HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (3) Citing Articles via Google Scholar Google Scholar Articles by Rachman, A. Articles by Thompson, A. L. Search for Related Content PubMed Articles by Rachman, A. Articles by Thompson, A. L. Agricola Articles by Rachman, A. Articles by Thompson, A. L. Related Collections Plant and Soil Interactions Soil Hydrology Infiltration

Division S-6—Soil & Water Management & Conservation

Influence of Stiff-Stemmed Grass Hedge Systems on Infiltration

^a Indonesia Center for Soil and Agroclimate Research and Development, Jl. Ir. H. Juanda 98 Bogor, Indonesia 16123
^b 302 Anheuser-Busch Natural Resources Building, Dep. of Soil, Environmental and Atmospheric Sciences, Univ. of Missouri, Columbia, MO 65211
^c 254 Agricultural Engineering Building, Dep. of Biological Engineering, Univ. of Missouri, Columbia, MO 65211

^* Corresponding author (AndersonS{at}missouri.edu)

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY REFERENCES

 
The ability of grass hedge systems to reduce runoff is critical to their effectiveness in controlling soil erosion. The reduction in runoff depends on the infiltration properties of soil managed with hedges. The objective of this study was to evaluate the effects of stiff-stemmed grass hedges on infiltration. The experiment was conducted on a site, which had been managed with switchgrass (Panicum virgatum L.) hedges for 10 yr at the USDA-ARS research station near Treynor, IA. The predominant soil was Monona silt loam (fine-silty, mixed, superactive, mesic Typic Hapludolls). Ponded infiltration measurements were used to determine field-saturated hydraulic conductivity (K_fs). Three positions were sampled: within grass hedges, within a deposition zone 0.5 m upslope from grass hedges, and within a row crop zone 7 m upslope from the hedges in soybean (Glycine max) production during 2001 and corn (Zea mays L.) production during 2002. A tension infiltrometer was used to measure infiltration at three selected tensions (50, 100, and 150 mm) in the grass hedge and row crop positions. The physically based Parlange, the Green and Ampt, and the empirically based Kostiakov infiltration models fit the measured data well (r² = 0.99–1.00). The K_fs within the grass hedge position was more than seven times greater than in the row crop position and 24 times greater than in the deposition position. The infiltration rate at 50- and 100-mm tension in the grass hedge position was significantly larger (P < 0.01) than in the row crop position; values at 150-mm tension were not significantly different. The K_fs was found to be similar in magnitude to laboratory measured saturated hydraulic conductivity (K_sat) treated with bentonite to eliminate by-pass flow. Grass hedges were found to enhance water infiltration compared with conventional row crop management.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY REFERENCES

 
WATER INFILTRATION into the soil determines the amount of surface runoff and subsurface recharge. Several factors influence infiltration rates including soil wetness (van Es, 1993; Azooz and Arshad, 1996), canopy cover (Pluhar et al., 1987), and pore structure and continuity (Ankeny et al., 1990; Vepraskas et al., 1991). Land use modifies many of the factors that control the infiltrability for a given soil. The direct effects of land use are related to plant canopy characteristics and the presence and activity of living and dead roots. Previous studies indicate that living roots may reduce hydraulic conductivity by compacting soil and obstructing macropores (Gish and Jury, 1981, 1983). Other studies, however, found that living roots increased soil hydraulic conductivity by indirectly increasing soil macroporosity (Warner and Young, 1991; Prieksat et al., 1994). High infiltration rates can be obtained when macropores are open to the soil surface (Beven and Germann, 1982) during ponded conditions.

Soil management has been found to have a more pronounced effect on infiltration than soil type (Sharma et al., 1980; Tricker, 1981). Tricker (1981) based his research on 3.6 km² of the Beeley Brook watershed and reported that vegetation type and land management had more predominant roles in influencing the spatial pattern of infiltration rates compared with soil variability. The study also indicated that grassland areas have significantly higher infiltration rates as compared with wooded areas. The higher infiltration rate on grassland areas was associated with the ground cover or the thickness of the litter layer. The litter layer has the ability to absorb water and slow runoff.

Grass hedge barriers are narrow, parallel strips of stiff, erect, dense grass planted close to the contour, but crossing concentrated flow areas at convenient angles for farming (Dabney et al., 1993). Grass hedges have been found to reduce runoff by 52 and 53% for soil loss under no-till conditions (Gilley et al., 2000). The lower runoff from grass hedges is probably related to the higher hydraulic conductivity in soils under the hedges as a result of the increase in macroporosity (Rachman et al., 2004). Grass hedges also facilitate sedimentation and deposition of eroded materials by reducing the carrying capacity of overland flow. Deposition of eroded materials upslope from the grass hedge due to reductions in runoff velocity and subsequent sedimentation may create a gradient in soil hydraulic properties as finer particles clog soil pores.

Few studies have been conducted to evaluate changes in infiltration under grass hedge management. Documentation of the positional infiltration pattern is essential for understanding the hydrology of the grass hedge system. The objectives of this study were to: (i) evaluate the effects of grass hedges on field-saturated hydraulic conductivity (K_fs) estimated from ponded infiltration measurements, (ii) measure the effects of stiff-stemmed grass hedges on tension infiltration, and (iii) determine the relationship between the K_fs and the laboratory measured saturated hydraulic conductivity (K_sat).

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY REFERENCES

 
Experimental Site
The study was conducted on a 6-ha watershed at the USDA-ARS National Soil Tilth Laboratory Deep Loess Research Station near Treynor, IA. The predominant soil is Monona silt loam. Surface soils are silt loam in texture (283 ± 14 g kg^–1 clay and 609 ± 14 g kg^–1 silt) and are classified as highly erodible land (HEL). The original watershed slope ranged from 2 to 4% within the ridges and valleys to 12 to 16% on side slopes. A detailed description of the watershed can be found elsewhere (Kramer et al., 1999; Kramer and Alberts, 2000). The area selected for study was on the same watershed and near the same general area as the Gilley et al. (2000) study.

Infiltration Measurements and Analysis
During the sampling for this study, the watershed was planted to soybeans in 2001 and corn in 2002. Three sampling positions within the grass hedge system were selected representing grass hedge, deposition zone, and row crop positions (Fig. 1) . The deposition zone position was 0.5 m upslope from the upper edge of the grass hedge, and the row crop position was 7 m upslope from the grass hedge. Infiltration rates were measured for the second and third hedges counted from the summit on 4 through 8 June 2001 and for the fourth and fifth hedges on 3 through 7 June 2002. Sampling positions are illustrated in Fig. 1.

View larger version (9K): [in this window] [in a new window]   Fig. 1. Schematic sketch of grass hedge system illustrating the width of hedge (W1), width of cropped area (W2), original soil slope (So), and sampling positions (grass hedge, deposition zone 0.5 m upslope of the hedge, and row crop 7 m upslope of the hedge).

Three infiltration models were used to fit infiltration data for the three positions. The models were the Green and Ampt (1911), the Parlange et al. (1982), and the Kostiakov (1932). The Parlange et al. (1982) model will be referred to as the Parlange model or equation throughout this paper. Clausnitzer et al. (1998) reported that the Green and Ampt gave the best parameter confidence interval for a two-parameter model, and that the Parlange equation fit infiltration data well for a two-parameter model. The Green and Ampt equation was modified by Philip (1957) for time (t) vs. cumulative infiltration (I), as follows:

[1]

The physically based Parlange equation for t vs. I is

[2]

The empirical Kostiakov (1932) infiltration model for infiltration rate (i) vs. t is

[3]

where t (T) is time, I (L) is the cumulative infiltration, S (L T^–0.5) is the sorptivity, K_s (L T^–1) is the saturated hydraulic conductivity, and B and m are characterizing constants. The procedure for estimating the S and K_s for the two parameter Green and Ampt and Parlange equations used the method proposed by Clothier and Scotter (2002). The B and m parameters for the empirical Kostiakov equation were estimated by fitting the cumulative infiltration version of Eq. [3] to measured I vs. t data using a nonlinear fitting procedure.

In addition, K_fs values were calculated according to Reynolds et al. (2002). Assuming one-dimensional water flow in the infiltration ring and divergent three-dimensional flow below the ring, Reynolds et al. (2002) derived the following equation:

[4]

where K_fs (L T^–1) is the field-saturated hydraulic conductivity, q_s (L T^–1) is the quasi-steady infiltration rate, a (L) is the radius of the infiltration ring, H (L) is the hydraulic head of ponded water in the ring, d (L) is the depth of ring insertion into the soil, C₁ and C₂ are dimensionless quasi-empirical constants (C₁ = 0.993 and C₂ = 0.578 for this infiltrometer), and * (L^–1) is the soil macroscopic capillary length, assumed to be equal to 0.012 mm^–1 for the row crop position, 0.004 mm^–1 for the deposition position, and 0.036 mm^–1 for the grass hedge position (Reynolds et al., 2002). The values for * were estimated using laboratory measured bulk density, water retention, and K_sat values.

When saturated infiltration rate measurements were completed, the water supply tube and the water flow control tube from the water reservoir were removed from the ring infiltrometer. Without removing the 25-cm diam. ring infiltrometer, infiltration was measured with a tension infiltrometer at 50-, 100-, and 150-mm tensions. The ring was filled with a layer of about 0.5 cm sand (between 0.25 and 0.42 mm diameter). The K_s and water entry of the silica sand were 283 m d^–1 and 22 cm, respectively (Wang et al., 1998). A water reservoir was attached to a 20-cm diam. tension infiltrometer preset at 50-mm tension then gently placed in contact with the sand. Infiltration was recorded for 20 min at 1-min intervals. After data for the 50-mm tension were recorded, the tension was increased by removing the bubbling tube from the disc and then setting the tension to 100 mm. This procedure was repeated for the 150-mm tension setting. Tension infiltration measurements were only conducted during 2002 and were not conducted on the deposition position due to low ponded infiltration readings.

The soil hydraulic conductivities for the tension infiltrometer data (K_t) were calculated based on the method proposed by Zhang (1997). The method requires measuring cumulative infiltration versus time and fitting the values with the following function:

[5]

where a (L T^–0.5) and b (L T^–1) are fitted parameters. The hydraulic conductivity of the soil is then computed from:

[6]

where A is:

[7]

[8]

where n (dimensionless) and (L^–1) are the van Genuchten parameters for the soil, r_o (L) is the disk radius of the base of the tension infiltrometer, and h_o (L) is the pressure head at the disk surface. The n and values for the silt loam soil were 1.41 and 0.002 mm^–1, respectively (Carsel and Parrish, 1988).

Intact samples were collected on 4 to 6 June 2001 using a core sampler (76 by 76 mm; Blake and Hartge, 1986). Six replicate locations per position were sampled at the 0- to 10-cm depth from undisturbed areas immediately outside of the locations where infiltration measurements were conducted. Data for K_sat (saturated hydraulic conductivity) were obtained from the Rachman et al. (2004) study. Additional K_sat measurements were made on the soil cores using bentonite–slurry to eliminate the interfacial voids from any visible macropores on the soil surface (Blanco-Canqui et al., 2002). The constant head method was used to measure saturated hydraulic conductivity (Klute and Dirksen, 1986).

The K_fs, q_s, K_s, S, and K_t values were log₁₀–transformed to normalize data before conducting statistical analyses. Coefficients of variation were calculated on transformed data. A test of homogeneity of variance (F-test between the largest and smallest position variances) among positions was conducted to determine whether further analysis of variance could be conducted due to the systematic arrangement of the positions. If there were no significant differences among position variances, an analysis of variance was done assuming a completely randomized design. The GLM procedure in the SAS program (SAS Institute, 1989) was used with significance set at P = 0.05. Significant differences between position means were assessed using the LSD (least significant difference) procedure at a 95% probability level (Duncan's LSD). Simple regression analyses were performed between K_fs and K_sat values.

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY REFERENCES

 
Ponded Infiltration Measurements
Three infiltration models fitted to measured infiltration data as a function of time for typical replicate grass hedge, row crop, and deposition positions for 2001 are shown in Fig. 2 . All models (Green and Ampt, Parlange, and Kostiakov) fit the measured infiltration data well with position average coefficients of determination (r²) near 1.0 (range from 0.99 to 1.00). The three models fit infiltration data for the three positions in both years with average slopes not significantly different from 1.0 and average intercepts not significantly different from 0.0. These data indicate that all three equations fit the data well for the three positions in both years.

View larger version (21K): [in this window] [in a new window]   Fig. 2. The models of Green and Ampt, Parlange, and Kostiakov fitted to measured ponded infiltration data for typical replicates under (A) grass hedge, (B) row crop, and (C) deposition positions; Treynor, IA in 2001.

The mean K_fs (average for both years) in the grass hedge position (130 mm h^–1) was seven times higher than in the row crop position (18 mm h^–1) and 24 times higher than in the deposition position (5.4 mm h^–1; Table 2). Excavation of soil beneath the grass hedge to a depth of 120 cm showed a large concentration of grass roots were found down to the 20-cm depth, with a lower concentration from the 20- to 40-cm depth, and only two or three old root channels within the 0.84 m² sampled area extended to the 120-cm soil depth. These channels provided numerous pathways for rapid infiltration of water (Vepraskas et al., 1991). Chan and Mead (1989) reported that permanent pasture had nearly four times the volume of macropores than tilled soil; therefore, we attribute the higher ponded infiltration rates in the grass hedge position to greater macroporosity and pore continuity. Since the grass hedges will be kept intact during succeeding years, this practice will likely maintain the continuity of pores for water movement.

In contrast, tilled soil decreased the macropore continuity (Chan and Mead, 1989; van Es, 1993). The crop management in the study site was changed from conventional tillage continuous corn to no-till soybean in 1997, 4 yr before the study was conducted. This period of time is probably insufficient to allow macropore continuity to increase to the level within the grass hedge system. The 4-yr period suggested by Voorhees and Lindstrom (1984) to produce a higher porosity under conservation tillage still does not reach the level under the grass hedge system. The low K_fs found in the deposition position probably was due in part to sedimentation of silt-sized materials and the detachment by rain splash of surface soil that destroyed macropores (Beven and Germann, 1982).

Tension Infiltration Measurements
Measured infiltration rates at 50-, 100-, and 150-mm tensions for the grass hedge and row crop positions are shown in Fig. 3 (data at 0 tension were from ponded infiltration). Infiltration rates were significantly higher (P < 0.01) in the grass hedge than in the row crop position at the 50- and 100-mm tensions but not at the 150-mm tension (Table 3). Infiltration rate decreased as the applied tension increased with the largest decrease occurring between the 0- to the 50-mm tension. The decrease in slope for infiltration with increasing tension was greater in the grass hedge position (0.034) than in the row crop position (0.029) indicating that larger pores (i.e., those that drain at lower tensions) were more responsible for conducting water in the grass hedge than in the row crop position (Ankeny et al., 1990). Rachman et al. (2004) reported that soil in the grass hedge position had two times greater macroporosity than in the row crop position. Therefore, the grass hedge position increased the formation of macropores, while the no-till management in the row crop position has probably not had sufficient time to increase macroporosity.

View larger version (17K): [in this window] [in a new window]   Fig. 3. Plot of quasi-steady state infiltration rate means (n = 6) vs. tension for the grass hedge and row crop positions at Treynor, IA in 2002. Bars represent the standard error of the means of six observations.

Correlation Between K_fs and K_sat
The laboratory data for saturated hydraulic conductivity (K_sat) measured with bentonite for the 0- to 10-cm depth are presented in Table 4. Statistical analyses for K_sat with bentonite were performed on log-transformed values since data for this parameter were not normally distributed. The transformation normalized the data. Significant differences were found among the three positions (P < 0.05) for K_sat with bentonite. The grass hedge position had significantly (P < 0.05) higher K_sat with bentonite followed by the row crop and the deposition positions (Table 4). The higher K_sat in the grass hedge position can be attributed to the abundance of macropores as indicated by the relatively higher macroporosity than for the other two positions.

Figure 4 shows the simple regression between K_fs and K_sat with bentonite (Fig. 4A) and K_sat without bentonite (Fig. 4B). The coefficients of determination (r²) were 0.79 between K_fs and K_sat with bentonite and 0.91 for between K_fs and K_sat without bentonite. If there were perfect agreement between the field and laboratory measurements of conductivity, the slope of the regression line would be 1.0 and the intercept would be 0. The slope of the regression was small (0.18) between K_fs and K_sat without bentonite, but closer to 1.0 (0.67) for the regression between K_fs and K_sat with bentonite. These results indicate that the K_sat without bentonite values were 5.5 times larger than the K_fs, while the K_sat with bentonite values were only 1.5 times larger than the K_fs. The largest differences (7.2 times larger) between K_fs and K_sat without bentonite were found in the deposition position and the smallest differences (1.9 times larger) were found in the row crop position. The differences found between K_fs and K_sat without bentonite in the row crop position were similar to those of Bouwer (1986). Bouwer (1986) proposed that K_fs could be estimated as 0.5 x K_sat, which in this study the coefficient was equal to 0.65 x K_sat (with intercept set to 0.0; r² = 0.79). Blanco-Canqui et al. (2002), who used the same method to plug the visible macropores on the soil surface, reported that K_sat values in the soil cores without bentonite were four times greater than in the cores with bentonite.

View larger version (19K): [in this window] [in a new window]   Fig. 4. Field saturated hydraulic conductivity (Kfs, 2001 data) vs. laboratory saturated hydraulic conductivity (Ksat) (A) with bentonite and (B) without bentonite (n = 18).

	SUMMARY

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY REFERENCES

 
Ponded infiltration measurements were taken to evaluate the effects of three positions (grass hedge, deposition, and row crop) on infiltration within a grass hedge system that had been in place since 1991. A tension infiltrometer was also used to measure infiltration rates at three tensions (50, 100, and 150 mm) for the grass hedge and row crop positions. Quasi-steady state infiltration rate data were used to estimate field-saturated hydraulic conductivity (K_fs). The grass hedge position had the greatest K_fs (130 mm h^–1) followed by the row crop position (18 mm h^–1) and the deposition position (5.4 mm h^–1). The grass hedge position had significantly higher (P < 0.01) infiltration rates at 50- and 100-mm tensions than in the row crop position; no significant differences in infiltration rates were found between the two positions at the 150-mm tension. K_fs values correlated well with K_sat with a coefficient of determination (r²) of 0.79 for K_sat with bentonite and 0.91 for K_sat without bentonite. However, the K_sat without bentonite overestimated the K_fs by 5.5 times, while the K_sat with bentonite overestimated the K_fs by a factor of 1.5.

Received for publication February 13, 2004.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY REFERENCES

 

• Ankeny, M.D., T.C. Kaspar, and R. Horton. 1990. Characterization of tillage and traffic effects on unconfined infiltration measurements. Soil Sci. Soc. Am. J. 54:837–840.[Abstract/Free Full Text]
• Azooz, R.H., and M.A. Arshad. 1996. Soil infiltration and hydraulic conductivity under long-term no-tillage and conventional tillage systems. Can. J. Soil Sci. 76:143–152.
• Bagarello, V., and G. Provenzano. 1996. Factors affecting field and laboratory measurement of saturated hydraulic conductivity. Trans. ASAE 39:153–159.
• Beven, K., and P. Germann. 1982. Macropores and water flow in soils. Water Resour. Res. 18:1311–1325.
• Blake, G.R., and K.H. Hartge. 1986. Bulk density. p. 363–375. In A. Klute (ed.) Methods of Soil Analysis. Part 1. 2nd ed. Agron. Monogr. No. 9. ASA and SSSA, Madison, WI.
• Blanco-Canqui, H., C.J. Gantzer, S.H. Anderson, E.E. Alberts, and F. Ghidey. 2002. Saturated hydraulic conductivity and its impact on simulated runoff for claypan soils. Soil Sci. Soc. Am. J. 66:1596–1602.[Abstract/Free Full Text]
• Bouma, J. 1982. Measuring the hydraulic conductivity of soil horizons with continuous macropores. Soil Sci. Soc. Am. J. 46:438–441.[Abstract/Free Full Text]
• Bouwer, M. 1986. Intake rate: Cylinder infiltrometer. p. 825–844. In A. Klute (ed.) Methods of soil analysis. Part 1. 2nd ed. Agron. Monogr. No. 9. ASA and SSSA, Madison, WI.
• Carsel, R.F., and R.S. Parrish. 1988. Developing joint probability distributions of soil water retention characteristics. Water Resour. Res. 24:755–769.
• Chan, K.Y., and J.A. Mead. 1989. Water movement and macroporosity of an Australian Alfisol under different tillage and pasture conditions. Soil Tillage Res. 14:301–310.
• Clausnitzer, V., J.W. Hopmans, and J.L. Starr. 1998. Parameter uncertainty analysis of common infiltration models. Soil Sci. Soc. Am. J. 62:1477–1487.[Abstract/Free Full Text]
• Clothier, B., D. Scotter, and J.-P. Vandervaere. 2002. Unsaturated water transmission parameters obtained from infiltration. p. 879–898. In J.H. Dane and G.C. Topp (ed.). Methods of soil analysis. Part 4. SSSA, Madison, WI.
• Clothier, B.E., and K.R.J. Smettem. 1990. Combining laboratory and field measurements to define the hydraulic properties of soil. Soil Sci. Soc. Am. J. 54:299–304.[Abstract/Free Full Text]
• Dabney, S.M., K.C. McGregor, L.D. Meyer, E.H. Grissinger, and G.R. Foster. 1993. Vegetative barriers for runoff and sediment control. p. 60–70. In K. Mitchell (ed.) Integrated resource management and landscape modification for environmental protection. ASAE, St. Joseph, MI.
• Everts, C.J., and R.S. Kanwar. 1992. Interpreting tension infiltrometer data for quantifying soil macropores: Some practical consideration. Trans. ASAE 36:423–428.
• Evett, S.R., F.H. Peters, O.R. Jones, and P.W. Unger. 1999. Soil hydraulic conductivity and retention curves from tension infiltrometer and laboratory data. p. 541–551. In M. Th. van Genuchten et al. (ed.) Characterization and measurements of the hydraulic properties of unsaturated porous media. Part I. U.S. Salinity Laboratory, USDA-ARS, University of California, Riverside.
• Gilley, J.E., B. Eghball, L.A. Kramer, and T.B. Moorman. 2000. Narrow grass hedge effects on runoff and soil loss. J. Soil Water Conserv. 55:190–196.
• Gish, T.J., and W.A. Jury. 1981. Estimating solute travel times through a crop root zone. Soil Sci. 133:124–130.
• Gish, T.J., and W.A. Jury. 1983. Effect of plant roots and root channels on solute transport. Trans. ASAE 26:440–444.
• Green, W.H., and G.A. Ampt. 1911. Studies on soil physics:1. Flow of air and water through soils. J. Agric. Sci. 4:1–24.
• Klute, A., and C. Dirksen. 1986. Hydraulic conductivity and diffusivity: Laboratory methods. p. 687–734. In A. Klute (ed.) Methods of soil analysis. Part 1. 2nd ed. Agron. Monogr. No. 9. ASA and SSSA, Madison, WI.
• Kostiakov, A.N. 1932. On the dynamics of the coefficient of water percolating in soils and the necessity of studying it from a dynamic view for the purpose of amelioration. Trans. 6th Congr. Int. Soc. Soil Sci. Russian part A:17–21.
• Kramer, L.A., M.R. Burkart, D.W. Meek, R.J. Jaquis, and D.E. James. 1999. Field-scale watershed evaluations on deep-loss soils: II. Hydrologic responses to different agricultural land management systems. J. Soil Water Conserv. 54:705–710.
• Kramer, L.A., and E.E. Alberts. 2000. Grass hedges for erosion control on a small HEL watershed. ASAE Paper No. 00–2082. ASAE, St. Joseph, MI.
• Paige, G.B., and D. Hillel. 1993. Comparisons of three methods for assessing soil hydraulic properties. Soil Sci. 155:175–189.
• Parlange, J.Y., I. Lisle, R.D. Braddock, and R.E. Smith. 1982. The three-parameter infiltration equation. Soil Sci. 133:337–341.
• Philip, J.R. 1957. The theory of infiltration: 4. Sorptivity and algebraic infiltration equation. Soil Sci. 84:257–264.
• Pluhar, J.J., R.W. Knight, and R.K. Heitschmidt. 1987. Infiltration rates and sediment production as influenced by grazing systems in the Texas rolling plains. J. Range Manage. 40:240–243.
• Prieksat, M.A., T.C. Kaspar, and M.D. Ankeny. 1994. Positional and temporal changes in ponded infiltration in a corn field. Soil Sci. Soc. Am. J. 58:181–184.[Abstract/Free Full Text]
• Rachman, A., S.H. Anderson, C.J. Gantzer, and E.E. Alberts. 2004. Soil hydraulic properties influenced by stiff-stemmed grass hedge systems. Soil Sci. Soc. Am. J. 68:1386–1393.[Abstract/Free Full Text]
• Reynolds, W.D., B.T. Bowman, R.R. Brunke, C.F. Drury, and C.S. Tan. 2000. Comparison of tension infiltrometer, pressure infiltrometer, and soil core estimates of saturated hydraulic conductivity. Soil Sci. Soc. Am. J. 64:478–484.[Abstract/Free Full Text]
• Reynolds, W.D., D.E. Elrick, E.G. Youngs, and A. Amoozegar. 2002. Field methods (vadose and saturated zone techniques). p. 817–826. In J.H. Dane and G.C. Topp (ed.). Methods of soil analysis. Part 4. SSSA Book Series No. 5. SSSA, Madison, WI.
• SAS Institute. 1989. SAS/STAT user's guide. Ver. 6. 4th ed. SAS Institute, Cary, NC.
• Sharma, M.L., G.A. Gander, and C.G. Hunt. 1980. Spatial variability of infiltration in a watershed. J. Hydrol. (Amsterdam) 45:101–122.
• Tricker, A.S. 1981. Spatial and temporal patterns of infiltrations. J. Hydrol. (Amsterdam) 49:261–277.
• van Es, H.M. 1993. Evaluation of temporal, spatial, and tillage induced variability for parameterization of soil infiltration. Geoderma 60:187–199.
• Vepraskas, M.J., A.G. Jongmans, M.T. Hoover, and J. Bouma. 1991. Hydraulic conductivity of saprolite as determined by channels and porous groundmass. Soil Sci. Soc. Am. J. 55:932–938.[Abstract/Free Full Text]
• Voorhees, W.B., and M.J. Lindstrom. 1984. Long-term effects of tillage method on soil tilth independent of wheel traffic compaction. Soil Sci. Soc. Am. J. 48:152–156.[Abstract/Free Full Text]
• Wang, D., S.R. Yates, and F.F. Ernst. 1998. Determining soil hydraulic properties using tension infiltrometers, time domain reflectometry, and tensiometers. Soil Sci. Soc. Am. J. 62:318–325.[Abstract/Free Full Text]
• Warner, G.S., and R.A. Young. 1991. Measurements of preferential flow beneath mature corn. p. 150–159. In T.J. Gish and A Shirmohammadi (ed.) Proc. of symposium on preferential flow, Chicago, IL, 16–17 Dec. 1991. ASAE, St. Joseph, MI.
• Zhang, R. 1997. Determination of soil sorptivity and hydraulic conductivity from the disk infiltrometer. Soil Sci. Soc. Am. J. 61:1024–1030.[Abstract/Free Full Text]

This article has been cited by other articles:

				H. Blanco-Canqui, C. J. Gantzer, and S. H. Anderson Performance of Grass Barriers and Filter Strips under Interrill and Concentrated Flow J. Environ. Qual., October 27, 2006; 35(6): 1969 - 1974. [Abstract] [Full Text] [PDF]

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (3) Citing Articles via Google Scholar Google Scholar Articles by Rachman, A. Articles by Thompson, A. L. Search for Related Content PubMed Articles by Rachman, A. Articles by Thompson, A. L. Agricola Articles by Rachman, A. Articles by Thompson, A. L. Related Collections Plant and Soil Interactions Soil Hydrology Infiltration