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When reviewing problems associated with industrial anddomestic waste buried in landfills worldwide, it seemsincongruous to even consider Switzerland with its famousmountain pastures and beautiful valleys. Yet within thistiny country are an estimated 40 000 small landfills, morethan one per km2 of inhabitable land. Although most areexpected to be harmless, Swiss government scientists havesuggested that approximately 8000 will require continu-ous monitoring and that about 500 of the most dangeroussites will require major remedial work at a total cost inexcess of $1.5 billion.

Many landfills in Switzerland and elsewhere are inclay- and sand-rich sediments of Quaternary age. Conse-quently, common features in the associated regional geo-

logic and hydrologic systems are expected. To develop a

cost-effective strategy for noninvasive investigations ofsmall garbage dumps, we evaluate here the informationcontent of various high-resolution geophysical data setscollected at a typical Swiss landfill. By employing severalgeophysical methods we:

determine the location, size, and geometry of individ-ual waste pits

estimate the nature of their contents and outline the different lithologies and structures of the

host sediments

With a thorough understanding of the possibilities and lim-itations of geophysical methods employed at this site, it

should be possible to modify our surveying strategy forapplication in other landfill investigations.

Stetten Test Site. The focus of our attention has been a land-fill near the village of Stetten in northern Switzerland(Figure 1). Erosion and sedimentation during and subse-quent to two major periods of glaciation formed the near-surface geology of this region. Deposited successively ona basement of consolidated Molasse sediments is a lowerlacustrine sequence of clay, a thick till unit, and an upperlacustrine sequence of fine clayey sand. The upper lacus-trine sequence is intersected by lenses and channels ofgravel and sand. Groundwater flows in a northwesterlydirection toward a nearby river and the depth to thegroundwater table varies seasonally between 3 and 5 m.

During the 1950s and 1960s, gravel from many near-surface lenses and channels was excavated for construc-tion projects. Between 1963 and 1973, the abandoned gravelpits proved convenient locations in which to dump indus-trial and household waste. The industrial refuse includednumerous steel drums containing chemical and oilresidues, metallic objects, paper, plastic, and textile fibersdistributed more or less randomly and partly burned(Figure 2). Upon closing the landfill, the waste was cov-ered with approximately 0.8 m of soil and the area recul-tivated. At the beginning of our investigation, reports andaerial photographs allowed us to delineate the approxi-mate extent of quarrying and landfill activities (shadedregion in Figure 1).

Lateral boundaries of waste pits and their contents. Todelineate the lateral boundaries of the composite landfill,densely sampled electromagnetic and vertical-gradientmagnetic data were collected using an EM-31 system andtwo optically pumped cesium-vapor magnetometers(Figures 3b and 3c). Operation of the EM-31 system is

based on the low induction number approximation, suchthat readings are only valid for apparent conductivities

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induction numbers. The resultant half-space conductivi-ties and susceptibilities represented average values forthe top 3-6 m of the shallow subsurface.

Most undisturbed natural sediments surrounding thelandfill have low to medium electrical conductivities (4-20 mS/m; Figure 4a), magnetic susceptibilities (0.003-0.004SI units; Figure 4b), and magnetic vertical gradients (10-+10 nT/m; Figure 4c). Conspicuous increases in all phys-ical properties occur across the landfill. Coincident anduniformly high conductivities (20-250 mS/m), suscepti-

bilities (>0.004 SI units), and magnetic vertical gradients(mostly 200 to 200 nT/m with values as high as 2000nT/m) outline two large regions that we interpret as two

distinct waste pits, W1 and W2. The high spatial samplingdensity of the new geophysical data allows the irregular

boundaries of the two waste pits to be delineated with an

0000 T HE LEADING EDGE FEBRUARY 1999 FEBRUARY 19 99 T HE LEADING EDGE 249

Figure 3. (a) Stetten Test Site within Switzerland. (b-f) Regions surveyed by different geophysical methods. (b) EM-31. (c) Magnetic. (d) Georadar. (e) Refraction seismic. (f) Reflection seismic. Heavy lines delineate profiles andshading outlines regions covered by areal surveys. Arrows in (d) locate georadar lines displayed in Figure 5.

a) b) c)

d) e) f)

Figure 4. (a) EM-31 conductivity data (grid cell: 1 x 2 m) obtained from joint inversions of quadrature and in-phasemeasurements made in vertical and horizontal modes. Conductivities (20 mS/m are due to waste material (W1 andW2) and fine sediments (W3 and W4). Conductivities 0.004 SI units indicate presence of metallic objects. (c)Vertical-gradient magnetic data (grid cell: 0.5 1 m). Undisturbed natural ground with gradients in range 10 nT/mare separated sharply from landfill with gradients mostly in range of 200 nT/m. Values 200 nT/m and 200 nT/mare represented by reds and blues, respectively. Vertical and horizontal axes are in meters.

a)

b) c)

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accuracy of 2-4 m (Figure 1). Waste pit W2 exhibits muchlarger geophysical anomalies than W1, suggesting thatmost of the industrial refuse (e.g., the steel containers) was

buried in the western part of the former excavation areaand that household garbage was largely dumped in theeastern part. The waste pits are separated by a well-definedquiet zone characterized by conductivities, susceptibilities,and vertical gradients comparable to those of the sur-rounding natural sediments. This 20-40 m wide zone prob-ably represents undisturbed ground not excavated due tolack of sufficiently high-quality gravel.

High-amplitude linear anomalies on all three physicalproperty maps define the location of a steel guard rail (R)lying on the surface. By comparison, the effects of a buried

copper telephone cable (T) are only observed on the EM-31 maps. Note that the apparent susceptibility anomalyacross the copper telephone cable is an artifact associatedwith the overly simplistic half-space model employed inour inversion process.

To supplement the electromagnetic and magnetic data,we recorded a three-dimensional (3-D) georadar data setacross the western boundary of waste pit W2 (Figure 3d).A noticeable reduction in georadar signal penetrationoccurred in crossing from undisturbed natural ground toland underlain by waste. Limited depth penetration (e.g.,Figure 5c), which correlates with conductive anomalies(Figure 4a), was caused by attenuation within the soil layercapping the landfill and within the waste itself. Only thetop 60 ns (approximately 1.7 m depth) of georadar in-line

section 86.8 m contained useful information. This sectioncrossed a portion of the waste pit characterized by EM-31conductivities >30 mS/m. The inhomogeneous characterof the near-surface waste resulted in a chaotic pattern ofoverlapping and interfering diffraction hyperbolas on geo-radar profiles and time slices (e.g., Figures 5 and 6).Although it was difficult to determine the exact nature ofindividual features within the waste, diffractions wereobserved to within ~0.8 m of the surface, suggesting thatmetallic objects immediately underlie the capping soil layer.

The irregular outer boundaries of the two waste pitsand the intervening zone of undisturbed ground wereequally well delineated by the electrical conductivity, mag-

netic susceptibility, and vertical-gradient magnetic maps.Although not covering as large an area, the georadar datarevealed essentially the same boundary locations. Fromthese data sets, the surface areas of the waste pits were esti-mated to be ~11,300 m2 and ~10,600 m2.

Lower boundaries of the waste pits. The depth extent ofthe composite landfill proved difficult to determine withconventional engineering-scale geophysical methods.Potential-field techniques cannot provide unique and accu-rate depth estimates, and attenuation due to the high elec-trical conductivities within the waste pits precludedlocating their lower boundaries with resistive-limited elec-tromagnetic methods and georadar techniques. Guided

and surface waves in seismic reflection data recordedacross the landfill effectively masked reflections shallowerthan ~50 m. As an alternative, we recorded seven high-


Figure 6. Time slice extracted from 3-D migrated geo-radar volume at 56 ns. Superimposed lines indicateboundary of waste based on magnetic and electromag-netic data and outline of gravel lens based on electro-magnetic data. Arrows locate georadar lines displayedin Figure 5.

Figure 5. Three parallel lines extracted from 3-D migrated georadar data volume (grid cell: 0.35 x 0.35 m). Antennacenter frequency: 100 MHz. (a) Line outside landfill, over gravel lens; quasi-continuous reflections observed fromsurface to 140 ns. X marks 24-m borehole. (b) Line outside landfill over lacustrine sediments; quasi-continuousreflections visible to 100 ns. (c) Line completely within landfill; very limited depth penetration over conductive

waste. Vertical:horizontal exaggeration = 10:1.

a) b) c)


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resolution seismic refraction profiles (q1-q4 and I1-I3 inFigure 3e) across the landfill and neighboring undisturbedland. To map reliably the small-scale heterogeneities of theunderground, we developed and applied a novel and flex-ible tomographic inversion scheme.

Figure 7 shows velocity tomograms obtained from inver-sions of traveltime data recorded along profile q1 (outsidethe landfill) and profile q2 (inside the landfill). Boundariesof waste pit W2 determined from electromagnetic and mag-netic data are indicated by the gray shading. There are goodcorrelations between the tomographic images at all profilecrossover points (I1-I3 in Figure 7). Velocities of near-surfacesediments are 400-800 m/s and those of deeper sedimentsare >1500 m/s. A sharp velocity gradient is recognized nearthe 1000 m/s isovelocity contour line. According to limited

borehole data and electrical resistivity soundings, this high-velocity gradient corresponds to the vadose zone, separat-ing mostly dry sediments above (blues in the velocitytomograms) from water-saturated sediments below (red-

browns). Amarked thickening of the near-surface low-veloc-ity layer to a maximum depth of ~11 m indicates the presenceof waste pit W2. Several regions of the two waste pits arecharacterized by low velocities that extend to depths of only5-6 m. They are indistinguishable from the natural sedi-

ments. Consequently, the velocity tomograms cannot beused to determine the lateral boundaries of the shallow partsof the waste pits.

From the velocity tomograms, the maximum depthextents of W2 and W1 are determined to be ~11 m and ~8m, respectively. Together with the surface area informationobtained from the electromagnetic and magnetic data, weestimate the maximum combined volume of the two wastepits to be ~175,000 m3.

Near-surface sediments. Initially, borehole data and elec-trical resistivity soundings helped define the broad-scaledistribution of near-surface sedimentary units. Moredetailed knowledge on the electrical structure of the top3-6 m of sediments was then extracted from the EM-31 mea-surements (Figure 4a). Electrical conductivities of the dom-inant fine clayey sands are in the range of 8-20 mS/m. Areasunderlain by higher proportions of clean gravel/sand haveelectrical conductivities 1500 m/s are rep-resented by browny reds. Gray shading outlinesboundaries of waste pit W2 crossed by profile q2.Waste pit boundaries are based on electromagnetic andmagnetic data. Crossing points of perpendicularrefraction profiles are identified by I1-I3. Vertical:hori-zontal exaggeration = 2:1. Vertical axis is in meters.

a)

b)

I1 I2 I3

I1 I2 I3


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reflection character. Reflections below this level are morediscontinuous, and reflection strengths are much weakerthan those above. We interpret the 200-ms reflection as orig-inating from the boundary between unconsolidated lacus-trine sediments and the underlying basement.

Integration of the data sets. Combining information fromthe borehole, electric resistivity (not shown here), electro-

magnetic, magnetic, seismic refraction, georadar, and seis-mic reflection data sets results in a consistent picture ofthe landfill and surrounding sediments. Figure 9 showsthe different data sets recorded along profile q2. The bound-aries of the waste site are well delineated on the electricalconductivity, magnetic susceptibility, and vertical-gradi-ent magnetic profiles. Two parts of waste pit W2 can bedistinguished: a broad zone between 0 and 120 m and anarrow one between 164 and 179 m. The anomaly inFigures 9a and 9b at around 185 m (R) results from the steelguard rail. It was moved after the electromagnetic surveyto a new position at 177 m in Figure 9c.

A broad electrical conductivity feature with superim-posed high-frequency anomalies represents the combinedeffect of the soil layer capping the waste pit and a large

composite mass of highly conducting waste material withinthe pit (e.g., steel containers, other metal objects, and/orwater with high ion concentration). More discrete anom-alies displayed in the magnetic susceptibility, and verti-cal-gradient magnetic profiles probably represent clustersof steel containers. Magnetic susceptibilities derived fromthe electromagnetic data represent the effects of inducedmagnetization to a depth of 3-6 m, whereas the vertical-gradient magnetic data are the result of induced and rema-nent magnetization to below the depth of bedrock.

The northwestern part of waste pit W2 is characterizedby a thick low-velocity zone extending to a depth of ~11


sediment very shallow lateral classification

bedrock at structure ground- sediment boundaries thickness of of waste

200 m 50-200 m water table structure of water waste site contents

reflection seismic

refraction seismic

georadarDC resistivity

magnetic

EM-31

decreas

ing

cost

Figure 10. Sketch of subsurface beneath Stetten TestSite based on all available data. (a) Viewed fromabove. (b) Viewed from below. Red = waste pits;orange = gravel lenses. Undulating blue (above) andgreen (below) surfaces = interpolated base of near-surface low-velocity layer. Irregular-shaped features =extrapolated details from neighboring region,intended to depict regions of high reflected energyreturn (see caption to Figure 8). Pink = extrapolatedtop of lower lacustrine sequence. Brown = extrapo-lated basement surface.

Table 1. Qualitative comparison of information content of different geophysical data sets.

No informationExcellent information

*More costly items are listed near the top of the table.

mete

r


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