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Subsurface heterogeneity in hydraulic properties and processes is a fundamental challenge in hydrogeology. We have developed an improved method of borehole dilution testing for hydrostratigraphic characterization, in which distributed temperature sensing (DTS) is used to monitor advective heat movement. DTS offers many advantages over conventional technologies including response times in the order of seconds rather than minutes, the ability to profile temperature synoptically in a well without disturbing the fluid column, sensitivity to a wider range of flow rates than conventional spinner and heat pulse flow meters, and the ease of interpretation. Open-well thermal dilution tests in two multiaquifer wells near Madison, Wisconsin, provided detailed information on the borehole flow regimes, including flow rates and the locations of inflows from both fractures and porous media. The results led to an enhanced understanding of flow in a hydrostratigraphic unit previously conceptualized as homogenous and isotropic.

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Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty assessment accounting for prior understanding and what is learned through model development and data assimilation. Model construction and data assimilation are time consuming and prone to errors, which motivates a repeatable workflow where revisions resulting from new interpretations or discovery of errors can be addressed and the analyses repeated efficiently and rigorously. In this work, motivated by the real world application of delineating risk-based (probabilistic) sources of water to supply wells in a humid temperate climate, a scripted workflow was generated for groundwater model construction, data assimilation, particle-tracking and post-processing. The workflow leverages existing datasets describing hydrogeology, hydrography, water use, recharge, and lateral boundaries. These specific data are available in the United States but the tools can be applied to similar datasets worldwide. The workflow builds the model, performs ensemble-based history matching, and uses a posterior Monte Carlo approach to provide probabilistic capture zones describing source water to wells in a risk-based framework. The water managers can then select areas of varying levels of protection based on their tolerance for risk of potential wrongness of the underlying models. All the tools in this workflow are open-source and free, which facilitates testing of this repeatable and transparent approach to other environmental problems.

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