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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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9000 Streampower-Diffusion Model Run Outputs

Authors: Martin, Jo;

9000 Streampower-Diffusion Model Run Outputs

Abstract

This dataset consists of the final topography from 9000 different model runs of a streampower-diffusion model. The model code used is attached in "diffusion_streampower_lem.py" and uses the LinearDiffuser, FlowAccumulator and FastscapeEroder components from the Landlab modeling framework. The models themselves were run with the LandlabBatcher utility, which used the model_params.json to define the parameters of the models and model_runs.db to keep track of which model runs correspond to what parameters and other metadata. The model runs use the follwing parameters, taken after Perron et al. 2008 (parameters also described in the model_params.json, model_runs.db, and model_runs.csv files) Parameter Value Rows 300 Columns 100 Grid Spacing 5 Meter Runtime 3,000,000 Years Timestep 500 Years Uplift Rate 0.001 Meters/Year Diffusivity 0.005-0.02 Meters^2/Year (30 evenly spaced values) Streampower K 0.00015-0.002 m^(0.4)/Year (30 evenly spaced valyes) Streampower m 0.3 Streampower n 0.7 Each set of parameters was run for 10 different random initial topographys, controlled by an expliclty set random seed. Each model run is saved as numpy array and labeled by a UUID. Use the model_run_params table in the model_runs.db, or the model_runs.csv file to match specific parameter sets to model run UUIDs. The model run .npy files are in the model_run_topography.tar.gz file

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average