Forschungszentrum Landschaftsentwicklung und Bergbaulandschaften (FZLB)
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Low frequency loop-loop electromagnetic induction (EMI) is widely used for monitoring soil electrical conductivity and water content. As a non-invasive geophysical technique, EMI allows for rapid and real-time electrical conductivity measurements. However, EMI has not yet been used much to back out the vertical (depth profile) conductivity structure due to problems with the inversion of measured apparent electrical conductivity (ECa) data. In this study, we used Bayesian inference with the MT-DREAM(ZS) algorithm to infer the electrical conductivity layering of the subsurface from EMI data.We test and evaluate our methodology using apparent electrical conductivity data measured along two transects in the Hühnerwasser catchment in Lusatia, Germany. These measurements were made using CMD-Explorer, a multi-configuration sensor with three inter-coil spacings and two antenna orientations. Three offsets and two antenna modes lead to six measurement depths. Electrical Resistivity Tomography (ERT) measurements were also carried out to provide reference conductivity values and to calibrate the EMI data. Such calibration is necessary for quantitative interpretation of the ECa values and to enable multi-layered inversion. The Discrete Cosine Transform (DCT) was used to reduce the number of unknown parameters, and different likelihood functions were used to evaluate the sensitivity of the posterior parameter distribution to residual assumptions. DCT-based inversion equates to a quasi-two-dimensional framework which incorporates all data along the profile and results in a low-dimensional over-determined optimization problem. Results demonstrated that although appropriate selection of the low frequency DCT coefficients is important, the definition of the likelihood function plays a crucial role in the estimation of parameter and predictive uncertainty. The use of a Gaussian likelihood function introduces artifacts in DCT-based inversion of EMI data. The use of a more flexible likelihood function results in more accurate results of the DCT-inversion. Integration of the DCT with the MT-DREAM(ZS) algorithm and a flexible generalized likelihood function appears promising for the inversion of low frequency loop-loop EMI data. The proposed approach promises accurate and high resolution estimation of subsurface hydrogeophysical properties from EMI data.
Potential field methods produce anomaly maps with different magnitudes and depths that are typically contaminated by noise, making them hard to interpret. In order to highlight edges of the anomalies with different depths and magnitudes, data filtering techniques have received a great attention, in particular for mineral explorations. Filtering approaches render to explore more details from potential field data maps. In this respect, high pass filters are commonly used for enhancing the anomaly edges all of which utilize gradients of the potential field. In order to apply different filters on the potential field data, major attempts have been made to make a balance between noise and the signal obtained from a filtered image (Cooper & Cowan, 2006).
High-Resolution Soil Electrical Conductivity Imaging from EMI D Based Probabilistic Inversion
(2018)
Electromagnetic induction (EMI) sensors allow for non-invasive soil characterizations. Proximal soil sensing using EMI hindered due to the problems related to the inversion of apparent electrical conductivity (ECa) data. In this study, I used Bayesian inference to obtain the electrical conductivity layering of the subsurface from multi-configuration EMI data. In this respect, generalized formal likelihood function was used to more accurately describe the sensitivity of the posterior parameter distribution to residual assumptions. Discrete Cosine Transform (DCT) was employed as a model compression technique to reduce the number of unknown parameters in the inversion. I considered apparent electrical conductivity pseudosection as a training image (TI) in multiple-point statistical simulations. Information from TI realizations were utilized to determine dominant DCT coefficients, as well as prior probability density functions for the subsequent probabilistic inversions. The potentiality of the proposed approach was examined through an experimental scenario. The results demonstrated that this methodology allows for soil electrical conductivity imaging with high resolution. This strategy permits to incorporate summary metrics from ensemble of ECa pseudosection realizations in the inversion without resorting to any complimentary source of information. The proposed approach ensures accurate and high resolution characterization of soil conductivity layering from measured ECa values.
The spatial variability of soil physical properties on the landscape scale is often increased by anthropogenic land occupation, not only by current land use but also through the legacies of past land use systems. The remains of historic charcoal hearts are an example for such a disturbance of the soil landscape by former forestry. Such relict charcoal hearths (RCH) exhibit a clearly altered soil stratigraphy, most prominently characterized by a technogenic substrate layer on the soil surface, and their soil physical properties can considerably differ from those of surrounding forest soils. The aim of our study is to characterize the soil water and temperature regime on RHC in a pre-industrial charcoal production area in Brandenburg, Germany, as compared with the surrounding sandy forest soils. Soil properties were analyzed in profiles on and around hearth sites and are monitored in a sensor transect equipped with soil
moisture sensors and pF-meters. Results of soil sample analyses show differences in density and porosity between the RCH soils and surrounding forest soils, not only in the technogenic layer but also in the buried soil layers on hearth sites. The soil water characteristic curves determined in the laboratory indicate a modified pore size distribution and lower plant available water contents in the RCH soils. Preliminary results of the ongoing soil water monitoring, however, show increased soil wetness in the RCH soils, along with lower soil moisture tensions. Furthermore, the measurements show higher variations of soil temperature in RCH soils. The results affirm that the legacies of historic charcoal production can increase the spatial variability of soil physical properties and therefore also of ecological site conditions in forest areas. The results of soil moisture monitoring suggest that a determination of soil physical parameters in the laboratory is not sufficient to characterize the spatio-temporal variations of the soil water regime.
Experimental catchments with well-known boundaries and characteristics may contribute valuable data to hydrological, critical zone and landscape evolution research. One of the most well-established and largest constructed catchments is the Chicken Creek catchment (6 ha area including a 0.4 ha pond, Brandenburg, Germany) representing an initial ecosystem undergoing a highly dynamic ecological development starting from clearly defined starting conditions. The water balance dynamics of the catchment was calculated using a simple mass balance approach to reveal the impact of ecological development during 12 years. Water storage in the catchment was calculated from a 3D-model of groundwater volumes, soil moisture measurements and water level recordings of the pond. The catchment water balance equation was resolved for evapotranspiration, the only part that was not measured directly. Due to the known boundary conditions and the inner structure of the catchment, we were able to quantify the different storage compartments and their role in hydrologic response. Our results indicate that for small catchments with a highly dynamic ecological development like the Chicken Creek, the knowledge about saturated and unsaturated storage volumes enables a good estimate and closure of the water balance using a rather simple approach, at least in annual resolution. We found a significant relationship between vegetation cover in the catchment and calculated ET. Time series of meteorological, hydrological, soil and vegetation data over 12 years enabled us to characterize the transient development of the catchment and to evaluate the effect of different feedback mechanisms on catchment hydrology. The dataset from the Chicken Creek catchment indicate at least three phases in ecosystem development, where initial abiotic feedbacks (e.g. erosion) were followed by more and
more biotic controls (e.g. biological soil crusts, vegetation succession and growth). Data from Chicken Creek in high spatial and temporal resolution provide a valuable database underlining the high importance of abiotic/biotic feedback effects that change the hydrologic functioning and response of the catchment more than the water balance itself revealed and thus have to be included in catchment models.
An artificial catchment was constructed to study initial soil and ecosystem development. Our research site is the hydrologic catchment area “Chicken Creek”, 20 km south of the city Cottbus (Germany), which is left to undirected succession. The approximately 6-ha catchment area was built in 2005 of coarse-textured quaternary sediments and forms a back- and foot-slope that flattens out to a pond. A clay liner, 2-3 m in thickness, seals the catchment at the bottom. The initial “soil” layer consists of sandy quaternary sediments, approximately 2–3 m in thickness, that overlay the clay liner. The sediments of the artificial system are in the very initial stage of soil formation. As a key process, the pore structure dynamics in the soil at the surface strongly influences erosion, infiltration, matter dynamics, and vegetation establishment. Little is known, however, about early macropore formation. This presentation focuses on observations of the general development of the catchment, with emphasis on soil structure modifications, such as soil surface crusts, structure formation from ground beetles, moss vegetation and its effect on water flow.
We visualized the soil structure and flow patterns using a combination of neutron radiography, neutron tomography (NT) and X-ray computed tomography (CT) experiments. All techniques were used to describe preferential pathways as a soil
structure with CT and the process of preferential flow of water with NT. For the first time, neutron radiation was applied on undisturbed soil cores to visualize water distributions in natural soils on three examples containing heterogeneities of different origin. Our observations demonstrate relatively high abiotic and biotic dynamics of soil pore structure in the soil surface even during the very early development stages of the catchment. The structure formation influences runoff and infiltration by forming sealing layers or preferential flow paths, due to biotic activity.
Eine zunehmende Knappheit ackerbaulicher Standorte und der zugleich steigende Bedarf an nachwachsenden Rohstoffen für die energetische und stoffliche Nutzung lösen verstärkt Konflikte zwischen der Nahrungsmittelproduktion und der Biomasseproduktion aus. Marginale Standorte kommen entsprechend immer stärker in den Blickpunkt als mögliche Erweiterungsflächen für die Biomasseproduktion. In der wissenschaftlichen Auseinandersetzung fehlt allerdings eine eindeutige Definition für derartige marginale Standorte. Gerade im Hinblick auf eine mögliche Reduzierung von Nutzungskonflikten ist die Abgrenzung zu stillgelegten, aber agrarisch nutzbaren Standorten oder zu natürlichen Badlands, mit naturschutzfachlichen Potentialen oftmals schwierig. Das EU H2020-Projekt SEEMLA untersucht Potentiale und Verfügbarkeit von marginalen Standorten europaweit. In Deutschland, Griechenland und der Ukraine wurden Pilotstandorte eingerichtet, auf denen der Anbau von Bioenergiepflanzen exemplarisch durchgeführt wird. Für eine erste Bewertung der Standortspotentiale und auch der Ursachen der Marginalität der Standorte wurden Bodenuntersuchungen an allen Pilotstandorten nach den Vorgaben des Muencheberger Soil Quality Rating-Verfahrens (SQR) (1) durchgeführt und die Standorte klassifiziert. Das SQR-Verfahren bewertet ausgewählte Boden- und Standortseigenschaften und bezieht zusätzlich mögliche limitierende Faktoren (Hazard Indicators) wie Versauerung, Versalzung, Vernässung etc. mit ein, um eine Gesamtbewertungszahl zur Bodenfruchtbarkeit zu ermitteln. Dieser Beitrag stellt anhand der SEEMLA-Standorte exemplarisch Böden marginaler Standorte vor. Mit Hilfe der SQR Hazard Indicators werden charakteristische limitierende Faktoren vorgestellt. Es wird zudem versucht, die untersuchten Standorte in eine mögliche Klassifikation marginaler Standorte einzupassen und ihre Eignung für die Biomasseproduktion einzuschätzen.
Der Lehrstuhl Bodenschutz und Rekultivierung der Brandenburgischen Technischen Universität Cottbus-Senftenberg (BTU CS) ist Projektpartner in dem von der Europäischen Union im Rahmen des Programms Horizon 2020 geförderten Forschungsprojekts SEEMLA → „Sustainable exploitation of biomass for bioenergy from marginal lands in Europe“ → „Nachhaltige Nutzung von Biomasse für Bioenergie von marginalen Standorten in Europa“. Übergeordnetes Ziel des Projektes ist die Ermittlung des Biomassepotenzials, das auf marginalen Standorten innerhalb von Europa nachhaltig produziert und energetisch verwertet werden kann. Die BTU CS hat in diesem Kontext Untersuchungen zur Bewertung der Marginalität von potenziellen Biomasse-Produktionsstandorten in Deutschland, Griechenland und der Ukraine durchgeführt. Zu diesem Zweck wurde das Müncheberger Soil-Quality-Rating System (SQR) (Müller et al. 2007) eingesetzt.