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  • 1
    Language: English
    In: Journal of Applied Geophysics, July 2012, Vol.82, pp.101-109
    Description: Continuous multi-offset surveys conducted with multi-channel ground-penetrating radar (GPR) systems have already shown their potential for a fast and high-resolution mapping of near-surface soil architecture and volumetric soil water content. Here, we study the accuracy of an 8-channel setup as a function of antenna separation, reflector depth and dielectric permittivity. This is done by Monte Carlo simulations that add noise to the components of the measuring process. We find that adapting the antenna setup to the particular situation is mandatory for an optimal accuracy. In the second step, we demonstrate the applicability and accuracy of our approach with a time-series of real data from a site with two pronounced reflectors. We find that the measured radargrams are highly reproducible and allow to determine reflector depths with an accuracy of about 0.1 m and soil relative dielectric permittivity with an accuracy of about 0.5. With this we quantify the effective field-scale dynamics of soil water for the layers between the ground-surface and the reflectors.
    Keywords: Multi-Channel Ground-Penetrating Radar ; Accuracy ; Field-Scale Soil Water Dynamics ; Hydrology ; Engineering
    ISSN: 0926-9851
    E-ISSN: 1879-1859
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  • 2
    Language: English
    In: GEOPHYSICS, 07/2012, Vol.77(4), pp.H45-H55
    Description: A new inversion scheme for common-offset ground-penetrating radar measurements at multiple antenna separations was proposed, which is intermediate between inverting of picked reflectors using ray-tracing and full-waveform inversion. The measurements are modeled similarly to the real data using 2D finite-difference time-domain simulations. These simulations are obtained with a parameterized model of the subsurface that consists of several layers with constant dielectric permittivity and an explicit representation of the layers' interfaces. Then, reflections in the modeled and in the real data are detected automatically, and the reflections of interest of the real data are selected manually. The sum of squared residuals of the reflections' traveltime and amplitude is iteratively minimized to estimate subsurface water content and geometry, i.e., the position and shape of the layer interfaces. The method was first tested with a synthetic data set and then applied to a real data set. The comparison of the method's result with ground-truth data showed an agreement with the subsurface geometry within plus or minus 5 cm and with the water content, a difference less than plus or minus 2% volume.
    Keywords: Geophysics ; Inversions ; Subsurface Water ; Modelling ; Methodology ; Methods and Instruments ; Legal/Governmental;
    ISSN: 0016-8033
    E-ISSN: 1942-2156
    Source: Society of Exploration Geophysicists (SEG, includes EEGS) (via CrossRef)
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  • 3
    Language: English
    In: Vadose Zone Journal, 2017, Vol.16(10), p.0
    Description: Characterizing the spatial and temporal patterns of soil properties and states such as soil moisture (theta ) remains an important challenge in environmental monitoring. At the Schafertal hillslope site, the spatial patterns of theta measured by a distributed monitoring network and those of apparent electrical conductivity (ECa) measured by electromagnetic induction were characterized based on an integrated monitoring approach, and their possible controlling factors were investigated. With this study, we aimed to quantify the factors controlling the observed spatial patterns of theta and ECa and their interrelation. A principal component analysis was used to identify patterns within a data set comprising theta measured on seven dates within one hydrological year at 40 locations (three depths each) and ECa extracted from spatial maps for the same positions and dates. The first three independent principal components were all important for characterizing the spatial organization of topsoil moisture and its temporal changes. The dominant pattern responded to time-invariant soil attributes such as spatial soil properties and terrain attributes and could explain the spatial organization of ECa only on four of the seven measurement dates. The second and third principal components described the spatial reorganization of the patterns in response to theta dynamics within the soil profile and water removal processes, respectively, and showed distinct time-varying effects on the spatial pattern of theta and ECa. Our results can help with designing field monitoring campaigns and improving modeling approaches by providing insights into the nonstationary control of static and dynamic attributes on the spatial pattern of theta and ECa.
    Keywords: Soils ; Applied Geophysics ; Agriculture ; Apparent Conductivity ; Cambisols ; Case Studies ; Central Europe ; Central Germany ; Depth ; Drainage Basins ; Dynamics ; Electrical Conductivity ; Electromagnetic Methods ; Europe ; Geophysical Methods ; Geostatistics ; Germany ; Gleysols ; Harz Mountains ; Hydrologic Cycle ; Hydrology ; Lower Harz Mountains ; Moisture ; Monitoring ; Patterns ; Principal Components Analysis ; Quantitative Analysis ; Saxony-Anhalt Germany ; Schafertal Basin ; Seasonal Variations ; Slopes ; Soils ; Spatial Distribution ; Spatial Variations ; Statistical Analysis ; Temporal Distribution ; Unsaturated Zone;
    ISSN: Vadose Zone Journal
    E-ISSN: 1539-1663
    Source: CrossRef
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  • 4
    In: Water Resources Research, February 2015, Vol.51(2), pp.861-884
    Description: This paper introduces a hierarchical simulation and modeling framework that allows for inference and validation of the likelihood function in Bayesian inversion of vadose zone hydraulic properties. The likelihood function or its analogs (objective functions and likelihood measures) are commonly assumed to be multivariate Gaussian in form; however, this assumption is not possible to verify without a hierarchical simulation and modeling framework. In this paper, we present the necessary statistical mechanisms for utilizing the hierarchical framework. We apply the hierarchical framework to the inversion of the vadose zone hydraulic properties within a multilayer soil profile conditioned on moisture content observations collected in the uppermost four layers. The key result of our work is that the goodness‐of‐fit validated likelihood function form provides empirical justification for the assumption of multivariate Gaussian likelihood functions in past and future inversions at similar sites. As an alternative, the likelihood function need not be assumed to follow a parametric statistical distribution and can be computed directly using nonparametric methods. The nonparametric methods are considerably more computationally demanding, and to demonstrate this approach, we present a smaller dimension synthetic case study of evaporation from a soil column. The main drawback of our work is the increased computational expense of the inversion. Hierarchical simulation framework for likelihood function validation Multilayer vadose zone parameter uncertainty characterization Statistical representation of parameter heterogeneity
    Keywords: Model Inversion ; Vadose Zone ; Likelihood Function ; Validation
    ISSN: 0043-1397
    E-ISSN: 1944-7973
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  • 5
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  • 6
    Language: English
    In: Vadose Zone Journal, 2015, Vol.14(11), p.0
    Description: We present an efficient method for sampling and spatial estimation of soil moisture at the small catchment scale which is based on terrain data and sparse soil moisture measurements. Accurate characterization of spatial soil moisture patterns and their temporal dynamics is important to infer hydrological fluxes and flow pathways and to improve the description and prediction of hydrological models. Recent advances in ground-based and remote sensing technologies provide new opportunities for temporal information on soil moisture patterns. However, spatial monitoring of soil moisture at the small catchment scale (0.1-1 km2) remains challenging and traditional in situ soil moisture measurements are still indispensable. This paper presents a strategic soil moisture sampling framework for a low-mountain catchment. The objectives were to: (i) find a priori a representative number of measurement locations, (ii) estimate the soil moisture pattern on the measurement date, and (iii) assess the relative importance of topography for explaining soil moisture pattern dynamics. The fuzzy c-means sampling and estimation approach (FCM SEA) was used to identify representative measurement locations for in situ soil moisture measurements. The sampling was based on terrain attributes derived from a digital elevation model (DEM). Five time-domain reflectometry (TDR) measurement campaigns were conducted from April to October 2013. The TDR measurements were used to calibrate the FCM SEA to estimate the soil moisture pattern. For wet conditions the FCM SEA performed better than under intermediate conditions and was able to reproduce a substantial part of the soil moisture pattern. A temporal stability analysis shows a transition between states characterized by a reorganization of the soil moisture pattern. This indicates that, at the investigated site, under wet conditions, topography is a major control that drives water redistribution, whereas for the intermediate state, other factors become increasingly important.
    Keywords: Catchment Area ; Ecological Distribution ; Soils ; Remote Sensing ; Modelling ; Flow ; Remote Sensing ; Elevation ; Catchment Areas ; Moisture Content ; Sampling ; Soil Water ; Monitoring ; Topography ; Sociology ; General ; Clhs, Conditioned Latin Hypercube Sampling ; Dem, Digital Elevation Model ; Fcm, Fuzzy C-Means ; Fcm Sea, Fuzzy C-Means Sampling and Estimation Approach ; Fpi, Fuzzy Performance Index ; Hru, Hydrological Response Unit ; Lop, Lots of Points ; Sld, Soil Landscape Descriptor ; NCE, Normalized Classification Entropy ; Nse, Nash-Sutcliffe Coefficient of Efficiency ; Slu, Soil-Landform Unit ; Srs, Stratified Random Sampling ; Swi, Saga Wetness Index ; Tdr, Time-Domain Reflectometry ; Tir, Total Annual Incoming Solar Radiation ; Ts, Temporal Stability ; Twi, Topographic Wetness Index;
    ISSN: Vadose Zone Journal
    E-ISSN: 1539-1663
    Source: CrossRef
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  • 7
    Language: English
    In: Hydrology and Earth System Sciences, 2017, Vol.21(1), pp.495-513
    Description: Electromagnetic induction#xC2;#xA0;(EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity#xC2;#xA0;(ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture#xC2;#xA0;(#xCE;#xB8;). The major aim of this study was to further investigate the potential of repeated EMI measurements to map#xC2;#xA0;#xCE;#xB8;, with particular focus on the temporal variability of the spatial patterns of ECa and#xC2;#xA0;#xCE;#xB8;. To this end, we compared repeated EMI measurements with high-resolution #xCE;#xB8;#xC2;#xA0;data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and #xCE;#xB8;#xC2;#xA0;dynamics are known. For the investigated site, (i)#xC2;#xA0;ECa showed small temporal variations whereas #xCE;#xB8;#xC2;#xA0;varied from very dry to almost saturation, (ii)#xC2;#xA0;temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of#xC2;#xA0;#xCE;#xB8;, and (iii)#xC2;#xA0;the ECa--#xCE;#xB8; relationship varied with time. Results suggest that (i)#xC2;#xA0;depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii)#xC2;#xA0;for soils with low clay content, the influence of#xC2;#xA0;#xCE;#xB8; on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and#xC2;#xA0;#xCE;#xB8;, and the use of EMI-based ECa data with respect to hydrological applications.
    Keywords: Electromagnetic Radiation – Usage ; Soil Moisture – Measurement;
    ISSN: Hydrology and Earth System Sciences
    ISSN: 10275606
    E-ISSN: 1607-7938
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  • 8
    Language: English
    In: Hydrology and Earth System Sciences Discussions, 03/04/2016, pp.1-28
    ISSN: Hydrology and Earth System Sciences Discussions
    E-ISSN: 1812-2116
    Source: CrossRef
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  • 9
    Language: English
    In: Vadose Zone Journal, 2017, Vol.16(10), p.0
    Description: Detailed information on the temporal and spatial evolution of soil moisture patterns is of fundamental importance to improve runoff prediction, optimize irrigation management and to enhance crop forecasting. However, obtaining representative soil moisture measurements at the catchment scale is challenging because of the dynamic spatial and temporal behavior of soil moisture. High-resolution remote sensing data provide detailed spatial information about catchment characteristics (e.g., terrain and land use) that can be used as proxies to estimate soil moisture. We assessed the potential use of combined multitemporal multispectral remote sensing (RS) and terrain data for estimating spatial soil moisture patterns at the small catchment scale. The fuzzy c-means sampling and estimation approach (FCM SEA) was applied to conduct a sensor (proxy) directed (guided) sampling and to reconstruct multitemporal soil moisture patterns based on time domain reflectometry measurements. A comprehensive soil moisture database for the Schafertal catchment, located in central Germany, was used to test, validate, and compare the FCM SEA performances of the combined remote sensing data with those of a benchmark approach driven solely by terrain data. Results from the study show that a FCM SEA model that integrates bi-temporal RS imagery and terrain data was more effective in estimating spatial soil moisture patterns relative to the benchmark model. It outperformed the benchmark model in 58% of the cases and was stable to explain about 50% of the total observed variance for a range of different catchment moisture conditions. This was achieved with only a small sample size (n = 30). The results of this study are promising because they highlight the importance of considering multitemporal RS and terrain data and demonstrate how in situ sensors can be optimally placed to enable cost-efficient monitoring and prediction of spatial soil moisture patterns at the small catchment scale.
    Keywords: Applied Geophysics ; Soils ; Agriculture ; Central Europe ; Central Germany ; Digital Terrain Models ; Drainage Basins ; Europe ; Fuzzy C-Means Analysis ; Fuzzy Logic ; Germany ; Imagery ; In Situ ; Laser Methods ; Lidar Methods ; Lower Harz Mountains ; Moisture ; Monitoring ; Multispectral Analysis ; Principal Components Analysis ; Rapideye ; Reflection ; Remote Sensing ; Sampling ; Satellite Methods ; Saxony-Anhalt Germany ; Schafertal Basin ; Size ; Soils ; Spatial Distribution ; Statistical Analysis ; Tdr Data ; Tereno ; Vegetation;
    ISSN: Vadose Zone Journal
    E-ISSN: 1539-1663
    Source: CrossRef
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  • 10
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