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Characterization of recharge through complex vadose zone of a granitic aquifer by time-lapse electrical resistivity tomography
Journal of Applied Geophysics 73 (2011) 35–44
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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 ev i e r. c o m / l o c a t e / j a p p g e o
Characterization of recharge through complex vadose zone of a granitic aquifer by time-lapse electrical resistivity tomography Tanvi Arora ⁎, Shakeel Ahmed National Geophysical Research Institute (Council of Scientific & Industrial Research), Uppal Road, Hyderabad 500 606, India
a r t i c l e
i n f o
Article history: Received 29 December 2009 Accepted 4 November 2010 Available online 26 November 2010 Keywords: Time lapse electrical resistivity tomography Recharge Vadose zone
a b s t r a c t The vadose zone is the main region controlling water movement from the land surface to the aquifer and has a very complex structure. The use of non-invasive or minimally invasive geophysical methods especially electrical resistivity imaging is a cost-effective approach adapted for long-term monitoring of the vadose zone. The main aim of this work is to know the fractures in the vadose zone, of granitic terrene, through which the recharge or preferred path recharge to the aquifer takes place and thus to relate moisture and electrical resistivity. Time lapse electrical resistivity tomography (TLERT) experiment was carried out in the vadose zone of granitic terrene at the Indian Geophysical Research Institute, Hyderabad along two profiles to a depth of 18 m and 13 m each. The profiles are 300 m apart. Piezometric, rainfall and soil moisture data were recorded to correlate with changes in the rainfall recharge. These TLERT difference images showed that the conductivity distribution was consistent with the recharge occurring along the minor fractures. We mapped the fractures in hard rock or granites to see the effect of the recharge on resistivity variation and estimation of moisture content. These fractures act as the preferred pathways for the recharge to take place. A good correlation between the soil moisture and resistivity is established in the vadose zone of granitic aquifer. Since the vadose zone exhibits extremely high variability, both in space and time, the surface geophysical investigations such as TLERT have been a simple and useful method to characterize the vadose zone, which would not have been possible with the point measurements alone. The analyses of the pseudosection with time indicate clearly that the assumption of the piston flow of the moisture front is not valid in hard rocks. The outcome of this study may provide some indirect parameters to the well known Richard's equation in studying the unsaturated zone. © 2010 Elsevier B.V. All rights reserved.
1. Introduction The Unsaturated zone, also termed as the vadose zone, is the portion of the Earth between the land surface and the phreatic zone or zone of saturation (“Vadose” is Latin for “shallow”). Water in the unsaturated zone has a pressure head less than the atmospheric pressure, and is retained by a combination of adhesion and capillary action. If the Unsaturated zone envelops soil, the water contained therein is termed as the soil moisture. Movement of water within the unsaturated zone is studied within soil physics and hydrology, particularly hydrogeology, and is of importance to agriculture, contaminant transport, and flood control. From a technical stand point, though hard rock areas occupy a greater part of our country, but very little knowledge exists about the “Vadose zone”, that spans the region between the ground surface and the fluctuating water table (Fig. 1). There is not much reliable information about the vadose zone that exists over hard rock
⁎ Corresponding author. Tel.: +91 40 23434684; fax: +91 40 23434651. E-mail address: [email protected] (T. Arora). 0926-9851/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.jappgeo.2010.11.003
formations. As a matter of fact one would need regional as well as large scale maps of weathering crust over hard rocks which are normally not available though sporadic pieces of information do exist through the reports of survey organizations. It is, therefore, essential to have a quantitative knowledge of the dynamics of the water storage and water movement mechanism in the unsaturated zone (vadose zone). This information about the water dynamics is required for the formulation and implementation of the artificial recharge projects, especially in the hard rock regions of the country. Electrical resistivity is a function of the textural and structural characteristics and is particularly sensitive to its water content (Sheets and Hendricks, 1995). Soils are of a porous medium, made up of nonconductive solid particles but contain electrolytes solution that conducts electric current by the movement of the free ions in the bulk solution as well as the ions adsorbed at the matrix surface. Water infiltration and ultimately aquifer recharge can be detected by studies of variations in the electrical sounding curves (Barraud et al., 1979; Cosentino et al., 1979). Groundwater flow direction and velocity can also be determined through the observation of the electrical resistivity decrease following salt water tracer injections in alluvial deposits (White, 1994). But in hard rock areas resistivity is controlled by
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Fig. 1. Vadose zone of the granitic aquifer.
electrolytic conduction as well. The recent development of a surface multielectrode method, known as electrical resistivity tomography (ERT), offers some interesting perspectives. This method is particularly well suited to the 2-D description of geological structures perpendicular to the measurement electrode line (Griffiths and Turnbull, 1985; Griffiths et al., 1990; Shima, 1990; Griffiths and Barker, 1993). TLERT presents great advantages for monitoring and is used in hydrological and environmental studies to monitor solutes and fluid flow in the porous media. Monitoring of vadose zone water movement such as water infiltration, root water uptake, borehole pumping test effects has been reported by many authors (Barker and Moore., 1998; Benderitter and Schott, 1999; Binley et al., 2001; Michot et al., 2001, 2003). Threedimensional monitoring of small fresh water plume movements through the vadose zone has become possible (Park, 1998). Zhou et al. (2001) also proposed a non-invasive method to monitor the soil water content changes over time by means of 3-D electrical tomography. The cited works revealed the capability of ERT data in monitoring water infiltration in vadose soil or through the vadose zone, as is our focus. This current study, unlike the previous ones, investigates the recharge flow dynamics in relation to the soil management. The primary geophysical method for monitoring the timing and spatial pattern of recharge in the vadose zone is the time lapse electrical resistivity tomography (TLERT) using a small electrode spacing on the surface. ERT is particularly appealing because it is non-invasive and allows for long-term quasi-continuous and spatially extensive data for monitoring in the saturated and vadose zones. Earlier workers (Daily et al., 1992; Zhou et al., 2001; Hayley et al., 2009) experimented to track the changes in resistivity through time and their work has been found to be useful for detecting the temporal changes in the moisture content of the vadose zone. Tanvi et al. (2005) has used the time lapse electrical resistivity tomography to monitor the variations in resistivity tomograms for short duration recharge. Barker et al. (2000) have used the high resolution electrical imaging to map the 3D movement of fluid in the vadose zone of the sandstone at a test site. Dutta et al. (2004) have used the resistivity imaging data of the hard rock terrain and also processed it to obtain a 3D variation of resistivity in the granitic terrain and identified the potential water bearing zones by correlating the results. Long-term monitoring of recharge at a fixed location under
different meteorological conditions will enable an improved understanding of groundwater recharge mechanisms for this critical component of the watershed system. By monitoring the vertical movement of the injected tritium through the soil column, the recharge can be estimated (Engerrand, 2002). The position of the tracer is indicated by a peak or a maximum in the tritium activity versus the depth plot. However, molecular diffusion, dispersion and aquifer heterogeneities may cause broadening of the peak. The methodology provides spot measurements of natural recharge but the estimation of recharge using the methods is expensive and cumbersome. The tracer studies cannot be undertaken at the place where we need repeated measurements after each event of rainfall and also the assumption of the vertical movement cannot be undertaken, as from the resistivity 2D tomograms the concept of the horizontal movement cannot be neglected. Thus, the variability of the moisture content is determined by the variability of the electrical resistivity measurements through electrical resistivity tomography (ERT). In the present work the influence of the natural recharge on the correlation structure of the resistivity data has been documented by analyzing the electrical resistivity imaging data. This analysis provides the condition or the extent of the saturation of moisture in the vadose zone. 2. A granitic vadose zone National Geophysical Research Institute (NGRI) watershed has a surface area of 13 km2 (http://www.ngri.org.in). The watershed (profile located at 17°24′53″ N and 78°33′ E) includes a good combination of rurally developed area and the urbanized part. The soil thickness in the whole area varies between less than a meter and 4 m in different zones. The NGRI watershed is crossed by dykes with generally east–west direction, situated at Nacharam, Tarnaka.The thickness of the weathered-rock layer ranges from 0 m to 30 m (Fig. 1) throughout the watershed. The underlying layer is granitic. The geology of the watershed consists of weathered rocks, from 0 to 30 m thick, covering a fissured granitic layer of 10 m thickness. The electrical soundings and field observations were used to determine the existence of a tectonic feature in the south of the NGRI campus that crosses the watershed in a north-east south-west direction. This feature is signaled by a sudden thickening of the
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weathered-rock horizon and probably represents a fracture corridor or a fault. The longitudinal resistivity was estimated by means of electrical soundings as estimated by Engerrand (2002). The groundwater in the watershed is intensively exploited by its inhabitants, institutes and industries. The withdrawal rates were quantified over 40-year periods from 1961 to 2001. In spite of the heavy withdrawal (11,000 m3/day), the water levels do not seem to be falling much in the watershed. The resistivity measurements were carried out with the resistivity meter Syscal R1 Junior (Iris Instruments, Orléans, France) equipped with 48 electrodes. The intensity and voltage accuracy is 0.3%, which is consistent with the measurements carried out under constant hydrogeologic conditions for about 10 h. The values were persistent within a tenth of an ohm-meter, i.e., one thousandth of the measured resistivity could reach several ohm-meters between two sets of measurements 1 h apart. The electrodes remained on the soil surface during all the experiment time to avoid any electrode polarization changes and to ensure the best quality of measurements. But for monitoring the moisture movement of water through the vadose zone the change of the subsurface resistivity is checked with the change in time. In the present study the change in the resistivity distribution has been observed and analyzed in the vadose zone of granitic terrene as an aid to examine the movement of the natural recharge i.e. rainfall. 3. Data acquisition 3.1. Time lapse electrical resistivity tomography The experiment set up included a row of 48 electrodes, lined up on the soil surface. The electrodes were separated by 2 m and 1.5 m, respectively at sites S1 and S2 (Figs. 2, 3 and 6) at NGRI campus. The Wenner–Schlumberger array was used to survey the profile. A total
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number of 529 datum points were measured at 23 data levels, which lead to the plotting of a pseudosection by the observed data sets. The variation in the ERT datasets has been observed for time prior, during and after the rainfall. 3.2. Self potential (SP) measurements A self potential survey was carried along the same profile at sites S1 and S2 as shown in Figs. 4 and 7. The black cross denotes the position of the electrode. The other electrode is kept at infinity; practically the distance should be more than 10 times the electrode spacing. The red rectangle denotes the area of the profile being covered by electrical resistivity tomography. The position of the neutron probe well is also being covered in the SP map (Fig. 4). As clearly shown in Fig. 4 there exists a potential being developed and observed on the ground surface due to the movement of fluids, both in the unsaturated zone as well as due to the piezometric heads. The streaming potential anomaly is being observed along the profile between the distances of 2 m and 14 m, shown encircled in green color in Fig. 4. This anomalous zone has the streaming potential of 17 V and to the very best of the data acquisition; this zone coincides very well with the recharge zone in the electrical resistivity tomograms (Fig. 3). Thereby, it confirms that this zone is the best place for the preferential recharge in the watershed. Also the SP data was acquired along site S2 (Fig. 7). The spacing between the electrodes is kept as 1.5 m (horizontally) and 3 m (vertically). The anomalous position is to the east of the profile and the results match very well with the soil moisture profile at this site S2. 3.3. Hydrological information The rainfall and water level bear an analogy with each other and there appears to be a good correlation of 88% between the water level
Fig. 2. Study area with two sites S1 and S2 in the granitic terrene of South India.
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Fig. 3. TLERT tomograms illustrating variations after the rainfall event at site S1.
T. Arora, S. Ahmed / Journal of Applied Geophysics 73 (2011) 35–44
SP anomaly at S1 SPanomalyatS1
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Neutron probe well for moisture measurement
8
4
0
0
2
4
6
8
10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
5
5.5
6
6.5
7
7.5
8
8.5
9
9.5
10
11
12
13
14
15
16
17
SP Map at the Site S1 (NGRI)
SP in Volts Fig. 4. Showing the SP anomaly at the site S1 of NGRI campus.
and the rainfall measurement at both the sites S1 and S2. The number of rainfall events affects the rising of the water level thereby resulting in the shallow water table. At both the sites the rainfall–water level relationship shows a similar trend (Fig. 8). As the rainfall shows a hike, the water level in the measuring borewell is becoming shallow. At site S1 the water level reduces by 65% for a fixed increase in rainfall of 42% and at site S2 the water level reduces by 72% following the same increase in rainfall.
3.4. Soil moisture data For the soil moisture measurements in the study area the indirect method of measurement is employed using the neutron probe measuring device available at NGRI. Two access tubes made up of aluminum, 2.5 in in diameter were installed in the soil at both the sites, S1 and S2. The standard method of installation was used and no difficulty was encountered in installing the tubes to depths of up to 15 m. The depths of the tubes ranged from 14 to 15 m and the maximum depth of installation was limited by the length of the guide
tubes available. Observations were made regularly up to the depths of the unsaturated zones at both the sites. Water content observations were made at each access tube more or less after each rainfall event during the monsoon cycle of 2005. Readings were taken at 0.30 m depth intervals from 0.30 m below the surface down to the bottom of the tube. Counting times of 30 s or 60 s were used throughout the study. The moisture content measured in each tube in the profile is assumed to represent the moisture of a layer extending midway to the adjacent measuring depths. The depths and the comparative change in the moisture percentages are being enumerated in a tabular form (Tables 1 and 2) 4. Data processing and interpretation The inversion of the measured resistivities is an essential step before the interpretation because the raw resistivity measurements rarely give the true structure of the soil. Panissod et al. (2001) showed that the 2-D inversion was appropriate in this case according to a 3-D inversion. So inverted resistivity sections were achieved with the RES2DINV software (Loke and Barker, 1996). This technique was
Fig. 5. Depthwise correlation of the resistivity variation at a particular depth in tomograms from a to m at site S1.
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Fig. 6. TLERT tomograms showing variations after the rainfall event at site S2.
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Table 1 Showing the zone wise variation of soil moisture in % at site S1.
9
6
3
0
41
3
1.5
4.5
6
7.5
9
10.5
12
SP Map at the site S2 (NGRI) 17.6
17
16
15
14.4 (in mV)
Fig. 7. SP anomaly at the site S2 of NGRI campus.
based on the smoothness-constrained least-squares method and it produced 2-D subsurface model from the apparent resistivity section. In the first iteration, a homogeneous earth model was used as a starting model for which the resistivity partial derivative values could be calculated analytically. For subsequent iterations, a quasi-Newton method was used to estimate the partial derivatives which reduced the computer time. In this method, the Jacobian matrices for a homogeneous earth model were used for the first iteration, and the Jacobian matrices for subsequent iterations were estimated by an updating technique. The model consisted of a rectangular grid. The software determined the resistivity of each mesh which gave a calculated electrical resistivity section according to the field measurements. The iterative optimization method attempted to reduce the differences between the measured resistivity values and those
Depth range (in m)
Change of moisture in% (initial and final)
1.2 to 1.6 m 3 to 3.7 m 4.8 to 5.2
4 2.8 5
calculated with the inversion model. The difference was estimated by the root mean square error (RMS error). Topographic correction was not taken into account for this inversion process, and each ERT was inverted independently. The model obtained from the inversion of the initial data set was not used as a reference model to constrain the inversion of the later time-lapse data sets, as it was possible with the recent version of RES2DINV software. A minimum of 5 successive iterations were made. However, for ERT inversions, the same number of data and mesh of the model were conserved, so the inversion of each ERT data was not totally independent. Each measured resistivity section was inverted. Water infiltration was indicated by variations in the electrical resistivity of the soils, as expected (Ward, 1990), i.e. the electrical resistivity in the soils decreases when the soil water content increases, and vice versa. To enhance the representation of that occurrence, the sections of resistivity changes were calculated in relation to some sections measured at typical moments representative of the particular hydric soil states. In this manner of calculating “difference images”, water infiltration was studied in relation to the first ERT (Fig. 3) measured at the initial soil moisture state at the beginning of the experimental monitoring. 4.1. At site S1 inside NGRI campus Normally, the data from the surveys conducted at different times are inverted independently, frequently with a smoothness-constrained least-squares inversion method (Loke, 1999). The changes in the vadose zone resistivity values are then determined by comparing the model resistivity values obtained from the inversions of an initial data set and the later data sets. In many cases, such an approach has given satisfactory results. However, in theory, since the inversion of each data set is carried out independently, there is no guarantee that the differences in the resistivity values are only due to the actual changes in the subsurface resistivity with time. Each inversion attempts to minimize the difference between the observed and calculated apparent resistivity values for an individual data set
Fig. 8. Rainfall against water level fluctuations for the monsoonal cycle of 2005 at sites S1 and S2.
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Table 2 Showing the zone wise variation of soil moisture in % at site S2. Depth range (in m)
Change of moisture in % (initial and final)
2.2 3.5 4.5 5.5
2 6 3 6
to to to to
2.5 m 4.2 m 4.7 m 6m
without taking into account the model obtained from the initial data set. The model obtained from the inversion of the initial data set is used as a reference model to constrain the inversion of the later timelapse data sets. A simple quotient method was employed (Singha and Gorelick, 2005 and the references therein) to minimize the differences in the model resistivity values between the initial model and the time-lapse model used. This method uses least-squares smoothness constraints to ensure that the differences in the model resistivity values vary in a smooth manner. This method takes care of the relative resistivity of the initial model with the subsequent model. A total of 35 tomograms were obtained but those which are relevant are being shown here from a to m (Fig. 3). The numerals along the numbering denote the date of data acquisition. The subsequent models show the difference in the resistivity of the models obtained from the inversion of the initial and the time-lapse data sets. On the basis of the profile at site S1, the first layer is extreme. The layers below the first layer are less resistive. It can be identified as the dry red soil sediments with the intermediate unconsolidated sapprolite. The altitude on the Northern side of the profile is slightly higher and most of the measurement devices (like neutron probe for soil moisture, borewell for water level measurement, and raingauge for measuring rainfall) are situated on the southern side of the profile. The resistivities of the underlying layers are less resistive in the profile g to m of Fig. 3, which could indicate that the recharge is more downwards along the profile. There is an overall change observed in the subsequent layers thus showing that the water flux is moving both horizontally as well as vertically. This may be confirmed with the soil moisture data. The highest resistivity is in the centre of the profile starting from 35 m to 63 m and is located vertically at the depth of 3 m. This may be indicative of the locally thicker dry sediments above the aquifer or the presence of some resistive body like a boulder. The resistive body appearing at depths of 3 m to 8 m may either be a 3D artifact due to the small relief or the actual presence of more resistive sediments at depth. It can also be due to the absence of minor fractures for recharge or due to the lack of a connecting porosity. At the passage S1P1, existing between 20 m and 42 m resistivities shows the vertical variations. There exists the non-uniform distribution of the moisture in the vertical profile following the rainfall infiltration. The passage of the recharge movement is quite clear in Fig. 3. Farther away on the line, the resistivity highs and lows exist in patches. At the indicative passage S1P2, between the profile lengths of 68 m and 76 m, the resistivity shows variations. These variations may be due to the different geological materials. Due to the high porosity, the connecting porosity in the well is connected to the depth of 12 m ultimately merging into the aquifer. But this part is not being considered much as there is not much control of the data at this part of the profile. The particular zones between 20 m and 42 m show the vertical as well as horizontal infiltration of the natural recharge. The pathways of the moisture could be known. The relative percentage change in the electrical resistivity is quite clear as compared from the pseudosections. This clearly brings out the respective zone of the preferential recharge, shown in the zones between the two red lines, along the profile lengths of 21 m to 42 m. This specific path for the recharge is later confirmed by the self potential anomaly (Fig. 4).
Fig. 5 shows the depth wise variations in the electrical resistivity as a measure of percentage. The respective time sections are taken as the difference from an initial model to the measured ones. Fig. 5 shows the depth wise correlation and is a representative of the 2D tomograms obtained in Fig. 3. The initial dataset is considered of 211004 (T0) and the corresponding ones are as T1 = T2 = T3 = T4 =
120605–211004 250705–211004 210805–211004 110905–211004:
Changes in the electrical resistivity associated with the recharge movement are of the order of 25% at the depths of 1.5 m to 3 m. Further the variations of resistivity are 8 to 10% in the depth range of 4 to 8 m. Advancing further deep, the resistivity after the complete monsoonal cycle shows the quantitative variation of 4 to 5% within the depths of 8 to 12 m but this variation becomes negligible as the ERT measurement reaches the aquifer at the depth of 11.8 m. This gives a pathway to trace the moisture. 4.2. At site S2 inside NGRI campus The experimental field setup was laid along a profile of 70.5 m with the electrode spacing of 1.5 m (Fig. 6) at site S2. The Wenner–Schlumberger array was used to survey the profile. A total number of 529 datum points were measured at 23 data levels, which lead to the plotting of a pseudosection (Fig. 6), by the observed data sets. The acquired tomograms (Fig. 6, from a to k) are being documented. A total of 35 tomograms were obtained but those which are relevant are being shown here from a to k at site S2 (Fig. 6). The numerals along the numbering denote the date of the data acquisition. On the basis of the profile at site S2, the first layer is extremely conductive, thereby proving that in the hard rock terrene the water exists in the weathered layer, as visible in the tomograms. The layers visible below the first layer, at the depth of 2 m are more resistive. Most of the measurement devices (like the neutron probe for soil moisture, borewell for water level measurement) are situated on the eastern side of the profile. The resistivity of the underlying layers is less resistive in the profile g to k of Fig. 6, which could indicate that the recharge is more downwards along the profile. There is an overall change observed in the layers thus showing that the water flux is moving both horizontally as well as vertically. This may be confirmed with the soil moisture profile. There exists a resistive layer at the position from 30 m to 48 m at the depths of 2 m to 6 m. Also the recharge takes place at the entrance of the electrode situated at 18 m to 24 m and 54 m to 57 m. The aquifer lies at the depth below 9 m, just below the resistive body. Yet another feature interrupts the pathways of the recharge front moving at the profile, which lies at 24 m to 29.5 m at the depths of 3 m–8 m. The high resistive body just below the point of 60 m may be indicative of a boulder or some resistive material. This resistive body may either be a 3D artifact due to the small relief or the actual presence of more resistive sediments at the depths. It can also be due to the absence of minor fractures for recharge or due to the lack of connecting porosity. The data shown in Fig. 3 and the corresponding Fig. 6 from the tomograms for the site S1 and site S2 are the differenced absolute inversion rather than the difference inversions (LaBrecque and Yang, 2000; Singha et al., 2003). Undoubtedly, the difference inversions would appear somewhat different because the systematic errors from the field and the discretization errors in the forward modeling tend to cancel out. Quantitatively the percent differences in the electrical resistivities associated with the arrival of the recharge match the recharge measurement fairly well both in time and space. The match is a scorer
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for the upper layers of the pseudosection because the fluid or rainfall measurements only indicate mobile recharge (soil moisture/rainfall), whereas the ERT measures mobile and immobile salts. Changes in the electrical resistivity associated with the recharge movement are of the order of 25% to 28% at the depth of 6 m (Fig. 9) which shows the coefficient of variation of the electrical resistivity as the result of movement of the recharge front for one complete cycle. Further the variation of resistivity is 6% in the depth range of 6 m, just at the onset of the monsoon in the month of May. Advancing further deep, the resistivity after the complete monsoonal cycle after the depth of 10 m the situation is completely reverse. The overall trend shows that there is an increase of moisture up to a depth of 2 m, which is the main parameter for a drastic change in resistivity. As the front is moving, due to the connecting porosity the resistivity shows the difference but to a deeper level, due to the lack of connecting porosity or minor fracture, the resistivity is reduced. These aspects are confirmed by the soil moisture. 5. Conclusion TLERT shows that the resistivity is not constant with time and is reliable and sufficient to represent the profile (Figs. 3, 6). This also confirms and justifies the most common application of the electrical resistivity methods applied for groundwater prospecting as the resistivities do change in time, the medium being unsaturated. 1. The estimation or assessment of rainfall recharge is of utmost importance in the field of groundwater hydrology but unfortunately no method exists for its direct measurement or detection. Thus its estimation through the measurements of related parameters is subjected to errors and biasness. 2. In this work TLERT, being a non-invasive technique, has been employed to characterize the spatio-temporal variations of the rainfall recharge so that it may improve its estimation by other methods. 3. The vadose zone of the granitic terrene is investigated and analyzed using comparatively simpler approach, for example, geophysical analytical methods like time lapse electrical resistivity tomography, self potential and soil moisture measurements as
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neutron probe. The surface geophysical methods are non-invasive methods and it is much easy to carry out repetitive measurement as well as at many locations while the measurement of soil moisture through Neutron probe requires much complicated procedures of drilling the slim holes, sealing it with aluminum tubes and calibration using the known conditions etc. 4. Prior to recharge there is no continuity of moisture, but after the rainfall there exists the continuity. This property certainly questions the applicability of the piston flow assumption often made in the recharge studies. 5. The repeated TLERT could support the estimation of the rainfall recharge qualitatively and can remove biasness in other methods. 6. This application opens up the wider expertise and scope in oil fields specially in locating the position for injecting the air during exploration. The present work is a simple case study to analyse the effect of the rainfall recharge on the resistivity and an attempt to map the moisture movement through the vadose zone leading to the water table by a series of experiments for a longer period. Barker and Moore (1998) discussed this in an experiment carried out at Birmingham, England. It is clear from the visualizations of the tomograms that there is a decrease in the resistivity values at the deeper depth levels due to the migration of water from the near surface zone. This work is also an attempt for the 4-D studies of the vadose zone where the time factor acts as an important aspect for the recharge movement and its movement through the vadose zone. This work may yield realistic results under field conditions when studied jointly with the hydrological information.
Acknowledgements The authors are grateful to Dr. V.P.Dimri, Director NGRI for his consent to publish this work. This study was funded by CSIR, India. TA is grateful to CSIR for providing the fellowship to carry out the research work.
Fig. 9. Showing the variation of coefficient of variation at S2.
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Loke, M.H., 1999. Time lapse resistivity imaging inversion. Proceedings of the 5th Meeting of the EEGS European Section, p. Em1. Loke, M.H., Barker, R.D., 1996. Rapid least-squares inversion of apparent resistivity pseudosections by a quasi-Newton method. Geophysical Prospectings 44, 499–524. Michot, D., dorigny, A., Benderitter, Y., 2001. Mise en evidence par resistivite electrique des ecoulements preferentiels et de l'assechement par le mais d'un Calcisol de Beauce irrigue. C.R.Acad. Sc. Paris, Serie lia, 332, pp. 29–36. Michot, D., Benderitter, Y., Dorigny, A., Nicoullaud, B., King, D., Tabbagh, A., 2003. Spatial and temporal monitoring of soilwater content with an irrigated corn crop cover using surface electrical resistivity tomography. Water Resour. Res. 39 (5), 1138. doi:10.1029/2002WR001581. Panissod, C., Michot, D., Benderitter, Y., Tabbagh, A., 2001. On the effectiveness of 2D electrical inversion results: an agricultural case study. Geophysical Prospecting 49, 570–576. Park, S., 1998. Fluid migration in the vadose zone from 3-D inversion of resistivity monitoring data. Geophysics 63, 41–51. Sheets, K.R., Hendricks, J.M.H., 1995. Non-invasive soil water content measurement using electromagnetic induction. Water Resources Research 31, 2401–2409. Shima, H., 1990. Two dimensional automatic resistivity inversion technique using alpha centers. Geophysics 55, 682–694. Singha, K., Gorelick, S.M., 2005. Saline tracer visualized with three-dimensional electrical resistivity tomography: field-scale spatial moment analysis. Water Resour. Res. 41, W05023. doi:10.1029/2004WR003460. Singha, K., Binley, A.M., Lane Jr., J.W., Gorelick, S.M., 2003. Electrical imaging of tracer migration at the Massachusetts Military Reservation, Cape Cod, in Symposium on the Application of Geophysics to Engineering and Environmental Problems (SAGEEP), April 6–10, 2003, San Antonio, Texas. Proceedings: Denver, Colorado, Environmental and Engineering Geophysical Society, CD-ROM. 11 pp. Tanvi, Arora, Krishnamurthy, N.S., Shakeel, Ahmed, 2005. TLERT to decipher the unsaturated zone. Published and Presented in the International Conference on Hydrological Perspectives for Sustainable Development, Held at IIT, vol. II. Allied Publishers Pvt. Ltd., Roorkee, pp. 846–852. Ward, S.H., 1990. Resistivity and induced polarisation methods. In: Ward, S.H. (Ed.), Geotechnical and Environmental Geophysics, vol. 1. Soc. of Exp. Geophys., Tulsa, Okla, pp. 147–189. White, P.A., 1994. Electrode arrays for measuring groundwater flow direction and velocity. Geophysics 59, 192–201. Zhou, Q.Y., Shimada, J., Sato, A., 2001. Three-dimensional spatial and temporal monitoring of soil water content using electrical resistivity tomography. Water Resources Research 37, 273–285.
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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 ev i e r. c o m / l o c a t e / j a p p g e o
Characterization of recharge through complex vadose zone of a granitic aquifer by time-lapse electrical resistivity tomography Tanvi Arora ⁎, Shakeel Ahmed National Geophysical Research Institute (Council of Scientific & Industrial Research), Uppal Road, Hyderabad 500 606, India
a r t i c l e
i n f o
Article history: Received 29 December 2009 Accepted 4 November 2010 Available online 26 November 2010 Keywords: Time lapse electrical resistivity tomography Recharge Vadose zone
a b s t r a c t The vadose zone is the main region controlling water movement from the land surface to the aquifer and has a very complex structure. The use of non-invasive or minimally invasive geophysical methods especially electrical resistivity imaging is a cost-effective approach adapted for long-term monitoring of the vadose zone. The main aim of this work is to know the fractures in the vadose zone, of granitic terrene, through which the recharge or preferred path recharge to the aquifer takes place and thus to relate moisture and electrical resistivity. Time lapse electrical resistivity tomography (TLERT) experiment was carried out in the vadose zone of granitic terrene at the Indian Geophysical Research Institute, Hyderabad along two profiles to a depth of 18 m and 13 m each. The profiles are 300 m apart. Piezometric, rainfall and soil moisture data were recorded to correlate with changes in the rainfall recharge. These TLERT difference images showed that the conductivity distribution was consistent with the recharge occurring along the minor fractures. We mapped the fractures in hard rock or granites to see the effect of the recharge on resistivity variation and estimation of moisture content. These fractures act as the preferred pathways for the recharge to take place. A good correlation between the soil moisture and resistivity is established in the vadose zone of granitic aquifer. Since the vadose zone exhibits extremely high variability, both in space and time, the surface geophysical investigations such as TLERT have been a simple and useful method to characterize the vadose zone, which would not have been possible with the point measurements alone. The analyses of the pseudosection with time indicate clearly that the assumption of the piston flow of the moisture front is not valid in hard rocks. The outcome of this study may provide some indirect parameters to the well known Richard's equation in studying the unsaturated zone. © 2010 Elsevier B.V. All rights reserved.
1. Introduction The Unsaturated zone, also termed as the vadose zone, is the portion of the Earth between the land surface and the phreatic zone or zone of saturation (“Vadose” is Latin for “shallow”). Water in the unsaturated zone has a pressure head less than the atmospheric pressure, and is retained by a combination of adhesion and capillary action. If the Unsaturated zone envelops soil, the water contained therein is termed as the soil moisture. Movement of water within the unsaturated zone is studied within soil physics and hydrology, particularly hydrogeology, and is of importance to agriculture, contaminant transport, and flood control. From a technical stand point, though hard rock areas occupy a greater part of our country, but very little knowledge exists about the “Vadose zone”, that spans the region between the ground surface and the fluctuating water table (Fig. 1). There is not much reliable information about the vadose zone that exists over hard rock
⁎ Corresponding author. Tel.: +91 40 23434684; fax: +91 40 23434651. E-mail address: [email protected] (T. Arora). 0926-9851/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.jappgeo.2010.11.003
formations. As a matter of fact one would need regional as well as large scale maps of weathering crust over hard rocks which are normally not available though sporadic pieces of information do exist through the reports of survey organizations. It is, therefore, essential to have a quantitative knowledge of the dynamics of the water storage and water movement mechanism in the unsaturated zone (vadose zone). This information about the water dynamics is required for the formulation and implementation of the artificial recharge projects, especially in the hard rock regions of the country. Electrical resistivity is a function of the textural and structural characteristics and is particularly sensitive to its water content (Sheets and Hendricks, 1995). Soils are of a porous medium, made up of nonconductive solid particles but contain electrolytes solution that conducts electric current by the movement of the free ions in the bulk solution as well as the ions adsorbed at the matrix surface. Water infiltration and ultimately aquifer recharge can be detected by studies of variations in the electrical sounding curves (Barraud et al., 1979; Cosentino et al., 1979). Groundwater flow direction and velocity can also be determined through the observation of the electrical resistivity decrease following salt water tracer injections in alluvial deposits (White, 1994). But in hard rock areas resistivity is controlled by
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Fig. 1. Vadose zone of the granitic aquifer.
electrolytic conduction as well. The recent development of a surface multielectrode method, known as electrical resistivity tomography (ERT), offers some interesting perspectives. This method is particularly well suited to the 2-D description of geological structures perpendicular to the measurement electrode line (Griffiths and Turnbull, 1985; Griffiths et al., 1990; Shima, 1990; Griffiths and Barker, 1993). TLERT presents great advantages for monitoring and is used in hydrological and environmental studies to monitor solutes and fluid flow in the porous media. Monitoring of vadose zone water movement such as water infiltration, root water uptake, borehole pumping test effects has been reported by many authors (Barker and Moore., 1998; Benderitter and Schott, 1999; Binley et al., 2001; Michot et al., 2001, 2003). Threedimensional monitoring of small fresh water plume movements through the vadose zone has become possible (Park, 1998). Zhou et al. (2001) also proposed a non-invasive method to monitor the soil water content changes over time by means of 3-D electrical tomography. The cited works revealed the capability of ERT data in monitoring water infiltration in vadose soil or through the vadose zone, as is our focus. This current study, unlike the previous ones, investigates the recharge flow dynamics in relation to the soil management. The primary geophysical method for monitoring the timing and spatial pattern of recharge in the vadose zone is the time lapse electrical resistivity tomography (TLERT) using a small electrode spacing on the surface. ERT is particularly appealing because it is non-invasive and allows for long-term quasi-continuous and spatially extensive data for monitoring in the saturated and vadose zones. Earlier workers (Daily et al., 1992; Zhou et al., 2001; Hayley et al., 2009) experimented to track the changes in resistivity through time and their work has been found to be useful for detecting the temporal changes in the moisture content of the vadose zone. Tanvi et al. (2005) has used the time lapse electrical resistivity tomography to monitor the variations in resistivity tomograms for short duration recharge. Barker et al. (2000) have used the high resolution electrical imaging to map the 3D movement of fluid in the vadose zone of the sandstone at a test site. Dutta et al. (2004) have used the resistivity imaging data of the hard rock terrain and also processed it to obtain a 3D variation of resistivity in the granitic terrain and identified the potential water bearing zones by correlating the results. Long-term monitoring of recharge at a fixed location under
different meteorological conditions will enable an improved understanding of groundwater recharge mechanisms for this critical component of the watershed system. By monitoring the vertical movement of the injected tritium through the soil column, the recharge can be estimated (Engerrand, 2002). The position of the tracer is indicated by a peak or a maximum in the tritium activity versus the depth plot. However, molecular diffusion, dispersion and aquifer heterogeneities may cause broadening of the peak. The methodology provides spot measurements of natural recharge but the estimation of recharge using the methods is expensive and cumbersome. The tracer studies cannot be undertaken at the place where we need repeated measurements after each event of rainfall and also the assumption of the vertical movement cannot be undertaken, as from the resistivity 2D tomograms the concept of the horizontal movement cannot be neglected. Thus, the variability of the moisture content is determined by the variability of the electrical resistivity measurements through electrical resistivity tomography (ERT). In the present work the influence of the natural recharge on the correlation structure of the resistivity data has been documented by analyzing the electrical resistivity imaging data. This analysis provides the condition or the extent of the saturation of moisture in the vadose zone. 2. A granitic vadose zone National Geophysical Research Institute (NGRI) watershed has a surface area of 13 km2 (http://www.ngri.org.in). The watershed (profile located at 17°24′53″ N and 78°33′ E) includes a good combination of rurally developed area and the urbanized part. The soil thickness in the whole area varies between less than a meter and 4 m in different zones. The NGRI watershed is crossed by dykes with generally east–west direction, situated at Nacharam, Tarnaka.The thickness of the weathered-rock layer ranges from 0 m to 30 m (Fig. 1) throughout the watershed. The underlying layer is granitic. The geology of the watershed consists of weathered rocks, from 0 to 30 m thick, covering a fissured granitic layer of 10 m thickness. The electrical soundings and field observations were used to determine the existence of a tectonic feature in the south of the NGRI campus that crosses the watershed in a north-east south-west direction. This feature is signaled by a sudden thickening of the
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weathered-rock horizon and probably represents a fracture corridor or a fault. The longitudinal resistivity was estimated by means of electrical soundings as estimated by Engerrand (2002). The groundwater in the watershed is intensively exploited by its inhabitants, institutes and industries. The withdrawal rates were quantified over 40-year periods from 1961 to 2001. In spite of the heavy withdrawal (11,000 m3/day), the water levels do not seem to be falling much in the watershed. The resistivity measurements were carried out with the resistivity meter Syscal R1 Junior (Iris Instruments, Orléans, France) equipped with 48 electrodes. The intensity and voltage accuracy is 0.3%, which is consistent with the measurements carried out under constant hydrogeologic conditions for about 10 h. The values were persistent within a tenth of an ohm-meter, i.e., one thousandth of the measured resistivity could reach several ohm-meters between two sets of measurements 1 h apart. The electrodes remained on the soil surface during all the experiment time to avoid any electrode polarization changes and to ensure the best quality of measurements. But for monitoring the moisture movement of water through the vadose zone the change of the subsurface resistivity is checked with the change in time. In the present study the change in the resistivity distribution has been observed and analyzed in the vadose zone of granitic terrene as an aid to examine the movement of the natural recharge i.e. rainfall. 3. Data acquisition 3.1. Time lapse electrical resistivity tomography The experiment set up included a row of 48 electrodes, lined up on the soil surface. The electrodes were separated by 2 m and 1.5 m, respectively at sites S1 and S2 (Figs. 2, 3 and 6) at NGRI campus. The Wenner–Schlumberger array was used to survey the profile. A total
37
number of 529 datum points were measured at 23 data levels, which lead to the plotting of a pseudosection by the observed data sets. The variation in the ERT datasets has been observed for time prior, during and after the rainfall. 3.2. Self potential (SP) measurements A self potential survey was carried along the same profile at sites S1 and S2 as shown in Figs. 4 and 7. The black cross denotes the position of the electrode. The other electrode is kept at infinity; practically the distance should be more than 10 times the electrode spacing. The red rectangle denotes the area of the profile being covered by electrical resistivity tomography. The position of the neutron probe well is also being covered in the SP map (Fig. 4). As clearly shown in Fig. 4 there exists a potential being developed and observed on the ground surface due to the movement of fluids, both in the unsaturated zone as well as due to the piezometric heads. The streaming potential anomaly is being observed along the profile between the distances of 2 m and 14 m, shown encircled in green color in Fig. 4. This anomalous zone has the streaming potential of 17 V and to the very best of the data acquisition; this zone coincides very well with the recharge zone in the electrical resistivity tomograms (Fig. 3). Thereby, it confirms that this zone is the best place for the preferential recharge in the watershed. Also the SP data was acquired along site S2 (Fig. 7). The spacing between the electrodes is kept as 1.5 m (horizontally) and 3 m (vertically). The anomalous position is to the east of the profile and the results match very well with the soil moisture profile at this site S2. 3.3. Hydrological information The rainfall and water level bear an analogy with each other and there appears to be a good correlation of 88% between the water level
Fig. 2. Study area with two sites S1 and S2 in the granitic terrene of South India.
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Fig. 3. TLERT tomograms illustrating variations after the rainfall event at site S1.
T. Arora, S. Ahmed / Journal of Applied Geophysics 73 (2011) 35–44
SP anomaly at S1 SPanomalyatS1
39
Neutron probe well for moisture measurement
8
4
0
0
2
4
6
8
10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
5
5.5
6
6.5
7
7.5
8
8.5
9
9.5
10
11
12
13
14
15
16
17
SP Map at the Site S1 (NGRI)
SP in Volts Fig. 4. Showing the SP anomaly at the site S1 of NGRI campus.
and the rainfall measurement at both the sites S1 and S2. The number of rainfall events affects the rising of the water level thereby resulting in the shallow water table. At both the sites the rainfall–water level relationship shows a similar trend (Fig. 8). As the rainfall shows a hike, the water level in the measuring borewell is becoming shallow. At site S1 the water level reduces by 65% for a fixed increase in rainfall of 42% and at site S2 the water level reduces by 72% following the same increase in rainfall.
3.4. Soil moisture data For the soil moisture measurements in the study area the indirect method of measurement is employed using the neutron probe measuring device available at NGRI. Two access tubes made up of aluminum, 2.5 in in diameter were installed in the soil at both the sites, S1 and S2. The standard method of installation was used and no difficulty was encountered in installing the tubes to depths of up to 15 m. The depths of the tubes ranged from 14 to 15 m and the maximum depth of installation was limited by the length of the guide
tubes available. Observations were made regularly up to the depths of the unsaturated zones at both the sites. Water content observations were made at each access tube more or less after each rainfall event during the monsoon cycle of 2005. Readings were taken at 0.30 m depth intervals from 0.30 m below the surface down to the bottom of the tube. Counting times of 30 s or 60 s were used throughout the study. The moisture content measured in each tube in the profile is assumed to represent the moisture of a layer extending midway to the adjacent measuring depths. The depths and the comparative change in the moisture percentages are being enumerated in a tabular form (Tables 1 and 2) 4. Data processing and interpretation The inversion of the measured resistivities is an essential step before the interpretation because the raw resistivity measurements rarely give the true structure of the soil. Panissod et al. (2001) showed that the 2-D inversion was appropriate in this case according to a 3-D inversion. So inverted resistivity sections were achieved with the RES2DINV software (Loke and Barker, 1996). This technique was
Fig. 5. Depthwise correlation of the resistivity variation at a particular depth in tomograms from a to m at site S1.
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Fig. 6. TLERT tomograms showing variations after the rainfall event at site S2.
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12
Table 1 Showing the zone wise variation of soil moisture in % at site S1.
9
6
3
0
41
3
1.5
4.5
6
7.5
9
10.5
12
SP Map at the site S2 (NGRI) 17.6
17
16
15
14.4 (in mV)
Fig. 7. SP anomaly at the site S2 of NGRI campus.
based on the smoothness-constrained least-squares method and it produced 2-D subsurface model from the apparent resistivity section. In the first iteration, a homogeneous earth model was used as a starting model for which the resistivity partial derivative values could be calculated analytically. For subsequent iterations, a quasi-Newton method was used to estimate the partial derivatives which reduced the computer time. In this method, the Jacobian matrices for a homogeneous earth model were used for the first iteration, and the Jacobian matrices for subsequent iterations were estimated by an updating technique. The model consisted of a rectangular grid. The software determined the resistivity of each mesh which gave a calculated electrical resistivity section according to the field measurements. The iterative optimization method attempted to reduce the differences between the measured resistivity values and those
Depth range (in m)
Change of moisture in% (initial and final)
1.2 to 1.6 m 3 to 3.7 m 4.8 to 5.2
4 2.8 5
calculated with the inversion model. The difference was estimated by the root mean square error (RMS error). Topographic correction was not taken into account for this inversion process, and each ERT was inverted independently. The model obtained from the inversion of the initial data set was not used as a reference model to constrain the inversion of the later time-lapse data sets, as it was possible with the recent version of RES2DINV software. A minimum of 5 successive iterations were made. However, for ERT inversions, the same number of data and mesh of the model were conserved, so the inversion of each ERT data was not totally independent. Each measured resistivity section was inverted. Water infiltration was indicated by variations in the electrical resistivity of the soils, as expected (Ward, 1990), i.e. the electrical resistivity in the soils decreases when the soil water content increases, and vice versa. To enhance the representation of that occurrence, the sections of resistivity changes were calculated in relation to some sections measured at typical moments representative of the particular hydric soil states. In this manner of calculating “difference images”, water infiltration was studied in relation to the first ERT (Fig. 3) measured at the initial soil moisture state at the beginning of the experimental monitoring. 4.1. At site S1 inside NGRI campus Normally, the data from the surveys conducted at different times are inverted independently, frequently with a smoothness-constrained least-squares inversion method (Loke, 1999). The changes in the vadose zone resistivity values are then determined by comparing the model resistivity values obtained from the inversions of an initial data set and the later data sets. In many cases, such an approach has given satisfactory results. However, in theory, since the inversion of each data set is carried out independently, there is no guarantee that the differences in the resistivity values are only due to the actual changes in the subsurface resistivity with time. Each inversion attempts to minimize the difference between the observed and calculated apparent resistivity values for an individual data set
Fig. 8. Rainfall against water level fluctuations for the monsoonal cycle of 2005 at sites S1 and S2.
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Table 2 Showing the zone wise variation of soil moisture in % at site S2. Depth range (in m)
Change of moisture in % (initial and final)
2.2 3.5 4.5 5.5
2 6 3 6
to to to to
2.5 m 4.2 m 4.7 m 6m
without taking into account the model obtained from the initial data set. The model obtained from the inversion of the initial data set is used as a reference model to constrain the inversion of the later timelapse data sets. A simple quotient method was employed (Singha and Gorelick, 2005 and the references therein) to minimize the differences in the model resistivity values between the initial model and the time-lapse model used. This method uses least-squares smoothness constraints to ensure that the differences in the model resistivity values vary in a smooth manner. This method takes care of the relative resistivity of the initial model with the subsequent model. A total of 35 tomograms were obtained but those which are relevant are being shown here from a to m (Fig. 3). The numerals along the numbering denote the date of data acquisition. The subsequent models show the difference in the resistivity of the models obtained from the inversion of the initial and the time-lapse data sets. On the basis of the profile at site S1, the first layer is extreme. The layers below the first layer are less resistive. It can be identified as the dry red soil sediments with the intermediate unconsolidated sapprolite. The altitude on the Northern side of the profile is slightly higher and most of the measurement devices (like neutron probe for soil moisture, borewell for water level measurement, and raingauge for measuring rainfall) are situated on the southern side of the profile. The resistivities of the underlying layers are less resistive in the profile g to m of Fig. 3, which could indicate that the recharge is more downwards along the profile. There is an overall change observed in the subsequent layers thus showing that the water flux is moving both horizontally as well as vertically. This may be confirmed with the soil moisture data. The highest resistivity is in the centre of the profile starting from 35 m to 63 m and is located vertically at the depth of 3 m. This may be indicative of the locally thicker dry sediments above the aquifer or the presence of some resistive body like a boulder. The resistive body appearing at depths of 3 m to 8 m may either be a 3D artifact due to the small relief or the actual presence of more resistive sediments at depth. It can also be due to the absence of minor fractures for recharge or due to the lack of a connecting porosity. At the passage S1P1, existing between 20 m and 42 m resistivities shows the vertical variations. There exists the non-uniform distribution of the moisture in the vertical profile following the rainfall infiltration. The passage of the recharge movement is quite clear in Fig. 3. Farther away on the line, the resistivity highs and lows exist in patches. At the indicative passage S1P2, between the profile lengths of 68 m and 76 m, the resistivity shows variations. These variations may be due to the different geological materials. Due to the high porosity, the connecting porosity in the well is connected to the depth of 12 m ultimately merging into the aquifer. But this part is not being considered much as there is not much control of the data at this part of the profile. The particular zones between 20 m and 42 m show the vertical as well as horizontal infiltration of the natural recharge. The pathways of the moisture could be known. The relative percentage change in the electrical resistivity is quite clear as compared from the pseudosections. This clearly brings out the respective zone of the preferential recharge, shown in the zones between the two red lines, along the profile lengths of 21 m to 42 m. This specific path for the recharge is later confirmed by the self potential anomaly (Fig. 4).
Fig. 5 shows the depth wise variations in the electrical resistivity as a measure of percentage. The respective time sections are taken as the difference from an initial model to the measured ones. Fig. 5 shows the depth wise correlation and is a representative of the 2D tomograms obtained in Fig. 3. The initial dataset is considered of 211004 (T0) and the corresponding ones are as T1 = T2 = T3 = T4 =
120605–211004 250705–211004 210805–211004 110905–211004:
Changes in the electrical resistivity associated with the recharge movement are of the order of 25% at the depths of 1.5 m to 3 m. Further the variations of resistivity are 8 to 10% in the depth range of 4 to 8 m. Advancing further deep, the resistivity after the complete monsoonal cycle shows the quantitative variation of 4 to 5% within the depths of 8 to 12 m but this variation becomes negligible as the ERT measurement reaches the aquifer at the depth of 11.8 m. This gives a pathway to trace the moisture. 4.2. At site S2 inside NGRI campus The experimental field setup was laid along a profile of 70.5 m with the electrode spacing of 1.5 m (Fig. 6) at site S2. The Wenner–Schlumberger array was used to survey the profile. A total number of 529 datum points were measured at 23 data levels, which lead to the plotting of a pseudosection (Fig. 6), by the observed data sets. The acquired tomograms (Fig. 6, from a to k) are being documented. A total of 35 tomograms were obtained but those which are relevant are being shown here from a to k at site S2 (Fig. 6). The numerals along the numbering denote the date of the data acquisition. On the basis of the profile at site S2, the first layer is extremely conductive, thereby proving that in the hard rock terrene the water exists in the weathered layer, as visible in the tomograms. The layers visible below the first layer, at the depth of 2 m are more resistive. Most of the measurement devices (like the neutron probe for soil moisture, borewell for water level measurement) are situated on the eastern side of the profile. The resistivity of the underlying layers is less resistive in the profile g to k of Fig. 6, which could indicate that the recharge is more downwards along the profile. There is an overall change observed in the layers thus showing that the water flux is moving both horizontally as well as vertically. This may be confirmed with the soil moisture profile. There exists a resistive layer at the position from 30 m to 48 m at the depths of 2 m to 6 m. Also the recharge takes place at the entrance of the electrode situated at 18 m to 24 m and 54 m to 57 m. The aquifer lies at the depth below 9 m, just below the resistive body. Yet another feature interrupts the pathways of the recharge front moving at the profile, which lies at 24 m to 29.5 m at the depths of 3 m–8 m. The high resistive body just below the point of 60 m may be indicative of a boulder or some resistive material. This resistive body may either be a 3D artifact due to the small relief or the actual presence of more resistive sediments at the depths. It can also be due to the absence of minor fractures for recharge or due to the lack of connecting porosity. The data shown in Fig. 3 and the corresponding Fig. 6 from the tomograms for the site S1 and site S2 are the differenced absolute inversion rather than the difference inversions (LaBrecque and Yang, 2000; Singha et al., 2003). Undoubtedly, the difference inversions would appear somewhat different because the systematic errors from the field and the discretization errors in the forward modeling tend to cancel out. Quantitatively the percent differences in the electrical resistivities associated with the arrival of the recharge match the recharge measurement fairly well both in time and space. The match is a scorer
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for the upper layers of the pseudosection because the fluid or rainfall measurements only indicate mobile recharge (soil moisture/rainfall), whereas the ERT measures mobile and immobile salts. Changes in the electrical resistivity associated with the recharge movement are of the order of 25% to 28% at the depth of 6 m (Fig. 9) which shows the coefficient of variation of the electrical resistivity as the result of movement of the recharge front for one complete cycle. Further the variation of resistivity is 6% in the depth range of 6 m, just at the onset of the monsoon in the month of May. Advancing further deep, the resistivity after the complete monsoonal cycle after the depth of 10 m the situation is completely reverse. The overall trend shows that there is an increase of moisture up to a depth of 2 m, which is the main parameter for a drastic change in resistivity. As the front is moving, due to the connecting porosity the resistivity shows the difference but to a deeper level, due to the lack of connecting porosity or minor fracture, the resistivity is reduced. These aspects are confirmed by the soil moisture. 5. Conclusion TLERT shows that the resistivity is not constant with time and is reliable and sufficient to represent the profile (Figs. 3, 6). This also confirms and justifies the most common application of the electrical resistivity methods applied for groundwater prospecting as the resistivities do change in time, the medium being unsaturated. 1. The estimation or assessment of rainfall recharge is of utmost importance in the field of groundwater hydrology but unfortunately no method exists for its direct measurement or detection. Thus its estimation through the measurements of related parameters is subjected to errors and biasness. 2. In this work TLERT, being a non-invasive technique, has been employed to characterize the spatio-temporal variations of the rainfall recharge so that it may improve its estimation by other methods. 3. The vadose zone of the granitic terrene is investigated and analyzed using comparatively simpler approach, for example, geophysical analytical methods like time lapse electrical resistivity tomography, self potential and soil moisture measurements as
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neutron probe. The surface geophysical methods are non-invasive methods and it is much easy to carry out repetitive measurement as well as at many locations while the measurement of soil moisture through Neutron probe requires much complicated procedures of drilling the slim holes, sealing it with aluminum tubes and calibration using the known conditions etc. 4. Prior to recharge there is no continuity of moisture, but after the rainfall there exists the continuity. This property certainly questions the applicability of the piston flow assumption often made in the recharge studies. 5. The repeated TLERT could support the estimation of the rainfall recharge qualitatively and can remove biasness in other methods. 6. This application opens up the wider expertise and scope in oil fields specially in locating the position for injecting the air during exploration. The present work is a simple case study to analyse the effect of the rainfall recharge on the resistivity and an attempt to map the moisture movement through the vadose zone leading to the water table by a series of experiments for a longer period. Barker and Moore (1998) discussed this in an experiment carried out at Birmingham, England. It is clear from the visualizations of the tomograms that there is a decrease in the resistivity values at the deeper depth levels due to the migration of water from the near surface zone. This work is also an attempt for the 4-D studies of the vadose zone where the time factor acts as an important aspect for the recharge movement and its movement through the vadose zone. This work may yield realistic results under field conditions when studied jointly with the hydrological information.
Acknowledgements The authors are grateful to Dr. V.P.Dimri, Director NGRI for his consent to publish this work. This study was funded by CSIR, India. TA is grateful to CSIR for providing the fellowship to carry out the research work.
Fig. 9. Showing the variation of coefficient of variation at S2.
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