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Using ground penetrating radar to investigate the water table depth in weatheredgranites — Sardon case study, Spain

M.R. Mahmoudzadeh a,⁎, A.P. Francés b, M. Lubczynski b, S. Lambot a

a Earth and Life Institute, Université catholique de Louvain, Croix du Sud 2 Box L7.05.02, B-1348 Louvain-la-Neuve, Belgiumb ITC Faculty of University of Twente, Hengelosestraat 99, PO Box 6, 7500 AA Enschede, The Netherlands

a b s t r a c ta r t i c l e i n f o

Article history:

Received 14 February 2011Accepted 24 December 2011

Available online 8 January 2012

Keywords:

Ground penetratin radar

Water table depth

Electrical resistivity tomography

GprMax2D

Precise and non-invasive measurement of groundwater depth is essential to support management of ground-

water resources. In that respect, GPR is a promising tool for high resolution, large scale characterization and

monitoring of hydrological systems. We applied GPR in a semi-arid catchment (Sardon, Salamanca, Spain) in

order to investigate the water table depth in weathered granites. We used a pulse radar with a single

200 MHz bowtie antenna combined with a differential GPS and a survey wheel for accurate positioning.

Measurements were performed following a series of transects crossing perpendicularly the bed of the Sardon

streams, which were dry during the survey period (September 2009). In order to transform the GPR data

from time to depth we estimated the soil dielectric constant using frequency domain re ectometry (FDR)

or water level depth information from several observation wells. Electrical resistivity tomography (ERT)

was applied along the GPR proles and compared to the GPR results. GPR signals were also simulated

using forward modeling (GprMax2D) of several hypothetic congurations of the subsurface. Those tech-

niques helped us to better understand and interpret the GPR data. In general, the shallow water table was

sparsely detected in the GPR proles ranging from ∼1 to ∼3 meters the entire catchment. The results showed

a good agreement of ERT and GPR proles. The comparison of measured and simulated GPR data showed

multiple reections in presence of the saturated fractured granite.

© 2012 Elsevier B.V. All rights reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2. Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.1. The study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.2. Data acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.3. Data processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.3.1. GPR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.3.2. ERT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.4. GPR simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

3. Results and interpretations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

3.1. Semi-homogenous layering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

3.2. Heterogeneity effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223.3. The effect of fractures in the saturated granite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.4. The clay effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.5. GPR data validation and uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Journal of Applied Geophysics 79 (2012) 17–26

⁎ Corresponding author. Tel.: +32 487251401; fax: +32 10473833.

E-mail address: [email protected] (M.R. Mahmoudzadeh).

0926-9851/$ – see front matter © 2012 Elsevier B.V. All rights reserved.

doi:10.1016/j.jappgeo.2011.12.009

Contents lists available at SciVerse ScienceDirect

Journal of Applied Geophysics

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / j a p p g e o

http://dx.doi.org/10.1016/j.jappgeo.2011.12.009http://dx.doi.org/10.1016/j.jappgeo.2011.12.009http://dx.doi.org/10.1016/j.jappgeo.2011.12.009mailto:[email protected]://dx.doi.org/10.1016/j.jappgeo.2011.12.009http://www.sciencedirect.com/science/journal/09269851http://www.sciencedirect.com/science/journal/09269851http://dx.doi.org/10.1016/j.jappgeo.2011.12.009mailto:[email protected]://dx.doi.org/10.1016/j.jappgeo.2011.12.009


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1. Introduction

Groundwater modeling is nowadays recognized as the best tool to

support management of groundwater resources (Lubczynski and

Gurwin, 2005). Presently, information on the depth and movement

of groundwater is collected from a limited number of often widely

spaced, piezometers and observation wells (Bentley and Trenholm,

2002; Doolittle et al., 2006) to prepare the potentiometric map

which can be used to estimate groundwater

ow direction,

owvelocities, and the location of discharge and recharge areas ( Livari

and Doolittle, 1994). These methods of data acquisition provide infor-

mation in specic, drilled boreholes where access to groundwater is

relatively easy. In that respect, ground penetrating radar (GPR) offers

promising perspectives for high resolution, continuous and large

scale characterization and monitoring of hydrological systems.

GPR has been primarily used to image the subsurface and detect

buried objects (Annan, 2002; Lambot et al., 2008; Slob et al., 2010) by

radiating electromagnetic waves into the ground and recording the

reections fromboundariesof subsurfacematerial having different elec-

tromagnetic parameters. Because of rapidratesof signal attenuation, the

penetration depth of GPR is greatly reduced in soils that have high elec-

trical conductivity (Doolittle et al., 2007). Theamount of electromagnet-

ic energy that is reected by an interface is dependent upon the

electromagnetic contrast between the two media. The reection coef -

cient of the subsurface represents the ratio between the reected and

incident elds. Abrupt boundaries that separate contrasting materials

reect more energy than gradual boundaries that separate layers with

similar electrical properties (Bano, 2006; Lambot et al., 2004).

The dielectric constant of soil materials is principally dependent

upon soil moisture but also varies to some extent with temperature,

density, and frequency. In low conductive materials, the soil moisture

is the major contributor to the soil dielectric constant (Bentley and

Trenholm, 2002; Topp et al., 1980). Nakashima et al. (2001) showed

that when there is water in a medium, like a groundwater layer,

whose dielectric constant is quite different from the non-saturated

media, it is possible to identify the medium within a multitude of

ambiguous media. In coarse-textured soils, the capillary fringe is nar-

row(Doolittle et al., 2006) which typically leads to a strong radarreec-tion.While on the contrary, inne-textured soil materials, the height of

the capillary fringe is larger than in coarse-texture materials with a

smooth transition between the dry and saturated soils. Bentley and

Trenholm (2002) showed that GPR can measure the topof the capillary

fringe and obtained an accuracy of ∼20 cm water table depth under

favorable conditions. They also investigated most of the error sources

on the estimation of the water table depth (WTD) and found that the

main sources of uncertainty are due to GPR velocity estimates and pre-

dicting the heightabove thewater table of thecapillary fringereection.

Our objectives in this research are: (1) to nd the spatial distribu-

tion of the water table depth in the granitic Sardon catchment (Spain)

with the continuous coverage along a transect, (2) to investigate the

ability of GPR to detect the reection from the underlying ssured

granite or bedrock and (3) to validate the GPR data using differentgeophysical techniques. In that respect, we used a pulse radar to col-

lect the GPR data along 37 transects, with some of them crossing per-

pendicularly the streams of the Sardon river which was dry during

the survey period. GPR simulations based on the stratigraphy of the

Sardon subsurface were performed using GprMax2D (Giannopoulos,

2005) to provide some insights for better interpreting the radar im-

ages. Electrical resistivity tomography (ERT) was used along several

GPR transects at the same period to investigate the water table and

the bedrocks. Soil sampling in the shallow surface was performed

throughout the study area at the same period to give us information

regarding the soil physical properties. The water level depth of the

existent wells was used to verify the GPR results and calibrate the

time-depth relation in the relevant GPR proles. In order to estimate

the shallow soil electrical properties, we used frequency domain

reectometry (FDR) for the proles when the exact WTD information

from the observation wells was not available.

2. Materials and methods

2.1. The study area

The Sardon catchment study site is located in the central-western

part of Iberian Peninsula in Spain (Fig. 1). The size of the catchment is∼80 km2 characterized by well dened boundaries. It has low human

impact because of low human population. The study area has a fault

line along the main stream of Sardon river and typical fractured gran-

ite rocks with standard hard rock hydrology (Lubczynski and Gurwin,

2005).

The climate in Sardon is semi-arid and it is typical for the central

part of the Iberian Peninsula. The 23-year mean rainfall, estimated

on the base of 6 Spanish Meteorological Institute rain gauges located

in the surroundings of the study area was ∼500 mm/year. The warm-

est and the most dry months in this catchment are July and August

when the average temperature is ∼22°C and rainfall is less than

20 mm/month (Lubczynski and Gurwin, 2005). Sardon river is dry

from mid-June to mid-October and in the rest of the year performs

a role of a drain, specially for direct runoff. The land cover in Sardon

is characterized by natural woody-shrub vegetation.

Granite compositions of the rocks inuence on the geology and

hydrogeology in the study area. The hydrology of Sardon is strongly

inuenced by weathering and fracturingprocess. We can generally rec-

ognize three hydrogeological layers in Sardon catchment. The top layer

is not consolidated and consists of weathered and alluvial deposits with

a thickness on average of 0-5 m up to 10 m ( Lubczynski and Gurwin,

2005). The soil texture of this layer is coarse which includes 52–90%

sand, 7–26% silt, and 4–22% clay obtained by soil sampling. Calculating

the transition zone and capillary fringe for this type of soil led to

∼10 cm thickness which is negligible compared to our used GPR signal

wavelength. The second layer is fractured granite with intercalations of

granodiorites, schists, gneises and quartzites that straggly outcrops in

the study area (Lubczynski and Gurwin, 2005). The thickness of this

layer varies between ∼60 m in the central part of the catchment to afew meters in the upland areas (Lubczynski and Gurwin, 2005). Last

layer is massive granite with some gneiss inclusions that has formed

impermeable rockbasement. This layer is deepest in thecenter of catch-

ment and near the Sardon boundaries is shallowest and can outcrop lo-

cally (Fig. 2). The groundwater table as typical for granitic areas is

shallow and mostly occurs in unconsolidated rocks.

2.2. Data acquisition

We used a time-domain GPR system (model SIR-20, Geophysical

Survey Systems, Inc., GSSI, Salem, Massachusetts, USA) combined with

a transmitting and receiving 200 MHz shielded bowtie antenna as an

impulse radar and a survey wheel for positioning. The used congura-

tion type for our survey provided 512 samples/scan and each sampleincluded 16 bits to record. GPR produces a Ricker-type pulse with fre-

quency bandwidth of 50–600 MHz. Gain functions were applied to

highlight subsurface reections and practically the time window was

limited to 100 ns in order to get better contrasted and less noisy signals.

The reasons for choosing a 200 MHz antenna are:

1. Bano (2006) showed that the transition zone above the water

table has signicant effects on the GPR reections. The water

table reection is the reection from the top of the capillary fringe

(Bentley and Trenholm, 2002). This reection can be affected

by the transition zone, and the reection contrast decreases by

decreasing the wavelength (increasing the antenna frequency, up

to 1200 MHz). Therefore water table cannot be seen even if shal-

low for relatively high frequencies.

18 M.R. Mahmoudzadeh et al. / Journal of Applied Geophysics 79 (2012) 17 – 26


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E1

E7

E4

E5

E6

E3E2

E8

P5

P7

P6

P8

P3

P4

P2

P1

R5R4

R3

R2

R1

W2

W3

W1

W6

W5

W4

W8

W9

W7

W11

W10

731000 732000 733000 734000 735000 736000 737000 738000 739000 740000 741000 742000 743000

4 5 4 8 0 0 0

4 5 5 0 0 0 0

4 5 5 2 0 0 0

4 5 5 4 0 0 0

4 5 5 6 0 0 0

4 5 5 8 0 0 0

LEGEND:

ERT Profile

Well (Piezometer)

Explained GPR Transects in the paper

Pond

Sardon catchment boundary

Sardon Streams

Other GPR transects

Elevation (m)

715 - 740

741 - 765

766 - 790

791 - 815

816 - 840

841 - 865

Andalucia

Aragon Castilla y Leon

Galicia

Castilla-La Mancha

Cataluna

Extremadura

Asturias

Valenciana

Murcia

Navarra

Madrid

Pais Vasco

La Rioja

Cantabria

Isles Baleares

Isles Baleares

Spain

Salamanca

0 2.000 4.0001.000Meters

Fig. 1. Location of the study area (Sardon catchment, Salamanca, Spain) and the GPR pro les. The blue solid lines represent the Sardon streams which were dry during the survey

period, the green meshes show the GPR proles while the brown meshes show the GPR proles which are discussed in this paper, cream crossed and blue circles show the location

of wells and ponds, respectively, and the red arrows show the location and direction of the ERT proles. Abbreviations: R = GPR prole, E = ERT prole, W = well, and P = pond.

19M.R. Mahmoudzadeh et al. / Journal of Applied Geophysics 79 (2012) 17 – 26


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2. Harari (1996) showed that the groundwater table can be detected

easily with a judicious selection of the antenna frequency and he

observed that the lower frequency antenna (100 MHz) was more

effective for locating the groundwater table, but the higher resolu-

tion of the 500 MHz antenna was more suitable for delineating the

wetting fronts and visualizing the cross-strata.

3. Annan (1991) suggested to use the longer wavelength (lower fre-

quency) antenna for water table detection, because he pointed out

when the ratio between the thickness of the transition zone and

the wavelength exceeds 0.3, the amplitude of the reected wave

is signicantly low and the water table reection cannot be seen.

Eq. (1) describes how to choose the GPR center frequency ( f ) as a

function of the transition zone thickness (hT ) and the averaged soildielectric constant (ε r ). In this equation R illustrates the Annan's

ratio (R=0.3) (Annan, 1991) where λ and c are the GPR effective

wavelength and the speed of the light in free space, respectively.

hT λ

bR

λ ¼ c f ffiffiffiffiffiε r

p

)⇒ f b

R:c

hT ffiffiffiffiffiε r

p ð1Þ

Therefore if we assume that for the worst case the thickness of the

transition zone in Sardon catchment equals to 20 cm, the wavelength

should be larger than 67 cm (Eq. (1)). This means that assuming a soil

dielectric constant of 5 (average soil dielectric constant for theground surface in Sardon), the antenna center frequency should be

less than ∼200 MHz ( f b201.25 MHz).

The main unit combined with a differential GPS (dGPS) from Leica

(model GPS1200) was mounted on a jeep (Fig. 3(a)). In order to

reduce the undesired reections, the antenna was located relatively

far from the jeep (∼12 m). In total the 37 transects were realized

within 4 days and for each transect the coordinates were recorded

manually by dGPS in a number of points of a transect. The shortest

transect was about 14 m and the longest one was about 3 km. Eleven

monitoring wells and 7 observation ponds that were located sparsely

in the study area, helped us to measure and validate the elevation of

the water table (Figs. 3(b) and 4). The WTD in the wells was mea-

sured using a piezometer sensor (Fig. 4) and the results are summa-

rized in Table 1.

In order to measure both the dielectric constant and electrical con-

ductivity of the shallow soil, the Hydra-probe soil sensor (Stevens

Water Monitoring Systems, Inc., Beaverton, Oregon, USA), which is a

frequency domain reectometry system (FDR) applying 50 MHz elec-

tromagnetic waves (Blonquist et al., 2005), was used.

For performing the electrical resistivity proles, we used the AGI

Supersting R8 system with external switch box and 56 stainless

steel electrodes as an ERT system, using the Schlumberger congura-

tion. The electrode spacing was set between 3 and 5 m which led to

165 and 275 m prole lengths.

2.3. Data processing

2.3.1. GPRVariable range gain functions were applied to the data to strengthen

deeper reections. In particular, the automated range gain function of

the system was removed and a power gain function (typically t 2.5)

was applied. To reduce the effect of the undesired signals such as

noise and clutter, a band passfrequency lter was applied to most data-

sets, with a bandwidth of 95–300 MHz. Y-axis was also transformed to

depth insteadof travel time using Eq. (2) forallproles. In this equation,

d and t illustrate depth and 2-way travel time, respectively. It is worth

noting that for time-depth transformation we used the value of shallow

soil dielectric constant where the exact WTD information from the

observation wells was not available. Otherwise this equation was con-

versely used to estimate the averaged ε r for the proles crossing the

wells or ponds where WTD is known.

d ¼ c :t 2 ffiffiffiffiffiε r

p ð2Þ

In order to distinguish the shallow bedrock reections from the

surface reection, the simple background removal technique was

applied to the relevant GPR proles using

B′

x; t ð Þ ¼ B x; t ð Þ−1N

XN n¼1

B xn; t ð Þ ð3Þ

where B( x, t ) is the raw GPR B-scan as a function of position x and

time t and B′( x, t ) is the GPR B-scan which the average background

has been subtracted while N indicates the total number of scans in

the B-scan.

Fig. 2. Schematic of E–W cross-section of Sardon catchment based on 3-layered granite compositions ( Lubczynski and Gurwin, 2005).



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As the altitude of the soil surface provides valuable information

regarding the hydrological behavior of the catchment, the GPR pro-

les were plotted with respect to altitude as provided by the dGPS

system. In order to compare the GPR prole with the existed ERT pro-

le using the same scale in x-axis, the desired part of the prole was

focused by cropping the beginning or ending of the prole.

2.3.2. ERT Inversions were done using AGI EarthImager2D (http://www.

agiusa.com/agi2dimg.shtml). Data editing was an important issue to

lter the noisy data of the ERT dataset and to insure the most reliable

inversion. We rst graphed the contact resistance measured during

the current injection at each electrode. A contact resistance value of

over 10,000 Ω indicates unacceptable data quality. Acceptable values

are less than 5000 Ω , ideally less than 2000 Ω . We selected and

removed the electrodes with all values >10,000 Ω and proceeded

with the inversion using the robust method and with no limit in the

resistivity bounds. The robust inversion was chosen since it was

expected sharp boundaries between the unsaturated and saturated

zone and between weathered granite or soil and fresh granite. After

the rst inversion, we removed all points with mist (RMSE>50%)

and proceeded again the inversion.

The ERT images were obtained by the 2-dimensional cubic inter-

polation of the inverted proles and plotting with respect to altitude

as provided by the dGPS. In order to compare the ERT prole with

GPR prole using the same scale in x-axis, the desired part of the pro-

le was focused by cropping the beginning or ending of the prole.

2.4. GPR simulations

In order to provide valuable insights for the radar data interpreta-tion, and in particular better recognize the saturated zone reection

in the GPR images, we used GPR forward modeling by means of

GprMax2D software V 1.5 (Giannopoulos, 2005) to model the Sardon

sublayers and the GPR reections. GprMax2D applies the Finite-

Difference Time-Domain method to solve numerically Maxwell's

equations. For modeling the Sardon case study, we used the Sardon

hydrolayer properties summarized in Table 2. We considered a 4 cm

distance between the GPR antenna phase centers (source and receiv-

er)and theground surface, with a source-receiver offset of 33 cm. The

cell size of the numerical models was assigned 2×2 cm. We used a

Ricker pulse with 200 MHz center frequency as an excitation source.

The time window was limited to 100 ns as for the eld data. A

power gain function of time with a factor 2.5 was applied to better

observe the later reections compared to the surface reection.

3. Results and interpretations

3.1. Semi-homogenous layering

GPR prole R1 is located in South-East of the study area with S –N

orientation and 263 m long. Observation well (W1), digging, and sam-

pling in this region show a semi-homogenous layering with 4 different

geological layers including∼1 m sandy-loam (76%sand, 17% silt,and 7%

clay), ∼0.5?–∼1 m soil pebbles, and both unsaturated and saturated

weathered granite(Fig.4). Fig. 5(b)represents thesimulatedGPR signal

using corresponding conguration shown in Fig. 5(a) also modeling the

capillary fringe with a height of 6 cm. The observed water table reec-

tion at ∼48 ns travel time shows the highest amplitude compared to

other reections above it. Fig. 5(c) shows a part of this GPR prolewhich crosses the well W1. In order to transform the time axis to the

depth we applied Eq. (2) using the averaged dielectric constant value

of 5 obtained by means of Hydra-probe soil sensor. This GPR prole

was processed using the processing procedure explained in Section 1.

W1 is located at position 78 m of the prole which has a water level

depth of 2.10 m measured using the piezometer sensor. This water

level on the cross-plot indicates the strong reections ranging between

2 and 3 m potentially due to thelocal water table because: (1) based on

GPR simulation this reection is the strongest one after applying the

gain, (2) the water table follows the topography smoothly, and this

reection is almost horizontal in this part, and (3) the center of this

reection (negative amplitude) satises W1 water level and also

shows a good agreement of changing the pressure head around the

well which leads to rise the capillary fringe. Fig. 5(d) shows a part of ERTproleE1 with almost the sameorientationof R1(N20W)and elec-

trode spacing of 3 m. This prole shows 3 different layers which are:

(1) the resistive unsaturated zone with a resistivity of 1000 Ω m and

above which is dry and composed by alluvium material with ∼2 m

thickness(the shallowest layer after 25 m along x-axis), (2) slightly sat-

urated weathered granite with a resistivity of less than 200 Ω m, and

(3) gradual transition of saturated weathered granite to lessweathered

granite with lower water content and the resistivity between 200 and

1000 Ω m alongthe prole after 25 m (starting below∼10 m). Compar-

isonof the ERT and GPR proles shows that thewater table reection is

mixed withthe weatheredgranite reectionspecially at x> 44 m which

can lead to an uncertainty of ∼1 m in detecting the water table reec-

tion. The ERT prole also shows that in interval of 0–5 and 26–33 m

the transition zone is shallow and wide leading to less reection

Fig. 3. (a) Combined GPR and dGPS equipments used in the Sardon study. (b) The shal-

low water table is visible in a pond.


http://www.agiusa.com/agi2dimg.shtmlhttp://www.agiusa.com/agi2dimg.shtmlhttp://localhost/var/www/apps/conversion/tmp/scratch_3/image%20of%20Fig.%E0%B3%80http://www.agiusa.com/agi2dimg.shtmlhttp://www.agiusa.com/agi2dimg.shtml


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contrast in the GPR prole. The simulated and measured GPR proles

also show that the geological contact between soil and granite is less

visible due to the existence of the shallow water table.

3.2. Heterogeneity effect

Fig. 6(c) shows GPR prole R2 obtained by following R1 with E–W

orientation until 312 m in x-axis and S–N orientation from there to

the end of prole. The length of this prole is 552 m and it crosses

the hill. The hill has 8.17 m height and ∼350 m width with the left

hillside slope of ∼5.14° and right hillside slope of ∼3.09°. R2 was pro-

cessed same as R1 and it also crosses the well W1. We used the

dielectric constant value of 5 for time-depth transformation. This pro-le shows a heterogeneous section of Sardon. Fig. 6(a) illustrates the

nonhomogeneous conguration which was simulated for this area.

The modeled conguration is the same as R1 conguration by repla-

cing the homogeneous pebble layer with a nonhomogeneous one.

200 cylinders with random size between 10 and 30 cm diameter

and random location with a cave shape and limited boundary were

created to dene the nonhomogeneous pebbles layer. Also capillary

fringe was modeled with 8 cm height. Fig. 6(b) shows the B-scan

and A-scan of the simulated signal. B-scan is illustrated in depth

using a value of 5 for ε r (the dielectric constant value of the rst

layer). The water table reection is visible around 2–2.3 m depth. Al-

though the water table layer is modeled parallel to the surface, the

water table reection is not smooth because of the effect of the het-

erogeneity of pebble layer. Also this heterogeneity affects on the ring-

ings and bedrock reection, i.e., the bedrock reection is not visible in

B-scan and some ringings after water table re

ection appears.Thanks to the background removal technique, the reection in

Fig. 6(c) which is highlighted with the red dashed line shows the

weathered/fractured bedrock. Referring to the drilled well W1

(Fig. 4), it shows that the fractured granite in this region is shallow

(less than 1.5 m depth) and covered with pebbles. Also W1 shows

that the weathered-fractured bedrock is saturated with water level

of 2.10 m depth. Fig. 6(d) focuses on the 70 m of the left hillside

also showing W1 as a cross-plot. The signicant reections observed

around 2-3 m depth corresponded to the mixed saturated sublayer

and bedrock reections. The reections are not horizontal probably

due to the heterogeneity of the pebbles layer.

3.3. The effect of fractures in the saturated granite

R3 is another GPR prole which was carried out in South-West of

Sardon with W–E orientation and 418 m long. In that area, the frac-

tured granite is shallow and saturated (∼1.5 m depth). Fig. 7(c)

shows the processed prole using topography correction and back-

ground removal. This prole crosses 2 wells, namely, W2 and W3.

The well W2 which is not deep enough has 0 m WTD (not dry),

1.6 m bottom depth and 803.50 m water table elevation while W3

has 1.51 m WTD, 2.00 m bottom depth, and 802.86 m water table

elevation. The distance between those wells is 29 m with a 32 cm dif-

ference in the location elevation. The water table reection and cross-

plot of the wells are shown in the gure as well. For time-depth trans-

formation, a dielectric constant value of 6.42 was practically obtained

to t the water table reection and existent water levels in the wells

(using Eq. (2), conversely). In order to better understand the effect of

the saturated fractured granite, a relevant conguration was modeledincluding 1 m soil layer, 70 cm weathered granite layer, and saturated

fractured granite using 400 horizontal tiny fractures randomly locat-

ed in the relevant layer. Fig. 7(a,b) shows the conguration and sim-

ulated B-scan and A-scan GPR data, respectively. The result of this

simulation shows whenever the fractured granite contains water,

multiple reections may occur (Fig. 7(b)). These multiple reections

may be caused due to the formation of waveguides for the short

wavelengths. Mostly the wavelength inside the water is reduced by

a factor of nine as compared to the wavelength in the air. These mul-

tiple reections are visible along almost the entire prole. In the

position range of 230–300 m the multiple reections are more visible

and stronger probably because of the presence of the fractured gran-

ite in this zone, i.e., the bedrock is more fractured in this part.

3.4. The clay effect

Inthe south partof Sardonnear the pond P4, the GPR proleR4 was

carried out with 290 m long and NW-SE direction. Also in this area the

ERT prole E4 was carried out with 275 m long (5 m electrode spacing

for 56 electrodes) and the same direction as R4. In order to match the

GPR and ERT proles, they were cropped in x-axis for 265 m long. R4

was processed in the same way as R3 and for time-depth transforma-

tion ε r =5 was used practically. The proles cross a dry stream at

65 m in x-axis. The lowest and highest elevations are separated by

9.48 m along 120 m long which lead to an average 4.52° slope for the

uphill. The stream channel is lled with alluvium material and had a

low water content during the survey period. Fig. 8(b) shows E4 and

illustrates a high conductive area of Sardon. Soil sampling showed

(c)

(b)

(a)

Fig. 4. A well from Sardon study case that shows an example of hydrostratigraphy of a

partof Sardon including thesaturatedzone (W7well,Fig. 1). (a)dry soil(coarse–texture).

(b) dry pebbles. (c) weathered granite.

Table 1

WTD in the wells and ponds in Sardon. For the location of each one refers to Fig. 1.

I D T ype W TD (m ) Wa ter ta ble eleva tion ( m) B ot tom dept h (m)

W1 Well 2.10 794.88 7.9

W2 Well 0.00 803.50 1.6

W3 Well 1.51 802.86 2.00

W4 Well 1.94 742.13 2.75

W5 Well 3.23 739.92 Not measured

W6 Well 2.50 761.82 3.13

W7 Well 1.99 803.70 3.36

W8 Well dry Dry 1.08

W9 Well 2.58 805.69 3.65

W10 Well Dry dry 1.53

W11 Well 1.00 733.35 1.8

P1 Pond 1.61 806.39 Not measured









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that this area is covered by weathered granite with heavy clay which

leads to a resistivity of ∼25 Ω m. E4 also shows the weathered/fractured

granite at a depth of >12 m with maximum resistivity of 350Ω m. This

amount of resistivity may refer to saturation of the bedrock. The pond

P4 is close to the location of 70 m in the x-axis of the prole and had

1.34 m WTD (Table 1) which shows that the water table in this region

is relatively shallow. Because of the existence of the clay in the soil of

this region capillary fringe rise is high and leads to no sharp boundary

for distinguishing the water table as well for R4 GPR prole which is

shown in Fig. 8(a). Nevertheless, there are a few different patterns in

both ERT and GPR proles which are discussed in the following. (1) At

the beginning part of E4 a transverse boundary is visible which sepa-

rates a high conductive part (b50 Ω m) and a relatively shallower less

conductive part (>120Ω m). This transverse boundary leads to a trans-

verse reection on R4 starting at the depth of 1.35 m (the expected

depth of water table referring to P4) and ending ∼4 m depth. This pat-

tern may refer to a different soil texture. (2) A shallow vertical high con-

ductive layer is visible at x=45 m of E4 which leads to almost a strong

multiple reections in R4 at the same location and which starts at the

depth of 0.5 m. (3) Crossing the stream bed at 65 m location leads to a

Table 2

Measured hydrolayer parameters of Sardon catchment (Salamanca, Spain) considered for GPR simulations. The electromagnetic parameters were measured using Hydra-probe soil

sensor and the thicknesses were measured using drilling and ERT methods.

Layer Stratigraphy σ (mS/m) ε r Thickness (m)

Min Max Value Min Max Value Min Max Value

Unsaturated soil A 0.67 2.00 1.43 3 9 5 0.0 3.0 2.0

Saturated soil A1 10.0 100 20.0 – – 25 0.0 6.0 1.0

Unsaturated soil pebbles B 1.33 5.00 2.00 7 9 8 0.1 0.5 0.5

Saturated soil pebbles B1 13.33 200 20.0 – – 20 0.1 0.5 0.0

Unsaturated weathered-granite C 1.00 2.00 1.25 5 15 7 0.0 2.0 1.0

Saturated weathered-granite C1 2.50 5.00 4.00 – – 27 5.0 50.0 10.0

Hard-granite D 0.20 0.67 0.50 – – 4 – – 100

x (m)

GPR Tx & RxFree Space

Unsaturated Soil εr = 5 σ = 1.43 mS/m

Unsaturated Soil Pebbles εr = 8 σ = 2 mS/m

Unsaturated Weathered Granite εr=7 σ=1.25 mS/m

Capillary fringe

Saturated Weathered Granite εr = 27 σ = 4 mS/m

0 1 2 3 4 5 6 7 8 9

2.5

2

1

0

x (m)

D e p t h ( m )

E z (V/m) × t (ns)

4 5

0

1

2

3

4

5

5

5

0

0.5

1

x 105

0 2

x 105

0

10

20

30

40

50

60

70

80

90

100

E z (V/m) × t (ns)

t

( n s )

Surface reflection →

Pebbles reflection →

Bedrock reflection →

Water table reflection

2nd order Pebble ringing→

2nd order Granite ringing→

2nd order WT ringing→

Position (m)

D e p t h ( m )

Well (W1)↓

Water level

Shallow and wide water table transition zones

10 20 30 40 50 60 70 80 90

0

1

2

3

4

5

Position (m)

D e p t h ( m )

ρ (Ω.m)

Resistive unsaturated zone

Saturated weathered granite

WT transition zone

Shallow and wide water table transition zones

Gradual transition zone between weathered and unweathered granite

0 10 20 30 40 50 60 70 80 90

0

24

6

8

10

12

14

16

18

200 1000 1500 2000 2500

(a) (b)

(c) (d)

D e p t h ( m )

Fig. 5. GPR and ERT proles (R1 and E1) are located at South-East of Sardon with S–N orientation crossing the well W1 (2.10 m of water level depth). (a) The used conguration for

GprMax2D, (b) gained simulated signal, (c) the cropped and processed GPR pro le R1 using a dielectric constant equals to 5 inferred from a FDR measurement performed at ∼80 m

along the prole, and (d) The cropped and processed ERT prole E1.



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different pattern in E4 because of soil textural difference in stream bed

compared to the adjacent areas. Thanks to less clay content of this part,

the water table reection is sharp and visible at the depth of 1.35 m on

R4prole. Weusedthisreection and P4 WTDto estimate the averaged

soil dielectric constant (ε r =5). (4) A high conductive soil exists at the

locationaround 190 m(resistivity is less than 10Ω m) which is relative-

ly close to the surface (E4, Fig. 8(b)). R4 shows a shallow and sharp re-

ection at this location which is stronger than adjacent reections. (5)

Atthe end ofERT pro

le after the location of 245 m an abruptchangingon the soil texture appears (resistivity higher than 200Ω m). This

changing of the soil texture leads to less capillary rise because of less

clay content. A reection at 1.35 m depth is visible on R4 of this part

which is horizontal and may be attributed to the water table, as com-

pared to the water table reection at x= 70 m. The reection around

3 m depth up to bottom along almost the entire prole may be caused

by the water table ringing and high attenuation of GPR signals. These

proles show that clay content strongly affects the detection of the

water table.

3.5. GPR data validation and uncertainties

We represented the topography correction in the GPR data pro-

cessing section and we used it for all the GPR proles. However, thelength of the GPR proles are too long leading to sweep a number

of different soil types and layering in each prole and therefore mak-

ing it dif cult to elucidate the local horizontal reections. Also due to

the lateral variability in the soil types, the time-depth transformation

of the GPR data is critical once using a unique dielectric constant for

an entire prole. In that respect we decided to sweep a short transect

containing the known WTDand with a gradient in the altitude. Fig. 9(b)

shows the GPR prole R5 (located in the east-south of the study area

with 21 m long) that we obtained close to the pond P5 to evaluate the

water table reection in the GPR data. The Hydra-probe was used in 3

points along the prole to collect the electromagnetic properties of

the shallow soil and showed a spacial surface dielectric constant vari-

ability of 3–24. The processed GPR prole by meansof only topography

correction and background removal is shown in the gure. The dielec-tric constant value of 3.1 (from the surface of the highest part of prole

obtained by FDR) was used for time-depth transformation. The contin-

uous and almost horizontal reection belonging to the water table is

clear along the entire prole. Close to the pond because of changing in

the pressure head, the top of the capillary fringe rises and leads to a

water table reection gradient in the prole as shown in the 0–7 m of

x-axis. In order to evaluate the depth accuracy of the detected reection

andnd the total uncertainty of WTD detection comingfrom FDR, dGPS

and time-depth transformation method we used 2 points along the

prole. The points are located at 9 and 17 m along the prole having

the dielectric constant values of 11.5 and 3.1 (obtained by FDR) and

the surface elevation values of 792.6 and 793.8 m (obtained by dGPS),

respectively. The respective water table reection times in the unpro-

cessed GPR pro

le (the raw GPR pro

le is not presented) are 20 and25 ns, and the calculated WTD for those points are 0.88 and 2.12 m,

respectively. Assuming that the water table is horizontal, the difference

ofthe WTD (∼d) for those pointsshould show the differenceof the sur-

face elevation (∼Z) between them. Referring to the calculated WTD

values leads to ∼d =1.24 m while the surface elevation values result

x (m)

D e p t h (

m )

GPR Tx & Rx

Free Space


Pebbles εr = 9 σ = 2 mS/m

Unsaturated Weathered Granite εr=7 σ=1.25 mS/m

Capillary fringe

Saturated Weathered Granite εr = 27 σ = 4 mS/m

0 1 2 3 4 5 6 7 8 93

2

1.5

0

Surface reflection

Pebbles reflection

WT reflection

x (m)

D e p t h ( m )

2 4 6 8

0

1

2

3

4

5

0 1

x 105

0

10

20

30

40

50

60

70

80

90

100

E z(V/m) t (ns)

t

( n s )


Pebbles reflection →


WT reflection→

Position (m)

D e p t h ( m )

Well (W1)

0 50 100 150 200 250 300 350 400 450 500

0

1

2

3

4

5

Watertable

Watertable

BedrockE S

(a)

(b)

(c)

(d)

Position (m)

D e p t h ( m )

← Well(W1)

← Water level

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

0

1

2

3

4

5

W N

Fig. 6. GPR prole (R2, 552 m long) is located at South-East of Sardon along a E –W

orientation until middle and S–N orientation from middle to the end crossing W1

well (2.10 m water level depth). (a) The used conguration for GprMax2D, (b) Gained

simulated signal, (c) The GPR prole R2 (focusing on the bedrock reection) processed

using a dielectric constant equals to 5 inferred from a FDR measurement performed at

∼25 m along the prole, (d) The 70 m cropped and processed R2 focused on water

table reection around the W1 well.



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∼Z=1.2 m. Therefore the resulting error is 4 cm, which is negligible

due to the observational and systematic errors. It is worth noting that

time-depth transformation may lead to a signicant error of WTD. The

processed GPR prole used the lowest value of ε r (3.1) for time-depth

transformation. Referring to the point which is located at x= 9 m

shows a WTD of 1.57 m while the expected WTD is 0.88 m and there-

fore results to a relative error of 57% for WTD.

4. Conclusions

This study emphasizes on non-invasive and large scale hydrogeo-

logical characterization and monitoring techniques in order to inves-

tigate the WTD in weathered granites. In that respect, GPR was

applied in a semi-arid catchment (Sardon) in 37 transects with atotal length of ∼23 km. In this research we found: (1) the shallow

water table returns a strong reection signal in the GPR images,

(2) the geological contact between soil and granite is less visible in

the GPR proles in existence of shallow water table, (3) the water

table reection is almost smooth and it follows quite well the topog-

raphy but can be affected by the heterogeneity of the layering above

it, (4) multiple reections are expected to happen in presence of sat-

urated fractured granite due to the creation of visible random wave-

guides for the radar, (5) clay presence in the soil affects the water

table reections and makes them nonvisible because of high capillar-

ity and signal attenuation, (6) time-depth transformation using a

single dielectric constant value may lead to a signicant error of

WTD, and (7) the Sardon water table type is local and it is sparsely

distributed in the entire catchment by depth ranging between ∼1 to∼3 m. It is worth noting that the common-mid-point (CMP) method

of GPR data acquisition would have improved the estimates of the

soil dielectric constant where the strong lateral variability in soil

dielectric constant does not exist. In the future, research will focus

on the full-waveform inversion of the radar data for a more accurate

layer reconstruction and interpretation.

Acknowledgment

This research wassupportedby the Universitécatholique de Louvain

(UCL, Belgium), and International Institute for Geo-Information Science

and Earth Observation (ITC, the Netherlands), and DIGISOIL projectnanced by the European Commission under the 7th Framework

Programme for Research and Technological Development. We greatly

x (m)

D e p t h ( m )

GPR Tx & Rx

Free Space


Weathered Granite εr = 15 σ = 2 mS/m

Saturated fractured Granite εr = 27 σ = 4 mS/m

0 1 2 3 4 5 6 7 8 93

1.7

1

0

x (m)

D e p t h ( m )

Surface reflection

Bedrock reflection

WT reflection

2 4 6 8

0

1

2

3

4

50 1

x 105

0

10

20

30

40

50

60

70

80

90

E z (V/m) × t (ns)



WT reflection →

t

( n s )

Position (m)

D e p t h ( m )

Well (W2)Well (W3)

0 50 100 150 200 250 300 350 400

0

1

2

3

4

5

Bedrockreflection

Water table reflection

(a)

(b)

(c)

Fig. 7. GPR prole with 418 m long (R3) from West to East located in South-West of

Sardon crossing 2 wells and s aturated fractured granite zone. (a) The used conguration

for GprMax2D, (b) Gained simulated signal, (c) The processed GPR prole R3 using a

dielectric constant equals to 6.42 inferred manually by tting the WTD of the wells (W2

and W3) and the strong continuous reection at ∼23 ns.

Position (m)

D e p t h ( m )

0 20 40 60 80 100 120 140 160 180 200 220 240 260

0

1

2

34

Transversereflection

Verticallayering

Sharp surfacereflection

WT

WT

Different soilstructure

NW SE

Crossing dry stream

Position (m)

D e p t h ( m )

( .m)

0 20 40 60 80 100 120 140 160 180 200 220 240 260

0510152025

0 50 100 150 200 250 300 340

Transverseconductive

layer

Verticalconductive

layer

Low conductivesoil

Saturatedweathered/fractured

granite

Crossing dry stream

High conductivesoil

(a)

(b)

Fig.8. GPR andERTproles(R4andE4) are locatedat southpartof Sardonin a conductive

area with heavy clay content and along a NW-SE (N250W) orientation with about 275 m

long for ERT and 290 m long for GPR prole. (a) The cropped and processed GPR prole

using a dielectric constant equals to 5 inferred manually by tting the WTD of the pond

P4 and the local horizontal reection at ∼19 ns located at ∼255 m along the prole (this

prole crosses the stream at ∼65 m in x-axis), (b) The cropped ERT prole.



10/10

acknowledge their support. Also we thank Mr. A.A. Mohammed from

ITC for his help during the eld campaign.

References

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Lubczynski, M.W., Gurwin, J., 2005. Integration of various data sources for transientgroundwater modeling with spatio-temporally variable uxes — Sardon studycase, Spain. Journal of Hydrology 306 (1–4), 71–96.

Nakashima, Y., Zhou, H., Sato, M., 2001. Estimation of groundwater level by GPR in anarea with multiple ambiguous reections. Journal of Applied Geophysics 47,241–249.

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Topp, G.C., Davis, J.L., Annan, A.P., 1980. Electromagnetic determination of soil –watercontent — measurements in coaxial transmission-lines. Water Resources Research16 (3), 574–582.

Fig. 9. GPR prole R5 with 21 m long carried out in east-south of the Sardon for validating the GPR data using FDR and dGPS, starting close to the pond P5. (a) Photograph, (b) The

processed GPR prole using a dielectric constant equals to 3.1 inferred from a FDR measurement performed at 17 m along the pro le (this prole starts close to the water and ends

ontheatland).The values of ε r shown in thegurewereinferred from FDRin theindicatedlocationsand dFDRindicates thecalculatedvalueof WTDusingthe water table reection travel

time obtained from GPR (t GPR) and the relevant ε r while depth indicates the WTD calculated using the unique ε r measured at 17 m along the prole.

http://dx.doi.org/10.1029/2003WR002641http://dx.doi.org/10.2136/vzj2007.0180http://dx.doi.org/10.2136/vzj2007.0180http://dx.doi.org/10.1029/2003WR002641

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