Paper currently under review.
Clone the repo (in terminal)
cd my/fav/directory git clone https://github.com/mitchellmcm27/streambank-model.git
Start up Matlab, navigate to the newly created
streambank-model folder in your Matlab file tree
load “model_data.mat” into matlab, which contains the input data table:
Run the model on a single site:
animate(optional) tells the function to plot animations of simulations and enables
plt(optional) plot only major results (no animations)
Run the model on all sites:
output = train_model_monthly(model_data)
An example of the model output is saved in the
output folder. The model outputs a struct that contains 3 objects:
output.tbl: data table with rows for each modeled site and columns for input data, erosion rates, and modeled rates
output.mdl1: statistical model object, using K1 erodibility (see paper)
output.mdl2: statistical model object, using K2 erodibility (see paper)
After fitting a model, you can estimate erosion rates at any location using the following function. You can write a custom function or other scheme to use the fitted equation in any way you wish. This function is provided as an example of the model application and uses the same datasets that were used in model training and estimates erosion rates throughout an entire river reach.
train_model_monthlyare hard-coded into the function logic
This function is similar to
train_model_monthly except that, rather than fitting a model to observed erosion rates, a fitted model is applied to the input data. The function thus requires all of the same data used in model fitting, except for observed erosion rates. The function applies the model on an entire NHD Flowline (vector polyline) matching the COMID of the given row. The function samples a raster dataset representing tree cover at many locations along the reach (see
data folder). You must supply the path to the raster data in the function
sample_fc_at_points (in the
gis folder). Three geotiffs are provided in the
forest folder, sufficient to run the model with the given data (obtained from the UMD Global Land Cover Facility).
Many of the other Matlab functions/scripts in the repo are outdated or are used by the functions I mentioned here. Be careful deleting functions (sorry).
literature folder contains the manuscript based on this model (currently under review). The folder also contains a bibliographic database (.bib file), which contains references for all of the literature cited in the paper. You can browse the .bib file in JabRef or import it into Mendeley or Zotero. The .bib file is a BiBTeX database generated by Mendeley Desktop and cleaned up in JabRef.
The other folders contain supporting functions. Some are required for the model calculations, others are only for plotting, colorbars, etc.