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DIVISION S-1-SOIL PHYSICS

Water Flow in Unsaturated Soil Below Turfgrass

Observations and LEACHM (within EXPRES) Predictions

^a Dep. of Land Resource Sci., Univ. of Guelph, Guelph, ON, Canada N1G 2W1

gparkin{at}lrs.uoguelph.ca

	ABSTRACT

TOP ABSTRACT INTRODUCTION Materials and methods Results and discussion Conclusions REFERENCES

 
In cropped soils, water sustains the plants, affects the transport of nutrients within the root zone, and controls the leaching of nutrients and chemicals to ground water. The objectives of this study were (i) to investigate the effects of turfgrass on water flow in sandy loam soil during the growing season using field lysimeters, and (ii) to test the abilities of the models EXPRES and LEACHN with free-drainage and lysimeter bottom-boundary conditions, respectively, to simulate water movement in the lysimeters. Twelve field lysimeters were packed with a three-horizon profile, topped with Kentucky bluegrass (Poa pratensis L.) sod, and monitored for 2 yr. Saturated hydraulic conductivity, measured on cores, was much greater and more variable for turf than soil. The moisture-retention curve for turf also had a much steeper drop in water content at low applied negative head than soil. The lysimeters became very dry during the summer, and only drained during the spring and autumn. The model EXPRES generally predicted water flow well, but had some difficulty with water redistribution during the drying periods (gravity drainage and evapotranspiration). In general, with the free-drainage bottom-boundary condition, EXPRES predicted more drainage and less drying during the summer than was observed. Under conditions of little to no irrigation, the free-drainage condition over-predicted and the lysimeter condition under-predicted the total amount of measured drainage. Model predictions of drainage under heavily irrigated conditions were similar for both bottom-boundary conditions.

Abbreviations: AE, average error • EXPRES, Expert System for Pesticide Regulatory Evaluations and Simulations • GTIERC, Guelph Turfgrass Institute and Environmental Research Centre • ME, maximum error • PET, potential evapotranspiration • RMSE, root mean square error • TDR, time domain reflectometry

	INTRODUCTION

TOP ABSTRACT INTRODUCTION Materials and methods Results and discussion Conclusions REFERENCES

 
THE WATER REGIME IN CROPPED SOILS

is important for the water needs of plants, the transport of nutrients within the root zone, and the leaching of chemicals to ground water. Turfgrass is a unique crop that requires unique management practices. It is valued for its aesthetic, recreational, and robust properties, and is especially important in urban areas where lawns, parks, golf courses, and recreational fields make up a considerable portion of unpaved land. Turfgrass can influence the water regime through plant uptake for evapotranspiration during the time it is biologically active (Fetter, 1994), changing hydraulic gradients in the process and affecting the physical properties of the transport medium, due to thatch development and rooting in the soil below. Turf's high growth density greatly modifies overland flow, nearly eliminating runoff in favor of infiltration. The overall effect is an increase in the amount of water entering the soil, which increases the water content and promotes solute transport (Beard and Green, 1994). The turfgrass system also has an abundance of earthworms; their burrowing increases aeration and water infiltration (Potter, 1993). These burrows, essentially single or interconnected macropores, can also act as primary flow conduits, providing rapid downward flow of solutes during ponded water conditions (Stehouwer et al., 1994).

For the past decade, more attention has been focused on turfgrass with respect to solute transport in cropped systems, mainly due to the perceived threat of fertilizer and pesticide leaching from golf courses. However, only recently have researchers started to use computer models in this area (Franke, 1992; Smith et al., 1993; Jabro et al., 1997). Many models have been developed to simulate transport through the soil, including PRZM (Carsel et al., 1984), LEACHM (Wagenet and Hutson, 1987), and CMLS (Nofziger and Hornsby, 1987). These deterministic models, which use a time-invariant set of model parameters to produce a unique solution, are based on physical processes of water infiltration, redistribution, and evaporation. Therefore, they are useful for testing our understanding of water flow or chemical transport behavior and for guiding further research efforts (Rao et al., 1988). Models can also be used to develop better management practices based on site-specific conditions.

The model EXPRES (Expert System for Pesticide Regulatory Evaluations and Simulations) (Mutch et al., 1993), developed as a management tool, combines the research models PRZM and LEACHM (Version 2) with a user-friendly interface. The model EXPRES includes extensive geographical and pesticide databases. We chose to test LEACHM within EXPRES mainly because the developers of EXPRES have added a snowmelt routine to LEACHM. This modification is particularly suitable for the climate conditions at our field site in Ontario, Canada.

Our objectives were (i) to measure the water content and drainage in unsaturated, sandy soil using field lysimeters topped with Kentucky bluegrass turf for two growing seasons, and (ii) to test the ability of the model LEACHM (within EXPRES) with a free-drainage bottom-boundary condition to simulate the soil water processes in this system. One drawback of EXPRES is that it does not have the lysimeter bottom-boundary condition option as available in the LEACHM, Version 3 set of programs, which includes LEACHN for simulating water flow and N transport under a crop. To assess the impact of the bottom-boundary condition on drainage calculations, we also used LEACHN, Version 3 (Hutson and Wagenet, 1992) with the lysimeter bottom-boundary condition to simulate the soil water processes in this system. The soil hydraulic properties of the turf layer were measured, and simulations using EXPRES and LEACHN were used to identify the turf layer's effect on water flow. Field measurements of soil water content and drainage from lysimeters were compared with EXPRES predictions. To date, testing of the LEACHM package has focused mainly on the transport of solutes, particularly inorganic tracers (bromide or chloride), fertilizers, and pesticides. The comparison of measured and modeled water balance components with the hydraulic properties of the turfgrass included in the models has not been addressed. In this study, we primarily examine water flow since it is generally the dominant process in solute transport and it is essential that a model simulate it effectively.

	Materials and methods

TOP ABSTRACT INTRODUCTION Materials and methods Results and discussion Conclusions REFERENCES

 
Lysimeter Set-up
Field lysimeters (Fig. 1) were constructed from 118-L, high-density polyethylene tanks, which are 81-cm long by 43-cm diam. cylinders with an 18-cm deep conical bottom and a 5-mm wall thickness (CANBAR, Waterloo, ON). The tanks were filled with Lisbon sandy loam from the Cambridge Research Station (near Cambridge, ON) and with 0.63-cm (¹₄'') diam. pea gravel in the conical bottom. The lysimeters were buried at the Guelph Turfgrass Institute and Environmental Research Centre (GTIERC) (43°32'50'' N, 80°13'50'' W), Guelph, ON, in the spring of 1995, placed even with the surrounding ground surface to prevent unnatural runoff or ponding. The entire site was then covered with Kentucky bluegrass sod. The grass was cut with shears to a minimum height of 5 cm, with the clippings left on the surface. The soil profile consists of a 5-cm thick turf layer, including about 2 cm of thatch (a layer of fibrous organic material and soil), a 25-cm thick A horizon (sandy loam) repacked to a dry bulk density of 1.55 g cm^-3, a 25-cm thick B horizon (loamy sand) repacked to a dry bulk density of 1.60 g cm^-3, and a 31-cm thick C horizon (sand) repacked to a dry bulk density of 1.65 g cm^-3.

View larger version (40K): [in this window] [in a new window]   Fig. 1 Schematic diagram of a lysimeter installed at GTIERC

Soil Hydraulic Properties
Air-dried soil for all three horizons was passed through a 2-mm sieve and repacked in cores to the same bulk density as in the lysimeters. Cores from the turf, including the thatch, were collected in situ from an additional lysimeter at GTIERC. Measurements of the soil water retention curve, between 0 and -1500 kPa, were made via the pressure plate method (Klute, 1986) using 3-cm long cores. The saturated hydraulic conductivity, K_s, was measured using 5- or 7-cm long repacked cores via the constant head permeameter method (Klute and Dirksen, 1986). Particle-size distribution was measured using the hydrometer method (Gee and Bauder, 1986).

To describe the water retention curve, EXPRES (and LEACHN) use functions relating volumetric water content () and matric potential (h), based on those proposed by Campbell (1974):

(1)

where _s is the volumetric water content at saturation, and a and b are empirical constants. Equation [1] was fit to the water-retention data using a nonlinear least squares fitting procedure available in MathCad, Version 6 (MathSoft, 1995).

Field Experiment
The study comprised two field seasons: the 1996 field season ran from 19 July 1996 to 8 Nov. 1996, and the 1997 field season ran from 11 May 1997 to 20 Dec. 1997. Twelve lysimeters were monitored in 1996 and 11 were monitored in 1997. Average values of water content measured by TDR and drainage were calculated and used for model testing. Half of the 12 lysimeters received irrigation of 46.2 mm on 25 July and 53.8 mm on 8 Aug. 1996, so separate modeling runs were performed for both conditions. All 11 lysimeters were irrigated with 10 mm of water on 5 Aug. 1997. Nitrogen fertilizer was applied at 160 kg N ha^-1 to six lysimeters on 17 July and 29 Oct. 1996, and to four lysimeters on 14 May, 25 July, and 28 Sept. 1997.

The climate data required as input for the models include air temperature, precipitation, and potential evapotranspiration (PET). Preliminary screening of several empirical models by Qian et al. (1996) revealed that the Penman–Monteith equation provided the most accurate estimate of turfgrass evapotranspiration; therefore, this equation, as described in Burman and Pochop (1994), was used. Hourly values of net radiation were obtained from the Elora weather station, Elora, ON, 15 km north of GTIERC. Hourly air temperatures, wind speeds at 10 m, and relative humidity readings were obtained from the GTIERC weather records. Any missing values at GTIERC were replaced with Elora weather data. Precipitation was also measured at GTIERC. Rainfall was determined with a tipping-bucket rain gauge, with a manual gauge for backup. Average snow depth was determined with a metered ruler and converted to depth of water using a snow density conversion of 0.10 cm of liquid water per cm of solid snow (Dunne and Leopold, 1978).

Model Descriptions
The computer model EXPRES (Mutch et al., 1993) contains a pesticide screening assessment and two mathematical simulation models, LEACHM (pesticide fate version) and PRZM, coupled to a text/graphical user–system interface and geographical and pesticide databases. The model LEACHM, Version 2 (Wagenet and Hutson, 1987) is a research-oriented simulation model requiring an extensive set of input parameters and variables describing site-specific soil, plant, and climatic conditions. Modeling was performed with independently measured parameters or those reported in the literature, including the EXPRES manual (Mutch et al., 1993). No attempt was made to derive parameters using the model and inverse procedures.

The subroutine for water flow, WATFLO, solves the one-dimensional Richards' equation:

(2)

where C(), the water capacity function, equals d/d; K() is the hydraulic conductivity as a function of matric head, ; is the volumetric water content; _w is a water source–sink term; z is depth; and t is time. See Wagenet and Hutson (1987) for more details on LEACHM, Version 2. The LEACHM model within EXPRES was modified by Mutch et al. (1993) to simulate snowmelt based on the mean daily temperature, and to account for surface runoff and losses of water and pesticide due to erosion.

A free-drainage bottom-boundary condition was selected for the EXPRES model runs. A lysimeter bottom-boundary condition was selected for the LEACHN, Version 3 model runs. The lysimeter bottom-boundary condition will allow drainage to occur only if the pressure head at the bottom of the lysimeter is zero or above, while the free-drainage bottom-boundary condition allows continuous drainage under a unit hydraulic gradient. See Hutson and Wagenet (1992) for more details on LEACHN, Version 3.

Model Inputs
Table 1 contains a list of the parameters required by the models and their values, excluding the measured soil properties, which are listed in Table 2 . The Help feature in EXPRES provided recommended values or lists of values to choose from based on the crop, for many of the parameters. Although no field measurements were taken, values of 35/60/5/0 (Troughton, 1957), representing a well-established turf, were used for the percent root distribution for the Turf/A/B/C layers. The root distribution is important for determining from where in the profile water is removed by the turfgrass.

(3)

(4)

(5)

where AE is the average error (or mean difference); ME is the maximum error between measured and predicted values within the study period; RMSE is the root mean square error; i is the measurement date; n is the number of sampling dates; M_i is the measured daily averages for all the lysimeters; and P_i is the predicted value. The AE indicates how strongly the model overestimates (positive sign) or underestimates (negative sign) the measured values. The ME indicates the maximum deviation between the model predictions and the measurements, and whether it is an overestimate or underestimate. We also calculated the relative error terms as AE and ME divided by the observed mean values. The RMSE quantifies the amount of scatter of the predicted and measured values about a 1:1 line. In each case, values nearer to zero reflect greater simulation accuracy. Smith et al. (1995), Jabro et al. (1995, 1997), and others have found such statistical methods useful for evaluating model performance.

	Results and discussion

TOP ABSTRACT INTRODUCTION Materials and methods Results and discussion Conclusions REFERENCES

 
Soil Hydraulic Properties
The saturated hydraulic conductivity, K_s, was much greater for turf than for the other horizons, although the particle-size distribution for the turf contained a larger percentage of fine particles (Table 2). This difference is likely due to the low bulk density of the thatch, along with the influence of macropores in the accompanying soil, created by rooting and worm burrowing action. Saturated hydraulic conductivity measurements were also more variable for the turf layer, as shown by the large standard deviation (Table 2), which may be due to the variability in thickness of the thatch layer and the random occurrence and size of macropores. This result is not surprising since the turf was sampled in the field.

Campbell's relationship (Eq. [1]) had some difficulty describing the rapid decline in water content just below saturation (Fig. 2) , especially in the layers with higher sand content. The RMSE values were 0.017 for the turf layer, 0.010 for horizon A, 0.031 for horizon B, and 0.049 for horizon C. The decline in the retention curve was very steep for the turf layer, which again suggests the presence of many large pores.

View larger version (24K): [in this window] [in a new window]   Fig. 2 Water-retention curves, derived by concurrent measurements of volumetric water content and soil matric potential and fit by Campbell's equation, for the A, B, and C soil horizons and the thatch layer

(6)

where P is precipitation, I is irrigation, E is evapotranspiration, D is drainage, R is runoff, and S is change in soil moisture storage as measured by the horizontal TDR probes. The runoff component, R, in Eq. [6] was assumed zero because the turfgrass was grown on a level surface. A comparison of measured and modeled values for the remaining components of Eq. [6] is given in Table 3 .

View larger version (33K): [in this window] [in a new window]   Fig. 3 Observed and predicted drainage for lysimeters for the 1996 field season (A) without irrigation; (B) with irrigation. Error bars indicate one standard deviation on either side of the mean

View larger version (20K): [in this window] [in a new window]   Fig. 4 Observed and predicted drainage for lysimeters for the 1997 field season. Error bars indicate one standard deviation on either side of the mean

View larger version (24K): [in this window] [in a new window]   Fig. 5 Average of observed volumetric water contents for the top of the A horizon (7 cm) and the bottom of the C horizon (85 cm), measured by TDR, for the 1997 field season

EXPRES and LEACHN Predictions
In general, the predictions of drainage and soil water contents compared favorably with the measured averages, as indicated by statistical and visual analyses, with the largest deviations associated with soil wetting in the late summer or autumn. The LEACHM version in EXPRES could not simulate the open lower-boundary condition of the lysimeters; therefore, modeling was performed with a free-drainage boundary (hydraulic potential gradient approximately equal to one) instead. This improper setting would help account for the predicted earlier start to drainage in the late summer or autumn (Fig. 3 and 4). For drainage, the ME occurred in either the spring (1997) or the autumn (1996), the times most affected by the bottom-boundary condition.

To test the effects of the lower-boundary condition on the water balance components (especially drainage), we used the stand-alone LEACHM model, Version 3 (Hutson and Wagenet, 1992), which includes the option of a lysimeter bottom-boundary condition. Under the lysimeter bottom-boundary condition, water can drain from the lysimeter only when the bottom layer is saturated and under zero pressure head or greater. As visible in Fig. 3 and 4, the model predictions of drainage using the lysimeter bottom-boundary condition were generally less than predictions using the free-drainage condition used in EXPRES.

The initial sharp increase in cumulative drainage (especially in Fig. 4) occurs because drainage water was not pumped from the lysimeters during the previous winter season. Therefore, the total drainage in May and June of 1997 of about 10 cm had accumulated in the soil profile during the entire winter season. The free-drainage bottom-boundary condition predicts this portion of the cumulative drainage curve much more accurately than the lysimeter bottom-boundary condition. The lysimeter bottom-boundary condition relies on a very accurate measurement of the saturated soil water content and uniform soil conditions at the base of the lysimeter to predict accurate drainage values.

A statistical analysis of the accuracy of EXPRES and LEACHN predictions performed for drainage is given in Table 4 . Note that the relative error terms are AE and ME divided by the observed mean drainage. The EXPRES model with a free-drainage bottom-boundary condition predicted more drainage than was observed (positive AE), with RMSE values ranging from 2 to 4.5 cm. The LEACHN model with the lysimeter bottom-boundary condition generally predicted less drainage than was observed (negative AE), with RMSE values ranging from 1.6 to 4.5 cm. Predicted drainage reacted similarly to measured drainage in terms of timing, but often differed in the amount, although predicted values fell within one standard deviation in the summer of 1997 and the autumn of 1996. Other researchers have reported successful use of LEACHM for predicting drainage from cropped soils, with AE and RMSE values in a similar range as in this study (Jemison et al., 1994; Jabro et al., 1995, 1997). Difficulties with snow accumulation and frozen soils, as well as macropore flow, were given as the prime causes for under-predictions in the winter and spring. Poor simulations of evapotranspiration and crop growth were used to explain the over-predictions in the summer for these studies. In our study, snow accumulation and evapotranspiration may be the sources of similar prediction errors.

In general, EXPRES predictions of water content, based on AE values (Tables 5 and 6), were high for the A horizon, slightly low for the B horizon, and low for the C horizon. Similar results as the A horizon observations have been previously reported (Clemente et al., 1994; Smith et al., 1995; Pearson et al., 1996).

An accurate retention curve and associated Campbell parameters are essential when using models like EXPRES since they affect, directly and through the unsaturated hydraulic conductivity, both drainage and the extent of plant evapotranspiration. In EXPRES, plant evapotranspiration is limited by the water content at the permanent wilting point, -1500 kPa, and the movement of water to the roots, which is related to the unsaturated hydraulic conductivity. The higher water contents predicted in the A horizon may indicate that the soil's ability to retain water has changed since packing occurred, with the formation of a greater number of larger pore sizes. This could be attributed to rooting or freeze–thaw action.

A visual comparison of predicted vs. measured water contents at shallow depths shows that EXPRES often predicted larger peaks in response to rain than were observed (Fig. 6) . Such large responses may indicate that the model is predicting greater drainage from the turf layer to the A horizon. Smith et al. (1995) reported that K_s values were larger from measurements performed on soil cores (5 cm) than on in situ soil columns, and attributed the difference to macropores short-circuiting flow in the smaller core samples. Therefore, the K_s value that we measured in cores for the turf layer may have been too large if continuous macropores existed throughout the entire length of the core. There were only a few instances of increases in observed water contents or drainage much sooner than predicted, which might indicate preferential flow had occurred.

View larger version (31K): [in this window] [in a new window]   Fig. 6 Observed average and predicted volumetric water contents at 7-cm depth for the 1997 field season

	Conclusions

TOP ABSTRACT INTRODUCTION Materials and methods Results and discussion Conclusions REFERENCES

 
Saturated hydraulic conductivity, measured on cores, was much greater and more variable for turf than for soil. The moisture-retention curve for turf also had a much steeper drop in water content at low applied negative head than soil. Both characteristics are likely due to the low bulk density of the thatch, along with the influence of macropores in the soil below, created by rooting and worm burrowing.

Field observations from the 2-yr lysimeter study with a sandy soil suggest that the majority of drainage below the root zone during the growing season occurs in the spring and late autumn. The impact of turfgrass on enhancing or reducing macropore flow in structured soils would be an interesting topic for further research.

Statistical analysis, using RMSE, AE, and ME, indicates that EXPRES simulated the water processes in soil below turf reasonably well, with error values for drainage and water contents similar to other studies on bare soils or crops. The lowest difference between predictions and measurements was for the B horizon, which was not surprising since it would be least affected by the bottom-boundary condition and the grass. Visual inspection of water content predictions indicate that they follow the observed fluctuations well, reacting similarly to rainfall events for wetting, but less so for drying. This suggests that EXPRES generally predicted water flow well, but had some difficulty with water redistribution during the drying periods (gravity drainage and evapotranspiration). The snowfall–snowmelt routine in EXPRES seemed to improve the model predictions of drainage in the late fall and early winter over LEACHN.

A comparison between the measured and modeled (using both free-drainage and lysimeter bottom-boundary conditions) hydrologic water balance for the turfgrass system was given. Generally, the free-drainage condition over-predicts and the lysimeter condition under-predicts the total amount of measured drainage.Klute Dirksen 1986

	ACKNOWLEDGMENTS

 
We greatly appreciate funding support from the Natural Science and Engineering Research Council of Canada, the Ontario Ministry of Agriculture, Food and Rural Affairs, Monsanto Canada Inc., and Agriculture Canada (Green Plan/Rural Conservation Clubs Program). We would also like to thank Dr. Allan Crowe, Canadian Centre for Inland Waters, for providing EXPRES, and Rick Gray for monitoring the lysimeters in the summer of 1996.

Received for publication March 3, 1999.

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