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  • Malden, US  (2)
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  • 1
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    ogs5py: A Python‐API for the OpenGeoSys 5 Scientific Modeling Package (2021)
    Blackwell Publishing Ltd | Malden, US
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    Publication Date: 2021-07-04
    Description: 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.
    Description: German Federal Environmental Foundation http://dx.doi.org/10.13039/100007636
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: 551.49 ; hydrogeology ; subsurface flow ; modeling ; software
    Type: article
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    CITATION GEO-LEO
  • 2
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    How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy (2021)
    Blackwell Publishing Ltd | Malden, US
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    Publication Date: 2022-04-01
    Description: We present a workflow to estimate geostatistical aquifer parameters from pumping test data using the Python package welltestpy. The procedure of pumping test analysis is exemplified for two data sets from the Horkheimer Insel site and from the Lauswiesen site, Germany. The analysis is based on a semi‐analytical drawdown solution from the upscaling approach Radial Coarse Graining, which enables to infer log‐transmissivity variance and horizontal correlation length, beside mean transmissivity, and storativity, from pumping test data. We estimate these parameters of aquifer heterogeneity from type‐curve analysis and determine their sensitivity. This procedure, implemented in welltestpy, is a template for analyzing any pumping test. It goes beyond the possibilities of standard methods, for example, based on Theis' equation, which are limited to mean transmissivity and storativity. A sensitivity study showed the impact of observation well positions on the parameter estimation quality. The insights of this study help to optimize future test setups for geostatistical aquifer analysis and provides guidance for investigating pumping tests with regard to aquifer statistics using the open‐source software package welltestpy.
    Description: Article impact statement: We present a workflow to infer parameters of subsurface heterogeneity from pumping test data exemplified at two sites using welltestpy.
    Description: German Federal Environmental Foundation (DBU) http://dx.doi.org/10.13039/100007636
    Keywords: ddc:551.49
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
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