Property:Extended model description
From CSDMS
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P
This class implements Voller, Hobley, and Paola’s experimental matrix solutions for flow routing. The method works by solving for a potential field at all nodes on the grid, which enforces both mass conservation and flow downhill along topographic gradients. It is order n and highly efficient, but does not return any information about flow connectivity.
Options are permitted to allow “abstract” routing (flow enforced downslope, but no particular assumptions are made about the governing equations), or routing according to the Chezy or Manning equations. This routine assumes that water is distributed evenly over the surface of the cell in deriving the depth, and does not assume channelization. You will need to back- calculate channel depths for yourself using known widths at each node if that is what you want. +
F
This class uses the Braun-Willett Fastscape approach to calculate the amount of erosion at each node in a grid, following a stream power framework. This should allow it to be stable against larger timesteps than an explicit stream power scheme. +
A
This code creates the channel centerline (i.e., the line equidistant between two banks) for a single thread-channel, using a second-order autoregressive model. The code implements a model for random centerlines proposed by Ferguson, R. I. (1976) Disturbed periodic model for river meanders, Earth Surface Processes 1(4), 337-347, doi:10.1002/esp.3290010403. This implementation also includes (1) controls for the node spacing and extent of channels, (2) removal of self-intersecting (cutoff) loops from modeled centerlines, and (3) a wrapper script to sweep model parameter space and generate alternate realizations using different random disturbance series. +
V
This code is based on Cellular Automata Tree Grass Shrub Simulator (CATGraSS). It simulates spatial competition of multiple plant functional types through establishment and mortality. In the current code, tree, grass and shrubs are used. +
H
This component calculates Hack’s law parameters for drainage basins.
Hacks law is given as
L = C * A**h
Where L is the distance to the drainage divide along the channel, A is the drainage area, and C are parameters.
The HackCalculator uses a ChannelProfiler to determine the nodes on which to calculate the parameter fit. +
C
This component calculates chi indices, sensu Perron & Royden, 2013, for a Landlab landscape. +
S
This component calculates steepness indices, sensu Wobus et al. 2006, for a Landlab landscape. Follows broadly the approach used in GeomorphTools, geomorphtools.org. +
F
This component generates random numbers using the Weibull distribution
(Weibull, 1951). No particular units must be used, but it was written with
the fire recurrence units in time (yrs).
Using the Weibull Distribution assumes two things: All elements within the study area have the same fire regime. Each element must have (on average) a constant fire regime during the time span of the study.<br>
As of Sept. 2013, fires are considered instantaneous events independent of
other fire events in the time series. +
D
This component identifies depressions in a topographic surface, finds an outlet for each depression. If directed to do so (default True), and the component is able to find existing routing fields output from the 'route_flow_dn' component, it will then modify the drainage directions and accumulations already stored in the grid to route flow across these depressions. +
This component implements a depth and slope dependent linear diffusion rule in the style of Johnstone and Hilley (2014). Soil moves with a prescribed exponential vertical velocity profile. Soil flux is dictated by a diffusivity, K, and increases linearly with topographic slope. +
E
This component implements exponential weathering of bedrock on hillslopes. Uses exponential soil production function in the style of Ahnert (1976).
Consider that w_0 is the maximum soil production rate and that d* is the characteristic soil production depth. The soil production rate w is given as a function of the soil depth d,
w = w_0^(-d/d*)
The ExponentialWeatherer only calculates soil production at core nodes. +
L
This component is closely related to the FlowAccumulator, in that this is accomplished by first finding flow directions by a user-specified method and then calculating the drainage area and discharge. However, this component additionally requires the passing of a function that describes how discharge is lost or gained downstream, f(Qw, nodeID, linkID, grid). See examples at https://github.com/landlab/landlab/blob/master/landlab/components/flow_accum/lossy_flow_accumulator.py to see how this works in practice. +
F
This components finds the steepest single-path steepest descent flow directions. It is equivalent to D4 method in the special case of a raster grid in that it does not consider diagonal links between nodes. For that capability, use FlowDirectorD8. +
This is a 1DV wave-phase resolving numerical model for fluid mud transport based on mixture theory with boundary layer approximation. The model incorporates turbulence-sediment interaction, gravity-driven flow, mud rheology, bed erodibility and the dynamics of floc break-up and aggregation. +
W
This is a Java Applet that allows the user to change different parameters (such as rainfall, erodibility, tectonic uplift) and watch how the landform evolve over time under different scenarios. It is based on a Cellular Automata algorithm. Two versions are available: linear and non-linear. Details can be found in:
Luo, W., Peronja, E., Duffin, K., Stravers, A. J., 2006, Incorporating Nonlinear Rules in a Web-based Interactive Landform Simulation Model (WILSIM), Computers and Geosciences, v. 32, n. 9, p. 1512-1518 (doi: 10.1016/j.cageo.2005.12.012).
Luo, W., K.L. Duffin, E. Peronja, J.A. Stravers, and G.M. Henry, 2004, A Web-based Interactive Landform Simulation Model (WILSIM), Computers and Geosciences. v. 30, n. 3, p. 215-220. +
G
This is a Landlab wrapper for A Wickert's gFlex flexure model (Wickert et al., submitted to Geoscientific Model Development). The most up-to-date version of his code can be found at github.com/awickert/gFlex.
This Landlab wrapper will use a snapshot of that code, which YOU need to install on your own machine. A stable snapshot of gFlex is hosted on PyPI, which is the recommended version to install.
If you have pip (the Python package install tool), simply run 'pip install gFlex' from a command prompt.
Alternatively, you can download and unpack the code (from github, or with PyPI, pypi.python.org/pypi/gFlex/), then run 'python setup.py install'. +
C
This is a special case of the Regional Ocean Modeling System(ROMS). The National Ocean Service presently has an Operational Forecast System (CBOFS) for the Chesapeake Bay which generates only water levels and depth‐integrated currents. As a next generation system, a fully three‐dimensional, baroclinic Forecast System (CBOFS2) was developed, calibrated and validated; this system will produce water levels, currents, temperature and salinity. First, a two‐month tides only simulation was conducted to validate the water levels and currents and thereafter, a synoptic hindcast simulation from June 01, 2003–September 01, 2005 was conducted to validate water levels, currents, temperature and salinity. Upon comparison with observations, CBOFS2 for the most part met the target NOS water level error criteria and for current error, the criteria were met exceptionally well; the temperature and salinity errors were frequently less than 1 C and 3 PSU respectively. Hence, the predictive accuracy of CBOFS2 warranted it being accepted as a suitable three‐dimensional upgrade to CBOFS.
Please see https://csdms.colorado.edu/wiki/Model:ROMS for details. +
N
This is a time-stepping point model which uses linear finite elements to determine the vertical structure of the horizontal components of velocity and density under specified surface forcing. Both a quadratic closure scheme and the level 2.5 closure scheme of Mellor and Yamada are used in this code. +
G
This is a tool that I created to help find knickpoints based on the curvature of a landscape. It provides information about a stream including, knickpoint locations, Elevation/distance that can be used to create longitudinal profiles, XYvalues of all the cells in a stream path, etc. The tool uses built-in tools for ArcGIS 10.x (so you must run this on a machine with ArcGIS 10.x installed), but it is written in python. I used it with a 1m LiDAR DEM, so I'm not totally sure how well it will pick out knickpoints on coarser gridded DEMs. +
A
This is an Arctic-delta reduced-complexity model that can reproduce the 2-m ramp feature observed in most Arctic deltas. The model is built by first reconstructing from published descriptions of the DeltaRCM-Arctic model (Lauzon et al., GRL, 2019), which is, in turn, based on DeltaRCM by Liang et al. (Esurf, 2015). All the modifications and refinements leading to this model (ArcDelRCM.jl) are detailed in a manuscript submitted to Earth Surface Dynamics journal for publication (Chan et al., 2022: esurf-2022-25). Options are retained to run this model with the "DeltaRCM-Arctic" (reconstruction) setting. The code is written purely in Julia language. +
