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From CSDMS
Edinburgh +
Active development and maintenance of the code has moved to GitHub and been incorporated within broader LSDTopoTools software package: https://github.com/LSDtopotools/LSDTopoTools2 +
United Kingdom +
University of Edinburgh +
Drummond Street +
EH8 9XP +
Model developer +
No but possible +
No but possible +
No but possible +
Single Processor +
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10:34:47, 27 May 2014 +
Topographic analysis; no calibration required. +
Two test DEMs are included in the reposito … 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.n be compared with figures from the paper. +
Any 1m resolution digital elevation model. +
The input file is a DEM in .flt format. A … 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).smudd/LSDTT_docs/html/channel_heads.html). +
There are two user-defined parameters whic … There are two user-defined parameters which need to be defined in the model. </br>1) The m/n value. This parameter is in the steady state stream power equation for channel slope:</br>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.</br></br>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).ore appropriate for lower-relief landscapes). +
This algorithm attempts to identify channe … 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.ted as appropriate for use with this tool. +
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. +
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). +
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. +
No time resolution constraints as this software performs topographic analysis. +
As is, no updates are provided +
This tool uses chi river profile analysis … 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)</br>and to the associated paper (http://onlinelibrary.wiley.com/doi/10.1002/2013WR015167/full)..wiley.com/doi/10.1002/2013WR015167/full). +
Fiona +
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float +
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0.25 +
Varies depending on the input DEM size +
Channel extraction tool +
algorithm +, data +, chi river profile +, river profile analysis +, predict channel head +, channel head locations +, chi river +, river profile +, profile analysis +, analysis to predict +, river networks +, predict channel +, head locations +, extraction of river +, river +, extracted channel heads +, high resolution lidar +, geomorphology +, hydrological +, bedrock channel erosion + and dreich algorithm +
As code +
Tool +
http://www.geos.ed.ac.uk/~smudd/LSDTT_docs/html/channel_heads.html +
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02:15:51, 17 September 2020 +
3 +
Algorithm for extracting channel networks from high resolution topographic data +
float +
Geography Building +
Drummond Street +
EH8 9XP +
false +
true +
GPL v2 +
Around 10 minutes to half an hour +
Through CSDMS repository +
https://github.com/csdms-contrib/dreich_algorithm +
Landscape-Scale +
2012 +
Model developer +
