4.7 Article

LakeEnsemblR: An R package that facilitates ensemble modelling of lakes

Journal

ENVIRONMENTAL MODELLING & SOFTWARE
Volume 143, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2021.105101

Keywords

Ensemble modeling; Vertical one-dimensional lake model; R package; Calibration; Thermal structure; Hydrodynamics

Funding

  1. WATExR project, ERA4CS, an ERA-NET
  2. MINECO
  3. FORMAS
  4. BMBF
  5. EPA
  6. RCN
  7. IFD
  8. European Union [690,462]
  9. NSF [DEB-1926050, DBI-1933016]
  10. European Union'sHorizon 2020Research and Innovation Programme under the Marie Sklodowska-Curie grant [722518]
  11. National Science Foundation ABI development grant [DBI 1759865]
  12. European Social Fund
  13. Sentinel North Research Internship Scholarship program for foreign students at Universite Laval
  14. German Science Foundation [DFG KI 853/13-1, CDZ 1259]
  15. Natural Sciences and Engineering Research Council of Canada [RGPIN-2018-06389]
  16. National Science Foundation [1754265, 1638704, 1761805]
  17. GLEON
  18. Direct For Biological Sciences
  19. Division Of Environmental Biology [1754265] Funding Source: National Science Foundation
  20. Direct For Computer & Info Scie & Enginr
  21. Div Of Information & Intelligent Systems [1761805] Funding Source: National Science Foundation
  22. Emerging Frontiers
  23. Direct For Biological Sciences [1638704] Funding Source: National Science Foundation

Ask authors/readers for more resources

Model ensembles have benefits compared to single-model applications, but are not frequently used in lake modeling. LakeEnsemblR is an R package that facilitates running ensembles of different vertical one-dimensional hydrodynamic lake models, standardizing input and workflow to simplify model benchmarking and improve collaborations between scientists.
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 onedimensional 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.

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