LakeEnsemblR: An R package that facilitates ensemble modelling of lakes

Model ensembles have several benefits compared to single-model applications but are not frequently used within the lake modelling community. Setting up and running multiple lake models can be challenging and time consuming, despite the many similarities between the existing models (forcing data, hyp...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2021-09, Vol.143, p.105101, Article 105101
Hauptverfasser: Moore, Tadhg N., Mesman, Jorrit P., Ladwig, Robert, Feldbauer, Johannes, Olsson, Freya, Pilla, Rachel M., Shatwell, Tom, Venkiteswaran, Jason J., Delany, Austin D., Dugan, Hilary, Rose, Kevin C., Read, Jordan S.
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Sprache:eng
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Zusammenfassung:Model ensembles have several benefits compared to single-model applications but are not frequently used within the lake modelling community. Setting up and running multiple lake models can be challenging and time consuming, despite the many similarities between the existing models (forcing data, hypsograph, etc.). Here we present an R package, LakeEnsemblR, that facilitates running ensembles of five different vertical one-dimensional hydrodynamic lake models (FLake, GLM, GOTM, Simstrat, MyLake). The package requires input in a standardised format and a single configuration file. LakeEnsemblR formats these files to the input required by each model, and provides functions to run and calibrate the models. The outputs of the different models are compiled into a single file, and several post-processing operations are supported. LakeEnsemblR's workflow standardisation can simplify model benchmarking and uncertainty quantification, and improve collaborations between scientists. We showcase the successful application of LakeEnsemblR for two different lakes. [Display omitted] •LakeEnsemblR is a new R package that lets users run ensembles of 1D lake models.•The package converts the user's standardised input to the files required by each model.•Executables and functions are provided to run and calibrate the models within R.•Multiple ensemble members are compiled in a single output file.
ISSN:1364-8152
1873-6726
1873-6726
DOI:10.1016/j.envsoft.2021.105101