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|CSDMS meeting abstract presentation=From G.K. Gilbert's "The Convexity of Hilltops" to highly-optimized numerical implementations of drainage basin evolution, models of landscape evolution have been used to develop insight into the development of specific field areas, create testable predictions of landform development, demonstrate the consequences of our current theories for geomorphic processes, and spark imagination through hypothetical scenarios. In this talk, I discuss how the types questions tackled with landscape evolution models have changed as observational data (e.g., high-resolution topography) and computational technology (e.g., accessible high performance computing) have become available. I draw on a natural experiment in postglacial drainage basin incision and a synthetic experiment in a simple tectonic setting to demonstrate how landscape evolution models can be used to identify how much information the topography or other observable quantities provide in inferring process representation and tectonic history. In the natural example, comparison of multiple calibrated models provides insight into which process representations improve our ability to capture the geomorphic history of a site. Projections into the future characterize where in the landscape uncertainty in the model structure dominates over other sources of uncertainty. In the synthetic case, I explore the ability of a numerical inversion to recover geomorphic-process relevant (e.g., detachment vs. transport limited fluvial incision) and tectonically relevant (e.g., date of fault motion onset) system parameters. | |CSDMS meeting abstract presentation=From G.K. Gilbert's "The Convexity of Hilltops" to highly-optimized numerical implementations of drainage basin evolution, models of landscape evolution have been used to develop insight into the development of specific field areas, create testable predictions of landform development, demonstrate the consequences of our current theories for geomorphic processes, and spark imagination through hypothetical scenarios. In this talk, I discuss how the types questions tackled with landscape evolution models have changed as observational data (e.g., high-resolution topography) and computational technology (e.g., accessible high performance computing) have become available. I draw on a natural experiment in postglacial drainage basin incision and a synthetic experiment in a simple tectonic setting to demonstrate how landscape evolution models can be used to identify how much information the topography or other observable quantities provide in inferring process representation and tectonic history. In the natural example, comparison of multiple calibrated models provides insight into which process representations improve our ability to capture the geomorphic history of a site. Projections into the future characterize where in the landscape uncertainty in the model structure dominates over other sources of uncertainty. In the synthetic case, I explore the ability of a numerical inversion to recover geomorphic-process relevant (e.g., detachment vs. transport limited fluvial incision) and tectonically relevant (e.g., date of fault motion onset) system parameters. | ||
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|Working group member=Terrestrial Working Group | |Working group member=Terrestrial Working Group | ||
|CSDMS meeting presentation=Katherine Barnhart CTSP 2018 meeting.pdf | |||
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Latest revision as of 09:06, 6 August 2018
CTSP: Coupling of Tectonic and Surface Processes
Testing landscape evolution models with natural and synthetic experiments
Abstract
From G.K. Gilbert's "The Convexity of Hilltops" to highly-optimized numerical implementations of drainage basin evolution, models of landscape evolution have been used to develop insight into the development of specific field areas, create testable predictions of landform development, demonstrate the consequences of our current theories for geomorphic processes, and spark imagination through hypothetical scenarios. In this talk, I discuss how the types questions tackled with landscape evolution models have changed as observational data (e.g., high-resolution topography) and computational technology (e.g., accessible high performance computing) have become available. I draw on a natural experiment in postglacial drainage basin incision and a synthetic experiment in a simple tectonic setting to demonstrate how landscape evolution models can be used to identify how much information the topography or other observable quantities provide in inferring process representation and tectonic history. In the natural example, comparison of multiple calibrated models provides insight into which process representations improve our ability to capture the geomorphic history of a site. Projections into the future characterize where in the landscape uncertainty in the model structure dominates over other sources of uncertainty. In the synthetic case, I explore the ability of a numerical inversion to recover geomorphic-process relevant (e.g., detachment vs. transport limited fluvial incision) and tectonically relevant (e.g., date of fault motion onset) system parameters.
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Of interest for:
