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Relating model parameters to basic soil properties.


The degree of preferential flow and transport differs from soil to soil and within a soil due to significant point-to-point changes in soil properties such as texture, structure, soil water content, bulk density or porosity, saturated hydraulic conductivity, clay content, and organic matter content (Jury 1986; Bouma 1990). All parameters characterising transport processes vary both laterally and vertically in an undisturbed soil (Donigian and Rao 1986).

Soil structure is one of the most significant soil physical properties that affect water and solute transport in a soil (Quisenberry and Phillips 1976; Beven and Germann 1982; Hatfield 1988; Andreini and Steenhuis 1990; Flury et al. 1994). Quisenberry and Phillips (1976) observed that water and solute flow through undisturbed (structured) columns was not convective-dispersive. Hatfield (1988) reported that applied water in a well-structured [B.sub.t] horizon of Cecil soil of the Piedmont region bypassed approximately 60-80% of the soil matrix once water entered macropores within the [B.sub.t].

Soil water content is one of the factors affecting water movement and chemical transport through macropores, but results have been contradictory. Some (White 1985; White et al. 1986; Shipitalo et al. 1990; Edwards et al. 1992) have reported that dry soil conditions increase macropore flow due to hydrophobicity of surface soil and cracks, while others (Coles and Trudgill 1985; Seyfried and Rao 1987; Ahuja et al. 1993) have reported that dry antecedent moisture conditions prevent macropore flow. Quisenberry and Phillips (1976) and Flury et al. (1994, 1995) observed that water and solute moved deeper under wet condition than dry condition in well-structured soils.

Quisenberry et al. (1993) proposed a soil classification system based on soil properties such as surface texture (clay content), clay mineralogy (expandable and non-expandable clays), and soil structure (structureless, massive, blocky, and prismatic) to predict water and chemical transport through soils. Although many experiments (Quisenberry and Phillips 1976; Hatfield 1988; Phillips et al. 1989; Nelson 1990; Han and Quisenberry 1991; Quisenberry et al. 1994; Bejat et al. 2000) quantifying the influence of texture and structure on water and solute transport have been conducted to evaluate this classification scheme, conceptualisations incorporating these soil characteristics into mathematical models are lacking. Roulier and Jarvis (2003) attempted to relate the model (MACRO) parameters to variations in fundamental soil properties.

In this study, we hypothesised that the model parameter values determined for a soil should be different from parameter values of other soils where each soil has unique properties. To test the hypothesis, the model was calibrated using the measured water content and solute (bromide or chloride) concentrations with depth and time in the profiles of 3 soils (Maury, Cecil, Lakeland). The calibrated model parameters for each soil were then plotted with depth on the same graph. Differences in the estimated parameter values of 3 soils were interpreted in relation to variations in fundamental soil characteristics such as texture and structure and thus the flow and transport characteristics of the soils. Whether there was a difference among the soils for a given model parameter was statistically tested.

Materials and methods

Model description

Jarvis et al. (1991) developed MACRO model, which is a detailed, mechanistic, dual-porosity model of water and solute transport in a soil. The MACRO model is a non-steady-state simulation of water flow and solute transport in a 1-dimensional (vertical) heterogeneous-layered field soils. A complete water balance is considered in the model, including saturated and unsaturated water flow. The model can be used to simulate non-reactive tracers (bromide, chloride), tritium, colloids, and pesticides. One of the important features of the model is that it can be run in either 1 (micropore) or 2 (micropore + macropore) flow domains using the same soil hydraulic properties. Since the model is presented in detail elsewhere (Jarvis and Larsson 1998), we will only describe in detail the parts that are especially related to this study.

The soil porosity is divided into 2 domains, micropores and macropores, at a given soil water pressure (boundary soil water pressure or tension, [[psi].sub.b]) and corresponding water content (boundary water content, [[theta].sub.b]) and hydraulic conductivity (boundary hydraulic conductivity, [[KAPPA].sub.b]). Micropores and macropores act as separate flow regions and each is characterised by a degree of saturation, conductivity, and flux. The vertical water flow through the micropores in the unsaturated zone is calculated using the Richards' equation:

[partial derivative][theta]/[partial derivative] = [partial derivative]/ [partial derivative]z[[KAPPA].sub.mi] ([partial derivative][psi]/ [partial derivative]z [+ or -] [S.sub.w]

where [theta] is the water content, t is the time, z is the vertical distance, [[KAPPA].sub.mi] is the unsaturated hydraulic conductivity in the micropores, is the soil water pressure, and [S.sub.w] accounts for water exchange between the 2 domains. The water release characteristic, [psi]([theta]), and the hydraulic conductivity function in the micropores, K([theta]), are calculated by the Brooks and Corey (1964) and the Mualem (1976) equations, respectively. The vertical water flow through the macropores is calculated by the Darcy equation assuming a unit hydraulic gradient (laminar flow under gravity, i.e. tension is not considered), the numerical equivalent of the analytical kinematic wave model (Germann and Beven 1985). Water exchange between the 2 domains, [S.sub.w], is treated as an approximate first-order process, neglecting the influence of gravity (Booltink et al. 1993) and assuming rectangular-slab geometry for the aggregates (van Genuchten and Dalton 1986).

Solute transport in the micropores is calculated by the convection--dispersion equation (CDE):

[partial derivative]([theta]c)/[partial derivative]t = [partial derivative]/[partial derivative]z(D[theta] [partial derivative]c/[partial derivative]z - qc)[+ or -][U.sub.e] D= [D.sub.v][[upsilon].sub.mi] + [D.sub.o]f*

where c is the solute concentration, D is the dispersion coefficient, q is the Darcy water flux density, [U.sub.e] is the source/sink term representing mass exchange between flow domains, [D.sub.v] is the dispersivity, [v.sub.mi] is the pore water velocity, [D.sub.o] is the diffusion coefficient in free water, and f* is the impedance factor (the constant). The solute transport in the macropores is calculated by neglecting the dispersion and diffusion in the CDE because convective transport is a dominant process in the macropores. The diffusive exchange of solute between the 2 flow domains and the convective fluxes of water and solute into the micropores are considered in the model. The exchange of solute between the micropores and macropores, [U.sub.e], is calculated by a combination of diffusion and convection (Jarvis and Larsson 1998).

Model parameters for the study

Model parameters were obtained from the simulation of water flow and solute transport in 3 soils with contrasting properties. The 3 studies will be briefly described. Quisenberry and Phillips (1976) applied water-tagged chloride to the surface of 6 plots of Maury silt loam soil by hand with a garden hose that had a wide nozzle and measured water content and chloride concentration distribution with depth (13 layers) and time (<2 days) after the application ceased under field conditions. The water flowed by gravity from an elevated barrel, and as a result, the rainfall intensity decreased slightly with time as the water head decreased. Ponding was never observed in any plot. Studies were conducted at different times during the growing season to study infiltration under different initial water conditions (see Quisenberry and Phillips 1976 for the experimental details).

Hatfield (1988) measured soil water pressure, soil water content, and unsaturated hydraulic conductivity as a function of water content,

[KAPPA]([theta]), with depth (5, 10, 15, 20, 30, 45, 60, 75, 90, and 105 cm) and time (every day during the 1-month drainage period) on 6 plots of Cecil loamy sand (clayey, kaolinitic, thermic Typic Hapludults) in the Clemson Experimental Forest near Clemson, South Carolina. Each plot area was enclosed with wooden boards installed to a depth of 0.15 m to allow ponding of applied water. Water was ponded on the soil surface until no change in water pressure with depth was observed. Each plot was covered with plastic to prevent loss of water due to evaporation. Hatfield (1988) also conducted soil water and chloride percolation experiments on 4 plots near the 6 in situ conductivity plots. Water containing chloride (2100 [micro]g/g) was applied to each plot with a rainfall simulator at 38.1 mm within 1 h. After the application of water and chloride and a 2-h redistribution period, 100 soil cores (samples) were obtained from each of 7 depths to determine the gravimetric water and chloride contents (see Hatfield 1988 for the experimental details).

Similarly, 2 experiments were conducted on Lakeland sandy soil. Dane et al. (1983) measured the distribution of drainage water with depth and time. Water was ponded on the soil surface until no change in water pressure with depth was observed. Nelson (1990) determined the distribution of water and bromide with depth 2 h after cessation of the application of 38.1 mm of bromide-tagged water (2705 [micro]g/g) within 1.5 h with a rainfall simulator composed of PVC with small holes drilled along the tops of the horizontal tubes (Nelson 1990). Eight hours before the experiment began, 25 mm of water was applied to the plots. Chloride-tagged water of 38.1 mm (1200 [micro]g/g) was applied as the initial solution 2 h before the bromide-tagged water application. Plots were covered with black plastic to prevent evaporation between applications (see Nelson 1990 for the experimental details).

Input parameters used in the MACRO model simulations may be divided into 3 groups: initially, those parameters that are directly measured through experiments; later these are either known or estimated from the literature; and finally they are directly calibrated by fitting model predictions to the observed data. The parameters directly measured were: soil water retention data; hydraulic conductivity as a function of water content; initial soil volumetric water content and solute concentration; bulk density; saturated water content; the day, number, amount, beginning and end of irrigation (actually user defined); and solute concentration in irrigation water. The parameters that were either known or estimated from the literature were: initial soil temperature, excluded volumetric water content, and diffusion coefficient in free water. Effective diffusion path-length (or aggregate half-width) was inferred from physical properties (particle size distribution) of soils and literature values (Saxena et al. 1994; Villholth and Jensen 1998; Larsson et al. 1999; Larsson and Jarvis 1999a, 1999b; Roulier and Jarvis 2003). Saturated hydraulic conductivity was estimated from the reports of Romkens et al. (1985) for Maury soil, Bruce et al. (1983) and Hatfield (1988) for Cecil soil, and Dane et al. (1983) for Lakeland soil. The parameters directly calibrated by fitting model prediction to observed data were: boundary pressure potential, boundary water content, residual water content, pore size distribution index in micropores, boundary hydraulic conductivity, tortuosity factors in macropores and micropores, dispersivity, and mixing-depth.

When water content is larger than the boundary water content, the pressure is calculated assuming a linear function, [psi]= [[phi].sub.b](([[theta].sub.s] - [theta])/([theta].sub.s] - [[theta].sub.b])). When the water content is smaller than the boundary water content, the pressure is calculated by the Brooks and Corey (1964) function, [psi] = [[psi].sub.b](([theta] - [[theta].sub.r])/([[theta].sub.b] - [[theta].sub.r]))- 1/[lambda]. After boundary pressure potential and corresponding water content were estimated visually from the water retention curve for each layer, water-retention data were fitted in MATLAB by using the Brooks and Corey (1964) equation, [psi] = [[psi].sub.b](([theta] - [[theta.sub.r])/([[theta].sub.b] - [[theta].sub.r]))-1/[lambda], to obtain the values of residual water content and the pore size distribution index in the micropores. If the water-retention data were not fitted accurately, different boundary soil water pressure and corresponding water content were chosen from the water-retention curve until the retention data were fitted.

When water content was larger than the boundary water content, a simple power law function, [KAPPA] = [[KAPPA].sub.b] + ([[KAPPA].sub.s] - [[KAPPA].sub.b])(([theta] - [[theta].sub.b])/([[theta].sub.s] - [[theta].sub.b))n*, was used to fit the measured conductivity-water content relation. Boundary hydraulic conductivity was determined from the measured conductivity-water content relation using boundary water content at the beginning of the modelling process. However, since the model could not simulate measured water content and chloride concentration with the measured values of the parameter, the boundary hydraulic conductivity was used as the fitting parameter in the model. The tortuosity factors in macropores, n*, and micropores, n, were used as fitting parameters.

After the simulation of water content with depth and time, the measured solute distribution was simulated. Three parameters affect solute transport in the model: (i) excluded volumetric water content, (ii) dispersivity, and (iii) mixing depth. We assumed no excluded volumetric water content due to anion exclusion in the profile. The dispersivity and mixing depth were directly calibrated by fitting the model's prediction to the observed data. The diffusion coefficient for water was set to [4.6e.sup.-10] [m.sup.2]/s in each plot.

The model parameters used in this study were effective diffusion path-length or aggregate half-width, boundary soil water tension, boundary hydraulic conductivity, saturated hydraulic conductivity, tortuosity in macropores, dispersivity, and mixing depth. The values of a given parameter for 3 soils were plotted with depth on the same graph and the results were interpreted based on the characteristics of the soils. Statistical analysis (ANOVA test) was made to determine if the means of a given model parameter for 3 soils were significantly different. Keeping the parameters constant in each soil, the model was run 2 times for each soil with the same application of water-tagged chloride in all 6 runs (4 cm in 2 h with 3000 [micro]g/g chloride). Initial chloride concentration in the profile of 3 soils was assumed to be zero. In one of the 2 runs, initial water content was assumed at the field capacity, whereas in the other run initial water content was 3% less than the field capacity, to investigate the effect of the relationship between initial water and field capacity on flow and transport properties of soils.

Results and discussion

Quisenberry and Phillips (1976) reported that macropore flow began at the soil surface in an undisturbed Maury silt loam soil, whereas macropore flow started at the tilled-untilled boundary (at 15 cm) if the soil was thoroughly tilled. Therefore, 2 types of flow occur in Maury soil: Darcian and preferential flow in the surface 15 cm, and mostly preferential flow below that depth. The description of flow through the profile of Maury soil is sketched in Fig. 1 for tilled soil.

Hatfield (1988) showed similar results for water and chloride transport in a Cecil soil. He determined that small decreases in water content greatly reduced [KAPPA] values below the 20-cm depth of 6 plots. Water moves more uniformly through the sandy soil near the surface due to more uniform distribution of soil pores, but non-uniformity in soil pores (effective soil structure) due to higher clay content in the lower part of the profile caused water to flow rapidly through the macropores. Spatial variability in macropore flow led Quisenberry et al. (1993) to consider Brewer's (1976) concept of primary, secondary, and tertiary structural units for Cecil soil. They observed that grass roots are often concentrated around the tertiary structural units in soils with strong structure. They hypothesised that the rapid macropore flow enters between tertiary structural units and continues to flow through these channels. Flow through the profile of Cecil soil is described in Fig. 1 for tilled soil.

Lakeland soil is composed of structureless and single-grained coarse sand. However, there is a sharp increase in the size fraction of the sand at approximately 30 cm even though the texture of the Lakeland soil is sand throughout the profile. Water flows uniformly through structureless and single-grained sand within the surface 30 cm. As soon as the water reaches the interface of the fine layer and the bottom coarse layer, fingers develop due to the difference in conductivities of the horizons. Flow through the Lakeland soil is described in Fig. 1 for tilled soil.

The clay content of Maury within the surface 15 cm is about 25% and increases linearly below that depth to 55% at 90 cm depth (Fig. 2a). The clay content of Cecil increases from 10% in the surface 10 cm to 70% at 30 cm depth and then decreases linearly to 50% at 105 cm depth (Fig. 2a). The clay content is <7% throughout the profile of the Lakeland (Fig. 2a). The soils are significantly different from each other in terms of clay content based on the ANOVA test (F2.27=24.713, P<0.05). Quisenberry et al. (1993) believed that the uniformity of flow, or extent of piston-type flow, is directly related to the aggregation of the A horizon, and aggregation in these soils is directly related to clay content. They showed a relationship between percent displacement within Ap horizons and clay content. The displacement was nearly complete (>95%) in soils with clay content <8%. However, a moderately linear relationship was observed for clay contents 8-30%. The per cent displacement was 15, 40, and 85% for the Maury, Cecil, and Lakeland soils, respectively.

Since clay content is low near the surface of the 3 soil profiles, aggregation or soil structural development is assumed to be weak except in the Maury. The clay content of Maury and Cecil below 15 cm depth is >25%; therefore, both soils had a well-developed structure. Flow is uniform near the surface of the profile through individual sand particles in Lakeland sandy soil, but channelling begins below 30 cm depth because of different sand layers. Aggregation or soil structure is represented in the model by the parameter of effective diffusion path-length or aggregate half-width. The values of this parameter with depth for 3 soils are shown in Fig. 2b. Smaller values of the parameter were used in the model for the 3 soils near the surface because of weak aggregation. The larger values were set in the model for depths lower than 15 cm in the Maury and Cecil soils, which indicates a slow exchange of water-tagged solute between the macropore channels and the soil matrix and results in a stronger preferential flow. Even though clay content is <7% throughout the profile of Lakeland soil, a large value of aggregate half-width was set based on the assumption that soil mass between the channels was an aggregate. The ANOVA test showed that the values of effective diffusion path-length (d), which is one of the key parameters controlling the extent of preferential flow, were not different ([F.sub.2.29] = 0.419, P = 0.662) among 3 soils. However, Roulier and Jarvis (2003) found significant difference (P < 0.05) between the diffusion path-lengths of hilltop (d = 96mm) and hollow (d = 13.2mm) soil columns. They also inferred that the diffusion path-length seems closely related to clay content where the hilltop and hollow soil columns had clay contents of 25.4 and 19.7%, respectively, indicating that soil texture has a significant control on soil structural development and, hence, preferential flow and transport.

Keeping the other model parameters constant, the model was run with 2 different initial water contents (less than or equal to the field capacity) for 3 soils to determine the response of the soils to initial water content. The main objective was to differentiate soils by utilising the effect of the initial water content on flow and transport properties of soils. The complete (100%) displacement was calculated to compare with the actual displacement of 3 soils. The results are presented in Fig. 3. When initial water content was at field capacity, the effect of preferential flow was more significant than when the initial water content was 0.03 [cm.sup.3]/[cm.sup.3] less than field capacity. As a result, less water and chloride were recovered in the profile of Maury soil. The recoveries of water and chloride were 49% and 60%, respectively, when initial water was equal to field capacity and 65% and 68% when initial water was 0.03 [cm.sup.3]/[cm.sup.3] less than field capacity (Fig. 3a). Quisenberry and Phillips (1976) reported the same results in their experimental study.


In the Cecil soil, less water was recovered in the lower initial water content and all of the applied chloride was recovered in both low and high initial conditions. The recoveries of water and chloride were 100% and 100% when initial water was equal to field capacity and 91% and 100% when initial water was 0.03 [cm.sup.3]/[cm.sup.3] less than field capacity (Fig. 3b). Similar to the Maury soil, preferential flow was more effective at the higher initial water content in the Lakeland soil. The recoveries of water and chloride were 98% and 100% when initial water was equal to field capacity and 100% and 100% when initial water was 0.03 [cm.sup.3]/[cm.sup.3] less than field capacity (Fig. 3c). in macroporous soils, the degree of macropore flow depends on the application rate, hydraulic conductivity, and initial water content. When the application rate exceeds the hydraulic conductivity, preferential flow through the macropores is likely to occur. Macropores become active as initial water content approaches the field capacity because micropores in the oil matrix are full of water and any added water starts flowing through macropores. Therefore, the relationship between initial water content and field capacity might help to determine the degree of the preferential flow.

Quisenberry et al. (1993) organised soils into 4 groups based on texture of the A horizon. In group 1 soils, clay content <8%, water and solute moved quite uniformly through the A horizon, and displacement of antecedent soil solution by the applied solution was nearly complete. Complete displacement was also calculated to show the uniformity of flow, or extent of piston-type flow. The increase in chloride concentration does not correspond to the increase in water content in Lakeland soil. Although water content does not increase within the 50-cm depth, chloride concentration increases significantly. This is an indication of a high level of displacement of antecedent moisture with the applied water because of low clay content (<8%). The displacement is almost complete at the top 15 cm of the profile. However, below the interface of a fine and a coarse sand layer, a significant fraction of the soil matrix will not be involved in the flow process because of fingering, and as a result, displacement is low (Fig. 3c).

In group 2 soils, clay content >8%, displacement in the A horizon is also high, but not as much so as group 1. The increase in chloride concentration with depth corresponds to the increase in water content in Cecil soil (Fig. 3b). If applied chloride-tagged water displaced the antecedent moisture in the soil matrix completely, chloride would reach the depth of 13.7cm. The arrival of chloride at the bottom of the profile is an indication of little displacement of antecedent water by the applied water. Flow through macropores causes water and chloride to reach the bottom of the profile at shorter duration than expected based on the common flow and transport theory.

In group 3 soils, clay content >8%, the percent displacement of antecedent solution with the applied solution is smaller than that of the groups 1 and 2. The increase in chloride concentration with depth corresponds to the increase in water content in Maury soil (Fig. 3a). This indicates that water-tagged chloride is not displacing antecedent soil water in the soil matrix; rather, it flows through some preferred pathways such as macropores. If the displacement was complete (100%), chloride would reach the depth of 8.4 cm. Even at the top 15 cm, the displacement was much less than the complete displacement because macropore flow begins at or very near the soil surface in silt loam soils. Only 2h after the application ceased, 49 and 60% of water and chloride were retained, respectively, in the profile (Fig. 3a).

Quisenberry et al. (1993) divided soils with non-expandable clays and quite strong structure into 2 groups: soils with primary and tertiary units and soils with only primary units. They reported that soils with primary units had much more uniform flow than soils with primary and tertiary units. However, in our study, Maury soil with only primary units has less displacement and recovery of chloride than that of Cecil soil with primary, secondary, and tertiary soil structural units (Fig. 3a, b).

In addition to the 3 main soil properties (texture, structure, and initial water content), significant model parameters (boundary water tension, boundary hydraulic conductivity, saturated hydraulic conductivity, and tortuosity in macropores) have been related to fundamental soil properties and thus their flow and transport characteristics (Fig. 4a-d).


Boundary soil water potential is constant with depth in the profiles of Maury, Cecil, and Lakeland soils, and the values are -7, -10, and -24.4 cm, respectively (Fig. 4a). Since the macroporores and, hence, macropore flow are dominant in sandy soils, especially at the bottom coarse sand layer with the contribution of fingers, using the largest value of boundary soil water potential might be representative for Lakeland soil. Even though this value is a division of soil pores into the macropore and micropore regions, it may not mean that pores having a smaller tension than this value are all conducting water through macropores, because this parameter alone does not control the magnitude of macropore flow. For instance, the relationship between the application rate and boundary hydraulic conductivity (saturated hydraulic conductivity of soil matrix) is also a significant parameter controlling this relation. Since the clay content at the lower depths of Cecil soil is higher than that of Maury soil, macroporosity might be lower as shown by water-retention curves. Very small values of boundary hydraulic conductivity at the top 15-cm depth in Maury soil indicate that a significant amount of water flow occurs through macropores (Fig. 4b). Similarly, Roulier and Jarvis (2003) showed that smaller values of the boundary hydraulic conductivity of the hilltop columns with higher clay content lead to a more frequent activation of the macropores. The ANOVA test indicated that the values of boundary hydraulic conductivity ([K.sub.b]), which is one of the key parameters controlling the extent of preferential flow, were significantly different ([F.sub.2.29] = 45.124, P < 0.05) among 3 soils. Roulier and Jarvis (2003) reported a similar result.

Saturated hydraulic conductivities with depth for Maury and Cecil are very similar, whereas the conductivity of Lakeland is higher than that of the others, especially at the lower depths (Fig. 4c). In general, since saturated hydraulic conductivity of a sandy soil is expected to be higher than that of the silty or clayey soil, using the higher value of this parameter for Lakeland soil might be representative. The ANOVA test revealed that the values of saturated hydraulic conductivity ([K.sub.b]) were significantly different ([F.sub.2.29] =43.807, P < 0.05) among 3 soils.

The same values of tortuosity in macropores with depth were used for Maury and Cecil except at the 20-cm depth of Cecil, and the smallest value of tortuosity was used for Lakeland except for the last 2 depths (Fig. 4d). Since the macropores in sandy soils such as Lakeland are composed of the pores between the individual sand particles, they are mostly straight compared with the pores in Maury and Cecil, where macropores are composed of cracks, worm holes, or root channels. The ANOVA test showed that the values of tortuosity in macropores were not different ([F.sub.2.29] = 0.703, P > 0.05) among 3 soils.

The constant parameter values with depth for each plot of each soil are given in Table 1. The mean dispersivity of the Maury soil (30 cm) is significantly larger than that of the Cecil soil (1 cm) even though similar tortuous macropores exist due to high clay content in both soils. Roulier and Jarvis (2003) determined that the estimated average dispersivity of the hilltop columns with higher clay content was significantly larger than that of the hollow columns with lower clay content. Similarly, the small values of dispersivity used in Lakeland soil might be reasonable because of low clay content. Mixing depth is here defined as the depth of complete mixing of resident soil water and incoming net rainfall. This controls solute concentrations in any excess water routed into the macropores at the soil surface. A higher value of mixing depth means more displacement of antecedent soil water with the applied water. Therefore, more retention of chloride occurs in the profile. A lower value of mixing depth causes less displacement of initial soil water with the applied water. Therefore, less chloride is retained in the profile. Since the flow occurs mostly through the macropores near the surface in Maury soil, the depths for the mixing of the applied and the antecedent water are very small for all 6 plots. In the sandy surface of Cecil soil, the mixing depths are, as expected, larger. However, in the similarly sandy surface of Lakeland soil, a very small value of mixing depth was used, possibly due to the effect of clay type and organic matter even though they are not so significant. The same value (0.5) of the tortuosity in the micropores with depth was used for the 3 soils.


The model parameters obtained from simulation of water flow and solute transport for 3 soils with contrasting properties were related to the basic properties and thus flow and transport characteristics of the soils, to determine whether the parameters defined for MACRO model reflected known differences in the physical characteristics of these 3 soils.

Although the soils had, based on the statistical analysis, contrasting textures (specifically clay content), the parameter values of effective diffusion path-length, which represents aggregation or structural development in the model, were not statistically different for 3 soils. In addition, the difference in tortuosity in macropores among 3 soils was not significant. However, soil hydraulic parameters such as saturated and boundary hydraulic conductivities were statistically different. The mean values of boundary soil water pressure were -7, -10, and -24.4cm for Maury, Cecil, and Lakeland soils, respectively. The mean values of solute transport parameters such as dispersivity and mixing depth were 30, 1, and 1 cm and 0.23, 1.47, and 0.001 mm for Maury, Cecil, and Lakeland soils, respectively.

These results suggest that relating the model parameters to basic soil properties in order to differentiate them by looking at the values of a given model parameter is promising even though the parameters such as effective diffusion path-length and tortuosity in macropores are not statistically different among the soils. Since the values of these 2 parameters are difficult to measure experimentally or estimate from well-established equations, the estimated values from the particle size distribution and literature might not be as accurate as they should be. More accurate estimation of these 2 parameters through experimental studies might lead to a better development of such a relation. For a future study, similar research might be conducted on a number of different soil series in order to develop a general soil classification system. Such a system can help to identify soil properties which affect transport processes and provide framework for development, or improvement, of mathematical transport models.
Table 1. Constant parameter values with depth for the simulation of
water flow and solute transport in the plots of Maury, Cecil, and
Lakeland soils


 1 2 3 4 5 6

 Dispersivity (cm)

Maury 50 10 50 50 10 10
Cecil 1 1 1 1
Lakeland 1

 Mixing depth (mm)

Maury 0.0001 0.0010 1.00E-07 0.0001 0.80 0.60
Cecil 2.8 2 0.1 1
Lakeland 0.001

 Tortuosity in micropores

Maury 0.5 0.5 0.5 0.5 0.5 0.5
Cecil 0.5 0.5 0.5 0.5 0.5 0.5
Lakeland 0.5 0.5 0.5 0.5 0.5 0.5


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Manuscript received 4 June 2003, accepted 25 May 2004
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Author:Merdun, Hasan; Quisenberry, Virgil L.
Publication:Australian Journal of Soil Research
Date:Dec 1, 2004
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