Does remote sensing help translating local SGD investigation to large spatial scales?

Within the last 20 years, studies on submarine groundwater discharge (SGD) have revealed numerous processes, temporal behavior and quantitative estimations as well as best-practice and localization methods. This plethora on information is valuable regarding the understanding of magnitude and effects of SGD for the respective location. Yet, since given local conditions vary, the translation of local understanding, magnitudes and effects to a regional or global scale is not trivial. In contrast, modeling approaches (e.g. ²²⁸Ra budget) tackling SGD on a global scale do provide quantitative global estimates but have not been related to local investigations. This gap between the two approaches, local and global, and the combination and/or translation of either one to the other represents one of the mayor challenges the SGD community currently faces.

But what if remote sensing can provide certain information that may be used as translation between the two, similar to transfer functions in many other disciplines allowing an extrapolation from in-situ investigated and quantified SGD (discrete information) to regional scales or beyond?

Admittedly, the sketched future is ambitious and we will certainly not be able to present a solution to the raised question. Nonetheless, we will show a remote sensing based approach that is already able to identify potential SGD sites independent on location or hydrogeological conditions. Based on multi-temporal thermal information of the water surface as core of the approach, SGD influenced sites display a smaller thermal variation (thermal anomalies) than surrounding uninfluenced areas. Despite the apparent simplicity, the automatized approach has helped to localize several sites that could be validated with proven in-situ methods. At the same time it embodies the risk to identify false positives that can only be avoided if we can ‘calibrate’ the so obtained thermal anomalies to in-situ data. We will present all pros and cons of our approach with the intention to contribute to the solution of translating SGD investigation to larger scales.