CHARACTERIZING SUBSURFACE COMPLEXITY OF AEOLIAN LANDFORMS WITH GEORADAR

The morphologically distinct three-dimensional dune forms (barchan, parabolic, star dunes) exhibit differences in their internal architecture, however these are often difficult to assess due to limited exposures or point-source core data. Characterization of the dip-section architecture is particularly important as it should allow the differentiation of dune morphotypes based on the preserved subsurface expression of dune migration. The relatively homogeneous gypsum dunes of White Sands National Monument, NM and quartz-dominated paraglacial aeolian sequences of Pine Barrens, NJ provide ideal settings for cataloguing the complexity of internal dune structure associated with different depositional modes. At White Sands, continuous 5-km-long ground-penetrating radar (GPR) profile and a number of site-specific surveys using 500 and 800 MHz MALA antennas, reveal a spectrum of subsurface reflection patterns within closely associated barchans and parabolic dunes. The images capture apparent paleo-slipface (lateral accretion surface) gradients, semi-lithified pedestals, and biogenic structures (vegetation traces and animal burrows). Rapidly advancing unvegetated barchans exhibit apparent slipface angles of 24-30˚ (migration-corrected), with multiple reactivation surfaces expressed as truncated reflections and changes in dip angle. In contrast to relatively uniform geometry of bounding surfaces within barchans, geophysical images of transitional and parabolic dunes display complex sigmoidal-oblique, chaotic, hummocky, and discontinuous patterns. The effect of vegetation during deposition and following plant burial, is one of the primary factors responsible for this complexity. At the Pine Barrens site, the low-angle (<2˚) reflections punctuated by multiple high-amplitude point-source (3D) signal return, suggest a random pattern of hummock-style deposition overprinted by vegetation. An assessment of dip-section transects is underway aimed at establishing a quantitative basis for utilizing subsurface complexity as a means of discriminating the types of aeolian landforms. This research has potential application to coastal regions where large portions of isolated and transverse dunes are preserved below the water table, making GPR the most viable and effective technique.