TY - JOUR A1 - Walter, J. A1 - Hamann, Göran A1 - Lück, Erika A1 - Klingenfuss, C. A1 - Zeitz, Jutta T1 - Stratigraphy and soil properties of fens: Geophysical case studies from northeastern Germany JF - Catena : an interdisciplinary journal of soil science, hydrology, geomorphology focusing on geoecology and landscape evolution N2 - 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. KW - Fen stratigraphy KW - Peat properties KW - Gyttja KW - Ground penetrating radar KW - Electrical conductivity KW - Electrical resistivity imaging Y1 - 2016 U6 - https://doi.org/10.1016/j.catena.2016.02.028 SN - 0341-8162 SN - 1872-6887 VL - 142 SP - 112 EP - 125 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Allroggen, Niklas A1 - van Schaik, N. Loes M. B. A1 - Tronicke, Jens T1 - 4D ground-penetrating radar during a plot scale dye tracer experiment JF - Journal of applied geophysics N2 - Flow phenomena in the unsaturated zone are highly variable in time and space. Thus, it is challenging to measure and monitor such processes under field conditions. Here, we present a new setup and interpretation approach for combining a dye tracer experiment with a 4D ground-penetrating radar (GPR) survey. Therefore, we designed a rainfall experiment during which we measured three surface-based 3D GPR surveys using a pair of 500 MHz antennas. Such a survey setup requires accurate acquisition and processing techniquesto extract time-lapse information supporting the interpretation of selected cross-sections photographed after excavating the site. Our results reveal patterns of traveltime changes in the measured GPR data, which are associated with soil moisture changes. As distinct horizons are present at our site, such changes can be quantified and transferred into changes in total soil moisture content. Our soil moisture estimates are similar to the amount of infiltrated water, which confirms our experimental approach and makes us confident for further developing this strategy, especially, with respect to improving the temporal and spatial resolution. (C) 2015 Elsevier B.V. All rights reserved. KW - Ground penetrating radar KW - Time-lapse imaging KW - Brilliant blue Y1 - 2015 U6 - https://doi.org/10.1016/j.jappgeo.2015.04.016 SN - 0926-9851 SN - 1879-1859 VL - 118 SP - 139 EP - 144 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schmelzbach, C. A1 - Scherbaum, Frank A1 - Tronicke, Jens A1 - Dietrich, P. T1 - Bayesian frequency-domain blind deconvolution of ground-penetrating radar data JF - Journal of applied geophysics N2 - Enhancing the resolution and accuracy of surface ground-penetrating radar (GPR) reflection data by inverse filtering to recover a zero-phased band-limited reflectivity image requires a deconvolution technique that takes the mixed-phase character of the embedded wavelet into account. In contrast, standard stochastic deconvolution techniques assume that the wavelet is minimum phase and, hence, often meet with limited success when applied to GPR data. We present a new general-purpose blind deconvolution algorithm for mixed-phase wavelet estimation and deconvolution that (1) uses the parametrization of a mixed-phase wavelet as the convolution of the wavelet's minimum-phase equivalent with a dispersive all-pass filter, (2) includes prior information about the wavelet to be estimated in a Bayesian framework, and (3) relies on the assumption of a sparse reflectivity. Solving the normal equations using the data autocorrelation function provides an inverse filter that optimally removes the minimum-phase equivalent of the wavelet from the data, which leaves traces with a balanced amplitude spectrum but distorted phase. To compensate for the remaining phase errors, we invert in the frequency domain for an all-pass filter thereby taking advantage of the fact that the action of the all-pass filter is exclusively contained in its phase spectrum. A key element of our algorithm and a novelty in blind deconvolution is the inclusion of prior information that allows resolving ambiguities in polarity and timing that cannot be resolved using the sparseness measure alone. We employ a global inversion approach for non-linear optimization to find the all-pass filter phase values for each signal frequency. We tested the robustness and reliability of our algorithm on synthetic data with different wavelets, 1-D reflectivity models of different complexity, varying levels of added noise, and different types of prior information. When applied to realistic synthetic 2-D data and 2-D field data, we obtain images with increased temporal resolution compared to the results of standard processing. KW - Deconvolution KW - Inverse filtering KW - Ground penetrating radar KW - GPR KW - Data processing KW - Vertical resolution Y1 - 2011 U6 - https://doi.org/10.1016/j.jappgeo.2011.08.010 SN - 0926-9851 VL - 75 IS - 4 SP - 615 EP - 630 PB - Elsevier CY - Amsterdam ER -