The beginning of the 20th century through the 1970s were good times for soil science in the USA, with relatively strong funding and overall growth in the profession. However, the soil science discipline in the USA hit hard times in the 1980s and 1990s. Federal funding for soil survey work began to decline as did student numbers in university programs and membership in the Soil Science Society of America (SSSA). Despite this, there were still many positive advances within soil science in the USA during these two decades. There was an increased use of geophysical instrumentation, remote sensing, geographic information systems (GIS), and global positioning systems (GPS), and research began in digital soil mapping, all of which lead to better understanding of the spatial distribution and variability of soils. Many NRCS soil products were put online, making them widely available to the general public, the use of soil knowledge was expanded into new areas such as archaeology and environmental work, and historic connections to geology were re-established. While expansion into new areas required soil science to evolve as a field, separating the discipline to an extent from its agricultural roots, it also helped reinvigorate the discipline. As we move through the early parts of the 21st century, student numbers are increasing in university soil science programs and membership in SSSA is at an all-time high. Digital soil mapping is being incorporated into the National Cooperative Soil Survey, and the impact of humans on the soil system is being fully recognized. The importance of soils is being recognized by events such as the United Nations declaration of 2015 as the “International Year of Soils”. The expansion of soils into new areas and widening recognition of the importance of soils gives the field hope for a bright future in the USA.

Experimental evidence has shown that soil layering can significantly alter water movement through soil profiles, especially in sloping landscapes. Detailed knowledge of soil layering and its position in the landscape is therefore necessary for determining dynamic subsurface flow. In this study, we used Ground Penetrating Radar (GPR) in combination with high resolution real-time soil water monitoring to investigate seasonal changes in GPR signals to identify soil horizon interfaces and their impacts on water flow in two contrasting soils. The results showed that 1) in the deep Rushtown soil located in a concave hillslope, GPR reflections in the Bw–BC and BC–C horizon interfaces became clearer as soil became wetter. Such increased contrast along interfaces was due to the presence of water associated with water-restricting BC horizon and lateral flow from upslope area; and 2) in the shallow Weikert soil located in a planar hillslope, GPR reflections in the soil–bedrock interface and the weathered–unweathered rock interface become intermittent as soil became wetter. This scattering of GPR reflection was due to the non-uniform distribution of water in fractured shale bedrock and possible tree root effects. While wet condition permitted the enhanced detection of water distribution in both soil profiles, optimal time for detecting soil layering was different for these two soils: wet condition was more suited for detecting water-restricting dense layer in the deep Rushtown soil, while dry season was optimal for identifying the soil–bedrock interface in the shallow Weikert soil. Overall, this study demonstrates the value of repeated GPR surveys in different seasons to capture subsurface hydrologic processes and the impacts of soil layering and preferential water distribution on seasonal changes of GPR signals. It also provides a useful reference for selecting optimal time for GPR survey in the field.

Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales.

Eutrophication associated with high concentrations of phosphorus in Missisquoi Bay has raised concerns about its influence on submersed aquatic vegetation. Subaqueous soils could play an important role in nutrient cycling, algae blooms, the spread of invasive aquatic vegetation, and water quality. The objectives of this study were to (a) characterize some of the morphological, physical and chemical properties of subaqueous soils in Missisquoi Bay based on ground-penetrating radar and soil analysis; and (b) assess relationships among the subaqueous soil landscapes, radar facies, and submersed aquatic vegetation. Coarse Stratified Sediments and Lacustrine Silt radar fades associated with Delta/Nearshore and Lakebed/Bay Bottom subaqueous soil-landscape units covered 90 percent of the study area. The Lacustrine Silt radar facies occurred in relatively deep, low-energy, depositional areas and had the highest P concentrations. The majority of the submersed aquatic vegetation was associated with Delta/Nearshore and Fringing Peatland subaqueous soil landscapes under shallow water.

Two sites located in the Northern Piedmont of Pennsylvania and suspected to have different levels of magnetic susceptibility (k) were examined using electromagnetic induction (EMI) and portable X-ray fluorescence (P-XRF). One site is underlain by micaceous schist and serpentinite; the other site by micaceous schist. The responses of an EM38-MK2-1 meter and the estimated k were greater in magnitude and more variable at the site underlain by serpentinite and micaceous schist. The average concentrations of Fe, Cr, Ni, and Ti were significantly higher in the site underlain by micaceous schist and serpentinite. At this site, high and significant correlations were derived between the concentrations of several metals measured with P-XRF and the in-phase (IP) response and the k of the upper 30 cm of the soil. Correlations were generally lower and less significant between the metals measured with P-XRF and the IP response and k at the site underlain by micaceous schist alone. As magnetic susceptibility is associated with greater amounts of ferromagnetic constituents in soils, the greater concentration of Fe measured with P-XRF at the site underlain by micaceous schist and serpentinite helps to explain the greater averaged and more variable EMI responses measured with the EM38-MK2-1 meter at the site underlain by micaceous schist and serpentinite. The contrast in the EMI and P-XRF data between these two sites was associated with differences in the mineralogy and lithologies of serpentinite and nonserpentinite derived soils.

To advance site-specific management, detailed functional (application-orientated) soil maps are desirable. This study presents an example of a functional soil map for the management of crop yields and soil moisture in an agricultural landscape located in central Pennsylvania, USA. A high-intensity soil map was prepared using electromagnetic induction (EMI), terrain attribute, and soil core data. Two soil properties, A horizon texture and depth to clay layer were found to be significantly correlated (p<0.05) with soil moisture and crop yields (corn and soybean). A functional soil map was generated by overlaying these two properties on the high-intensity soil map. Spatial and temporal variations in soil moisture and crop yield within different functional map units were statistically compared with those within different map units on the second-order and the high-intensity soil maps. While soil moisture and crop yield did not show obvious difference among map units of the second-order soil map, clear differences were observed among the functional soil map units developed in this study. This study demonstrates that the accuracy and utility of second-order soil maps for site-specific management can be improved using EMI and functional soil mapping approaches.

It all began for me in Florida in the late 1970s when a USDA Soil Conservation Service (SCS) soil scientist became friends with a NASA engineer at the Kennedy Space Center. The soil scientist recognized that manual and mechanical augers and probes provide highly needed and detailed soil information but were also slow and tedious to use, thus limiting the number of observations that could be made. The soil scientist and NASA engineer wanted a faster and less labor-intensive tool that could be used to increase the quality and quantity of soil information. In 1979, in a cooperative project, USDA-SCS, NASA, and the Florida Department of Transportation studied the use of resistivity and ground-penetrating radar (GPR) in soil survey (Benson and Glaccum, 3; Johnson et al., 6). After reviewing the existing literature, the group decided that GPR would offer the greatest possibility. Working with a geophysical company (Technos, Inc., Miami, FL), more than 12 km of continuous radar data were collected at sites in Polk and Hardee Counties, Florida. A conclusion drawn from this study was that GPR provides a means of obtaining a large quantity of detailed soil information in a relatively short time (Johnson et al., 6). Furthermore, these researchers observed that “borings are needed to establish ground truth for [radar] signatures” and that once correlations between borings and radar imagery have been developed, “lat-eral extension of information can be made with a high degree of accuracy without additional borings” (Johnson et al., 6). Shortly after the study by Johnson et al. (6), a brief article about it appeared in a newsletter by USDA-SCS (11). At that time, I was a soil scientist in North Dakota. When I read the article, I remember saying to my soil survey party members, “Those turkeys in Florida think that they can map soils with radar.” Shortly after the article was written, a GPR unit was purchased, and a vacancy announcement for a GPR operator in Florida was issued. Well, at that time, I thought that I had too many North Dakota winters and needed to get back East. No one in Florida seemed to want the job, and I had some experience with a different type of radar in the Navy, and so began one of the most rewarding and enjoyable rides of my life. Shortly after arriving in Florida, I was sent to New Hampshire for radar training at Geophysical Surveys System, Inc. (GSSI). I was accompanied by Dr. Ron Patezold, a soil physicist with SCS, who was then assigned to a USDA Agricultural Research Service (ARS) facility in Beltsville, MD. Ron was interested in using GPR to assess variations in soil moisture content. Ron and I would take turns either operating the radar control unit or pulling the radar antenna across a test area. In order to make the best interpretation, Ron would “over gain” while I tended to “under gain” the radar signal. Less rather than more information provided me with a better image on which to make my interpretation, and for Ron, it was the opposite. There is no cookbook setting with GPR, and so the lesson learned was that GPR results depend on the interpreter. While attending classroom sessions at GSSI, my attention was often distracted by a large map on a wall that showed the effective ground conductivity for the conterminous USA. This map was developed by the Federal Communication Commission in 1954. The performance of GPR depends on the electrical conductivity of soils. Soils having high electrical conductivity rapidly attenuate radar energy, restrict penetration depths, and severely limit the effectiveness of GPR. The FCC map (Fine, 5) provided general guidance as to suspected rates of signal attenuation, penetration depths, and relative suitability of GPR within different areas of the United States. Because this map was prepared at a small scale (1:2,500,000) and from a limited sample population (7,000 ray paths and 127 soil samples), broad generalizations were naturally made. While I didn't know it at the time, this map would play a major role in my GPR career. Often times, I would get a call asking if GPR would work in a specific soil or area of the country. I would look at a copy of this map, which was hung over my desk, and answer “yes” or “no” based on the observed radar performance for the effective conductivity values given for Florida and in other areas that I had worked with GPR. As far as the property or target in the soil that the radar was going to be used to detect, I had no clue unless I had already tried to identify it in Florida. In my early GPR days, little was known about the performance of GPR in different soils. Ground-penetrating radar was a relatively new technology, and very little was known or written about its use. The first commercially available GPR had only been marketed in the mid-1970s. In one of the earlier references on GPR, the dielectric permittivity for “average soil” was listed as 16 (Morey, 9). This “average” soil would elude me throughout my GPR career. Soils are too spatially and temporally variable for an “average” value to have significance. This map of effective ground conductivity provided early guidance as to the use of GPR for soil investigations in different parts of the USA. My first radar unit was extremely bulky and cumbersome. Typically, in relatively open areas, the control and recording units were housed in a vehicle with an antenna towed in a sled behind this mobile platform. The unit was powered by the vehicle's battery. In more inaccessible areas, the unit was carried into a site with either a generator or a set of marine batteries for a power source. In many inhospitable terrains (e.g., steeply forested, densely vegetated), this was a most onerous task that I never looked forward to. The transmission line, which connected the control unit with the antenna, was 30 m long. As a result, an area with this radius could be surveyed around the control and recording units before these components needed to be repositioned. Radar data were displayed on an oscilloscope and strip charts. Interpretations were made directly from raw data on strip charts. There was a tape recorder, but it was not intended for field use and never worked well. Available signal-processing techniques were extremely primitive and largely borrowed from the seismic community. Florida possesses optimal soil conditions for the use of GPR: extensive areas of electrically resistive sands. My first venture out of Florida was in 1983 to Texas and Oklahoma for both soil and engineering GPR studies. My first location was near Hondo, TX. I still can recall the scene as I drove up to the site along the highway. The SCS state soil scientist had gathered a very large crowd of highway department officials, SCS soil scientists and engineers, and university faculty and students to witness the radar chart the depth to bedrock. That was one of the longest days of my career. Texas is not the sand pile that Florida is, especially along the highway northeast of Hondo. With the GPR, I never saw the bedrock until it was exposed at the surface. Well, that day, I learned to appreciate soils with high clay contents and expansive clay mineralogy. The lesson learned was that GPR results are site specific and soil dependent. The first radar unit that was purchased by USDA consisted of a control unit (A), power distribution unit (B), tape recorder (C), and graphic recorder (D). Three antennas were also purchased with this unit, operating at a center frequency of 80, 120, and 300 MHz. Early radar units were bulky and cumbersome. In relatively open areas, mobile surveys were conducted towing the antenna behind a vehicle (A). In more inaccessible areas, the GPR unit had to be carried in and powered off a generator with the antenna limited to a 30 m search radius (B). The use of GPR gradually expanded in soil science and agriculture. In 1986, a small group of soil scientists representing USDA-SCS, USDA-ARS, and the University of Florida got together in Tifton, GA to discuss GPR and the challenges that they were facing. They were joined by geophysicists from the USA and other countries. In 1988, the University of Florida and USDA-SCS hosted the Second International Symposium on Geotechnical Applications of Ground-Penetrating Radar in Gainesville, FL. Following these meetings, an international conference on GPR has been held every two years in countries around the world. Presently, the 14th International Conference on GPR (GPR2012) is being hosted by Tongji University, in Shanghai, China. It is always a pleasurable thought that these conferences were begun by a small group of soil scientists wanting to know more about GPR. During my first 10 years with GPR, this geophysical method was on a wide variety of soils in different physiographic regions throughout the USA. These were the “dog-and-pony show” days of my career: Ground-penetrating radar was a novel tool in soil survey, and many soil scientists wanted to see it demonstrated on their soils. More often than not, soils that were unfavorable for GPR were selected and results were disappointing. However, knowledge in the form of a geographic perspective into the soil properties that influence GPR did come out of these setbacks. It must be said that in many studies, GPR did provide accurate and detailed information. During this period, it was principally used to evaluate soil properties and estimate the variability and the taxonomic composition of soil map units. In this capacity, GPR was repeatedly used to chart the lateral extent and depth of soil horizons; delineate pans, water tables, and bedrock and stratigraphic surfaces; assess soil compaction and plow pan development; and infer variations in soil texture, organic matter content, humification, and cementation. I always felt that GPR is a relatively expensive tool that must be kept in use and in the field rather than sitting on a shelf. In addition, I always felt a need to seek out new avenues of application and provide service to all potential customers. In the late 1980s, after completing back-to-back assignments using GPR to non-destructively detect brown rot and hollows in standing trees in Mississippi and to map the distribution of pocket gopher burrows in Kansas, my supervisor referred to me as a “loaded, misdirected cannon.” I missed the point and considered his statement as a compliment. In the mid-1990s, GPR transitioned from analog to digital systems. Radar units became increasingly smaller, lighter weight, and less expensive. Each new unit provided increased capabilities. Pedestrian surveys, with the GPR control and recording unit attached to a harness worn by the operator, became the standard field protocol. In the last 15 years, significant advances have occurred and at an accelerated rate in GPR technology. My first radar unit was a subsurface interface radar (SIR)-8 system, which I used for 15 years. In the last 15 years, I have gone through three different radar systems: SIR-2, SIR-2000, and SIR-3000. All of these succeeding units provided increased capabilities and advantages for soil investigations. In the late-1990s, signal processing matured, opening new windows of opportunity for GPR. Today, advanced signal-processing techniques are routinely used in many applications, and processing has become the “key” to modern GPR interpretations. The use of advanced processing techniques has greatly improved the characterization of some subsurface features. It was becoming evident at this time that the map prepared for the FCC was too coarse and inaccurate to guide GPR applications. In 2002, collaborative work by soil scientists and GIS specialists from the USDA-NRCS National Cartography and Geospatial Center, National Soil Survey Center, and National Geospatial Management Center resulted in the development of the Ground-Penetrating Radar Soil Suitability Map of the Conterminous United States. This thematic map, as well as state GPR soil suitability maps, has largely replaced the 1954 FCC map as a guide for projecting the relative suitability of soils to GPR. During the past decade, the union of GPR with GPS has permitted the collection of georeferenced GPR data sets, which can be manipulated and displayed in GIS or other imaging software. This synergy has greatly improved the utility of GPR in soil investigations. In addition, newly developed interactive interpretation modules provide for the rapid, semi-automatic “picking” of subsurface features. This has expedited interpretations and has resulted in the compilation of large data sets that are automatically transcribed into layer files, which can be imported into GIS or Excel spreadsheets for analysis. The Ground-Penetrating Radar Soil Suitability Map of the Conterminous United States shows that only 22% of the soils (colored green) are considered well suited to GPR. Thirty-six and seven percent of the soils are considered poorly and unsuited to GPR (colored brown and purple), respectively. Ground-penetrating radar has changed considerably over the years. Present GPR systems are well suited to soil investigations. Within USDA-NRCS, the number of radar operators has expanded greatly in this century. Presently there are 15 radar units located in 12 states [AR, CA, CT, FL (3), GA (2), MA, RI, PA, NC, NJ, WI, and WV]. Many universities have GPR systems and are using them in a wide variety of research activities. As many new radar operators are recent college graduates, they have introduced new and more contemporary skill sets. Using advanced analysis and display formats, they are exploiting the full digital data and analysis capabilities of modern GPR systems. Over the years, GPR has been able to adjust to new areas of emphasis. In recent years, it has been successfully used to characterize and map subaqueous and anthropogenic soils. It has also been extensively used in hydropedological and hydrogeophysical investigations. Here, it is being used to characterize soil, stratigraphic, and lithologic structures that influence the movement of water in both the saturated and unsaturated zones at scales ranging from several meters to watersheds. Rapidly advancing and often leap-frogging technologies have changed the way GPR soil investigations are being conducted. Present GPR systems are intergraded with GPS, and results are often displayed in GIS. Today, GPR rests on a firm foundation in soils and agriculture. Younger minds, exploring new areas of application, are continually putting out new additions onto this foundation. These younger, more innovative minds are finding new ways to process and archive radar data so that they will not be lost as has been the case in the past. They are open to the use of different technologies with GPR and seek new avenues for its use. For those interested in learning more about GPR, there have been numerous dissertations and articles written on its theory and application. Several books have been written expressly on GPR (e.g., Daniels, 4; Jol, 7; Miller et al., 8) while others have chapters devoted to GPR (e.g., Allred et al., 1; Rubin and Hubbard, 10). International conferences are held specifically for GPR, while others have papers presented on the topic. In addition, several focus groups have been established in professional organizations devoted to near-surface geophysics. Looking back on the last thirty years, I am pleased with the modest advancements that have been made with GPR in soils and agriculture and the even greater progress that has been made in system design and signal-processing procedures. I am confident that, in the future, GPR will have an expanded role to play in both soil and agriculture research and applications. My journey with GPR is almost over, and it has been a most enjoyable ride.

Although ground-penetrating radar (GPR) is extensively used to characterize the regolith, few studies have addressed the effects of chemical and mineralogical compositions of soils and bedrock on its performance. This investigation evaluated the performance of GPR on two different granitic regoliths of somewhat different mineralogical composition in the San Jacinto Mountains of southern California. Radar records collected at a site where soils are Alfisols were more depth restricted than the radar record obtained at a site where soils are Entisols. Although the Alfisols contain an argillic horizon, and the Entisols have no such horizon of clay accumulation, the main impact on GPR effectiveness is related to mineralogy. The bedrock at the Alfisol site, which contains more mafic minerals (5% hornblende and 20% biotite), is more attenuating to GPR than the bedrock at the Entisol site, where mafic mineral content is less (<1% hornblende and 10% biotite). Thus, a relatively minor variation in bedrock mineralogy, specifically the increased biotite content, severely restricts the performance of GPR.

Sodium- and salt-affected soils extend well over 10 million hectares in the Northern Great Plains (NGP) of the USA. Levels of soil sodicity and salinity vary spatially across the landscape; vertically with soil depth, and temporally; making it difficult to characterize, classify, and manage these soils. Laboratory measurements are relatively time-consuming and costly to obtain, and are therefore limited in number. Surrogate field measures of apparent electrical conductivity (ECa) obtained with electromagnetic induction (EMI) are being evaluated to improve the classification, mapping, interpretation and management of these soils in the NGP. This paper examines the use of EMI with the ESAP (ECe Sampling, Assessment, and Prediction) software program to predict and map the variability of soil sodicity and salinity at field scales. Large ECa data sets were collected across four fields located within the Rolling Soft Shale Plain resource area of southwestern North Dakota. These data sets were used with the ESAP-RSSD (response surface sampling design) program to locate a minimum number of soil sampling (calibration) sites within each field where soils were sampled for laboratory characterization. Geo-referenced ECa and soil profile characterization data were used to calibrate appropriate predictive equations for soil sodicity and salinity and to estimate the spatial variability of both properties. At all sites, soils became more sodium-affected and saline with increasing depths. For the 0 to 90 cm depth interval (primary rooting zone), soils were dominantly saline (>4 dS/cm) non-sodic (SAR <13) and saline-sodic (>4 dS/m and SAR >13). However, inclusions of non-saline (<4 dS/m) and non-sodic (SAR <13) soils occurred in each unit of management. Simulations were use to characterize spatial patterns of soil sodicity and salinity. This methodology shows promise for improving the understanding of soil-landscape relationships and impacting the classifications and interpretations for sodium-affected and saline soil map units in the NGP.

The ability to inventory and map soil salinity at regional scales remains a significant challenge to scientists concerned with the salinization of agricultural soils throughout the world. Previous attempts to use satellite or aerial imagery to assess soil salinity have found limited success in part because of the inability of methods to isolate the effects of soil salinity on vegetative growth from other factors. This study evaluated the use of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery in conjunction with directed soil sampling to assess and map soil salinity at a regional scale (i.e., 10-10(5) km(2)) in a parsimonious manner. Correlations with three soil salinity ground truth datasets differing in scale were made in Kittson County within the Red River Valley (RRV) of North Dakota and Minnesota, an area where soil salinity assessment is a top priority for the Natural Resource Conservation Service (NRCS). Multi-year MODIS imagery was used to mitigate the influence of temporally dynamic factors such as weather, pests, disease, and management influences. The average of the MODIS enhanced vegetation index (EVI) for a 7-yr period exhibited a strong relationship with soil salinity in all three datasets, and outperformed the normalized difference vegetation index (NDVI). One-third to one-half of the spatial variability in soil salinity could be captured by measuring average MODIS EVI and whether the land qualified for the Conservation Reserve Program (a USDA program that sets aside marginally productive land based on conservation principles). The approach has the practical simplicity to allow broad application in areas where limited resources are available for salinity assessment.

The search for unmarked and clandestine graves is a labor-intensive, time-consuming, and often frustrating task. Several geo-physical methods are available, which can be expediently used with little or no disturbances to sites, among which ground-penetrating radar (GPR) is often considered the most useful tool to delineate possible graves. This paper is the result of many years of GPR testing for unmarked graves in Connecticut. Natural and cultural conditions are considered in the failure and/or success of detection, and the use of GPR in archaeological studies.

Soil Survey HorizonsVolume 50, Issue 1 p. 25-30 Article Three "G's" for Soil-Bedrock Depth Interpretations Jim Doolittle, Corresponding Author Jim Doolittle Research Soil Scientist Jim.Doolittle@lin.usda.gov USDA-NRCS-NSSC, Newtown Square, PASearch for more papers by this authorDebbie Surabian, Debbie Surabian Soil Scientist USDA-NRCS, Tolland, CTSearch for more papers by this authorShawn McVey, Shawn McVey Assistant State Soil Scientist USDA-NRCS, Tolland, CTSearch for more papers by this authorDonald Parizek, Donald Parizek Soil Scientist USDA-NRCS, Windsor, CTSearch for more papers by this author Jim Doolittle, Corresponding Author Jim Doolittle Research Soil Scientist Jim.Doolittle@lin.usda.gov USDA-NRCS-NSSC, Newtown Square, PASearch for more papers by this authorDebbie Surabian, Debbie Surabian Soil Scientist USDA-NRCS, Tolland, CTSearch for more papers by this authorShawn McVey, Shawn McVey Assistant State Soil Scientist USDA-NRCS, Tolland, CTSearch for more papers by this authorDonald Parizek, Donald Parizek Soil Scientist USDA-NRCS, Windsor, CTSearch for more papers by this author First published: 04 August 2015 https://doi.org/10.2136/sh2009.1.0025Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume50, Issue1Spring 2009Pages 25-30 RelatedInformation

The fundamental purposes of a soil survey are to show (cartographically) the geographic distribution of the soils and make land-use predictions about those soils. A wide array of environmental, ecological, agricultural, geological, and natural resource issues have placed greater demands on soil survey information. Traditional soil maps, soil map units, and interpretations may be inadequate when confronting these complex issues, and in particular, issues that require detailed hydrologic information.

Electromagnetic induction (EMI) and global positioning system (GPS) data were used with geographical information system (GIS) to improve a high intensity soil survey that was completed with traditional methods in northwest Illinois. Apparent conductivity (ECa) maps provided additional layers of information, which improved knowledge of soils and directed soil sampling. The information provided by ECa maps and additional soil sampling led soil scientists to recognize different soils and modify mapping concepts. Within the site, ECa maps assisted the identification and delineation of soil polygons and improved the quality of the high-intensity soil map. White spatial ECa patterns influenced the judgments of soil scientists, ECa maps were not accepted as a substitute for a high-intensity soil map.

In coarse-textured soils, ground-penetrating radar (GPR) can provide continuous, high-resolution records that chart the depth to water tables. The use of this information can increase confidence in hydropedological site assessments and reduce the number of wells needed for water-table depth and ground-water flow determinations. Ground-penetrating radar was used to map spatial and temporal variations in water-table depths and ground-water flow patterns within an unconfined aquifer located beneath an eolian landscape in northwestern Indiana. Compared with the data collected at a limited number of wells, the greater number of observations with GPR provided more comprehensive site coverage and mapped more intricate local ground-water flow patterns. Over a 2-year period, GPR revealed systematic temporal and spatial variations in water-table depths and local ground-water flow patterns.