نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Agriculture is the main economic pillar of the Helmand Basin; however, it faces severe water scarcity due to unsustainable consumption. Previous studies have optimized cropping patterns based on economic and water factors in arid regions. However, the unique conditions of Helmand require a multi-objective optimization approach that integrates economic, ecological, and environmental factors. This study develops a multi-objective mathematical model to determine the optimal cropping pattern for Helmand to maximize farmer profits while minimizing water consumption and environmental impacts. The model simulates cropping areas for major regional crops using multi-objective linear programming. In this regard, to obtain the optimal cultivation pattern with the desired objectives, the genetic algorithm was used as a random optimization method. The desired information was obtained from the Agricultural and Jihad Organization and Regional Water of Sistan and Baluchestan Province, and the relevant calculations were performed in MATLAB and CROPWAT software. The crop year determined in this study is 2018-2019 and the selected crops include wheat, corn, barley, black grapes, cucumber, eggplant, onion, legumes, and medicinal plants. Results indicate that the optimal cropping pattern reduces annual water consumption by 29%, nitrogen leaching by up to 14%, and increases economic yield by 11% compared to current practices. Virtual water imports of wheat and corn reduce local water consumption by 18% and improve economic yield by up to 5%. This integrated modeling approach provides data-driven scenario-based decision support for guiding policies on optimal cropping strategies. The findings demonstrate the potential of multi-objective optimization combined with virtual water imports to sustainably enhance agriculture despite water scarcity. This study can be used as a road map for policy makers and farmers to improve and sustain agriculture in the Hirmand basin.
کلیدواژهها English
اعظمی، آ.، میرک زاده، ع ا. و آذری، آ.1403. بهینه سازی الگوی کشت محصولات زراعی شهرستان صحنه براساس محدودیت منابع. جغرافیا و برنامه ریزی محیطی. 35(2): 87-114.
پور اصغر سنگاچین، ف. و ابراهیمیخوسفی، م. 1397. بررسی تأثیرات برنامههای تنظیم آب کشورهای همسایه در حوضههای مشترک مرزی بر ایران. مرکز پژوهشهای توسعه و آیندهنگری. سازمان برنامه و بودجه کشور.
جهان تیغ، ح. ١٤٠١. بهینه سازی الگوی کشت محصولات کشاورزی در راستای مدیریت مصرف آب در شهرستان گرگان. نشریه علمی پژوهشی مهندسی آبیاری و آب ایران. 12(۳): 369-385.
حسینی، س. م. و مازندرانی زاده، ح. 1401. بررسی تأثیر بهینهسازی توأم توزیع آب و الگوی کشت بر درآمد کشاورزان (مطالعه موردی: شبکه قزوین). نشریه علوم و مهندسی آبیاری. 45(2): 47-61.
زارعزاده، م.، مرید، س.، کریمی، ن.، مدنی، ک. و فاطمی، فرشاد.1397. روند توسعه اراضی کشاورزی در حوضه هیرمند افغانستان و چشمانداز آن با استفاده از طبقهبندی شیپایه تصاویر ماهوارهای و مدل ژئومد. نشریه آبیاری و زهکشی ایران. 1(12): 209-221.
شاه نظری، ع. و صادقی، س. 1402. بهینه سازی معیارهای الگوی کشت مبتنی بر توسعه پایدار و افزایش بهره وری آب کشاورزی در حوضه آبریز تجن. نشریه علوم آب و خاک. 27(2): 163-177.
صالحی شفا، ن.، بابازاده.، ح، آقا یاری.، ف. و صارمی، ع.1401. تعیین الگوی کشت مطلوب با تأکید بر مصارف بهینه آب کشاورزی در دشت شهریار تهران. نشریه آبیاری و زهکشی ایران. 16(1): 119-133.
عبد شاهی.، ع. مردانی نجفآبادی.، م. و زینالی، م.1399. تعیین الگوی بهینه کشت محصولات کشاورزی در شهرستان ملاثانی: کاربرد مدل بهینهسازی چندهدفه استوار. اقتصاد کشاورزی و توسعه. 28(3): 175-203.
کلاهی، م., حسینعلی، ف. و کریمائی طبرستانی، م. 1401. تعیین الگوی بهینه کشت با هدف حداقلسازی آب مجازی و حداکثرسازی سود اقتصادی محصولات: مطالعه موردی دشت عمرانی در خراسانرضوی. نشریه آبیاری و زهکشی ایران، 16(6): 1221-1232.
گل پذیر، م., ابراهیمی، ک., مدرسی، ف., و شمسی، م. 1402. کمیسازی ارزش اقتصادی منابع آب کشاورزی استان اصفهان با رویکرد اصلاح الگوی کشت و بر مبنای آب مجازی. مجله تحقیقات اقتصاد و توسعه کشاورزی ایران. 54(3)، 575-592.
وفایینژاد، ع. 1395. بهینه سازی الگوی کشت با استفاده از روش TOPSIS و الگوریتم ژنتیک بر مبنای قابلیتهای GIS (مطالعه موردی: اراضی بخش جلگه، استان اصفهان). اکو هیدرولوژی. 3(1): 69-82.
Aliyar, Q., Zulfiqar, F., Datta, A., Kuwornu, J. K. and Shrestha, S. 2022. Drought perception and field-level adaptation strategies of farming households in drought-prone areas of Afghanistan. International Journal of Disaster Risk Reduction. 72: 102862.
Al-Zahrani, M., Musa, A. and Chowdhury, S. 2016. Multi-objective optimization model for water resource management: a case study for Riyadh, Saudi Arabia. Environment, development and sustainability. 18: 777-798.
Bastian, C. T., McLeod, D. M., Germino, M. J., Reiners, W. A. and Blasko, B. J. 2002. Environmental amenities and agricultural land values: a hedonic model using geographic information systems data. Ecological economics. 40(3): 337-349.
Bratman, G. N., Hamilton, J. P. and Daily, G. C. 2012. The impacts of nature experience on human cognitive function and mental health. Annals of the New York academy of sciences.1249(1): 118-136.
Deb, K., Sindhya, K. and Hakanen, J. 2016. Multi-objective optimization. In Decision sciences (pp. 161-200). CRC Press.
Elshall, A. S., Arik, A. D., El-Kadi, A. I., Pierce, S., Ye, M., Burnett, K. M. and Chun, G. 2020. Groundwater sustainability: A review of the interactions between science and policy. Environmental Research Letters. 15(9): 093004.
Faisal Basiri, A. 2009. Options for improving irrigation water allocation and use: A case study in hari rod river basin, Afghanistan (Doctoral dissertation, AIT).
Goes, B. J. M., Howarth, S. E., Wardlaw, R. B., Hancock, I. R. and Parajuli, U. N. 2016. Integrated water resources management in an insecure river basin: a case study of Helmand River Basin, Afghanistan. International Journal of Water Resources Development. 32(1): 3-25.
Haggerty, R., Sun, J., Yu, H., & Li, Y. 2023. Application of machine learning in groundwater quality modeling-A comprehensive review. Water Research, 233, 119745.
Hekmatnia, M., Safdari, M., Ahmadi, A. and Monibi, H. 2022 National savings in freshwater consumption in Iran by virtual water imports (a case study on cereals). Water and Environment Journal. 36(4): 656-666
Hekmatnia, M., Isanezhad, A., Ardakani, A. F., Ghojghar, M. A. and Ghaleno, N. D. 2023. An attempt to develop a policy framework for the global sustainability of freshwater resources in the virtual water trade. Sustainable Production and Consumption. 39: 311-325.
Hekmatnia, M., Ardakani, A. F., Isanezhad, A. and Monibi, H. 2024. A novel classification of virtual water trade for the sustainability of global freshwater resources. Environment, Development and Sustainability. 26(3): 7377-7408.
Chapagain, A. K. and Hoekstra, A. Y. 2003. Virtual water trade: A quantification of virtual water flows between nations in relation to trade of livestock and livestock products, Value of water Research Report Series No.13, UNESCO-IHE, pp. 49-76.
Huang, H., Xie, P., Duan, Y., Wu, P. and Zhuo, L. 2023. Cropping pattern optimization considering water shadow price and virtual water flows: A case study of Yellow River Basin in China. Agricultural Water Management. 284: 108339.
Iqbal, M. W., Donjadee, S., Kwanyuen, B. and Liu, S. Y. 2018. Farmers’ perceptions of and adaptations to drought in Herat Province, Afghanistan. Journal of Mountain Science. 15(8): 1741-1756.
Jain, S., Ramesh, D., & Bhattacharya, D. 2021. A multi-objective algorithm for crop pattern optimization in agriculture. Applied Soft Computing, 112: 107772.
Kumar, S., & Sharma, R. 2023. Resource use efficiency optimization of major farming systems in hills of Himachal Pradesh. Indian Journal of Ecology.50(3): 893-899.
Kaleeswaran, V., Dhamodharavadhani, S. and Rathipriya, R. 2021. Multi-crop selection model using binary particle swarm optimization. In Innovative Data Communication Technologies and Application: Proceedings of ICIDCA 2020 (pp. 57-68). Springer Singapore.
Li, X., Kang, S., Niu, J., Du, T., Tong, L., Li, S. and Ding, R. 2017. Applying uncertain programming model to improve regional farming economic benefits and water productivity. Agricultural Water Management. 179: 352-365.
Mohammadzadeh, A., Vafabakhsh, J., Mahdavi Damghani, A. and Deihimfard, R. 2022. Optimal land allocation to crop production in different decision priorities and water availability scenarios: East Azerbaijan province of Iran. Archives of Agronomy and Soil Science. 68(5): 597-614.
Najafabadi, M. M., Ziaee, S., Nikouei, A., & Borazjani, M. A. 2019. Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study. Agricultural Systems. 173: 218-232.
Ritzel, B. J., Eheart, J. W. and Ranjithan, S. 1994. Using genetic algorithms to solve a multiple objective groundwater pollution containment problem. Water resources research. 30(5): 1589-1603.
Qureshi, A. S. and Akhtar, M. 2004. A survey of drought impacts and coping measures in Helmand and Kandahar provinces of Afghanistan. Lahore & Tehran: International Water Management Institute.
Soltani, H. A., & Khajehpour, E. 2020. Optimal cropping pattern in Afghanistan considering environmental sustainability. International Journal of Agricultural Management and Development (IJAMAD). 10(4): 333-346.
Sun, J. X., Yin, Y. L., Sun, S. K., Wang, Y. B., Yu, X. and Yan, K. 2021. Review on research status of virtual water: The perspective of accounting methods, impact assessment and limitations. Agricultural Water Management. 243: 106407.
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.
Tabesh, M. and Asadzadeh, A. 2013. A multi-objective optimization model for crop planning and virtual water trade: A case study from Iran. Journal of cleaner production. 52: 408-417.
Tewabe, D. and Dessie, M. 2020. Enhancing water productivity of different field crops using deficit irrigation in the Koga Irrigation project, Blue Nile Basin, Ethiopia. Cogent Food & Agriculture. 6(1): 1757226.
United Nations. 2011. Managing Afghanistan's transboundary waters. UNEP in Afghanistan.
Ward, F. A., & Pulido-Velazquez, M. 2008. Water conservation in irrigation can increase water use. Proceedings of the National Academy of Sciences. 105(47): 18215-18220.