A probabilistic framework for the cover effect in bedrock erosion

Turowski, Jens M.; Hodge, Rebecca

doi:10.5194/esurf-2016-59

Cited by 12 publications

(16 citation statements)

References 29 publications

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“…I use this bedrock exposure model for both the sediment cover‐shear stress model and the saltation abrasion erosion model described below. I note that other formulations of the cover effect have been proposed (Turowski et al, ; Turowski & Hodge, ) that incorporate a probabilistic approach to sediment cover and future work should explore if such formulations predict fundamentally different behavior in river systems over landscape evolution time scales.…”

Section: Modelmentioning

confidence: 99%

The Dynamics of Channel Slope, Width, and Sediment in Actively Eroding Bedrock River Systems

Yanites

2018

JGR Earth Surface

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The evolution of rivers in eroding landscapes plays a key role in determining landscape relief and modulating climate‐tectonic interactions. A common approach to quantifying river system evolution uses a one‐dimensional, detachment‐limited stream power equation. One potential drawback of this model is that it does not incorporate the effects of changes in channel width or the role of sediment transport dynamics. Here I present a new method for modeling the influence of channel width on river dynamics to explore how variable width and sediment transport impact river profile evolution. With this approach, vertical river erosion can operate based on any number of river erosion models, such as a simple shear stress model (e.g., detachment limited), sediment cover‐shear stress hybrid models, or mechanistic saltation‐abrasion models. I explore the sensitivity of these three models to increases in rock‐uplift rate (i.e., 2, 3, 5, 10, and 20× increase). Generally, the results show that incorporating channel width adjustment or sediment transport dynamics lowers the sensitivity of a river profile to rock‐uplift rate. For the sediment transport‐dependent models, the degree of sensitivity depends on whether the system is limited by bedrock exposure or erosion potential (i.e., detachment potential). The approach produces transient responses that reveal distinct patterns of width and slope, which may provide valuable insight into the limiting physical mechanisms of bedrock erosion in a region. The implications of the work are broad and include the potential to distinguish underlying erosion controls from field observations of width and slope as well as understanding climate‐tectonic interactions.

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Section: Modelmentioning

confidence: 99%

The Dynamics of Channel Slope, Width, and Sediment in Actively Eroding Bedrock River Systems

Yanites

2018

JGR Earth Surface

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“…Processes such as landsliding, sediment transport and soil perturbation can thus be treated probabilistically or tagged as stochastic (Benda and Dunne, 1997; Miller and Burnett, 2008; Bennett et al . 2014; Turowski and Hodge, 2017; Furbish et al . 2018).…”

Section: Acknowledging Uncertainty In Geomorphologymentioning

confidence: 99%

Bayesian geomorphology

Korup

2020

Earth Surf Processes Landf

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Summary The rapidly growing amount and diversity of data are confronting us more than ever with the need to make informed predictions under uncertainty. The adverse impacts of climate change and natural hazards also motivate our search for reliable predictions. The range of statistical techniques that geomorphologists use to tackle this challenge has been growing, but rarely involves Bayesian methods. Instead, many geomorphic models rely on estimated averages that largely miss out on the variability of form and process. Yet seemingly fixed estimates of channel heads, sediment rating curves or glacier equilibrium lines, for example, are all prone to uncertainties. Neighbouring scientific disciplines such as physics, hydrology or ecology have readily embraced Bayesian methods to fully capture and better explain such uncertainties, as the necessary computational tools have advanced greatly. The aim of this article is to introduce the Bayesian toolkit to scientists concerned with Earth surface processes and landforms, and to show how geomorphic models might benefit from probabilistic concepts. I briefly review the use of Bayesian reasoning in geomorphology, and outline the corresponding variants of regression and classification in several worked examples. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd

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“…The shape of our inferred tools-and-cover effect is similar to that found in rotary mill experiments (Sklar and Dietrich, 2001), but has a slower decay of incision rate, indicating a weaker cover effect. The tools and cover effects can be modeled with a power function of sediment mass (T17, Turowski and Hodge, 2017). Applied to the abrasion mill experiments, T17 collapses to a special case in which additional sediment falls equally on exposed and already covered bedrock (Turowski, 2007).…”

Section: Controls On Bedrock Incisionmentioning

confidence: 99%

Wave-driven geomorphology of Pacific carbonate coastlines: from landscape to wavelength scale

Bramante¹

2020

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The shallow marine ecosystems of coral atolls and the human communities they support are among the most vulnerable to anthropogenic climate change. Sea-level rise threatens to inundate low-lying reef islands, tropical cyclone intensification threatens islands with flooding and erosion, and ocean warming and acidification threaten the health of coral reefs. Unfortunately, the sediment dynamics that shape the morphol-

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A probabilistic framework for the cover effect in bedrock erosion

Cited by 12 publications

References 29 publications

The Dynamics of Channel Slope, Width, and Sediment in Actively Eroding Bedrock River Systems

The Dynamics of Channel Slope, Width, and Sediment in Actively Eroding Bedrock River Systems

Bayesian geomorphology

Wave-driven geomorphology of Pacific carbonate coastlines: from landscape to wavelength scale

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