بررسی همبست آب، انرژی و غذا با رویکرد پویایی سیستم‌ها؛‌ مطالعه موردی دشت ورامین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه اگرواکولوژی، پژوهشکده علوم محیطی، دانشگاه شهید بهشتی، تهران، ایران

2 گروه اقتصاد محیط زیست و منابع طبیعی، پژوهشکده علوم محیطی، دانشگاه شهید بهشتی، تهران، ایران

چکیده

سابقه و هدف: تغییرات اقلیمی و اکوسیستمی در هماهنگی با عواملی چون رشد جمعیت و مدیریت نادرست منابع،
بسیاری از الگوهای مدیریت منابع طبیعی را به چالش کشیده است. هدف از این تحقیق شناخت روابط همبست
آب، انرژی و غذا در دشت ورامین به روش مدل ذهنی و پویایی همبست آب، انرژی و غذا تحت سناریوهای سیاستی
بود.
مواد و روش ها:  داده ها و روابط مربوط به مدل ذهنی از طریق گفتگو و مشارکت با کشاورزان و مدیران منطقه
جمع آوری گردید. داده های مربوط به مدل پویایی همبست نیز از طریق Mental Modeler به وسیله نرمافزار
که برای منطقه مورد مطالعه توسعه WEF سازمان ها، ذینفعان منطقه و مقالات معتبر جمع آوری شد. مدل همبست
داده شده است از روابط به هم پیوسته برای مدلسازی ز یرسیستم های آب، کشاورزی و انرژی و تعاملات آنها تشکیل
ساخته شد و دوره شبیه سازی یک دوره 20 ساله در نظر Vensim شده است. مدل شبیه سازی با استفاده از نرم افزار
گرفته شد. معادلات حاکم در هر ز یرسی ستم بر اساس معادلات پا یه رویکرد پو یا یی سیستم ها و نمودارهای حلقه
علی هر ز یرسیستم با استفاده از روابط و بازخوردهای مثبت و منفی ایجاد شد.
نتایج و بحث: نتایج مدلسازی پویایی همبست نشان داد وضعیت منابع آب سطحی و امنیت آبی دشت طی دوره
20 سال به ترتیب برابر با 158 میلیون مترمکعب و 162 - میلیون مترمکعب خواهد بود؛ که نشان از کاهش منابع
در مقا یسه با وضعیت پایه دارد. نتایج مدل بدون اعمال سناریو نشان داد طی دوره 20 ساله حجم آبخوان دشت
ورامین از مقدار 4000 میلیون مترمکعب به 2700 میلیون مترمکعب کاهش خواهد یافت. این موضوع نشان می دهد
سیاست های تأمین منابع آب ازجمله استفاده بی رویه از چاه ها، توسعه شهرنشینی و ایجاد صنایع و همچنین عدم
افزایش بهره وری آب کشاورزی از طریق روش های نوین آ بیاری دلیل بروز چنین مسئله ای است. اعمال سناریوهای
تخصیص نیاز محیط زیستی تالاب بندعلیخان نشان داد دشت توان اکولوژیکی برای تخصیص آب به تالاب نخواهد
داشت به طوریکه در 20 سال آینده امنیت آبی دشت به 180 - میلیون مترمکعب می رسد. همچنین اعمال سناریو
افزایش راندمان آبیاری بدون افزایش سطح ز یر کشت از 58 درصد به 70 درصد در بهبود کاهش تقاضای آب
کشاورزی و افزایش سطح کشت مؤثر بود. افزایش سطح زیر کشت نیز تا مقدار 41600 هکتار اثر مثبت بر تقاضای
آب کشاورزی داشت اما بیش از این مقدار سبب افزایش فشار منابع آبی گردید. بر اساس محدودیت های منابع آ بی
و کاهش امنیت آب در دشت ورامین، تولید محصول دشت نیز با کاهش روبه رو خواهد شد. دشت ورامین به دلیل
همجواری با شهرستان تهران نقش مهمی در تأمین نیاز مردم تهران و شهرستان های اطراف دارد.
نتیجه گیری: بررسی نتایج و روند مقایسه داده ها نشان داد طی دوره 20 ساله، دشت ورامین وضعیت نامطلوبی در
زمینه منابع آب و تولید غذا خواهد داشت. مدیریت منابع دشت ورامین نیازمند تغییر در باورها و ارزش های سازمانی،
کشاورزی و توسعه ای دارد. توسعه سیستم های خورشیدی  به منظور تأمین نیاز انرژی، راه اندازی تصفیه خانه فاضلاب
شهرستان ورامین و توسعه تصفیه خانه جنوب تهران، حرکت به سمت فشرده ساز ی پایدار در ایجاد پایداری منابع
دشت به منظور بهره برداری صحیح منابع مؤثر است. از سویی دیگر افزایش راندمان آبیاری بدون افزایش سطح کشت
می تواند در متعادل کردن وضعیت فعلی کمک کننده باشد به طوریکه با اجرای سیاست های برنامه ششم توسعه
تقاضای آب کشاورزی تا حدودی کاهش می یابد و فشار بر منابع آب ز یرزمینی کاسته می شود.

کلیدواژه‌ها

عنوان مقاله [English]

Investigating of Water, Energy, and Food Nexus with the Systems Dynamics Approach; a Case Study of Varamin Plain

نویسندگان [English]

  • Alireza Shahmohammadi 1
  • Korous Khoshbakht 1
  • Hadi Veisi 1
  • Mohammad Reza Nazari 2
1 Department of Agroecology, Shahid Beheshti University, Environmental Sciences Research institute, Shahid Beheshti University, Evin, Tehran, Iran
2 Environment and Natural Resources Economics Department, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran
چکیده [English]

Introduction: Climate and ecosystem changes in coordination with other factors have challenged
many basic paradigms of natural resource management. The purpose of this research was to know
the correlation between water, energy, and food in Varamin Plain by the method of the mental
model and the dynamics of water, energy, and food correlation under political scenarios.
Material and Methods: Data and relationships related to the mental model were collected
through interviews with the farmers and managers of the region using the Mental Modeler
software. Data related to the correlation dynamics model was also collected through organizations,
regional stakeholders and authoritative articles. The WEF nexus model developed for the study
area consists of interconnected relationships for modeling water, agriculture and energy
subsystems and their interactions. The simulation model was built using Vensim software, and the
simulation period was considered a 20-year period. The equations in each subsystem were created
based on the basic equations of the system dynamics approach and the causal loop diagrams of
each subsystem using relationships and positive and negative feedbacks.
Results and Discussion: The results of system dynamic modeling showed that the state of surface water
resources and water security of the plain will be 158 million cubic meters and -162 million cubic meters,
respectively, during the period of 20 years, which shows the reduction of resources compared to the
original situation. The results of the model without applying the scenario showed that the volume of the
Varamin Plain aquifer will decrease from 4000 million cubic meters to 2700 million cubic meters during
the 20-year period. This shows that the policies of providing water resources, including the excessive use
of wells, the development of urbanization and the creation of industries, as well as the lack of increase in
the productivity of agricultural water through modern irrigation methods, are the reasons for such a
problem. The application of scenarios for the allocation of the environmental needs of the Bandalikhan
wetland showed that the plain will not have the ecological capacity to allocate water to the wetland, so
that in the next 20 years, the water security of the plain will decrease to 180 million cubic meters. Also,
applying the scenario of increasing irrigation efficiency without increasing the cultivated area from 58%
to 70% was effective in improving the reduction of agricultural water demand and increasing the
cultivated area. The increase in cultivated area up to 41,600 hectares had a positive effect on agricultural
water demand, but more than this amount caused the pressure on water resources to increase. Based on
the limitations of water resources and the reduction of water security in the Varamin Plain, the production
of the plain's products will also face a decrease. Due to its proximity to the city of Tehran, the Varamin
Plain plays an important role in meeting the needs of the people of Tehran and the surrounding cities.
Conclusion: Examining the results and comparing the data showed that during the 20-year period,
Varamin Plain will have an unfavorable situation regarding water resources and food production.
The management of the resources of Varamin Plain requires a change in organizational,
agricultural and developmental approaches. The development of solar systems in order to meet
the energy needs, the establishment of the wastewater treatment plant in Varamin and the
development of the treatment plant south of Tehran, as well as moving towards sustainable
compression is effective in creating the stability of the plains resources in order to properly exploit
the resources. On the other hand, increasing the irrigation efficiency without increasing the
cultivation area can help in balancing the current situation so that with the implementation of the
policies of the sixth development plan, the demand for agricultural water will be reduced to some
extent and the pressure on the underground water resources will be reduced.

کلیدواژه‌ها [English]

  • Keywords: : Mental model
  • Sustainable intensification
  • Systems dynamics
  • Underground water resources
  • Water security

مراجع

Abbasi, F., Sarrab, F. and Abbasi, N., 2015. Evaluation of the efficiency of irrigation water in Iran. Irrigation and Drainage Structures Engineering Research Journal. 17)67(, 113-128. (In Persian with English abstract). https://doi.org/10.22092/aridse.2017.109617.
Ahmadi, A., Malek Mohammadi, B. and Mozaal, L., 2021. Use of modeling in the development of scenarios of water resources and uses; Case study: study area of Varamin Plain. Journal of water and sustainable development. 8(3), 1-10. (In Persian with English abstract). https://doi.org/10.22067/JWSD.V8I3.2021.1030.
Ahmadvand, A., Varandinaderi, A., Bastan, M. and Yahyaei, M., 2014. Analysis of Tehran construction and demolition waste management with system dynamics approach. Asian Journal of Research in Business Economics and Management. 4(8), 234-242.
Alizadeh, H., Liaghat, A. and Sohrabi, T., 2014. Assessing pressurized irrigation systems development scenarios on groundwater resources using system dynamics modeling. Journal of Water and Soil Resources Conservation. 3(4), 1-15. (In Persian with English abstract). SID. https://sid.ir/paper/232321/en.
Arnold, L.R., 2011. Estimates of Deep-Percolation Return Flow beneath a Flood- and a Sprinkler-Irrigated Site in Weld County, Colorado, U.S. Geological Survey Scientific Investigations Report 2011–5001, US Geological Survey: Reston, VA, USA, 225p.
Azizi, H.R., Nejatian, N., Athari, M.A., Hashemi, S.S., 2021. The effects of climate change on the drought trend of Varamin plain using De-Martonne index. Newar. 45(112-113), 67-76. (In Persian with English abstract). https://doi.org/10.30467/NIVAR.2021.266357.1177
Azizi, H.R., Nejatian, N., 2019. Calculation of underground water balance of Varamin Plain. Geography and Human Relationships. 3(3), 189-204. (In Persian with English abstract). https://doi.org/ 10.22034/GAHR.2021.263228.1487.
Bala, B.K., Arshad, F.M., Noh, K.M., 2017. Systems thinking: system dynamics. In System Dynamics. Springer, Singapore. 15-35. https://link.springer.com/book/10.1007/978-981-10-2045-2.
Benson, D., Gain, A.K. and Rouillard, J.J., 2015. Water governance in a comparative perspective: From IWRM to a “nexus” approach? Water Alternatives. 8 (1), 756–773.
Soares Dal Poz, M.E., de Arruda Ignácio, P.S., Azevedo, A., Francisco, E.C., Piolli, A.L., Gheorghiu da Silva, G., Pereira Ribeiro, T., 2022. Food, Energy and Water Nexus: An Urban Living Laboratory Development for Sustainable Systems Transition. Sustainability. 14(12), 7163.‏ https://doi.org/10.3390/su14127163.
Denicola, E., Aburizaiza, O.S., Siddique, A., Khwaja, H., 2015. Climate Change and Water Scarcity: The Case of Saudi Arabia. Annals of Global Health. 81(3), 342–353. https://doi.org/10.1016/j.aogh.2015.08.005.
Erb, K.H., Haberl, H., DeFries, R., Ellis, E., Krausmann, F., Verburg, P.H., 2012. Pushing the Planetary Boundaries. Science. 14, 1419-1420.  https://doi.org/10.1126/science.338.6113.1419-d.
FAO, 2014. Walking the Nexus Talk.  Assessing the water-energy-food nexus in the context of the sustainable energy for all initiative. Retrieved from http://www.fao.org.
FAO, 2019. Macronutrients and micronutrients. Available online at http://www.fao.org/elearning/Course/NFSLBC/en/story_content/external_files/Essential_Nutrients.pdf
FAO, 2021. World Food Situation. FAO: Rome, Italy.
Ferrati, R., Canziani, G.A., Moreno D.R., 2005. Estero del Ibera: hydrometeorological and hydrological characterization. Ecological Model. 186, 3–15. https://doi.org/10.1016/j.ecolmodel.2005.01.021.
Garg, K.K., Akuraju, V., Anantha, K.H., Singh, R., Whitbread, A.M., Dixit, S., 2022. Identifying potential zones for rainwater harvesting interventions for sustainable intensification in the semi-arid tropics. Scientific Reports. 12(1), 1-18. https://www.nature.com/articles/s41598-022-07847-4.
Glykas, M., 2010. Fuzzy cognitive maps: Advances in theory, methodologies, tools and applications (Vol. 247). Springer Science & Business Media.‏ https://link.springer.com/book/10.1007/978-3-642-03220-2.
Gray, S.R.J., Gagnon, A.S., Gray, S.A., O’Mahony, C., Muir, D., Falaleeva, M., 2014. Are local coastal managers detecting the problem? Assessing stakeholder perception of climate vulnerability using Fuzzy Cognitive Mapping. Ocean and Coastal Management. 94, 74-89. https://doi.org/10.1016/j.ocecoaman.2013.11.008.
Hajjar R., Kozak R.A., 2015. Exploring public perceptions of forest adaptation strategies in Western Canada: Implications for policy-makers. Forest Policy and Economics. 61, 59–69. https://doi.org/10.1016/j.forpol.2015.08.004.
Henly-Shepard, S., Gray, S., Cox, L., 2015. The use of participatory modeling to promote social learning and facilitate community disaster planning. Environmental Science & Policy. 45, 109-122. https://doi.org/10.1016/j.envsci.2014.10.00.
Hobbs, R.J., 2016. Degraded or just different? Perceptions and value judgments in restoration decisions. Restoration Ecology. 24, 153–158. https://doi.org/10.1111/rec.12336.
Jones, N. A., Perez, P., Measham, T. G., Kelly, G. J., d’Aquino, P., Daniell, K. A., Ferrand, N., 2009. Evaluating participatory modeling: developing a framework for cross-case analysis. Environmental management. 44(6), 1180. https://doi.org/10.1007/s00267-009-9391-8.
Jones, N.A., Ross, H., Lynam, T., Perez, P. and Leitch, A., 2011. Mental Models: An Interdisciplinary Synthesis of Theory and Methods. Ecology and Society. 16(1), 46. https://www.jstor.org/stable/26268859.
Karimlou, N., Hassani, A., Rashidi Mehrabadi, A., Nazari, M.R., 2020. Developing a model for decision-makers in dynamic modeling of urban water system management. Water Resource Management. 34 (2), 481-499. https://doi.org/10.1007/s11269-019-02428-z.
Khoshneshin, F. and Bastan, M., 2014. Analysis of dynamics of crisis management in the earthquake and performance Improvement using system dynamics methodology. 10th International Conference on Industrial Engineering, University of Tehran, Tehran, Iran.
Larson, M.A., Heintzman, R.L., Titus, J.E., Zhu, W., 2016. Urban wetland characterization in south-central New York State. Wetlands. 36, 821-829.‏ https://doi.org/10.1007/s13157-016-0789-9.
Meyer, K., Kurian, M., 2017. The Role of International Cooperation in Operationalizing the Nexus in Developing Countries: Emerging Lessons of the Nexus Observatory. In: Abdul Salam, P., Shrestha, S., Pandey, V.P., Anal, A.K. (Eds.), Water‐Energy‐Food Nexus: Principles and Practices. Wiley. pp 89-102.‏
Ministry of Agricultural Jihad, 2020. Agricultural statistics, second volume of 2022. Planning and economic deputy, information and communication technology center. 93 pages. Available online at: https://www.maj.ir/Dorsapax/userfiles/Sub65/amar99-1400.pdf
Ministry of Energy, 2015. Iran Water Resources Management Company. Water balance report of Varamin plain study area.
Mo, L., Chen, J., Xie, Y., 2023. Wetlands conservation in Beijing of China: Present status and development strategies. Watershed Ecology and the Environment. 5, 73-79.‏ https://doi.org/10.1016/j.wsee.2023.01.002.
Mohanty, P., Patnaik, S., 2017. Energy‐Centric Operationalizing of the Nexus in Rural Areas: Cases from South Asia. In: Abdul Salam, P., Shrestha, S., Pandey, V.P., Anal, A.K. (Eds.), Water‐Energy‐Food Nexus: Principles and Practices. Wiley. pp117-126.‏
Monem, M.J., Delavar, M., Hosseini, M., 2020. Application and Evaluation of Water, Food and Energy (NEXUS) in Irrigation Networks Management: Case Study of Zayandehrud Irrigation Network, Iranian Jour. of Irrigation & Drainage. 14, 276-285. (In Persian with English abstract).  https://doi.org/20.1001.1.20087942.1399.14.1.24.7.
Newaz, M.W., Rahman, S., 2019. Wetland resource governance in Bangladesh: An analysis of community-based co-management approach. Environmental Development. 32, 100446.‏ https://doi.org/10.1016/j.envdev.2019.06.001.
Newell, R., Raimi, D., Villanueva, S. and Prest, B., (2021). Global energy outlook 2021: pathways from Paris. June, https://media.rff.org/ documents/RFF_GEO_2021_Report_1.pdf
Nyam, Y.S., Kotir, J.H., Jordaan, A., Ogundeji, A.A., 2022. Identifying behavioural patterns of coupled water‐agriculture systems using system archetypes. Systems Research and Behavioral Science. 39(2), 305-323. https://doi.org/10.1002/sres.2753.
Pakmehr, S., Yazdanpanah, M., Baradaran, M., 2021. Explaining farmers’ response to climate change-induced water stress through cognitive theory of stress: An Iranian perspective. Environment, Development and Sustainability. 23, 5776–5793. https://doi.org/10.1007/s10668-020-00846-3.
Phan, J.C.R., Smart, O., Sahin, S.J., Capon, W.L., 2018.  Hadwen Assessment of the vulnerability of a coastal freshwater system to climatic and non-climatic changes: a system dynamics approach. Journal of Clean Production. 183, 940-955. https://doi.org/10.1016/j.jclepro.2018.02.169.
Ravar, Z., Zahraie, B., Sharifinejad, A., Gozini, H., Jafari, S., 2020. System dynamics modeling for assessment of water food–energy resources security and nexus in Gavkhuni basin in Iran. Ecological Indicators. 108, 105682.‏ https://doi.org/10.1016/j.ecolind.2019.105682.
Rosenbaum, E., 2022. Mental models and institutional inertia. Journal of Institutional Economics. 18(3), 361-378. https://doi.org/10.1017/S174413742100059X.
Rule, T.A., 2022. Positive-Sum Water-Energy-Food Nexus Governance. NYU Environmental Law Journal. 31. https://heinonline.org/HOL/LandingPage?handle=hein.journals/nyuev31&div=7&id=&page=
Santo, A.R., Guillozet, K., Sorice M.G, Baird T.D, Gray S., Donlan C.J, Anderson C.B., 2017. Examining private landowners’ knowledge systems for an invasive species. Human Ecology. 45, 449–462. https://doi.org/10.1007/s10745-017-9920-7.
Schuurman, G.W., Hoffman, C.H., Cole, D.N., Lawrence, D.J., Morton, J.M., Magness, D.R., Fisichelli, N.A., 2020. Resist-accept-direct (RAD)-a framework for the 21st-century natural resource manager. National Park Service.‏ No. 2020/2213. https://doi.org/10.36967/nrr-2283597.
Sonti, N.F., Campbell, L.K., Svendsen, E.S., Johnson, M.L., Auyeung, D.N., 2020. Fear and fascination: Use and perceptions of New York City’s forests, wetlands, and landscaped park areas. Urban Forestry & Urban Greening. 49, 126601.‏ https://doi.org/10.1016/j.ufug.2020.126601.
Sun, B., Yang, X., 2019. Simulation of water resources carrying capacity in Xiong’an New Area based on system dynamics model. Water. 11(5), 1085. https://doi.org/10.3390/w11051085.
Tavanir, 2020. Statistics of tavanir. Available online at: https://amar.tavanir.org.ir
Treur, J. and Van Ments, L., 2022. Mental models and their dynamics, adaptation, and control: a self-modeling network modeling approach. Springer Nature.‏ Volume 394.
Valivand, F., Katibeh, H., 2022. Evaluation of Quantitative and Qualitative Management Plans in Varamin Plain Aquifer. Journal of Water and Wastewater. Journal of Water and Wastewater. 33(4), 36-50.‏ https://doi.org/10.22093/wwj.2022.315051.3197.
Wang, X., Dong, Z., Sušnik, J., 2023. System dynamics modelling to simulate regional water-energy-food nexus combined with the society-economy-environment system in Hunan Province, China. Science of the Total Environment. 863, 160993.‏ https://doi.org/10.1016/j.scitotenv.2022.160993.
Williams, J.W., Ordonez, A., Svenning, J.C., 2020. A unifying framework for studying and managing climate-driven rates of ecological change. Nature Ecology and Evolution. 5, 17-26. https://doi.org/10.1038/s41559-020-01344-5.
Yousefi, E., Sayadi, M.H., Chamanehpour, E., Ghasami, F., Amini, Z., 2023. Using the new approach of ecosystem management to develop the ecological management plan of Kaji Namakzar Wetland of Nehbandan. Journal of Environmental Science Studies. 8(1), 6191-6209. . https://doi.org/10.22034/JESS.2022.366919.1896
فصلنامه علوم محیطی
دوره 22، شماره 1
فروردین 1403
صفحه 1-20

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