1887
  1. Home
  2. A-Z Publications
  3. Near Surface Geophysics
  4. Volume 21, Issue 2
  5. Article
Volume 21, Issue 2
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

Abstract

Geoelectric and electromagnetic (EM) methods are rapid and non‐invasive geophysical techniques for estimating groundwater properties and characterizing the spatial and temporal variability of subsurface formations. However, to quantitatively interpret the EM data, the systematic error due to calibration problems and random error must be considered. We conducted coincident EM and electrical resistivity tomography (ERT) surveys in January and December 2018 on Big Pine Key, FL. In this study, we used vertical electrical sounding (VES) data extracted from a 220 m long ERT profile to calibrate the EM data. The inverted VES data were used as input in the EM forward model to estimate the quadrature component response. Then, the observed offset between the calculated and observed quadrature data was corrected using a multiple linear regression model. Finally, the calibrated quadrature data were converted to apparent electrical conductivity and inverted as a 2‐layer model using both the full solution and the low induction approximation. These models were used to assess the temporal and spatial variations of conductivity on a 2.2 km long E–W trending profile across the island. The calibrated apparent electrical conductivity on the profile decreased between January and December 2018, with the largest decreases in the lower elevation regions of the profile. In addition, the 2‐layer models inverted using the full solution and low induction approximation showed the depth of the freshwater interface increased by December 2018. These observations suggest the recovery of the freshwater lens due to precipitation. Based on this study, we concluded the VES at pilot locations can be used for calibration purposes and verification of the accuracy of EM measurements.

© 2023 European Association of Geoscientists & Engineers. © 2022 European Association of Geoscientists & Engineers.
Loading

Article metrics loading...

/content/journals/10.1002/nsg.12244
2023-03-21
2024-04-18

  • From This Site

    /content/journals/10.1002/nsg.12244
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Abraham, J.D., Deszcz‐Pan, M., Fitterman, D.V. & Burton, B.L. (2006) Use of a handheld broadband EM induction system for deriving resistivity depth images. In: Symposium on the application of geophysics to engineering and environmental problems, 2006. https://doi.org/10.4133/1.2923642
  2. Al‐Fouzan, F., Harbert, W., Dilmore, R., Hammack, R., Sams, J., Veloski, G. et al. (2004) Methods for removing signal noise from helicopter electromagnetic survey data. Mine Water Environ, 23, 28–33. https://doi.org/10.1007/s10230‐004‐0033‐3
     [Google Scholar]
  3. Anderson, W.L. (1979) Numerical integration of related Hankel transforms of orders 0 and 1 by adaptive digital filtering. Geophysics, 44, 1287–1305.
     [Google Scholar]
  4. Baty, F., Ritz, C., Charles, S., Brutsche, M., Flandrois, J.P. & Delignette‐Muller, M.L. (2015) A toolbox for nonlinear regression in R: the package nlstools. Journal of Statistical Software, 66(5), 1–21.
     [Google Scholar]
  5. Bongiovanni, M., Bonomo, N., de la Vega, M., Martino, L. & Osella, A. (2008) Rapid evaluation of multifrequency EMI data to characterize buried structures at a historical Jesuit Mission in Argentina. Journal of Applied Geophysics, 64(1–2), 37–46.
     [Google Scholar]
  6. Brodie, R. & Sambridge, M. (2006) A holistic approach to inversion of frequency‐domain airborne EM data. Geophysics, 71, G301–G312. https://doi.org/10.1190/1.2356112.
     [Google Scholar]
  7. Cangialosi, J.P., Latto, A.S. & Berg, R. (2018) Hurricane Irma (30 August–12 September 2017). Tropical cyclone reports. University Park: National Hurricane Center. https://www.nhc.noaa.gov/data/‐tcr/AL112017_Irma.pdf
  8. Constable, S.C., Parker, R.L. & Constable, C.G. (1987) Occam's inversion: a practical algorithm for generating smooth models from electromagnetic sounding data. Geophysics, 52(3), 289–300.
     [Google Scholar]
  9. Day‐Lewis, F.D., White, E.A., Johnson, C.D., Lane, J.W. & Belaval, M. (2006) Continuous resistivity profiling to delineate submarine groundwater discharge—examples and limitations. The Leading Edge, 25(6), 724–728.
     [Google Scholar]
  10. Delefortrie, S., De Smedt, P., Saey, T., Van De Vijver, E. & Van Meirvenne, M. (2014) An efficient calibration procedure for correction of drift in EMI survey data. Journal of Applied Geophysics, 110, 115–125.
     [Google Scholar]
  11. Deszcz‐Pan, M., Fitterman, D.V. & Labson, V.F. (1998) Reduction of inversion errors in helicopter EM data using auxiliary information. Exploration Geophysics, 29(2), 142–146.
     [Google Scholar]
  12. Ekstrøm, C.T. (2014) Teaching instant experience with graphical model validation techniques. Teaching Statistics, 36(1), 23–26.
     [Google Scholar]
  13. Fan, X., Dufresne, A., Whiteley, J., Yunus, A.P., Subramanian, S.S., Okeke, C.A. et al. (2021) Recent technological and methodological advances for the investigation of landslide dams. Earth‐Science Reviews, 218, 103646.
     [Google Scholar]
  14. Farquharson, C.G., Oldenburg, D.W. & Routh, P.S. (2003) Simultaneous 1D inversion of loop–loop electromagnetic data for magnetic susceptibility and electrical conductivity. Geophysics, 68(6), 1857–1869.
     [Google Scholar]
  15. Fitterman, D.V. (2015) Tools and techniques: active‐source electromagnetic methods. In: Schubert, G. (Eds.), Treatise on geophysics, Oxford, UK: Elsevier, pp. 233–259. http://doi.org/10.1016/B978‐0‐444‐53802‐4.00193‐7
     [Google Scholar]
  16. Fitterman, D.V. & Deszcz‐Pan, M. (1998) Helicopter EM mapping of saltwater intrusion in Everglades National Park. Florida. Exploration Geophysics, 29(2), 240–243.
     [Google Scholar]
  17. GSSI. (2019) Profiler EMP‐400. Geophysical.com. From https://www.‐geophysical.com/products/profiler‐emp‐400 [Retrieved July 30, 2019].
  18. Hanssens, D., Van De Vijver, E., Waegeman, W., Everett, M.E., Moffat, I., Sarris, A. et al. (2021) Ambient temperature and relative humidity–based drift correction in frequency domain electromagnetics using machine learning. Near Surface Geophysics, 19(5), 541–556.
     [Google Scholar]
  19. Hanson, C.E. (1980) Freshwater resources of Big Pine Key, Florida (No. 80–447). U.S. Geological Survey. https://doi.org/10.3133/ofr80447
  20. Hanusz, Z. & TarasiŃska, J. (2014) Simulation study on improved Shapiro–Wilk tests for normality. Communications in Statistics – Simulation and Computation, 43(9), 2093–2105. https://doi.org/10.1080/03610918.2013.844835
     [Google Scholar]
  21. Keller, G.V. & Frischknecht, F.C. (Eds.) (1966) Electrical methods in geophysical prospecting. Oxford, New York: Pergamon Press.
     [Google Scholar]
  22. Khan, M.N., Gong, Y., Hu, T., Lal, R., Zheng, J., Justine, M.F. et al. (2016) Effect of slope, rainfall intensity and mulch on erosion and infiltration under simulated rain on purple soil of south‐western Sichuan province, China. Water, 8(11), 528.
     [Google Scholar]
  23. Kiflai, M.E., Whitman, D., Price, R.M., Frankovich, T.A. & Madden, C.J. (2022) Geophysical characterization in the shallow water estuarine lakes of the Southern Everglades, Florida. Applied Sciences, 12(3), 1154.
     [Google Scholar]
  24. Kiflai, M.E., Whitman, D., Ogurcak, D.E. & Ross, M. (2019) The effect of Hurricane Irma storm surge on the freshwater lens in Big Pine Key, Florida using electrical resistivity tomography. Estuaries and Coasts, 43, 1032–1044. https://doi.org/10.1007/s12237‐019‐00666‐3
     [Google Scholar]
  25. Kiflai, M.E. (2020) Hydrogeophysical characterization and imaging in the mangrove lakes region of Everglades National Park and Big Pine Key, Florida, USA [FIU Electronic Theses and Dissertations]. p. 4475. https://digitalcommons.fiu.edu/etd/4475
  26. Kozak, M. & Piepho, H.P. (2018) What's normal anyway? Residual plots are more telling than significance tests when checking ANOVA assumptions. Journal of Agronomy and Crop Science, 204(1), 86–98.
     [Google Scholar]
  27. Langevin, C.D., Stewart, M.T. & Beaudoin, C.M. (1998) Effects of sea water canals on fresh water resources: an example from Big Pine Key, Florida. Ground Water, 36(3), 503–513.
     [Google Scholar]
  28. Lavoué, F., van der Krak, J., Rings, J., André, F., Moghadas, D., Huisman, J.A. et al. (2010) Electromagnetic induction calibration using apparent electrical conductivity modelling based on electrical resistivity tomography. Near Surface Geophysics, 8(6), 553–561.
     [Google Scholar]
  29. McNeill, J.D. (1980) Electromagnetic terrain conductivity measurement at low induction numbers. In Technical Note TN-6. Geonics Limited, Canada, Ontario: Mississauga, pp. 1–15.
     [Google Scholar]
  30. Minsley, B.J., Bruce, D.S., Richard, H., James, I.S. & Garret, V. (2012) Calibration and filtering strategies for frequency domain electromagnetic data. In: Symposium on the application of geophysics to engineering and environmental problems, 2010. https://doi.org/10.4133/1.3445431
  31. Moghadas, D. & Vrugt, J.A. (2019) The influence of geostatistical prior modeling on the solution of DCT‐based Bayesian inversion: A case study from chicken creek catchment. Remote Sensing, 11(13), 1549. https://doi.org/10.3390/rs11131549
     [Google Scholar]
  32. Murray, C.J., Last, G.V. & Truex, M.J. (2005) Review of geophysical techniques to define the spatial distribution of subsurface properties or contaminants. Richland, Washington: Pacific NorthwestNational Laboratory, Report number, PNNL‐15305, 1–40. https://www.pnnl.gov/main/publications/external/technical_reports/pnnl‐15305.pdf
     [Google Scholar]
  33. Neal, A., Grasmueck, M., McNeill, D.F., Viggiano, D.A. & Eberli, G.P. (2008) Full‐resolution 3D radar stratigraphy of complex oolitic sedimentary architecture: Miami Limestone, Florida, U.S.A. Journal of Sedimentary Research, 78(9), 638–653.
     [Google Scholar]
  34. Nash, J.E. & Sutcliffe, J.V. (1970) River flow forecasting through conceptual models part I — A discussion of principles. Journal of Hydrology, 10(3), 282–290. Bibcode: 1970JHyd…10..282N. https://doi.org/10.1016/0022-1694(70)90255‐6
     [Google Scholar]
  35. Ogurcak, D.E. (2015) The effect of disturbance and freshwater availability on lower Florida keys coastal forest dynamics. Florida International University. https://doi.org/10.25148/etd.‐FIDC000187
     [Google Scholar]
  36. R Core Team (2019) R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R‐project.org/
     [Google Scholar]
  37. Robert, T., Caterina, D., Deceuster, J., Kaufmann, O. & Nguyen, F. (2012) A salt tracer test monitored with surface ERT to detect preferential flow and transport paths in fractured/karstified limestones. Geophysics, 77(2), B55–B67.
     [Google Scholar]
  38. Ross, M.S., Ogurcak, D.E., Stoffella, S., Sah, J.P., Hernandez, J. & Willoughby, H.E. (2020) Hurricanes, storm surge, and Pine forest decline on a low limestone Island. Estuaries and Coasts, 43, 1045–1057.
     [Google Scholar]
  39. Scott, T.M. (2001) Text to accompany the geologic map of Florida. Florida Geological Survey Open File Report, p. 80.
  40. Siemon, B., Stuntebeck, C., Sengpiel, K.P., Röttger, B., Rehli, H.J. & Eberle, D.G. (2002) Investigation of hazardous waste sites and their environment using the BGR helicopter‐borne geophysical system. Journal of Environmental & Engineering Geophysics, 7(4), 169–181.
     [Google Scholar]
  41. Shanahan, P.W., Binley, A., Whalley, W.R. & Watts, C.W. (2015) The use of electromagnetic induction to monitor changes in soil moisture profiles beneath different wheat genotypes. Soil Science Society of America Journal, 79(2), 459–466.
     [Google Scholar]
  42. Shapiro, S.S. & Wilk, M.B. (1965) An analysis of variance test for normality (complete samples). Biometrika, 52, 591–611.
     [Google Scholar]
  43. Stewart, M. (1988) Electromagnetic mapping of fresh‐water lenses on small oceanic islands. Ground Water, 26(2), 187–191.
     [Google Scholar]
  44. Stoyer, C. (2019) IX1D Resistivity, IP, EM Software (Version 3) [Computer software]. Colorado, USA. http://www.interpex.com/ix1dv3/ix1dv3.htm
  45. Stoyer, C.H. (2010) Equivalence analysis of DC and EM data for layered models using the resolution matrix. In: Symposium on the application of geophysics to engineering and environmental problems 2010. Society of Exploration Geophysicists, pp. 173–182.
  46. Tan, X., Mester, A., von Hebel, C., Zimmermann, E., Vereecken, H., van Waasen, S. & van der Kruk, J. (2019) Simultaneous calibration and inversion algorithm for multiconfiguration electromagnetic induction data acquired at multiple elevations Calibration inversion for rigid‐boom EMI. Geophysics, 84(1), EN1–EN14.
     [Google Scholar]
  47. Thiesson, J., Kessouri, P., Schamper, C. & Tabbagh, A. (2014) Calibration of frequency‐domain electromagnetic devices used in near‐surface surveying. Near Surface Geophysics, 12(4), 481–491.
     [Google Scholar]
  48. USGS . (2017) USGS measures the impacts of Hurricane Irma. U.S. Geological Survey. https://www.usgs.gov/news/usgs‐measures‐impacts‐hurricane‐irma
  49. Von Hebel, C., Rudolph, S., Mester, A., Huisman, J.A., Kumbhar, P., Vereecken, H. et al. (2014) Three‐dimensional imaging of subsurface structural patterns using quantitative large‐scale multiconfiguration electromagnetic induction data. Water Resources Research, 50(3), 2732–2748.
     [Google Scholar]
  50. Von Hebel, C., van der Kruk, J., Huisman, J.A., Mester, A., Altdorff, D., Endres, A.L. et al. (2019) Calibration, conversion, and quantitative multi‐layer inversion of multi‐coil rigid‐boom electromagnetic induction data. Sensors, 19, 4753. https://doi.org/10.3390/s19214753
     [Google Scholar]
  51. Von Hebel, C., Matveeva, M., Verweij, E., Rademske, P., Kaufmann, M.S., Brogi, C. et al. (2018) Understanding soil and plant interaction by combining ground‐based quantitative electromagnetic induction and airborne hyperspectral data. Geophysical Research Letters, 45, 7571–7579. https://doi.org/10.1029/2018GL078658
     [Google Scholar]
  52. Wait, J.R. (1959) Induction by an oscillating magnetic dipole over a two layer ground. Applied Scientific Research, Section B, 7(1), 73–80.
     [Google Scholar]
  53. Wightman, M.J. (1990) In: Kruse, S. (Ed.) Geophysical analysis and Dupuit‐Ghyben‐Herzberg modeling of freshwater lenses on Big Pine Key, Florida [M.S. Thesis]. University of South Florida.
     [Google Scholar]
  54. Wightman, M.J. (2010) Geophysical and hydrogeological study of freshwater lenses on Big Pine Key, FL. 1423. GeoView, Inc.
     [Google Scholar]
  55. Xiao, C., Ye, J., Esteves, R.M. & Rong, C. (2016) Using Spearman's correlation coefficients for exploratory data analysis on big dataset. Concurrency and Computation: Practice and Experience, 28(14), 3866–3878.
     [Google Scholar]
  56. Zarroca, M., Bach, J., Linares, R. & Pellicer, X.M. (2011) Electrical methods (VES and ERT) for identifying, mapping and monitoring different saline domains in a coastal plain region (Alt Empordà, Northern Spain). Journal of Hydrology, 409(1–2), 407–422.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1002/nsg.12244
Loading
Geophysical mapping of freshwater lens in Big Pine Key, Florida: Electromagnetic Induction Calibration and Application
Near Surface Geophysics 21, 152 (2023); https://doi.org/10.1002/nsg.12244
/content/journals/10.1002/nsg.12244
/content/journals/10.1002/nsg.12244
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): electrical resistivity; electromagnetic methods; full solution inversion; Hurricane Irma; low induction approximation

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error