LakeEnsemblR: An R package that facilitates ensemble modelling of lakes. (September 2021)

• Record Type: Journal Article
• Authors: 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.
• Is Part Of: Environmental modelling & software. Volume 143(2021)
• Publication Date: 2021-09
• Subjects: Ensemble modeling -- Vertical one-dimensional lake model -- R package -- Calibration -- Thermal structure -- Hydrodynamics; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2021.105101
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: 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. Graphical abstract: Image 1 Highlights: 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.