A Numerical Framework for Wall Dissolution Modeling

Grm, Aleksander; Šuštar, Tomaž; Rodič, Tomaž; Gabrovšek, Franci

doi:10.1007/s11004-016-9641-2

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…Fleurant et al (2008) modelled the evolution of cockpit karst and stressed the importance of spatial anisotropy in landscape evolution. Modern modelling approaches, such as computational fluid dynamics, have been used to model the evolution of scallops under turbulent flow conditions (Grm et al 2017).…”

Section: Karst Hydrogeologymentioning

confidence: 99%

Recent advances in karst research: from theory to fieldwork and applications

Parise

Gabrovšek

Kaufmann

et al. 2018

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Karst landscapes and karst aquifers, which are composed of a variety of soluble rocks such as salt, gypsum, anhydrite, limestone, dolomite and quartzite, are fascinating areas of study. As karst rocks are abundant on the Earth's surface, the fast evolution of karst landscapes and the rapid flow of water through karst aquifers present challenges from a number of different perspectives. This collection of 25 papers deals with different aspects of these challenges, including karst geology, geomorphology and speleogenesis, karst hydrogeology, karst modelling, and karst hazards and management. Together these papers provide a state-of-the-art review of the current challenges and solutions in describing karst from a scientific perspective.

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Section: Karst Hydrogeologymentioning

confidence: 99%

Recent advances in karst research: from theory to fieldwork and applications

Parise

Gabrovšek

Kaufmann

et al. 2018

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“…Such calculations are needed to estimate contrasts in erosion rates along the passage wall. Some attempts to model flow structures and shear stress use computational fluid dynamics (CFD) to solve the Navier-Stokes equation for incompressible flow (Covington and Perne, 2015;Grm et al 2017;Hammer et al 2011). While these methods can calculate flow structures, they are computationally expensive and are not currently suitable for cross-section evolution over thousands of time steps.…”

Section: Introductionmentioning

confidence: 99%

“…Some attempts to model flow structures and shear stress use computational fluid dynamics (CFD) to solve the Navier‐Stokes equation for incompressible flow (Covington and Perne, 2015; Grm et al . 2017; Hammer et al . 2011).…”

Section: Introductionmentioning

confidence: 99%

Modeling cave cross‐section evolution including sediment transport and paragenesis

Cooper

Covington

2020

Earth Surf Processes Landf

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Summary Deposits within caves are often used to interpret past landscape evolution and climate conditions. However, cave passage shapes also preserve information about past conditions. Despite the usefulness of passage shape, no previous models simulate cave cross‐section evolution in a realistic manner. Here we develop a model for evolving cave passage cross‐sections using a shear stress estimation algorithm and a shear stress erosion rule. Our model qualitatively duplicates observed cave passage shapes so long as erosion rates vary with shear stress, as in the case of transport limited dissolution or mechanical erosion. This result provides further evidence that erosion rates within caves are not typically limited by surface reaction rates, even though current speleogenesis models predict surface‐rate limitation under most turbulent flow conditions. By adding sediment transport and alluviation to the model we successfully simulate paragenetic channels. Simulations duplicate the hypothesized dynamics of paragenesis, whereby: 1) the cross‐section of a phreatic passage grows until shear stress is sufficiently reduced that alluviation occurs, 2) the floor of the passage becomes armored and erosion continues on the ceiling and walls, 3) negative feedback produces an equilibrium cross‐sectional area such that shear stress is sufficient to transport incoming sediment. We derive an approximate scaling relationship that indicates that equilibrium paragenetic channel width scales with the square root of discharge, and weakly with the inverse of sediment supply. Simulations confirm this relationship and show that erosion mechanism, sediment size, and roughness are secondary controls. The inverse scaling of width with sediment supply in paragenetic channels contrasts with surface bedrock channels, which respond to larger sediment supplies by widening. Our model provides a first step in simulating cave cross‐section evolution and points to the need for a better understanding of the dominant erosion mechanisms in soluble bedrock channels. © 2020 John Wiley & Sons, Ltd.

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