Journal of Advanced Informatics in Water, Soil, and Structure

Journal of Advanced Informatics in Water, Soil, and Structure

Study of the Process of Contaminant Transport and Pumping in a Laboratory Model

Document Type : Research Article

Authors
Mohammad Javad Zeynali 1
Mohammad Nazeri Tahroudi 2
Omolbani Mohammadrezapour 3
1 Department of Civil Engineering and Architecture, University of Torbat Heydarieh, Torbat Heydarieh, Iran.
2 Department. of Water Engineering, Lurestan University, Khoarramabad, Iran.
3 Department of Water Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.
10.22048/wss.2024.468425.1012
Abstract
In this research, the objective is to study the process of contaminant transport and pumping in a laboratory model. A two-dimensional laboratory model was used in this research. The length, width, and height of the model respectively were 140 cm, 5 cm, and 57 cm. Chambers were provided on the left and right sides of the model to store water and create a constant hydraulic head. The material used in this model was glass beads, which act similarly to sand particles. Sampling tubes were installed at five points A to E along the length of the model and at three depths. Finally, at specific times after the contaminant release, a sample of the contaminant was injected and its concentration was analyzed. The research results showed that at a gradient of 0.05, the contaminant transport rate was significantly higher than at a gradient of 0.014. Therefore, the depth penetration of the contaminant is less at a gradient of 0.05 than at a gradient of 0.14. On the other hand, contaminant pumping at points C2 and D2 showed that pumping from point C2 more effectively reduced the contaminant concentration in the entire laboratory model. This holds for contaminants with other concentrations as well. Contaminant concentration and hydraulic gradient are two important factors in the amount of contaminant transport. Also, for effective contaminant pumping, the best location for pumping contaminated water is somewhere near the seepage site and in the path of the contaminant movement.
Keywords
Contaminant
Laboratory Model
Pumping
Seepage
Transport
Subjects
  1. Alexander, A.C., Ndambuki, J.M., Salim, R.W. and Manda, A.K., (2018). Groundwater remediation optimization using solving constraint integer program (scip). Groundwater for Sustainable Development, 7, pp.176-184.
  2. Boddula, S. and Eldho, T.I., (2017). A moving least squares based meshless local petrov-galerkin method for the simulation of contaminant transport in porous media. Engineering Analysis with Boundary Elements, 78, pp.8-19.
  3. Darabi, B. And Ghafouri, H., (2007). Optimal identification of ground-water pollution sources.
  4. Eldho, T. I., & Swathi, B. (2018). Groundwater contamination problems and numerical simulation. Environmental Contaminants: Measurement, Modelling and Control, 167-194.
  5. Erickson, M., Mayer, A. and Horn, J., (2002). Multi-objective optimal design of groundwater remediation systems: application of the niched Pareto genetic algorithm (NPGA). Advances in Water Resources, 25(1), pp.51-65.
  6. Esfahani, H. K., & Datta, B. (2018). Fractal singularity–based multiobjective monitoring networks for reactive species contaminant source characterization. Journal of Water Resources Planning and Management, 144(6), 04018021.
  7. Gorelick, S.M., Voss, C.I., Gill, P.E., Murray, W., Saunders, M.A. and Wright, M.H., (1984). Aquifer reclamation design: the use of contaminant transport simulation combined with nonlinear programing. Water Resources Research, 20(4), pp.415-427.
  8. Guneshwor, L., Eldho, T.I. and Vinod Kumar, A., (2018). Identification of groundwater contamination sources using meshfree RPCM simulation and particle swarm optimization. Water Resources Management,  32(4), pp.1517-1538.
  9. Joswig, P., Vernocchi, S., Pilone, A., Violetti, A., Brunetti, E., Pellegrini, M., & Grava, A. (2017). Continuously optimizing a groundwater remediation system in complex fractured media. Universtà degli Studi di Cagliari.
  10. Kumar, D., Ch, S., Mathur, S. and Adamowski, J., (2015). Multi-objective optimization of in-situ bioremediation of groundwater using a hybrid metaheuristic technique based on differential evolution, genetic algorithms and simulated annealing. Journal of Water and Land Development.
  11. Mategaonkar, M., Eldho, T.I. and Kamat, S., (2018). In-situ bioremediation of groundwater using a meshfree model and particle swarm optimization. Journal of Hydroinformatics, 20(4), pp.886-897.
  12. Ouyang, Q., Lu, W., Hou, Z., Zhang, Y., Li, S. and Luo, J., (2017). Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method. Journal of contaminant hydrology, 200, pp.15-23.
  13. Sbai, M.A., (2019). Well rate and placement for optimal groundwater remediation design with a surrogate model. Water, 11(11), p.2233.
  14. Seyedpour, S.M., Kirmizakis, P., Brennan, P., Doherty, R. and Ricken, T., (2019). Optimal remediation design and simulation of groundwater flow coupled to contaminant transport using genetic algorithm and radial point collocation method (RPCM). Science of The Total Environment, 669, pp.389-399.
  15. Singh, A. and Minsker, B.S., (2008). Uncertainty‐based multiobjective optimization of groundwater remediation design. Water resources research, 44(2).
  16. Wang, Y., Xiao, W.H., Wang, Y.C., Wei, W.X., Liu, X.M., Yang, H. and Chen, Y., (2018), October. Simulating-optimizing coupled method for pumping well layout at a nitrate-polluted groundwater site. In IOP Conference Series: Earth and Environmental Science (Vol. 191, No. 1, p. 012071). IOP Publishing.
  17. Yang, A., Yang, Q., Fan, Y., Suo, M., Fu, H., Liu, J. and Lin, X., (2018a). An Integrated Simulation, Inference and Optimization Approach for Groundwater Remediation with Two-Stage Health-Risk Assessment. Water, 10(6), p.694.
  18. Yang, A.L., Dai, Z.N., Yang, Q., Mcbean, E.A. and Lin, X.J., (2018b), May. A Multi-objective Optimal Model for Groundwater Remediation under Health Risk Assessment in a Petroleum contaminated site. In IOP Conference Series: Earth and Environmental Science (Vol. 146, No. 1, p. 012014). IOP Publishing.
  19. Zeynali, M. J., Nazeri Tahroudi, M., and Mohammadrezapour, O. (2024). Optimizing Pump-and-Treat Method by Using Optimization-Simulation Models. Sustainable Earth Trends, 4(3), 19-30. doi: 10.48308/set.2024.236332.1060
  20. Zeynali, M. J., Nazeri Tahroudi, M., and Mohammadrezapour, O. (2024). Investigating the Optimization-Simulation Problem of Groundwater Remediation Under Various Scenarios. Water Harvesting Research, 7(1), 125-139.
  21. Zeynali, M. J., Pourreza-Bilondi, M., Akbarpour, A., Yazdi, J., & Zekri, S. (2022a). Optimizing pump-and-treat method by considering important remediation objectives. Applied Water Science, 12(12), 268.
  22. Zeynali, M. J., Pourreza-Bilondi, M., Akbarpour, A., Yazdi, J., & Zekri, S. (2022b). Development of a contaminant concentration transport model for sulfate-contaminated areas. Applied Water Science, 12(7), 169.
Journal of Advanced Informatics in Water, Soil, and Structure
Volume 1, Issue 1 - Serial Number 1
January 2025
Pages 75-85

  • Receive Date 18 July 2024
  • Revise Date 16 October 2024
  • Accept Date 05 November 2024
  • First Publish Date 01 January 2025
  • Publish Date 01 January 2025