Vertical radar profiling for the assessment of landfill capping effectiveness

In this paper we present the results of the characterization of a large landfill cap by means of ground-penetrating radar (GPR) measurements. The GPR data were collected in boreholes, using a vertical radar profile (VRP) configuration, where one antenna was kept at the ground surface while the other was progressively lowered into the borehole. This yields a vertical profile of GPR velocity from which a moisture content profile can be obtained. VRPs were conducted in 15 boreholes available on-site, all having been drilled through the protective cap and the waste mass into the underlying native soil. The separation between the boreholes (many tens of metres) makes it infeasible to characterize the site via other forms of hole-to-hole GPR measurements, with the exception of a few pairs of holes drilled at the periphery of the waste mass and therefore of limited usefulness. The VRP data allowed for the characterization of the moisture content profile across the waste body down to the water table, very close to the natural land surface, providing evidence that the waste is generally fairly dry (moisture content less than 10% on average). In order to assess the effectiveness of the cap, two surveys where conducted in March and April 2005 using all the boreholes with the aim of identifying moisture content changes due to natural rainfall and especially artificial irrigation over a limited area surrounding one of the boreholes. The time-lapse VRP results show that in the irrigated area a measurable amount of water seeps through the cap and changes the waste moisture content. Elsewhere, we basically observed no changes in moisture content due to natural infiltration during the same period: this fact does not confirm or exclude that some degree of leakage can occur. Direct in-situ permeability measurements, albeit more localized than VRP data, confirm that the landfill cap is not totally impermeable, thus corroborating the results derived from geophysical measurements.

[1]  Mats Svensson,et al.  Dense resistivity and induced polarization profiling for a landfill restoration project at Härlöv, Southern Sweden , 2007, Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA.

[2]  W. Daily,et al.  The effects of noise on Occam's inversion of resistivity tomography data , 1996 .

[3]  Dale F. Rucker,et al.  Correcting Water Content Measurement Errors Associated with Critically Refracted First Arrivals on Zero Offset Profiling Borehole Ground Penetrating Radar Profiles , 2004 .

[4]  A. P. Annan,et al.  Measuring Soil Water Content with Ground Penetrating Radar: A Review , 2003 .

[5]  A. Binley,et al.  Vadose zone flow model parameterisation using cross-borehole radar and resistivity imaging , 2001 .

[6]  Tamaz Chelidze,et al.  Electrical spectroscopy of porous rocks: a review—I. Theoretical models , 1999 .

[7]  David L. Alumbaugh,et al.  Estimating moisture contents in the vadose zone using cross‐borehole ground penetrating radar: A study of accuracy and repeatability , 2002 .

[8]  H. Vereecken,et al.  Imaging and characterisation of subsurface solute transport using electrical resistivity tomography (ERT) and equivalent transport models , 2002 .

[9]  A. Peter Annan,et al.  The Early Development of TDR for Soil Measurements , 2003 .

[10]  A. Binley,et al.  Examination of Solute Transport in an Undisturbed Soil Column Using Electrical Resistance Tomography , 1996 .

[11]  Roger Guérin,et al.  Review of state of the art methods for measuring water in landfills. , 2007, Waste management.

[12]  Jens Tronicke,et al.  Vertical Radar Profiling: Influence of Survey Geometry on First-Arrival Traveltimes and Amplitudes , 2005 .

[13]  David L. Alumbaugh,et al.  Cross‐borehole ground‐penetrating radar for monitoring and imaging solute transport within the vadose zone , 2006 .

[14]  Andrew Binley,et al.  Applying petrophysical models to radar travel time and electrical resistivity tomograms: Resolution‐dependent limitations , 2005 .

[15]  Michael D. Knoll,et al.  Multivariate analysis of cross‐hole georadar velocity and attenuation tomograms for aquifer zonation , 2004 .

[16]  G. C. Topp,et al.  A REEXAMINATION OF THE CONSTANT HEAD WELL PERMEAMETER METHOD FOR MEASURING SATURATED HYDRAULIC CONDUCTIVITY ABOVE THE WATER TABLE1 , 1983 .

[17]  Filippos Vallianatos,et al.  Investigation of waste disposal areas using electrical methods: a case study from Chania, Crete, Greece , 2007 .

[18]  Motoyuki Sato,et al.  Application of vertical radar profiling technique to Sendai Castle , 2000 .

[19]  Alberto Villa,et al.  An experiment of non‐invasive characterization of the vadose zone via water injection and cross‐hole time‐lapse geophysical monitoring , 2007 .

[20]  F. Day‐Lewis,et al.  Assessing the resolution‐dependent utility of tomograms for geostatistics , 2004 .

[21]  Andrew Binley,et al.  Modeling unsaturated flow in a layered formation under quasi-steady state conditions using geophysical data constraints , 2005 .

[22]  Jeffrey W. Roberts,et al.  Estimation of permeable pathways and water content using tomographic radar data , 1997 .

[23]  R. Schulin,et al.  Calibration of time domain reflectometry for water content measurement using a composite dielectric approach , 1990 .

[24]  Frederick D. Day-Lewis,et al.  Time‐lapse imaging of saline‐tracer transport in fractured rock using difference‐attenuation radar tomography , 2003 .

[25]  S. Swift,et al.  Smooth inversion of VSP traveltime data , 1999 .

[26]  Michael D. Knoll,et al.  Traveltime inversion of vertical radar profiles , 2006 .

[27]  A. Binley,et al.  DC Resistivity and Induced Polarization Methods , 2005 .

[28]  Per Christian Hansen,et al.  Analysis of Discrete Ill-Posed Problems by Means of the L-Curve , 1992, SIAM Rev..

[29]  C. Aran,et al.  Leachate recirculation: moisture content assessment by means of a geophysical technique. , 2004, Waste management.

[30]  Numerical verification and extension of an analytic generalized inverse for common-depth-point and vertical-seismic-profile traveltime equations , 1988 .

[31]  R. Parker,et al.  Occam's inversion; a practical algorithm for generating smooth models from electromagnetic sounding data , 1987 .

[32]  Frederick D. Day-Lewis,et al.  Time‐lapse inversion of crosswell radar data , 2002 .

[33]  Giorgio Cassiani,et al.  Multilayer ground-penetrating radar guided waves in shallow soil layers for estimating soil water content , 2007 .

[34]  Keith Beven,et al.  Vadose Zone Flow Model Uncertainty as Conditioned on Geophysical Data , 2003, Ground water.

[35]  Brian J. Mailloux,et al.  Hydrogeological characterization of the south oyster bacterial transport site using geophysical data , 2001 .

[36]  Michael D. Knoll,et al.  VSP traveltime inversion: Near‐surface issues , 2004 .

[37]  R. Knight,et al.  Effect of antennas on velocity estimates obtained from crosshole GPR data , 2005 .

[38]  A. P. Annan,et al.  Electromagnetic determination of soil water content: Measurements in coaxial transmission lines , 1980 .

[39]  D. Alumbaugh,et al.  The application of ground penetrating radar attenuation tomography in a vadose zone infiltration experiment. , 2004, Journal of contaminant hydrology.

[40]  Johan Alexander Huisman,et al.  Measuring soil water content with ground penetrating radar , 2003 .

[41]  C. Strobbia,et al.  Vertical Radar Profiles for the Characterization of Deep Vadose Zones , 2004 .

[42]  Rosemary Knight,et al.  Determining water content and saturation from dielectric measurements in layered materials , 1999 .

[43]  J. J. Peterson Pre-inversion Corrections and Analysis of Radar Tomographic Data , 2001 .

[44]  H. Kim,et al.  Inequality constraint in least-squares inversion of geophysical data , 1999 .