LakeEnsemblR: An R package that facilitates ensemble modelling of lakes

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Tadhg N. Moore - , Dundalk Institute of Technology (Autor:in)
  • Jorrit P. Mesman - , University of Geneva, Uppsala University (Autor:in)
  • Robert Ladwig - , University of Wisconsin-Madison (Autor:in)
  • Johannes Feldbauer - , Professur für Limnologie (Gewässerökologie), Institut für Hydrobiologie (Autor:in)
  • Freya Olsson - , Centre for Ecology and Hydrology (Autor:in)
  • Rachel M. Pilla - , Miami University (Autor:in)
  • Tom Shatwell - , Helmholtz-Zentrum für Umweltforschung (UFZ) (Autor:in)
  • Jason J. Venkiteswaran - , Wilfrid Laurier University (Autor:in)
  • Austin D. Delany - , University of Wisconsin-Madison (Autor:in)
  • Hilary Dugan - , University of Wisconsin-Madison (Autor:in)
  • Kevin C. Rose - , Rensselaer Polytechnic Institute (Autor:in)
  • Jordan S. Read - , United States Geological Survey (Autor:in)

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.

Details

OriginalspracheEnglisch
Aufsatznummer105101
FachzeitschriftEnvironmental Modelling and Software
Jahrgang143
PublikationsstatusVeröffentlicht - Sept. 2021
Peer-Review-StatusJa

Schlagworte

Schlagwörter

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