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Determination of the optimal location of wells in aquifers with an accurate simulation-optimization model based on the meshless local Petrov-Galerkin

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Abstract

In this research, a simulation-optimization model is utilized to determine the optimum location of wells on two unconfined aquifers (steady condition and transient state) with different boundary conditions. Meshless local Petrov-Galerkin (MLPG) and particle swarm optimization (PSO) are employed for the simulation model and optimization algorithm, respectively. MLPG model is first verified by comparing results with analytical and finite difference solutions. The obtained results from MLPG show more accuracy than FDM. In PSO, the objective function is defined as the summation of the absolute difference between water table before and after extraction in each node. In the first aquifer, results show that the content of objective function before using simulation-optimization model is 61 m; however, it reaches 17 m when the optimal location is selected. The value of objective function after using simulation-optimization model has 27% reduction in value. The second aquifer has ten extraction wells and investigated in two cases with different boundary conditions. In both cases, the value of objective function is decreased significantly after applying SO model.

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References

  • Akbari A, Bagri RA, Bordas SPA, Rabczuk T (2010) Analysis of ThermoelasticWaves in a two-dimensional functionally graded materials domain by the Meshless local Petrov-Galerkin (MLPG) method. Comput Model Eng Sci 65(1):27–74

    Google Scholar 

  • Al-Naeem A (2014) Effect of excess pumping on groundwater salinity and water level in hail region of Saudi Arabia. Res J Environ Toxicol 8(3):124–135

    Article  Google Scholar 

  • Atluri SN, Zhu TA (1998) A new MEshless method (MLPG) approach in computational mechanics. Comput Mech 22(2):117–127

    Article  Google Scholar 

  • Atluri SN, Zhu TL (2000) The meshless local Petrov-Galerkin (MLPG) approach for solving problems in elasto-statics. Comput Mech 25:169–179

    Article  Google Scholar 

  • Ayvaz MT (2009) Application of harmony search algorithm to the solution of groundwater. Adv Water Resour 32:916–924

    Article  Google Scholar 

  • Ayvaz MT, Karahan H (2008) Simulation/optimization model for the identification of unknown groundwater well locations and pumping rates. J Hydrol 257:76–92

    Article  Google Scholar 

  • Bartolino J, Cunningham WL (2003) Ground-water depletion across the nation, USGS

  • Bear J (1979) Hydraulics of groundwater, the University of Michigan. McGraw-Hill International Book Co

  • Belytschko T, Lu YY, Gu L (1994) Elements free Galerkin methods. Int J Numer Methods Eng 30(2):229–256

    Article  Google Scholar 

  • Blaszyk T, Gorski J (1981) Ground-water quality changes during exploitation. Groundwater 19:28–33

    Article  Google Scholar 

  • Boddula Swathi, T.I. Eldho, (2014) Groundwater flow simulation in unconfined aquifers using meshless local Petrov–Galerkin method. Engineering Analysis with Boundary Elements 48:43-52

  • Cyriac R, Rastogi AK (2016) Optimization of pumping policy using coupled finite element-particle swarm optimization modelling. ISH J Hydraul Eng 22(1):88–99

  • Duouit J (1863) Estudes Theoriques et Pratiques sur le Mouvement desEaux. Dunod, Paris

    Google Scholar 

  • El-Ghandour HA, Elsaid A (2013) Groundwater management using a new coupled model of flow analytical solution and particle swarm optimization. Int J Water Resour Environ Eng 5(1):1–11

    Article  Google Scholar 

  • Elsheikh WHY, Shigidi AMT (2018) OPTIMIZATION OF PUMPING FROM AL-SIDIR WELLFIELD, BARA AQUIFER, 2nd conference of civil engineering, Sudan

  • Ganji Khorramdel N, Mohammadi K, Monem MJ (2008) Optimization of observation well network for the estimation of groundwater balance using double water table fluctuation method. J Water Soil 22(2):359–370

    Google Scholar 

  • Gaur S, Chahar BR, Graillot D (2011) Analytic elements method and particle swarm optimization based simulation–optimization model for groundwater management. J Hydrol 402:217–227

    Article  Google Scholar 

  • Ghaseminijad A, Shourian M (2019) A simulation–optimization approach for optimal design of groundwater withdrawal wells’ location and pumping rateconsidering desalination constraints. Environ Earth Sci 78:270–281

    Article  Google Scholar 

  • Gill MK, Kaheil YH, Khalil A, McKee M, Bastidas L (2006) Multiobjective particle swarm optimization for parameter estimation in hydrology. Water Resour Res 42(7)

  • Gou X, Hu T, Wu C, Zhang T, Lv Y (2013) Multi-objective optimization of the proposed multi-reservoir operating policy using improved NSPSO. Water Resour Manag 27:2137–2153

    Article  Google Scholar 

  • Hamraz BS, Akbarpour A, Pourreza Bilondi M, Sadeghi Tabas S (2015) On the assessment of ground water parameter uncertainty over an arid aquifer. Arab J Geosci 8(12):10759–10773

  • Izady A, Abdalla O, Joodavi A, Chen M (2017) Groundwater Modeling and Sustainability of a Transboundary Hardrock–Alluvium Aquifer in North Oman Mountains. Water 9(3):161

    Article  Google Scholar 

  • Izquierdo J, Montalvo I, Pérez R, Tavera M (2008) Optimization in water systems: a PSO approach, in Proceedings of the 2008 Spring simulation multiconference

  • Joodavi A, Zare M, Mahootchi M (2015) Development and application of a stochastic optimization model for groundwater management: crop pattern and conjuctive use consideration. Stoch Environ Res Risk Assesss 29(6):1637–1648

    Article  Google Scholar 

  • Kennedy J, Eberhart R (1995) Particle swarm optimization, in Proceeding of IEEE Intenational Conference on neural networks

  • Ketabchi H, Ataie-Ashtiani B (2015) Assessment of a parallel evolutionary optimization approach for efficient management of coastal aquifers. Environ Model Softw 74:21–38

    Article  Google Scholar 

  • Kulkarni NH (2015) Numerical simulation of groundwater recharge from an injection well. Int J Water Resour Environ Eng 7(5):75–83

    Article  Google Scholar 

  • Kumar N, Reddy J (2007) Multipurpose reservoir operation using particle swarm optimization. J Water Resour Plan Manag 133:192–201

    Article  Google Scholar 

  • Liu G (2002) Mesh free methods: moving beyond the finite element method. CRC press, Boca Raton

  • Liu GR, Gu YT (2005) An introduction to Meshfree methods and their programming. Springer, Singapore

  • Mategaonkar Meenal, T. I. Eldho, (2011a) MESHLESS POINT COLLOCATION METHOD FOR 1D AND 2D GROUNDWATER FLOW SIMULATION. ISH Journal of Hydraulic Engineering 17 (1):71-87

  • Mategaonkar Meenal, T.I. Eldho, (2011b) Simulation of groundwater flow in unconfined aquifer using meshfree point collocation method. Engineering Analysis with Boundary Elements 35 (4):700-707

  • McKinney D, Lin M (1994) Genetic algorithm solution of groundwater management models. Water Resour Manag 30:1897–1906

  • Mohtashami A, Akbarpour A, Mollazadeh M (2017a) Development of two dimensional groundwater flow simulation model using meshless method based on MLS approximation function in unconfined aquifer in transient state. J Hydroinf 19(5):640–652

    Article  Google Scholar 

  • Mohtashami A, Akbarpour A, Mollazadeh M (2017b) Modeling of groundwater flow in unconfined aquifer in steady state with meshless local Petrov-Galerkin. Modares Mech Eng 17(2):393–403

    Google Scholar 

  • Mohtashami A, Hashemi Monfared SA, Azizyan G, Akbarpour A (2019) Determination the capture zone of wells by using meshless local Petrov-Galerkin numerical model in confined aquifer in unsteady state( case study: Birjand aquifer). Iranian J Ecohydrol 6(1):239–255

    Google Scholar 

  • Mollazadeh M, Barani G A, Rasouli A (2008) Optimiztion the shape of gravity dams using particle swarm optimization, in 6th of Iranian hydraulic conference, Shahrekord

  • Saadatpour M, Afshar A (2013) Multi objective simulation-optimization approach in pollution spill response management model in reservoirs. Water Resour Manag 27:1851–1865

    Article  Google Scholar 

  • Sadeghi Tabas S, Akbarpour A, Pourreza Bilondi M, Samadi SZ (2015) Application of cuckoo optimization algorithm in automatic calibration of aquifer hydrodynamic parameters using mathematical model. Iranian J Irrig Drain 9(2):345–356

    Google Scholar 

  • Sadeghi Tabas S, Samadi SZ, Akbarpour A, Pourreza Bilondi M (2016) Sustainable groundwater modeling using single-and multi-objective optimization algorithm. J Hydroinf 18(5):1–18

    Google Scholar 

  • Saeedpanah I, Samsami-Khodadad H (2015) Numerical simulation of groundwaters flow by using analytical particle, in 8th National Congress of civil engineering, Babol

  • Stacey A, Jancic M, Grundy I (2003) Particle swarm optimization with mutation, in Congress on Evolutionary Computation

  • Tissa HI, Doll P (1989) A discrete kernel method of Charactristic model of solute transport in water table Aqufers. Water Resour Manag 25(5):857–867

  • Vrugt JA, Robinson BA (2007) Improved evolutionary optimization from genetically adaptive multimethod search. PNAS Proc Natl Acad Sci U S A 104(3):708–711

    Article  Google Scholar 

  • Zambrano-Bigiarini M, Rojas R (2006) A model-independent particle swarm optimisation software for model calibration. Environ Model Softw 43:5–25

    Article  Google Scholar 

  • Zhang Z, Jiang Y, Zhang S, Geng S, Wang H, Sang G (2014) An adaptive particle swarm optimization algorithm for reservoir operation optimization. Appl Soft Comput 18:167–177

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran

    Ali Mohtashami

  2. Civil Engineering Department, University of Sistan and Baluchestan, Zahedan, Iran

    Seyed Arman Hashemi Monfared

  3. Civil Engineering Department, University of Sistan and Baluchestan, Zahedan, Iran

    Gholamreza Azizyan

  4. Civil Engineering Department, University of Birjand, Birjand, Iran

    Abolfazl Akbarpour

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  1. Ali Mohtashami
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  2. Seyed Arman Hashemi Monfared
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  3. Gholamreza Azizyan
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  4. Abolfazl Akbarpour
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Correspondence to Seyed Arman Hashemi Monfared.

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Responsible Editor: Zeynal Abiddin Erguler

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Mohtashami, A., Monfared, S.A.H., Azizyan, G. et al. Determination of the optimal location of wells in aquifers with an accurate simulation-optimization model based on the meshless local Petrov-Galerkin. Arab J Geosci 13, 26 (2020). https://doi.org/10.1007/s12517-019-5039-z

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