Year: 2025
Type: preprint
Abstract: Allogenic forcing of sediment production generates sedimentary signals that we use to understand the past. These signals may be buffered or shredded by autogenic processes as they travel through sediment routing systems from source to sink. Studies on signal propagation tend to focus on either signal buffering by deterministic fluvial networks or signal shredding by stochastic processes. Stochastic processes generate noise that can obscure or degrade signals, especially below a threshold correlation timescale inherent to each process. It remains unclear whether this timescale exists when stochastically and deterministically modeled processes interact with each other. We address this knowledge gap by coupling stochastic landsliding and deterministic fluvial processes in a 2D numerical landscape evolution model in which we vary landslide frequency, sediment erodibility, and fluvial transport length scale to generate various dynamic steady state scenarios. We explore how the interaction of the landslide and fluvial processes affects landscape morphology and sediment export from the catchment. Though landslides produce instantaneous mass fluxes from hillslopes to channels, the deposited material can only be slowly evacuated by the fluvial system. This creates an emergent correlation timescale set by the residence time of landslide deposits. Efficient fluvial systems erode deposits faster and are more likely to transmit higher-frequency signals down-system. These results can be used to predict where paleo‐tectonic and paleo-climatic signals are more likely to be preserved in strata.
Institutions: Tulane University, Vrije Universiteit Amsterdam, Lehigh University
Language: English
Subfield: Earth-Surface Processes
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: gold
Funder: National Science Foundation
Awards: Collaborative Research: Facility: CSDMS: Engaging a thriving community of practice in Earth-surface dynamics, Collaborative Research: Frameworks: OpenEarthscape - Transformative Cyberinfrastructure for Modeling and Simulation in the Earth-Surface Science Communities, Collaborative Research: TESPRESSO: Tectonic Encoding, Shredding, and PRopagation of Environmental Signals as Surface Observables
OpenAlex ID: W4415187352
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