SciKit-GStat Uncertainty: A software extension to cope with uncertain geostatistical estimates

This study is focused on an extension of a well established geostatistical software to enable one to effectively and interac-tively cope with uncertainty in geostatistical applications. The extension includes a rich component library, pre-built inter-faces and an online application. We discuss the concept of replacing the empirical variogram with its uncertainty bound. This enables one to acknowledge uncertainties characterizing the underlying geostatistical datasets and typical methodolog-ical approaches. This allows for a probabilistic description of the variogram and its parameters at the same time. Our ap-proach enables (1) multiple interpretations of a sample and (2) a multi-model context for geostatistical applications. We focus the sample application on propagating observation uncertainties into manual variogram parametrization and analyze its effects. Using two different datasets, we show how insights on uncertainty can be used to reject variogram models, thus constraining the space of formally equally probable models to tackle the issue of parameter equifinality. (c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Automated summary

This study focuses on extending geostatistical software to effectively cope with uncertainty in geostatistical applications. The extension includes a rich component library, pre-built interfaces and an online application. The study discusses replacing the empirical variogram with its uncertainty bound to acknowledge underlying uncertainties and allows for a probabilistic description of the variogram and its parameters. The approach enables multiple interpretations of a sample and a multi-model context for geostatistical applications.