Numerical modeling of glacial erosion and headwall processes in alpine valleys

MacGregor, K. R.; Anderson, Robert S.; Waddington, Edwin D.

doi:10.1016/j.geomorph.2008.04.022

Cited by 122 publications

(142 citation statements)

References 76 publications

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“…where K is a constant that characterizes the erodibility of the subglacial material (Laitakari et al, 1985;MacGregor et al, 2009;Duhnforth et al, 2010) and l is another constant generally equal to 1 (Table 1). While a few recent studies have used more sophisticated rules for erosion (MacGregor et al, 2009;Iverson, 2012), this is the same rule as used in previous ICE-Cascade and other glacially influenced, landscape evolution models (e.g., Braun et al, 1999;Herman and Braun, 158 R. M. Headley and T. A. Ehlers: Ice flow models and glacial erosion over multiple glacial-interglacial cycles 2008; Kessler et al, 2008;Egholm et al, 2012b;Yanites and Ehlers, 2012).…”

Section: Glacial Modelsmentioning

confidence: 99%

“…(1), is based upon another assumption, and various other erosion laws tie the erosion rate to other powers of the sliding velocity (Hallet, 1979;Iverson, 1995;MacGregor et al, 2009), the ice flux (Kessler et al, 2008), or the basal shear stress (Pollard and Deconto, 2007), and a different choice would influence the patterns of erosion and the locations of maximum erosion rate. Comparing the magnitude of effects of erosion laws on developing topography can be difficult for a number of reasons: scaling factors and constants might vary; the ice physics, which can add further complications, determine the basal shear stress; and subglacial hydrology is still quite complicated.…”

Section: Comparison To Other Modelsmentioning

confidence: 99%

“…These models have ranged from simple 2-D glacial profile models (Anderson et al, 2006;MacGregor et al, 2009) to more complex 3-D models that incorporate a variety of processes and mechanisms (Kessler et al, 2008;Egholm et al, 2012a;Pedersen and Egholm, 2013). Other studies have incorporated glacial erosion into landscape dynamic models that also include fluvial and hillslope erosional processes (Herman and Braun, 2008;Egholm et al, 2011;Yanites and Ehlers, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Ice flow models and glacial erosion over multiple glacial–interglacial cycles

Headley

Ehlers

2015

Earth Surf. Dynam.

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Abstract. Mountain topography is constructed through a variety of interacting processes. Over glaciological timescales, even simple representations of glacial-flow physics can reproduce many of the distinctive features formed through glacial erosion. However, detailed comparisons at orogen time and length scales hold potential for quantifying the influence of glacial physics in landscape evolution models. We present a comparison using two different numerical models for glacial flow over single and multiple glaciations, within a modified version of the ICE-Cascade landscape evolution model. This model calculates not only glaciological processes but also hillslope and fluvial erosion and sediment transport, isostasy, and temporally and spatially variable orographic precipitation. We compare the predicted erosion patterns using a modified SIA as well as a nested, 3-D Stokes flow model calculated using COMSOL Multiphysics.Both glacial-flow models predict different patterns in time-averaged erosion rates. However, these results are sensitive to the climate and the ice temperature. For warmer climates with more sliding, the higher-order model yields erosion rates that vary spatially and by almost an order of magnitude from those of the SIA model. As the erosion influences the basal topography and the ice deformation affects the ice thickness and extent, the higher-order glacial model can lead to variations in total ice-covered area that are greater than 30 % those of the SIA model, again with larger differences for temperate ice. Over multiple glaciations and long timescales, these results suggest that higher-order glacial physics should be considered, particularly in temperate, mountainous settings.

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Section: Glacial Modelsmentioning

confidence: 99%

Section: Comparison To Other Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Ice flow models and glacial erosion over multiple glacial–interglacial cycles

Headley

Ehlers

2015

Earth Surf. Dynam.

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“…Estas diferencias se avienen con las observaciones de Li et al (2001), que indican que los valles que han estado glaciados suelen presentar una morfología más abierta (en forma de U) que los valles no glaciados en ambientes similares, y con las de Brocklehurst y Whipple (2006) y MacGregor et al (2009) que demuestran que los perfiles de los valles modelados por glaciares suelen ser significativamente diferentes a los mostrados por cursos fluviales no afectados por la dinámica glaciar, que presentan un perfil más irregular, con rupturas de pendiente bien marcadas.…”

Section: Comparación Entre Valles Con Morfología Glaciar Y Fluvialunclassified

“…Los glaciares son uno de los agentes de modelado más importantes de la Tierra, y sus formas, tanto erosivas como deposicionales, caracterizan el relieve de amplias superficies del planeta (Benn y Evans, 2010). En las áreas de montaña, los glaciares tienden a ocupar los valles fluviales previos, modificando su morfología; así, los perfiles de los valles glaciares suelen ser diferentes a los que tienen un origen únicamente fluvial, tanto longitudinalmente (Brocklehurst y Whipple, 2006;MacGregor et al, 2009) como transversalmente (Li et al, 2001). Además, los glaciares movilizan mayor cantidad de sedimentos que los ríos, evidenciando su mayor capacidad erosiva en zonas de montaña (Montgomery, 2002;Brook et al, 2006).…”

Section: Introductionunclassified

Influencia de la glaciación en la red de drenaje: el ejemplo de los valles de Respina y Rebueno (Alto Porma, Cordillera Cantábrica, noroeste de España)

Danis-Álvarez

González

2017

CIG

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Glacial landscape evolution by subglacial quarrying: A multiscale computational approach

2016

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Quarrying of bedrock is a primary agent of subglacial erosion. Although the mechanical theory behind the process has been studied for decades, it has proven difficult to formulate the governing principles so that large‐scale landscape evolution models can be used to integrate erosion over time. The existing mechanical theory thus stands largely untested in its ability to explain postglacial topography. In this study we relate the physics of quarrying to long‐term landscape evolution with a multiscale approach that connects meter‐scale cavities to kilometer‐scale glacial landscapes. By averaging the quarrying rate across many small‐scale bedrock steps, we quantify how regional trends in basal sliding speed, effective pressure, and bed slope affect the rate of erosion. A sensitivity test indicates that a power law formulated in terms of these three variables provides an acceptable basis for quantifying regional‐scale rates of quarrying. Our results highlight the strong influence of effective pressure, which intensifies quarrying by increasing the volume of the bed that is stressed by the ice and thereby the probability of rock failure. The resulting pressure dependency points to subglacial hydrology as a primary factor for influencing rates of quarrying and hence for shaping the bedrock topography under warm‐based glaciers. When applied in a landscape evolution model, the erosion law for quarrying produces recognizable large‐scale glacial landforms: U‐shaped valleys, hanging valleys, and overdeepenings. The landforms produced are very similar to those predicted by more standard sliding‐based erosion laws, but overall quarrying is more focused in valleys, and less effective at higher elevations.

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Numerical modeling of glacial erosion and headwall processes in alpine valleys

Cited by 122 publications

References 76 publications

Ice flow models and glacial erosion over multiple glacial–interglacial cycles

Ice flow models and glacial erosion over multiple glacial–interglacial cycles

Influencia de la glaciación en la red de drenaje: el ejemplo de los valles de Respina y Rebueno (Alto Porma, Cordillera Cantábrica, noroeste de España)

Glacial landscape evolution by subglacial quarrying: A multiscale computational approach

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