Distributed irrigation control (DIC) for site-specific management and/or operation of fixed irrigation systems is easier to install and maintain as compared to centralized irrigation control (CIC), but requires multiple controllers in the field. The advantages of DIC over CIC systems include: (1) reduced wiring and piping requirements, (2) a lower risk of complete system failure due to mechanical damage or lightening strikes, and (3) more flexibility when modifying or extending the system. In this study, a low cost solar-powered feedback controller for DIC of fixed irrigation systems was developed and tested. The specific tasks included the controller design (hardware and software), performance evaluation, and power optimization. The controller uses soil water potential (SWP) measurements to control the amount of water applied to each specific management area of a field, and measured system hydraulic pressure to communicate with other controllers. Each controller is autonomously powered by a solar panel and battery, eliminating hard-wire connections among control units. The results indicate that the controller was effective in maintaining the SWP in the root zone close to a predetermined management allowed deficit (MAD). The power supply was optimized using simulated and measured solar radiation data from two locations.

The effects of some common vapor pressure deficit (VPD) and net irradiance (R-n) calculation methods on the accuracy of ETo values estimated by using the standardized ASCE Penman-Monteith (ASCE-PM) equation for short grass were examined by comparing the estimated ETo values with measured ETo values in a humid climate. Sensitivity analysis showed 17% and 84% change in the estimated daily ET, values per unit change in the calculated VPD and R-n values, respectively. A total of 12 VPD and 27 R-n calculation methods were examined. Analyses of variance indicated lack of equality in the means of estimated ET, values obtained by different VPD and R-n methods. The percent mean error in the estimated ETo values ranged from -0.9 to -8.4% for VPD methods and from -0.3 to -19.7% for R-n methods. On the basis of the coefficient of determination (r(2)) and the standard error of the estimated (S-y/x) values, the VPD calculated from saturation vapor pressure (e(s)), estimated by averaging the e(s) at the maximum and minimum daily air temperatures, and actual vapor pressure (e(a)), estimated by using either the average of minimum and maximum relative humidity or the dew-point temperature, gave more accurate results. Net irradiance (R-n) estimated by using a regression of relative short-wave solar irradiance, as well as a linear regression on the square root of e(a), resulted in relatively more accurate estimates of ETo than that obtained by methods based on e(a) or clear-sky data alone. These results indicate that in a humid climate, some of the VPD and R-n methods have a significant effect on the accuracy of the ETo estimated by using the standardized ASCE-PM equation.

Errors associated with visual inspection and interpretations of radargrams often inhibit the intensive surveyingof widespread areas using ground-penetrating radar (GPR). To automate the interpretive process, this article presents anapplication of a fuzzy-neural network (F-NN) classifier for unsupervised clustering and classification of soil profiles usingGPR imagery. The classifier clusters and classifies soil profile strips along a traverse based on common pattern similaritiesthat can relate to physical features of the soil (e.g., number of horizons; depth, texture, and structure of the horizons; andrelative arrangement of the horizons, etc.). This article illustrates this classification procedure by its application on GPR data,both simulated and actual. Results show that the procedure is able to classify the profile into zones that corresponded withthe classifications obtained by visual inspection and interpretation of radar grams. Application of F-NN to a study site insouthwest Tennessee gave soil groupings that are in close correspondence with the groupings obtained in a previous study,which used the traditional methods of complete soil morphological, chemical, and physical characterization. At a crossovervalue of 3.0, the F-NN soil grouping boundary locations fall within a range of .2.7 m from the soil groupings determinedby the traditional methods. These results indicate that F-NN can supply accurate real-time soil profile clustering andclassification during field surveys.

A comprehensive instrumentation system was installed at four sites across the state of Tennessee to monitor seasonal variations in the environmental factors affecting flexible pavement response. This paper presents some selected findings obtained from over five years of continuous data collection. The data included temperature and water content of the various pavement layers, and weather information. Falling weight deflectometer (FWD) tests were used to observe the pavement response during different seasons. The measured seasonal variations in subgrade and base water content were observed to be small. Consistent with these observations, the seasonal variations in FWD back calculated subgrade modulus were small, suggesting that these effects may not be important in the design of pavements in moderate climates. Since the pavement systems were anew construction, little pavement distress was observed over the study period. However, as the pavements age, water infiltration may increase leading to greater water content changes in the unbound materials.

A non-intrusive survey method was developed that examined the relationships among spatial and temporal variations of soil water content, soil texture, and bulk electrical conductivity (ECa) in a 7.5 ha research watershed in southwestern Tennessee. Our goal was to identify areas that may exhibit rapid movement of subsurface moisture, as this is a precursor of offsite agrochemical migration. The survey protocol identified similar and dissimilar temporal variations in ECa patterns. Repeated spatial measurements of ECa, starting at near field capacity and then progressing through the draining and drying process, supplied visually shifting ECa patterns that correspond to dynamic soil moisture variations and subsurface morphology transitions. We noted that spatial ECa patterns for a field remained somewhat analogous across data gathering events, shifting in relative amplitude along with seasonal moisture levels. For this study, we considered soil morphology constant over the short data acquisition interval, with short-term subsurface moisture variations as the parameter primarily influencing ECa changes. We inferred soil morphology as the major factor for ECa pattern similarity across time. Follow-up soil coring analysis along two separate low-to-high ECa transects supported this assumption for this site.

Within a 10-ha field site, annual surface applications of atrazine were made to a 0.37-ha bermed plot from 1999 to 2001, and a potassium-bromide tracer was applied in 1993 and 2000. The field site includes an intensive network of 40 shallow monitoring wells, 12 deep monitoring wells, a precipitation gauge, and a H-flume with an automated sampler to quantify and sample runoff. In the spring of 2003, twenty-one continuous soil cores were collected to a depth of approximately 3.4 m and analyzed for atrazine, bromide, and water content. Using a mass balance approach, the relative amounts of water transported from the site as runoff, subsurface plug-flow, and subsurface preferential flow were calculated.When detected, atrazine concentrations were typically just above the analytical detection limit of 7.5 mug per liter of sod pore water. Although atrazine appeared relatively persistent within the soil profile, a quantitative analysis of its transport proved difficult due to the low concentrations. The bromide distributions demonstrated apparent classic plug flow with the exception that up to 82% (mean of 58%) of the applied bromide was absent from the soil profiles. The missing bromide was attributed to subsurface preferential flow, which is supported by the detection of atrazine and bromide in the shallow monitoring wells 150 m from the application area soon after application. One-dimensional plug-flow modeling of the bromide transport adequately predicted the measured bromide profiles when the applied bromide mass was left as an unknown variable. Results of the modeling suggest that without prior knowledge of the mass of a released solute, quantifying the true mass of solute released from sod core analysis alone may be difficult if preferential flow is occurring.

Multisegment time domain reflectometry (TDR) probes are an attractive alternative to single-segment probes when used for the in situ measurement of water content changes in pavement systems. Because several independent measurements are made along the length of the multisegment probe, these instruments offer several advantages over the more traditional TDR probes. These include the ability to obtain measurements over a greater volume of soil, the ability to install the probe into relatively undisturbed soils, and the redundancy provided by multiple measurements from the same instrument. However, because of the difference in signal strength along the probe, all segments do not provide the same level of accuracy. Several factors that must be considered when using these probes are discussed, including the sources of measurement error and the temperature dependence of the measurements in some segments. A method is described by which the results from lower accuracy segments can be used when higher accuracy segments fail during service, taking advantage of the redundancy provided by multisegment probes. The method is demonstrated on data from a site from which over 4 years of continuous water content measurements have been obtained.

Conducting precise soil investigations rapidly and nonintrusively is of great interest to soil scientists and engineers. As such, comparisons of ground‐penetrating radar (GPR), electromagnetic induction (EMI), and traditional soil survey techniques were made on loessial soils in southwest Tennessee. The objectives of this study were to: (i) conduct a complete soil morphological, chemical, and physical characterization by methods; (ii) conduct a nonintrusive soil investigation by GPR and EMI; and (iii) compare the results from a traditional investigation with the nonintrusive investigation. The soils were located on an upland position. Parent material was loess–alluvium–Tertiary sand. Measured loess thickness ranged from 90 to 144 cm and measured alluvium thickness ranged from 82 to 151 cm. Soil morphological and physical properties in the upper 130 cm of nine pedons were analyzed statistically and grouped by pedon sample site. For an unbiased assessment, all GPR and EMI data were analyzed independently by pedon sample site, and data were grouped on the basis of similarities. Groupings of sites were compared by Kappa statistics. At the subgroup level, all sites were classified as Ultic Hapludalfs. Groupings of sites based on soil morphology and physical data had strong agreement with groupings of sites based upon GPR data, which were first targeted by a precursory EMI survey.

Ground-penetrating radar (GPR) technology has supplied invaluable assistance in numerous criminal investigations. However, field personnel desire further development such that the technology is rapidly deployable, and it provides both a simple user interface and sophisticated target identification. To assist in the development of target identification algorithms, our efforts involve gathering background GPR data for the various site conditions and circumstances that often typify clandestine burials.For this study, forensic anthropologists established burial plots at The University of Tennessee Anthropological Research Facility (ARF). These plots contain donated human cadavers lying in various configurations and depths. Each plot includes a fleshed cadaver with varying combinations of human skeletal remains, construction material, and backfill.We scanned the plots using two GPR systems. The first system is a multi-frequency synthetic-aperture unit (GPR-X) developed by the Department of Energy's Special Technologies Laboratory (STL), Bechtel Nevada (Koppenjan et al., 2000). The impulse radar system is a newly released commercial unit (SIR-20) manufactured by Geophysical Survey Systems, Inc. (GSSI). This paper provides example scans from each system, and a discussion of the survey protocol and general performance.

Established and emerging geophysical technologies offer many promising applications for precise near-surface surveying. Scientists are investigating these non-invasive surveying techniques to enhance soil mapping and research. A non-invasive soil surveying system was developed to rapidly map soil characteristics. This system employs an all-terrain utility vehicle towing a nonmetallic carriage that cradles a commercially available ground conductivity meter Autonomous data streams of time-stamped soil conductivity data and global positioning system (GPS) data are immediately downloaded to a computer after a survey. Both data sets are automatically merged using the time stamp data as an index. Using geographical information software (GIS), conductivity maps of increased data density are produced on-site. The mobile surveying system increased total conductivity sampling rate by a factor of >100, and increased data density by a factor of >10 over a conventional manual survey method when operating over a 1-ha open test site. For open fields that can be easily traversed with a utility vehicle, the mobile surveying system was found to greatly enhance data quality by increasing data density, and to dramatically increase both data acquisition efficiency and data post-processing speeds.

Precision agriculture, environmental mapping, and rural construction benefit from subsurface imaging by revealing the spatial variability of underground features. Features surveyed of agricultural interest are bedrock depth, soil horizon thicknesses, and buried-object features such as drainage tile. For these applications, ground-penetrating radar (GPR) is an effective near-surface imaging technology. GPR technologies are used to survey large, open land tracts, whereby subsurface features are ultimately geo-referenced using a geographic information system (GIS) database. This article describes the concept of employing a differentially corrected global position system (DGPS) to provide real-time position location. The system automatically embeds distance referencing markers within the GPR image file, essentially acting as a virtual survey wheel. Markers containing geo-referenced position information are generated "on-the-go" at predefined travel increments. This GPR surveying system supplies high automation and has increased our overall survey and image post-processing efficiency.

Ground-penetrating radar (GPR) data were collected over a 10-year period on sites composed of loess over alluvium over Tertiary sands. During wet periods, radargrams exhibited ephemeral columnar patterns occurring in and around the alluvium/Tertiary, sand interface. Following prolonged dry periods, radargrams did not exhibit the columnar patterns. Extracted soil cores contained vertical preferential flow paths and vertical macro pores. A trench excavation revealed increased preferential flow paths in those areas that exhibited columnar patterns. Conductivity shifts and sharper dielectric contrasts of localized moisture ponded or drained at this interface may cause reverberation patterns beneath.

In a previous study, we demonstrated that fuzzy evapotranspiration (ET) models can achieve accurate estimationof daily ET comparable to the FAO PenmanMonteith equation, and showed the advantages of the fuzzy approach over othermethods. The estimation accuracy of the fuzzy models, however, depended on the shape of the membership functions and thecontrol rules built by trialanderror methods. This paper shows how the trial and error drawback is eliminated with theapplication of a fuzzyneural system, which combines the advantages of fuzzy logic (FL) and artificial neural networks (ANN).The strategy consisted of fusing the FL and ANN on a conceptual and structural basis. The neural component providedsupervised learning capabilities for optimizing the membership functions and extracting fuzzy rules from a set of inputoutputexamples selected to cover the data hyperspace of the sites evaluated. The model input parameters were solar irradiance,relative humidity, wind speed, and air temperature difference. The optimized model was applied to estimate reference ET usingindependent climatic data from the sites, and the estimates were compared with direct ET measurements from grasscoveredlysimeters and estimations with the FAO PenmanMonteith equation. The modelestimated ET vs. lysimetermeasured ETgave a coefficient of determination (r 2 ) value of 0.88 and a standard error of the estimate (Syx) of 0.48 mm d 1 . For the sameset of independent data, the FAO PenmanMonteithestimated ET vs. lysimetermeasured ET gave an r 2 value of 0.85 andan Syx value of 0.56 mm d 1 . These results show that the optimized fuzzyneuralmodel is reasonably accurate, and iscomparable to the FAO PenmanMonteith equation. This approach can provide an easy and efficient means of tuning fuzzyET models.

In a two-stage study, the possibility of using high-rate anaerobic digesters to enhance the performance of dairy lagoons was explored. Four anaerobic sequencing batch reactors (ASBR) and four downflow anaerobic filters (DFAF) were tested, with two of each type operated at 25 degreesC, and the other two at 35 degreesC. The first stage of the experiment explored using the high-rate digesters on liquid effluent from a screw-press treating dairy manure slurry. The first-stage experiment demonstrated that settling processes, rather than biodegradation, accounted for most of the organic matter reduction in both reactor types, when operated at a 0.5-d hydraulic retention time. Specifically, settling accounted for an average-of 100% of the chemical oxygen demand (COD) removal in the ASBR reactors, and for an average of 72% of the COD removal in the DFAF reactors. These results prompted the second stage of the experiment, which explored the possibility of using the reactors to remove volatile fatty acids (VFAs) from dairy lagoon supernatant. Diluted manure slurry was spiked with acetic acid (HAc) to simulate the supernatant of an overloaded lagoon. At VFA loading rates of 1.0 and 3.0 kg HAc m(-3) d(-1), both reactor types achieved moderate VFA removal. However, at a loading rate of 6.0 kg HAc m-3 d-1, the ASBR reactors were ineffective, whereas the DFAF reactors, at both 25degreesC and 35degreesC, removed more than 80% of the influent HAc. At a loading rate of 12 kg HAc m(-3) d(-1), the DFAFs achieved removal rates of 75%; removal rates dropped to 50% at the maximum loading tested, 24 kg HAc m(-3) d(-1). Based on these experiments, it appears that the DFAF reactors are suited to the task of rapidly removing accumulated VFA from lagoon supernatant.

Free-drainage lysimeters, commonly used in agriculture to monitor evapotranspiration and solute transport, were installed at three highway test sites in Tennessee. The lysimeters were installed below flexible pavement systems just beneath the coarse-graded asphalt stabilized base. The lysimeters collect water infiltrating the unbound aggregate (stone base) and monitor the quantity of infiltration by diverting the flow into tipping bucket rain gauges. One test site indicated infiltration beneath the longitudinal joint in the first several months of monitoring. A second test site, where the dense surface layer was not in place, indicated infiltration correlating with rainfall. Data from this site were used to develop a model to predict the measured infiltration based on the recorded rainfall. The monitoring method and modeling approach may be applicable in the investigation of pavement permeability, drainage system efficiency, and the role of infiltration in the seasonal variation of water content of unbound pavement layers.

Offsite movement of waterborne agrochemicals is increasingly targeted as a nonpoint source of water quality degradation. Our research has indicated that subsurface water movement is variable and site-specific, and that a small soil volume frequently conducts a large volume of flow. This concentrated flow is usually caused by soil morphology, and it often results in water moving rapidly offsite from certain areas of fields; little or no lateral subsurface flow may occur in other areas. Identifying these subsurface regions is difficult using conventional soil survey and vadose zone sampling techniques In this study, traditional surveying is combined with electromagnetic induction (EMI) and ground penetrating radar (GPR) mapping to identify areas with high potential for subsurface offsite movement of agrochemicals, optimizing these identification techniques, and expanding the mapping procedures to make them useful at the field-scale for agricultural production practices. Conclusions from this research are: 1) EMI mapping provides rapid identification of areas of soil with a high potential for offsite movement of subsurface water, 2) GPR mapping of areas identified by EMI mapping provides a means to identify features that are known to conduct concentrated lateral flow of water, and 3) combining the capabilities of EMI and GPR instrumentation make possible the surveys of large areas that would otherwise be impossible or unfeasible to characterize.

Time domain reflectometry (TDR) systems are being used widely for in situ measurement of soil water content. Water content is calculated based on the measured dielectric properties of the soil system. TDR systems for water content measurement were originally developed for use in soils with low bulk densities similar to those found in agriculture. Four highway test sites in Tennessee were instrumented with five-segment TDR probes in the soil subgrade and in the unbound aggregate sub-base (Rainwater et al. 1999). These materials are more dense than agricultural soils. After several months of data collection and field verification, the TDR predicted water contents and gravimetric water contents did not coincide. For this reason, a study was per-formed with the TDR equipment using each of the four test site subgrade soils and an unbound aggregate sub-base sample. Ten previously published TDR water content relationships were evaluated to determine which relationship most accurately predicted water content for the subgrade soils and for the unbound aggregate sub-base using the five-segment probe. During the course of the study it was necessary to evaluate the manufacturer's relationship between the measured propagation time and the corrected propagation time, which accounts for the epoxy fill between the probe waveguides. The relationship was revised to reduce significant variation in corrected propagation times between segments.The relationship between inverse signal velocity and soil water content proposed by Herkelrath et al. (1991) most accurately predicted water content for all subgrade soils; however, this relationship required the derivation of a soil-specific slope and intercept. The equation proposed by Baran (1994) most accurately predicted water contents for the unbound aggregate sub-base. Both of these expressions appear to provide a better prediction than the widely used Topp's relationship.

Development of a rapid and nonintrusive method for obtaining accurate soil morphological information is critical for pinpointing areas that are prone to leaching. The purpose of this, study was to evaluate the suitability of using ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques in combination to gather soil morphological information on loessial soils. A survey of apparent electrical conductivity (ECa) was conducted in southwestern Tennessee at 10-m increments throughout a 1-ha field. Based on variation in the EMI data, a 36-m transect was selected for further investigation by GPR using a 200-Nmz antenna. A hydraulic excavator was used to trench the site to a depth of 3 m, and a complete soil morphological investigation was performed along the trench face at 6-m increments. Readings from the EMI showed a moderate correlation with percent fragic properties (r = 0.40). Average depth to the loess/alluvium. interface interpreted from the GPR was 1.20 m, and to the alluvium/Tertiary sand interface, 1.88 m. The loess/alluvium and alluvium/Tertiary sand interfaces interpreted from the GPR data had strong relationships to the measured depths, R-2 = 0.90 and 0.88, respectively. Results from this study show that using precursory EMI data to pinpoint GPR surveys is a precise, accurate, and rapid means of acquiring field-scale soil morphological information.

Lateral subsurface movement of water and solutes is of considerable interest to researchers and resource managers in many fields. Soil structure and morphology are often the dominant factors that control water and solute movement. In Major Land Resource Area 134 (Southern Mississippi Valley Silty Uplands) extending from southern Illinois to northern Louisiana, loess surface soil covers the underlying paleosol, forming a textural discontinuity that often creates transient saturated conditions. Shallow wells screened at this interface were installed to collect perched water, and bromide was applied as a tracer in 1993, Lateral movement of the bromide was very spatially varied, but bromide persisted in some areas until 1999 in the flow patterns that were initially identified. During the first year following application in 1999, lateral movement of atrazine was similar to the flow paths identified with the tracer; suggesting that the subsurface movement occurred in relatively well defined, but unpredictable areas of flow.

During the past twenty years there has been a steady increase in the number of automatic weather stations used for agricultural research and management. To date there has been little information available to operators wishing to standardize the installation, operation, calibration, maintenance, and data collection of these stations. The Irrigation Management Committee (SW-244) of the American Society of Agricultural Engineers (ASAE) has recognized the need for guidelines and has been developing an Engineering Practice to assist operators of automatic agricultural weather stations. The purpose of this Engineering Practice is to establish minimum recommendations for measurement, reporting, siting, operation, maintenance, and data management procedures for these weather stations. Additionally, these recommended procedures are intended to assist in the planning of automatic agricultural weather station installation and operation. The scope of the Engineering Practice applies to automatic weather stations installed individually, or as part of a network of stations, for the measurement and reporting of specific weather variables in agricultural environments. This Engineering Practice also addresses a recommended core set of measurements and general siting considerations for agricultural weather stations. It is recognized that special purpose agricultural weather stations may deviate from the recommendations developed for a standard installation, particularly with respect to sensor deployment and station siting conditions. This engineering practice does not specifically address these special purpose stations.