STRATIGRAPHY OF COASTAL AEOLIAN SAND DUNES: MODELS VS. GPR IMAGING

The genesis and internal stratigraphy of coastal aeolian sand dunes are often inferred from models based on dune geometry and sedimentary processes, shallow trenches, natural scours, and/or interpretations of ancient strata. However, there is some difficulty of directly observing the stratigraphy of aeolian landforms, particularly in large dunes, and those containing complex bedforms and/or multiple reactivation surfaces. The distinctive nature of the aeolian environment, that is the relative homogeneity of sediments (quartzitic sand), provides a unique opportunity for ground penetrating radar (GPR) to reveal subsurface details. The noninvasive GPR method provides near-surface, high-resolution, near continuous profiles within these increasingly sensitive, depositional settings. PulseEKKO 100 and 1000 GPR acquisition systems were used with 200, 400 and 1000 volt transmitters. Step size and antennae separation varied depending on antennae frequency and site conditions. Each trace was vertically stacked and the digital profiles were processed and plotted using pulseEKKO software. The transects were topographically corrected based on laser level surveys. To measure depth, near surface velocity measurements were calculated from common midpoint (CMP) surveys.

The application of radar stratigraphic analysis on the collected GPR data provided the framework to investigate both lateral and vertical stratigraphic variations within these coastal aeolian deposits. Radar images were interpreted as showing dune cross-stratification (dip orientation and dip angle varied), scoured bounding surfaces, buried paleosols (where present), as well as the position of the water table. The internal dune structures revealed by GPR graphically demonstrate the response of aeolian dunes through time and to variations in wind regime, sediment supply, and human interference. Data will presented from selected study sites with in the US (California, Michigan, Oregon, North Carolina, Washington, Wisconsin) and other locations worldwide. Where possible, comparisons to available data and/or models will be made.