Evaluating Aquifer's Hydrodynamic Parameters Using Pumping Tests and Geoelectric Data (Case Study: Alluvial Aquifer in the Northeast of Gachsaran City)

Document Type : Research Article

Authors

• A. Khedri ¹
• A. Saberinasr ²
• N. Kalantari ²

¹ Director of Kusar Dam, Kohgiluyeh and Boyer-Ahmad Regional Water Authority, Yasuj, Iran

² Faculty of Earth Sciences, Shahid Chamran Univercity of Ahvaz, Ahvaz, Iran

10.22067/jsw.2024.86955.1389

Abstract

Introduction
 The comprehension of the hydrogeological conditions of the aquifer and the determination of its hydraulic characteristics, such as hydraulic conductivity, transmissivity coefficient, and specific storage, are crucial for the management and preservation of groundwater resources. Various conventional methods, including empirical formulas, laboratory techniques (constant and falling head), tracer tests, field tests (Lugeon, Lefranc, slug, flowmeter, and pumping tests), and groundwater inverse modeling, are employed to establish these characteristics, particularly hydraulic conductivity. Empirical formulas are limited to ideal conditions, and in laboratory methods, the sample must be kept undisturbed. Due to the impracticality of measuring large-scale effective factors, the hydraulic conductivity determined through laboratory methods is also the only representative of the hydraulic conductivity at the sampling point. Tracer studies encounter numerous constraints, such as time, cost, porosity determination, and tracer dispersion in multilayered aquifers. It is also difficult to determine the average hydrodynamic properties of the heterogeneous aquifer based on the data obtained from a specific section of the Lefranc and Slug tests. Consequently, pumping tests are commonly selected for hydraulic parameter estimation. Although costly and time-intensive, these tests provide more precise coefficients. Geophysical methods have been greatly developed during the last two decades and have shown a significant correlation with the hydraulic parameters of the aquifer derived from borehole pumping tests or direct laboratory measurements. This approach minimizes uncertainties in numerical model calibration, improves data coverage, and reduces the time and cost of regional hydrogeological investigations. The conventional approach, known as the electrical resistivity method, is still widely used in global and local research projects for evaluating aquifer hydraulic characteristics (Ige et al., 2018; Arétouyap et al., 2019; Youssef, 2020; Ullah et al., 2020; de Almeida et al., 2021; Lekone et al., 2023). Therefore, this study aims to use the integrated approach of the geophysical method and pumping test as a cost-effective and efficient alternative for estimating the hydraulic parameters of the alluvial aquifer in the northeast of Gachsaran city.
 
Material and Methods
 The research area is an alluvial aquifer located 5 km to the northeast of Gachsaran, between coordinates 50-52 to 51-09 E longitude and 30-15 to 30-28 N latitude. Using 86 vertical electrical soundings, Archie's equations, and the IPI2win software, the hydraulic characteristics of the aquifer under investigation were estimated. Subsequently, these characteristics were then compared to the coefficients derived from the data of two pumping test wells, which were calculated using the Aquifer test software and obtained via the Cooper-Jacob and Neuman methods.
 
Results and discussion
 The hydrodynamic coefficients of the aquifer were initially determined using the Cooper-Jacob method in this study. The hydraulic conductivity values for wells one and two are 4.9 m/day and 5.7 m/day, respectively. Correspondingly, the storage coefficient values for wells one and two are 0.015 and 0.021, respectively. Based on the Cooper-Jacob approach, it is deduced that if the storage coefficient values exceed 0.001, the aquifer is classified as unconfined. In this study, the storage coefficient values for both pumping wells suggest that the aquifer is unconfined. Since the vertical flow component and the delayed yield phenomenon should also be taken into account in unconfiend aquifers, the Neuman analytical model has been used in the studied aquifer. The values of specific yield (Sy) for pumping wells one and two, which are related to delayed yield, are 0.05 and 0.04, respectively. These values were calculated by analyzing the first segment of the curve derived from the Neuman logarithmic drawdown-time plot. The storage coefficient values for pumping wells one and two, extracted from the second section of the curve, are 0.015 and 0.021, respectively. Furthermore, the transmissivity value for well number 1 was 323 m²/day, while for well number 2, it was 655.5 m²/day. The vertical electrical sounding (VES) data were subsequently initially analyzed and interpreted using the IPI2win software and the equalization curve method (partial curve matching technique). The coefficients denoted as m and n, indicative of the degree of cementation of the sediments, were determined based on the sedimentary composition prevalent in the area. Archie's equations were employed to calculate the formation factor and porosity parameters. The aquifer exhibits a porosity range of approximately 0.15 in the eastern and southeastern parts (near the outlet of the plain) and around 0.41 in the centeral, northern, and northwestern sections of the area (next to the Asmari Formation). The specific yield (Sy) of the aquifer was calculated using the provided formula:
 
The minimum and maximum specific yield were estimated as 0.006 (in the eastern and southeastern regions) and 0.089 (in the western and northwestern regions of the plain), respectively, with an average value of 0.04. The transmissivity coefficients for the entire aquifer were then calculated based on the fitted relationship between hydraulic conductivity (K) and formation factor (F):
 
The range of transmissivity coefficients varies from a minimum of 63 m²/day (in the western and northwestern sections of the plain) to a maximum of 608.9 m²/day (in the eastern and southeastern areas). The average transmissivity coefficient is calculated as 323.7 m²/day. To ensure the precision of the geoelectric method's coefficients, a comparative analysis was conducted with the hydrodynamic coefficients obtained from the two pumping test wells, as presented in the table below:
 




Well No.


K(m/d)


T(m²/d)


Sy




PT^*


VES^*


PT


VES


PT


VES




1


4.9


3.6


323


237


0.05


0.05




2


5.7


5.5


655.5


632.5


0.04


0.03




^*PT: Pumping Test; VES: Vertical Electrical Sounding




 
Conclusion
 The evaluation and comparison of the hydrodynamic coefficients derived from the aforementioned methods indicate that the geoelectric method coefficients exhibit acceptable agreement with the pumping test coefficients. In other words, the analysis of the pumping test conducted using the Neuman technique in the unconfined aquifer revealed that well number two displayed a greater transmissivity coefficient, while well number one presented a higher specific yield. These findings are confirmed by the geoelectric approach. Consequently, such hybrid approaches, which include simultaneous analysis of geophysical methods (such as VES) and pumping tests will be a great alternative to multiple costly pumping tests for evaluating the hydrodynamic coefficients of an aquifer. Moreover, employing this hybrid technique enables the generation of dense hydrodynamic coefficients in an aquifer for use as inputs in the groundwater model.
 

Keywords

• Gachsaran
• Hydrodynamic coefficients
• Pumping Test
• Vertical Electrical Soundings

Main Subjects

• Agricultural Meteorology

©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

References

1. Abdulrazzaq, Z.T., Al-Ansari, N., Ahmed Aziz, N., Agbasi, O.E., & Etuk, S.E. (2020). Estimation of main aquifer parameters using geoelectric measurements to select the suitable wells locations in Bahr Al-Najaf depression, Iraq. Groundwater for Sustainable Development, 11, 100437. https://doi.org/10.1016/j.gsd.2020.100437
2. Ahmadi, S. (2008). Investigating and forecasting the fluctuations of the Imamzadeh Jafar plain aquifer in Gachsaran city with a perspective on the effects of artificial recharge and using the MODFLOW model. Master Thesis in Hydrogeology, Science Faculty, Islamic Azad University Science and Research Branch, Tehran. Iran. (In Persian with English abstract)
3. Archie, GE. (1942). The electrical resistivity log as an aid in determining some reservoir characteristics. Transactions of the AIME, 146(01), 54-62. https://doi.org/10.2118/942054-G
4. Arétouyap, Z., Bisso D., Méli'I, J.L., Nouck, F.N., Njoya, A., & Asfahani, J. (2019). Hydraulic parameters evaluation of the Pan-African aquifer by applying an alternative geoelectrical approach based on vertical electrical soundings. Geofísica Internacional, 58(2), 113-126. https://doi.org/10.22201/igeof.00167169p.2018.58.2.1964
5. Bobachev, C. (2002). IPI2Win: A windows software for an automatic interpretation of resistivity sounding data. PhD Thesis, Moscow State University, Russia.
6. Calvache, M.L., Sánchez-Úbeda, J.P., Duque, C., López-Chicano, M., & de la Torre, B. (2016). Evaluation of analytical methods to study aquifer properties with pumping tests in coastal aquifers with numerical modelling (Motril-Salobreña Aquifer). Water Resources Management, 30, 559–575. https://doi.org/10.1007/s11269-015-1177-6
7. Chen, J., Hubbard, S., & Rubin, Y. (2001). Estimating the hydraulic conductivity at the South Oyster Site from geophysical tomographic data using Bayesian techniques based on the normal linear regression model. Water Resources Research, 37(6), 1603-1613. https://doi.org/10.1029/2000WR900392
8. Crestani, E., Camporese, M., & Salandin, P. (2015). Assessment of hydraulic conductivity distributions through assimilation of travel time data from ERT-monitored tracer tests, Advances in Water Resources, 84, 23-36. https://doi.org/10.1016/j.advwatres.2015.07.022
9. Darvishzadeh, A. (2003). Geology of Iran. 5^th Edition, 902P, Amirkabir Publication, Tehran. (In Persian)
10. de Almeida, A., Maciel, D.F., Sousa, K.F., Nascimento, C.T.C., & Koide, S. (2021). Vertical electrical sounding (VES) for estimation of hydraulic parameters in the Porous aquifer. Water, 13(2), 170(1-15). https://doi.org/10.3390/w13020170
11. Falowo, O.O., Daramola, A.S., & Ojo, O.O. (2019). Aquifers hydraulic parameters measurement and analysis by pumping test. American Journal of Water Resources, 7(4), 146-154. https://doi.org/10.12691/ajwr-7-4-3
12. Frohlich, R.K., & Kelly, W.E. (1988). Estimates of specific yield with the geoelectric resistivity method in glacial aquifers. Journal of Hydrology, 97(1-2), 33-44. https://doi.org/10.1016/0022-1694(88)90064-9
13. George, N.J., Ibuot, J.C., & Obiora, D.N. (2015). Geoelectrohydraulic parameters of shallow sandy aquifer in Itu, Akwa Ibom State (Nigeria) using geoelectric and hydrogeological measurements. Journal of African Earth Sciences, 110, 52-63. https://doi.org/10.1016/j.jafrearsci.2015.06.006
14. Hasan, M., Shang, Y., Jin, W., & Akhter, G. (2019). Assessment of aquifer vulnerability using integrated geophysical approach in weathered terrains of South China. Open Geosciences, 11, 1129–1150. https://doi.org/ 10.1515/geo-2019-0087
15. Hasan, M., Shang, Y., Jin, W., & Akhter, G. (2021). Estimation of hydraulic parameters in a hard rock aquifer using integrated surface geoelectrical method and pumping test data in southeast Guangdong, China. Geosciences Journal, 25, 223–242. https://doi.org/10.1007/s12303-020-0018-7
16. Hatami Golmakani, P., Sheikh, V.B., & Hosseinalizadeh M. (2017). The effect of measurement methods on saturated hydraulic conductivity in eastern loess lands of Golestan province. Journal of Soil Management and Sustainable Production, 6(4), 87-102. (In Persian with English abstract). https://doi.org/10.22069/ejsms. 2017.10322.1614
17. Huntley, D. (1986). Relations between permeability and electrical resistivity in granular aquifers. Groundwater, 24(4), 466-474. https://doi.org/10.1111/j.1745-6584.1986.tb01025.x
18. Ige, O., Obasaju, D., Baiyegunhi, C., Ogunsanwo, O., & Baiyegunhi, T. (2018). Evaluation of aquifer hydraulic characteristics using geoelectrical sounding, pumping and laboratory tests: A case study of Lokoja and Patti Formations, Southern Bida Basin, Nigeria. Open Geosciences, 10(1), 807-820. https://doi.org/10.1515/geo-2018-0063
19. Jacob, CE. (1944). Notes on determining permeability by pumping tests under water-table conditions. US Geological Survey open-file report. 1945, University of Illinois at Urbana-Champaign, USA. Partial penetration of pumping well, adjustments for: US Geol. Survey open-file report. 1947, Drawdown test to determine effective radius of artesian well: Am. Soc. Civil Eng. Trans. 1944;112:1047-70.
20. Kazakis, N., & Vargemezis, G. (2016). Voudouris K.S., Estimation of hydraulic parameters in a complex porous aquifer system using geoelectrical methods. Science of The Total Environment, 550, 742-750. https://doi.org/10.1016/j.scitotenv.2016.01.133
21. Lashkaripour, Gh., Yazdanpanah, F., & Ansari, Kh. (2013). Investigating the relationship between permeability coefficient (k) and gradation and proposing the empirical formula. In 8^th Conference of the Iranian Association of Engineering Geology and the Environment, 6 November 2013, Ferdowsi University of Mashhad, Mashhad, Iran. (In Persian)
22. Lekone, O.S., Tafesse, N.T., Ranganai, R.T., Laletsang, K., & Masaka, T.L. (2023). Estimation of Aquifer Hydraulic Parameters Using Geo-electric Method in the Dukwi Wellfields, North-eastern Botswana, PREPRINT (Version 1) available at Research Square, 1-27. https://doi.org/10.21203/rs.3.rs-3052755/v1
23. Minutti, C., Illman W.A., & Gomez S. (2020). A New Inverse Modeling Approach for Hydraulic Conductivity Estimation Based on Gaussian Mixtures. Water Resources Research, 56(9), 1-21. https://doi.org/10.1029/ 2019WR026531
24. Nakhaei, M., & Lashkaripour, Gh. (2004). Estimation of Porosity and Specific yield of Shooru Aquifer by Resistivity method. Journal of Science (Tarbiat Moalem University), 3(1), 191-202. (In Persian)
25. Neuman, S.P. (1972). Theory of flow in unconfined aquifers considering delayed response of the water table. Water Resources Research, 8(4), 1031-1045. https://doi.org/10.1029/WR008i004p01031
26. Perdomo, S., Ainchil, J.E., & Kruse, E. (2014). Hydraulic parameters estimation from well logging resistivity and geoelectrical measurements. Journal of Applied Geophysics, 105, 50-58. https://doi.org/10.1016/j.jappgeo.2014. 02.020
27. Rostami, A., Hassani-Giv, M. (2011). Investigating the relationship between cementation and porosity as determined by core analysis and comparing it to Shell and Borai's experimental relationships in one of the dolomite reservoirs in southwest Iran. Scientific Journal of Oil and Gas Exploration and Production, 82, 61-65. (In Persian)
28. Schimschal, U. (1981). The relationship of geophysical measurements to hydraulic conductivity at the brantley damsite, New Mexico. Geoexploration, 19(2), 115-125. https://doi.org/10.1016/0016-7142(81)90024-7
29. Song, X.M., Kong, F.Z., & Zhan, S. (2011). Assessment of water resources carrying capacity in Tianjin city of China. Water Resources Management, 25, 857–873. https://doi.org/10.1007/s11269-010-9730-9
30. Taheri-tizro, A.T., Voudouris, K., & Basami, Y. (2012). Estimation of porosity and specific yield by application of geoelectrical method–a case study in western Iran. Journal of Hydrology, 454, 160-172. https://doi.org/10.1016/ j.jhydrol.2012.06.009
31. Theis, C.V. (1935). The relation between the lowering of the piezometric surface and the rate and duration of discharge of a well using ground‐water storage. Eos, Transactions American Geophysical Union, 16(2), 519-524. https://doi.org/10.1029/TR016i002p00519
32. Ullah, F., Su, L.J., Ullah, H., & Asghar, A. (2020). Estimation of hydraulic parameters of an unconfined aquifer by using geoelectrical and pumping test data: a case study of the Mandi Bahauddin District, Pakistan. Arabian Journal of Geosciences, 13, 484. https://doi.org/10.1007/s12517-020-05488-3
33. Urish, D.W. (1981). Electrical resistivity-hydraulic conductivity relationships in glacial outwash aquifers. Water Resources Research, 17(5), 1401-1408. https://doi.org/10.1029/WR017i005p01401
34. Vogeler, I., Carrick, S., Cichota, R., & Lilburne, L. (2019). Estimation of soil subsurface hydraulic conductivity based on inverse modelling and soil morphology. Journal of Hydrology, 574, 373-382. https://doi.org/10.1016/j. jhydrol.2019.04.002
35. Vu, M.T., & Jardani, A. (2022). Mapping of hydraulic transmissivity field from inversion of tracer test data using convolutional neural networks. CNN-2T, Journal of Hydrology, 606, 127443, https://doi.org/10.1016/j.jhydrol. 2022.127443
36. Yeh, Y.J., Lee, C.H., & Chen, S.T. (2000). A tracer method to determine hydraulic conductivity and effective porosity of saturated clays under low gradients. Groundwater, 38, 522-529. https://doi.org/10.1111/j.1745-6584.2000.tb00244.x
37. Youssef, M.A.S. (2020). Geoelectrical analysis for evaluating the aquifer hydraulic characteristics in Ain El-Soukhna area, West Gulf of Suez, Egypt. NRIAG Journal of Astronomy and Geophysics, 9(1), 85-98. https://doi. org/10.1080/20909977.2020.1713583