Proximal soil sensing is a collection of technologies that employ a sensor close to, or in direct contact with, the soil. The sensor measures a soil property directly or indirectly. Viscarra Rossel et al. (2011) provide a description of proximal soil sensing, sensing technologies, and the soil properties these technologies can measure. This chapter describes different types of proximal sensing tools that can be used to map soil attributes of importance for agriculture and natural resource management.1 Soil properties vary in space and over time. As a consequence, they are seldom adequately described at field and landscape scales by traditional soil survey tools. Traditional methods of soil sampling and analyses provide detailed information at specific locations. This information, however, is limited in number, volume, and spatial coverage. See chapter 3 for a discussion of the standards and protocols used to examine and describe soils at the pedon scale in the field. At field and landscape scales, the characterization of the spatial and temporal variations is prohibitively time-consuming, expensive, and impractical using traditional point-sampling methods alone. Remote sensing (e.g., satellite images and aerial photos) can provide excellent spatial coverage, but measurements are mostly indirect and typically limited to the top 5–6 cm of soil. In addition, resolution is generally

The continuing loss of urban wetlands due to an expanding human population and urban development pressures makes restoration or creation of urban wetlands a high priority. However, urban wetland restorations are particularly challenging due to altered hydrologic patterns, a high proportion of impervious surface and stormwater runoff, degraded urban soils, historic contamination, and competitive pressure from non-native species. Urban wetland projects must also consider human-desired socio-economic benefits. We argue that using current wetland restoration approaches and existing regulatory “success” criteria, such as meeting restoration targets for vegetation structure based on reference sites in non-urban locations, will result in “failed” urban restorations. Using three wetland Case Studies in highly urbanized locations, we describe geophysical tools, stormwater management methods, and design approaches useful in addressing urban challenges and in supporting “successful” urban rehabilitation outcomes. We suggest that in human-dominated landscapes, the current paradigm of “restoration” to a previous state must shift to a paradigm of “rehabilitation”, which prioritizes wetland functions and values rather than vegetation structure in order to provide increased ecological benefits and much needed urban open space amenities.

Assessing and managing the spatial variability of hydropedological properties are important in environmental, agricultural, and geological sciences. The spatial variability of soil apparent electrical conductivity (ECa) measured by electromagnetic induction (EMI) techniques has been widely used to infer the spatial variability of hydrological and pedological properties. In this study, temporal stability analysis was conducted for measuring repeatedly soil ECa in an agricultural landscape in 2008. Such temporal stability was statistically compared with the soil moisture, terrain indices (slope, topographic wetness index (TWI), and profile curvature), and soil properties (particle size distribution, depth to bedrock, Mn mottle content, and soil type). Locations with great and temporally unstable soil ECa were also associated with great and unstable soil moisture, respectively. Soil ECa were greater and more unstable in the areas with great TWI (TWI > 8), gentle and concave slope (slope < 3%; profile curvature > 0.2). Soil ECa exponentially increased with depth to bedrock, and soil profile silt and Mn mottle contents (R-2 = 0.57), quadratically (R-2 = 0.47), and linearly (R-2 = 0.47), respectively. Soil ECa was greater and more unstable in Gleysol and Nitosol soils, which were distributed in areas with low elevation (< 380 m), thick soil solum (> 3 m), and fluctuated water table (shallow in winter and spring but deep in summer and fall). In contrast, Acrisol, Luvisol, and Cambisol soils, which are distributed in the upper slope areas, had lower and more stable soil ECa. Through these observations, we concluded that the temporal stability of soil ECa can be used to interpret the spatial and temporal variability of these hydropedological properties.

Landscape-soil-hydrology relationships vary across landscapes and are often exceedingly complex. Characterizing these complex relationships at different spatial-temporal scales and their impacts on subsurface flow and transport is a major challenge in hydropedology. Soil-landscape relationships have been traditionally inferred from point-based pedologic observations. These observations are then often extrapolated to the landscape, but seldom measured or directly confirmed across the landscape. Data gaps thus exist at the intermediate scales of hillslopes and catchments in terms of actual subsurface soils distribution and their features (termed soil-landscape architecture here), which will affect the upscaling of point-based monitoring data or the downscaling of remote-sensing data. This chapter illustrates two commonly-used geophysical tools ground-penetrating radar (GPR) and electromagnetic induction (EMI) - in revealing complex soil-landscape architecture and its impacts on subsurface flow. We investigated two contrasting landscapes - one cropland and one forestland - that are typical of the Ridge and Valley Physiographic Region in eastern United States. Repeated or time-lapsed GPR and EMI were emphasized to provide a better understanding of subsurface architecture and its effects on subsurface flow through soil moisture change over the time scales of seasons or precipitation/infiltration events. Our results showed that 1) relative difference in soil apparent electrical conductivity (ECa) across the landscapes remained relatively stable over time, which corresponded to stable soil-landform units; 2) changes in ECa over seasons within the same landscape indicated (to some degree) active zones of subsurface flow, which corresponded with simulated water flow paths and observed soil morphology; 3) south- vs. north-facing hillslopes and linear vs. concave slopes showed differences in EMI and GPR responses, which reflected the underlying differences in soil architecture; 4) depth to bedrock was highly variable across the two landscapes, but predictable patterns in the forestland were revealed through extensive GPR surveys; and 5) subsurface preferential flow pathways and patterns were identified through time-lapsed GPR investigations, which showed significant differences between shallow and deep soils. This study demonstrates the potential of geophysical tools in easing the technological bottleneck of subsurface investigation and closing data gaps at the intermediate scales.

Some South Dakota soils contain high levels of available selenium (Se) for crop uptake. A field study was conducted to determine if any popular wheat (Triticum aestivum) varieties demonstrate differential Se uptake. A total of 280 samples including eight winter wheat and ten spring wheat varieties were analyzed for grain Se concentration and uptake for two growing years. Soil samples were sequentially fractionated into (1) plant available (0.1 M KH2PO4 extractable) and (2) conditionally available (4 M HCl extractable) pools and analyzed separately for total Se. Selenium concentration in wheat grain had a wide variability and the mean value over two years was 0.63 µg Se g−1. Grain Se concentration and Se uptake were not significantly different by wheat varieties tested in this study. Grain Se concentration was significantly correlated with soil Se levels, soil pH, and orthophosphate-P content within a location, but grain Se concentration was strongly influenced by geographical location in which different amounts of soil Se bioavailability occurred.

The objective of this study was to investigate whether oxyanionic phosphate (P) and sulfate (S) fertilizer management could influence selenium (Se) uptake by wheat (Triticum aestivum) in medium and high Se areas. Field studies were established at two locations for two growing seasons in central South Dakota, USA. Phosphate fertilizer was applied using three different methods (banded with seed, surface-broadcasted in the fall, or surface-broadcasted in the spring) using six different P rates. Sulfate fertilizers were broadcasted at four rates in the fall. Selenium concentration in wheat grain was significantly influenced by the interaction of P application methods and rates, but it was dependent on location. Grain Se concentration decreased in high Se availability soil when P fertilizer was applied, due to the dilution effect. Grain Se concentration and uptake was significantly decreased as S applications increased due to the competition effect, but the depression was apparent in high Se availability soil. The results from this study showed that P and S fertilizer management can influence Se level in wheat grain grown in naturally high Se areas, even though overall grain Se level was strongly associated with location variation.

Changes in soil pH and chemical composition of solutions in vadose zone strongly affect selenite (SeO32−) adsorption and desorption properties. In this study, batch experiments were carried out to evaluate the properties of SeO32− adsorption and desorption in four South Dakota soils as a function of pH and the presence of competitive oxyanions. Selenite adsorption capacity of the soils was strongly dependent on soil pH and decreased with increasing pH between 5 and 9. Selenite adsorption capacity increased with increasing specific surface area of the soils, and Langmuir isotherm was described as an SeO32− adsorption behavior. The presence of phosphate (HPO42−) in solution significantly decreased the partition coefficient values and adsorption maximum from Langmuir isotherm on all tested soils. Although HPO42− addition affected SeO32− adsorption in all soils, the effect had depended on the pool size of SeO32− adsorption site. The competitive effect between SeO32− and HPO42− was less apparent in soils with a high adsorption capacity, and the competitive effect was more apparent in low-adsorbing capacity soils. The amount of SeO32− adsorbed per unit area was lower in the presence of HPO42− in solution, but the depression by HPO42− addition was greater in low-adsorbing capacity soils compared with high-adsorbing capacity soils because of the much fewer adsorption sites. Contrary to HPO42−, sulfate in solution had little effect on SeO32− adsorption on all tested soils, which indicates that specific adsorption plays a major role in the adsorption of SeO32−. The desorption of adsorbed SeO32− was found to be dependent on the amount of SeO32− initially adsorbed on soils and HPO42− in solution. Significantly more SeO32− desorbed when HPO42− was in solution compared with sulfate.

Soil apparent electrical conductivity (ECa) measured by electromagnetic induction (EMI) has been widely used to interpret soil spatial variability. We investigated the use of repeated EMI surveys, in combination with depth to bedrock and terrain attributes, to improve soil mapping in a 19.5‐ha agricultural landscape. The first two surveys were done in 1997 and 2006, in which different meters (EM38, EM31, and Dualem‐2), dipole orientations, and geometries were compared. The EM38 operated in vertical dipole orientation was then used in another six surveys in different seasons from 2008 to 2009. Results showed that the optimal use of EMI depends on the targeted soil properties, landscape characteristics, specific EMI meter and its setting, and the timing of the survey. The EM31 operated in vertical dipole orientation provided the deepest measurement depth (6 m) among the three meters used and showed the strongest relationship with depth to bedrock in the study area (r2 = 0.58). Because the top 2 m of soil profiles exhibited distinct textural differences across the landscape, the EM31 operated in horizontal dipole orientation and Dualem‐2 operated in horizontal co‐planar geometry (both with 3‐m measurement depth) showed the best correlation with silt content (r2 = 0.45–0.47). The best EMI mapping of major soil distribution across this landscape requires optimal timing (wet period) and an appropriate meter and setting. No single EMI survey or the relative difference in ECa of repeated EMI surveys was sufficient to obtain the best possible soil map for the study area. Instead, a combination of repeated EMI surveys, depth to bedrock, and terrain attributes provided the best mapping of soils in this agricultural landscape and doubled the accuracy of map unit purity compared with the existing second‐order soil map.

Repeated electromagnetic induction (EMI) surveys have merits of revealing temporal changes in heterogeneous soilscapes such as subsurface hydrologic dynamics. We conducted eight repeated EMI surveys from 1997 to 2009 over a 19.5-ha agricultural field that revealed soil and water patterns. The first two surveys were done in 1997 and 2006 and compared different EMI meters (EM38, EM31, and Dualem-2), dipole orientations, and geometries. Another six surveys were conducted in different seasons in 2008 to 2009 using the EM38 operated in vertical dipole orientation. Soil apparent electrical conductivity (ECa) collected during the wetter periods (>10-mm antecedent precipitation during the previous 7 d) showed greater spatial variability (greater sills and shorter spatial correlation lengths), indicating the influence of soil water distribution on soil ECa. During a relatively short time period, most soil properties controlling ECa (e.g., texture, organic matter, and depth to bedrock) remain unchanged. Thus, repeated EMI surveys can capture the dynamics of soil moisture change and related subsurface flow paths in the landscape. Significantly (p < 0.05) higher ECa was detected in areas close to simulated subsurface flow paths, especially during the wetter periods; however, such flow paths could not be pinpointed directly from the ECa maps because of the limitation in ECa spatial resolution. In wetter areas, significant correlation between the relative difference in ECa and that in measured soil moisture was observed (r(2) = 0.59-0.77), but not in drier areas. During drier periods or at drier locations, the influences of soil moisture and flow path on ECa were masked by terrain and other soil properties. Thus, the optimal use of EMI for detecting subsurface hydrologic dynamics would be during wet periods or in wet areas across the landscape in this study.

The United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS) recently revised its ground-penetrating radar (GPR) soil suitability maps (GPRSSM). These maps, which have been prepared for most areas of the USA at different scales and levels of resolution, show the relative suitability of soils for GPR soil investigations. These digital maps are based on physical and chemical properties of approximately 22,000 different soils. The smaller scale (1:250,000) Ground-Penetrating Radar Soil Suitability Map of the Conterminous United States shows the relative suitability of soils to GPR within major soil and physiographic areas. The larger scale (1:12,000 to 1:63,360) state ground-penetrating radar soil suitability maps duplicate the scale and level of detail of the original soil survey maps. GPR soil suitability maps have been used to evaluate the relative appropriateness of using GPR, select the most suitable antennas, and assess the need and level of data processing. Limitations of these maps are discussed and examples of radar records collected in soils having different GPR suitability indices are presented.

Ground-penetrating radar (GPR) has considerable potential for the detection and identification of sediment-filled wedges and relict polygonal patterns in mid-latitude areas. Relict cryogenic macrostructures have been described previously both within and outside the maximum extent of the Late Wisconsinan glacial border in many regions of the USA. The features were formed under climatic conditions associated with permafrost and periglacial conditions and provide evidence of climate change. In this study, buried relict cryogenic macrostructures were identified with GPR. On some two-dimensional GPR (2D GPR) records, boundaries with the host materials are indistinguishable or blurred resulting in the features being overlooked, misinterpreted and/or imprecisely delineated. Three-dimensional GPR (3D GPR) was able to delineate buried networks of sediment-filled wedges and provided more meaningful information than 2D radar records. When supplemented with adequate ground-truth observations, GPR offers considerable potential for imaging, interpreting and mapping near-surface cryogenic macrostructures in former periglacial environments. Copyright (C) 2009 John Wiley & Sons, Ltd.

Abstract No studies have been conducted to evaluate the potassium (K) quantity‐intensity (Q/I) relationships that exist in eastern South Dakota soils and how that may affect K fertility interpretations. The objectives of this study were to i) evaluate the K status of smectite‐dominant soils through quantity‐intensity relationships and (ii) relate the findings to current research on soil K release and plant availability. Soil and plant tissue samples were collected from eight different corn production fields across east‐central South Dakota. Samples were collected from areas where corn plants did or did not exhibit K deficiency symptoms. Quantity‐intensity plots were developed and used to derive the typical Q/I parameters. Little difference existed in Q/I parameters and the form of Q/I plots among field sites. The ARe K and ΔK0 values ranged from 0.0013 to 0.0113, and −0.47 to 0.18 cmolc kg−1, respectively, and most sites were considered K insufficient. The predominant phyllosilicate present in the clay‐sized fraction was montmorillonite with an estimated 17% tetrahedral charge. These soils would not be expected to contribute much plant‐available, nonexchangeable K and would be in need of frequent K fertilization. Presumably, these and similar soils, upon K exhaustion, rely heavily on K released from K‐bearing silt‐sized particles and may be highly dependent on surface‐controlled dissolution processes for labile K replenishment. Additional research needs to be conducted concerning the release kinetics of K from K‐bearing minerals of these soils.

Meters Depth to bedrock (m) 0.4 - 0.5 0.5 - 1.0 1.0 + Field border (a) (b) Fig.2. Maps of slope (a), the depth to bedrock (b) derived using EM survey (resolution 30 X 30m), winter wheat grain yield (c), and the predicted depth to bedrock (d) (resolution: 4 X 2m) using the method shown in Fig.3. (c) (d) ± Predicted Depth to Bedrock (m) 0 - 0.5 0.5 - 1.0 1.0 + Field border

Potassium ions (K+) may become "fixed" between adjacent phyllosilicate layers under waterlogged conditions, rendering K less available to plant uptake. This phenomenon was investigated under greenhouse conditions to determine if K fixation due to biogeochemical reduction contributed to the K deficiency in corn (Zea mays L.) in the northern Great Plains (South Dakota). The objective of this study was to evaluate the effects of a single reduction-oxidation (redox) event on soil K fractions and plant K uptake in montmorillonitic soils. Surface soil (Udolls, 0-15 cm) was collected from various sites across east-central South Dakota and used in a completely randomized greenhouse pot study (2 x 4 factorial). Reduced (Re) and reduced/reoxidized (Re/Ox) treatments were established, and corn was grown to the V5 stage of growth in a two cropping sequence. Potassium levels among soil K fractions did not significantly change upon the redox event. Dry matter (DM) yields were not significantly affected by the redox event. Cumulative K-uptake ranged from 25.7 to 33.2 mg K (kg soil(-1)), and there were no significant differences between treatments. No increase in K fixation was observed as the result of a single reduction-oxidation event. A single redox event does not cause K fixation in four montmorillonitic soils studied under greenhouse, conditions.