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: [e-mail] 1) MODEL ENSEMBLESThe 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.