Submarine groundwater discharge (SGD) can be an important pathway for nutrients entering coastal systems. However SGD flow paths can be difficult to identify and flow volumes difficult to quantify. This study assesses whether geophysical techniques are potentially cost effective methods for detecting the presence or lack of SGD within an estuary environment found in Sarasota Bay, Florida. In this area, a rapid increase in urbanization has led to increased nitrogen loading into the bay, with some 10% of this loading attributed to SGD. Discharging groundwater is expected to be fresher and hence higher resistivity, than "background" surface waters. Thus resistivity surveys sensitive to seafloor conductivities may be useful for identifying zones of SGD. However, terrain resistivities are influenced by matrix geology as well as pore water resistivity. In this study we compare the results of marine resistivity surveys against both geochemical measures of SGD (radon tra cers) and seismic profiles indicative of subsurface structure to better determine the relative impacts of geology and SGD on marine resistivity measurements in Sarasota Bay. On both regional (kilometers to tens of kilometers) and local scales (hundreds of meters) the relationship between marine resistivity and tracer-based SGD estimates does not follow the expected pattern of higher resistivities associated with higher SGD flux. Seafloor resistivities instead appear primarily influenced by stratigraphy, particularly the presence of a clay layer at ~10-15 m depth in the southern part of the bay. In the southern bay, resistivities decrease at the depths associated with the clay layer. On the local (hundreds of meters) scale, lateral variations in resistivities derived from inversions of resistivity data were not found to be reproducible; nearly-coincident lines collected 30 minutes apart in time show different local signatures. This apparent local lateral variability in the resistivi ty profiles is inferred to be a result of inversion of noisy streaming resistivity data.