Model:DrEICH algorithm

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DrEICH algorithm




Metadata

Also known as Channel extraction tool
Model type Tool
Model part of larger framework
Incorporated models or components:
Spatial dimensions 2D
Spatial extent Landscape-Scale
Model domain Terrestrial, Hydrology
One-line model description Algorithm for extracting channel networks from high resolution topographic data
Extended model description This tool uses chi river profile analysis to predict channel head locations across a landscape and therefore allow the extraction of river networks. It is most suitable for use with high resolution LiDAR (1m) DEMs. The model requires an input DEM in float format and will output the extracted channel heads and networks, also in float format. For detailed information about how to use this tool please refer to the documentation (http://www.geos.ed.ac.uk/~smudd/LSDTT_docs/html/channel_heads.html)

and to the associated paper (http://onlinelibrary.wiley.com/doi/10.1002/2013WR015167/full).

Keywords:

geomorphology, hydrological, bedrock channel erosion,


First name Fiona
Last name Clubb
Type of contact Model developer
Institute / Organization University of Edinburgh
Postal address 1 Geography Building
Postal address 2 Drummond Street
Town / City Edinburgh
Postal code EH8 9XP
State
Country United Kingdom
Email address f.clubb@ed.ac.uk
Phone +44 (0)131 650 9170
Fax


First name Simon
Last name Mudd
Type of contact Model developer
Institute / Organization University of Edinburgh
Postal address 1 Rm 1.05d Geography Building
Postal address 2 Drummond Street
Town / City Edinburgh
Postal code EH8 9XP
State
Country United Kingdom
Email address simon.m.mudd@ed.ac.uk
Phone +44 (0)131 650 2535
Fax


First name David
Last name Milodowski
Type of contact Model developer
Institute / Organization University of Edinburgh
Postal address 1 Geography Building
Postal address 2 Drummond Street
Town / City Edinburgh
Postal code EH8 9XP
State
Country United Kingdom
Email address D.T.Milodowski@ed.ac.uk
Phone +44 (0)131 650 9170
Fax


Supported platforms Unix, Linux
Other platform
Programming language C++
Other program language
Code optimized Single Processor
Multiple processors implemented
Nr of distributed processors
Nr of shared processors
Start year development 2012
Does model development still take place? Yes
If above answer is no, provide end year model development
Code development status As is, no updates are provided
When did you indicate the 'code development status'? 2020
Model availability As code
Source code availability
(Or provide future intension)
Through CSDMS repository
Source web address
Source csdms web address https://github.com/csdms-contrib/dreich_algorithm
Program license type GPL v2
Program license type other
Memory requirements Varies depending on the input DEM size
Typical run time Around 10 minutes to half an hour


Describe input parameters The input file is a DEM in .flt format. A driver text file is also required which contains the parameters used for the extraction. Information on the parameters needed in the driver file is available in the documentation (http://www.geos.ed.ac.uk/~smudd/LSDTT_docs/html/channel_heads.html).
Input format
Other input format float
Describe output parameters
Output format
Other output format float
Pre-processing software needed? Yes
Describe pre-processing software A chi analysis of the landscape must first be performed to get the correct m/n value for the landscape. This can be done using the chi analysis toolkit available on CSDMS (https://csdms.colorado.edu/wiki/Model:Chi_analysis_tools).
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 This tool works under the assumption that the channels incise approximately based on the stream power law. It identifies the channel head as the upstream limit of fluvial incision based on the chi profile of the channel.
Describe key physical parameters and equations There are two user-defined parameters which need to be defined in the model.

1) The m/n value. This parameter is in the steady state stream power equation for channel slope: dz/dx = (U/K)^1/n * A(x)^(-m/n), where U is rock uplift rate, K is an erodibility coefficient, A is drainage area, and m and n are constants. The best fit m/n value for each landscape must be determined using the chi analysis toolkit (https://csdms.colorado.edu/wiki/Model:Chi_analysis_tools) before the DrEICH algorithm can be run. The routines in the chi analysis toolkit provide a statistical method of identifying the m/n value for the landscape.

2) The number of linked pixels with a contour curvature > 0.1 m^-1. The first stage in the DrEICH algorithm is identifying valleys with positive curvature in which to run the model. A valley is selected to contain a channel head if there are more than a defined number of pixels in that valley with a contour curvature greater than 0.1. This parameter does not affect the location of the channel head within each valley, but does affect how many valleys will be selected. A default value of 10 is suggested, but this may need to vary depending on the relief of the landscape (a lower value of 5 may be more appropriate for lower-relief landscapes).

Describe length scale and resolution constraints This algorithm attempts to identify channel head, which are features present on a metre to sub-metre scale. Therefore, the accuracy of the prediction will decrease as the DEM resolution becomes coarser. 1 to 2m resolution DEMs are suggested as appropriate for use with this tool.
Describe time scale and resolution constraints No time resolution constraints as this software performs topographic analysis.
Describe any numerical limitations and issues With larger DEMs this tool will take longer to run - it takes around half an hour to run with a 1m DEM with 23000 rows and 18000 columns. Documentation is available for guidance.


Describe available calibration data sets Topographic analysis; no calibration required.
Upload calibration data sets if available:
Describe available test data sets Two test DEMs are included in the repository, both from Wayne National Forest, Ohio. Two example driver files, one for each DEM, are also included. These DEMs are the same as are used in the associated manuscript (http://onlinelibrary.wiley.com/doi/10.1002/2013WR015167/full) so that the resulting channel networks can be compared with figures from the paper.
Upload test data sets if available:
Describe ideal data for testing Any 1m resolution digital elevation model.


Do you have current or future plans for collaborating with other researchers? Yes
Is there a manual available? Yes
Upload manual if available:
Model website if any http://www.geos.ed.ac.uk/~smudd/LSDTT_docs/html/channel_heads.html
Model forum / discussion board
Comments Active development and maintenance of the code has moved to GitHub and been incorporated within broader LSDTopoTools software package: https://github.com/LSDtopotools/LSDTopoTools2


This part will be filled out by CSDMS staff

OpenMI compliant No but possible
BMI compliant No but possible
WMT component No but possible
PyMT component
Can be coupled with:
Model info
Fiona Clubb
Mudd, Milodowski
Citation indices DrEICH algorithm
Nr. of pubs: 3
Citations: 65
h-index: 3
Qrcode DrEICH algorithm.png
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Introduction

History

References




Citation indices DrEICH algorithm
Nr. of pubs: 3
Citations: 65
h-index: 3



Featured publication(s)YearModel describedType of ReferenceCitations
Clubb, Fiona J.; Mudd, Simon M.; Milodowski, David T.; Hurst, Martin D.; Slater, Louise J.; 2014. Objective extraction of channel heads from high-resolution topographic data. Water Resources Research, 50, 4283–4304. 10.1002/2013WR015167
(View/edit entry)
2014DrEICH algorithm
Model overview 54
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