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Annual row crop production on the naturally occurring claypan soils of the eastern Great Plains may require field operations during somewhat wet conditions and this potentially results in soil compaction by the commonly-used, heavy-weight tractors and equipment. The objectives of this experiment were (i) to determine if compaction reduced yield and growth of soybean [Glycine max (L.) Merr.] and grain sorghum [Sorghum bicolor (L.) Moench] grown on a claypan soil (fine, mixed, thermic Mollic Albaqualf) and (ii) to determine the effect of wheel tracks on selected soil properties and whether chisel plow tillage could reduce wheel-track compaction. Compaction treatments were (i) ALL- all of the plot compacted, (ii) WT-wheel-track compaction, (iii) WTC-wheel-track compaction followed by a chisel tillage operation, and (iv) NO-no intentional compaction. In general, it took until the third year of annually repeated compaction in the ALL treatment to reduce crop growth and yields compared with the NO compaction treatment. Even though nearly half of the area was compacted each year in the WT treatment, few measured crop parameters decreased. In wheel tracks, soil penetrometer resistance and bulk density increased and air permeability decreased compared with out of tracks. However, chisel tillage appeared to eliminate the compaction by reducing penetration resistance and bulk density and increasing air permeability to values similar to out of tracks. Thus, compaction of claypan soils may not often be a problem for producers in this area, especially if occasional chisel tillage is included to remove possible compacted zones.

Soil water pressures, measured over space and time, are needed to predict the direction of water flow and chemical transport in the vadose zone. Advanced tensiometers (ATs), which utilize a water-filled porous cup connected directly to a pressure transducer, can be installed at almost any location and depth using standard drilling techniques such as auger drilling, but these methods can significantly disturb the site. For sites where minimal disturbance is desired, alternate approaches for tensiometer placement have been sought. To test installation techniques and performance longevity, advanced tensiometers were placed into the ground at a test site near Richland, WA using two different installation methods, auger drilling and a drive-cone push technique. The tensiometers were subsequently monitored for nearly 2 yr without refilling or recalibration. The data indicated that tensiometers placed by the auger technique took several months to equilibrate, while the cone push units came to equilibrium within 24 h following their installation. Soil water pressures always remained above -90 cm pressure head (-90 mbar) at depths >90 cm. At the greatest depth (730 cm), positive then negative pressures were observed as the water table was lowered and the soil drained. The results suggest that for our test conditions (coarse sandy soil, no vegetation), soil water pressures stay well within the tensiometer range and unit gradient conditions persist, indicating a draining profile. Advanced tensiometers, placed either by auger or cone penetrometer, provide a robust and reliable method for long-term monitoring of soil water pressure profiles.

An electronically‐controlled, portable, cone penetrometer was designed, built, and tested. The penetrometer was driven electrically through a linear actuator. Cone position was sensed by a 10‐turn potentiometer, and force was sensed with an electronic load cell. A laptop computer controlled the linear actuator and recorded signals from the sensors through a data logger equipped with a serial interface. The penetrometer was capable of driving the cone at 0.84 cms‐1 (±5%) over a load range of 0 to 180 kg. The system allowed force and position excursion limits to be set through software and provided data sets at 1‐cm increments to depths of 45 cm and forces to 2,000 N. The penetrometer demonstrated good repeatability among closely spaced probings when force per unit cone area was plotted against depth.

Tensiometers are required for measuring soil-water potential at depths greater than several meters to quantify the direction and rate of soil-water movement. This paper describes a permanently installed tensiometer (advanced tensiometer) designed to measure soil-water potentials at any depth below land surface. This advanced tensiometer was designed with a removable pressure transducer to allow for field calibration and servicing and has two parts, a permanently installed outer tensiometer assembly and a removable transducer assembly. The permanently installed portion has a porous cup, an adapter containing a reservoir of water, and an outer guide pipe that extends to the land surface. The removable electronic pressure transducer assembly has a stopper on the bottom, a connector to attach the stopper to a pressure transducer, and an inner guide tube to raise and lower the assembly. The transducer assembly is lowered into the outer tensiometer assembly until the stopper connects and seals into the permanently installed adapter. This configuration of the advanced tensiometer allows it to be installed at any depth. Advanced tensiometers were operated with no maintenance at depths of 2 to 4.8 meters for periods of more than 3 months.The nearly constant temperature condition in boreholes provided stable, long-term water potential values and reduced field maintenance.

Spatial variability of N mineralization represents a potential problem in predicting the quantity of N mineralized under field conditions. An understanding of mineralization variability is needed if prediction of potential mineralization is to be incorporated into fertilizer recommendation models. The objective of this study was to characterize spatial variability of N mineralization in a Kansas agricultural field. Intact undisturbed soil cores were collected at 108 locations within a 1.7-ha field following wheat (Triticum aestivum L.) harvest. The undisturbed cores were incubated aerobically, and NO 3 - was leached periodically as a measure of mineralization. Variability was characterized by examining the spatially distributed values of mineralization potential, N 0 , and mineralization rate constant, k, parameters of the classical first-order mineralization rate model. Values of N 0 were distributed normally with low variability (coeffident of variation [CV] = 15%) and weak autocorrelation. Values of k also followed a normal distribution with low variability (CV = 14%) but were spatially independent. Both N 0 and k determined the spatial pattern of N m , the quantity of N mineralized at a particular time. Variability in k controlled the spatial pattern of N m earlier in the incubation period, and variability in N 0 controlled the spatial pattern late in the incubation period. The incubation approach used in this study allowed characterization of the spatial patterns in N 0 , but the spatial variability of k observed in this study may not adequately represent field conditions because conditions of constant temperature and water content were used.

Quantifying the direction and rate of soil water movement beneath landfill disposal areas requires tensiometers capable of monitoring soil water potentials from one to several hundred meters below land surface. This paper describes a new way to use tensiometers to measure soil water potentials at nearly any depth. Two portable tensiometers were constructed and tested in the field. One portable tensiometer was sealed with a septum stopper, lowered to the bottom of a borehole, allowed to equilibrate, and retrieved to land surface. The soil water potentials were then determined through the septum stopper using a pressure transducer equipped with a hypodermic needle. A second portable tensiometer was constructed with an electronic pressure transducer with leads brought to land surface to allow continuous monitoring of soil water potentials without removing the tensiometer from the borehole for extended time periods. The portable tensiometers are retrieved to land surface periodically to refill with de-aired water. Both portable tensiometers were operated in the field with little maintenance for periods exceeding 2 months at depths of 4 to 6 meters. The response time of the portable tensiometers ranged from a few hours to several days and was limited by the contact between the porous cup and the soil. The slow response time was not found to be a serious problem in deep boreholes. The nearly constant temperature conditions found in deep boreholes were found to contribute to stable, long-term tension values and to reducing maintenance normally required by standard tensiometers.

Soil water characteristic curves are a prerequisite for quantifying the field soil water balance and predicting water flow in unsaturated soils. The spatial variation of water retention in the root zone influences water availability for plants, evaporation, and fluxes of water and solutes through soils. The purpose of this study was to determine the ability of a popular model for the soil water retention function to describe the spatial variability of measured retention data and to investigate the application of a water content scaling theory to reduce the apparent spatial variation of soil water retention. Using a combination of Tempe cells and 1.5-MPa pressure plate extractors, we measured soil water retention at six pressure heads. In total, 281 undisturbed soil core samples were taken from the Ap horizon (0 to 17-cm depth increments) along an 80-m transect on a bare silt loam soil at 0.30-cm intervals. Sample statistics were calculated to identify outliers and erroneous data. A four-parameter retention model (θ s , θ r , α, n) was fitted to the data, and water content scale factors were also calculated. The soil water retention model was found to be extremely flexible in fitting the measured data. The parameters in the retention model showed a structured variance with a range of influence between 12 and 30. The number of parameters needed to characterize the field variability was 912 for the retention model. Scaling theory applied to the water retention data significantly reduced the apparent spatial variability. One scale factor also showed a structured variance, indicating a spatial correlation distance of greater than 30 m. Using the Akaike information criterion, we found that scaling theory could adequately represent the spatial variation in water retention with only 460 parameters. Sampling, calibration and/or experimental errors were thought to account for more than 50% of the total variability

The majority of procedures for in situ measurement of the unsaturated hydraulic conductivity are variations of the instantaneous profile method. A vertically nonuniform soil requires the unsaturated hydraulic functions to be estimated at each horizon. Scaling systems have evolved in an attempt to reduce the number of hydraulic functions needed to characterize water flow through heterogeneous soils. In this study, we extended the concept of water content scaling to nonuniform soil profiles, tested the effectiveness of scaling for reducing apparent spatial variability, and estimated the unsaturated hydraulic functions for a naturally occurring loamy sand field site. Two instantaneous profile experiments conducted at Etiwanda, CA, provided soil water content and pressure head (h) data vs. depth (z) and time (t). Water retention, and hydraulic conductivity, functions fitted to data from the 15-cm depth at Plot 1 were arbitrarily chosen as the reference hydraulic properties to which the other depths and plots were scaled. Based on a unit-gradient analysis of the drainage data, the slope of the hydraulic conductivity function, was estimated as z/t. Scaling other depths and plots to the reference location was done using an iterative procedure that provided least-squares estimates of the two scaling parameters ( and ) and a corresponding transformed depth variable (z*). Scaled water content, , plotted vs. z*/t, using data from all depths and plots, coalesced to a single curve. Scaling successfully coalesced heterogeneous soil hydraulic properties into unique functions for both and View complete article To view this complete article, insert Disc 5 then click button8

The unsaturated hydraulic properties are important parameters in any quantitative description of water and solute transport in partially saturated soils. Currently, most in situ methods for estimating the unsaturated hydraulic conductivity (K) are based on analyses that require estimates of the soil water flux and the pressure head gradient. These analyses typically involve differencing of field-measured pressure head (h) and volumetric water content (θ) data, a process that can significantly amplify instrumental and measurement errors. More reliable methods result when differencing of field data can be avoided. One such method is based on estimates of the gravity drainage curve K'(θ) = dK/dθ which may be computed from observations of θ and/or h during the drainage phase of infiltration drainage experiments assuming unit gradient hydraulic conditions. The purpose of this study was to compare estimates of the unsaturated soil hydraulic functions on the basis of different combinations of field data θ, h, K, and K'. Five different data sets were used for the analysis: (1) θ-h, (2) K-θ, (3) K'-θ (4) K-θ-h, and (5) K'-θ-h. The analysis was applied to previously published data for the Norfolk, Troup, and Bethany soils. The K-θ-h and K'-θ-h data sets consistently produced nearly identical estimates of the hydraulic functions. The K-θ and K'-θ data also resulted in similar curves, although results in this case were less consistent than those produced by the K-θ-h and K'-θ-h data sets. We conclude from this study that differencing of field data can be avoided and hence that there is no need to calculate soil water fluxes and pressure head gradients from inherently noisy field-measured θ and h data. The gravity drainage analysis also provides results over a much broader range of hydraulic conductivity values than is possible with the more standard instantaneous profile analysis, especially when augmented with independently measured soil water retention data.

Monitoring the vadose zone below buried waste provides an early warning of contaminate Advanced Tensiometer transport toward the groundwater. To quantify the transport mechanisms, vadose zone hydraulic characteristics and the physical variables need to be obtained. We have designed and implemented a Vadose Zone Monitoring System (VZMS) to monitor or sample the 3 state variables of the vadose zone, water potential, water content and chemical concentration. The state variables are monitored using an Advanced Tensiometer (AT), a borehole water content sensor (BWCS) and a vacuum lysimeter, respectively. This system was installed at the Savannah River Site (SRS) E-Area disposal site, where low level wastes have been disposed of in shallow trenches. The system has operated for The system has operated for several months providing nearly continuous water content and water potential data. The vacuum lysimeters were activated on a quarterly schedule. Installation details and an example data set are presented to illustrate the effectiveness of the VZMS, and demonstrate the utility of the VZMS as an indicator of contaminant transport.

Fixed gradient models result when the gradient term in the soil moisture equation is assumed to vary only with depth (remains invariant in time). The fixed gradient assumption results in a first-order partial differential equation that is transformable to a mathematical form identical to that for a uniform soil. When the transformation was applied to field data, all water content data were found to plot along a single curve. Assuming a fixed gradient and an exponential form for K(Θ) resulted in a fitted curve with an r2 = 0.847 (d.f. = 405) when data from three sites and seven depths were used. Assuming a power function for K(Θ) resulted in a similar r2. Prior to applying the transform, hydraulic conductivity required 42, 42, and 63 parameters to fit data obtained at the 21 spatial points sampled, assuming a Davidson, Watson or Brooks and Corey function, respectively. With the transform 23, 23, and 24 parameters were required for the three K(Θ) functions, respectively.

Wheat is grown in many areas of the world with environmental conditions similar to those in southeastern Kansas. Rainfall averages 100 cm year −1 and the subsoil has a high clay content, which probably impedes percolation and drainage. Much of the rainfall occurs over winter when the wheat is transpiring at low rates. Thus, saturated soil-moisture conditions may develop and persist for extended periods. This study was designed as two experiments to examine the response of wheat ( Triticum aestivum L.) planted on ridges to facilitate drainage as compared with other tillage systems. In two site-years for Experiment 1, ridge:skipfurrow (wheat planted 25-cm apart, i.e., paired rows straddling small ridges that are on 76-cm centers) resulted in 15–30% higher yields than either non-ridged reduced or no-tillage systems. Intermediate yields were obtained with ridge: no-skip (one row of wheat planted in the furrows as well as two rows on each ridge). In two site-years for Experiment 2, ridge: no-skip resulted in higher yields than either reduced or conventional tillage, with intermediate yields from ridge: skip-furrow. Rainfall patterns may account for the differences in ridge system responses. Gravimetric soil moisture was lower in ridge systems than in “flat” reduced, conventional, or no-tillage systems. Yield tended to be greater with dribble than broadcast applications of urea-ammonium nitrate (UAN) solution as a spring topdress, especially for ‘Arkan’ variety wheat. Grain N content was 3–8% higher with dribble than broadcast UAN applications.

Hydraulic conductivity data are frequently summarized using mathematical functions that quantify the relationship between water content (θ) and hydraulic conductivity (K(θ)). This study was done to determine the effects of the choice of the K(θ) function and to determine if field data from layered profiles could be summarized using only one parameter per depth. Three K(θ) functions together with a matching factor were fitted to hydraulic conductivity data from a field plot. The functions were Km(θ/θm)1/β, Km[(θm−θc)/(θ−θc)]1/n,and Km exp {α(θ−θm)}, where α, β, n, Km, θc, and θm, are parameters to be estimated. For each function, two methods were considered. Method 1 fitted a different value to α, β, n, and Km for each depth while maintaining θc at a fixed value. All hydraulic conductivity functions fit data from a Muir silt loam equally well, as evidenced by the coefficient of linearity (r2) values greater than 0.72, mean square error (MSE) values less than 0.97, and coefficient of variation (CV) values less than 50%. The fitting was accomplished using ln {K} as the dependent variable. Method 2 fitted values by depth only to Km, and all other parameters were held constant. The hydraulic conductivity functions performed equally well, with r2 values greater than 0.60, MSE values less than 1.2, and CV values of 50% or less. When some loss of precision can be tolerated, the number of parameters required to summarize data from a layered soil can be reduced.

Steady-state infiltration rates were measured in a field plot with infiltrometers of 5-, 25-, and 127-cm inside diameter. Measurements were made with the three ringsizes along five parallel transects, spaced 125 cm apart. The infiltrometers were placed adjacent to each other along each transect (i.e., one hundred twenty-five 5-cm rings, twenty-five 25-cm rings, and five 127-cm rings per transect). Infiltration rates were found to be lognormally distributed for all ringsizes and autocorrelated for the 5-cm ringsize. The 5-cm data showed that a large fraction of the water infiltrated through a small fraction of the plot area. Autocorrelation functions were determined and power spectrums computed. A first-order autoregressive process was found to describe the 5-cm data, and variances of samples composited along a transect agreed with sample variances. The variances for the 25- and 127-cm infiltrometers were compared with sample variances, assuming a simple two-dimensional autocovariance function. Agreement was found for the 127-cm rings, but not for the 25-cm rings.

Analysis and data interpolation of penetration resistance ( CI ) are complicated by the effects of soil water content (θ) and bulk density ( Bd ). Analysis is also complicated by the serial correlation in error over depths, which results in standard errors for hypothesis testing which are incorrect. A method is presented that attempts to normalize the effects of water content and bulk density by using a covariate analysis to adjust the CI at each depth to a reference value of θ and Bd . This adjustment works as long as there is a relationship between CI vs. θ and Bd . A time-series analysis is used to eliminate the serial correlation of errors when separating treatments across depths. This is done by using a first- or second-order data transformation based on residuals and a general linear method of analysis, the parameter estimates obtained are unbiased and standard errors associated with these estimates are correct.

When the one-dimensional moisture flow equation is simplified by applying the unit gradient approximation, a first-order partial differential equation results. The first-order equation is hyperbolic and easily solved by the method of P. 0. Lax. Three published K(6) relationships were used to generate three analytical solutions for the drainage phase following infiltration. All three solutions produced straight lines or nearly straight lines when log of total water above a depth was plotted versus log of time. Several suggestions for obtaining the required parameters are presented and two example problems are included to demonstrate the accuracy and applicability of the method. Additional Index Words: Cauchy problem, redistribution, characteristic value problem, hydraulic conductivity, infiltration. Sisson, J. B., A. H. Ferguson, and M. Th. van Genuchten. 1980. Simple method for predicting drainage from field plots. Soil Sci. Soc. Am. J. 44:1147-1152. W DRAINING from soil profiles is an important factor in many contemporary and environmental problems. In the Northern Great Plains this water is responsible for the annual destruction of thousands of hectares of cropland by contributing to the formation and growth of saline seeps (Brown and Ferguson, 1973; Ferguson et al., 1972). In some irrigated areas, subsurface drainage water contributes to river pollution (Wierenga and Patterson, 1972). Estimation of the rate and quantity of drainage water contributing to these problems is essential to finding feasible solutions. But estimating these variables requires predicting the hydrologic behavior of large areas and frequently the characterization of many soils under field conditions. This necessitates the use of simple, yet accurate, models which contain parameters that can be obtained on site as quickly as possible. This paper considers a special class of models based on the assumption of a unit gradient of the total potential head. Several studies (cf. Black et al., 1969, and Davidson et al., 1969, among others) have shown that a unit gradient often exists during the redistribution and drainage phases when a uniform profile is draining freely in the absence of a shallow water table. Three solutions are presented, each based upon a different conductivity equation. Two example problems are further included to demonstrate the use of the present approach. THEORETICAL CONSIDERATIONS The equation for predicting the one-dimensional flow of water in porous materials is (Taylor and Ashcroft, 1972): 80 3T 9 37 [1] 9 — 0(z,t) is the volumetric moisture content, t = time, z = depth (positive downward), K = K(0) is the hydraulic conductivity, and H H(6,z) = h(6)-z; i.e., H(hydraulic head) = h (pressure head) — ^(gravitational head). When a unit gradient in the total head H is assumed, 9H/3z = -1, Eq. [1] becomes