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Management of dewatering schemes in an open cast mine operation using groundwater fow modeling: a case study of karst aquifer, Tamil Nadu, India

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
An efficient dewatering scheme helps the management authority of mines in decision-making on the minimum quantity of withdrawal of groundwater from open-cast mines to avoid excessive groundwater withdrawal from the mines. Karst aquifers are characterized by a dual flow system consisting of Darcy flow and non-Darcy flow in the Matrix and conduits respectively. Due to lack of site-specific data, it is difficult to model the flow behavior in the dual flow system. This study evaluated equivalent porous medium (EPM) approach and the hybrid approach/combined discrete-continuum approach (CDC) for modeling groundwater flow in a karst aquifer and found that hybrid approach is suitable for modeling the flow in the karst aquifer system. Hybrid approach is applied to derive the optimum dewatering scheme for safe mining of limestone in the Adanakurichi limestone mines of Tamil Nadu, India and was found that an additional 20% increase in pumping is required in the year 2020 compared to 2016 to bring the water level to the limestone bottom. Wavelet coherence diagram was used to identify the interrelation between rainfall and groundwater levels, and also between the groundwater levels at different locations. The results from the study will be helpful for the better management of groundwater control operations in karst aquifers, under various safe level of operations. MODFLOW 2005 was used to model the aquifer based on EPM approach and for modeling based on hybrid approach conduit fow process (CFP) Mode 1in MODFLOW was used.
Czasopismo
Rocznik
Strony
283--303
Opis fizyczny
Bibliogr. 27 poz.
Twórcy
  • Department of Civil Engineering, IIT Madras, Chennai, Tamil Nadu 600036, India
  • Department of Civil Engineering, NIT Calicut, Calicut, Kerala 673601, India
  • Department of Civil Engineering, NIT Calicut, Calicut, Kerala 673601, India
Bibliografia
  • 1. Bakalowicz M (2005) Karst groundwater: a challenge for new resources. Hydrogeol J 13:148–160
  • 2. Barrett ME (1996) A parsimonious model for simulation of flow and transport in a karst aquifer. PhD Thesis. The University of Texas at Austin, Texas, p 180.
  • 3. GEC 2015 (2015) Report of the ground water resource estimation committee; Government of India, New Delhi.
  • 4. Grinsted A, Moore JC, Jevrejeva S (2004) Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process Geophys 11:561–566
  • 5. Harbaugh AW, Banta ER, Hill MC, McDonald MG (2000) MODFLOW-2000, the U.S. Geological Survey modular ground-water model—user guide to modularization concepts and the ground water flow process. U.S. Geological Survey Open-File Report 00–92, p 121
  • 6. Hill M, Stewart M, Martin A (2010) Evaluation of the MODFLOW-2005 conduit flow process. Ground Water 48(4):549–559
  • 7. Kiraly L (1998) Modelling karst aquifers by the combined discrete channel and continuum approach. Bull Du Centre D’hydrogeologie 16:77–98
  • 8. Liedl R, Sauter M, Huckinghaus D, Clemens T, Teutsch G (2003) Simulation of the development of karst aquifers using a coupled continuum pipe flow model. Water Resour Res 39(3):1057
  • 9. Lindgren RJ, Dutton AR, Hovorka SD, Worthington SRH, Painter S (2004) Conceptualization and simulation of the Edwards Aquifer, San Antonio Region, Texas, Scientific Investigations Report, Reston, Virginia
  • 10. Long JCS, Remer JS, Wilson CR, Witherspoon PA (1982) Porous media equivalents for networks of discontinuous fractures. Water Resour Res 18(3):645–658
  • 11. McDonald MG, Harbaugh AW (1984) A modular three-dimensional finite difference ground-water flow model. U.S. Geological Survey Open-File Report. pp 83–875
  • 12. McDonald MG, Harbaugh AW (1988) A modular three-dimensional finite-difference ground-water flow model. Technical report, U.S. Geol. Survey, Reston. VA
  • 13. Nourani V, Mousavi S (2016) Spatiotemporal groundwater level modeling using hybrid artificial intelligencemeshless method. J Hydrol 536:10–25
  • 14. Putnam LD, Long AJ (2009) Numerical groundwater-flow model of the Minnelusa and Madison hydrogeologic units in the Rapid City area, South Dakota. U.S. Geological Survey Scientific Investigations Report 2009–5205
  • 15. Qi P, Zhang G, Xu YJ, Wang L, Ding C, Cheng C (2018) Assessing the influence of precipitation on shallow groundwater table response using a combination of singular value decomposition and cross-wavelet approaches. Water 10(5):598
  • 16. Quinn JJ, Tomasko D, Kuiper JA (2006) Modeling complex flow in a karst aquifer. Sed Geol 184(3–4):343–351
  • 17. Reimann T, Hill ME (2009) MODFLOW-CFP: a new conduit flow process for MODFLOW-2005. Ground Water 47(3):321–325
  • 18. Reimann T, Geyer T, Shoemaker B, Liedl R, Sauter M (2011) Effects of dynamically variable saturation and matrix-conduit coupling of flow in karst aquifers. Water Resour Res 47:W11503. https://doi.org/10.1029/2011WR010446
  • 19. Roshni T, Jha MK, Deo RC, Vandana A (2019) “Development and evaluation of hybrid artificial neural network architectures for modeling spatio-temporal groundwater fluctuations in a complex aquifer system,” water resources management: an international journal, published for the European Water Resources Association (EWRA), Springer. Eur Water Resour Assoc (EWRA) 33(7):2381–2397
  • 20. Saller SP, Ronayne MJ, Long AJ (2013) Comparison of a karst groundwater model with and without discrete conduit flow. Hydrogeol J 21(7):1555–1566
  • 21. Scanlon BR, Mace RE, Barrett ME, Smith B (2003) Can we simulate regional groundwater flow in a karst system using equivalent porous media models? Case study, Barton 64, Springs Edwards aquifer, United States of America. J Hydrol 276:137–158
  • 22. Shoemaker WB, Kuniansky EL, Birk S, Bauer S, Swain ED (2008) Documentation of a conduit flow process (CFP) for MODFLOW-2005
  • 23. Sithara S, Pramada SK, Thampi SG (2020) Sea level prediction using climatic variables: a comparative study of SVM and hybrid wavelet SVM approaches. Acta Geophys 68(6):1779–1790
  • 24. Surinaidu L, Rao VG, Rao NS, Srinu S (2014) Hydrogeological and groundwater modeling studies to estimate the groundwater inflows into the coal Mines at different mine development stages using MODFLOW, Andhra Pradesh, India. Water Resour Indus 7:49–65
  • 25. Torrence C, Webster P (1999) Interdecadal changes in the ENSO-monsoon system. J Clim 12(8):2679–2690
  • 26. Varalakshmi V, Venkateswara Rao B, Surinaidu L, Tejaswini M (2014) Groundwater flow modeling of a hard rock aquifer: case study. J Hydrol Eng 19(5):877–886
  • 27. Xu Z, Hu BX (2017) Development of a discrete—continuum VDFST—CFP numerical model for simulating seawater intrusion to a coastal karst aquifer with a conduit system. Water Resour Res 53:688–711
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cdf9c0b1-0030-4c96-9511-027f44bef6ec
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