Reprinted from the Journal of Environmental Quality
Vol. 18, no. 4, October-December 1989, Copyright © 1989, ASA, CSSA, SSSA
677 South Segoe Road, Madison, WI 53711 USA
Vertical and Lateral Components of Soil Nutrient Flux in a Hillslope
J. W. Gaskin,* J. F. Dowd, W. L. Nutter, and W. T. Swank
balance, and (ii) calculation of flux based on Darcy's
Law. The water-balance approach estimates water flux
as the residual of the mass-balance equation, using
inputs to the soil, losses to interception, evapotranspiration and changes in soil storage. Usually, the
water is assumed to percolate vertically to the next
level or out of the soil system. Flux calculations can
be a direct computation of Darcy's Law, or an indirect
calculation such as the Richard's Equation. Darcy's
Law states that flux is the product of the hydraulic
conductivity and the energy gradient in the soil. Soil
water potential can be measured with tensiometers
and coupled with hydraulic conductivity data to predict flux. Both vertical and lateral flux can be determined.
Russell and Ewel (1985) compared the two methods
and conclude the water-balance approach is superior.
They assumed vertical percolation because there was
no impeding soil layer. This is a poor assumption on
hillslopes where water movement is known to have a
lateral component (Harr, 1977; Weyman, 1973; Whipkey, 1965). Although lateral flow is associated with an
impeding layer or a decrease in hydraulic conductivity
with depth (Zaslavsky and Rogowski, 1969), Nutter
(1975) showed that lateral flow occurs under homogenous soil conditions in a sloping soil model, and
McCord and Stephens (1987) provided field evidence
for this phenomenon. Therefore, lateral flow should
not be ignored in hillslope sites. In order to determine
the importance of the lateral component of flow, Darcy's Law must be used.
Many of the forest ecosystems impacted by acid deposition are in mountainous regions where the evaluation of leaching in the soil may be complicated by
lateral flow. Therefore, the objectives of this study
were: (i) to determine the importance of vertical and
lateral flow in a forested hillslope receiving atmospheric deposition and (ii) to estimate chemical flux
during and immediately after a storm.
ABSTRACT
The vertical and lateral components of chemical flux during storm
events were investigated in a Typic Hapludult to assess their importance in understanding the effects of atmospheric deposition on
hillslope sites. Vertical and lateral water flux were calculated from
soil water potential data and hydraulic conductivity curves. Throughfall, stemflow, forest floor leachate, and soil solution from the BA,
Bt, and BC horizons were sampled and analyzed for SO4, NO3-N,
Cl, HCO], H, K, Ca, Mg, and Na. Total lateral flow as a ratio of
totaf vertical flow averaged 0.23 and 0.30 in the A and BA horizons,
respectively, indicating lateral fluxes were an important path of nutrient movement in the surface horizons. The highest lateral flow
occurred in the A horizon during dry antecedent moisture conditions
and in the BA horizon during wet antecedent moisture conditions.
Fluxes of all ions except HCO3, NO3-N, and H peaked in the forest
floor leachate and the BA soil solution, then decreased with depth.
Decreases of SO4 flux between the BA and BC horizons could not
be explained by the lag of solute movement or by lateral solute losses,
demonstrating the system was an effective SO4 sink.
A CCELERATED SOIL NUTRIENT LEACHING due tO
./"Y acid deposition is an environmental concern.
Field studies have examined the effects on forest nutrient status and nutrient cycling by measuring soil
solution concentrations (Johnson et al., 1985; Cronan
et al., 1978; Ulrich et al., 1980). Chemical mechanisms
of leaching have been identified with models (Reuss,
1980, 1983) and in the laboratory (Johnson and Henderson, 1979; Johnson and Todd, 1983), and the hypotheses generated have been tested in the field (Johnson et al., 1986; Khanna et al., 1987). Results from
these simulations and field studies have shown the
importance of determining nutrient flux through the
soil for a complete understanding of the environmental impacts of acid deposition.
Nutrient flux is commonly estimated by multiplying
the measured nutrient concentrations times an estimated water flux. Although uncertainty exists concerning methods of obtaining representative soil nutrient concentrations, the estimate of water flux is the
source of the greatest uncertainty in the nutrient-flux
calculation. Direct measurement of water flux is not
possible. Van der Ploeg and Beese (1977) have shown
that tension lysimeter volumes cannot be used to estimate water flux. Therefore, a separate estimate must
be made. Two methods are primarily used: (i) water
METHODS
Site Description
The study was conducted on Watershed 1 of the USDA
Forest Service Coweeta Hydrologic Laboratory near Otto,
NC, which is a site for measurement of atmospheric deposition and nutrient fluxes (Swank and Reynolds, 1987).
The Coweeta basin is located in the Blue Ridge province
of the southern Appalachians. Underlying rock consists of
granite gneiss and schists in the Coweeta Group and the
Tallulah Falls Formation (Hatcher, 1979). The climate is
considered marine. Annual rainfall is evenly distributed and
averages around 1800 mm per year (Swank and Douglass,
J.W. Gaskin, J.F. Dowd, and W.L. Nutter, School of Forest Resources, Univ. of Georgia, Athens, GA 30602; and W.T. Swank,
Coweeta Hydrologic Lab., 999 Coweeta Lab Rd, Otto, NC 28763.
Received 27 July 1988. *Corresponding author.
Published in J. Environ. Qual. 18:403-410 (1989).
403
404
J. ENVIRON. QUAL., VOL. 18, OCTOBER-DECEMBER 1989
WS1
Watershed Scale-Feet
500
1000
• Tensiometer
Set 4
6.1m
Tensiometer
Sets
&4m
Zero
Tensiometer
Lysimeter
Tensiometer Set 1
Tensiometer Set 2
o
6m
Stemflow
Collector
o
aw
00
-15m
Fig. 1. Site map and diagram of the study plot located at the Coweeta Hydrologic Laboratory near Otto, NC.
1975). However, the area experienced a deficit of 734 mm
from average precipitation during the study period from October 1985 to November 1986.
Watershed 1 is a 16.2-ha south-facing watershed. It was
clearcut in 1956 to 1957 and eastern white pines (Pinusstrobus L.) were hand planted in 1957. The soils are fine-loamy,
micaceous, mesic Typic Hapludults (Fannin series) and
coarse-loamy, micaceous, mesic Typic Dystrochrepts (Chandler series).
A 6- by 15-m study plot was located in the Fannin series
on the lower midslope of the watershed. Elevation of the
study plot was 713 m slope—48% and aspect-southeastern
(146°). A site map and schematic diagram of the plot instrumentation is shown in Fig. 1.
Soil Water Flux
Four tensiometer sets were installed. Two sets each contained nine tensiometers placed to bracket the average lysimeter cup depth in the BA, Bt and BC horizons, and were
used to calculate vertical flux. Two additional sets each contained three tensiometers placed at the average lysimeter cup
depth in each horizon, perpendicular to the slope, and were
used to calculate lateral flux. The tensiometers were read
every 2 to 4 h during rainfall and less frequently after the
rain ended.
Soil water characteristic curves were determined for the
A, BA, Bt, and BC horizons with a pressure-plate apparatus
(Richards, 1965) using 12 undisturbed cores (5.3-cm diam.
by 3.0-cm long) from each horizon. Laboratory estimates of
saturated hydraulic conductivity (KJ were determined by
the constant-head method (Klute, 1965) using 6 to 7 undisturbed cores (5.3-cm diam. by 6.0-cm long) per horizon.
Field measurements of saturated hydraulic conductivity
(Kfc) were made with a Guelph permeameter (Reynolds and
Elrick, 1985) using 5- and 10-cm heads in a 3-cm radius well.
Seven to 8 measurements of K^, were obtained just below
the study plot in the BA (mean depth 17 cm), Bt (mean depth
31 cm) and at the top of the BC (mean depth 60 cm) horizons.
Only two of these measurements resulted in a negative estimate of Kfc using the LaPlace method (one each in the Bt
and the BC horizons). The negative values were not used.
Kfs could not be obtained for the shallow A horizon (9.0 cm).
An estimate of Kfs for the A horizon was extrapolated using
the KfS in the BA horizon and the ratio of the K,s in the A
and BA horizons. Unsaturated hydraulic conductivity was
calculated from the soil water characteristic curve data, using
the saturated hydraulic conductivity as a matching factor by
the method of Millington and Quirk (1959) as modified by
Kunze et al. (1968). A summary of soil characteristics, the
mean of six to seven repetitions of the hydraulic conductivity
GASKIN ET AL.: NUTRIENT FLUX IN A HILLSLOPE PINE PLANTATION SOIL
405
Table 1. Selected soil characteristics of a Typic Hapludult (Fannin series). All means are geometric.
Horizon
A
BA
Bt
BC
Depth
cm
0-9
9-28
28-62
62-91
mean
Texture
si
scl
c
cl
g/cm
0.79
0.94
1.03
1.10
SD
89t
27
7
7
t Calculated from the ratio of the BA/A K, and the BA Kf,
t pb = bulk density; Kf, = saturated hydraulic conductivity determined in the field; K,, •
measurements for each method, and parameters of the Millington Quirk equation is presented in Table 1.
Vertical and lateral water fluxes were calculated from tensiometer readings and hydraulic conductivity curves using
Darcy's Law. Vertical fluxes were calculated for each time
period using the total heads obtained from tensiometers
bracketing a horizon for sets 1 and 2, then averaged. Lateral
fluxes were calculated from the total heads obtained from
tensiometers in the middle of the BA, Bt, and BC horizons.
Lateral fluxes were computed between tensiometer sets 2 and
3 and sets 3 and 4, then averaged. Total flux is the sum of
the average fluxes over time for a storm. The flux calculations did not account for hysteresis and assumed isotropic
conditions within a soil horizon. Because soil water potential
in the A horizon was not measured in the lateral tensiometer
sets, lateral flux over time in the A horizon was not calculated. However, total lateral flux in the A horizon for a storm
event was estimated by difference:
I QAL = I qAv ~ AA - I qBA
Jo
Jo
Jo
where:
i
qAL = total lateral flux in the A horizon (cm)
qAV = total vertical flux in the A horizon (cm)
AA = total change in storage in the A horizon (cm)
i =
QUA total flux into the BA horizon (cm)
Mass balance computations assuming negligible evapotranspiration during a storm event were used as a check of
the Darcy flux. Each soil horizon was considered a slab of
unit width, horizon depth, and slope length. The slope length
extended from the watershed boundary to the plot boundary,
which allowed the assumption of zero lateral flux across the
upper face of the slab. The change in storage for each soil
horizon determined by mass balance was compared with the
change in storage obtained from the tensiometers using the
moisture characteristic curves.
Chemistry
Stemflow collection collars were attached to nine dominant and codominant white pines; samples were collected
from each tree. Throughfall was collected with 10 26-cmdiam. funnels positioned randomly in the plot. A plasticscreen plug was used in the funnel neck to prevent large
participates from contaminating the sample. Two similar
precipitation collectors were placed in a clearing at the base
of the watershed. Precipitation, throughfall, and stemflow
collectors were covered during dry periods and opened before storm events.
Four lysimeter pits were excavated along the contour of
the slope. Lysimeters made of high-flow (100 kPa air entry
low
mean
SD
porosity
79
58f
8
363
109
8
110
3
2
103
94
123
19
30
19
0.70
0.64
0.60
0.59
cm/h-
3
saturated hydraulic conductivity determined in the laboratory.
value, Soil Moisture Equipment Corp., Santa Barbara, CA)
ceramic cups and PVC pipe were installed horizontally in
the BA (12 cm), the Bt (30 cm), and the BC horizon (75 cm)
of each pit. Constant tension was maintained with hanging
water columns at 10 kPa in two pits and 30 kPa in two pits.
Zero-tension lysimeters (Jordan, 1968) were installed at the
forest floor-mineral soil interface upslope from each pit.
Storm events started with the inception of rainfall and
ended when tensiometer readings began to rise after reaching
a minimum, indicating the soil profile was drying out. Precipitation, throughfall, and stemflow volumes were measured at the end of the storm and a subsample was retained
for chemical analysis. Forest-floor leachate and soil-solution
samples were collected in 250- and 100-mL increments, respectively, during the storm event. Samples were refrigerated
immediately after collection. AH samples except soil solution
were filtered with Whatman GF/C micropore filters (1.2-/t
effective retention). Three filter blanks were run and the average filter-blank concentration was subtracted from the concentrations of the filtered samples.
Samples were analyzed for H, HCO3, SO4, Cl, NO3-N, K,
Ca, Mg, and Na. Bicarbonate and H analyses were performed
within 24 h of collection. Hydrogen-ion concentration was
calculated from pH. Bicarbonate was determined by titration
with weak H2SO4 (0.005 M or 0.01 M). Anions were determined colorimetrically. Cations were analyzed by atomic
absorption spectrophotometry.
The number of soil-solution samples per storm ranged
from five to eight in the BA horizon, zero to four in the Bt
horizon, and zero to three in the BC horizon. Chemical flux
for the soil solution was calculated by multiplying the average water-flux estimates for the time period over which
the sample was collected with the concentrations. The resultant chemical fluxes were summed for the storm and averaged by horizon. Vertical and lateral components of flux
were
considered separately. All ions were reported as molc
nr2 storm"1. Percent change of an ion between horizons was
calculated after subtracting the laterally moving concentrations.
RESULTS AND DISCUSSION
Soil Water Flux
Soil water flux was calculated for five storms occurring between May 1985 and November 1986. Figure 2 shows the initial soil water profile for Storm 1,
3, 4, and 5 obtained from the average of tensiometer
sets 1 and 2, and the moisture characteristic curve.
The initial soil water profile for Storm 2 (13-15 October 1986; 17 mm precipitation) is not shown due to
instrument failure from extremely dry antecedent soil
water conditions. Soil solution samples collected from
this storm were the first since Storm 1 on 26 May 1986.
Storms were grouped into dry antecedent conditions
(Storm 1, 2, and 3) and wet antecedent soil water conditions (Storm 4 and 5) for comparison.
406
J. ENVIRON. QUAL., VOL. 18, OCTOBER-DECEMBER 1989
O-i
-20-
x-x
A-«
Q-Q
o-o
STORM
STORM
STORM
STORM
1
3
4
5
E
o
CL
Ld
Q
-40-
O
-60-
0.15
0.25
0.20
0.30
3
3
SOIL WATER CONTENT (cm /cm )
Fig. 2. Initial soil water profile for Storm 1 (26-29 May 1986,
precipitation of 69 mm), Storm 3 (23-27 Oct. 1986, precipitation
of 100 mm), Storm 4 (10-13 Nov. 1986, precipitation of 21 mm)
and Storm 5 (19-23 Nov. 1986, precipitation of 32 mm).
Total storm fluxes calculated from hydraulic conductivity curves obtained using Kfc as a matching factor were two orders of magnitude greater than throughfall/stemflow (TF/SF) input. The K,s measurements
were extremely high, even though flow down the sides
of the core rings was excluded with cutoff rings. The
high laboratory measurements were attributed to small
roots and other continuous channels in the cores common to well-developed forest soils. Field measurements were made in an attempt to incorporate a larger
soil volume and diminish the effect of continuous
channels. Total storm fluxes calculated from unsaturated hydraulic conductivity curves using Kfs were in
better agreement with inputs, but still appeared high.
Estimated vertical fluxes in the A horizon were three
times the TF/SF inputs, ranging from 4.4 times the
inputs in Storm 2 to 1.7 in Storm 3. The best agreement of total storm fluxes and inputs was obtained
using curves developed with the lowest Kfs in each
horizon as a matching factor (Table 2). The necessity
of reducing hydraulic conductivity curves is not unusual in forest soils. Van Grinsven et al. (1987) report
reducing hydraulic conductivity curves 5 to 60 times
Table 2. Total vertical (vert) and lateral (lat) water flux for Storm
1 through 5 calculated from tensiometer data and hydraulic conductivity curves generated using the lowest measured field saturated hydraulic conductivity.
Precipitation
TF/SFf
Horizon
A vert
lat
BA vert
lat
Bt vert
lat
BC vert
lat
Storm 1
Storm 2
Storm 3
Storm 4
Storm 5
6.9
4.2
1.7
1.4
10.0
8.3
2.1
1.6
3.2
2.6
2.5
0.7
1.3
0.3
0.6
0.1
0.0
0.0
1.8
3.8
1.5
1.7
0.7
0.7
0.1
0.5
0.0
2.0
0.2
1.5
0.5
0.8
0.1
0.2
0.0
2.1
0.3
1.7
0.6
1.1
0.1
0.3
0.0
1.0
0.2
0.5
0.0
0.1
0.0
t TF/SF = ratio of throughfall to stemflow.
in order to match observed matric potentials in a forest
of the Netherlands.
In addition to using TF/SF inputs as a constraint
on the flux estimates, the change in storage obtained
from mass-balance calculations using the best flux estimates were compared with measured change in storage to help assess flux validity. Calculated change in
storage was generally higher than the measured change
in storage (Table 3). The higher calculated values indicate vertical fluxes were too high as a result of overestimating vertical hydraulic conductivity, or lateral
fluxes were too small as a result of underestimating
lateral conductivity, or some degree of both. The Kfs
is an average of vertical and lateral conductivity (Reynolds and Elrick, 1985), which may cause overestimates of vertical flux and underestimates of lateral flux
in hillslope sites.
The largest decrease in total storm flux occurred
between the A and BA horizons during dry antecedent
conditions, and between the BA and Bt horizons during wet antecedent conditions. Results in Table 2 indicate these decreases were caused by lateral flux because the mean total lateral flux as a ratio of vertical
flux in the A horizon was greater during dry antecedent
conditions than during wet ones (dry mean = 0.33 vs.
wet mean = 0.12).
Decreases in hydraulic conductivity with depth in
soils enhances lateral flow. Measurements indicated a
decrease in saturated hydraulic conductivity between
the A and BA horizons, and also between the BA and
Bt horizons. Although the variability of these measurements was high, the increase in soil bulk density
and the change in texture with depth (Table 1) supported the existence of the conductivity decreases.
The effect of the difference in hydraulic conductivities between horizons was the greatest when a wet
horizon overlaid a drier one. During dry antecedent
conditions, the BA could not transmit water as fast as
the A could supply it, and water was shunted laterally.
The same process occurred at the BA-Bt interface during wet antecedent conditions. The ratio of lateral to
vertical flux in the BA horizon was related to precipitation depth as well as the antecedent conditions.
Table 3. A comparison of calculated change in storage from mass
balance calculations (calculated S) and measured in storage from
tensiometer data (measured S) for each storm by horizon.
Storm Sampling
number
level
1
BA
Bt
BC
2
BA
Bt
BC
3
BA
Bt
BC
4
5
BA
Bt
BC
BA
Bt
BC
Calculated Measured
S
S
1.0
0.7
_
_
-
1.4
1.8
-
1.6
0.6
0.6
0.7
0.5
0.7
—
—
—
1.4
1.8
0.2
0.2
0.3
0.3
-
407
GASKIN ET AL.: NUTRIENT FLUX IN A HILLSLOPE PINE PLANTATION SOIL
During the wet antecedent conditions and the driest
antecedent conditions (Storm 1 and 2), the ratio of
lateral to vertical flux averaged 0.36 and 0.22, respectively. Although Storm 3 occurred during dry antecedent conditions, the large amount of precipitation
apparently filled storage in the BA horizon, allowing
a high ratio of lateral flow (0.41).
Lateral flow in the Bt horizon did not vary as much
with antecedent soil water conditions, the ratio of lateral to vertical flux ranging from 0.9 to 0.17. The consistency of the proportion of lateral to vertical flow in
the Bt may be due to the negligible difference in saturated hydraulic conductivity between the Bt and BC.
Due to the extremely dry conditions for the year, the
proportion of lateral flow may be atypical for this site.
There was no significant lateral flow in the BC horizon.
Storm 3 illustrated the pattern of flux through time
during the storm events sampled (Fig. 3). Vertical flux
showed a sharp increase after rainfall, with the increase
lagged as the wetting front moved through the soil
profile. Lateral flux increased sharply in the BA horizon, but was damped with depth. In the desorption
phase, lateral flux tended to become constant while
vertical flux decreased. These results are consistent
with data from physical soil models showing that lateral flux becomes more important as the soil dries
(Nutter, 1975).
The pattern of flux over time was similar for Storm
3, 4, and 5. Ratios of vertical to lateral flux over time
for these storms showed high variability at the storm
beginning when storage was being filled. As the storm
progressed, the ratios for each storm became quite similar in both the BA and Bt horizons (Fig. 4). The ratio
of lateral to vertical flux at the point of maximum
vertical flux was more consistent across storms, ranging from 0.39 to 0.42 in the BA and 0.12 to 0.13 in
theBt.
These results indicate the amount of lateral flow was
controlled by the soil water content and the depth of
precipitation. Once the storage was filled to some
threshold level, lateral flow was a relatively constant
ratio of vertical flow.
The largest source of error associated with the flux
calculations was the method of measuring saturated
hydraulic conductivity. The problem of obtaining realistic values of saturated hydraulic conductivity was
largely caused by the spatial variability of the soil.
Although total flux estimates were dependent on the
saturated hydraulic conductivity used to generate unsaturated hydraulic conductivity curves, they were reasonable because the total storm fluxes were close to
SF/TF inputs.
Error associated with gradient estimates was small
because there were only small differences in soil water
potential measured at comparable depths (mean, 0.7
kPa). Variability of the difference in soil water potential was strongly influenced by antecedent conditions
(standard deviation of 2 kPa for wet storms and 18
kPa for dry storms), suggesting the occurrence of preferential flow zones during dry antecedent conditions.
Consequently, errors in flux prediction may be greatest
during dry antecedent conditions.
This analysis assumed that the soil was isotropic;
the same saturated hydraulic conductivity applied to
both directions of flow. Therefore, the ratio of lateral
to vertical flux was independent of the saturated hydraulic conductivity (Table 4). In layered soils, where
anisotropy occurs, lateral conductivities are often
1.4
1
STORM 3
o-a STORM 4
STORM 5
o) BA HORIZON
o
u
0)
>
D
k_
<L>
"S
00
O
<
a:
0
0.02-1
10
20
40
50
60
70
1.0-1
o-e STORM 3
o-o STORM 4
*-a STORM 5
0.00
o
(J
b) Bt HORIZON
0.8-1
<u
0.6-
o
i_
0)
O
B-Q A VERTICAL FLUX
a-a BA VERTICAL FLUX
o-« BA LATERAL FLUX
o—o Bt VERTICAL FLUX
a-B Bt LATERAL FLUX
*-*.BC VERTICAL FLUX
20
40
60
80
100
CUMULATIVE TIME (hrs)
Fig. 3. Flux during Storm 3 for each horizon. Negative numbers
indicate downward flux, positive numbers indicate upward flux.
The dark horizontal bar indicates rainfall duration.
0.4-
o
I—
0.0-
10
20
30
40
50
60
70
CUMULATIVE TIME (hrs)
Fig. 4. Ratios of lateral to vertical flux for three storms. The time
scale is adjusted to the beginning of each storm's rainfall.
408
J. ENVIRON. QUAL., VOL. 18, OCTOBER-DECEMBER 1989
Table 4. A comparison of the ratio of lateral to vertical fluxes calculated using the mean field-measured saturated hydraulic conductivity (K,,)
and the low Kfs. Ratios for the A horizon were not included, as they were obtained by difference. Lateral flux in the BC was negligible.
Dry antecedent conditions
Storm 1
Horizon
low
0.20
0.08
BA
Bt
Wet antecedent conditions
Storm 2
low
low
0.23
0.17
0.24
0.0
Storm 4
Storm 3
0.20
0.0
0.41
0.13
StormS
low
low
0.41
0.14
0.34
0.12
0.33
0.13
0.33
0.13
0.35
0.09
Table 5. Average storm concentrations and standard errors for anions and cations present in the precipitation (P); throughfall (TF); stemflow
(SF); forest floor leachate (FF); and the soil solution from the A, BA, Bt, and BC horizons.
Component
S04
Cl
NO,-N
HCOj
P
8.88
3.73
16.55
1.50
38.44
4.73
77.27
11.38
71.73
2.64
37.40
0.43
9.54
0.42
5.05
0.91
12.19
2.90
23.35
5.92
50.43
7.33
79.32
7.85
50.46
5.03
26.06
3.20
7.71
2.75
5.78
2.81
1.29
0.22
1.50
0.06
0.57
0.32
0.36
0.16
0.07
0.03
0.56
0.14
1.13
0.61
0.20
0.08
1.80
0.21
X
SE
TF
X
SE
SF
X
FF
X
BA
X
SE
SE
SE
Bt
X
SE
BC
X
SE
higher than vertical conductivities. The difference between the measured and calculated change of storage
suggested that such a condition may exist for this site.
However, measurement of the anisotropy of this site
was beyond the scope of this study. We feel the assumption of isotropy in each soil horizon gives a lower
bound estimate of the ratio of lateral to vertical flux
in each horizon.
Recent research has emphasized the importance of
macropore flow in a variety of soils (Beven and Germann, 1982). Some studies in forest soils indicate the
major portion of water flux during storms occurs as
macropore flow rather than as flow through the soil
matrix (DeVries and Chow, 1978). This study did not
address the amount of macropore flow occurring during storms; thus an unknown portion of the soil-water
flux has been excluded. However, we feel macropore
flow is likey to be small on a plot or watershed scale
at this site because (i) no pipeflow was ever observed
during storm events, even though old root channels
and other visible pores were present in the soil-pit
faces, (ii) in general, the surface horizons wetted up
before subsurface horizons, and (iii) quickflow averages only 3% of the total annual flow on watershed 1,
which indicates that the bulk of the water is moving
through the soil matrix.
Chemistry
Soil-solution samples were collected at two tensions.
The probability distributions of each ion were tested
for differences by horizon (Wilcoxon Sum Rank, a =
0.05) to see if the two tensions sampled the same population. The BC-horizon soil solution and HCO3 in
the BA and the Bt horizon were not tested due to the
limited sample size. Eleven of 14 probability distri-
31.25
7.26
53.79
5.23
43.90
0.66
1.89
0.24
28.44
3.56
77.00
14.85
58.10
5.38
58.26
4.88
25.09
0.96
11.12
0.41
Ca
Mg
Na
H
12.48
0.21
0.62
0.26
4.61
0.59
8.76
1.78
32.09
3.00
53.52
4.42
10.66
2.59
5.87
1.98
8.74
1.17
18.44
3.95
35.02
2.28
31.27
2.98
32.84
1.58
17.56
5.63
6.39
2.62
27.78
3.15
11.21
0.98
1.09
0.40
2.98
0.01
0.40
0.04
8.43
1.25
15.82
3.17
77.50
6.38
82.66
4.81
56.81
1.74
24.80
5.86
35.46
1.38
21.93
1.27
butions were not different, therefore we could not conclude that the samples came from different populations and the samples were pooled by horizon for
average equivalents in a storm. Average concentrations and standard errors are given in Table 5.
Average fluxes of SO4, Cl and the base cations for
all storms were highest in the forest-floor leachate and
the BA-horizon soil solution, then decreased with
depth in the soil (Fig. 5). The fluxes of NO3-N and H
peaked in the precipitation and decreased as they
moved through the system. The flux of both these ions
was very low (<0.011 and <0.012 molc, respectively)
in the soil solution. Bicarbonate flux was low in the
input samples (mean, 0.015 molc), and increased in
the soil solution as water dissolved CO2.
Sulfate was the dominant anion throughout the system, except in the BC horizon. The maximum sulfate
flux was in the forest-floor leachate. Sulfate flux was
approximately five times greater than HCO3 in the BA
horizon. The difference decreased in the Bt where SO4
flux was 30% greater than HCO3. In contrast, SO4 flux
was 43% less than HCO3 in the BC horizon.
Although results from other temperate forest ecosystems indicate HCO3 and organic acids are the primary mobile anions in the soil solution (McColl and
Cole, 1968), Johnson et al (1988) report SO4 is the
dominant anion in soil solution collected over a 2- to
3-yr period at Coweeta. High SO4 values are also reported in the soil solution and groundwater from areas
that receive sizable atmospheric inputs (Cronan et al.,
1978). The Coweeta basin is subject to atmospheric
SO4 deposition (Swank and Waide, 1988) and preliminary results from Swank and Reynolds (1987) indicate dry deposition may be a major source of belowcanopy fluxes. The amount of SO4 in the soil solution
may be higher than normal because the 1985 to 1986
GASKIN ET AL.: NUTRIENT FLUX IN A HILLSLOPE PINE PLANTATION SOIL
409
2.5-
2.0-
me?4
r~lN03-N
EE23HCO3
a] AVERAGE
ANION FLUX
1.5-
.
P
f
.
1.O-
?
i Imolc/m2/storr
"E
3
t
In
P
2.0-I
1.5-
HI I !iLllL. „
TF
SF
FF
BAV
BA,
|K
3Ca
I.'.'.'.'.'.'.! Mo
EESSDNa
IH
Btv
Bt|
BCV
BC|
b) AVERAGE CATION FLUX
1.O-
0.5-
TF
SF
FF
BAV
BA|
Btv
Bt|
BCV
BC|
SAMPLING LEVEL
Fig. 5. Average nutrient flux for all storms at each sampling level. P = precipitation, TF = throughfall, SF = stemflow, FF = forest-floor
leachate, BA, = BA soil-solution vertical component, BA, = BA horizon soil-solution lateral component, Bt, = Bt horizon soil-solution
vertical component, Bt, = Bt horizon soil-solution lateral component, BC, = BC horizon soil-solution vertical component, BC, = BC
horizon soil-solution lateral component.
water year encompassed a 100-yr drought. High rates
of mineralization combined with low rates of flushing
due to the dry soil conditions may have caused a
buildup of SO4 in the surface horizons that was beginning to move through the system with the fall
storms. However, SO4 concentrations are within the
range reported for a 45-yr-old pitch pine stand 10 km
north of the Coweeta basin (Swank and Swank, 1984).
Average SO4 flux was not greater than HCO3 in the
BC horizon. The decreases in SO4 flux could be due
to the lag of water and solute movement to the lower
horizons. However, some SO4 was immobilized. The
percent decrease of Cl, which may be considered a
conservative tracer, was 44% from the BA to the Bt
horizon, compared with 61% for SO4. Sulfate retention
can be attributed to adsorption (Johnson and Henderson, 1979) or microbial transformation (Fitzgerald
and Johnson, 1982) both of which have been shown
to be important in Coweeta soils.
It is important to recognize that the percent decrease
of solute fluxes excludes losses from lateral water
movement. Lateral solute flux was small in the Bt and
BC horizons (ratio of lateral to vertical 0.12 and 0.5,
respectively), but high in the BA (0.28). The ratio of
solutes moving laterally in the A horizon was probably
also high. Total amounts of lateral flux may be greater
in the lower horizons under more-saturated conditions.
Errors inherent in soil nutrient flux estimates in the
soil are associated with the water-flux calculations,
which has been previously discussed, and the problem
of obtaining a representative concentration. Litaor
(1988) questions the validity of soil-solution concentrations obtained from suction lysimeters, but this is
the best nondestructive method currently available.
CONCLUSIONS
The most significant finding of this study was the
importance of the total lateral-flux component in the
A and BA horizons, where the ratio of lateral to vertical flux averaged 0.23 and 0.30, respectively. These
ratios are conservative, as each horizon was considered isotropic.
Antecedent soil-water conditions determined where
the largest portion of lateral flow occurred. During dry
antecedent conditions, the greatest lateral flow was in
the A horizon. High lateral flow occurred in the BA
horizon during wet antecedent conditions and with
large-volume storms. After soil storage reached some
threshold level during a storm event, the ratio of lateral to vertical flux became relatively constant in the
BA and Bt horizons.
The fluxes of SO4, Cl, NO3-N, K, Ca, Mg, and H in
the soil solution were greatest in the BA horizon and
decreased with depth. The decreases of SO4 could not
be explained by the lag of solute movement to the
lower horizons or by lateral solute losses, indicating
SO4 was being immobilized.
Approximately 0.30 of ion equivalents moved lat-
410
J. ENVIRON. QUAL., VOL. 18, OCTOBER-DECEMBER 1989
erally in the BA horizon. The soil solution moving
laterally does not equilibrate with the lower horizons.
This may be especially important for SO4, which is
adsorbed in the lower horizons (Johnson and Todd,
1983) and immobilized. Because cation leaching is dependent on mobile anions (Johnson and Cole, 1980),
the fact that a considerable portion of the SO4 was
moving laterally in the BA horizon implies greater
leaching of cations may take place in the surface horizons during storm events.
Results from this study must be interpreted in light
of the extremely low rainfall during the storm collection period. The dry conditions may have affected
both the soil-solution chemistry and the proportion
and magnitude of vertical and lateral fluxes.
ACKNOWLEDGMENTS
This research was funded in part by the USDA Forest
Service, Southeastern Forest Exp. Stn. through a grant from
the Electric Power Research Inst. under Contract RP 23261 with Oak Ridge National Lab. The senior author would
like to thank the Coweeta staff for their help and moral
support during this study.
REFERENCES
Beven, K., and P. Germann. 1982. Macropores and water flow in
soil. Water Resour. Res. 18:1311 -1325.
Cronan, C.S., W.A. Reiners, "R.C. Reynolds, Jr., and G.E. Lang.
1978. Forest floor leaching: contributions from mineral organic,
and carbonic acids in New Hampshire subalpine forests. Science
(Washington, DC) 200:309-311.
DeVries, J., and T.L. Chow. 1978. Hydrologic behavior of a forested
mountain soil in Coastal British Columbia. Water Resour. Res.
14:935-942.
Fitzgerald, J.W., and D.W. Johnson. 1982. Transformations of sulphate in forested and agricultural lands, p. 411-426 In A.I. More
(ed.) Sulphur '82, Proc. Conf. London. 14-17 Nov. 1982. British
Sulphur Corp. Ltd., London!
•
Harr, R.D. 1977. Water flux in soil and subsoil on a steep forested
slope. J. Hydrol. (Amsterdam) 33:37-58.
Hatcher, R.D., Jr. 1979. The Coweeta Group and Coweeta syncline:
major features of the North Carolina—Georgia Blue Ridge. Southeast. Geol. 21:17-29.
Johnson, D.W., and D.W. Cole. 1980. Anion mobility in soils: relevance to nutrient transport from forest ecosystems. Environ. Int.
3:79-90.
Johnson, D.W., D.W. Cole. H. Van Miegroet, and F.W. Hornig.
1986. Factors affecting anion movement and retention in four
forest soils. Soil Sci. Soc. Am. J. 50:776-783.
Johnson, D.W., and G.S. Henderson. 1979. Sulfate adsorption and
sulfur fractions in a highly weathered soil under a mixed deciduous forest. Soil Sci. 128:34-40.
Johnson, D.W., J.M. Kelly, W.T. Swank, D.W. Cole, H. Van Miegroet, J.W. Hornbeck, R.S. Pierce, and D. Van Lear. 1988. The
effects of leaching and whole-tree harvesting on cation budgets of
several forests. J. Environ. Qual. 17:418-424.
Johnson, D.W., D.D. Richter, G.M. Lovett, and S.E. Lindberg. 1985.
The effects of atmospheric deposition on potassium, calcium, and
magnesium cycling in two deciduous forests. Can. J. For. Res.
15:773-782.
Johnson, D.W., and D.E. Todd. 1983. Relationships among iron,
carbon, and sulfate in a variety of forest soils. Soil Sci. Soc. Am.
J. 47:792-800.
Jordan, C.F. 1968. A simple, tension-free lysimeter. Soil Sci. 105:8186.
Khanna, P.K., J. Prenzel, K.J. Meiwes, B. Ulrieh, and E. Matzner.
1987. Dynamics of sulfate retention by acid forest soils in an acidic
deposition environment. Soil Sci. Soc. Am. J. 51:446-452.
Klute, A. 1965. Laboratory measurements of hydraulic conductivity
of saturated soil. In C.A. Black (ed.) Methods of soil analysis, Part
1: Physical and mineratogical properties, including statistics of
measurement and sampling. Agronomy 9:210-220.
Kunze, R.J., G. Uehara, and K. Graham. 1968. Factors important
in the calculation of hydraulic conductivity. Soil Sci. Soc. Am. J.
32:760-765.
Litaor, M.I. 1988. Review of soil solution samples. Water Resour.
Res. 24:727-733.
McColl, J.G., and D.W. Cole. 1968. A mechanism of cation transport in a forest soil. Northwest Sci. 42:134-140.
McCord, J.T., and D.B. Stephens. 1987. Lateral moisture flow beneath a sandy hillslope without an apparent impeding layer. Hydrological Processes 1:225-238.
Millington, R.J., and J.P. Quirk. 1959. Permeability of porous media. Nature 183:387-388.
Nutter, W.L. 1975. Moisture and energy conditions in a draining
soil mass. Technical Completion Report ERC 0875. Univ. of
Georgia, School of For. Resources, Athens.
Reuss, J.O. 1980. Simulation of soil nutrient losses resulting from
rainfall acidity. Ecol. Modell. 11:15-38.
Reuss, J.O. 1983. Implications of the calcium-aluminum exchange
system for the effect of acid precipitation on soils. J. Environ.
Qual. 12:591-595.
Reynolds, W.D., and D.E. Elrick. 1985. In situ measurement of fieldsaturated hydraulic conductivity, sorptivity, and the alpha-parameter using the Guelph permeameter. Soil Sci. 140:292-301.
Richards, L.A. 1965. Physical condition of water in soil. In C.A.
Black (ed) Methods of soil analysis, Part 1: Physical and mineralogical properties, including statistics of measurement and sampling. Agronomy 9:128-131.
Russell, A.E., and J.J. Ewel. 1985. Leaching from a tropical Andept
during big storms: a comparison of three methods. Soil Sci.
139:181-189.
Swank, W.T., and J.E. Douglass. 1975. Nutrient flux in undisturbed
and manipulated forest ecosystems in the Southern Appalachian
Mountains, p. 445-456. In Proc. Tokyo Symp. on the hydrological
characteristics of riverbasins and the effects on these characteristics of better water management, Tokyo, Japan. 1-8 Dec. IAHS,
Washington, DC.
Swank, W.T., and L.J. Reynolds. 1987. Analysis of dry and wet
deposition, throughfall and stemflow event chemistry in a Pinus
strobusL. plantation, p. 127-136. In Acidification and water pathways. Vol. 2, Bolkesjo, Norway. 4-5 May. The Norwegian National Committee for Hydrology, Oslo.
Swank, W.T., and W.T.S. Swank. 1984. Dynamics of water chemistry in hardwood and pine ecosystems, p. 335-346. In T.P. Burt
and D.E. Walling (ed.) Proc. Int. Geographical Union Commission on Field Experiments in Geomorphology, Exeter and Huddersfield, UK. 16-24 Aug 1981. Geo Books, Norwich, England.
Swank, W.T., and J.B. Waide. 1988. Characterization of baseline
precipitation and stream chemistry and nutrient budgets for control watersheds. In W.T. Swank and D.A. Crossley (ed.) Forest
hydrology and ecology at Coweeta. Springer-Verlag, New York.
Ulnch, B., R. Mayer, and P.K. Khanna. 1980. Chemical changes
due to acid precipitation in a loess-derived soil in central Europe.
Soil Sci. 130:193-199.
van der Ploeg, R.R., and F. Beese. 1977. Model calculations for the
extraction of soil water by ceramic cups and plates. Soil Sci. Soc.
Am. J. 41:466-470.
van Grinsven, J.J.M., N. van Breeman, and J. Mulder. 1987. Impacts of acid atmospheric deposition on woodland soils in the
Netherlands: I. Calculation of hydrologic and chemical budgets.
Soil Sci. Soc. Am. J. 51:1629-1634.
Weyman, D.R. 1973. Measurements of the downslope flow of water
in a soil. J. Hydrol. (Amsterdam) 20:276-288.
Whipkey, R.Z. 1965. Sub-surface flow from forested slopes. IAHS
10th Anniv. Bull. (2):74-85.
Zaslaysky, p., and A.S. Rogowski. 1969. Hydrologic and morphologic implications of anisoptropy and infiltration in soil profile
development. Soil Sci. Soc. Am. Proc. 33:594-599.