3D modeling of groundpenetrating radar data across a realistic sedimentary model Abstract   Groundpenetrating radar (GPR) is an established geophysical tool to explore a wide range of nearsurface environments. Today, the use of synthetic GPR data is largely limited to 2D because 3D modeling is computationally more expensive. In fact, only recent developments of modeling tools and powerful hardware allow for a timeefficient computation of extensive 3D data sets. Thus, 3D subsurface models and resulting GPR data sets, which are of great interest to develop and evaluate novel approaches in data analysis and interpretation, have not been made publicly available up to now.  We use a published hydrofacies data set of an aquiferanalog study within fluvioglacial deposits to infer a realistic 3D porosity model showing heterogeneities at multiple spatial scales. Assuming freshwater saturated sediments, we generate synthetic 3D GPR data across this model using novel GPUacceleration included in the opensource software gprMax. We present a numerical approach to examine 3D wavepropagation effects in modeled GPR data. Using the results of this examination study, we conduct a spatial model decomposition to enable a computationally efficient 3D simulation of a typical GPR reflection data set across the entire model surface. We process the resulting GPR data set using a standard 3D structural imaging sequence and compare the results to selected input data to demonstrate the feasibility and potential of the presented modeling studies. We conclude on conceivable applications of our 3D GPR reflection data set and the underlying porosity model, which are both publicly available and, thus, can support future methodological developments in GPR and other nearsurface geophysical techniques.

ResIPy, an intuitive open source software for complex geoelectrical inversionmodeling Abstract   Electrical resistivity tomography (ERT) and induced polarization (IP) methods are now widely used in many interdisciplinary projects. Although field surveys using these methods are relatively straightforward, ERT and IP data require the application of inverse methods prior to any interpretation. Several established noncommercial inversion codes exist, but they typically require advanced knowledge to use effectively. ResIPy was developed to provide a more intuitive, userfriendly, approach to inversion of geoelectrical data, using an open source graphical user interface (GUI) and a Python application programming interface (API). ResIPy utilizes the mature R2cR2 inversion codes for ERT and IP, respectively. The ResIPy GUI facilitates data importing, data filtering, error modeling, mesh generation, data inversion and plotting of inverse models. Furthermore, the easy to use design of ResIPy and the help provided inside makes it an effective educational tool. This paper highlights the rationale and structure behind the interface, before demonstrating its capabilities in a range of environmental problems. Specifically, we demonstrate the ease at which ResIPy deals with topography, advanced data processing, the ability to fix and constrain regions of known geoelectrical properties, timelapse analysis and the capability for forward modeling and survey design.