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BayesLands, a Bayesian framework for Badlands that fuses information obtained from complex forward models with observational data and prior knowledge. As a proof-of-concept, we consider a synthetic and real-world topography with two free parameters, namely precipitation and erodibility, that we need to estimate through BayesLands. The results of the experiments shows that BayesLands yields a promising distribution of the parameters. Moreover, the challenge in sampling due to multi-modality is presented through visualizing a likelihood surface that has a range of suboptimal modes.
Badlands overview - Basin Genesis Hub presentation (2017)
Installation:
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Stepwise instructions to install BayesLands and it's prerequisite python packages are provided in the installation.txt file.
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bl_mcmc.py - File that executes an mcmc chain.
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bl_preproc - File includes functions to crop rescale or edit input topographies to be used in the model.
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bl_postproc - File used to produce figures for posterior distributions of the free parameters and time variant erosion deposition.
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bl_surflikl - File used to generate the likelihood surface of the free parameters.
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bl_topogenr - File used to generate the input and final-time topography used by the mcmc file.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License along with this program. If not, see http://www.gnu.org/licenses/lgpl-3.0.en.html.
If you come accross a bug or if you need some help compiling or using the code you can drop us a line at: - [email protected] - [email protected]
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Salles, T. & Hardiman, L.: Badlands: An open-source, flexible and parallel framework to study landscape dynamics, Computers & Geosciences, 91, 77-89, doi:10.1016/j.cageo.2016.03.011, 2016.
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Salles, T.: Badlands: A parallel basin and landscape dynamics model, SoftwareX, 5, 195–202, doi:10.1016/j.softx.2016.08.005, 2016.
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Salles, T., Ding, X. and Brocard, G.: pyBadlands: A framework to simulate sediment transport, landscape dynamics and basin stratigraphic evolution through space and time, PLOS ONE 13(4): e0195557, 2018.
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Salles, T., N. Flament, and D. Muller: Influence of mantle flow on the drainage of eastern Australia since the Jurassic Period, Geochem. Geophys. Geosyst., 18, doi:10.1002/2016GC006617, 2017 -- Supplementary materials: Australian Landscape Dynamic
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Salles, T., X. Ding, J.M. Webster, A. Vila-Concejo, G. Brocard and J. Pall: A unified framework for modelling sediment fate from source to sink and its interactions with reef systems over geological times, Nature Scientific Report, doi:10.1038/s41598-018-23519-8, 2018
When you use Badlands or BayesLands, please cite the above papers.