Faghih, Zahra , Haroon, Amir , Jegen, Marion , Gehrmann, Romina, Schwalenberg, Katrin, Micallef, Aaron , Dettmer, Jan, Berndt, Christian , Mountjoy, Joshu J Joseph and Weymer, Bradley A. (2024) 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. Water Resources Research, 60 (3). e2023WR035714. DOI 10.1029/2023WR035714.

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Abstract

The study of offshore freshened groundwater (OFG) is gaining importance due to population growth and environmental pressure on coastal water resources. Marine controlled source electromagnetic (CSEM) methods can effectively map the spatial extent of OFG systems using electrical resistivity as a proxy. Integrating these resistivity models with sub-surface properties, such as host-rock porosity, allows for estimates of pore-water salinity. However, evaluating the uncertainty in pore-water salinity using resistivity models obtained from deterministic inversion approaches presents challenges, as they provide only one best-fit model, with no associated estimate of uncertainty. To address this limitation, we employ trans-dimensional Markov-Chain Monte-Carlo inversion on marine time-domain CSEM data, acquired in the Canterbury Bight, New Zealand. We integrate resistivity posterior probability distributions with borehole and seismic reflection data to estimate pore-water salinity with corresponding uncertainty estimates. The results highlight a low-salinity groundwater body in the center of the survey area, hosted by consecutive silty- and fine-sand layers approximately 20–60 km from the coast. The posterior probability distribution of resistivity models indicates freshening of the OFG body toward the shoreline within a permeable, coarse-sand layer 40–150 m beneath the seafloor, suggesting an active connection between the OFG body and the terrestrial groundwater system. The approach demonstrates how Bayesian inversion constrains the uncertainties in resistivity models and subsequently in pore-water salinity estimates. Our findings highlight the potential of Bayesian inversion to enhance our understanding of OFG systems and provide uncertainty constraints for hydrogeological modeling, thereby contributing to sustainable water resource development.

Key Points

A Bayesian workflow is employed to evaluate uncertainty in pore-water salinity estimates

Offshore groundwater in Canterbury Bight stores freshened pore-water in fine-grained sediments, likely extending from the onshore aquifer

Correlation between pore-water salinities and seismic-derived stratigraphy provides boundary conditions for hydrogeological modeling

Plain Language Summary

Geophysical methods that measure the electromagnetic properties of the Earth are effective in investigating freshwater sources beneath the seafloor. By combining the geophysical and geological information, we can better assess the quality of this groundwater. In this study, we develop a workflow that uses statistical methods to integrate electromagnetic observations with borehole and acoustic measurements along the eastern coast of the South Island of New Zealand. We aim to improve our understanding of the groundwater quality beneath the seafloor. Our research confirms the presence of freshened groundwater within the sandy seafloor up to 60 km from the coastline. Importantly, our observations indicate that the groundwater quality increases toward the coast. These findings are significant as they enhance the hydrogeological modeling of the groundwater system and suggest its potential as a source of freshwater.

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