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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Groundwater level modelling ensemble for Bayesian Model Averaging

Authors: Wöhling, Thomas;

Groundwater level modelling ensemble for Bayesian Model Averaging

Abstract

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 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.

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Keywords

Groundwater/analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average