Defining Hydrogeological Site Similarity with Hierarchical Agglomerative Clustering.

Hydrogeological information about an aquifer is difficult and costly to obtain, yet essential for the efficient management of groundwater resources. Transferring information from sampled sites to a specific site of interest can provide information when site-specific data is lacking. Central to this approach is the notion of site similarity, which is necessary for determining relevant sites to include in the data transfer process. In this paper, we present a data-driven method for defining site similarity. We apply this method to selecting groups of similar sites from which to derive prior distributions for the Bayesian estimation of hydraulic conductivity measurements at sites of interest. We conclude that there is now a unique opportunity to combine hydrogeological expertise with data-driven methods to improve the predictive ability of stochastic hydrogeological models.

ogs5py: A Python-API for the OpenGeoSys 5 Scientific Modeling Package.

High-performance numerical codes are an indispensable tool for hydrogeologists when modeling subsurface flow and transport systems. But as they are written in compiled languages, like C/C++ or Fortran, established software packages are rarely user-friendly, limiting a wider adoption of such tools. OpenGeoSys (OGS), an open-source, finite-element solver for thermo-hydro-mechanical-chemical processes in porous and fractured media, is no exception. Graphical user interfaces may increase usability, but do so at a dramatic reduction of flexibility and are difficult or impossible to integrate into a larger workflow. Python offers an optimal trade-off between these goals by providing a highly flexible, yet comparatively user-friendly environment for software applications. Hence, we introduce ogs5py, a Python-API for the OpenGeoSys 5 scientific modeling package. It provides a fully Python-based representation of an OGS project, a large array of convenience functions for users to interact with OGS and connects OGS to the scientific and computational environment of Python.

Estimating pathway-specific contributions to biodegradation in aquifers based on dual isotope analysis: theoretical analysis and reactive transport simulations.

At field sites with varying redox conditions, different redox-specific microbial degradation pathways contribute to total contaminant degradation. The identification of pathway-specific contributions to total contaminant removal is of high practical relevance, yet difficult to achieve with current methods. Current stable-isotope-fractionation-based techniques focus on the identification of dominant biodegradation pathways under constant environmental conditions. We present an approach based on dual stable isotope data to estimate the individual contributions of two redox-specific pathways. We apply this approach to carbon and hydrogen isotope data obtained from reactive transport simulations of an organic contaminant plume in a two-dimensional aquifer cross section to test the applicability of the method. To take aspects typically encountered at field sites into account, additional simulations addressed the effects of transverse mixing, diffusion-induced stable-isotope fractionation, heterogeneities in the flow field, and mixing in sampling wells on isotope-based estimates for aerobic and anaerobic pathway contributions to total contaminant biodegradation. Results confirm the general applicability of the presented estimation method which is most accurate along the plume core and less accurate towards the fringe where flow paths receive contaminant mass and associated isotope signatures from the core by transverse dispersion. The presented method complements the stable-isotope-fractionation-based analysis toolbox. At field sites with varying redox conditions, it provides a means to identify the relative importance of individual, redox-specific degradation pathways.

Linear exchange model for the description of mass transfer limited bioavailability at the pore scale.

Reactive transport simulations are a common approach for the quantitative assessment of contaminant biodegradation in the subsurface. To use knowledge on microbial kinetics for the simulation of in situ biodegradation, the mass transfer processes controlling the bioavailability of the contaminants need to be described appropriately. A common approach to account for this problem is using a linear exchange model controlling the link between bulk and bioavailable concentration. Assuming that the subsequent degradation is controlled by the bioavailable concentration, only, these two steps can be combined to an analytical expression for the overall reaction rate know as the Best-Equation. In our work, we evaluate this approach for its ability to describe biodegradation kinetics limited by pore-scale mass transfer. Results from explicit numerical and analytical simulations of mass transport and reactive consumption at the pore scale are used to test the accuracy of results obtained using the Best-Equation. Our analysis shows that strictly spoken the Best-Equation is not valid. However, a good approximation can be achieved with errors of less than 6% in cases of moderate bioavailability and much lower errors in cases of either low or high bioavailability. These results support the description of mass transfer processes used in many reactive transport models. Furthermore, we present a method to obtain an accurate estimate of the unknown rate parameter controlling the diffusive mass transfer processes at the pore scale.