کاربرد مدل هیبریدی FEM-ACO در تعیین مکان های بهینه چاه های برداشت

نوع مقاله: مقاله پژوهشی


1 دانشیار گروه مهندسی عمران، دانشکده مهندسی، دانشگاه بیرجند، بیرجند، ایران

2 علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند

3 گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند.


در این مقاله، یک مدل هیبریدی بهینه‌سازی – شبیه‌سازی برای ارزیابی سیاست پمپاژ مطلوب در یک آبخوان مصنوعی استفاده شده است. در این مطالعه میزان افت سطح آب زیرزمینی در یک آبخوان آزاد فرضی به مساحت 5/1 کیلومتر مربع و سه هدایت هیدرولیکی متفاوت با ضخامت 100 متر و هم‌چنین تعداد ده حلقه چاه برداشت مورد بررسی قرار گرفت. جهت تخمین سطح آب زیرزمینی آبخوان از روش المان محدود و جهت بهینه‌سازی موقعیت چاه‌های برداشت از الگوریتم جامعه مورچگان استفاده شد و در نهایت مدل FEM-ACO ارائه گردید. موقعیت چاه‌های برداشتی با دبی مشخص به صورتی بهینه‌یابی می‌شود که میزان افت سطح آب زیرزمینی در آبخوان کمینه گردد. در این راستا تعداد مقادیر مختلف تعداد مورچه‌ها، تأثیر میزان تبخیر فرامان و تأثیر درصد نخبه‌های یک مجموعه از مورچه‌ها بر مقدار تابع هدف مورد بررسی قرار گرفت. نتایج نشان داد که الگوریتم‌های مورچگان ترتیبی و الگوریتم مورچگان نخبه با عملکردی تقریباً یکسان بهترین عملکرد را در بین الگوریتم‌های مورچگان داشته‌اند و پس از آن‌ها، الگوریتم جامعه مورچگان و الگوریتم مورچگان بیشینه-کمینه در رتبه‌های بعدی قرار دارند. تمامی الگوریتم‌های مورچگان خیلی زود به همگرایی رسیدند که این همگرایی زودرس به یک بهینه سراسری مناسب را می‌توان به دلیل استفاده از قیود زنجیره‌ای دانست. در نهایت بعد از بررسی مدل ارائه شده، موقعیت مناسب چاه‌های برداشت مشخص گردید. هم‌چنین نتایج نشان داد که حداکثر افت آب آبخوان حدود 5/2 متر می‌باشد.


عنوان مقاله [English]

Application of the FEM-ACO Hybrid Model in Determining the Optimum Locations for Pumping Wells

نویسندگان [English]

  • Abolfazl Akbarpour 1
  • mohamad javad zeynali 2
  • Mohammad Nazeri-Tahroudi 3
1 Associate Professor, Department of Civil Engineering, University of Birjand., Birjand., Iran
2 Science and engineering of water,faculty of agriculture, Birjand university
3 Department of Sciences and Water Engineering, University of Birjand
چکیده [English]

In this paper, an optimization simulation hybrid model is used to evaluate the optimum pumping policy in an artificial aquifer. In this study, the groundwater level drop was investigated in a hypothetical free aquifer with a surface area of 1.5 square kilometers and three different hydraulic conductivity with a thickness of 100 meters, as well as ten pumping wells. In order to estimate the groundwater level of the aquifer, the finite element method was used and to optimize the position of the wells, used the algorithm of the ant colony and finally the FEM-ACO model was presented. The position of wells with a specific discharge is optimized to minimize groundwater level losses in the aquifer. In this regard, the number of different number of ants, the effect of Foramen evaporation and the effect of the elite percentage of an ant collection on the value of the objective function were investigated. The results showed that sequencer antler algorithms and elite ant anchor algorithms with almost identical performance have the best performance among the antler algorithms, and after that, the antler community algorithm and the max-minimal ant antler algorithm are in the next ranks. All of the ant colony algorithms arrived too quickly into convergence, which makes this early convergence a suitable global optimum due to the use of chain constraints. Finally, after considering the proposed model, the proper position of the wells was determined. The results also showed that the maximum water loss in the aquifer is about 2.5 m.

کلیدواژه‌ها [English]

  • Ant algorithm
  • aquifer
  • Finite Element
  • Groundwater
  • optimization
Ahlfeld, D.P., Baro-Montes, G., 2008. Solving unconfined groundwater flow management problems with successive linear programming Journal of water resources planning and management. 134:404-412
Ahlfeld, D.P., Heidari, M., 1994. Applications of optimal hydraulic control to ground-water systems Journal of Water Resources Planning and Management. 120: 350-365
Al-Naeem, A.A., 2014. Effect of excess pumping on groundwater salinity and water level in Hail region of Saudi Arabia Research Journal of Environmental Toxicology. 8:124
Atwood, D.F., Gorelick, S.M., 1985. Hydraulic gradient control for groundwater contaminant removal Journal of Hydrology. 76:85-106
Ayvaz, M.T., Karahan, H., 2008. A simulation/optimization model for the identification of unknown groundwater well locations and pumping rates Journal of Hydrology. 357:76-92
Babbar-Sebens, M., Minsker, B.S., 2012. Interactive genetic algorithm with mixed initiative interaction for multi-criteria ground water monitoring design Applied Soft Computing. 12:182-195
Badv, K., Deriszadeh, M., 2005. Wellhead protection area delineation using the analytic element method Water, Air, & Soil Pollution.161:39-54
Bear, J., 2012. Hydraulics of groundwater. Courier Corporation,
Blaszyk, T., Gorski, J., 1981. Ground‐Water Quality Changes during Exploitation Groundwater. 19:28-33
Chang, L.C., Shoemaker, C.A., Liu, P.L.F., 1992. Optimal time‐varying pumping rates for groundwater remediation: Application of a constrained optimal control algorithm Water Resources Research. 28:3157-3173
Craig, J., Rabideau, A., 2006. Finite element transport modeling using analytic element flow solutions Water resources research, 42
Das, A., Datta, B., 2001. Application of optimisation techniques in groundwater quantity and quality management Sadhana. 26:293-316
Famiglietti, J.S., Lo, M., Ho, S.L., Bethune, J., Anderson, K.J., Syed, T.H., ... & Rodell, M., 2011. Satellites measure recent rates of groundwater depletion in California's Central Valley. Geophysical Research Letters. 38(3).
Gaur, S., Chahar., B.R., Graillot, D., 2011. Analytic elements method and particle swarm optimization based simulation–optimization model for groundwater management Journal of hydrology 402:217-227
Gautam, D., Prajapati, R., 2014. Drawdown and dynamics of groundwater table in Kathmandu valley, Nepal The Open Hydrology Journal 8
Hoos, H.H, Stützle, T., 2000. SATLIB: An online resource for research on SAT. Sat. 283-292.
Ketabchi, H., Ataie-Ashtiani, B., 2015. Evolutionary algorithms for the optimal management of coastal groundwater: a comparative study toward future challenges Journal of Hydrology 520:193-213
Mahar, P.S., Datta, B., 2000. Identification of pollution sources in transient groundwater systems Water Resources Management 14: 209-227
Mantoglou, A., 2003. Pumping management of coastal aquifers using analytical models of saltwater intrusion Water resources research. 39
Mantoglou, A., Papantoniou, M., 2008. Optimal design of pumping networks in coastal aquifers using sharp interface models Journal of hydrology. 361:52-63.
McKinney, D., Lin, M., 1992. Design methodology for efficient aquifer remediation using pump and treat systems IN: Computational Methods in Water Resources IX 2
Peralta, R.C., Forghani, A., Fayad, H., 2014. Multiobjective genetic algorithm conjunctive use optimization for production, cost, and energy with dynamic return flow Journal of Hydrology 511:776-785
Pokrajac, D., Lazic, R., 2002. An efficient algorithm for high accuracy particle tracking in finite elements Advances in Water Resources. 25: 353-369
Prickett, T.A., 1979. Ground‐Water Computer Models—State of the Art Groundwater. 17:167-173
Scanlon, B., Reedy, R., Gates, J., 2010. Effects of irrigated agroecosystems: 1. Quantity of soil water and groundwater in the southern High Plains, Texas Water Resources Research. 46
Steward, D.R., Allen, A.J., 2013. The Analytic Element Method for rectangular gridded domains, benchmark comparisons and application to the High Plains Aquifer Advances in water resources. 60. pp.89-99
Wagner, B.J., 1995. Recent advances in simulation‐optimization groundwater management modeling Reviews of Geophysics 33:1021-1028
Wang, H., Shu, Y.A., 2005. Study on ground water resources multi-objective dynamic programming management model in western Daqing city. In: Proc. 7th National Congress on Hydrodynamics and 19th National Conf. on Hydrodynamics.1157-1167
Wang, H.F., Anderson, M.P., 1995. Introduction to groundwater modeling: finite difference and finite element methods. Academic Press,
Willis, R. 1983. A unified approach to regional groundwater management Groundwater hydraulics.392-407
Yu, F., Lu, W., Li, P., Xin, X., Li, J., 2012. Dynamic optimal control for groundwater optimization management with covariates Journal of Hydroinformatics. 14:386-394