ارزیابی عملکرد روش‌های عددی در شبیه‌سازی جریان آب زیرزمینی (مطالعه موردی: آبخوان بیرجند)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دکتری منابع آب، گروه علوم و مهندسی آب، دانشگاه بیرجند. بیرجند، ایران.

2 استاد گروه علوم و مهندسی آب، دانشگاه بیرجند، بیرجند، ایران.

3 دانشیار گروه علوم و مهندسی آب، دانشگاه بیرجند، بیرجند، ایران. گروه پژوهشی تغییر اقلیم و خشکسالی، دانشگاه بیرجند، بیرجند، ایران.

10.22034/hydro.2023.12330

چکیده

داشتن دانش و اطلاع دقیق از وضعیت منابع آب زیرزمینی جهت برنامه‌ریزی و توسعه پایدار در مناطق خشک و نیمه‌خشک اهمیت دوچندانی دارد. از طرفی به‌دلیل این‌که مدل‌سازی آب زیرزمینی در مطالعات میدانی دارای مشخصاتی نظیر مرزهای نامنظم، ناهمگنی و ناهمسانگردی و همچنین شرایط مرزی و مدل مفهومی پیچیده است، دشواری‌های زیادی در فرایند شبیه‌سازی وجود دارد. به‌دلیل قابلیت‌های مناسب و عملکرد قابل‌قبول روش‌های عددی، این پژوهش در نظر دارد تا یک چارچوب مناسب جهت شبیه‌سازی آب زیرزمینی در مناطق خشک را که مبتنی بر روش‌های تفاضل محدود (FD)، اجزای محدود (FE) و بدون شبکه (Mfree) است، ارائه کند. معادله جریان آب زیرزمینی براساس روش‌های FD، FE و Mfree گسسته شد و عملکرد آن‌ها در یک آبخوان فرضی و یک مطالعه میدانی مورد ارزیابی قرار گرفت. ارزیابی نتایج عددی به‌دست‌آمده در آبخوان فرضی و مقایسه با جواب تحلیلی، حاکی از آن است که عملکرد هر سه مدل‌ عددی قابل‌قبول است. به‌طوری‌که مقدار شاخص RMSE برای روش‌های Mfree، FE و FD به‌ترتیب 005/0، 016/0 و 018/0 متر به دست آمد. لکن با افزایش پیچیدگی‌های شبیه‌سازی در مطالعه میدانی، از دقت روش‌های عددی مبتنی بر مش (شبکه‌بندی) نظیر FD و FE کاسته شد. ارزیابی عملکرد روش FD نشان داد که این روش در مسائل با هندسه‌های منظم و شرایط مرزی ساده از عملکرد خوبی برخوردار است، لکن در مسائل واقعی و شرایط واقعی با هندسه‌های نامنظم که با ناهمسانگردی و ناهمگنی مواجه هستند از دقت آن به‌شدت کاسته می‌شود. به‌طوری‌که مقدار شاخص RMSE برای روش FD در آبخوان واقعی، حدود 77/1 متر به­دست آمد. نتیجه فوق البته با شدت کمتر برای روش FE نیز صادق است (مقدار RMSE برای FE و در آبخوان واقعی حدود 36/0 به­دست آمد). همچنین نتایج این مطالعه در خصوص روش Mfree ثابت کرد که این روش ضمن داشتن دقت بالاتر نسبت به روش‌های FD و FE از انعطاف‌پذیری بسیار بالایی در مواجه با هندسه‌های نامنظم و موضوعات ناهمسانگردی و ناهمگنی برخوردار است. مقدار شاخص RMSE برای روش Mfree در مطالعه میدانی، 26/0 متر به­دست آمد.

کلیدواژه‌ها


عنوان مقاله [English]

Performance Assessment of Numerical Solutions in Groundwater Simulation (case study: Birjand aquifer)

نویسندگان [English]

  • Ahmad Jafarzadeh 1
  • Abbas Khashei 2
  • Mohsen PurrezaBilondi 3
1 PhD Graduate of Water Resources, Department of Water Engineering, University of Birjand, Birjand, Iran.
2 Professor of Water Engineering, Department of Water Engineering, University of Birjand, Birjand, Iran.
3 Associated Professor of Water Engineering, Department of Water Engineering, University of Birjand, Birjand, Iran. Research Group of Drought and Climate change, University of Birjand, Birjand, Iran.
چکیده [English]

The extensive knowledge of groundwater resources' status has double importance for the planning of the sustainable future in the arid regions. Strictly, without an efficient model with accurate simulation, it is impossible to have a good understanding of groundwater behavior. Since groundwater modeling in real problems comprises irregular boundaries, heterogeneity, anisotropy, and conceptualization, there exist many challenges in the simulation process. Due to proper acceptable performance, this study aims to present a proper framework to simulate groundwater flow based on Finite Difference (FD), Finite Element (FE), and Meshfree (Mfree) methods. The governing equation of groundwater flow was discretized through FD, FE, and Mfree approximations, and their performance was examined in two case studies: hypothetical case and field study. The findings of this study revealed that the Mfree has more applicability than others because some noticeable challenges were found in the simulation process of the FD and FE. Comparison of analytical solutions and simulated values in the hypothetical aquifer indicated that all methods are compliant. In terms of the RMSE criterion, the Mfree, FE, and FD were evaluated respectively, 0.005, 0.016, and 0.018 m. However, the numerical methods' act, especially the mesh-based methods (FD and FE) in the field study, becomes less accurate. Performance assessment of the FD indicated that this method has good ability in a simple test case with regular geometry, while in an aquifer with irregular geometry associated with isotropy and heterogeneity, its accuracy is greatly diminished. So that, the RMSE for FD methods in field study was evaluated 1.77 m. The same results may be obtained from the FE method, such that its RMSE was obtained 0.36 m. Investigations of this study showed that the FE needs time-consuming preprocessing practices to implement in the different aquifer. The results of the Mfree application indicated that this method is more efficient than others due to its very high flexibility in irregular geometry with isotropy and heterogeneity issues. The RMSE for the Mfree in the field study obtained 0.26 m.

کلیدواژه‌ها [English]

  • Arid Region
  • Finite Element
  • Mesh Less
  • Structure Uncertainty Weighted Residuals
رضایی، س.، جوادی، س.، کاردان مقدم، ح.، (1399). ارزیابی راهکارهای مدیریت منابع آب زیرزمینی با استفاده از رویکرد اجزای محدود در شبیه‌سازی عددی. هیدروژئولوژی، 5(2): 32-42.
کرد، م.، اصغری‌مقدم، ا.، نخعی، م.، (1398). مدل‌سازی عددی آبخوان دشت اردبیل و مدیریت آن با استفاده از بهینه‌سازی برداشت آب زیرزمینی. هیدروژئولوژی، 4(1): 153-167.
جعفرزاده، احمد، خاشعی سیوکی، عباس، وشهیدی، علی. (1394). مدل‌سازی اثرات تغییر اقلیم روی نیاز آبی زعفران در خراسان جنوبی با استفاده از سیستم اطلاعات جغرافیایی. پژوهش های زعفران، 3(2). 174-163.
Akbarpour, A., Zeynali, M.J., Tahroudi, M.N., (2020). Locating optimal position of pumping Wells in aquifer using meta-heuristic algorithms and finite element method. Water Resources Management, 34(1): 21-34.
Aliyari, F., Bailey, R.T., Tasdighi, A., Dozier, A., Arabi, M., Zeiler, K., (2019). Coupled SWAT-MODFLOW model for large-scale mixed agro-urban river basins. Environmental Modelling & Software, 115: 200-210.
Anshuman, A., Eldho, T.I., (2019). Modeling of transport of first-order reaction networks in porous media using meshfree radial point collocation method. Computational Geosciences, 23(6): 1369-1385.
Arnold, J. G., Allen, P. M., Bernhardt, G., (1993). A comprehensive surface-groundwater flow model. Journal of hydrology, 142(1-4): 47-69.
Bailey, R.T., Park, S., Bieger, K., Arnold, J.G., Allen, P.M., (2020). Enhancing SWAT+ simulation of groundwater flow and groundwater-surface water interactions using MODFLOW routines. Environmental Modelling & Software, 126: 104660.
Bastani, M., Harter, T., (2019). Source area management practices as remediation tool to address groundwater nitrate pollution in drinking supply wells. Journal of contaminant hydrology, 226: 103521.
Belytschko, T., Krongauz, Y., Organ, D., Fleming, M., Krysl, P., (1996). Meshless methods: an overview and recent developments. Computer methods in applied mechanics and engineering, 139(1): 3-47.
Cheng, A.D., Golberg, M.A., Kansa, E.J., Zammito, G., (2003). Exponential convergence and H‐c multiquadric collocation method for partial differential equations. Numerical Methods for Partial Differential Equations: An International Journal, 19(5), 571-594.
Choopani, A., Dehghani, M., Nikoo, M.R., (2020). Determining hydrogeological parameters of an aquifer in Sirjan Basin using Envisat ASAR interferometry and groundwater modelling. International Journal of Remote Sensing, 41(2): 655-682.
Colombani, N., Giambastiani, B.M.S., Mastrocicco, M., (2017). Long term monitoring of aquifer salinization processes in a physical analog model. European Water, 57: 413-416
El Seblani, Y., Shivanian, E., (2019). Boundary value identification of inverse Cauchy problems in arbitrary plane domain through meshless radial point Hermite interpolation. Engineering with Computers, 1-14.
Fadugba, O.G., Ojuri, O.O., Adetukasi, A.O., Fadugba, O.O., (2020). Laboratory treatability of hydrocarbon contaminated groundwater using engineered nanotechnology. Materials Today: Proceedings, 38, 696-699.
Gelsinari, S., Doble, R., Daly, E., Pauwels, V.R., (2020). Feasibility of Improving Groundwater Modeling by Assimilating Evapotranspiration Rates. Water Resources Research, 56(2), e2019WR025983.
Hamraz, B., Akbarpour, A., Bilondi, M.P., Tabas, S.S., (2015). On the assessment of ground water parameter uncertainty over an arid aquifer. Arabian journal of Geosciences, 8(12): 10759-10773.
Hu, Y., Li, H., Jiang, Z., (2020). Efficient semi-implicit compact finite difference scheme for nonlinear Schrödinger equations on unbounded domain. Applied Numerical Mathematics. 153, 319-343.
Illangasekare, T., Doll, P., (1989). A Discrete Kernel Method of Characteristics Model of Solute Transport in Water Table Aquifers. WATER RESOURCES RESEARCH, 25(5): 857–867.
Jafarzadeh, A., Pourreza-Bilondi, M., Siuki, A.K., Moghadam, J.R., (2021). Examination of Various Feature Selection Approaches for Daily Precipitation Downscaling in Different Climates. Water Resources Management, 35(2): 407-427.
Jafarzadeh, A., Bilondi, M. P., Afshar, A. A., & Yaghoobzadeh, M. (2017). Reliability estimation of rainwater catchment system using future GCM output data (case study: Birjand city). Eur. Water, 59, 169-175.
Javandel, I., Witherspoon, P.A., (1968). Application of the finite element method to transient flow in porous media. Society of Petroleum Engineers Journal, 8(03): 241-252.
Karimi, L., Motagh, M., Entezam, I., (2019). Modeling groundwater level fluctuations in Tehran aquifer: Results from a 3D unconfined aquifer model. Groundwater for Sustainable Development, 8: 439-449.
Kulkarni, N.H., (2015). Numerical simulation of groundwater recharge from an injection well. Internat. Jour. Water Resour. Environ. Engg, 7(5): 75-83.
Langevin, C.D., Hughes, J.D., Banta, E.R., Niswonger, R.G., Panday, S., Provost, A.M., (2017). Documentation for the MODFLOW 6 groundwater flow model (No. 6-A55). US Geological Survey.
Li, J., Chen, Y., Pepper, D., (2003). Radial basis function method for 1-D and 2-D groundwater contaminant transport modeling. Computational Mechanics, 32(1-2): 10-15.
Liu, G.R., Gu, Y.T. (2005). An introduction to meshfree methods and their programming. Springer Science & Business Media. 2005. 773 p.
Liu, W.K., Chen, Y., Jun, S., Chen, J.S., Belytschko, T., Pan, C., Chang, C.T., (1996). Overview and applications of the reproducing kernel particle methods. Archives of Computational Methods in Engineering, 3(1): 3-80.
Matiatos, I., Varouchakis, E.A., Papadopoulou, M.P., (2019). Performance evaluation of multiple groundwater flow and nitrate mass transport numerical models. Environmental Modeling & Assessment, 24(6): 659-675.
Majumder, P., Eldho, T.I., (2020). Artificial Neural Network and Grey Wolf Optimizer Based Surrogate Simulation-Optimization Model for Groundwater Remediation. Water Resources Management, 34(2): 763-783.
Mohsenipour, M., Shahid, S., Ebrahimi, K., Ismail, T., Wang, X.J., (2019). Simulation of nitrate transport and fate in groundwater in presence of kaolin. Journal of Soil and Water Conservation, 74(1): 67-76.
Mohtashami, A., Akbarpour, A.,Mollazadeh, M., (2017). Development of two-dimensional groundwater flow simulation model using meshless method based on MLS approximation function in unconfined aquifer in transient state. Journal of Hydroinformatics, 19(5): 640-652.
Mohtashami, A., Monfared, S.A.H., Azizyan, G., Akbarpour, A., (2020). Determination of the optimal location of wells in aquifers with an accurate simulation-optimization model based on the meshless local Petrov-Galerkin. Arabian Journal of Geosciences, 13(2): 26.
Mustafa, S.M.T., Nossent, J., Ghysels, G., Huysmans, M., (2020). Integrated Bayesian Multi-model approach to quantify input, parameter and conceptual model structure uncertainty in groundwater modeling. Environmental Modelling & Software, 126, 104654.
Pacheco, F.A.L., Martins, L.M.O., Quininha, M., Oliveira, A.S., Fernandes, L.S., (2018). Modification to the DRASTIC framework to assess groundwater contaminant risk in rural mountainous catchments. Journal of Hydrology, 566: 175-191.
Remson, I., Appel, C.A., Webster, R.A., (1965). Ground-water models solved by digital computer. Journal of the Hydraulics Division, 91(3): 133-147.
Rodhe, A., (2012). Physical models for classroom teaching in hydrology. Hydrology & Earth System Sciences, 16(9). 3075-3082.
Sabzzadeh, I., Shourian, M., (2020). Maximizing crops yield net benefit in a groundwater-irrigated plain constrained to aquifer stable depletion using a coupled PSO-SWAT-MODFLOW hydro-agronomic model. Journal of Cleaner Production, 262, 121349.
Sadeghi-Tabas, S., Samadi, S.Z., Akbarpour, A., Pourreza-Bilondi, M., (2017). Sustainable groundwater modeling using single-and multi-objective optimization algorithms. Journal of Hydroinformatics, 19(1): 97-114.
Salari, M., HosseiniKheirabad, M., Ehteshami, M., Niloufar, S., Moaddeli, E.T., (2020). Modeling of Groundwater Quality for Drinking and Agricultural Purpose: A Case Study in Kahorestan plain. Journal of Environmental Treatment Techniques, 8(1): 346-352.
Sarakorn, W., Vachiratienchai, C., (2018). Hybrid finite difference–finite element method to incorporate topography and bathymetry for two-dimensional magnetotelluric modeling. Earth, Planets and Space, 70(1): 103.
Sayed, E., Riad, P., Elbeih, S.F., Hassan, A.A., Hagras, M., (2020). Sustainable groundwater management in arid regions considering climate change impacts in Moghra region, Egypt. Groundwater for Sustainable Development, 100385.
Schaback, R., Wendland, H., (2001). Characterization and construction of radial basis functions. Multivariate approximation and applications. Cambridge University Press. pp 1-24.
Selzer, P., Cirpka, O.A., (2020). Postprocessing of standard finite element velocity fields for accurate particle tracking applied to groundwater flow. Computational Geosciences, 24, 1605-1624.
Shrestha, S., Neupane, S., Mohanasundaram, S., Pandey, V.P., (2020). Mapping groundwater resiliency under climate change scenarios: A case study of Kathmandu Valley, Nepal. Environmental Research, 183: 109149.
Simpson, M. J., Clement, T.P., (2003). Comparison of finite difference and finite element solutions to the variably saturated flow equation. Journal of hydrology, 270(1-2): 49-64.
Summa, G., Tataranni, A., D’Abramo, G., (2019). Electrical analogue for discharge versus time analysis in a pumping well. Hydrogeology Journal, 27(4): 1527-1536.
Vaezihir, A., Bayanlou, M.B., Ahmadnezhad, Z., Barzegari, G., (2020). Remediation of BTEX plume in a continuous flow model using zeolite-PRB. Journal of Contaminant Hydrology, 230: 103604.
Wang, H.F., Anderson, M.P. (1995). Introduction to groundwater modeling: finite difference and finite element methods. Academic Press. 237 p.
Witherspoon, P.A., Mueller, T.D., Donovan, R.W., (1962). Evaluation of underground gas-storage conditions in aquifers through investigations of groundwater hydrology. Journal of Petroleum Technology, 14(05): 555-561.
Zienkiewichz, O.C., Mayer, P., Cheung, Y.K., (1966). Solution of anisotropic seepage problem by finite elements. In Proc. ASCE , 92: 111-120.