Long-Term Landscape Evolution Modeling: The Role of Dynamic Topography, Flexural Isostasy, and Sea Level

Date of Award

December 2017

Degree Type


Degree Name

Doctor of Philosophy (PhD)


Earth Sciences


Robert Moucha


Dynamic Topography, Flexural Isostasy, Landscape Evolution

Subject Categories

Physical Sciences and Mathematics


Despite the wide variety of sub-disciplines and specializations which make up the Earth sciences, it is becoming increasingly important to acknowledge and understand the interconnectedness of the Earth systems or “spheres” which are collectively embodied by these sub-disciplines. These include, but are not limited to, the atmosphere, hydrosphere (rivers, lakes, etc.), cryosphere (glaciers and ice sheets), earth surface and shallow subsurface, crust, mantle, and core (inner and outer).

Our understanding of the interaction between different Earth spheres continues to improve in large part due to modeling and model coupling. Not unsurprisingly, Earth surface processes affect nearly every other Earth sphere – from the mantle to the atmosphere, and the importance of surface processes has been recognized in fields outside the geomorphological realm for centuries. However, it is only since the late 1960s that computer models of Earth surface processes were developed. Beginning with analytical models of processes such as river network development using fractal and geometric relationships, landscape evolution models have continued to become more computationally intensive, incorporating the complex interaction of erosion and sediment transport with geophysical phenomena such as flexural isostasy. However, even as of 2012, these models were still hindered by computational inefficiencies which made large scale modeling of certain processes, and process coupling, inadequate.

Fastscape, a landscape evolution model described by Braun and Willett (2012) used a new implicit algorithm to solve the governing equations of large-scale erosion in a fraction of the time of their predecessors. The FastScape model also solves for large scale processes such as flexural isostasy and hillslope diffusion, and was used by Braun et al., (2013) to model the influence of the convective mantle on erosion rates over a large, flat, area. Such a large model with high resolution was necessary to properly show how drainage capture in response to a migrating dome of uplift, as produced by mantle convection (dynamic topography), could drive increased erosion rates across a landscape.

In subsequent chapters I use a Fastscape-algorithm based model which I developed to explore varied responses to different landscape perturbations. The model solves for fluvial erosion using the FastScape implicit method, which is a rapid numerical solution for the nonlinear advection equation known as the stream power equation. However, the model described below is also unique in that it is one of few to incorporate large-scale deposition on continental margins, which here is modeled as a geometric shape (a cone), with coupled geodynamic effects including flexural isostasy.

In Chapter 1, I expand upon Braun et al., (2013) by modeling the landscape response to the passing of a dynamic topography wave of uplift in an (artificially generated) landscape with significant pre-existing relief, to show that significant erosional response does not need to be driven exclusively by drainage capture. A large, pronounced erosional response to dynamic topography can persist in areas with significant relief for millions of years driven principally by changes in relief. However, I also show, using a model of deposition, that such a response may be hard to recognize in the geologic record without also analyzing spatial differences in the pattern of deposition.

In a more direct study of the mantle’s influence on the surface, Rowley et al., (2013) released their paper on the influence of dynamic topography on the 3.5 Ma Organgeburg scarp in the southeastern United States. They showed that most of the varied topography along the 500+ km long wave-cut scarp could be explained by mantle convection models, which showed that dynamic topography changes caused most of the ~60 meter variation in elevation from south to north. However, there was still a bit left to explain; shorter wavelength, smaller amplitude deformations along the scarp, particularly in the northern portion, could not be attributed to mantle convection modeling alone.

In Moucha and Ruetenik (2017), we expanded upon this study by showing that the flexural response to erosion and deposition fully accounts for these smaller-wavelength fluctuations in elevation along the Orangeburg scarp. In Chapter 2, I show that 5 younger, enigmatically high shorelines in South Carolina could also have been significantly flexurally uplifted in response to loading and unloading along the U.S. Atlantic passive margin since 410 Ka, by up to 10 meters. The along-shore changes in elevation due to flexural deformation allow the modeled shorelines to better match the shape of observed shorelines.

Chapter 3 is a follow-up to a prior study by Val et al. (2016), which used cosmogenic nuclides erosion rates within the Iglesia basin of Argentina. They showed that a significant spike in erosion rates in the wedge-top may result from downstream deformation within this wedge-top basin. I use landscape evolution modeling to show that the resulting pattern in erosion rates may be more complex than what is described: downstream deformation can result in an upstream propagating wave of lower erosion rates, followed by a sudden spike in erosion rates. Additionally, I show that regions of low erosion rate correspond to surface uplift which results in the development of large, flat, surfaces (or paleo-surfaces) that can be identified in the landscape.

Taken together, I hope that these studies show the potential for landscape evolution modeling as it is applied to a variety of problems in tectonics, climate, and geodynamics, as well as the importance of coupling landscape evolution models to other large-scale Earth-system models.


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