Probabilistic Evaluation of Geoscientific Hypotheses with Geophysical Data: Application to Electrical Resistivity Imaging of a Fractured Bedrock Zone

Miltenberger, Alex; Uhlemann, Sebastian; Mukerji, Tapan; Williams, Kenneth H; Dafflon, Baptiste; Wang, Lijing; Murakami-Wainwright, Haruko

doi:10.1029/2021JB021767

Probabilistic Evaluation of Geoscientific Hypotheses with Geophysical Data: Application to Electrical Resistivity Imaging of a Fractured Bedrock Zone

Journal Article · Thu Aug 26 00:00:00 EDT 2021 · Journal of Geophysical Research. Solid Earth

DOI:https://doi.org/10.1029/2021JB021767· OSTI ID:1819015

^[1]; ^[2]; Mukerji, Tapan ^[3]; ^[2]; ^[2]; ^[3]; ^[2]

Stanford Univ., CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stanford University, Department of Geophysics
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Stanford Univ., CA (United States)

As climate changes and populations grow, groundwater sustainability is becoming increasingly important. Groundwater models, based on a conceptual understanding of the subsurface structure, are crucial tools for making sustainable management decisions. Conceptual models of the subsurface are based on knowledge of geological processes, and, frequently, observations from geophysical data. A frequent problem in groundwater model development occurs when multiple geological phenomena could explain a single subsurface observation. Uncertainty in geophysical data makes it even more difficult to discern which explanations are consistent with the geophysics. Here, we present a framework for testing geological when a geological feature is observed in geophysical data, but its physical characteristics are uncertain. The framework builds on Popper-Bayes methods developed in previous work, and is applied to study a fractured bedrock zone in a mountainous watershed in southwest Colorado. First, we outline six hypotheses based on the geological history of the watershed. Then, using the proposed Popper-Bayes approach, we demonstrate that three of the six hypotheses are inconsistent with measured electrical resistivity data, even after accounting for uncertainty. Finally, we discuss the importance of the prior model, and how this framework for handling geophysical uncertainty can be applied in other settings.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1819015

Alternate ID(s):: OSTI ID: 1823175

Journal Information:: Journal of Geophysical Research. Solid Earth, Journal Name: Journal of Geophysical Research. Solid Earth Vol. 126; ISSN 2169-9313

Publisher:: American Geophysical UnionCopyright Statement

Country of Publication:: United States

Language:: English

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