Inferring Heterogeneity in Aquitards Using High-Resolution D and ...

Inferring Heterogeneity in Aquitards Using High-Resolution D and ...

Inferring Heterogeneity in Aquitards Using

High-Resolution dDandd 18 O Profiles

by M. Jim Hendry 1 and L.I. Wassenaar 2,3


Vertical depth profiles of pore water isotopes (dD and d 18 O) in clay-rich aquitards have been used to show

that solute transport is dominated by molecular diffusion, to define the timing of geologic events, and to estimate

vertical hydraulic conductivity. The interpretation of the isotopic profiles in these studies was based on pore water

samples collected from piezometers installed in nests (typically 4 to 15 piezometers) over depths of 10 to 80 m.

Data from piezometer nests generally have poor vertical resolution (meters), raising questions about their capacity

to reveal the impact of finer scale heterogeneities such as permeable sand bodies or fractured till zones on solute

transport. Here, we used high-resolution (30-cm) depth profiles of dD and d 18 O from two continuously cored boreholes

in a till aquitard to provide new insights into the effects of sand bodies on solute transport. High-resolution

core-derived profiles indicate that such heterogeneities can cause major deviations from one-dimensional diffusion

profiles. Further, comparison of piezometer-measured values with best-fit diffusion trends shows subtle deviations,

suggesting the presence of heterogeneities that should not be ignored. High-resolution profiles also more

clearly defined the contact between the highly fractured oxidized zone and the underlying unoxidized zone than

the piezometers.


Thick aquitards are often regarded as good candidates

for waste storage because the bulk hydraulic conductivity

(K) of massive nonfractured clay-rich media is

typically , 1 3 10 -10 m/s (Gerber and Howard 2000;

Hendry 1983; Keller et al. 1986; McKay et al. 1993). At

such low K values, long-term ground water flow rates in

these deposits are estimated to be 1 m/1000 years or

lower (Hendry 1988; Keller et al. 1989; Remenda et al.

1996; Hendry and Wassenaar 1999), and as a result solute

transport is controlled by molecular diffusive

1 Corresponding author: Department of Geological Sciences,

114 Science Place, University of Saskatchewan, Saskatoon, SK,

Canada, S7N 5E2; (306) 966-5720;

2 Department of Geological Sciences, University of Saskatchewan,

Saskatoon, SK, Canada, S7N 5E2

3 Environment Canada, 11 Innovation Blvd., Saskatoon, SK,

Canada, S7N 3H5

Received November 2008, accepted February 2009.

Copyright ª 2009 The Author(s)

Journal compilation ª 2009 National Ground Water Association.

doi: 10.1111/j.1745-6584.2009.00564.x

transport instead of physical flow. Diffusive transport is

very attractive from a waste storage and management

perspective because subsurface solute (or waste) transport

is not only slow but can also be accurately predicted

in one dimension (1D), a feature almost certainly unique

to low K clay-rich geologic deposits. However, the overall

effect of small-scale (centimeters or less) spatial geologic

heterogeneities (sand streaks, fractures) has largely

been overlooked in nearly all studies of thick aquitard

deposits, and may be of sufficient importance to not be


The presence of geological heterogeneities such as

fractures (Hendry 1983; McKay et al. 1993; Gerber et al.

2001) and sand streaks (Harrington et al. 2007; Gerber

et al. 2001) is commonly encountered in clay aquitards.

These heterogeneities can be spatially extensive or discontinuous

and can create perturbations in transport flow

paths and rates. For example, lateral advective solute

transport can occur in near-surface fractured (and oxidized)

zones of aquitards (D’Astous et al. 1989; Jørgensen and

Fredericia 1992; McKay et al. 1993; McKay and Fredericia

1995; Hendry et al. 1986; Hendry 1988; Simpkins and Vol. 47, No. 5–GROUND WATER–September-October 2009 (pages 639–645) 639

Bradbury 1992) with fluid velocities up to 200 m/d

(Jørgensen et al. 1998). The average ground water velocity

in sand layers within an aquitard was estimated by

Harrington et al. (2007) be 10 2 to 10 3 m/year. Thus, solute

transport in fractured zones and sand layers can be described

as being controlled by advection within the heterogeneity

coupled with diffusion between the heterogeneity

and adjacent clay-rich matrix media (c.f. Sudicky and

Frind 1982; Harrington et al. 2007).

Field studies of the impact of small-scale spatial heterogeneities

on overall solute transport in clay aquitards

are notably absent. This absence can be attributed to the

collection of vertical depth profiles of solutes (and stable

isotopes as conservative tracers of water) in most aquitards

from nested piezometers at the meter scale, exceeding

the finer spatial detail relevant to define smaller-scale

heterogeneities. Piezometer nests in aquitards traditionally

consist of multiple or bundled piezometers completed

at vertical intake spacings of 1.0 m or more. As

a result, geochemical and isotopic data collected from

these piezometers may have insufficient vertical spatial

resolution to identify heterogeneity related solute transport

mechanisms. Vertical spatial resolution of geochemical

and isotopic parameters is further compromised by

the use of long piezometer intake zones (typically 0.6 to

3 m long).

Solute transport modeling in aquitards is typically

done using simple 1D (vertical) diffusion theory. Comparisons

between measured field data and simulated 1D

diffusive profiles often provide excellent coarse fits, but

sometimes result in puzzling offsets, poor fits, or inexplicable

outliers (c.f. Desaulniers et al. 1981; Remenda

et al. 1994, 1996; Husain 1996). Whether outliers are the

result of inappropriate assumptions in the diffusion

transport model, inherent errors within the data (e.g.,

leaky piezometer seals, poor analyses), or missing information

(e.g., small-scale heterogeneities) is not clear,

and these outliers are rarely discussed. The omission of

small-scale heterogeneities is likely to result in an erroneous

interpretation of solute migration, which can have

serious implications for estimates of contaminant


Here we examined the influence of geologic heterogeneities,

consisting of a discrete permeable sand layer

and near-surface fracturing on solute transport in a claytill

aquitard using high-resolution vertical profiles of

d 18 O and dD. High-resolution d 18 O and dD depth profiles

were obtained from continuously cored boreholes using

aH 2O (liquid)-H2O (vapor) pore water equilibration and laser

spectroscopy technique (Wassenaar et al. 2008). We compared

our high-resolution data with data collected from

adjacent traditional piezometers.

Study Site

Our study was conducted at a long-term aquitard

research site (King Site) in southern Saskatchewan, about

140 km south of Saskatoon, Canada. The aquitard site

covers a surface area of about 200 3 400 m. Geologic

heterogeneities (oxidized fractured zone overlying a massive

nonfractured zone and a sand layer) were found at

the site, and the site is hydrogeologically well characterized

and instrumented with more than 45 conventional

piezometers completed at depths less than 45 m below

ground surface (bgs). The near-surface geology consists

of approximately 80 m of clay-rich Battleford till (Shaw

and Hendry 1998). Hydrogeological and hydrochemical

studies over the past decade show the upper 3 to 4 m of

the till is oxidized and fractured and the underlying till is

unoxidized and apparently nonfractured (Shaw and

Hendry 1998). The K of the unoxidized and unfractured

till is low (K , 10 -10 m/s) with a downward groundwater

velocity between 0.5 and 0.8 m/10 ka (Shaw and Hendry

1998; Hendry and Wassenaar 1999). By contrast, the K of

the oxidized and fractured till is greater and more variable

(Harrington et al. 2007) and the groundwater flow system

is dynamic, responding to spring snowmelt and precipitation

events (Shaw and Hendry 1998). The water

table, located in the fractured zone, ranges seasonally

from 0 to 3 m bgs. Solute transport is dominated by diffusion

in the unoxidized till zone and by fracture flow in the

oxidized till zones (e.g., Harrington and Hendry 2005;

Hendry and Wassenaar 1999, 2000; Hendry et al. 2000).

Recent testing revealed the presence of a medium- to

coarse-grained sand layer of highly variable thickness

(,2 mmto51 m thick) within the clayey aquitard matrix

across the site (Harrington et al. 2007). A discontinuous

sand layer was observed between 12 and 15 m bgs and,

based on grain-size data, the K of the sand is estimated to

range between 1 3 10 -2 and 2 3 10 -2 m/s (Harrington

et al. 2007).

Sampling and Analyses

Pore Water dD and d 18 O

Continuous core samples were obtained from two

new boreholes (BV1 and BV2) located 70 m apart collected

in December 2007. BV1 was located in an area of

the study site where no apparent sand layer was expected;

BV2 was located in an area with a known sand layer.

Cores were collected with a split spoon sampler (1.5 m

long 3 71 mm ID) starting at the water table (3.6 m bgs).

Coring at BV1 was terminated at 15.4 m bgs because of

refusal (large rock). Coring at BV2 was terminated at

18.3 m bgs. A sand layer was encountered in BV2 from

9.8 to 15.9 m bgs. Coring was limited to 11.0 to 12.2 and

14.0 to 15.9 m bgs in this zone. Free water was not

observed in BV1, but was present in BV2 originating

from the saturated sand layer.

Subsamples (~75 mm long) were taken from the

cores every 30 cm. The outer 15 mm was removed with

a putty knife immediately after collection to minimize

contamination of the subsamples by drilling procedures.

All core subsamples were placed into labeled, double

sealed, polyethylene bags in the field and stored in coolers

for immediate transport to the laboratory. Samples

were analyzed in the laboratory for the dD and d 18 Oof

640 M.J. Hendry, L.J. Wassenaar GROUND WATER 47, no. 5: 639–645

pore water using H 2O (liquid)-H2O (vapor) pore water equilibration

and laser spectroscopy (Wassenaar et al. 2008).

The accuracy and precision of this method, based on

using standard waters and the analysis of replicate core

samples, were better than 60.2& for d 18 O and 60.5&

for dD. Details of the core sample collection and analytical

methods are presented in Wassenaar et al. (2008). In

addition, water samples were collected from 45 piezometers

installed at depths , 45 m bgs in two series

(B- and BJ-series). The water samples were analyzed for

dD andd 18 ObystandardCO2-water and H2-water equilibration

techniques and laser spectroscopy (Lis et al. 2008).

Transport Modeling of dD and d 18 O Depth Profiles

The effective diffusion coefficient (D e) for diffusive

transport of dD through a porous medium is defined as:

De ¼ Dos ð1Þ

where Do is the diffusion coefficient in free water and s is


The 1D diffusive transport of a conservative solute

through a homogeneous and isotropic media can be

described by Fick’s first law:


Jdiff ¼ neDe



where C is the solute concentration, ne is the effective

porosity, and x is the distance in the direction of transport.

Under transient conditions, the diffusive mass transport is

calculated by combining the continuity equation with

Fick’s first law (Equation 2). Expressing it in Fick’s second

law for 1D transport yields:




¼ De

2C @x2 ð3Þ

where @C/@t defines the change in concentration with

time in the x-direction.

The numerical model POLLUTEv6 (Rowe and

Booker 1997) was used to solve Equation 3 for dD profiles

from the continuously cored profiles and from the

two piezometer nests over time, assuming a homogenous

semi-infinite unoxidized till (i.e., no sand body). For consistency,

the solutions were obtained assuming a D e of 1.7 3

10 -10 m 2 /s for this till aquitard based on radial diffusion

cell testing (Hendry and Wassenaar 1999). In simulations

of the downward migration of dD in a nonhomogeneous

unoxidized till (i.e., till containing a sand body), a De of

1.7 3 10 -8 m 2 /s was assigned to the sand to ensure mixing

across the sand lens. The POLLUTE modeling results

for the homogenous semi-infinite unoxidized till were

confirmed with an analytical solution to Equation 3 from

Shackelford (1991). The fit between the modeling results

and field data was optimized using the least mean squared

error method (MSE) (Hayter 1996), in which the MSE

was optimized by varying the time to develop the profile

in the numerical solution.

Results and Discussion


The depth to the contact between the oxidized and

unoxidized zones (based on color change) was between

3.9 to 4.3 and 4.6 to 4.9 m bgs at BV1 (Figure 1) and

BV2 (Figure 2), respectively. These depths are somewhat

deeper than those reported by Shaw and Hendry (1998)

(3 to 4 m bgs) and demonstrate the depth to this transition

is not constant across the study site. A thin saturated sand

streak (~2 mm thick) was encountered at 14.0 m bgs at

BV1, and a thick saturated sand layer (5.4 m thick) was

encountered at 10.2 to 15.4 m bgs at BV2. The presence

of this discontinuous sand layer is supported by recent

data from the site (Harrington and Hendry 2005; Harrington

et al. 2007). Harrington and Hendry (2005) confirm the

considerable variability in the thickness of this sand layer

(0.8 to 4.5 m). The lack of free water in holes drilled for

the installation of the piezometers (Shaw and Hendry

1998) reveals the sand lens is either very thin or laterally

discontinuous across the site. The range in the reported

thickness demonstrates that predicting the presence of

sand layers in these deposits is difficult, even across

a small test site. Because sand layers ranging in thickness

over short distances are common in clay tills in the Interior

Plains of North America (Hendry, unpublished data;

Burnett 1981), the conditions observed at the King site

are likely to be representative.

Figure 1. High-resolution dD depth profile from core samples

collected below the water table at BV1. The analytical error is

represented by horizontal bars and the field-determined

depths to the contact between the oxidized and unoxidized

till zones and the sand streak are shown. The open box

and whisker data reflect the depth to the water table measured

in a water table well at the site (1995 to 2008; unpublished

data). The solid line represents the best-fit simulated diffusion

profile (commencing about 14 ka BP) assuming no sand streak

present. M.J. Hendry, L.J. Wassenaar GROUND WATER 47, no. 5: 639–645 641

Figure 2. High-resolution dD depth profile from core samples

collected below the water table at BV2. Symbols are as

in Figure 1. The solid line represents the best-fit simulated

diffusion profile commencing about 9 ka BP, and the dashed

line represents the simulated diffusion profile commencing

about 14 ka BP.

dD and d 18 O Profiles

In Figure 3, a cross plot of dD vs. d 18 O of pore water

from BV1 and BV2 cores and the piezometers illustrates

a well-defined linear correlation. The dD and d 18 O data

from the BV cores and piezometers fell within the 99%

CI of the Saskatoon precipitation regression (Environment

Canada, unpublished data, 2009), and hence showed no

significant isotopic deviations from the Saskatoon local

meteoric water line (LMWL). The range in dD and d 18 O

data along the LMWL is the result of mixing of modern

isotopically positive pore waters with older isotopically

depleted pore waters (Hendry and Wassenaar 1999). The

strong correlation between the dD and d 18 O data allowed

us to focus our discussion on one isotope. We selected

the dD because it had a smaller analytical error relative to

the range in concentration compared to d 18 O.

Piezometer samples

Detailed vertical profiles of dD from the B- and

BJ-series piezometers yield similar shaped depth profiles

(Figure 4). The large range in dD values from the five

piezometers completed in the oxidized till zone (–146&

to –127&) reflects the dynamic nature of water migration

in this zone. Below the oxidized-unoxidized contact, the

profile exhibits a classic diffusion-shaped curve. The

trends with depth are the same as described by Hendry

and Wassenaar (1999).

The lowest dD value of –178& between 36 and

44 m bgs is attributed to paleoglacial melt waters incorporated

into the till during its deposition in the late

Pleistocene (Hendry and Wassenaar 1999; Remenda et al.

1994). Hendry and Wassenaar (1999) also attribute the

Figure 3. Cross plot of dD and d 18 O data obtained from

cores and piezometers compared to the Saskatoon LMWL

(1990 to 2007; Environment Canada). Closed diamonds and

closed triangles are data from core samples collected from

BV1 and BV2, and open circles are data from piezometers

installed at the site with depths

Figure 4. Detailed dD depth profile from porewater samples

collected from B- and BJ-series piezometers (open triangle

and open diamonds, respectively). The horizontal and vertical

bars through the data points represent the standard deviation

in the analyses and the length of the piezometer intake

zone (symbols represent the middepth of intake zones),

respectively. The open box and whisker data reflect the

depth to the water table measured in a water table well at

the site (1995 to 2008; unpublished data). The approximate

location of the contact between the oxidized and unoxidized

till zones (3.8 m) is from Hendry and Wassenaar (1999). The

solid and dashed lines represent the best-fit simulated diffusion

profile to the B- and BJ-series piezometer data. For

comparison, the best-fit simulations for the core data from

BV1 and BV2 (dot-dash and long dashes, respectively) are

also presented.

Unlike pore water depth profiles for dD at BV1,

which show no effect of the 2 mm sand streak, the presence

of the thicker sand layer at BV2 is clearly evident in

the dD data. It is reflected by a relatively uniform (i.e.,

well-mixed) dD value through the entire thickness of the

sand layer (–162&), with diffusive mixing trends in both

the overlying and underling aquitard material.

Transport of dD

Figure 1 shows a best-fit 1D diffusive transport

model for the BV1 profile in the unoxidized zone, assuming

a fully homogeneous till aquitard (no sand streak

included in the model). This fit was determined using the

upper boundary condition defined at the oxidizedunoxidized

contact (3.8 m bgs; –138&). In these simulations,

the initial dD value throughout the profile was

assumed to be –178& (rationale presented in Hendry and

Wassenaar [1999]). The model results yielded an excellent

fit to the high-resolution core data (MSE ¼ 0.9); in

this case the time required to develop the diffusion profile

was 14 ka BP. The lack of significant ‘‘outliers’’ in the

measured data vs. model confirms that the thin 2 mm

sand streak exerts no measurable effect on the vertical dD

profile at the resolution of the profile (30 cm).

Figure 2 shows the best-fit simulated profile for

BV2. This fit was determined using the upper boundary

condition defined at the oxidized-unoxidized contact (4.7 m

bgs; –141&). As for BV1, the initial dD value throughout

the profile was assumed to be –178&. This simulation

fit the measured values well (MSE ¼ 0.8). This

‘‘best fit,’’ however, required a time of evolution of 9 ka

BP, or nearly ~5 ka less than the BV1 data at the same

study site. Simulating the profile using a time frame of

14 ka, as obtained for BV1, provided a very poor fit to

the BV2 data (Figure 2; MSE ¼ 31.7) and greatly overestimated

the measured dD profile (e.g., the simulated

value in the sand layer was ~4& higher than the field

measured values). Although speculative, the variability in

dD in the sand layer may be the result of vertical heterogeneity

in the K of the sand. The presence of dD values

lower than the simulated values to 1.5 m below the

measured base of the sand layer may suggest that the base

of the sand layer may be deeper than observed in close

proximity to BV2.

The poor fit between the simulation and field data

for BV2 using a 14 ka development time can be attributed

to the assumption of simple 1D diffusive transport while

ignoring the lateral transport effect of the sand layer on

the dD profile (Harrington et al. 2007; discussed subsequently).

Transport simulations (not presented) that

removed dD from the sand layer to reflect lateral solute

transport support this hypothesis and yield very good fits

to the measured data for the 14 ka simulation time.

Because original dD values in the sand and the distribution

of the sand layer across the site are not known, no

additional information could be gleaned from this profile.

Further, our modeling assumes that the onset of diffusion

at BV1 and BV2 commenced at about the same time.

Because the core holes are in close proximity, this

assumption was considered reasonable.

As noted previously, long-term solute transport in

aquitards is most commonly determined by simulating

coarsely spaced piezometer data to yield a best fit to the

field data in 1D (c.f. Desaulniers et al. 1981; Remenda

et al. 1994; Hendry and Wassenaar 1999). In keeping with

this approach, best-fit diffusion profiles for both B- and BJseries

piezometer data in the unoxidized zone were determined

using upper boundary and initial values and depth to

the top of the unoxidized till zone of –138&, –178&, and

3.8 m bgs, respectively (Figure 4). Results of the best-fit

simulations for both piezometer series were similar (MSE

¼ 0.9). The differences between the simulated profiles

were mostly minor, with the B-series well data being on

average ,1& lower than the BJ-series piezometers. Most

striking, however, was that these two measured piezometer

profiles provided no evidence for the presence of the sand


The time to generate the BJ-series profile (~13 ka

BP) was in good agreement with data from BV1

(Figure 4). This suggests the BJ-series profile is not

affected by the presence of the sand layer. By contrast,

however, the time to generate the B-series (10 to 11 ka

BP) is considerably less than for the BJ and BV1 profiles M.J. Hendry, L.J. Wassenaar GROUND WATER 47, no. 5: 639–645 643

and the fit is not as good for B-series between 15 and

30 m bgs (Figure 4). This suggests the B-series profile is

subtly affected by the presence of the sand body.

To further assess the effect of a sand body on the piezometer

profiles, we compared the dD data from the piezometers

to the simulated fits for the BV1 and BJ-series

piezometers (Figure 4). Three B-series piezometers completed

at the depth of the sand body (9.9, 11.4, and 13.0 m

bgs) plotted above our best-fit simulated profiles, suggesting

these piezometers are indeed influenced by the sand

layer. Profiles of dissolved Cl - from the two piezometer

nests (Figure 5) confirm the subtle displacement of these

data is attributed to advective solute transport in the sand

layer as evidenced by the peak in Cl - between 10 and 15 m

bgs. Hendry et al. (2000) and Harrington et al. (2007) indicate

the Cl - in the peak originates upgradient from the study

site and show the decrease in Cl - above and below the peak

is the result of diffusion of Cl - from the sand layer into the

surrounding till over the past 5 kyr. This observation implies

that even minor outliers in the measured isotopic data

from idealized vertical 1D profiles cannot be ignored

because they can reflect the presence of heterogeneities that

can affect overall solute transport in the aquitard. Further,

the presence of the outliers observed at the King site was

the result of the installation of an unusually great number of

piezometers. If three to four piezometers had been installed

over the depth of interest, as is typically the case, we may

not have observed the effect of the sand layer and again

misinterpreted solute transport at the site.

Figure 5. Porewater Cl - vs. depth profiles from porewater

samples collected from B- and BJ-series piezometers (open

triangle and open diamonds, respectively). The horizontal

and vertical bars through the data points represent the standard

deviation in the analyses and the length of the sand

pack (symbols represent the middepth of intake zones),

respectively. The open box and whisker data reflect the

depth to the water table measured in a water table well at

the site (1995 to 2008; unpublished data).


This study showed that high-resolution (30-cm) profiling

of dD and d 18 O of pore water from core samples

can be used to better define the hydrogeology of near surface

clay-rich aquitards, especially at sites requiring

a detailed and thorough understanding of the risk of longterm

solute migration. These high-resolution profiles suggest

that they can be used to define the contact between

zones characterized by dynamic water movement in the

oxidized zone and diffusion-dominated transport in the

underlying unoxidized zones, in good agreement with

the color change between these two zones. Because the

likelihood of sand layers of very variable thickness and

distribution within till aquitards is great, even across sites,

high-resolution profiling shows limiting profiling to only

one or two ‘‘representative’’ locations should be avoided.

At the scale of our measurement, the effects of a thin

(,2 mm) sand streak on solute transport were not evident.

By comparison, the impact of the sand layer on solute

transport based on dD andd 18 O profiles collected from

piezometer nests was poorly defined and suggests any subtle

deviation in these profiles from a simple 1D (vertical)

diffusion profile warrants study. Finally, defining long-term

solute transport using simple 1D models with dD andd 18 O

profiles from limited piezometers may be problematic, and

basing the interpretation of transport in aquitards solely

on the isotopes of water can be misleading; the use of a

halogen or additional tracers in conjunction with the stable

isotopes of water should be considered for defining

hydrogeologic zonations (permeable sand layer vs. clay



V. Chostner provided assistance with sample collection

and analyses and A. Jensen assisted with transport

modeling. S.L. Barbour reviewed a draft of this manuscript.

Comments provided by Andrew Herczeg, Tim

Eaton, and an anonymous reviewer improved the quality

of the manuscript. Financial support was provided by the

Natural Sciences and Engineering Research Council of

Canada, Cameco Co. Ltd., and Saskatchewan Potash

Producers Association to MJH. Environment Canada

provided funding to LIW.


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