Abstract

Abstract. Theoretical and experimental work (Furbish et al., 2021a, b) indicates that the travel distances of rarefied particle motions on rough hillslope surfaces are described by a generalized Pareto distribution. The form of this distribution varies with the balance between gravitational heating, due to conversion of potential to kinetic energy, and frictional cooling, due to particle–surface collisions; it varies from a bounded form associated with rapid thermal collapse to an exponential form representing isothermal conditions to a heavy-tailed form associated with net heating of particles. The generalized Pareto distribution in this problem is a maximum entropy distribution constrained by a fixed energetic “cost” – the total cumulative energy extracted by collisional friction per unit kinetic energy available during particle motions. That is, among all possible accessible microstates – the many different ways to arrange a great number of particles into distance states where each arrangement satisfies the same fixed total energetic cost – the generalized Pareto distribution represents the most probable arrangement. Because this idea applies equally to the accessible microstates associated with net cooling, isothermal conditions and net heating, the fixed energetic cost provides a unifying interpretation for these distinctive behaviors, including the abrupt transition in the form of the generalized Pareto distribution in crossing isothermal conditions. The analysis therefore represents a novel generalization of an energy-based constraint in using the maximum entropy method to infer non-exponential distributions of particle motions. Moreover, the energetic costs of individual particle motions follow an extreme-value distribution that is heavy-tailed for net cooling and light-tailed for net heating. The relative contribution of different travel distances to the total energetic cost is reflected by the product of the travel distance distribution and the cost of individual particle motions – effectively a frequency–magnitude product.

Highlights

  • In two companion papers (Furbish et al, 2021a, b) we examine a theoretical formulation of the probabilistic physics of rarefied particle motions and deposition on rough hillslope surfaces

  • The formulation predicts a generalized Pareto distribution of particle travel distances whose form varies with the balance between gravitational heating, due to conversion of potential to kinetic energy, and frictional cooling, due to particle–surface collisions

  • The generalized Pareto distribution varies from a bounded form associated with thermal collapse and rapid deposition to an exponential form representing isothermal conditions to a heavy-tailed form associated with net heating of particles and decreased deposition

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Summary

Introduction

In two companion papers (Furbish et al, 2021a, b) we examine a theoretical formulation of the probabilistic physics of rarefied particle motions and deposition on rough hillslope surfaces. The generalized Pareto distribution is not selected in an empirical manner based on goodness-of-fit criteria applied to data sets Rather, this distribution is dictated by the physics of the problem, just as, for example, the Boltzmann distribution (an exponential distribution) emerges in classical statistical mechanics from consideration of the accessible energy microstates of a gas system. This distribution is dictated by the physics of the problem, just as, for example, the Boltzmann distribution (an exponential distribution) emerges in classical statistical mechanics from consideration of the accessible energy microstates of a gas system In this problem the versatile form of the generalized Pareto distribution – its apparent success in describing three distinctive energetic behaviors of rarefied particle motions – is enigmatic. In the fourth companion paper (Furbish and Doane, 2021) we step back and examine the philosophical underpinning of the statistical mechanics framework for describing sediment particle motions and transport

Elements of the distribution of travel distances
Maximum entropy distribution
Energetic cost as a maximizing constraint
Constraints
Maximization
Cumulative energetic cost
Frictional loss to heat
Discussion and conclusions
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