DISENTANGLING PRIMARY CONTROLS ON LANDSCAPE EVOLUTION OF THE NORTH-CENTRAL ANDES: NEW 10BE EROSION RATES FROM SOUTHERN PERU

Isolating and quantifying the relative influences of different factors affecting landscape evolution is a longstanding goal of modern tectonic geomorphology. The role of climate has been particularly controversial. Recent work suggests that the topography of the eastern north-central Andes of Peru and Bolivia is largely adjusted to the regional orographic rainfall gradient that it experiences. Here, we present 19 new ¹⁰Be catchment-average erosion rates sampled across the strongest portion of this rainfall gradient in southern Peru. Using a rainfall-weighted variant of the normalized channel steepness index, k_snQ, we show that channel steepness values and thus topography are adjusted to spatially varying rainfall. We find that subsets of catchments spanning up to nearly an order of magnitude of annual rainfall (~0.5 to 5 m/yr) cluster into narrow ranges of k_snQ and erosion rate, suggesting that these catchments are in equilibrium with rainfall as the unique combinations of parameters in each that determine k_snQ all faithfully reflect erosion rate. Additionally, we find that rocks with similar physical characteristics define distinct relationships between k_snQ and erosion rate, suggesting k_snQ is also resolving lithologic variations in erodibility. However, substantial uncertainty exists in parameters describing these relationships, largely due to analytical uncertainty inherent to ¹⁰Be measurements. By combining our new data with 38 published erosion rates from Peru and Bolivia, we collapse the range of compatible parameter values and resolve robust, nonlinear k_snQ–erosion rate relationships suggestive of important influences of erosional thresholds, rock properties, sediment characteristics, and temporal runoff variability. In contrast, neither climatic nor lithologic effects are clear using the traditional channel steepness metric, k_sn. Together, these results provide compelling evidence that the north-central Andes represents one of the best natural examples identified to date where the influence of climate can be identified and further studied. Furthermore, they highlight that accounting for spatial rainfall variations is essential for disentangling the multiple influences of climate, lithology, and tectonics common in mountain landscapes, which is a necessary first step toward greater understanding of how these landscapes evolve.