Approximate Bayesian Computation with Random Forest and Sensitivity Analysis for the calibration of a complex aquatic ecological model

DOI

This dataset gather scripts and data files that are related to the calibration of the model Delft3D-BLOOM on the case study of Lake Champs-sur-Marne with the ABC-RF (Approximate Bayesian Computation – Random Forest) method coupled with sensitivity analysis.

There are several types of files: (1) observed and simulated data, that is the data coming from the set of 30000 simulations that have been performed to make the calibration; (2) R and matlab scripts for the application of the calibration strategy and the analysis/plot of the results; (3) files with results of the calibration runs performed for the calibration of the model BLOOM on the case study of Lake Champs-sur-Marne.

Delft3D-WAQ (DELWAQ), 3426

Identifier
DOI https://doi.org/10.15454/QSR3YO
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.15454/QSR3YO
Provenance
Creator Piccioni, Francesco; Casenave, Céline ORCID logo; Baragatti, Meïli; Cloez, Bertrand; Vinçon-Leite, Brigitte ORCID logo
Publisher Recherche Data Gouv
Contributor Casenave, Céline; Debaly, Zinsou Max
Publication Year 2022
Rights etalab 2.0; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/etalab-2.0.html
OpenAccess true
Contact Casenave, Céline (INRAE)
Representation
Resource Type Dataset
Format application/zip; application/pdf
Size 234090160; 181531
Version 2.0
Discipline Geosciences; Mathematics; Earth and Environmental Science; Environmental Research; Natural Sciences