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Published online 1 March 2007
Published in J Environ Qual 36:597-606 (2007)
DOI: 10.2134/jeq2006.0368
© 2007 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
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TECHNICAL REPORTS

Vadose Zone Processes and Chemical Transport

Dissolved Organic Carbon Fluxes under Bare Soil

Jan Mertensa,*, Jan Vanderborghta,b, Roy Kasteelb, Thomas Pützb, Roel Merckxa, Jan Feyena and Erik Smoldersa

a Soil and Water Management, K.U. Leuven, Celestijnenlaan 200E, B-3001 Heverlee, Belgium
b Agrosphere, ICG-IV, Forschungszentrum Jülich GmbH, D-52425 Jülich, Germany

* Corresponding author (mertensja{at}yahoo.co.nz)

Received for publication September 14, 2006.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
The flux of dissolved organic carbon (DOC) in soil facilitates transport of nutrients and contaminants in soil. There is little information on DOC fluxes and the relationship between DOC concentration and water flux in agricultural soils. The DOC fluxes and concentrations were measured during 2.5 yr using 30 automatic equilibrium tension plate lysimeters (AETPLs) at 0.4 m and 30 AETPLs at 1.20-m depth in a bare luvisol, previously used as an arable soil. Average annual DOC fluxes of the 30 AETPLS were 4.9 g C m–2 y–1 at 0.4 m and 2.4 g C m–2 y–1 at 1.2 m depth. The average leachate DOC concentrations were 17 mg C L–1 (0.4 m) and 9 mg C L–1 (1.2 m). The DOC concentrations were unrelated to soil moisture content or average temperature and rarely dropped below 9 mg C L–1 (0.4 m) and 5 mg C L–1 (1.2 m). The variability in cumulative DOC fluxes among the plates was positively related to leachate volume and not to average DOC concentrations at both depths. This suggests that water fluxes are the main determinants of spatial variability in DOC fluxes. However, the largest DOC concentrations were inversely proportional to the mean water velocity between succeeding sampling periods, suggesting that the maximal net DOC mobilization rate in the topsoil is limited. Elevated DOC concentrations, up to 90 mg C L–1, were only observed at low water velocities, reducing the risks of DOC-facilitated transport of contaminants to groundwater. The study emphasizes that water flux and velocity are important parameters for DOC fluxes and concentrations.

Abbreviations: AETPL, automatic equilibrium tension plate lysimeter • DOC, dissolved organic carbon


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
THE presence of dissolved organic carbon (DOC) and its transport through soils plays a role in the global carbon cycle (Jardine et al., 2006), in the growth and metabolism of soil microorganisms (Lundquist et al., 1999b), and soil formation processes (Jansen et al., 2005). In addition, DOC has been found to easily associate with nutrients (Qualls and Haines, 1991), contaminants (Guggenberger et al., 1998), and metals (Temminghoff et al., 1997; Weng et al., 2002) and can therefore enhance or retard the transport of these solutes through the soil (Totsche et al., 1997; Totsche and Kögel-Knabner, 2004). It is clear that the DOC-facilitated transport of solutes in soil requires information on DOC concentrations.

Neff and Asner (2001) present a literature review of measured DOC fluxes through the surface soil, subsurface soil, and in streams across a range of ecosystems under forest vegetation and grasses. The surface (0–0.2 m) soil fluxes range between 10 and 85 g C m–2 y–1 while subsurface fluxes (0.2–1 m) vary between 2 and 40 g C m–2 y–1. Neff and Asner (2001) suggest that DOC fluxes under grassland and perhaps agricultural ecosystems are lower than in forested ecosystems but that information is scarce. Additionally, DOC fluxes and concentrations sampled in a field soil can have considerable temporal and spatial variability (Zsolnay, 2003). In their review, Kalbitz et al. (2000) conclude that seasonal effects on DOC concentrations show an increasing trend of higher DOC concentrations with increasing temperatures. However, this trend is clearer in laboratory than in field studies. It seems unlikely that the release of DOC under field conditions depends entirely on temperature. Hydrological conditions, litter fall, soil texture, as well as other soil properties can mask the temperature response of DOC concentrations in the field (Kalbitz et al., 2000). Zsolnay (2003) stated that there is a major deficit in research dealing with the variation of DOC in space and time. The most significant effect of water fluxes on DOC is the release of DOC at the beginning of a rewetting period (e.g., Lundquist et al., 1999a; Münch et al., 2002; Kaiser and Guggenberger, 2005). This is probably the most consistent finding that matches both field and laboratory studies and is attributed to an accumulation of DOC from microbiological detritus during dry periods (e.g., cell death and lysis) and the physical disintegration of soil organic matter (SOM).

Kalbitz et al. (2000) state that under field conditions, DOC fluxes and concentrations are likely more affected by the water flux and DOC retardation properties of soil horizons than by biotic controls. For example, DOC may be strongly adsorbed to mineral surfaces in subsoil horizons with low carbon contents, resulting in low DOC concentrations in the soil solutions. Furthermore, laboratory experiments have often contradicted field observations, primarily because hydrology was not taken into account. Several studies have shown that DOC concentrations in soil solutions decrease significantly with soil depth and that sorption of DOC to mineral surfaces is far more important than the decomposition of DOC (Kalbitz et al., 2000). Tipping et al. (1999) showed that the leaching of DOC is greatly affected by the sorption of DOC to mineral horizons thereby attenuating possible climate change effects on DOC leaching. On the contrary, Worral and Burt (2004) show a significant climate-driven increase in DOC concentrations in UK river waters. Lajtha et al. (2005) recently concluded from field lysimetry that adding wood debris increased the DOC concentrations at 0.3 m but not at 1 m. Since the labile C fraction in their soil solutions had been shown to be quite low, they argued that abiotic sorption rather than microbial uptake is responsible for the majority of DOC removal in the soil profile. Alborzfar et al. (2001) found a steep DOC gradient in the unsaturated zone below a football field that was irrigated with DOC-rich groundwater. An increase in organic carbon with time in the top layer suggested retention rather than degradation for part of the removal. Münch et al. (2002) show that DOC concentrations in leachates of small unsaturated soil columns decrease with increasing pore water velocities. Contrarily, preferential flow of leachate water containing DOC reduces the contact time between the DOC and the mineral soil and might lead to accelerated leaching of DOC and possibly associated solutes.

The objectives of this study are to quantify DOC fluxes and concentrations in the field. The spatial and temporal variability of DOC fluxes and concentrations are analyzed in terms of water velocity, temperature, and soil moisture content. This study presents in situ measurements of DOC fluxes and concentrations under bare soil conditions. Most field studies dealing with DOC fluxes and concentrations are located in forests, meadows, or under cultivated land. This study differs because the measured DOC fluxes and concentrations originate solely from the soil organic carbon pool and not from any input of organic material through plants or residues. Therefore, variability in DOC concentrations measured in this study (under bare soil) must be the result of the balance between (i) DOC release from the soil organic carbon, (ii) DOC decomposition by microbiological activity, (iii) DOC immobilization by sorption, and (iv) transport processes through the soil. The study aims at identifying processes that determine the spatial and temporal variations in DOC concentrations and fluxes excluding variability of carbon input in soils. Therefore DOC concentrations were monitored at several locations and two depths in a bare soil field plot. To make the link between local water fluxes, average pore water velocities, and the spatial-temporal variability of DOC concentrations and fluxes, bromide was applied as an inert tracer and its concentrations as well as local leachate volumes were monitored.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 REFERENCES
 
Site Description
The experimental site was a flat agricultural field located near Merzenhausen, Germany. The field was bare since 1996 and it remained without plants throughout the experimental period. The field was kept bare using the herbicide Roundup (glyphosate) sprayed at regular intervals with an application rate of 4 L ha–1. The only available knowledge of the agronomic history of the experimental field is that the straw was frequently plowed in but no organic manure was applied in the last 25 yr. The soil is classified as an orthic luvisol (FAO, 1998) with silt being the dominant textural fraction. Table 1 shows selected physical and chemical soil properties. The groundwater table is situated at approximately 15 m below the surface. Earthworm burrows were found to be abundant to a depth of >1.5 m, although few direct connections to the soil surface existed because of the frequent plowing. Mean annual temperature is 9.5°C and mean annual precipitation amounts to 689 mm equally distributed throughout the year.


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  		Table 1. Selected physical and chemical properties of the soil at the experimental test site in Merzenhausen (Kasteel et al., 2007). Soil was air-dried and sieved to 2 mm before the analysis. All weight fractions are based on the total mass of soil.

 
Experimental Design
Leachate was sampled using the automatic equilibrium tension plate lysimeter (AETPL) system in which leachate is continuously sampled by controlling the suction below the tension plate to be similar to the soil matric pressure in the soil profile surrounding the tension plate (Brye et al., 1999; Siemens et al., 2003; Masarik et al., 2004; Mertens et al., 2005). A total of 60 AETPLs were installed divided over five sampling pits and two sampling depths: 0.4 and 1.2 m below surface (Fig. 1). The pits have a radius of about 0.8 m, are located about 10 m apart and extend to a depth of about 2 m (Fig. 1). The ceramic plates have an air-entry value smaller than –10 m H2O, a surface area of 0.056 m2, and a thickness of 0.01 m. Around the circumference of each pit, six AETPLs at 0.4-m depth and six AETPLs at 1.2-m depth were installed. The plates were installed inside a 0.7-m-long tunnel which was manually dug through holes in the cylinder walls. The front end of the ceramic plates are located 0.56 m outside the pit so that the distance from the middle of the pit to the front end of the plates equals 1.36 m as indicated in Fig. 1. Before installation, the plates were covered with a layer of moist soil to ensure good contact with the undisturbed soil. The plates were consequently jacked up and held up using screw jacks. In every pit, three tensiometers were installed at 0.4-m depth and three at 1.2-m depth. The average tensions measured at each depth in each pit was forwarded to the suction control unit and applied as vacuum to the corresponding suction plate. Leachate was collected from each AETPL every 2 to a maximum of 4 wk for about 2.5 yr, its volume recorded, and analyzed for Br– and DOC. Bromide concentrations were measured using ion chromatography where the water samples were eluted with a 9.0 mM Na2CO3 on a Dionex AS9-HC anion exchange column. Dissolved organic carbon inside the leachate was measured using the non-purgable organic carbon (NPOC) method. NPOC was determined by injecting an aliquot of the sample into a thermal combustion tube to convert carbon into carbon dioxide which is flushed from the tube using carrier gas and measured using a non-dispersive infrared gas analysis system. NPOC analysis involves the removal of inorganic carbon by acidification and sparging with carrier gas before analysis, and is a direct measurement of the DOC content. Therefore, the term DOC (dissolved organic carbon) is used throughout the rest of the manuscript.


Figure 1
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  		Fig. 1. Experimental layout: (a) location of the five pits, (b) zoom into 1 pit, each pit is equipped with six automatic equilibrium tension plate lysimeters (AETPLs) at 0.4 m and six AETPLs at 1.2-m depth, (c) location of the trench in which soil moisture content and soil temperatures were measured, and (d) location of the climatological station.

 
Figure 1 shows the location of a nearby 10-m-long measuring trench in which soil moisture content was measured using 102 TDR (0.2-m rods) probes (17 TDR probes at 0.20, 0.45, 0.60, 0.80, 1.0, and 1.5 m below soil surface). Additionally, soil temperature was measured using a total of 21 temperature probes (three temperature probes at 0.05, 0.20, 0.45, 0.60, 0.80, 1.0, and 1.5 m below soil surface). Both soil temperature and moisture content were measured at a daily temporal resolution. For comparison with measured DOC concentrations in the sampled leachate, the daily soil moisture content of the 17 TDR probes at 0.20, 0.45, and 1.0 m were averaged. Consequently, for each leachate sampling date, the average of the daily soil moisture contents between the previous sampling date and the current is calculated. The same is done for the three daily temperature measurements at 0.05-, 0.45-, and 1-m depth.

Bromide Tracer Experiment
A bromide (Br–) tracer experiment was performed by spraying a 0.228 mm pulse of Br– solution on 13 Nov. 1997 over an area of 1 ha covering the pits using a tractor. This resulted in an average pulse density of 24.9 g Br m–2. The application homogeneity was measured using 38 cups of 0.12 by 0.12 m. The spatial variability of the bromide application, expressed as the coefficient of variation was 12%. The reader is referred to Pütz et al. (1999) and Kasteel et al. (2007) for a more detailed description of the entire experimental setup.

Bromide Transport Analysis
In this study, the bromide breakthrough curves obtained at each AETPL are analyzed using time moment analysis. This is in contrast with the combination of the classical convection-dispersion equation (using a two-dimensional unsaturated zone model) and the time moment analysis performed by Kasteel et al. (2007). Additionally, only the 1.2 m data are analyzed by Kasteel et al. (2007) while in this study, both the 0.4 and 1.2 m breakthrough curves are analyzed. The advantage of the time moment analysis is that no assumptions are required regarding the underlying processes for the characterization of the concentration curves. The normalized time moments, TN [LN], are defined as

Formula 1[1]
where {tau}0 (M L–2) equals the total mass of bromide recovered per unit area and Cwf (M L–3) is the flux concentration in the liquid phase. Since we are dealing with atmospheric boundary conditions, a transformed time coordinate, i.e., the cumulative amount of leachate, I (L), is used in the further analysis. The first normalized time moment (N = 1), T1 (L) can be related to the quantity of water required for the center of mass to arrive at the depth of observation. The pore volume, PV (–), sampled by the AETPL is calculated as the relation between the first moment of its Br– breakthrough curve and its installation depth:

Formula 2[2]
where z (L) is the installation depth of the AETPL. The pore volume represents the volume of water that needs to be displaced before the tracer breaks through normalized by the volume of the soil from which water is captured by the AETPL. For column studies, in which flow is vertical, this soil volume is well-defined. In that case, the pore volume represents the ‘effective’ volumetric water content which needs to be displaced before the tracer breaks through. For AETPLs, the ‘capture volume’ is not defined so that the PV may be larger or smaller than the volumetric water content in a virtual cylinder above the AETPL.

The number of pore volumes, #PV (–), that have been sampled by each AETPL over the entire or part of the monitoring period can be calculated as:

Formula 3[3]
where V (L3) is the volume of the leachate sampled by the AETPL over the entire duration of the experiment and A (L2) is the cross-sectional area of the AETPL. A time-averaged water velocity, v (LT–1) can be calculated from #PV as:

Formula 4[4]
where tmonitoring (T) is the monitoring time. The number of sampled pore volumes is thus a measure for the time-averaged water velocity which expresses the average velocity of the water moving through the soil profile toward the AETPL.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
REFERENCES
 
Leachate Flux Densities, Bromide Mass Recoveries, and Annual Dissolved Organic Carbon Flux Densities
Figure 2 shows the boxplots of the annual leachate flux densities (mm y–1), Br– recoveries (g m–2), and annual DOC flux densities (g C y–1 m–2) sampled by the six AETPLs at 0.4- and 1.2-m depths in each of the five pits. The large extent of the boxplot whiskers indicate a high variability of the annual leachate and DOC flux densities as well as of Br– mass recoveries among AETPLs around the same pit for all five pits and both depths. No significant pit effect (P < 0.025) was found by ANOVA for the annual leachate and DOC flux densities and Br– mass recoveries, i.e., the variability among AETPLs of different pits is not larger than the variability among AETPLs within the same pit.


Figure 2
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  		Fig. 2. Boxplots of the annual leachate flux densities (mm y–1), Br– recoveries (mg m–2), and annual DOC (dissolved organic carbon) flux densities (mg C y–1 m–2) sampled by the six automatic equilibrium tension plate lysimeters (AETPLs) at 0.4- and 1.2-m depths in each of the five pits. Each boxplot has lines at the lower quartile, median, and upper quartile values; lines (whiskers) extending from each end of the box show the extent of data. Outliers are data with values beyond the ends of the whiskers; if there is no data outside the whisker, a dot is placed at the bottom whisker.

 
The annual water flux density averaged over the 30 AETPLs equals 345 mm in the plates at 0.4-m depth vs. 284 mm in the plates at 1.2-m depth. However, the leachate flux captured by the AETPLs varies between 284 and 1687 mm for the plates at 0.4-m depth and between 266 and 1228 mm for the plates at 1.2-m depth over the two and a half year study period. Kasteel et al. (2007) attribute these extreme differences in total cumulative amounts of water and Br– to (i) spatial variability in local-scale hydraulic properties, i.e., soil heterogeneity, (ii) differences in properties of the suction plates (in particular hydraulic conductivities), and (iii) lateral redistribution of the infiltrating water at the soil surface by its microtopography. Based on the ANOVA analysis, it is concluded that there is no need to consider the pits as ‘blocks’ in any of the further analyses.

The average annual DOC flux densities are 4.9 g C m–2 y–1 at 0.4-m depth and 2.4 g C m–2 y–1 at 1.2-m depth (Fig. 2). Siemens et al. (2003) report comparable fluxes under arable land: between 6 and 9 g C m–2 y–1 at 0.9-m depth and between 1 and 2 g C m–2 y–1 between 3- and 5.6-m depth. As suggested by Neff and Asner (2001), we find that the DOC flux densities measured at 0.4-m depth under bare soil are significantly lower than those reported under forest vegetation cover, where surface fluxes ranged between 10 and 85 g C m–2 y–1at 0 to 0.2 m, and between 2 and 40 g C m–2 y–1 at 0.2 to 1 m. Note that subsurface fluxes at 1.2 m under forests can be as low as the fluxes measured in this study under bare soil (2.4 g C m–2 y–1). This suggests that, independent of the soil cover, most of the DOC is either sorbed to the soil matrix or biologically consumed as it moves through the soil (Tipping et al., 1999; Alborzfar et al., 2001; Lajtha et al., 2005). Most authors therefore consider that the DOC fluxes at a soil depth of about 0.90 to 1 m represent the DOC export by leaching (Guggenberger and Kaiser, 2003).

Bromide recoveries at 1.2 m equal an average of 23 g m–2 over all AETPLs which is close to the nominal dose of 24.9 g m–2. However, Br– recoveries at 0.4 m equal an average of 35 g m–2 over all AETPLs. On the basis of numerical simulations, Kasteel et al. (personal communication, 2006) attribute this apparent contradiction partly to the effect of upward water and Br– fluxes during dry periods. Bromide that passed the plates at 0.4-m depths during rain events can be transported upward again during a subsequent dry period and can be collected by the plates due to lateral exchanges. This is not the case for the plates at 1.2-m depth since the plane of zero flow (border between upward and downward flow) never reaches that deep in dry periods. We argue that this mechanism does not lead to overestimation of the DOC flux at 0.4 m: Gjettermann et al. (2004) report sorption partitioning coefficient (KD) values of DOC sorption to agricultural top and subsoils varying between 1 and 20 L kg–1. This is equivalent to retardation factors between 5 and 100 assuming a soil bulk density of 1500 kg m–3 and a volumetric moisture content of 0.4. This retardation is strong enough to limit oversampling of DOC at 0.4 m due to upward water fluxes.

Bromide Breakthrough in Relation with Total Amount of Leachate Volume
To further analyze and explain the large observed spatial variability in sampled leachate volumes by the different AETPLs, the first moments, T1, of the Br– breakthrough curves at each AETPL are calculated. Figure 3 plots the average Br– concentration of all AETPLs at 0.4 and 1.2 m against the corresponding average measured cumulative leachate volume or infiltration. The average T1 at 0.4-m depth is calculated to be 213 mm while at 1.2 m T1 equals 365 mm, both indicated on Fig. 3. This corresponds to an effective PV of 213 mm/400 mm or 0.53 at 0.4-m depth and 365 mm/1200 mm or 0.3 at 1.2-m depth. The effective PV of 0.53 at 0.4 m is unrealistically high but can be partly attributed to upward water fluxes during dry periods. Additionally, the first moments, T1, pore volumes, PV, number of PV captured by an AETPL, and the average water velocity, v, vary considerably between the different AETPLs. The variability in PV or T1 and in #PV or v may be explored by different hypotheses about the flow heterogeneity in the field:

  1. The capture zones have similar volumes and similar contributing areas (i.e., the area of the capture zone at the soil surface where water infiltrates uniformly) but the volumetric water content is different in the different capture zones (the uniform flow but variable water content case);
  2. The capture zones have similar volumes and similar volumetric water contents but different contributing areas (corresponds to the preferential flow case); and
  3. The capture zones have different volumes and different contributing areas but the capture volume and contributing area are correlated (tortuous flow field with locally convergent and divergent flow).


Figure 3
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  		Fig. 3. Average bromide concentration (mg L–1) against average cumulative infiltration (mm) of all automatic equilibrium tension plate lysimeters (AETPLs) at 0.4 and at 1.2 m, ie., the average breakthrough curves at 0.4- and 1.2-m depths. First moments (T1) are indicated by the vertical dotted lines.

 
The soil moisture contents measured using the TDR probes installed in the measuring trench (Fig. 1) revealed over the 2.5 yr average standard deviations of the 17 TDR probes at 0.45- and 1-m depths of 0.025 cm3 cm–3 at 0.45 m and 0.020 cm3 cm–3 at 1-m depth. Although no soil moisture content sensors were installed directly around the circumference of the different pits, large differences in soil moisture contents in between AETPL locations are therefore also unlikely. Hypothesis 1 can therefore be rejected since the volume of water sampled by the different AETPLs shows a large variability (Fig. 2). Hypothesis 2 implies that samplers that collect a high water volume are sampling preferential flow domains in which rapid transport occurs so that the v or #PV should be correlated to the total volume of water sampled. Since the capture zone volumes are assumed to be similar, the variance of T1 should be small. Figure 4 shows the total #PV sampled over the entire sampling period against the total amount of leachate volume sampled by each AETPL at 0.4- and 1.2-m depth. Since there is no correlation between the #PV and the total volume of water sampled (coefficient of determination R2 of 0.09 and 0.02 at 0.4- and 1.2-m depth respectively), the total amount captured by each AETPL is not a function of the average velocity of the water moving through the soil toward that AETPL. The lack of correlation between sampled volume or local water fluxes and the average velocity of the Br– tracer from the soil surface to the local samplers suggests that measured local high water fluxes or total sampled water volumes do not correspond with continuous preferential flow paths from the soil surface to the samplers so that hypothesis 2 can be rejected. This does, however, not imply that preferential flow did not occur during short periods within the experimental period but solely that it only minimally contributed to the total volume of water captured by each AETPL.


Figure 4
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  		Fig. 4. Total number of pore volumes (–) sampled against the total amount of leachate volume (mm) sampled by each automatic equilibrium tension plate lysimeter (AETPL) at 0.4 and 1.2 m.

 
When the capture volume is variable but correlated to the contribution area, AETPLs with a large contribution area or large total volume of water sampled correspond with a large capture volume that needs to be displaced before the tracer breaks through so that total volume of water sampled is correlated with T1. Figure 5 confirms this hypothesis and shows a positive correlation (linear correlation coefficient R2 of 0.80 and 0.75 at 0.4- and 1.2-m depth respectively) between the total amount of water sampled by each AETPL and its first moment, T1. Hypothesis 3 also assumes that variations of sampled water volume are due to a divergence or convergence of flow lines above the AETPL. Concluding we can say that water converged to some AETPLs (large T1) while circumflowing other AETPLs (small T1) and the large variability in sampled leachate volumes is related to the magnitude of the sampled pore volume but cannot be attributed to preferential flow processes.


Figure 5
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  		Fig. 5. First moment (mm) against the total amount of leachate volume (mm) sampled at 0.4 and 1.2 m.

 
Dissolved Organic Carbon Concentrations
The DOC concentrations in the 30 AETPLs over the monitoring period varied between 0.8 and 92.5 mg C L–1 at 0.4-m depth and 0.1 and 50.5 mg C L–1 at 1.2-m depth (Fig. 6). The mean and standard deviation of the DOC concentration in space and time over all AETPLs at 0.4-m depth is 17.0 ± 10.6 mg C L–1 compared with 9.3 ± 7.7 mg C L–1 at 1.2 m. Contrary to the large spatial variability in sampled leachate volumes and DOC fluxes presented in Fig. 2, spatial variations in DOC concentrations at both 0.4 and 1.2 m among AETPLs are small as indicated by the standard deviations. The coefficient of variation (defined as standard deviation divided by average) of measured leachate volumes over all 60 AETPLs over the entire experimental period is 1.03 while the coefficient of variation for the corresponding DOC concentrations only equals 0.76.This smaller variability in DOC concentrations in space and time at both depths as well as the further reduction in variability of the DOC concentration with depth suggests a buffering effect of the soil on the DOC concentration. In consequence, the large spatial variability in cumulative DOC fluxes is mainly due to the variability in leachate volumes and not due to differences in DOC concentrations between AETPLs. A positive correlation was indeed found between average annual DOC flux (x in g C y–1 m2) and annual leachate volume (y in mm) of all 30 AETPLs at 0.4-m depth (y = 89x, correlation coefficient = 0.89) and at 1.2-m depth (y = 119x, correlation coefficient = 0.83).


Figure 6
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  		Fig. 6. Average and standard deviation of the measured dissolved organic carbon (DOC) concentration (mg C L–1) at each of the sampling dates at 0.4- and 1.2-m depth.

 
Figure 6 shows that DOC concentrations follow the same temporal dynamics at 0.4- and 1.2-m depths from February 1999 onward, suggesting an environmental control on the DOC concentration. No soil temperature or soil moisture content was measured around the circumference of any of the pits. Therefore, soil temperature and soil moisture content measured in the nearby trench were used. No large differences were expected between soil temperature and soil moisture content around the pits and in the nearby measuring trench because of the flat topography and the small distance between both measurement locations. The DOC concentration measured in the leachate sampled at 0.4 and 1.2 m was influenced by soil temperature and soil moisture content of the entire soil through which it traveled. Therefore, soil temperature (0.05, 0.45, and 1 m) and soil moisture content measurements (0.2, 0.45, and 1 m) of the upperlying soil were used for comparison. Figure 7 shows that DOC concentrations are not associated with the temperatures (averaged over three temperature probes and in between the last and the sampling date of DOC measurement) measured at 0.05-, 0.45-, or 1-m depth in the nearby measuring trench. The lack of a temperature effect on the DOC concentration is in contrast with other studies (e.g., Guggenberger et al., 1998; Tipping et al., 1999). However, these studies report DOC concentrations under forest or cultivated land in contrast with the bare soil here. In those studies, decay of plant residues and microbial decay of this organic material is affected by temperature. No association is found between DOC concentrations and soil moisture contents at 0.20-, 0.45-, or 1-m depths (Fig. 7). As reported by Kalbitz et al. (2000), studies on the relationship between soil moisture and DOC concentrations have shown varying results. Several studies attribute the increase in DOC concentrations with increasing soil moisture content to an enhanced microbial activity. However, Guggenberger and Zech (1994) found no effects of soil moisture on the DOC concentrations, even under a forest floor. In this study, soil moisture content did not decrease strongly due to the absence of a growing crop.


Figure 7
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  		Fig. 7. Dissolved organic carbon (DOC) concentration (mg C L–1) against the averaged temperatures (°C) and soil moisture contents (cm3 cm–3) between two subsequent sampling dates.

 
The variability of DOC concentrations was further investigated in relation to water velocity. This may reveal if non-equilibrium sorption processes occur. Under the hypothesis that fast-flowing water has less time for interaction with the soil matrix and hence to be ‘loaded’ with DOC, a negative correlation between water velocity and DOC concentration is expected. Setting tmonitoring in Eq. [4] to the number of days between two subsequent sampling dates yields the time-averaged velocity of the water flow during the DOC sampling period. Figure 8 presents the relation between this average water velocity and the DOC concentration in the collected leachate at both 0.4- and 1.2-m depth. Figure 8 suggests a baseline value of the DOC concentrations, i.e., a minimum concentration independent of the water velocity. At 0.4 m this baseline concentration is around 9 mg C L–1 while at 1.2 m around 5 mg C L–1. Figure 8 also shows that high water velocities result in low DOC concentrations at both depths. This is consistent with the results of Münch et al. (2002) that show a decrease in DOC concentration with increasing pore water velocities in small unsaturated soil columns. Fast-flowing water results in a decreased contact time with the soil matrix and therefore less time for desorption and/or dissolution of DOC resulting in lower liquid concentrations compared with slow flow. This pattern corresponds to a model where two or more different processes control DOC concentration: a first process which controls the baseline concentration (an equilibrium concentration) and a second process(es) that releases additional DOC. The first process explains why the spatial variability in DOC fluxes is mainly affected by water fluxes. The second process(es) can have a limited net production rate (ie. kinetic process), yielding the inverse relationship with water velocity. Low leachate velocities are required to obtain high DOC concentrations, but not all slow flowing water contains high DOC concentrations, i.e., the second process(es) might be under environmental control. It is clear that such a concept requires experimental validation, e.g., using undisturbed soil columns with variable flow.


Figure 8
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  		Fig. 8. Time-averaged water velocity (mm d–1) between two subsequent sampling dates against measured dissolved organic carbon (DOC) concentration (mg C L–1) at 0.4- and 1.2-m depth.

 
At very low sampling speeds, there are a number of samples that have a DOC concentration below the baseline. These extreme low DOC concentrations were almost all sampled in August 1998 when maximum temperatures were recorded. A high microbial DOC consumption can be thought of as a possible reason to explain these extreme low DOC concentrations. From an environmental point of view, it is noteworthy that high DOC concentrations are only found in slow-flowing water. Therefore, DOC-facilitated transport occurs at relatively low velocities. This increases the chances of complete degradation in case of DOC-pesticide associations and increases the time in which metals originating from DOC-metal associations can sorb. It must be stressed that the inverse relationship between water velocity and DOC concentrations is observed under bare soil and may be different in soils amended with organic material (e.g., plant residues, forests, gray water, sludge, etc.) or in soils where preferential flow is significant.

In conclusion, our findings corroborate the statement by Kalbitz et al. (2000) that the soil hydrological regime, and in this study non-equilibrium transport processes in particular, is possibly more important than biotic controls when evaluating DOC concentrations under field conditions. It was found that the spatial variability in DOC fluxes to deeper soil horizons is primarily related to that of water flux. This suggests that DOC concentrations are buffered to some extent. However, an inverse relationship was found between the maximal DOC concentrations and water flux, indicative that maximal net release rate is limited.


   ACKNOWLEDGMENTS
 
This study was carried out as cooperation between the Agricultural Centre Monheim, BAYER AG, Leverkusen, and the Inst. of Chemistry and Dynamics of the Geosphere IV: Agrosphere (ICG-IV), Forschungszentrum, Jülich. Funding is also provided by Deutsche Bundesstiftung Umwelt, Osnabrück. This research was additionally supported by a grant of the Onderzoeksfonds Katholieke Universiteit Leuven, Belgium (GOA-06-07-TBA).


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