Evolution and erosional dynamics of intermontane basins on the Puna Plateau, NW Argentina

Abstract:

The Puna Plateau in NW Argentina is the southern part of the second-largest orogenic plateau on Earth with a mean elevation of 4.0 ± 0.5 km (±2s). The Puna is an integral part of the south-central Andes that exhibit a steep E-W topographic and climatic gradient: The first windward topographic rise east of the Puna constitutes a significant orographic barrier resulting in high orographic rainfall. Westward, the higher-elevation areas of the windward flanks become progressively drier, until arid conditions are attained in the orogen interior. The Puna repeatedly experienced significant paleoclimatic changes reflected by fluvial and lacustrine terraces associated with lake highstands related to deeper penetration of moisture into the orogen and thus an orogenward shift of the climate gradient. The southern Puna is compartmentalized into more than 500 separate, internally-drained sedimentary basins with varying catchment size. Here, we quantify the erosion-rate gradients and their impact on basin evolution and their importance on the formation of the plateau morphology. We rely on sedimentary archives, digital topography, and a new set of cosmogenic inventories of river sands (10Be) and bedrock-erosion rates (10Be and 26Al) from the eastern and central plateau. Erosion rates from internally drained catchments in the eastern plateau are similar to the externally drained, semi-arid intermontane basins in the E Cordillera, which bounds the plateau, but are ten-fold (or more) lower than erosion rates in the humid and steep sections along the eastern windward flanks. Within the plateau realm, erosion rates are ten-fold lower in the central than in the eastern parts. We analyze high-resolution topography from ASTER- and interferometry-derived Digital Elevation Models (DEMs) that we have validated with more 10’000 differential GPS ground control points. We demonstrate distinct topometric gradients across the Puna that can be linked to spatial variations in rainfall and vegetation cover.