Groundwater level modelling ensemble for Bayesian Model Averaging

This repository contains data files for the paper entitled:
"Comparing physics-based, conceptual and machine-learning models to predict groundwater levels by BMA"

written by: Thomas Wöhling, Alvaro Oliver Crespo Delgadillo, Moritz Kraft and Anneli Guthke

submitted to the Journal Groundwater (Wiley). 
For further enquiries contact: thomas.woehling@tu-dresden.de

1) MODEL ENSEMBLES
The folder ENSEMBLES contains 5 Matlab-structures with model ensembles.
Each ensemble consists of model realizations of 6 different models (see paper).

Each structure contains the following variables:

    *.GW_levels ... a matrix of [m x n] model realizations (simulations of groundwater levels in [m.a.s.l.]), where
                m = number of realitaions and n = number of time steps
    *.Model_Id ... signifies a [n,1] vector of model numbers of the ensemble members (1..6)
    *.Time_vector ... time vector [1,n] in Matlab format
    *.Observations ... the [1,n] vector of observed groundwater levels in [m.a.s.l.]
    *.LL ... the [m,1] vector of likelihood values for each model realization
    *.BMA_weights ... the [1,6] vector of BMA model weights

Note, in case of the "All_wells"- Ensemble, the observation vector is a [4,n] matrix.