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

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.