Model:Meanderpy

Meanderpy

Also known as
Model type	Single
Model part of larger framework

Incorporated models or components:

Spatial dimensions	3D
Spatial extent	Landscape-Scale, Reach-Scale
Model domain	Terrestrial
One-line model description	A simple kinematic model of meandering
Extended model description	"meanderpy" is a Python module that implements a simple numerical model of meandering, the one described by Howard & Knutson in their 1984 paper "Sufficient Conditions for River Meandering: A Simulation Approach" (https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/WR020i011p01659). This is a kinematic model that is based on computing migration rate as the weighted sum of upstream curvatures; flow velocity does not enter the equation. Curvature is transformed into a 'nominal migration rate' through multiplication with a migration rate (or erodibility) constant; in the Howard & Knutson (1984) paper this is a nonlinear relationship based on field observations that suggested a complex link between curvature and migration rate. In the 'meanderpy' module we use a simple linear relationship between the nominal migration rate and curvature, as recent work using time-lapse satellite imagery suggests that high curvatures result in high migration rates (Sylvester et al., 2019).

Keywords:	fluvial morphodynamics, meandering,

Name	Zoltan Sylvester
Type of contact	Model developer
Institute / Organization	The University of Texas at Austin
Postal address 1
Postal address 2
Town / City	Austin
Postal code	78713-8924
State	Texas
Country	United States
Email address	zoltan.sylvester@beg.utexas.edu
Phone
Fax

Supported platforms	Unix, Linux, Mac OS
Other platform
Programming language	Python
Other program language
Code optimized	Single Processor
Multiple processors implemented
Nr of distributed processors
Nr of shared processors
Start year development	2018
Does model development still take place?	Yes
If above answer is no, provide end year model development
Code development status	Active
When did you indicate the 'code development status'?	2020
Model availability	As code
Source code availability (Or provide future intension)	Through web repository
Source web address	https://github.com/zsylvester/meanderpy
Source csdms web address
Program license type	Apache public license
Program license type other
Memory requirements	--
Typical run time	minutes

Describe input parameters	channel width (m), channel depth (m), padding (number of nodepoints along centerline), sampling distance along centerline, number of iterations, dimensionless Chezy friction factor, threshold distance at which cutoffs occur, migration rate constant (m/s), vertical slope-dependent erosion rate constant (m/s), time step (s), density of water (kg/m3), which time steps will be saved, approximate number of bends you want to model, initial slope (setting this to non-zero results in instabilities in long runs)
Input format	ASCII
Other input format
Describe output parameters	channel centerlines; 3d model
Output format	Binary
Other output format
Pre-processing software needed?	No
Describe pre-processing software
Post-processing software needed?	No
Describe post-processing software
Visualization software needed?	No
If above answer is yes
Other visualization software

Describe processes represented by the model	Simple linear relationship between the nominal migration rate and curvature
Describe key physical parameters and equations	--
Describe length scale and resolution constraints	--
Describe time scale and resolution constraints	--
Describe any numerical limitations and issues	--

Describe available calibration data sets
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Describe available test data sets
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Describe ideal data for testing

Do you have current or future plans for collaborating with other researchers?

Is there a manual available?	No
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Model website if any
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Featured publication(s)	Year	Model described	Type of Reference	Citations
Sylvester, Zoltán; Durkin, Paul; Covault, Jacob A.; 2019. High curvatures drive river meandering. Geology, 47, 263–266. 10.1130/G45608.1 (View/edit entry)	2019	Meanderpy	Model overview	67
See more publications of Meanderpy