Constraining the lithostratigraphic architecture of a buried bedrock valley using surface electrical resistivity and seismic refraction tomography

Abstract

Buried bedrock valleys are common erosional features in northern mid-latitude environments forming through glaciofluvial or paleoalluvial processes and are typically infilled by Quaternary-aged sediments. The erosional extent and geometry of the valley including a weathered interface, along with sediment infill that can contain complex sequences of unconsolidated aquifer and aquitard sediments, mean these features may act as preferential pathways to deeper bedrock aquifers. Non-invasive geophysical tools can provide rapid, high-resolution subsurface characterization of these features. This study evaluates the application of electrical resistivity and seismic refraction tomography along two transects centred over a buried bedrock valley in Elora, Ontario, Canada. Geophysical measurements were combined with existing continuous core records and an electrofacies model based on downhole geophysical logs to constrain the morphology and infilled lithostratigraphic architecture of the valley. Bedrock competency associated with lithology may act as a control on depth and width of valley incision during erosion, with resistivity measurements of the bedrock revealing a potential association between interpreted mechanical properties and variations in the resolved valley morphology. Seismic velocity corroborated these contrasting valley widths but could not assess bedrock competency variability below the bedrock interface. This study reveals the sequence of events depositing sediments in the valley, yielding a revised architectural mapping that improves on previous regional-scale lithostratigraphic interpretations. Results will be of use to groundwater practitioners requiring detailed conceptualization of this buried bedrock valley and its role on preferential zones of groundwater flow. Similar approaches can be used for delineation of these common and hydrogeologically significant features.