Hydrodynamic Factors Affecting The Persistence Of The Exxon Valdez Oil In A Shallow Bedrock Beach

1. Hydrodynamic factors affecting the persistence
of the Exxon Valdez oil in a shallow bedrock beach
Yuqiang Xia,1,2
Hailong Li,1,2
Michel C. Boufadel,2
and Youness Sharifi2
Received 4 February 2010; revised 8 June 2010; accepted 12 July 2010; published 16 October 2010.
[1] We report a field study and numerical modeling of multicomponent flow in a tidal
gravel beach in Knight Island, Prince William Sound, Alaska, where oil from the
1989 Exxon Valdez oil spill persisted. Field measurements of water table, salinity, and
tracer (lithium) concentration were obtained for around a week during the summer of 2008.
The numerical model MARUN was used to simulate the field observations. On the basis
of field experiments and numerical simulations, the beach was identified to have a
two‐layered hydraulic structure: a high‐permeability surface layer underlain by a
low‐permeability lower layer. The hydraulic conductivity was found to be 5 × 10−2
m s−1
for the surface layer and 7 × 10−6
m s−1
for the lower layer. The simulations reproduced the
observed water table, salinity, and lithium concentrations accurately. The small flow
entering the beach from the land side resulted in a beach water table dropping below the
interface of the two layers. This seems to be the major reason for the presence of oil in the
lower layer. The exchange flow between the beach and the sea due to tidal influence
was ∼2.12 m3
d−1
m−1
. The patterns of inflow and outflow rates showed that the maximum
seawater‐groundwater exchange occurred in the middle to high intertidal zone, which
explains the persistence of oil in the lower intertidal zone. To explore bioremediation of
the beach with nutrient amendment, a numerical simulation of nutrient application on the
beach surface was conducted, where the applied nutrient concentration was 5,000 mg L−1
.
The results showed that the nutrient concentration remaining in oiled areas after a
week was larger than 50 mg L−1
, which is larger than that needed for maximum microbial
growth (2–10 mg L−1
). This implies that the bioremediation via nutrient application on the
beach surface could be adopted if nutrients were the only limiting factor.
Citation: Xia, Y., H. Li, M. C. Boufadel, and Y. Sharifi (2010), Hydrodynamic factors affecting the persistence of the Exxon
Valdez oil in a shallow bedrock beach, Water Resour. Res., 46, W10528, doi:10.1029/2010WR009179.
1. Introduction
[2] The 1989 Exxon Valdez oil spill polluted around
800 km of rocky intertidal shorelines within Prince William
Sound (PWS), Alaska [Bragg et al., 1994; Neff et al., 1995].
Recent studies by scientists from the National Oceanic and
Atmospheric Administration (NOAA) [Short et al., 2004,
2006] estimated that between 60 and 100 tons of subsurface
oil persist in many initially polluted beaches along PWS.
The persistence of oil was noted by other studies [Michel
and Hayes, 1999; Taylor and Reimer, 2008; Li and Boufadel,
2010]. Carls et al. [2001] showed that intertidal mussel
beds with significant contamination included most previ-
ously oiled areas in PWS, particularly within the Knight
Island group and the Kenai Peninsula. Short et al. [2006]
reported that sea otters and ducks would encounter subsur-
face lingering Exxon Valdez oil in northern Knight Island
while foraging there.
[3] To restore oiled beaches [Michel et al., 2006], it is
necessary to have a thorough understanding of the beach
hydrogeological characteristics [Owens et al., 2008]. How-
ever, research on gravel beaches has been dominated by
geomorphological and sedimentological studies of sediment
character [Buscombe and Masselink, 2006; Horn and
Walton, 2007]. Few studies have attempted to examine the
groundwater flow and solute transport in gravel beaches.
Recently, Li and Boufadel [2010] demonstrated the hydro-
geological mechanism contributing to the persistence of
subsurface Exxon Valdez oil in a gravel beach on Eleanor
Island, PWS. The beach reported by them is a sedimentary
single pocket beach with a thickness of 3 m and there was
freshwater recharge from the inland. The beach in this study
is on Knight Island, and is a “sheltered bedrock/rubble”
[Michel and Hayes, 1999; Page et al., 2008]. It is also
around 11 km from the beach investigated by Li and Boufadel
[2010]. Knight Island, in western PWS (Figure 1a), was
heavily polluted by the Exxon Valdez oil spill [Neff et al.,
1995; Peterson et al., 2003], and is site to the most exten-
sive subsurface oil residues and the highest average total
petroleum hydrocarbon concentrations [Taylor and Reimer,
2008].
1
School of Environmental Studies and Biogeology and
Environmental Geology Laboratory, China University of Geosciences,
Wuhan, China.
2
Department of Civil and Environmental Engineering, Temple
University, Philadelphia, Pennsylvania, USA.
Copyright 2010 by the American Geophysical Union.
0043‐1397/10/2010WR009179
WATER RESOURCES RESEARCH, VOL. 46, W10528, doi:10.1029/2010WR009179, 2010
W10528 1 of 17

2. [4] The present investigation has two goals. The first is to
identify beach hydrogeological characteristics and the sec-
ond is to relate them, if possible, to the persistence of the
Exxon Valdez oil spill. For this purpose, our investigations
targeted an oiled transect of a tidal gravel beach (KN0114A)
at the coordinates 147° 47′ 24.34″ W, 60° 29′ 5.56″ N in
northern Knight Island (Figure 1). Three observation wells
(W3, W4, and W5) and piezometers were installed in the
transect (Figures 1b and 1c), and field results were com-
plemented with numerical simulations using MARUN
[Boufadel et al., 1999b]. The pattern of tide‐induced cir-
culation was investigated numerically to provide insights
into the factors affecting the subsurface lingering of the
1989 Exxon Valdez oil spill in this area. In addition,
amendment of the beach with nutrient on the surface was
investigated to explore the bioremediation of oil on this
beach.
2. Methods
[5] Beach topography (Figure 1c) was surveyed using the
Electronic Total Station (SET330R3, SOKKIA CO. LTD,
Japan). The landward side of the transect is bounded by a
cliff (Figure 1b). During high tides, the whole beach surface
becomes submerged by seawater (Figure 2) and the water
line covers around 5 m of the rock formation at the foot of
the cliff. The beach slope varied as one moves seaward. It is
11% between 0 and 5.7 m, 3.8% between 5.7 m and 8.65 m,
9.5% between 8.65 m and 12.05 m, 4.8% between 12.05 m
and 17.4 m, and 14% seaward of 17.4 m.
[6] The beach surface consists of coarse sediments (peb-
bles, cobbles, and boulders) intertwined between rocks, its
thickness revealed in field investigation is typically less than
0.6 m. The lower layer consists of compacted coarse sedi-
ments (with occasional boulders) and fine‐grained sedi-
ments, which is underlain by the impermeable bedrock
(Figure 2). In general, the oil patch was around 30 cm deep
and around 5 cm thick. However, oil was also found at
shallower depths, almost at the surface. The oil was in the
amount of Heavy Oil Residue (HOR), according to the
ASTM F1687–97, 2003 classification. Studies [e.g., Page
et al., 2008; Boehm et al., 2008] noted that the positions
and extents of oil plumes did not change between mea-
surements conducted in 2001 and those conducted in 2007.
This indicates that oil is entrapped in the small pores in the
beach (i.e., residual oil). Therefore, the effect of oil on water
flow is probably minor, as the conveyance of water flow in
the large pore is much larger than those in the small pores.
In addition, the natural variability of permeability of intact
sediments is probably comparable to the local effects of oil.
Therefore, it is reasonable to neglect the effect of oil on
water flow in this beach.
[7] Along the transect, three pits (W3, W4, and W5) were
hand dug down to a maximum depth 0.60 m whenever
Figure 1. (a) Location of the selected beach (KN0114A)
in Knight Island, Prince William Sound, Alaska (147°
54′∼147°18′W, 60°48′∼59°24′ N). The 1989 Exxon Valdez
oil spills contaminated Knight (KN) Island, the Kenai Pen-
insula (KP), the Kodiak Island archipelago (KI), the Alaska
Peninsula (AP), Montague Island (MI), and other Prince
William Sound islands [after Peterson et al., 2003]. (b) Site
picture. Cliff on the landward side of the beach and three
observation wells (W3, W4, and W5) are shown. Note that
surrounding big rocks screened the view of W5 in this picture.
“W” preceding the numbers is for the wells. (c) Topographic
contours of the beach and locations of three observation
wells. The area where the oils persist is shaded. The manifold
for tracer application between W3 and W4 is represented by
a black bar.
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3. possible. The detailed information about pits and other
locations is presented in Table 1.
[8] In each pit, a PVC pipe and a multiport sampling well
were installed vertically. The PVC pipe was already slotted
across over the whole length to allow water passage. A
pressure transducer (MiniDiver, data logger) was placed at
the bottom of the PVC pipe to record the water pressure
every 10 min from 20 June 2008 15:45 P.M. (initial time t = 0
in this paper), and the measurement durations differed with
the locations. It varied from 4 days and to around 6 days.
[9] The barometric pressure, monitored by an air pressure
sensor (BaroLogger, DL‐500, Schlumberger), was subtracted
from the readings of the pressure transducers to obtain the
water level. During the field study, rainfall occurred during
00:00 A.M. to 8:00 A.M. of 22 June 2008 (time from 33 h to
41 h on the graphs). The total precipitation, measured using
a makeshift rain gauge, was 1.5 cm.
[10] The multiport sampling wells were made of stainless
steel and contained ports at various levels. The ports were
spaced at the interval of 0.23 m and were labeled A, B, C,
and D from the bottom up. Each port was connected via a
tubing that extended to the top of the pipe. A tygon tube was
placed on each of the tubings, and it was connected to a luer
lock three‐way valve. To prevent blockage by fine sedi-
ments to guarantee good hydraulic connection between the
beach pore water and the water inside the well, the multiport
wells were wrapped with fine stainless steel screen.
[11] After the pit excavation for well installation, the pits
were filled with the extracted sediments, which were rela-
tively loose in comparison to the surrounding material
within the pit. This provided an unwanted increase in the
permeability in the pit, which we refer to as the “pit effect.”
[12] A tracer study was conducted by applying seawater
solutions of lithium nitrate (lithium was the conservative
tracer) on the beach surface through a manifold placed
between W3 and W4. The manifold was a perforated 5 m
long, 1.5 inch ID PVC tube that contained 2 mm orifices
uniformly distributed along its whole length. The orifices
were turned upward, and the uniformity of the height of
water jets was achieved by adjusting the elevation of the
Figure 2. Schematic cross section of the beach. Well locations and tracer application location are
shown. The tidal range is around 4.8 m. The intersection of the low tide mark with the beach face occurs
at x = 30.0 m, z = 0 m. The interface of the surface and lower layers is also shown. Detailed information
about wells and other locations is presented in Table 1. Four different boundary conditions used are
represented by different lines: boundary condition 1, zero flow and zero mass transport; boundary con-
dition 2, specified water pressure equal to the tidal seawater depth above the boundary point and salinity
dependent on the flow direction (at each location on the beach surface, seawater concentration was
assigned when the flow enters the domain from the sea, and zero concentration gradient was assigned
when the flow leaves the domain); boundary condition 3, tidal moving boundary condition (the same as
boundary condition 1 in the portion emerging in the air and the same as boundary condition 2 in the
portion submerged in the seawater); and boundary condition 4, specified freshwater flux from inland and
salinity of 0.0 g L−1
.
Table 1. Surface Elevation and Depths of Two Layers at Different
Locations
Locationsa
x (m)
Surface
Elevation (m)
Thickness of
Surface Layer (m)
Depth to
Bedrock (m)
LBc 0.0 2.98 0.17 0.56
W3 0.30 2.95 0.30 0.56
MT 2.57 2.69 0.29 0.60
W4 5.70 2.34 0.28 0.63
W5 8.65 2.22 0.25 0.58
L1 12.05 1.90 0.10 0.58
L2 17.40 1.64 0.10 0.58
RBc 40.0 −1.50 0.10 0.58
a
LBc and RBc denote the landward and seaward boundaries of transect,
respectively. L1 and L2 are only used to delineate the geometry of the
surface and interfaces, as no wells were installed at these locations. MT
denotes the location of manifold from which the tracer was applied onto
the beach surface.
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4. manifold. For example, if the height of the jets was high at
the right end of the manifold, then that end was raised by
shimming a pebble underneath it, which caused the height of
the jets at that location to decrease.
[13] The tracer solutions were pumped from two 200 L
tanks in sequence. The first tank contained a concentration
of 3,290 mg L−1
of lithium nitrate and was used in the first
55 min, and the second tank contained a concentration of
4,350 mg L−1
of lithium nitrate and was used in the next
50 min. The corresponding lithium concentrations of tracer
solution were 329 mg L−1
and 435 mg L−1
, respectively.
The difference in concentration was because it was not
feasible to accurately measure the water volume in the tanks
because they got deformed upon placement on uneven
pavements. The flow rate per unit length of the 5 m long
manifold was 86 ± 9.1 L h−1
m−1
. The application occurred
during the falling tide; it started at 21 June 2008 8:30 A.M.
(t = 16.75 h) and lasted for 1 h and 45 min. During tracer
application, no ponding was observed on the beach surface.
[14] Pore water samples were obtained mainly within
5 h after the tracer application (time from ∼17 h to ∼22 h;
see Figure 5). They were approximately 40 mL, and were
collected with 60 mL luer lock syringes from the multiport
sampling wells and placed in 125 mL polyethylene bottles
(Fischer Scientific, Fairlawn, NJ). The samples were shipped
to the laboratory at Temple University for chemical analysis
of chlorine and lithium concentration. The chlorine concen-
tration was transformed into salinity using the well‐known
chlorine‐salinity ratio of 19.4:35 [Duxbury and Duxbury,
2001] for each of the total 62 samples. The average salinity
in samples collected from the seawater adjacent to the beach
was 24.2 g L−1
. The lithium concentrations of 55 samples
were measured by atomic absorption spectroscopy with an
air‐acetylene flame at 670.8 nm (210VGP Atomic Absorp-
tion Spectrophotometer, Buck Scientific, Inc).
[15] Because we did not have pressure sensors that were
capable of capturing the elevation of the low tide, we fitted a
theoretical expression of tide [Merritt, 2004] to the observed
open water level at W5. The analytical expression was
HTide t
ð Þ ¼ hMSL þ
X
5
i¼1
Ai cos !it þ 8i
ð Þ; ð1Þ
where HTide is the tide level, hMSL denotes the mean sea
level, and the summation represents five harmonic compo-
nents (O1, K1, M2, S2, and N2; see Table 2) for tides. The
parameters Ai, wi and 8i are the amplitude (m), frequency
(rad h−1
) and phase shift (rad) of the ith component of tide,
respectively. The mean sea level and the value of the 5 tidal
components were estimated by the least square method, and
their values are listed in Table 2. Although the theoretical
expression for tide contains 17 components, experimenta-
tion with the expression [Li and Boufadel, 2010] revealed
that five components are sufficient. The observed and sim-
ulated tidal levels are reported in Figure 3.
[16] A two‐dimensional numerical model was employed
to reproduce the observed water level, salinity and tracer
Figure 3. Measured water level above surface of W5 (circles) and tidal level fitting results (solid line)
used in the numerical simulations. Elapsed times are defined as number of hours since 20 June 2008
15:45 P.M. (the start time for field monitoring works, t = 0). An entire spring‐neap tide cycle is shown.
Tidal parameter values are also presented in Table 2.
Table 2. Fitting Results of Sea Tidesa
Harmonic
Component i
Amplitude
Ai (m)
Phase Shift
8i (rad) Explanationb
1 0.274 3.107 Main lunar diurnal (O1),
w1 = 0.243 rad h−1
2 0.620 3.724 Lunar‐solar diurnal (K1),
w2 = 0.262 rad h−1
3 1.331 −1.397 Main lunar semidiurnal (M2),
w3 = 0.506 rad h−1
4 0.249 −1.193 Main solar semidiurnal (S2),
w4 = 0.524 rad h−1
5 0.239 −4.401 Lunar elliptic (N2),
w5 = 0.496 rad h−1
a
Mean sea level hMSL = 2.358 m.
b
Detailed explanations can be found in work by Merritt [2004, Table 4].
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5. concentrations. Details about the numerical model and its
implementation are presented in section 5.
3. Field Results
[17] Figure 4 reports the observed water tables at wells
W3, W4, and W5. It shows that the observed water table at
W3 kept falling at the same speed as that of the tide for a
while after the beach surface was exposed. After that, the
water table elevation abruptly separated from falling tides
and was approximately constant until subsequent flood tide
arrived. The same behavior was observed at other wells
(W4 and W5) on the transect (Figure 4). This was also
observed in the sedimentary gravel beach on Eleanor Island
investigated by Li and Boufadel [2010]. This behavior of
water table variation indicates a two‐layered beach structure:
a high‐permeability surface layer underlain by a low‐
permeability layer. The surface layer would have a perme-
ability so high such that the water table within it falls as fast
as the falling tide. The lower layer would have a perme-
ability so low that the water table does not drop much within
it. This behavior of water table variation is different from
that observed in a homogeneous beach where the dropping
velocity of the water table is more or less smooth [e.g.,
Figure 4. Observed (circles) and simulated (solid lines) water table at W3, W4, and W5. The sudden
change in the movement of the water table suggests the presence of two layers. The tidal level and the
elevations of the beach surface, of the interface, and of the pressure transducers (PT) installed at these
observation wells are shown.
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6. Nielsen, 1990; Robinson and Gallagher, 1999; Gibbes et al.,
2008].
[18] The average salinity of samples collected in the
seawater adjacent to the beach was 24.2 g L−1
. Figure 5
shows the observed salinity variation with time at different
depths (labeled with Ports A and B) of wells W3, W4, and
W5. The salinity ranged from ∼16 g L−1
to ∼24 g L−1
with
the average of 20 g L−1
for t ≤ 30 h. However, it decreased
for t ≥ 40 h to reach around 12 g L−1
. This is probably due to
the rainfall that occurred during the period 33–41 h (1.5 cm
of rainfall). Thus, it can be concluded that, in the absence of
rainfall, little or no freshwater flow enters the beach from the
landward side.
[19] Figure 6 shows the observed lithium concentration of
the pore water at different ports (each corresponding to a
different depth) of wells W3, W4, and W5. The tracer
concentration at well W3 which is landward of application
manifold reached a maximum of around 1.0 mg L−1
. The
tracer concentrations at wells W4 and W5 reached much
larger values. At W4, they reached 251 mg L−1
at Port A
and 378 mg L−1
at Port B. At W5 they reached 171 mg L−1
at Port A and 210 mg L−1
at Port B. These results indicate
that main movement of the applied tracer was seaward of the
manifold and downward, but a landward movement
accompanied with a great dilution existed. The concentra-
tions at W4 and W5 increased to their maximums during the
first low tide after application (started at t = 16.75 h), and
then decreased generally with time. This is probably because
the tracer was applied during the falling tide, when a sea-
ward movement occurs.
4. Laboratory Results
[20] The capillary parameters of sediment samples were
estimated by fitting the van Genuchten model [van Genuchten,
1980] to capillary retention experiments [Bear, 1972; Boufadel
et al., 1998]. The van Genuchten model relates the effective
saturation ration Se to the capillary pressure:
Se ¼
S Sr
1 Sr
¼
1
1 þ jyj
ð Þn
m
; ð2Þ
where S is the soil moisture ratio (actual soil moisture
divided by porosity), Sr is the residual soil moisture ratio,
and Se is the effective saturation ratio. The parameters a, n,
and m are typically estimated by fitting, and they are dis-
cussed next.
[21] Nonlinear optimization using the software GRG2
[Lasdon et al., 1978] was used to conduct the fitting of
equation (2) to observed capillary retention data. GRG2 is a
generalized reduced gradient algorithm that we used in prior
work [Boufadel et al., 1998]. Table 3 lists the resulting
values of the van Genuchten parameters. The average values
were a = 10.9 m−1
, n = 1.74, and Sr = 0.036 for these
sediments. The inverse of a provides an approximation of
the capillary fringe [Boufadel et al., 1999b], which is thus
equal to 9.2 cm, reflecting the coarseness of the sediments.
The small value of n (theoretically greater than 1 and usually
less than 8) reflects a relatively wide pore size distribution.
The estimated value of Sr is on the low side in soils, as it is
usually around 0.1. Such a small value reflects the presence
of large pores of the surface layer that get easily desaturated
during low tides.
5. Modeling
5.1. Numerical Model
[22] Numerical simulations were conducted using the
MARUN (MARine UNsaturated) model [Boufadel et al.,
1999b], which can simulate two components (one is salin-
ity and another could be nutrient [Li et al., 2007] or tracer
concentration) in variably saturated porous media, taking
into account the effects of salt concentration on water den-
sity and water viscosity [Boufadel et al., 1999b; Boufadel,
2000].
[23] The equation for the conservation of the water and
salt/nutrient/tracer can be written as
@S
@t
þ S0S
@y
@t
þ S
@
@t
¼
@ Kx
@y
@x
@x
þ
@ Kz
@y
@z
@z
þ
@ 2
Kz
ð Þ
@z
; ð3Þ
where b is the density ratio [–] defined as r/r0 and d is the
dynamic viscosity ratio [–] defined as m0/m. r and r0 are
salt‐dependent water density [M L−3
] and freshwater density
[M L−3
], respectively. m0 and m are freshwater dynamic
viscosity [M L−1
T−1
] and salt‐dependent water dynamic
viscosity [M L−1
T−1
]. is the porosity of the porous
medium [–], S is the soil moisture ratio [–], S0 is the specific
storage [L−1
], y is the pressure head [L], and Kx and Kz are
the horizontal and vertical freshwater hydraulic conductiv-
ities [L T−1
].
[24] The soil moisture ratio and the freshwater hydraulic
conductivity are correlated by the van Genuchten [1980]
model:
for y 0; Se ¼ 1:0; Kx ¼ Kx0; Kz ¼ Kz0; ð4Þ
for y 0; Se is given by equation (2) and Ki = Ki0
ffiffiffiffiffi
Se
p
[1 −
(1 − Se
1/m
)m
]2
, i = (x, z), where Kx0 and Kz0 are the saturated
horizontal and vertical hydraulic conductivity for freshwater,
respectively.
[25] Following Boufadel et al. [1999b] and Boufadel
[2000], the solute transport equation (convection‐dispersion
equation) can be written as
S
@c
@t
¼ r SD rc
ð Þ q rc; ð5Þ
where c is the solute concentration (salt + tracer) expressed
in grams per liter of solution. q = (qx, qz) is the Darcy flux
vector given by
q ¼ qx; qz
ð Þ ¼ Ki
@y
@x
;
@y
@z
þ
; i ¼ x; z
ð Þ: ð6Þ
The term D represents the physical dispersion tensor written
as
D ¼
1
jjqjj
Lq2
x þ T q2
z L T
ð Þqxqz
L T
ð Þqxqz T q2
x þ Lq2
z
; ð7Þ
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7. Figure 5. Observed (symbols) and simulated (solid lines) salinity at ports of W3, W4, and W5. The
salinity of seawater is 24.2 g L−1
. The tidal level and the elevations of the beach surface and of port
A at these observation wells are also shown.
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8. where ||q|| =
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
q2
x þ q2
z
p
, aL and aT are the longitudinal and
transverse dispersivities [L], respectively. The cross dis-
persion terms account for the situation where the flow
direction is not aligned with any of the major axes.
5.2. Numerical Implementation
[26] Figure 2 depicts the cross‐shore domain of the sim-
ulation. The simulated beach has a length of 40 m and a
uniform thickness of 1 m, and was assumed to be piecewise
homogeneous within each of the three layers (the surface
layer, the lower layer, and the bedrock layer). The bedrock
layer was assigned a very small hydraulic conductivity
(10−11
m s−1
) to reflect the bedrock of the simulated beach.
A zone of the same permeability as the surface layer was
used to characterize the pits, which were 0.2 m∼0.4 m wide
in the x direction, and as deep as the buried tip of sampling
well. The tracer application was simulated by specifying the
water flow rate and concentrations of salt and tracer during
the application at the two boundary nodes on the beach
surface closest to the manifold.
[27] The mesh contained 5,694 nodes and 10,900 trian-
gular elements. In the horizontal direction, the spacing
between nodes was 0.1 m between 0 m and 18 m, and
increased to 0.5 m going from 18 m to 40 m, respectively.
The vertical spacing was 0.12 m below a depth of 0.58 m
and 0.03 m above that depth.
5.3. Boundary and Initial Conditions
[28] In our simulations, the rainfall was specified as an
input from the inland on the basis of the following facts:
(1) The rainfall occurred only for 8 h; however, freshwater
runoff due to the rainfall was observed on the surface of the
cliff for the whole duration of the field study. (2) The ver-
tical input of the rainfall into the beach surface was negli-
gible since it occurred during a high tide level and was
subjected to the rapid flushing/mixing of the tides. (3) The
freshwater runoff became invisible when it arrived at the
beach surface, indicating that it entered into the high‐
permeability surface layer. For these reasons, a flux (non-
zero Neumann boundary condition) was specified on two
nodes of the landward boundary (x = 0) immediately above
the interface of the two layers during the monitoring period
of 6 days. The salt concentration was set at zero on these
two nodes, representing freshwater. Note that when the flow
is zero, a zero dispersive flux of the solute results in a zero
mass flow rate of salt across the landward boundary. At the
remaining nodes of the landward boundary, a no‐flow
Figure 6. Observed (symbols) and simulated (solid lines)
lithium concentration of the pore water at W3, W4, and
W5. The tidal level and the elevations of the beach surface
and of port A at these observation wells are also shown.
Table 3. Values of the van Genuchten Parameters Estimated by
Capillary Retention Experiments at Various Wells
W3 W4 W5a
Average
Sample Depth 0–10 cm
11.83b
12.31 NA 12.07
1.85c
1.65 NA 1.75
0.01d
0.067 NA 0.038
Sample Depth 20–30 cm
NA 11.04 9.20 10.12
NA 1.67 1.72 1.69
NA 0.01 0.059 0.034
Average Depth
11.83 11.68 9.20 10.90
1.85 1.66 1.72 1.74
0.01 0.038 0.059 0.036
a
NA means not available.
b
Here a represents the characteristic pore size of the beach soil [L−1
].
c
Here n represents the uniformity of the pores.
d
Here Sr is the residual saturation ratio.
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9. boundary condition was assigned for the groundwater flow
and zero dispersive flux for the solute.
[29] The boundary condition on the beach surface (the
right and upper boundaries of the domain) was updated at
each time step, which is known as “tidal moving boundary
condition.” All boundary conditions used in this paper are
shown in Figure 2. As no seepage face was observed in the
field, the seepage face simulation module within MARUN
was inactivated. Readers interested in investigations on
seepage faces could consult the work of Naba et al. [2002,
and references therein].
[30] The start time of simulation was chosen at the
beginning of the field measurement, i.e., t = 0. Figure 4
shows that the tidal level (3.4 m) was higher than the
whole beach (2.98 m) at t = 0, that is, the whole beach was
submerged by tides. As the beach gets submerged com-
pletely by the seawater during high tide, and as there was no
freshwater before t = 0, there was no need to have a “spin
up” period for the model, as conducted by other studies
[Michael et al., 2005; Li and Boufadel, 2010]. Thus the
initial head distributions were equal to the tidal level (3.2 m)
in the domain submerged by the seawater at t = 0. The initial
concentration in the domain equals the seawater salinity,
namely 24.2 g L−1
.
6. Modeling Results
[31] When the beach was treated as consisting of one
layer, there was no value for the hydraulic conductivity that
reproduced the observed abrupt change in the falling speed
of the water table (Appendix A). Therefore, the beach was
treated as consisting of two layers whose properties were
obtained by calibration.
[32] The hydraulic conductivities were found to be 5 ×
10−2
m s−1
for the surface layer and 7 × 10−6
m s−1
for the
lower layer. The longitudinal and transverse dispersivities
were found to be 0.1 m and 0.01 m, respectively. The van
Genuchten parameters (a, n) were found by calibration to be
(40 m−1
, 7) for the surface layer. As the lower layer
remained submerged, the model was insensitive to its cap-
illary properties. These values for the surface layer suggest a
capillary fringe of 0.025 m, which is much smaller than that
obtained in the lab (around 0.10m). In addition, the high
value of “n” reflects a highly uniform pore size distribution,
which usually occurs when the large pores dominate. We are
inclined to accept these values over those obtained in the
laboratory because the MARUN model is physically based
and because it is probable that the coarse sediments of the
surface layer were mixed with the finer sediments of the
lower layer during sample extraction. The mixing of sedi-
ments in the samples would decrease the value of a. Note
for example, that the laboratory values of the van Genuchten
parameters decrease with depth (Table 3). The calibrated
values based on MARUN simulations are summarized in
Table 4.
[33] The freshwater flux was 1.8 × 10−5
m2
s−1
during
rainfall (from 33 h to 41 h), and 9 × 10−6
m2
s−1
otherwise.
There is a degree of subjectivity of assuming a constant flux
over long durations. However, this approach is common in
hydrology in the absence of detailed data (e.g., constant
recharge over a year [Prieto and Destouni, 2005]). In
addition, the flux is still small and does not affect the main
thrust of the paper, which is to characterize beach hydraulics
and investigate the factors affecting the persistence of the
Exxon Valdez oil spill.
[34] Figure 4 shows the simulated and observed water
levels at all wells, the difference between them was less than
0.05 m in most cases, which is small considering the tidal
range of approximately 5.0 m. This evidences furthermore
the existence of two layers.
[35] Figure 5 shows that the model was able to capture
the overall salinity variation with time. In particular, the
decrease in salinity at t ≥ 40 h was well captured at most
ports of wells W4 and W5. This indicates that the transport
time of water within the beach was well determined.
[36] Figure 6 shows the simulated lithium concentration
of the pore water well matched the observed one at W3, W4,
and W5. The simulated arriving time of lithium at W4
matched with the observed one closely. The simulated
arriving time at W5 shows a small delay compared with the
observed one. In spite of this small discrepancy, the arrival
time and values of the simulated lithium at W4 and W5 are
comparable to the observed values.
7. Discussion
7.1. Groundwater Flow in Intact Sediments
[37] Simulations that excluded the “pit effects,” tracer
application, and rainfall were conducted to provide insights
into the oil persistence in intact sediments. To depict the
flow process in the intact sediments, the domain used in
section 5.2 was refined using the mesh resolution of 0.03 m
in vertical direction and of 0.05 m in horizontal direction
Table 4. Model Parameter Values Used in the Numerical Simulations
Symbol Definition Units Valuea
a Sand capillary fringe parameter of the van Genuchten [1980] model 1 m−1
40, 0.5
N Sand grain size distribution parameter of the van Genuchten [1980] model ‐ 7, 2
Ko Saturated freshwater hydraulic conductivity m s−1
5 × 10−2
, 7 × 10−6
aL Longitudinal dispersivity m 0.1
aT Transverse dispersivity m 0.01
Fitting parameter of density‐
concentration relationship
L g−1
7.63 × 10−4
S0 Specific storage 1 m−1
10−5
Sr Residual soil saturation ‐ 0.01
Porosity ‐ 0.30
CONVP The convergence criterion of pressure head in the Picard iterative
scheme of MARUN code
m 10−5
tDm Product of tortuosity and diffusion coefficient m2
s−1
10−9
a
Where two values are given, the first is for the surface layer and the second is for the lower layer.
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10. throughout the domain. The mesh contained 24,924 nodes
and 48,180 triangular elements. The model parameters
identified using the observed water level, salinity and lith-
ium concentration in section 6 were used in the simulations.
[38] Figure 7 shows that the simulated water levels at W3,
W4, and W5. During low tides, the water tables at these
three wells were lower than the interface of the two layers.
This behavior of the water table explains the persistence of
oil on this beach. During the initial oiling (March 1989),
whenever the water table fell below the interface, oil float-
ing on it entered into the lower layer, and got entrapped
there by the capillary forces of the fine‐grained sediments.
The surface layer acted as a temporary storage for oil for the
filling of the lower layer. Compared with stranded surface
oil spills that usually lose their fluidity rapidly, an oil
entrapped in the surface layer gets attenuated and weathered
much slowly, retaining therefore its fluidity. The two‐layered
beach structure and the subsurface oil persistence found at
wells W3, W4, and W5 are consistent with the findings of Li
and Boufadel [2010] in a beach (147° 34′ 17.42″ W, 60° 33′
45.57″ N) on Eleanor Island, ∼11 km northwest of this beach.
[39] The presence of oil in the surface layer of this beach
in contrast to the beach studied by Li and Boufadel [2010] is
probably due to the absence of freshwater seaward flow on
this beach. Li and Boufadel [2010] reported freshwater
seaward flow in their beach, which would cause the dis-
lodgement of oil from the surface layer of the oiled transect.
This could have been enhanced by the fact that the seaward
flow is made up of freshwater whose interfacial tension with
oil is larger than that of saltwater (Environmental Science
and Technology Center, Environment Canada, Databases
and software, 2006, http://www.etc‐cte.ec.gc.ca/databases/
Figure 7. Simulated water table (solid lines) at W3, W4, and W5 in the intact beach. The tidal level and
the elevations of the beach surface and of the interface are also shown to indicate the submersion period.
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11. OilProperties/oil_prop_e.html), which would minimize the
breakup of oil into smaller droplets that could be lodged
within the pore matrix.
[40] Figure 8a shows the time series of the normal pore
water velocity at wells W3, W4 and W5 at 0.1m below the
interface of the layers. The normal velocity is defined as the
velocity normal to the interface of the two layers. It is
positive when water flows out of the lower layer. Figure 8a
shows that water flow at W3 was into the lower layer for
most of the time. The flow was outward during falling tides
until the tide level dropped below the interface of the two
layers. This indicates that water from the landward side
enters the beach mostly through the upper layer and per-
colates into the lower layer. This is further confirmed in
Figure 8b, which shows that water from the land side enters
through the upper layer and replenishes the lower layer (note
the vectors just above the water table at W3).
[41] Figure 8a shows that the flow at W4 was outward
almost always. The maximum magnitude of velocity at W4
(around 2 cm d−1
) was about 6 times smaller than that at
W3. At W5, the flow was inward most of the time. How-
ever, this water was not coming from the upper layer, rather
from the lower layer landward of W5, as the velocity vectors
at x = 8.0 m show (Figure 8b). This suggests that the pore
volume at W5 might not be replenished with oxygen‐rich
water from the seaside. Rather from water that already
propagated within the beach and probably lost its oxygen
due to the biological oxygen demand of biogenic and
hydrocarbon material [Slomp and Van Cappellen, 2004; Li
and Boufadel, 2010].
[42] Figure 9 reports the Darcy velocity distribution
within the transect averaged over a spring‐neap tidal cycle
(15 days). The velocity in the surface layer is much higher
than that in the lower layer due to the permeability differ-
ence between the two layers. The velocity magnitude in both
layers decreased seaward of x = 17 m. The velocity vectors
in the surface layer near W3 (0∼3 m) are pointing down-
ward, indicating the fill‐up mechanisms of the beach from
the landward side. Similar dynamics seem to occur in the
surface layer between W4 and W5. The velocity vectors in
the lower layer mainly point seaward, implying a seaward
flow occurring there. This indicates that oxygen‐rich water
from the sea enters the beach and propagates into the lower
layer seaward, potentially losing its oxygen content.
[43] Figure 10 shows the inflow rate and outflow rate of
tidal water averaged over a spring‐neap tide cycle at dif-
ferent zones of the transect. The inflow and outflow rates are
larger in the zones 2 m ≤ x ≤ 6 m and 8 m ≤ x ≤ 12 m than
Figure 8. (a) Changes of simulated pore water normal velocities to the layers’ interface with time at 0.1 m
below the interface at wells W3, W4, and W5. Positive is outbound. (b) Pore water velocity (banded
color contours) in the transect during low tide (t = 266 h). The size of the arrows is not proportional to the
magnitude; it was reported to indicate the direction. The magnitude is given by the contours. The water
table is represented by the dashed line.
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12. that at other zones, which is due to the relatively larger
beach slope and thickness of the high‐permeability surface
layer there. The relatively small thickness of the surface
layer near the landward area of W3 (Table 1) and the no‐flow
inland boundary would induce the relative smaller rates
between 0 m and 2 m.
[44] Although the beach slope between L2 (x = 17 m) and
the low tide mark (x = 30 m) is the largest one in the
transect, the inflow and outflow rates within this area are
relatively small, which is consistent with a decrease in the
water velocity as one moves seaward (Figure 9). The out-
flow rate is larger than the inflow rate at 17 m ≤ x ≤ 30 m,
and all the flow rates decrease going seaward in that seg-
ment. The inflow and outflow rates below the low tide mark
(30 m x ≤ 40 m) are close to zero, indicating that the
offshore beach groundwater is almost stagnant compared
Figure 9. Average pore water velocity (banded color contours) in the transect calculated over a spring‐
neap tide cycle. Similar to Figure 8, the arrows with uniform length were used to indicate the velocity
direction only.
Figure 10. The inflow rate (volume of seawater entering the beach domain in unit length of the beach
surface in the cross‐shore direction and unit length in the along‐shore direction per day) and outflow rate
averaged over a spring‐neap tide cycle at different zones of the transect. The different locations, the beach
slope, and the thickness of the surface layer are also shown.
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13. with the onshore groundwater flow, which is consistent with
the results of Li et al. [2008]. These findings suggest that
during the seawater‐groundwater circulation across the
beach‐sea interface, most seawater enters and leaves the
beach surface within the middle to the high intertidal zone.
The total outflow flux was computed at 2.12 m3
d−1
m−1
, and
the total inflow flux was almost the same 2.119 m3
d−1
m−1
.
There was no additional water (e.g., freshwater, rainfall)
recharged the aquifer. The mass balance between the inflow
flux and outflow flux is good.
[45] Our findings provide an explanation for the persis-
tence of the Exxon Valdez oil spill on this beach. The oil
reached this beach within less a week following a major
storm [Neff et al., 1995]. The viscosity of the oil was not
thus too high to prevent its percolation in the beach during
low tides [Short et al., 2006]. As the water table on this
beach dropped beneath the interface of the two layers, oil
floating on the water table entered the lower layer and
remained entrapped there by capillary forces. At locations
where the water table remained above the layers’ interface,
the oil did not persist on those transects [Li and Boufadel,
2010]. The lack of natural biodegradation of oil could be
due to lack of nutrients, lack of oxygen, or both. We explore
next a situation where bioremediation is enhanced by the
addition of nutrients. This subsumes that either the beach
contains enough oxygen or that the applied solution has a
high concentration of oxygen such that the environment in
the beach is aerobic.
7.2. Numerical Simulation of Nutrient Application
[46] The maximum concentration of nutrients in PWS is
less than 0.4 mg N L−1
[Bragg et al., 1994; Eslinger et al.,
2001], an order of magnitude lower than the concentration
needed for maximum microbial growth, which ranges from
2 (sometimes 5) to 10 mg N L−1
[Lewis et al., 1995; Venosa
et al., 1996; Boufadel et al., 1999a; Wrenn et al., 2006].
Subsequently, the natural biodegradation rate of oil is
expected to be slow if the concentration of nutrients was
small. The nutrient’s pathway in the beach plays an equally
important role to their concentration. Seawater laden with
nutrients [Eslinger et al., 2001] would fill the beach during
high tides and drain from it during low tides. However, the
net effect of the tide is a seaward flow in beaches [Nielsen,
1990; Boufadel et al., 1998; Ataie‐Ashtiani et al., 1999;
Boufadel, 2000] causing the nutrients to travel within beach
seaward to eventually exit to sea. The beach would be devoid
of nutrients if the replenishment from the sea is small.
[47] Bioremediation of sediments polluted by hydro-
carbons by nutrient amendment has been studied in the lab
[Boufadel et al., 1999a; Du et al., 1999; Venosa and Zhu,
2003]. It was also used for remediating the Exxon Valdez
Oil Spill [Pritchard, 1991; Bragg et al., 1994]. See also
Pritchard [1991], Swannell and Head [1994], Swannell et al.
[1996] and Atlas and Bragg [2009]. However, we are
not aware of any information on the movement of applied
nutrients within the beaches of PWS. For this reason, we
attempt to provide such information numerically.
[48] To explore the effectiveness of the nutrient applica-
tion for oil bioremediation in the two‐layered gravel beach,
we conducted numerical simulations of nutrient application
on beach, assumed intact (i.e., the pits were removed). We
assumed that there was no rainfall to facilitate the inter-
pretation of the results. The applied nutrient solution was set
at 5 g L−1
and the salt concentration was set at 24.2 g L−1
,
the seawater salinity at this beach. This is because it would
be easier to use seawater to apply the nutrient solution rather
than transporting freshwater to the site. Thus, the solute
concentration of the applied solution is 29.2 g L−1
. The
location, start time with relation to tide, and duration of
nutrient application are the same as that for tracer applica-
tion in this paper: Nutrients application between W3 and W4
that started at t = 16.75 h and lasted 1.75 h. The application
flow rate was set at 2.4 × 10−5
m3
m−1
s−1
. We also assumed
that the applied nutrient concentration is too high to be
affected by the consumption rate of nutrients. This is a rea-
sonable assumption unless excessive nitrate reduction takes
place under anoxic conditions [Slomp and Van Cappellen,
2004]. Nevertheless, the goal herein is to understand
nutrients pathways rather than their consumption rates.
[49] Figure 11 reports contours of the plume at various
times after the application. Figure 11a shows that the plume
moves mainly seaward above the water table when tide falls.
Figure 11b shows that the plume moves landward and
downward after the tide rose, which is consistent with
observations in a laboratory beach [Boufadel et al., 2006]. It
is also consistent with the numerical nutrient application on
a homogeneous beach [Li et al., 2007]. Figure 11c shows
that the nutrient distribution in the surface layer significantly
varied with the tide, while that in the lower layer was less
affected by the tide. The nutrient concentration dramatically
decreased within three tidal cycles after application (t =
55 h, Figure 11c); however, its concentration remained
larger than 10 mg L−1
more than a week after application (t =
181 h, Figure 11d). Particularly, the nutrient concentration
remaining in oiled areas (W3, W4, and W5) was larger than
50 mg L−1
(Figure 11d). These findings suggest that
nutrients applied on this beach would tend to stay more than
a week in the lower layer in contact with oil. The fluctua-
tions at the bottom of the plumes are typical of gravitational
instabilities that develop whenever a heavy solution overlies
a light solution [Oostrom et al., 1992a, 1992b; Schincariol
et al., 1994; Simmons et al., 2001].
8. Conclusions
[50] The subsurface oil from the 1989 Exxon Valdez spill
persists in many initially polluted beaches along Prince
William Sound (PWS), Alaska. To identify beach hydraulics
related to the persistence of oil, field measurements and
numerical simulations were conducted in an oiled transect of
a tidal gravel beach perpendicular to the shoreline. The
Figure 11. The spatial distribution of the nutrient concentration (in g L−1
) at four times during the numerical nutrient
application test in the intact beach. The nutrient application was started at t = 16.75 h and lasted 1.75 h. The beach water
table and tidal level are shown using dashed lines. The interface (solid line) of the surface and lower layers is also shown to
indicate the distribution of nutrient in two layers. Vectors with uniform length are used to indicate the velocity direction
only.
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14. Figure 11
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15. transect was located on northern Knight Island in PWS at
the coordinates 147° 47′ 24.34″ W, 60° 29′ 5.56″ N. Three
observation wells and piezometers were installed in the
transect to measure water level, salinity and tracer (lithium)
concentration. The measurement durations differed with
location from 4 days to a maximum of around 6 days. Water
samples were collected for chemical analysis of salinity and
lithium concentration.
[51] Observed water level, salinity, and lithium concen-
tration were reproduced using the finite element model
MARUN [Boufadel et al., 1999b]. The results indicated the
presence of a two‐layered beach structure. The hydraulic
conductivities of the surface layer and the lower layer were
5 × 10−2
m s−1
and 7 × 10−6
m s−1
, respectively. The
interface of the two layers was obtained on the basis of field
measurements and model calibrations against the observed
data.
[52] During low tides, the water tables at observation
wells were lower than the interface of the two layers, which
provides an explanation for the persistence of oil in this
beach. The very permeable surface layer probably acted as
funnel and temporary storage for the oil to fill the less
permeable lower layer whenever the water table dropped
below the interface of the two layers. Once the oil enters the
lower layer, it gets entrapped there by the capillary forces of
the fine‐grained sediments. Thus, the small flow due to
rainfall entering the beach from the land side resulted in the
water table dropping below the interface of the two layers,
which was probably the major reason for the presence of oil
in the lower layer in this beach.
[53] The tide‐induced seawater‐groundwater exchange
in the intertidal zone of the beach was estimated to be
2.12 m3
d−1
m−1
. The maximum exchange occurred in the
middle to high intertidal zone, which further contributes to
the persistence of oil in the lower intertidal zone.
[54] Bioremediation via nutrient amendment was
explored by simulating numerically nutrient application on
the beach surface. The applied solution was 29.2 g L−1
with a
nutrient solution of 5 g L−1
and seawater salinity of 24.2 g L−1
at this beach. The results showed that the applied nutrient
concentration stayed in oiled areas over a week after appli-
cation and it was larger than 50 mg L−1
, a concentration larger
than needed for maximum microbial growth (2–10 mg L−1
).
This suggests that nutrient amendment on this beach would
enhance oil biodegradation if nutrients were the limiting
factor. Other limiting factors could be the lack of oxygen,
Figure A1. Comparisons of simulated water tables in the beach using a one‐layer model and the two‐
layer model. The simulated water table under the two‐layer model is shown in Figure 7. Two simulations
of the one‐layer model were conducted using two different values of hydraulic conductivity when other
model parameters were the same as the two‐layer model.
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16. which could either prevent biodegradation [Reddy et al.,
2002; Venosa and Zhu, 2003] or cause denitrification [Slomp
and Van Cappellen, 2004].
Appendix A
[55] We conducted six simulations where we treated the
beach as homogeneous (combining the surface and lower
layers into one layer, one‐layer model) to compare the
simulated water tables with that obtained by our two‐layer
system in the beach (compared with the case shown in
Figure 7). Six examples were conducted using different values
of hydraulic conductivity: K = 0.01 m s−1
, K = 0.007 m s−1
,
K = 0.005 m s−1
, K = 0.003 m s−1
, K = 0.001 m s−1
, and K =
0.0005 m s−1
. The simulations had a very small conver-
gence rate when K values were large (K = 0.01 m s−1
, K =
0.007 m s−1
), while seepage face occurred during simula-
tions when K values were small (K = 0.001 m s−1
, and K =
0.0005 m s−1
). Since during all these simulations the water
tables in three observation wells have similar changes, here
we only present the simulated water tables at wells W4
and W5 from two simulations (K = 0.005 m s−1
and K =
0.003 m s−1
) in Figure A1. Figure A1 shows that when the
tidal level is lower than the ground surface, the dropping
velocity of the water table within a homogeneous beach
does not reproduce the sudden change observed in the data.
[56] Acknowledgments. This work was supported by Exxon Valdez
Oil Spill Trustee Council (070836). However, it does not necessarily reflect
the views of the Council, and no official endorsement should be inferred.
This work was conducted during the first author’s visit to the Department
of Civil and Environmental Engineering, Temple University, Philadelphia,
United States. The first author’s work was also supported by the “111 Project”
of China (B08030). The authors appreciate the discussions with Danis
Botrus about the field investigations. We thank many Temple University
faculty and students who assisted in this work. The paper highly benefited
from the comments and suggestions from the Editor, Associate Editor, and
three anonymous reviewers.
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