This fileset contains all of the model output used to generate Figure 4, and its companions in the supporting information, from Glade, Shobe, Anderson, and Tucker (submitted).
These figures use output from the BlockLab landscape evolution model (https://doi.org/10.5281/zenodo.2584363). All model output required to generate Figure 4 from the manuscript, and the accompanying plots from the supporting information, is included here.
The model output consists of time series of topographic elevation for the channel (the entire channel profile) and three points along the hillslope, which are user-determined in the driver script when running the BlockLab model.
Three types of Python 2.7 scripts are presented here. The first, "reorganize_channel_elevation_timeseries.py", only needed if dealing with raw model output, aggregates channel elevation data from the many .npy binaries exported by the BlockLab model and exports this data as three .npy binaries, one for the complete elevation history of each of three chosen channel nodes. The same goes for "reorganize_channel_cover_timeseries.py", which serves the same function for extracting information about channel bed cover over time.
The third type of script, called for example "erosion_blocky_1_meter.py" (the file name changes for each model realization), plots the model output. "Erosion" figures consist of 10-year and 1000-year averaged erosion rates at three points on the channel and hillslope. "Cover" figures show channel erosion rates and channel cover fractions averaged over the same 10- and 1000-year moving windows.
Each .zip file contains a folder with the data and plotting scrips for a single model realization. Eight model realizations were presented in the paper: Four "blocky" simulations in which blocks of rock were delivered from a resistant caprock to the landscape, and four "control" simulations in which blocks of caprock immediately turned to soil upon their release. For each of these two scenarios, we tested four different values for the caprock thickness (and therefore block size): 0.1 m, 0.5 m, 0.8 m, and 1.0 m.
Please see the associated paper for more information about the model and parameter values.
Funding
NSF EAR-1323137, EAR-1331828, and EAR-1529284. CMS was supported by a National Defense Science and Engineering Graduate Fellowship and a University of Colorado Chancellor’s Fellowship.