Refine
Year of publication
Document Type
- Article (45)
- Part of a Book (2)
- Monograph/Edited Volume (1)
- Conference Proceeding (1)
Keywords
Kartierung der elektrischen Leitfähigkeit zur Erfassung räumlicher Variationen von Bodenparametern
(1999)
Die elektrische Leitfähigkeit als eine Steuergröße für die teilflächenspezifische Landwirtschaft
(1998)
Deep crustal structure of the Northeast German Basin : new DEKORP-BASIN ï96 deep-profiling results
(1999)
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.
The application of electrical resistivity tomography to peatlands supports conventional coring by providing data on the current condition of peatlands, including data on stratigraphy, peat properties and thickness of organic deposits. Data on the current condition of drained peatlands are particularly required to improve estimates of carbon storage as well as losses and emissions from agriculturally used peatlands. However, most of the studies focusing on electrical resistivity tomography surveys have been conducted on natural peatlands with higher groundwater levels. Peatlands drained for agriculture have not often been studied using geophysical techniques. Drained sites are characterized by low groundwater levels and high groundwater fluctuations during the year, which lead to varying levels of water saturation. To validate better electrical resistivity tomography surveys of drained peatlands, the aim of this laboratory study is to investigate the influence of varying water saturation levels on electrical conductivity (reciprocal of resistivity) for a variety of peat and gyttja types, as well as for different degrees of peat decomposition. Results show that different levels of water saturation strongly influence bulk electrical conductivity. Distinct differences in this relationship exist between peat and gyttja substrates and between different degrees of peat decomposition. Peat shows an exponential relationship for all degrees of decomposition, whereas gyttja, in particular organic-rich gyttja, is characterized by a rather unimodal relationship. The slopes for the relationship between electrical conductivity and water content are steeper at high degrees of decomposition than for peat of low degrees of decomposition. These results have direct implications for field electrical resistivity tomography surveys. In drained peatlands that are strongly susceptible to drying, electrical resistivity tomography surveys have a high potential to monitor the actual field water content. In addition, at comparable water saturations, high or low degrees of decomposition can be inferred from electrical conductivity.
Two types of electrical conductivity sensors were evaluated to prospect circular ditches surrounding former Bronze Age burial mounds, complementing aerial photography. The first sensor was based on the electrical resistivity (ER) method, while the second sensor was based on frequency-domain electromagnetic induction (FDEM). Both sensors were designed with multiple receivers, which measure several depth sensitivities simultaneously. First, the sensors were tested on an experimental site where a rectangular structure with limited dimensions was dug in a sandy soil. The structure appeared as a higher conductivity anomaly in the low-conductivity sand. Then, both methods were applied on two Bronze Age sites with different soil properties, which were discovered by aerial photography. The first site, in a sandy soil, gave only very weak anomalies. Soil augering revealed that the ditch filling consisted of the same sandy material as the surrounding, therefore this filling was not able to cause a high-conductivity contrast. Due to its lower sensitivity to noise in the low-conductive range, the ER-sensor produced a more pronounced anomaly than the FDEM-sensor. The second site was located on top of a ridge with a shallow substrate of Tertiary, coastal sediments. The ditch was very clearly visible on the sensor maps as a conductive low. At this location, the soil augering revealed that the ditch was dug through an alternating clay-sand layer and subsequently filled up with silty material from the topsoil. Overall, the shallow receiver separation produced anomalies that were both stronger and that corresponded better to the geometry of the ditches. The other receiver separations provided more information on the natural soil layering, and in the case of the ER-array they could be used to obtain a cross-section of the actual electrical conductivity with 2-D inversion modelling. The results of this study proofed that conductivity sensors can detect Bronze Age ditches, with varying contrast depending on the soil geomorphology. Moreover, the sensor maps combined with soil observations by coring provided insight in the environmental conditions that influence the contrast of the anomalies seen on the aerial photographs and the sensor maps.
Magnetische Kartierung einer Kreisgrabenanlage im Oderbruch bei Platkow, Lankreis Märkisch-Oderland
(1997)
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.
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%.
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.
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.
Inland salt meadows are particularly valuable ecosystems, because they support a variety of salt-adapted species (halophytes). They can be found throughout Europe; including the peatlands of the glacial lowlands in northeast Germany. These German ecosystems have been seriously damaged through drainage. To assess and ultimately limit the damages, temporal monitoring of soil salinity is essential, which can be conducted by geoelectrical techniques that measure the soil electrical conductivity. However, there is limited knowledge on how to interpret electrical conductivity surveys of peaty salt meadows. In this study, temporal and spatial monitoring of dissolved salts was conducted in saline peatland soils using different geoelectrical techniques at different scales (1D: conductivity probe, 2D: conductivity cross-sections). Cores and soil samples were taken to validate the geoelectrical surveys. Although the influence of peat on bulk conductivity is large, the seasonal dynamics of dissolved salts within the soil profile could be monitored by repeated geoelectrical measurements. A close correlation is observed between conductivity (similar to salinity) at different depths and temperature, precipitation and corresponding groundwater level. The conductivity distribution between top- and subsoil during the growing season reflected the leaching of dissolved salts by precipitation and the capillary rise of dissolved salts by increasing temperature (similar to evaporation). Groundwater levels below 0.38 cm resulted in very low conductivities in the topsoil, which is presumably due to limited soil moisture and thus precipitation of salts. Therefore, to prevent the disappearance of dissolved salts from the rooting zone, which are essential for the halophytes, groundwater levels should be adjusted to maintain depths of between 20 and 35 cm. Lower groundwater levels will lead to the loss of dissolved salts from the rooting zone and higher levels to increasing dilution with fresh rainwater. The easy-to-handle conductivity probe is an appropriate tool for salinity monitoring. Using this probe with regressions adjusted for sandy and organic substrates (peat and organic gyttja) additional influences on bulk conductivity (e.g. cation exchange capacity, water content) can be compensated for and the correlation between salinity and electrical conductivity is high.
In near- surface geophysics, ground-based mapping surveys are routinely used in a variety of applications including those from archaeology, civil engineering, hydrology, and soil science. The resulting geophysical anomaly maps of, for example, magnetic or electrical parameters are usually interpreted to laterally delineate subsurface structures such as those related to the remains of past human activities, subsurface utilities and other installations, hydrological properties, or different soil types. To ease the interpretation of such data sets, we have developed a multiscale processing, analysis, and visualization strategy. Our approach relies on a discrete redundant wavelet transform (RWT) implemented using cubic-spline filters and the a trous algorithm, which allows to efficiently compute a multiscale decomposition of 2D data using a series of 1D convolutions. The basic idea of the approach is presented using a synthetic test image, whereas our archaeogeophysical case study from northeast Germany demonstrates its potential to analyze and process rather typical geophysical anomaly maps including magnetic and topographic data. Our vertical-gradient magnetic data show amplitude variations over several orders of magnitude, complex anomaly patterns at various spatial scales, and typical noise patterns, whereas our topographic data show a distinct hill structure superimposed by a microtopographic stripe pattern and random noise. Our results demonstrate that the RWT approach is capable to successfully separate these components and that selected wavelet planes can be scaled and combined so that the reconstructed images allow for a detailed, multiscale structural interpretation also using integrated visualizations of magnetic and topographic data. Because our analysis approach is straightforward to implement without laborious parameter testing and tuning, computationally efficient, and easily adaptable to other geophysical data sets, we believe that it can help to rapidly analyze and interpret different geophysical mapping data collected to address a variety of near-surface applications from engineering practice and research.
Information regarding the spatial distribution of soil water content is key in many disciplines and applications including soil and atmospheric sciences, hydrology, and agricultural engineering.
Thus, within the past decades various experimental methods and strategies have been developed to map spatial variations in soil moisture distribution and to monitor temporal changes.
Our study examines the combination of electrical resistivity mapping and point observations of soil moisture to infer the spatial and the temporal variability of soil moisture.
Over a period of around two years, we performed field measurements on six days to collect repeated electrical resistivity mapping data for a nine-hectare test site south-east of Berlin, Germany.
Permanently installed TDR probes, temporary TDR measurements within permanently installed tubes, and gravimetric measurements using soil samples provided soil moisture data at various selected points.
In addition, soil analysis and classification results are available for 132 regularly distributed positions up to depths of 1.2 m.
We compare and link three-dimensional resistivity models obtained via data inversion to soil composition and soil moisture as provided by our point data.
Both the soil samples and the resistivity models indicate a two-layer medium characterized by a sandy top layer with varying thickness and a loamy bottom soil.
For all six field campaigns, we observe similar resistivity patterns reflecting the temporally stable influence of soil texture.
While the overall patterns are stable, the range of resistivity values changes with soil moisture. Finally, to estimate spatial models of soil moisture, we link our soil moisture and resistivity data using empirical petrophysical models relying on a second order polynomial function.
We observe a mean prediction error for soil moisture of +/-0.034 m3 & BULL; m? 3 using all observation points while we notice that point-specific models further reduce the error.
Thus, we conclude that our experimental and data analysis strategies represent a reliable approach to establish site-specific models and to estimate three-dimensional moisture distribution including temporal variations.