Lithology and orographic precipitation control river incision in the tropical Andes

Abstract

Process-based geomorphic transport laws enable to assess the impact of rainfall variability on bedrock river incision over geological timescales. However, isolating the role of rainfall variability on erosion remains difficult in natural environments in part because the variability of rock strength and its resistance to incision are poorly constrained. Here, we explore spatial differences in the rate of bedrock river incision in the tropical Andes. The Ecuadorian Andes are characterized by strong rainfall gradients due to orographic precipitation sourced in the Amazon basin. In addition, the tectonic configuration 20 has generated a profound lithological heterogeneity. The relative role of either these controls in modulating river incision on millennial time scales, however, remains unclear. Using 10 Be catchment-wide erosion rates, meteorological and hydrological data, as well as data on bedrock erodibility, we provide quantitative constraints on the importance of rainfall variability and lithological variations. Explicit incorporation of rock erodibility in river incision models predicated on the stream power equation enables us to identify a first order control of lithology on river incision rates. Rainfall variability based on a spatially 25 and temporally explicit hydrological dataset and a stochastic-threshold river incision model explain regional differences in river incision that cannot be attributed to topographical and/or lithological variability.

Isolating Lithologic Versus Tectonic Signals of River Profiles to Test Orogenic Models for the Eastern and Southeastern Carpathians

“…Amongst these intrinsic forcings, the effect of differential lithology on fluvial morphology has been a recent focus of geomorphological studies (e.g. Bernard et al, 2019;Campforts et al, 2019;Forte et al, 2016;Kirby et al, 2003;Peifer Bezerra, 2018;Seagren & Schoenbohm, 2019;Strong et al, 2019;Thaler & Covington, 2016;Yanites et al, 2017). Rivers flowing over harder rocks tend to have steeper channels and affect the overall landscape morphology (e.g.…”

“…Careful acknowledgement of lithological heterogeneities still permits the interpretation of climatic and tectonic signals from river morphology (e.g. Campforts et al, 2019;Kirby et al, 2003), but can also confuse the signal (e.g. Strong et al, 2019) and potentially lead to misinterpretation.…”

Predicting gully densities at sub‐continental scales: a case study for the Horn of Africa

“…While ME is commonly used to evaluate models in geomorphic research (e.g. de Vente et al, 2013;Campforts et al, 2019), it is also highly sensitive to outliers. As complementary measures, we therefore also calculated the overall Bias (see Eq.…”

HyLands 1.0: a Hybrid Landscape evolution model to simulate the impact of landslides and landslide-derived sediment on landscape evolution

“…A main finding of those authors is that the role of allogenic fluvial response (i.e. transient adjustment to an external perturbation) can only be understood when considering autogenic fluvial dynamics such as the existence of incision thresholds (Snyder et al, 2003;Lague et al, 2005) and the internal lithological heterogeneity in a landscape (Campforts et al, 2019;Glade et al, 2019). However, the role of landslides in long-term landscape evolution, and especially the dynamic interaction between river incision and landslide activity, is only poorly understood.…”

“…CRN data has been used to calibrate river incision models that explicitly integrate the stochastic nature of fluvial incision over time (DiBiase and Whipple, 2011;Scherler et al, 2017;Campforts et al, 2019). However, CRN data is sensitive to landslide activity (Niemi et al, 2005;Yanites et al, 2009;Wang et al, 2017) and the calibration of stochastic river incision models has been shown to be sensitive to landslide activity (Campforts et al, 2019). HyLands directly simulates stochastic landsliding and hence enables explicit simulation of the impact of landsliding on CRN-derived erosion rates, making them a promising tool to constrain HyLands.…”