با همکاری انجمن اقتصاد کشاورزی ایران

نوع مقاله : مقالات پژوهشی به زبان انگلیسی

نویسندگان

1 گروه اقتصاد کشاورزی، دانشگاه فردوسی مشهد، مشهد، ایران

2 گروه اقتصاد کشاورزی، دانشگاه تهران، ایران

3 گروه علوم زمین، دانشگاه شهید بهشتی، تهران، ایران

10.22067/jead.2025.91123.1320

چکیده

منابع آب زیرزمینی به‌عنوان یک منبع حیاتی برای کشاورزی در مناطق خشک محسوب می‌شوند که برداشت بی‌رویه از آن‌ها منجر به چالش‌های جدی مانند کاهش سطح آب و افزایش کم‌آبی شده است. این مطالعه با تمرکز بر نیاز فوری به مدیریت پایدار منابع آب زیرزمینی، از رویکرد تصمیم‌گیری گروهی مشارکتی با حضور ذینفعان متنوع، به‌ویژه کشاورزان، استفاده می‌کند. نادیده گرفتن مشارکت کشاورزان در فرآیند تصمیم‌گیری منجر به سیاست‌های ناکارآمد شده است. این پژوهش با به‌کارگیری روش‌های تصمیم‌گیری چندمعیاره(MCDM) ، به‌ویژه تکنیک‌های آنتروپی شانون فازی وTOPSIS  فازی، راهبردهای کاهش مصرف آب زیرزمینی در منطقه صفی‌آباد شمال خراسان، ایران را اولویت‌بندی می‌کند. داده‌های کیفی حاصل از مصاحبه با ذینفعان، بینش‌هایی در مورد چالش‌ها و فرصت‌های مرتبط با استفاده از آب زیرزمینی ارائه می‌دهد و دو راهبرد اصلی را شناسایی می‌کند: (۱) انتقال به کشت محصولات کم‌آب‌بر و (۲) پذیرش سیستم‌های آبیاری مدرن. این راهبردها نه تنها کاهش قابل توجهی در مصرف آب را نوید می‌دهند، بلکه از شیوه‌های کشاورزی پایدار نیز حمایت می‌کنند. یافته‌ها بر اهمیت همکاری ذینفعان در اجرای سیاست‌های مؤثر مدیریت آب تأکید می‌کنند تا استفاده مسئولانه از منابع تضمین شده و پایداری بلندمدت حاصل شود. این مطالعه به‌عنوان الگویی برای پژوهش‌های آینده عمل می‌کند و از روش‌های ترکیبی که تحلیل‌های کیفی و کمی را ادغام می‌کنند، برای ارائه توصیه‌های سیاستی و بهبود مدیریت منابع آب حمایت می‌کند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Group Decision-Making of Agricultural Stakeholders towards Sustainable Groundwater Resources Management: A Case Study in North Khorasan

نویسندگان [English]

  • M. Bahrami Nasab 1
  • A. Firoozzare 1
  • A. Dourandish 2
  • M. Sabouhi 1
  • M. Ghorbani 3

1 Department of Agricultural Economics, Ferdowsi University of Mashhad, Iran

2 Department of Agricultural Economics, University of Tehran, Tehran, Iran

3 Department of Earth Sciences, Shahid Beheshti University, Tehran, Iran

چکیده [English]

Groundwater is a vital resource for agriculture in arid regions which its over-extraction has led to significant challenges of declining water levels and increased scarcity. This study addresses the urgent need for sustainable groundwater management by employing an inclusive group decision-making approach involving diverse stakeholders, with a focus on farmers. Overlooking the participation of farmers in the decision-making approach led to ineffective policies. Utilizing Multi-Criteria Decision-Making (MCDM) methods, specifically the fuzzy Shannon entropy and Fuzzy TOPSIS techniques, the research prioritizes strategies for reducing groundwater consumption in the Safi-Abad region of North Khorasan, Iran. Qualitative data from stakeholder interviews provided insights into the challenges and opportunities related to groundwater use, revealing two primary strategies: (i) transitioning to low water-demand crops; and (ii) adopting modern irrigation systems. These approaches not only promise significant reductions in water usage but also support sustainable agricultural practices. The findings highlighted the importance of stakeholder collaboration in implementing effective water management policies, ensuring responsible resource use, and securing long-term viability. This study served as a model for future research, advocating for mixed methods integrating qualitative and quantitative analyses to inform policy recommendations and improve water resource management.

کلیدواژه‌ها [English]

  • Agricultural water management
  • Decision-making
  • Farmers role
  • Stakeholder participation
  • Water conservation strategies

©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)

  1. Ahmadi, A., Kerachian, R., Skardi, M.J.E., & Abdolhay, A. (2020). A stakeholder-based decision support system to manage water resources. Journal of Hydrology, 589, Article 125138. https://doi.org/10.1016/j.jhydrol.2020.125138
  2. Alamanos, A., Mylopoulos, N., Loukas, A., & Gaitanaros, D. (2018). An integrated multicriteria analysis tool for evaluating water resource management strategies. Water, 10(12), 1795. https://doi.org/10.3390/w10121795
  3. Ali, I., & Khan, N. (2022). Evaluating the impact of climate change on the agriculture sector of Pakistan using multi-criteria decision making (MCDM). Natural and Applied Sciences International Journal (NASIJ), 3, 72-84. https://doi.org/10.47264/idea.nasij/3.2.6
  4. Ashraf, S., AghaKouchak, A., Alizadeh, A., Mousavi Baygi, M., Moftakhari, H.R., Mirchi, A., Anjileli H., & Madani, K. (2017). Quantifying anthropogenic stress on groundwater resources. Scientific Reports, 7(1), 1-12. https://doi.org/10.1038/s41598-017-12877-4.
  5. Boser, A., Caylor, K., Larsen, A., Pascolini-Campbell, M., Reager, J., & Carleton, T. (2024). Field-scale crop water consumption estimates reveal potential water savings in California agriculture. Nature Communications, 15, 2366. https://doi.org/10.1038/s41467-024-46031-2.
  6. Cai, X., Lasdon, L., & Michelsen, A. (2004). Group decision making in water resources planning using multiple objective analysis. Journal of Water Resources Planning and Management, 130, 4–14. https://doi.org/10.1061/(ASCE)0733-9496(2004)130:1(4)
  7. Çebi, U., Özer, S., Öztürk, O., Aydın, B., & Çakır, R. (2023). Yield and water productivity of rice grown under different irrigation methods. The Journal of Agricultural Science, 161(3), 387–397. https://doi.org/10.1017/S0021859623000308.
  8. Chen, C.T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114, 1-9. https://doi.org/10.1016/S0165-0114(97)00377-1.
  9. Davis, K.F., Seveso, A., Rulli, M.C., & D’Odorico, P. (2017). Water savings of crop redistribution in the United States. Water, 9(2), 83. https://doi.org/10.3390/w9020083.
  10. Garai, T., & Garg, H. (2022). Multi-criteria decision making of water resource management problem (in agriculture field, Purulia district) based on possibility measures under generalized single valued non-linear bipolar neutrosophic environment. Expert Systems with Applications, 205, https://doi.org/10.1016/j.eswa.2022.117715.
  11. Hadelan, L., Jež Rogelj, M., Gugić, J., Crnčan, A., & Zrakić Sušac, M. (2020). Multi‐criteria evaluation of locations for irrigation system implementation. Irrigation and Drainage, 69. https://doi.org/10.1002/ird.2512.
  12. Haghshenas Haghighi, M., & Motagh, M. (2024). Uncovering the impacts of depleting aquifers: A remote sensing analysis of land subsidence in Iran. Science Advances, 10(19), eadk3039. https://doi.org/10.1126/sciadv.adk3039.
  13. Hamidifar, H., Ghorbani, M., Bakhshandeh, M., & Gholami, S. (2023). A multi-criteria multidimensional model for optimal selection of rural water supply systems. Aqua, 72. https://doi.org/10.2166/aqua.2023.028.
  14. Hatami-Marbini, A., & Kangi, F. (2017). An extension of fuzzy TOPSIS for a group decision making with an application to Tehran Stock Exchange. Applied Soft Computing, 52, 1084-1097. https://doi.org/10.1016/j.asoc.2016.09.021
  15. Hosseinzadeh Lotfi, F., & Fallahnejad, R. (2010). Imprecise Shannon’s entropy and multi-attribute decision making. Entropy, 12, 53-62. https://doi.org/10.3390/e12010053
  16. Hwang, C.-L., & Yoon, K.P. (1981). Multiple attribute decision making: Methods and applications. A state-of-the-art survey. Springer-Verlag. https://doi.org/10.1007/978-3-642-48318-9
  17. Izadikhah, M., & Salehi, A. (2014). A novel method to extend SAW for decision-making problems with interval data. Decision Science Letters, 3, 225–236. https://doi.org/10.5267/j.dsl.2013.11.001.
  18. Jafarnejad Chaghooshi, A., Fathi, M.R., & Kashef, M. (2012). Integration of fuzzy Shannon's entropy with fuzzy TOPSIS for industrial robotic system section. Journal of Industrial Engineering and Management (JIEM), 5(1), 102-114. https://doi.org/10.3926/jiem.397
  19. Jahanshahloo, G.R., Lotfi, F.H., & Izadikhah, M. (2006). Extension of the TOPSIS method for decision-making problems with fuzzy data. Applied Mathematics and Computation, 181(2), 1544-1551. https://doi.org/10.1016/j.amc.2006.02.057
  20. Kacprzak, D. (2017). Objective weights based on ordered fuzzy numbers for fuzzy multiple criteria decision-making methods. Entropy, 19(7), 373. https://doi.org/10.3390/e19070373.
  21. Kacprzak, D. (2019). A doubly extended TOPSIS method for group decision making based on ordered fuzzy numbers. Expert Systems with Applications, 116, 243-254. https://doi.org/10.1016/j.eswa.2018.09.023.
  22. Kacprzak, D. (2020). An extended TOPSIS method based on ordered fuzzy numbers for group decision making. Artificial Intelligence Review, 53, 2099–2129. https://doi.org/10.1007/s10462-019-09728-1
  23. Kaya, T., & Kahraman, C. (2010). Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul. Energy, 35, 2517–2527. https://doi.org/10.1016/j.energy.2010.02.051.
  24. Khanzadi, M., Nasirzadeh, F., Eftekhari, N., & Hassani, S. M. H. (2009, August 20-21). Selection of the optimal project execution system using fuzzy multi-criteria decision-making and group opinion aggregation. In Proceedings of the Fifth International Project Management Conference. Tehran, Iran.
  25. Lee, S.-G., Adelodun, B., Ahmad, M.J., & Choi, K.S. (2022). Multi-level prioritization analysis of water governance components to improve agricultural water-saving policy: A case study from Korea. Sustainability, 14(6), 3248. https://doi.org/10.3390/su14063248
  26. Leghari, S.J., Hu, K., Wei, Y., Wang, T., & Laghari, Y. (2024). Modelling the effects of cropping systems and irrigation methods on water consumption, nitrogen fates, and crop yields in the North China Plain. Computers and Electronics in Agriculture, 218, https://doi.org/10.1016/j.compag.2024.108677
  27. Madani, K. (2014). Water management in Iran: What is causing the looming crisis? Journal of Environmental Studies and Sciences, 4(4), 315-328. https://doi.org/s13412-014-0182-z
  28. Meran, G., Siehlow, M., & von Hirschhausen, C. (2021). Integrated water resource management: Principles and applications. In G. Meran, M. Siehlow, & C. von Hirschhausen (Eds.), The Economics of Water (pp. 23–121). Springer. https://doi.org/10.1007/978-3-030-48485-9_3.
  29. Mohammadi, M., Zandhasami, H., & Yazdani, H. (2020). Identification and ranking of collaborative entrepreneurship mechanisms as a type of corporate entrepreneurship using hybrid method (fuzzy Shannon entropy and fuzzy ARAS). Industrial Technology Development, 18(42), 31–52.
  30. Moltz, H., Wallace, C., Sharifi, E., & Bencala, K. (2020). Integrating sustainable water resource management and land use decision-making. Water, 12, https://doi.org/10.3390/w12082282.
  31. Noori, A., Bonakdari, H., Salimi, A.H., & Gharabaghi, B. (2021). A group multi-criteria decision-making method for water supply choice optimization. Socio-Economic Planning Sciences, 77, 101006. https://doi.org/10.1016/j.seps.2020.101006
  32. Noori, R., Maghrebi, M., Mirchi, A., Tang, Q., Bhattarai, R., Sadegh, M., Noury, M., Torabi Haghighi, A., Kløve, B., & Madani, K. (2021). Anthropogenic depletion of Iran's aquifers. Proceedings of the National Academy of Sciences of the United States of America, 118(25), e2024221118. https://doi.org/10.1073/pnas.2024221118
  33. Nouri, M., Homaee, M., Pereira, L.S., & Bybordi, M. (2023). Water management dilemma in the agricultural sector of Iran: A review focusing on water governance. Agricultural Water Management, 288, https://doi.org/10.1016/j.agwat.2023.108480.
  34. Opricovic, S., & Tzeng, G.-H. (2004). Multi-criteria decision making methods: A comparative study. European Journal of Operational Research, 156(3), 445–455. https://doi.org/10.1016/j.ejor.2003.08.012.
  35. Permono, B., & Kurniati, A. (2024). Decision-making processes in resource management: Lessons from the agriculture sector. Journal of Resource Management and Decision Engineering, 3(2), 13-23. https://doi.org/10.61838/kman.jrmde.3.2.3.
  36. Pocco, V., Chucuya, S., Huayna, G., Ingol-Blanco, E., & Pino-Vargas, E. (2023). A multi-criteria decision-making technique using remote sensors to evaluate the potential of groundwater in the arid zone basin of the Atacama Desert. Water, 15(7), 1344. https://doi.org/10.3390/w15071344
  37. Pourmand, E., Mahjouri, N., Hosseini, M., & Nik-Hemmat, F. (2020). A multi-criteria group decision-making methodology using interval type-2 fuzzy sets: Application to water resources management. Water Resources Management, 34, 1-26. https://doi.org/10.1007/s11269-020-02657-7
  38. Priyan, K. (2021). Issues and challenges of groundwater and surface water management in semi-arid regions. In Groundwater Resources Development and Planning in the Semi-Arid Region (pp. 1-17). https://doi.org/10.1007/978-3-030-68124-1_1
  39. Radmehr, A., Bozorg-Haddad, O., & Loaiciga, H. (2022). Integrated strategic planning and multi-criteria decision-making framework with its application to agricultural water management. Scientific Reports, 12, https://doi.org/ 10.1038/s41598-022-12194-5.
  40. Sadi-Nezhad, S., & Damghani, K. K. (2010). Application of a fuzzy TOPSIS method based on modified preference ratio and fuzzy distance measurement in assessment of traffic police centers performance. Applied Soft Computing Journal, 10, 1028-1039.
  41. Sheikhipoor, B., Javadi, S., & Banihabib, M. E. (2018). A hybrid multiple criteria decision-making model for the sustainable management of aquifers. Environmental Earth Sciences, 77. https://doi.org/10.1007/s12665-018-7894-4.
  42. Tork, H., Javadi, S., & Hashemy Shahdany, S.M. (2021). A new framework of a multi-criteria decision making for agriculture water distribution system. Journal of Cleaner Production, 306, https://doi.org/10.1016/j.jclepro.2021.127178
  43. Tsakmakis, I., Kokkos, N., Pisinaras, V., Papaevangelou, V., Hatzigiannakis, E., Arampatzis, G., Gikas, G., Linker, R., Zoras, S., Evagelopoulos, V., Tsihrintzis, V., Battilani, A., & Sylaios, G. (2017). Operational precise irrigation for cotton cultivation through the coupling of meteorological and crop growth models. Water Resources Management, 31, 1547–1562. https://doi.org/10.1007/s11269-016-1548-7
  44. Thảo, N., & Nhung, L. (2019). A novel multi-criteria decision making method for evaluating water reuse applications under uncertainty. Vietnam Journal of Agricultural Sciences, 1(3), 230-239. https://doi.org/10.31817/vjas.2018.1.3.04
  45. Yilmaz, B., & Harmancioglu, N. (2010). Multi-criteria decision making for water resource management: A case study of the Gediz River Basin, Turkey. Water SA, 36, 563-576. https://doi.org/10.4314/wsa.v36i5.61990
  46. Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
CAPTCHA Image