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Precision farming overcomes the paradigm of uniform field treatment by site-specific data acquisition and treatment to cope with within-field variability. Precision farming heavily relies on spatially dense information about soil and crop status. While it is often difficult and expensive to obtain precise soil information by traditional soil sampling and laboratory analysis some geophysical methods offer means to obtain subsidiary data in an efficient way. In particular, geoelectrical soil mapping has become widely accepted in precision farming. At present it is the most successful geophysical method providing the spatial distribution of relevant agronomic information that enables us to determine management zones for precision farming. Much work has been done to test the applicability of existing geoelectrical methods and to develop measurement systems applicable in the context of precision farming. Therefore, the aim of this paper was to introduce the basic ideas of precision farming, to discuss current precision farming applied geoelectrical methods and instruments and to give an overview about our corresponding activities during recent years. Different experiments were performed both in the laboratory and in the field to estimate first, electrical conductivity affecting factors, second, relationships between direct push and surface measurements, third, the seasonal stability of electrical conductivity patterns and fourth, the relationship between plant yield and electrical conductivity. From the results of these experiments, we concluded that soil texture is a very dominant factor in electrical conductivity mapping. Soil moisture affects both the level and the dynamic range of electrical conductivity readings. Nevertheless, electrical conductivity measurements can be principally performed independent of season. However, electrical conductivity field mapping does not produce reliable maps of spatial particle size distribution of soils, e.g., necessary to generate input parameters for water and nutrient transport models. The missing step to achieve this aim may be to develop multi-sensor systems that allow adjusting the electrical conductivity measurement from the influence of different soil water contents.
Magnetic susceptibility is an important indicator of anthropogenic disturbance in the natural soil. This property is often mapped with magnetic gradiometers in archaeological prospection studies. It is also detected with frequency domain electromagnetic induction (FDEM) sensors, which have the advantage that they can simultaneously measure the electrical conductivity. The detection level of FDEM sensors for magnetic structures is very dependent on the coil configuration. Apart from theoretical modelling studies, a thorough investigation with field models has not been conducted until now. Therefore, the goal of this study was to test multiple coil configurations on a test field with naturally enhanced magnetic susceptibility in the topsoil and with different types of structures mimicking real archaeological features. Two FDEM sensors were used with coil separations between 0.5 and 2 m and with three coil orientations. First, a vertical sounding was conducted over the undisturbed soil to test the validity of a theoretical layered model, which can be used to infer the depth sensitivity of the coil configurations. The modelled sounding values corresponded well with the measured data, which means that the theoretical models are applicable to layered soils. Second, magnetic structures were buried in the site and the resulting anomalies measured to a very high resolution. The results showed remarkable differences in amplitude and complexity between the responses of the coil configurations. The 2-m horizontal coplanar and 1.1-m perpendicular coil configurations produced the clearest anomalies and resembled best a gradiometer measurement.
Swedish long-term soil fertility experiments were used to investigate the effect of texture and fertilization regime on soil electrical conductivity. In one geophysical approach, fields were mapped to characterize the horizontal variability in apparent electrical conductivity down to 1.5 m soil depth using an electromagnetic induction meter (EM38 device). The data obtained were geo-referenced by dGPS. The other approach consisted of measuring the vertical variability in electrical conductivity along transects using a multi-electrode apparatus for electrical resistivity tomography (GeoTom RES/IP device) down to 2 m depth. Geophysical field work was complemented by soil analyses. The results showed that despite 40 years of different fertilization regimes, treatments had no significant effects on the apparent electrical conductivity. Instead, the comparison of sites revealed high and low conductivity soils, with gradual differences explained by soil texture. A significant, linear relationship found between apparent electrical conductivity and soil clay content explained 80% of the variability measured. In terms of soil depth, both low and high electrical conductivity values were measured. Abrupt changes in electrical conductivity within a field revealed the presence of 'deviating areas'. Higher values corresponded well with layers with a high clay content, while local inclusions of coarse-textured materials caused a high variability in conductivity in some fields. The geophysical methods tested provided useful information on the variability in soil texture at the experimental sites. The use of spatial EC variability as a co-variable in statistical analysis could be a complementary tool in the evaluation of experimental results.
The determination of the total carbon storage of peatlands is of high relevance in the context of climate-change mitigation efforts. This determination relies on data about stratigraphy and peat properties, which are conventionally collected by coring. Ground-penetrating radar (GPR) and electrical resistivity imaging (ERI) can support these point data by providing subsoil information in two-dimensional cross-sections. In this study, GPR and ERI were conducted at two groundwater-fed fen sites located in the temperate zone in north-east Germany. The fens of this region are embedded in low conductive glacial sand and are characterised by thick layers of gyttja, which can be either mineral or organic. The two study sites are representative of this region with respect to stratigraphy (total thickness, peat and gyttja types) and ecological conditions (pH-value, trophic condition). The aim of this study is to assess the suitability of GPR and ERI to detect stratigraphy and peat properties under these characteristic site conditions. Results show that GPR clearly detects the interfaces between (i) Carex and brown-moss peat, (ii) brown-moss peat and organic gyttja, (iii) organic- and mineral gyttja, and (iv) mineral gyttja and the parent material (glacial sand). These layers differ in bulk density and the related organic matter content. ERI, however, does not delineate these layers; rather it delineates regions of varying properties. At our base-rich site, pore fluid conductivity and cation.exchange capacity are the main factors that determine peat electrical conductivity (reverse of resistivity), whereas organic matter and water content are most influential at the more acidic site. Thus the correlation between peat properties and electrical conductivity are driven by site-specific conditions, which are mainly determined by the solute load in the groundwater at fens. When the total organic deposits exceed a thickness of 5 m, the depth of investigation by GPR is limited due to increasing attenuation. This is not a limiting factor for ERI, where the transition from organic deposits to glacial sand is visible at both sites. Due to these specific sensitivities, a combined application of GPR and ERI meets the demand for up-to-date information on carbon storage of peatlands, which is, moreover, very site-specific because of the inherent variety of ecological conditions and stratigraphy between peatlands in general and between fens and bogs in particular. (C) 2016 Elsevier B.V. All rights reserved.