The role of vegetation optimality in the Budyko framework
DOI10.5281/zenodo.7361655Zenodo7361655MaRDI QIDQ6705647
Dataset published at Zenodo repository.
Author name not available (Why is that?)
Publication date: 11 September 2022
In this study, we test how vegetation optimality explains convergence on the Budyko-curve. This is done for five study sites along the North Australian Tropical Transect, five catchments in Australia and a selection of catchments of the CAMELS-dataset. We test the following hypotheses: - Model simulations based on vegetation optimality lead to a better reproduction of the empirical Budyko curve than model simulations without self-optimized vegetation. - The empirical parameter nstays constant as climate changes, as long as vegetation cover and rooting depths stay constant. - Changes in n values are a result of slowly varying, long-term vegetation properties. How to use this project This project contains all pre- and post-processing scripts for the model runs to test our hypotheses. All final figures are in the notebooks, as well as the supplementary analyses. These scripts can be re-used for other applications. This is also a Renku project. Hence, to use this repository for your own analysis, create a free login for renku, then fork the project and modify it to your liking. The simplest way to start this project is right from the Renku platform - just click on the `Environments` tab and start a new session. This will start an interactive environment right in your browser. To work with the project anywhere outside the Renku platform, click the `Settings` tab where you will find the git repo URLs - use `git` to clone the project on whichever machine you want. Python and conda packages are in `requirements.txt` and `environment.yml`. Please consult the various documentation sources for renkulab(https://renkulab.io/).
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