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Crop yield variations are strongly influenced by the spatial and temporal availabilities of water and nitrogen in the soil during the crop growth season. To estimate the quantities and distributions of water and nitrogen within a given soil, process-oriented soil models have often been used. These models require detailed information about the soil characteristics and profile architecture (e.g., soil depth, clay content, bulk density, field capacity and wilting point), but high resolution information about these soil properties, both vertically and laterally, is difficult to obtain through conventional approaches. However, on-the-go electrical resistivity tomography (ERT) measurements of the soil and data inversion tools have recently improved the lateral resolutions of the vertically distributed measurable information. Using these techniques, nearly 19,000 virtual soil profiles with defined layer depths were successfully created for a 30 ha silty cropped soil over loamy and sandy substrates in Central Germany, which were used to initialise the CArbon and Nitrogen DYnamics (CANDY) model. The soil clay content was derived from the electrical resistivity (ER) and the collected soil samples using a simple linear regression approach (the mean R-2 of clay = 0.39). The additional required structural and hydrological properties were derived from pedotransfer functions. The modelling results, derived soil texture distributions and original ER data were compared with the spatial winter wheat yield distribution in a relatively dry year using regression and boundary line analysis. The yield variation was best explained by the simulated soil water content (R-2 = 0.18) during the grain filling and was additionally validated by the measured soil water content with a root mean square error (RMSE) of 7.5 Vol%.
Direct current systems employing a kinematic surveying strategy allow to analyze the electrical resistivity of the subsurface for large areas (i.e., several hectares). Typical applications are found in precision agriculture, archaeological prospecting and soil sciences. With the typical survey setting, the collected data sets are often characterized by a rather high level of noise and a rather coarse lateral sampling compared to data acquired with fixed electrodes. We therefore present an efficient one-dimensional inversion approach in which we put special attention on modeling the effects of noise. We apply this method to data recorded with a five-offset equatorial dipole-dipole system employing rolling electrodes. By performing several synthetic tests with realistic noise levels, we found that the considered five-configuration soundings allow for a reliable imaging of two-layer cases in the uppermost two meters of the subsurface, where the subsurface can be assumed to follow a horizontally layered geometry within 3 m around the system. By analyzing the corresponding sensitivity functions, we also show that the equatorial dipole-dipole array is relatively well suited for a 1D inversion approach compared to standard in-line electrode arrays. To illustrate this aspect, we show that our method can provide results similar to those obtained with a 2D Wenner imaging procedure for data recorded across a well-constrained 2D target. We finally apply our method to a large five-offset data set acquired in an agricultural study. The final pseudo-3D model of electrical resistivity is in accordance with borehole data available for the surveyed area. Our results demonstrate the applicability and the versatility of the presented inversion approach for large-scale data sets as they are typically collected with such rolling electrode systems. (C) 2017 Elsevier B.V. All rights reserved.
We present an algorithm that performs sequentially one-dimensional inversion of subsurface magnetic permeability and electrical conductivity by using multi-configuration electromagnetic induction sensor data. The presented method is based on the conversion of the in-phase and out-of-phase data into effective magnetic permeability and electrical conductivity of the equivalent homogeneous half-space. In the case of small-offset systems, such as portable electromagnetic induction sensors, for which in-phase and out-of-phase data are moderately coupled, the effective half-space magnetic permeability and electrical conductivity can be inverted sequentially within an iterative scheme. We test and evaluate the proposed inversion strategy using synthetic and field examples. First, we apply it to synthetic data for some highly magnetic environments. Then, the method is tested on real field data acquired in a basaltic environment to image a formation of archaeological interest. These examples demonstrate that a joint interpretation of in-phase and out-of-phase data leads to a better characterisation of the subsurface in magnetic environments such as volcanic areas.
The Lower Rhine Graben (Central Europe) is a prime example of a seismically active low-strain rift zone characterized by pronounced anthropogenic and climatic overprint of structures, and long recurrence intervals of large earthquakes. These factors render the identification of active faults and surface ruptures difficult. We investigated two fault scarps in the Lower Rhine Graben, to decipher their structural character, offset and potential seismogenic origin. Both scarps were modified by anthropogenic activity. The Hemmerich site lies c. 20 km SW of Cologne, along the Erft Fault. The Untermaubach site lies SW of Duren, where the Schafberg Fault projects into the Rur River valley. At the Hemmerich site, geomorphic and geophysical data, as well as exploratory coring reveal evidence of repeated normal faulting. Geophysical analysis and palaeoseismological excavation at the Untermaubach site reveal a complex fault zone in Holocene gravels characterized by subtle gravel deformation. Differentiation of tectonic and fluvial features was only possible with trenching, because fault structures and grain sizes of the sediments were below the resolution of the geophysical data. Despite these issues, our investigation demonstrates that valuable insight into past earthquakes and seismogenic deformation in a low-strain environment can be revealed using a multidisciplinary approach.
Deep crustal structure of the Northeast German Basin : new DEKORP-BASIN ï96 deep-profiling results
(1999)
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.
GEOPHILUS ELECTRICUS (nickname GEOPHILUS) is a novel system for mapping the complex electrical bulk resistivity of soils. Rolling electrodes simultaneously measure amplitude and phase data at frequencies ranging from 1 mHz to 1 kHz. The sensor's design and technical specifications allow for measuring these parameters at five depths of up to ca. 1.5 m. Data inversion techniques can be employed to determine resistivity models instead of apparent values and to image soil layers and their geometry with depth. When used in combination with a global positioning system (GPS) and a suitable cross-country vehicle, it is possible to map about 100 ha/day (assuming 1 data point is recorded per second and the line spacing is 18 m). The applicability of the GEOPHILUS system has been demonstrated on several sites, where soils show variations in texture, stratification, and thus electrical characteristics. The data quality has been studied by comparison with 'static' electrodes, by repeated measurements, and by comparison with other mobile conductivity mapping devices (VERIS3100 and EM38). The high quality of the conductivity data produced by the GEOPHILUS system is evident and demonstrated by the overall consistency of the individual maps, and in the clear stratification also confirmed by independent data.
The GEOPHILUS system measures complex values of electrical resistivity in terms of amplitude and phase. Whereas electrical conductivity data (amplitude) are well established in soil science, the interpretation of phase data is a topic of current research. Whether phase data are able to provide additional information depends on the site-specific settings. Here, we present examples, where phase data provide complementary information on man-made structures such as metal pipes and soil compaction.
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.