The age of alluvial surfaces can play a key role in deciphering surface processes and landscape evolution. However, the most common dating methods (e.g. with cosmogenic nuclides like 10Be) are expensive and time-consuming. We propose an approach that utilizes a limited number of 10Be samples in combination with hyperspectral data to estimate surface ages.
Specifically, we make use of known alterations of the spectral reflectance of geochemical surfaces caused by weathering processes, e.g., clay mineral and iron oxide formation. Changes consist of an overall increase in reflection, but mainly the development of characteristic absorption features. Our aim is to detect these weathering features via hyperspectral satellite imagery to build a ground-truthed spectral-age model for estimating alluvial surface ages over large regions.
To test this approach along the Río Santa Cruz in southern Patagonia, we dated 7 out of 13 fluvial terrace levels that yielded exposure ages up to 1.5 My, and we conducted in situ spectral measurements using a field spectrometer. By comparing these observations to satellite data (Landsat 8 and EnMAP), we can estimate ages and make better correlations of undated surfaces along the 250-km length of the river. Surprisingly, the age range of the model indicates slower than expected weathering rates and a major methodological advance in the detection of weathering processes via hyperspectral satellite.