Unifying particle-based and continuum models of hillslope evolution with a probabilistic scaling technique

TL;DR

This paper introduces a probabilistic scaling technique to unify particle-based and continuum models of hillslope evolution, enabling better understanding and simulation of geomorphic processes.

Contribution

It presents a novel approach connecting particle and continuum models using probabilistic scaling, with characterization of stationary distributions and equilibrium profiles.

Findings

Particle model stationary distributions characterized.

Continuum limit identified through heuristic scaling.

Simulations demonstrate hillslope response to perturbations.

Abstract

Relationships between sediment flux and geomorphic processes are combined with statements of mass conservation, in order to create continuum models of hillslope evolution. These models have parameters which can be calibrated using available topographical data. This contrasts the use of particle-based models, which may be more difficult to calibrate, but are simpler, easier to implement, and have the potential to provide insight into the statistics of grain motion. The realms of individual particles and the continuum, while disparate in geomorphological modeling, can be connected using scaling techniques commonly employed in probability theory. Here, we motivate the choice of a particle-based model of hillslope evolution, whose stationary distributions we characterize. We then provide a heuristic scaling argument, which identifies a candidate for their continuum limit. By simulating instances of the particle model, we obtain equilibrium hillslope profiles and probe their response to perturbations. These results provide a proof-of-concept in the unification of microscopic and macroscopic descriptions of hillslope evolution through probabilistic techniques, and simplify the study of hillslope response to external influences.