scholarly journals Inverting Topography for Landscape Evolution Model Process Representation: 3. Determining Parameter Ranges for Select Mature Geomorphic Transport Laws and Connecting Changes in Fluvial Erodibility to Changes in Climate

2020 ◽  
Vol 125 (7) ◽  
Author(s):  
Katherine R. Barnhart ◽  
Gregory E. Tucker ◽  
Sandra G. Doty ◽  
Charles M. Shobe ◽  
Rachel C. Glade ◽  
...  
Keyword(s):  
Landscape Evolution ◽  
Evolution Model ◽  
Process Representation ◽  
Parameter Ranges ◽  
Transport Laws

scholarly journals Inverting Topography for Landscape Evolution Model Process Representation: 1. Conceptualization and Sensitivity Analysis

2020 ◽  
Vol 125 (7) ◽  
Author(s):  
Katherine R. Barnhart ◽  
Gregory E. Tucker ◽  
Sandra G. Doty ◽  
Charles M. Shobe ◽  
Rachel C. Glade ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Landscape Evolution ◽  
Evolution Model ◽  
Process Representation

scholarly journals Inverting Topography for Landscape Evolution Model Process Representation: 2. Calibration and Validation

2020 ◽  
Vol 125 (7) ◽  
Author(s):  
Katherine R. Barnhart ◽  
Gregory E. Tucker ◽  
Sandra G. Doty ◽  
Charles M. Shobe ◽  
Rachel C. Glade ◽  
...  
Keyword(s):  
Landscape Evolution ◽  
Evolution Model ◽  
Calibration And Validation ◽  
Process Representation

GRAINSIZE DEPENDENT TRANSPORT AND DEPOSITION IN A LANDSCAPE EVOLUTION MODEL

2019 ◽  
Author(s):  
Erica Emry ◽  
◽  
Kyungdoe Han ◽  
Michael Berry ◽  
Jolante van Wijk ◽  
...  
Keyword(s):  
Landscape Evolution ◽  
Evolution Model ◽  
Dependent Transport

SIGNUM: A Matlab, TIN-based landscape evolution model

2012 ◽  
Vol 45 ◽  
pp. 293-303 ◽  
Author(s):  
A. Refice ◽  
E. Giachetta ◽  
D. Capolongo
Keyword(s):  
Landscape Evolution ◽  
Evolution Model

scholarly journals Scaling and similarity of a stream-power incision and linear diffusion landscape evolution model

2018 ◽  
Vol 6 (3) ◽  
pp. 779-808 ◽  
Author(s):  
Nikos Theodoratos ◽  
Hansjörg Seybold ◽  
James W. Kirchner
Keyword(s):  
Steady State ◽  
Peclet Number ◽  
Degrees Of Freedom ◽  
Landscape Evolution ◽  
Initial Conditions ◽  
Evolution Model ◽  
Model Parameters ◽  
Stream Power ◽  
Linear Diffusion ◽  
Characteristic Scales

Abstract. The scaling and similarity of fluvial landscapes can reveal fundamental aspects of the physics driving their evolution. Here, we perform a dimensional analysis of the governing equation of a widely used landscape evolution model (LEM) that combines stream-power incision and linear diffusion laws. Our analysis assumes that length and height are conceptually distinct dimensions and uses characteristic scales that depend only on the model parameters (incision coefficient, diffusion coefficient, and uplift rate) rather than on the size of the domain or of landscape features. We use previously defined characteristic scales of length, height, and time, but, for the first time, we combine all three in a single analysis. Using these characteristic scales, we non-dimensionalize the LEM such that it includes only dimensionless variables and no parameters. This significantly simplifies the LEM by removing all parameter-related degrees of freedom. The only remaining degrees of freedom are in the boundary and initial conditions. Thus, for any given set of dimensionless boundary and initial conditions, all simulations, regardless of parameters, are just rescaled copies of each other, both in steady state and throughout their evolution. Therefore, the entire model parameter space can be explored by temporally and spatially rescaling a single simulation. This is orders of magnitude faster than performing multiple simulations to span multidimensional parameter spaces. The characteristic scales of length, height and time are geomorphologically interpretable; they define relationships between topography and the relative strengths of landscape-forming processes. The characteristic height scale specifies how drainage areas and slopes must be related to curvatures for a landscape to be in steady state and leads to methods for defining valleys, estimating model parameters, and testing whether real topography follows the LEM. The characteristic length scale is roughly equal to the scale of the transition from diffusion-dominated to advection-dominated propagation of topographic perturbations (e.g., knickpoints). We introduce a modified definition of the landscape Péclet number, which quantifies the relative influence of advective versus diffusive propagation of perturbations. Our Péclet number definition can account for the scaling of basin length with basin area, which depends on topographic convergence versus divergence.

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