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\begin{document}

\title{Characterizing Offshore Freshened Groundwater Salinity Patterns using
Trans-dimensional Bayesian Inversion of Controlled Source
Electromagnetic Data: A Case Study from the Canterbury Bight, New
Zealand}



\author[1]{Zahra Faghih}%
\author[2]{Amir Haroon}%
\author[2]{Marion Jegen}%
\author[3]{Romina Gehrmann}%
\author[4]{Katrin Schwalenberg}%
\author[5]{Aaron Micallef}%
\author[6]{Jan Dettmer}%
\author[7]{Christian Berndt}%
\author[8]{Joshu J Joseph Mountjoy}%
\author[9]{Bradley A. Weymer}%
\affil[1]{GEOMAR Helmholtz Centre for Ocean Research}%
\affil[2]{GEOMAR}%
\affil[3]{Dalhousie University}%
\affil[4]{BGR - Federal Institute for Geosciences and Natural Resources}%
\affil[5]{Monterey Bay Aquarium Research Institute (MBARI)}%
\affil[6]{University of Calgary}%
\affil[7]{GEOMAR Helmholtz Centre for Ocean Research Kiel}%
\affil[8]{National Institute of Water \& Atmospheric Research}%
\affil[9]{Shanghai Jiao Tong University}%


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  \date{May 24, 2024}


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\begin{abstract}
Although marine controlled source electromagnetic (CSEM) methods are
effective for investigating offshore freshened groundwater (OFG)
systems, interpreting the spatial extent and salinity of OFG remains
challenging. Integrating CSEM resistivity models with information on
sub-surface properties, such as host-rock porosity, allows for estimates
of pore-water salinity. However, deterministic inversion approaches pose
challenges in quantitatively analyzing these estimates as they provide
only one best-fit model with no associated estimate of model parameter
uncertainty. To address this limitation, we employ a trans-dimensional
Markov-Chain Monte-Carlo inversion on marine CSEM data, under the
assumption of horizontal stratification, collected from the Canterbury
Bight, New Zealand. We integrate the resulting posterior distributions
of electrical resistivity with borehole and seismic reflection data to
quantify pore-water salinity with uncertainty estimates. The results
reveal a low-salinity groundwater body in the center of the survey area
at varying depths, hosted by consecutive silty- and fine-sand layers
approximately 20 to 60 km from the coast. These observations support the
previous study's results obtained through deterministic 2-D inversion
and suggest freshening of the OFG body closer to the shore within a
permeable, coarse-sand layer 40 to 150 m beneath the seafloor. This
implies a potential active connection between the OFG body and the
terrestrial groundwater system. We demonstrate how the Bayesian approach
constrains the uncertainties in resistivity models and subsequently in
pore-water salinity estimates. Our findings highlight the potential of
Bayesian inversions in enhancing our understanding of OFG systems,
providing crucial boundary conditions for hydrogeological modeling and
sustainable water resource development.%
\end{abstract}%



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