مدیریت آب های زیرزمینی دشت اردبیل با استفاده از مدل سازی عامل بنیان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد مهندسی آب/ دانشکده مهندسی عمران، دانشگاه تبریز، ایران.

2 استاد / گروه مهندسی آب و محیط زیست، دانشکده مهندسی عمران، دانشگاه تبریز، ایران.

3 همکار علمی، انستیتو آب کلرادو/ فورت کالینز، کلرادو، آمریکا.

4 دانشیار / گروه علوم زمین، دانشکده علوم طبیعی، دانشگاه تبریز، ایران.

چکیده

تعاملات اجتماعی-هیدرولوژیکی یکی از الزامات مهم برای مدیریت منابع آب در مناطق تحت تنش آبی است. آبخوان اردبیل یکی از آبخوان‌های ممنوعه تحت فعالیت‌های شدید رو به رشد است. سطح آب زیرزمینی در این آبخوان به طور چشمگیری کاهش یافته است و این منطقه را به سوی یک فاجعه‌ی محیط زیستی هدایت می‌کند. در این مطالعه، یک مدل شبیه‌سازی-بهینه‌سازی برای حل مشکل آب زیرزمینی اردبیل توسعه داده شده است که تغییرات تراز آب زیرزمینی را شبیه‌سازی و مقادیر بهینه برای استخراج آب را تعیین می‌کند. این مدل‌ها به وسیله‌ی یک روش جدید توسعه داده شده در MATLAB به هم متصل شده‌اند که امکان دسترسی به بسته‌های مختلفMODFLOW را فراهم کرده و برای اجرای مکرر مدل‌ها حافظه‌ کمتری را اشغال می‌کند. مدل شبیه‌سازی-بهینه‌سازی به منظور شبیه‌سازی رفتار و تعامل ذینفعان به یک مدل عامل بنیان متصل شده است. به همین منظور ابتدا ذینفعان کلیدی و مطلوبیت هر یک از آن‌ها تعیین شده است. سپس الگوریتم بهینه‌سازی ازدحام ذرات به منظور برآورد مقادیر برداشت آب، استفاده و در مرحله بعد با استفاده از روش برنامه‌ریزی سازشی بهترین گزینه از میان مجموعه جواب‌ها با لحاظ دید کارشناسی انتخاب شده است. در نهایت، مدل عامل بنیان با در نظر گرفتن تنش‌های اجتماعی و قوانین مدیریتی (تشویقی و جریمه‌ای) مقادیر برداشت نهایی را فراهم کرده است. نتایج نشان می‌دهد که تقاضای آب زیرزمینی در مقایسه با مقدار اولیه به میزان 22 درصد کاهش یافته است. این میزان کاهش تقاضا باعث افزایش 90 سانتی متری سطح آب زیرزمینی به طور متوسط برای کل دشت شده است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Groundwater Management in Ardabil Plain Using Agent-Based Modeling

نویسندگان [English]

  • Saeid Najjar Ghabel 1
  • Mahdi Zarghami 2
  • Masih Akhbari 3
  • Ata Allah Nadiri 4
1 M.Sc. Graduated of Water Engineering, Department of Civil Engineering, University of Tabriz, Tabriz, Iran.
2 Professor, Department of Civil Engineering, University of Tabriz, Tabriz, Iran. Email: mzarghami@tabrizu.ac.ir
3 Visiting Scholar, Colorado Water Institute, Fort Collins, Colorado, USA.
4 Associate Professor, Department of Earth Science, University of Tabriz, Tabriz, Iran.
چکیده [English]

Modeling socio-hydrological interactions are one of the essential requirements for water resources management in water-stressed areas. The Ardabil aquifer (Northwestern Iran) is one of the restricted aquifers under intense development activities. The water table is dramatically declining and leading the area to an environmental disaster. In this study, a simulation-optimization model has been developed for solving the Ardabil groundwater problem, which simulates groundwater level changes and determines the optimal water exploitation values. These models have been linked by a new method in the MATLAB which provides access to various MODFLOW packages and takes up less memory. The simulation-optimization model has been then linked to an agent-based model, which simulates agents’ behavior and their interactions. For this purpose, firstly the key agents and their desirability have been determined. Then, the particle swarm optimization algorithm is used to estimate the agents’ desired groundwater exploitation values. In the next step, the best solution using the compromised programming method is selected according to the experts' point of view. Finally, the agent-based model provided the final exploitation values, taking into account social pressure and management rules (incentive and penalties). The results show that groundwater demand is reduced up to 22% in comparison to the initial value. This demand reduction resulted in 90 cm of the increase in the groundwater level for the entire plain.

کلیدواژه‌ها [English]

  • Agent-based modeling
  • Groundwater modeling
  • Optimization model
  • Compromising Programming
  • Ardabil plain Aquifer
Aban Pajouh Consulting Engineers (2010) Comprehensive studies and balancing and artificial recharge in Ardabil plain. Technical report, Tehran, 219p (In Persian)
Akhbari M (2012) Models for management of water conflicts: a case study of the San-Joaquin watershed. PhD Dissertation, Department of Civil and Environmental Engineering, Colorado State University
Akhbari M, Grigg NS (2013) A framework for an agent-based model to manage water resources conflicts. Water Resources Management 27(11):4039-4052
Akhbari M, Grigg NS (2015) Managing water resources conflicts: modelling behavior in a decision tool. Water Resources Management 29(15):5201-5216
Al-Amin S, Berglund EZ, Larson KL (2015) Agent-based modeling to simulate demand management strategies for shared groundwater resources. World Environmental and Water Resources Congress 2015: Floods, Droughts, and Ecosystems 2067-2072
Ayvaz MT, Karahan H (2008) A simulation/optimization model for the identification of unknown groundwater well locations and pumping rates. Journal of Hydrology 357(1):76-92
Bakarji J, O’Malley D, Vesselinov VV (2017) Agent-based socio-hydrological hybrid modeling for water resource management. Water Resources Management 31(12):3881-3898
Becu N, Perez P, Walker A, Barreteau O, Page C.Le (2003) Agent-based simulation of a small catchment water management in northern Thailand. Ecological Modelling 170(2):319-331
Cooper PJ, Dimes J, Rao KP, Shapiro B, Shiferaw B, Twomlow S (2008) Coping better with current climatic variability in the rain-fed farming systems of sub-Saharan Africa: An essential first step in adapting to future climate change?. Agriculture, Ecosystems & Environment 126(1):24-35
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
Dietz T (2003) The struggle to govern the commons. Science 302(5652):1907-1912
Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, IEEE, 39-43
Edwards M, Ferrand N, Goreaud F, Huet S (2005) The relevance of aggregating a water consumption model cannot be disconnected from the choice of information available on the resource. Simulation Modelling Practice and Theory 13(4):287-307
Farhadi S, Nikoo MR, Rakhshandehroo GR, Akhbari M, Alizadeh MR (2016) An agent-based-nash modeling framework for sustainable groundwater management: A case study. Agricultural Water Management 177:348-358
Filatova T, Polhill JG, van Ewijk S (2016) Regime shifts in coupled socio-environmental systems: review of modelling challenges and approaches. Environmental Modelling & Software 75:333-347
Ghazali M, Honar T, Nikoo M (2018) A hybrid TOPSIS-agent-based framework for reducing the water demand requested by stakeholders with considering the agents’ characteristics and optimization of cropping pattern. Agricultural Water Management 199:71-85
Gini C (1921) Measurement of inequality of incomes. The Economic Journal 31(121):124-126
Giuliani M, Castelletti A (2013) Assessing the value of cooperation and information exchange in large water resources systems by agent-based optimization. Water Resources Research 49(7):3912-3926
Gorelick SM (1983) A review of distributed parameter groundwater management modeling methods. Water Resources Research 19(2):305-319
Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, Heinz SK, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe'er G, Piou C, Railsback SF, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi S, Stillman RA, Vabø R, Visser U, DeAngelis DL (2006) A standard protocol for describing individual-based and agent-based models. Ecological Modelling 198(1-2):115-126
Grimm V, Berger U, DeAngelis D, Polhill J, Giske J, Railsback S (2010) The ODD protocol: A review and first update. Ecological Modelling 221(23):2760-2768
Hu Z, Chen Y, Yao L, Wei C, Li C (2016) Optimal allocation of regional water resources: From a perspective of equity–efficiency tradeoff. Resources, Conservation and Recycling 109:102-113
Liu J, Zheng C, Zheng L, Lei Y (2008) Ground water sustainability: Methodology and application to the North China Plain. Ground Water 46(6):897-909
Lotfi S, Araghinejad S (2017) A review on challenges in application of agent-based models in water resource systems. Iran-Water Resources Research 13(2):115-126 (In Persian)
McDonald MG, Harbaugh AW (2003) The history of MODFLOW. Journal of Ground Water 41(2):280-283
Mulligan KB, Brown C, Yang Y-CE, Ahlfeld DP (2014) Assessing groundwater policy with coupled economic-groundwater hydrologic modeling. Water Resources Research 50(3):2257-2275
National center for supercomputing applications (access data: September, 2 2016), Available: <https://support.hdfgroup.org>
Ohab-Yazdi SA, Ahmadi A (2018) Evaluating and simulation of the behavior and interactions of stakeholders and regional water company under agent-based model framework, in Lenjanat Sub-Basin of Zayandehrood River Basin. Iran-Water Resources Research 14(2):142-154 (In Persian)
Reeves HW, Zellner ML (2010) Linking MODFLOW with an agent-based land-use model to support decision making. Ground Water 48(5):649-660
Schreinemachers P, Berger T (2011) An agent-based simulation model of human–environment interactions in agricultural systems. Environmental Modelling & Software 26(7):845-859
Singh A, Bürger CM, Cirpka OA (2013) Optimized sustainable groundwater extraction management: general approach and application to the city of Lucknow, India. Water Resources Management 27(12):4349-4368
Sivakumar MVK, Das HP, Brunini O (2005) Impacts of present and future climate variability and change on agriculture and forestry in the arid and semi-arid tropics. Climatic Change 70(1):31-72
Sivapalan M, Savenije HHG, Blöschl G (2012) Socio-hydrology: A new science of people and water. Hydrological Processes 26(8):1270-1276
Todd DK, Mays LW (2005) Groundwater hydrology. Third edition, John Wiley & Sons, New York, 656p
Xiao Y, Fang L, Hipel K, Wre H, Asce F (2018) Agent-based modeling approach to investigating the impact of water demand management. Journal of Water Resources Planning and Management 144(3):1-12
Young HP (1999) Diffusion in social networks. Working Paper No 2, Brookings Institution, Washington DC
Zarghami M, Szidarovszky F (2011) Multicriteria analysis: applications to water and environment management. Springer, Berlin, 159p
Zekri S, Triki C, Al-Maktoumi A, Bazargan-Lari MR (2015) An optimization-simulation approach for groundwater abstraction under recharge uncertainty. Water Resources Management 29(10):3681-3695
Zeleny M (1973) Compromise programming. In: multicriteria decision making. University of South Carolina Press, Columbia, 262-301
Zellner ML (2008) Embracing complexity and uncertainty: The potential of agent-based modeling for environmental planning and policy. Planning Theory and Practice 9(4):437-457