The inversion of geoelectric data is nonunique. Therefore, electric resistivity tomography (ERT) usually results in different subsurface models that fit observed apparent resistivity values equally well. To reduce the uncertainty, constraints on the geometry and resistivity of subsurface structures can be incorporated into the ERT inversion. We test different ways of constraining ERT by applying (1) improved starting models, (2) structural constraints, and (3) structural and resistivity constraints. A priori information is needed for these approaches, which is acquired from direct push electrical conductivity (DP-EC) logs and vibracores in our study. We found that adapting high vertical resolution of DP-EC logs to coarser ERT resolution requires blocking of the logs. These blocked logs can be used for constraining the ERT inversion with resistivity and structural constraints along so-called regions around the log locations, which was found to be the best approach. In this case, ground truthing with additional DP-EC logs that were not used for constraining showed the lowest root-mean-square error between logs and ERT model.

Hyperbolic diffractions in Ground Penetrating Radar (GPR) data are caused by a variety of subsurface objects such as pipes, stones, or archaeological artifacts. Supplementary to their location, the propagation velocity of electromagnetic waves in the subsurface can be derived. In recent years, it was shown that deep learning tools can automatically detect hyperbola in radargrams using data measured over urban infrastructure, which are relatively clear. In contrast, in this study, we used an archaeological dataset with diverse underground structures. In the first step we used the deep learning network RetinaNet to detect hyperbola automatically and achieved an average precision of 0.58. In the next step, 10 different approaches for hyperbola fitting and thus velocity determination were applied. The derived information was validated with manually determined velocities and apex points. It was shown that hyperbola extraction by using a threshold and a column connection clustering (C3) algorithm followed by simple hyperbola fitting is the best method, which had a mean velocity error of 0.021 m/ns compared to manual determination. The average 1D velocity-depth distribution derived in 10 ns intervals was in shape comparable to the manually determined one, but had a systematic shift of about 0.01 m/ns towards higher velocities.

We present a case study of a bog showing how an integrated approach of multi-method geophysical sounding and local soil sampling can be used to identify, differentiate, and map organic sediments. Our study is based on ground-penetrating radar (GPR), electrical resistivity tomography (ERT) and shear-wave seismic (SH seismic) profiling applied to sediments of the former Lake Duvensee (northern Germany), nowadays a bog. This is a well-known locality for remains from the Mesolithic hunter-gatherers’ occupation that has been attracting archaeological and geoarchaeological research for100 years. The bog is embedded in low conductive glacial sand and is characterized by layers of different gyttja sediments (detritus and calcareous). The present study was conducted in order to identify the bog morphology and the thickness of the peat body and lake sediments, in order to understand the basin evolution. To validate the geophysical results, derived from surface measurements, drilling, soil analyses as well as borehole guided wave analysis of electromagnetic waves and Direct-Push (DP-EC) have been carried out and used for comparison. It turned out that each method can distinguish between sediments that differ in grain size, particularly between peat, lake sediments (gyttjas and mud) and basal glacial sand deposits. GPR is even able to separate between strongly and weakly decomposed peat layers, which is also clear considering resistivity variations in the ERT computation. From the association between geophysical properties and sediment analysis (e.g., water content and organic matter) different gyttjas were distinguished (coarse and fine) and seismic velocity was correlated to bulk density. Moreover, GPR and SH-wave seismics present different resolutions, confirming that the latter allows measurements, which are more focused on determining the extension of basal sand deposits, the depth of which is difficult to reach with GPR. Representative values of electrical resistivity, dielectric permittivity, and shear wave velocity have been determined for each sediment type and are therefore available to complete the investigation of wetland environments. Fine grained lake sediments were difficult to differentiate by the applied methods. This could be a result of high ionic concentration within the permanent groundwater body, partly masking the sediment properties.

In this study, we investigate GPR measurements in freshwater of less than 5 m at four different locations to derive rules of thumb in terms of depth penetration, resolution, and material contrasts of the method for 200 and 400 MHz antennas under field conditions. The objective is to improve the attractiveness of the method for archaeological issues in water, as there are hardly any studies on this subject so far. The depth penetration of 2–4 m is negligibly influenced by the choice of the 200 or 400 MHz antenna. Organic material in the water column also does not affect the water depth but offers new fields of applications for mapping and volume estimation of biomass in lakes with GPR. The horizontal resolution in the cm range in the direction of the profile and in the dm range across the profile could not be improved by the narrow antenna radiation pattern of 0.1 for materials of <80% porosity to the water column and for materials of 45% porosity to water-saturated sand. Large reflection coefficients also show, for example, granite to sand and gyttja to wood. The water column has a considerable effect on the data quality of the 400 MHz antenna from a depth of 2 m due to the antenna ringing. Furthermore, multiples must be expected in a water column <0.5 m. The method can especially complement the common geophysical methods of seismics and geoelectrics to exclude material ambiguities. The major advantage is the simple setting of the land equipment in the water.

This study presents the results of a marine geophysical survey performed in the Igaliku fjord in southern Greenland in order to understand the harbour setting of the former Norse settlement Garðar (modern Igaliku). The aims of the survey were (a) to reconstruct the former coastline during the first centuries of the Norse settlement period (c. 11/12th centuries) and (b) to search for archaeological remains on the seabed connected to maritime traffic and trade. In order to approach these goals, we used an integrated marine survey system consisting of a side-scan sonar and a reflection seismic system. The system was designed for lightweight transport, allowing measurements in areas that are logistically difficult to access. The side-scan sonar data revealed no remains of clear archaeological origin. Bathymetric data from seismic seabed reflection and additional Differential GPS height measurements yielded a high-resolution bathymetric map. Based on estimates of Holocene relative sea level change, our bathymetry model was used to reconstruct the shift of the high and low-water line since the early Norse period. The reconstructed coastline shows that a small island, which hosts the ruins of a tentative Norse warehouse at the mouth of the present harbour, was connected to the shore at low tide during the early Norse period. In addition, reflection seismics and side-scan sonar images reveal a sheltered inlet with steep slopes on one side of the island, which may have functioned as a landing bridge used to load ships. We also show that the loss of fertile land due to sea level rise until the end of the Norse settlement was insignificant compared to the available fertile land in the Igaliku fjord and is thus not the reason for the collapse of the colony.

We investigate how suitable ground penetrating radar (GPR) and geoelectrics are to prospect the remains of submerged wooden archaeological constructions in the water column. For this purpose, we determined the contrasts of electric resistivity and dielectric permittivity from measurements on present-day wood samples, serving as simplified approximations of water saturated and undegraded archaeological wood. As common substitutes of hard and soft construction wood, we investigated oak and spruce wood. The electric resistivity and dielectric permittivity were determined with increasing moisture content from small-scale electric and GPR measurements using a Wenner alpha array and a 2 GHz Palm antenna in a watering experiment. In a water-saturated state, resistivity values of 20 were observed. The anisotropy effects and deviations of the wood species were seen to be up to 30%. On the basis of this, the relative material contrasts of wood with respect to fresh water, sand, and clay were calculatedand compared to values found in the literature for seismic contrasts. Geoelectric, GPR, and seismic measurements show contrasts of 0.3 to 0.8, −0.4 to 0.2, and −0.24 to 0.35, depending on the surrounding material and structural orientation of the wood. The highest contrasts were found for wood in fresh water, followed by clayey and sandy subsoils. On the basis of the determined contrasts, analytical calculations were performed showing that an object of 0.5 m diameter can be detected at depths between 0.5 m and 1.5 m with geoelectrics (Schlumberger) and at depths between 0.5 m and 3 m with ground penetrating radar measurements (400 MHz).