Abstract
AbstractThe extraction of groundwater for drinking water purposes is one of the most important uses of the natural subsurface. Sustainable management of groundwater resources requires detailed knowledge of the hydraulic properties within the subsurface. Typically, these properties are not directly accessible. The evaluation of hydraulic properties therefore requires hydraulic stimuli of the subsurface (e.g., injection and extraction of groundwater, tracer tests, etc.) with subsequent data analysis. In this context, tomographic techniques and inversion strategies originally derived for geophysical surveying can be transferred to hydraulic applications. In addition, geophysical techniques may be used to monitor hydraulic tests. The latter requires fully coupled hydrogeophysical inversion strategies, accounting for the entire process chain from hydraulic properties via flow and transport to the application of the geophysical surveying techniques. The project “Tomographic methods in hydrogeology” focuses on the development of a geostatistical inversion method for transient tomographic data of multiple hydraulic investigation techniques, the model-based optimal design of tomographic surveys, and the development of experimental techniques and equipment for an efficient execution of tomographic surveys in a hydrogeological context using the model-based design and providing data for the inversion. In this chapter we will show selected examples of the project’s outcome. The examples include developments related to the joint geostatistical inversion of tomographic data sets, its efficient parallelization, and its application to a 3D-inversion of tomographic thermal tracer tests. Furthermore we present a method for solving the inversion of transient tomographic data sets which usually suffer from high computational efforts. Related to the acquisition of tomographic data sets, we also discuss the development of tracer-tomographic methods using heat as tracer.KeywordsHydraulic ConductivityHydraulic HeadDomain DecompositionObservation WellTracer TestThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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