’ Views. Iranian Journal of Science and Technology, Transactions of Civil Engineering. 45(2): 1077-1088.
Inas, E. G., Grigg, N. and Waskom, R. 2017. Water-food-energy: nexus and non-nexus approaches for optimal cropping pattern. Water Resources Management. 31(15): 4971-4980.
Jain, S., Ramesh, D. and Bhattacharya, D. 2021. A multi-objective algorithm for crop pattern optimization in agriculture. Applied Soft Computing. 112: 107772.
Jiang, Y., Xu, X., Huang, Q., Huo, Z. and Huang, G. 2016. Optimizing regional irrigation water use by integrating a two-level optimization model and an agro-hydrological model. Agricultural water management. 178: 76-88.
Kaleeswaran, V., Dhamodharavadhani, S. and Rathipriya, R. 2021. Multi-crop Selection Model Using Binary Particle Swarm Optimization. In Innovative Data Communication Technologies and Application (pp. 57-68). Springer, Singapore.
Karamouz, M., Zahraie, B., Kerachian, R. and Eslami, A. 2010. Crop pattern and conjunctive use management: a case study. Irrigation and Drainage: The journal of the International Commission on Irrigation and Drainage. 59(2): 161-173.
Ketsripongsa, U., Pitakaso, R., Sethanan, K. and Srivarapongse, T. 2018. An Improved differential evolution algorithm for crop planning in the Northeastern Region of Thailand. Mathematical and Computational Applications. 23(3): 40.
Khashei-siuki, a., Ghahreman, b. and Kouchakzadeh, m. 2010. Application of Agricultur Water Allocationand Management by PSO Optimization Technic (Case study: Nayshabur Plaine) Journal of Water and Soil. 27(2): 292-303.
Najafabadi, M. M., Ziaee, S., Nikouei, A. and Borazjani, M. A. 2019. Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study. Agricultural Systems. 173: 218-232.
Rath, A., Swain, P. C. 2021. Optimal allocation of agricultural land for crop planning in Hirakud canal command area using swarm intelligence techniques. ISH Journal of Hydraulic engineering. 27(1): 38-50.
Rawabdeh, H., Shatanawi, M., Scardigno, A. and Todorovic, M. 2010. Optimization of the cropping pattern in Northern and Southern part of the Jordan Valley under drought conditions and limited water availability. Economics of Drought and Drought Preparedness in a Climate Change Context. Options Méditerranéenes Série A. 95: 199-206.
Regulwar, D. G. and Gurav, J. B. 2013. Two-Phase Multi Objective Fuzzy Linear Programming Approach for Sustainable Irrigation Planning. Journal of Water Resource and Protection. 5(6): 642-651.
Sadati, S. K., Speelman, S., Sabouhi, M., Gitizadeh, M. and Ghahraman, B. 2014. Optimal irrigation water allocation using a genetic algorithm under various weather conditions. Water. 6(10): 3068-3084.
Sarma, A. K., Misra, R., and Chandramouli, V. 2006. Application of genetic algorithm to determine optimal cropping pattern. Opsearch. 43(3): 320-329.
Shirdeli, A. and Dastvar, S. 2014. An optimization technique for cropping patterns and land consolidation: A case study for irrigation network. Management Science Letters. 4(9): 2087-2092.
Shirshahi, F., Babazadeh, H., EbrahimiPak, N. and Khaledian, M. 2020. Sustainable optimization of regional agricultural water use by developing a two-level optimization model. Arabian Journal of Geosciences. 13(4): 1-12.
Shreedhar, R., Hiremath, C.G. and Shetty, G.G. 2015. Optimization of Croping pattern using Linear Programming Model for Markandeya Command Area. International Journal of Scientific & Engineering Research. 6(9): 1311-1326
Singh, A. and Panda, S. N. 2013. Optimization and simulation modelling for managing the problems of water resources. Water resources management. 27(9): 3421-3431.
Su, X., Li, J. and Singh, V. P. 2014. Optimal allocation of agricultural water resources based on virtual water subdivision in Shiyang River Basin. Water Resources Management. 28(8): 2243-2257.
Tafteh, A., Babazadeh, H., Ebrahimipak, N. A. and Kaveh, F. 2014. Optimization of irrigation water distribution using the MGA method and comparison with a linear programming method. Irrigation and drainage. 63(5): 590-598.
Varade, S. Patel, J. N. 2018. Determination of optimum cropping pattern using advanced optimization algorithms. Journal of Hydrologic Engineering.  23(6): 05018010.
Wardlaw, R. and Bhaktikul, K. 2004. Application of genetic algorithms for irrigation water scheduling. Irrigation and Drainage: The journal of the International Commission on Irrigation and Drainage. 53(4): 397-414.
Zeng, X., Kang, S., Li, F., Zhang, L. and Guo, P. 2010. Fuzzy multi-objective linear programming applying to crop area planning. Agricultural Water Management. 98(1): 134-142.
نشریه آبیاری و زهکشی ایران
دوره 16، شماره 1 - شماره پیاپی 91
فروردین و اردیبهشت 1401
صفحه 119-133

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