Quantifying moraine degradation as a relative dating technique
Abstract
When moraines degrade, two distinct changes in their morphology occur: 1) weathering of boulders on the moraine surface leads to fewer and smaller boulders over time; 2) initially sharp crests of the moraine become gentle over time as erosion transports material downhill. These two attributes of moraines, surface roughness and the sharpness of the crest, are important parameters to characterize the evolution of glaciated landscapes but they have not been quantified. We established two metrics to quantify these attributes of moraine morphology using high-resolution elevation data and compared them against publicly available cosmogenic ages. The surface roughness of the moraines is proportional to the number and size of the boulders, and we quantified it by calculating the standard deviation of slope determined from 1-m LiDAR data. For example, each boulder on the moraine surface produces local slope, and a large number of boulders on a young moraine should lead to a high variability of slopes, measured in degrees. Second, we quantified the sharpness of moraine crests by measuring the maximum curvature along crest-perpendicular transects. Young moraines tend to have sharp crests resulting in high values of the maximum curvature, compared to gentle crests of old moraines with low curvature values. We analyzed only the surfaces of well-dated lateral moraines with five or more cosmogenic ages per moraine. Preliminary results show a weak negative temporal correlation in the surface roughness and the sharpness of the moraine crests. However, the correlation is more apparent at 100,000-yr scale than at 10,000-yr scale, probably because most of the moraines date to ~1622 ka. The correlation between these morphologic metrics and age can be improved by analyzing older moraines from a variety of climate conditions. This new relative dating technique can be used for mapping glacial landscapes in other planets, such as Mars.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMEP55A1051E