The quantitative meaning of resistivity data in a coastal setting: a Belgian case study

In coastal areas, the natural groundwater flow is affected by human activities, such as managed aquifer recharge (MAR) and groundwater extraction. They can induce saltwater intrusion and impact the fresh submarine groundwater discharge (FSGD). Resistivity methods, such as electrical resistivity tomography (ERT) and continuous resistivity profiling (CRP) are easy to use and very effective to assess the distribution of salt and freshwater in coastal environments. The Western Belgian coast, De Panne and Koksijde, was already investigated with ERT and CRP by Paepen et al. (2022; 2020). In this area, the source of FSGD is a sandy dune ridge of around 2.5 km wide. Now, we compare the FSGD footprint in front of De Panne and Koksijde to other Belgian coastal sites (Raversijde, Wenduine, Knokke-Heist, and Zwin), which have a different structure of the phreatic aquifer and a much smaller dune belt.

The quantitative interpretation of ERT and CRP is not straightforward, but image appraisal tools - such as the model resolution matrix (R), cumulative sensitivity matrix (S), and depth of investigation index (DOI) - can aid (Caterina et al., 2013). To be able to quantitatively assess the resistivity inversion models, five synthetic models were created (Paepen et al., 2022). These models reflect the present situation of the Western Belgian coast, where we find freshwater outflow on the lower beach or below the low water line. Based on the inversion models of the synthetic cases, the model resolution matrix, cumulative sensitivity matrix, and DOI (Oldenburg & Li, 1999) were calculated. The image appraisal tools were then compared to the error on the salinity for each cell in the inversion model (we find an error below 0.05 acceptable). This allows to define a threshold of the different image appraisal tools for which the model can be quantitatively assessed and to apply them to the field data. The thresholds reveal that no quantitative interpretation is possible for the zones of FSGD and that the FSGD resistivity is underestimated by the inversion process, so the salinity of the outflow is overestimated. Nevertheless, lateral qualitative changes can be deduced from the inversion models.

References

Caterina, D., Beaujean, J., Tanguy, R., & Nguyen, F. (2013). A comparison study of different image appraisal tools for electrical resistivity tomography. Near Surface Geophysics, 11, 639-657. https://doi.org/10.3997/1873-0604.2013022

Oldenburg, D. W., & Li, Y. (1999). Estimating depth of investigation in dc resistivity and IP surveys. Geophysics, 64(2), 403-416. https://doi.org/10.1190/1.1444545

Paepen, M., Deleersnyder, W., De Latte, S., Walreavens, K., & Hermans, T. (2022). Effect of Groundwater Extraction and Artificial Recharge on the Geophysical Footprints of Fresh Submarine Groundwater Discharge in the Western Belgian Coastal Area. Water, 14(7), 1040. https://doi.org/10.3390/w14071040

Paepen, M., Hanssens, D., De Smedt, P., Walraevens, K., & Hermans, T. (2020). Combining resistivity and frequency domain electromagnetic methods to investigate submarine groundwater discharge (SGD) in the littoral zone. Hydrology and Earth System Sciences, 24, 3539-3555. https://doi.org/10.5194/hess-24-3539-2020