تعیین شاخص یک‌پارچه آب- اقتصاد- محیط‌زیست برای تخصیص منطقه‌ای منابع آب در استان‌های ایران

اقتصاد و توسعه منطقه ای

مقاله 3، دوره 28، 1بهار و تابستان 21، شهریور 1400، صفحه 41-74   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.22067/erd.2021.69591.1028

نویسندگان

محمد هادی اکبرزاده¹؛ مسعود خداپناه^{* 2}؛ منصور زراء نژاد³

¹دانشجوی دکتری رشته اقتصاد، دانشکده اقتصاد و علوم اجتماعی، دانشگاه شهید چمران اهواز، اهواز، ایران

²دانشیار اقتصاد و عضو هیئت علمی دانشکده اقتصاد و علوم اجتماعی، دانشگاه شهید چمران اهواز

³استاد تمام و عضو هیئت علمی دانشکده اقتصاد و علوم اجتماعی دانشگاه شهید چمران اهواز، اهواز، ایران.

چکیده

چکیده
بحران­های آبی در بسیاری نقاط جهان به­عنوان چالش­هایی اصلی در برابر توسعه پایدار مناطق شناخته می­شوند. یکی از راه­حل­های مواجهه با چالش­های مربوط به کم­آبی، استفاده از سیستم­های یک­پارچه آب-اقتصاد- محیط­زیست برای سیاست­گذاری پایدار منابع آب منطقه­ای است. با این حال، هنوز سیاست­گذاری منطقه­ای منابع آب در استان­های ایران بر اساس یک سیستم یک­پارچه برای تخصیص منابع آب در قالب یک فرآیند هماهنگ در توسعه پایدار بخش­های آبی، اقتصادی-اجتماعی و محیط­زیست انجام نمی­شود. هدف این پژوهش تعیین شاخص یک­پارچه آب-اقتصاد-محیط­زیست برای سیاست­گذاری منطقه­ای منابع آب در استان­های ایران با بهره­گیری از سیستم ارزیابی جامع فازی و رویکرد آنتروپی بوده است. برای این منظور، پس از تعیین شاخص آب- اقتصاد – محیط­زیست بر اساس جدیدترین مبانی نظری و تجربی، این شاخص برای 31 استان در کشور ایران برآورد شده است. همچنین وضعیت هر یک از استان­های کشور در زیرشاخص­های پنج­گانه منابع آب، تکنولوژی و حمل­ونقل، اقتصادی، اجتماعی و محیط­زیست تعیین شده است. مطابق یافته­های پژوهش، استان­های اردبیل، کرمان، خراسان شمالی، سمنان، سیستان و بلوچستان، فارس، قزوین، مرکزی و یزد دارای وضعیت نسبتاً ضعیف در زیرشاخص منابع آب بوده­اند. همچنین نتایج حاصل از برآورد شاخص کل آب- اقتصاد- محیط­زیست، استان­های گیلان، مازندران، چهارمحال بختیاری و خوزستان به­عنوان مناسب­ترین استان­های ایران برای اجرای راهبرد آب مجازی شناخته می­شوند. در سایر استان­های کشور نیز، بسته به وضعیت قوت یا ضعف آن استان در هر یک از ابعاد پنج­گانه در شاخص یک­پارچه آب- اقتصاد- محیط‌زیست، نیازمند اتخاذ رویکرد و سیاست­گذاری متناسب با شرایط خاص آن استان برای دستیابی به توسعه منطقه­ای پایدار وجود دارد.

کلیدواژه‌ها

شاخص یک‌پارچه؛ منابع آب منطقه‌ای؛ آنتروپی شانون؛ سیستم ارزیابی جامع فازی؛ استان‌های ایران

سایر فایل های مرتبط با مقاله

chkide 21.pdf

مراجع

References

Abu-Sharar, T. M.; Al-Karablieh, E. K. & Haddadin, M. J. (2012). Role of Virtual Water in Optimizing Water Resources Management in Jordan. Water resources management, 26(14), 3977-3993.

 Allan, J. A. (1997). 'Virtual water': A Long-Term Solution for Water Short Middle Eastern economies? (pp. 24-29). London: School of Oriental and African Studies, University of London.

Allan, J. A. (2003). Virtual Water-the Water, Food, and Trade Nexus. Useful Concept or Misleading Metaphor? Water International, 28(1), 106-113.

Amoori Z.; Bordbar, A. & Heidanejad, M. (2014). 'Quantity and Quality Evaluation of Virtual water trade in Iran (Case study of Khuzestan province), International Journal of Geology, Agriculture and Environmental Sciences, Volume 2, Issue 1, February, 2014.

Ansink, E. (2010). Refuting Two Claims about Virtual Water Trade, Ecological Economics, 69(10), 2027-2032.

Arabi Yazdi, A.; Alizadeh, A. & Mohammadian, F. (2009). Study of ecological water footprint in Iran's agricultural sector, Journal of Water and Soil (Agricultural Sciences and Industries), Volume 23, Number 4, Winter, 2009, pp. 15-1 (in Persian).

Arya, V. & Kumar, S. (2020). Knowledge measure and entropy: a complementary concept in fuzzy theory, Granular Computing, 1-13.

Azadi-Nejad, A.; Amadeh, H. & Emami Meybodi, A. (2010). Effective factors in technical efficiency of the industrial sector in Iranian provinces, Economic Research, Volume 49, 1, pp. 173-188 (in Persian).

Bakhshoodeh, M. & Dehghanpur, H. (2016). Modeling Crop Cultivation Pattern Based on Virtual Water Trade: Evidence from Marvdasht in Southern Iran. Iran Agricultural Research, 34(2), 29-34.

Cai, B.; Zhang, W., Hubacek, K.; Feng, K.; Li, Z.; Liu, Y. & Liu, Y. (2019). Drivers of Virtual Water Flows on Regional Water Scarcity in China. Journal of Cleaner Production, 207, 1112-1122.

Caldera, U.; Bogdanov, D., Fasihi, M., Aghahosseini, A. & Breyer, C. (2020). Securing future water supply for Iran through 100% renewable energy powered desalination. International Journal of Sustainable Energy Planning and Management, 23, pp 36-89.

Chen, G. Q., & Li, J. S. (2015). Virtual water assessment for Macao, China: highlighting the role of external trade. Journal of Cleaner Production, 93, 308-317.

Cui, X.; Wu, X., He, X., Li, Z., Shi, C., & Wu, F. (2018). Regional Suitability of Virtual Water Strategy: Evaluating with an Integrated Water-Ecosystem-Economy Index, Cleaner Production, 199, 659-667.

Darbandsari, P.; Kerachian, R., & Malakpour-Estalaki, S. (2017). An Agent-based behavioral simulation model for residential water demand management: The case-study of Tehran, Iran, Simulation Modelling Practice and Theory, 78, 51-72.

Delgado, A., & Romero, I. (2017). Environmental Conflict Analysis Using an Integrated Grey Clustering and Entropy-Weight Method: A Case Study of a Mining Project in Peru, Environmental Modelling & Software, 77, 108-121.

Duarte, R.; Pinilla, V., & Serrano, A. (2016). Understanding Agricultural Virtual Water Flows in the World from an Economic Perspective: A Long-Term Study. Ecol. Indicators 2016, 61, 980-990.

El-Sadek, A. (2012). Virtual Water: An Effective Mechanism for Integrated Water Resources Management, Agricultural Sciences, 2(03), 248.

Faramarzi, M., Yang, H., Mousavi, J., Schulin, R., Binder, C. R., & Abbaspour, K. C. (2010). Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran. Hydrology and Earth System Sciences, 14(8), 1417-1433.

Friesen, J.; Sinobas, L. R., Foglia, L., & Ludwig, R. (2017). Environmental and social-economic methodologies and solutions towards integrated water resources management, 906-908.

Garrick, D. E., Hanemann, M., & Hepburn, C. (2020). Rethinking the economics of water: an assessment. Oxford Review of Economic Policy, 36(1), 1-23.

Gawel, E., & Bernsen, K. (2013). What is wrong with Virtual Water Trading? On the Limitations of the Virtual Water Concept, Environment and Planning C: Government and Policy, 31(1), 168-181.

Gong, L., & Jin, C. (2016). Fuzzy comprehensive evaluation for carrying capacity of regional water resources, Water resources management, 23(12), 2505-2513.

Haak, L., & Pagilla, K. (2020). The water-economy nexus: a composite index approach to evaluate urban water vulnerability. Water Resources Management, 34(1), 409-423.

Hoekstra, A. Y., Karandish, F. & Hogeboom, R. J., (2021). Physical versus virtual water transfers to overcome local water shortages: A comparative analysis of impacts, Water Resources, 147, 103811.

Holmberg, J., & Sandbrook, R. (2019). Sustainable development: what is to be done? Policies for a small planet (pp. 19-38). Routledge.

Islamic & Iranian Center of Progress (2016). Iran's water resources management: challenges and strategies, Water Institute, Environment, Food Security and Natural Resources, 2016 (In Persian).

Ismaili-Fard, M. & Kaveh F. H. (2017). Pathology of water policy in Iran, Quarterly Journal of Social and Cultural Strategy, Fifth Year, No. 21, Winter 2017, pp. 169-197 (in Persian).

139. Reimer. J. (2012). On the Economics of Virtual Water Trade, Ecological
     Economics, 75:135-139.

Jalil-Pir, H. (2012). The role of water pricing in the agricultural sector on the balance of water resources, Economic Journal, Monthly Review of Economic Issues, No. 2, May 2012, 128-119 (in Persian).

Jia, S.; Long, Q., & Liu, W. (2017). The Fallacious Strategy of Virtual Water Trade. International Journal of Water Resources Development, 33(2), 340-347.

Joodaki, G., Wahr, J., & Swenson, S. (2014). Estimating the human contribution to groundwater depletion in the Middle East, from GRACE data, land surface models, and well observations, Water Resources Research, 50(3), 2679-2692.

Kacprzak, D. (2017). Objective weights based on ordered fuzzy numbers for fuzzy multiple criteria decision-making methods. Entropy, 19(7), 373.

Karamouz, M., Yazdi, M. S., Ahmadi, B., & Zahraie, B. (2011). A system dynamics approach to economic assessment of water supply and demand strategies. In World Environmental and Water Resources Congress 2011: Bearing Knowledge for Sustainability (pp. 1194-1203).

Katyaini, S., Barua, A., & Duarte, R. (2020). Science-policy interface on water scarcity in India: Giving ‘visibility’to unsustainable virtual water flows (1996–2014). Journal of Cleaner Production, 275, 124059.

Khalili, d. (2016). Challenges facing water resources management in drought conditions in Iran, Journal of Strategic Research in Agricultural Sciences and Natural Resources, 1, 2, pp. 149-164 (in Persian).

Liu, J., Hull, V., Batistella, M., DeFries, R., Dietz, T., Fu, F., ... & Zhu, C. (2013). Framing sustainability in a telecoupled world. Ecology and Society, 18(2).

Madani, K. (2014). Water management in Iran: what is causing the looming crisis? Journal of environmental studies and sciences, 4(4), 315-328.

Madani, K. Amir A. & Ali Mirchi (2016). Iran’s Socio-economic Drought: Challenges of a Water-Bankrupt Nation, Iranian Studies, 49:6, 997-1016.

Majerník, V. (2014). Entropy—A universal concept in sciences. Natural Science, 2014.

Manshadi, H. D., Niksokhan, M. H., & Ardestani, M. (2015). A quantity-quality model for inter-basin water transfer system using game theoretic and virtual water approaches. Water Resources Management, 29(13), 4573-4588.

Merrett, S. (2003). Virtual Water and the Kyoto Consensus: A Water Forum Contribution. Water International, 28(4), 540-542.

Mohammadi-Kanigolzar, F., Ameri, J. D., & Motee, N. (2014). Virtual Water Trade as a Strategy to Water Resource Management in Iran. Journal of Water Resource and Protection, 6(02), 141.

Mohammad-Jani A. & Yazdanian N. (2014). Analysis of the water crisis in Iran and its management requirements, Ravand Quarterly Journal, Volume 21, Numbers 65 & 66, 2014, pp. 117-144 (in Persian).

Mousavi, S. N., Akbari, S. M. R., Soltani, Gh,. & M. Zarei (2010). Virtual water, a new strategy to deal with water crisis, The First National Conference on Water Crisis Management, March 2010 (in Persian).

Nasrollahi, M., Khosravi, H., Moghaddamnia, A., Malekian, A., & Shahid, S. (2018). Assessment of drought risk index using drought hazard and vulnerability indices.  Journal of Geosciences, 11(20), 1-12.

Nasrollahi, Z. & Zarei, M. (2018). "Study of virtual water flows in Iran's economy: analysis of water sector relationships using output data approach", Quarterly Journal of Econometric Modeling, Volume 2, Issue 4, Fall 2018 (in Persian).

Nguyen, T. D., Edenhofer, O., Grimalda, G., Jakob, M., Klenert, D., Schwerhoff, G., & Siegmeier, J. (2018). Policy options for a socially balanced climate policy. G20 Insights. T20 Task Force on Global Inequality and Social Cohesion.

Pires, A., Morato, J., Peixoto, H., Botero, V., Zuluaga, L. (2017). Sustainability Assessment of indicators for integrated water resources management. Science of the total environment, 578, 139-147.

Pouran, R. Raghfar H. Ghasemi, A. & Bazazan, F. (2018). Calculating the economic value of virtual water using maximizing irrigation water efficiency approach", Iranian Journal of Water Economics, Volume 6, Number 21, Spring 2018. pp. 189-212 (in Persian).

Qasemipour, E., & Abbasi, A. (2020). Virtual water flow and water footprint assessment of an arid region: A case study of South Khorasan province, Iran. Water, 11(9), 1755.

Qudusi, H. & Davari H. (2017). Critical analysis of virtual water from a policy perspective. Water and Sustainable Development, 3 (1), 47-58 (in Persian).

Razavi, S. & Davari, K. (2014). The role of virtual water management in Iran water resources management, Water and Sustainable Development, Volume 1, No. 1, March 2014, pp. 9-18 (in Persian).

Roodposhti, M., Aryal, J., Shahabi, H., & Safarrad, T. (2016). Fuzzy shannon entropy: A hybrid gis-based landslide susceptibility mapping method. Entropy, 18(10), 343.

Runkler, T. A. (1997). Selection of appropriate defuzzification methods using application specific properties. IEEE transactions on fuzzy systems, 5(1), 72-79.

Sartori, M., Schiavo, S., Fracasso, A., & Riccaboni, M. (2017). Modeling the Future Evolution of the Virtual Water TradeN: A combination of Network and Gravity Models. Water Resources, 110, 538-548.

Sarvin., Etaei, S., & Montaseri, M. (2021). Development of hydro-social-economic-environmental sustainability index (HSEESI) in integrated water resources management. Environmental Monitoring and Assessment, 193(8), 1-29.

Shannon, C. E. (2001). A Mathematical Theory of Communication. SIGMOBILE Mob Comput Commun Rev, 5 (1): 3–55.

Siddique, Muhammad. "Fuzzy decision making using max-min, MMR methods." (2009).

Sun, S., Wang, Y., Engel, B. A., & Wu, P. (2016). Effects of Virtual Water Flow on Regional Water Resources Stress: A Case Study of Grain in China. Science of the Total Environment, 550, 871-879.

Tahamipour, M. Abbas, S. & Arab Mazar, A. (2015). "Virtual water trade pattern in economic activities of Gilan province: application of augmented input-output tables, Quarterly Journal of Environmental Sciences, Volume 13, Issue 3, Fall 2015 (in Persian).

Talon, A., & Curt, C. (2017). Selection of appropriate defuzzification methods: Application to the assessment of dam performance. Expert Systems with Applications, 70, 160-174.

Tomislav, K. (2018). The concept of sustainable development: From its beginning to the contemporary issues. Zagreb International Review of Economics & Business, 21(1), 67-94.

Van der Voort, N., & Vanclay, F. (2015). Social impacts of earthquakes caused by gas extraction in the Province of Groningen, The Netherlands, Environmental Impact Assessment Review, 50, 1-15.

Wang, Z., Zhang, L., Zhang, Q., Wei, Y. M., Wang, J. W., Ding, X., & Mi, Z. (2019). Optimization of Virtual Water Flow via Grain Trade within China. Ecological Indicators, 97, 25-34

Wichelns, D. (2004). The Policy Relevance of Virtual Water Can Be Enhanced by Considering Comparative Advantages. Agricultural Water Management, 66(1), 49-63.

Wu, D. S., Feng, X., & Wen, Q. Q. (2011). The Research of Evaluation for Growth Suitability of Carya Cathayensis Sarg. Based on PCA and AHP. Procedia Engineering, 15, 1879-1883.

www.amar.org.ir

www.doe.ir

www.iwmi.cgiar.org

Yang, H.; Zehnder, A.J. (2002). Water Scarcity and Food Import: A Case Study for Southern Mediterranean Countries, World Development, 2002, 30, 1413-1430.

Ye, W., Xu, X., Wang, H., Wang, H., Yang, H., & Yang, Z. (2016). Quantitative assessment of resources and environmental carrying capacity in the northwest temperate continental climate ecotope of China. Environmental Earth Sciences, 75(10), 868.

Zadeh, L. A. (2015). Fuzzy logic—a personal perspective, Fuzzy sets and systems, 281, 4-20.

Zulqarnain, R. M., Xin, X. L., Saeed, M., & Ahmed, N. (2020). Application of Interval Valued Fuzzy Soft Max-Min Decision Making Method in Medical Diagnosis. International Journal of Pharmaceutical Sciences Review and Research, 62(1), 56-60.