LakeEnsemblR: an R package that facilitates ensemble modelling of lakes
Moore, Tadhg N.; Mesman, Jorrit P.; Ladwig, Robert; Feldbauer, Johannes; Olsson, Freya ORCID: https://orcid.org/0000-0002-0483-4489; Pilla, Rachel M.; Shatwell, Tom; Venkiteswaran, Jason J.; Delany, Austin D.; Dugan, Hilary; Rose, Kevin C.; Read, Jordan S.. 2021 LakeEnsemblR: an R package that facilitates ensemble modelling of lakes. Environmental Modelling & Software, 143, 105101. 14, pp. 10.1016/j.envsoft.2021.105101
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Abstract/Summary
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.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | 10.1016/j.envsoft.2021.105101 |
UKCEH and CEH Sections/Science Areas: | Water Resources (Science Area 2017-) |
ISSN: | 1364-8152 |
Additional Information. Not used in RCUK Gateway to Research.: | Open Access paper - full text available via Official URL link. |
Additional Keywords: | ensemble modeling, vertical one-dimensional lake model, R package, calibration, thermal structure, hydrodynamics |
NORA Subject Terms: | Ecology and Environment Computer Science |
Date made live: | 17 Jun 2021 11:51 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/530530 |
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