@misc{12230,
  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.}},
  author       = {{Moore, Tadhg N. and Mesman, Jorrit P. and Ladwig, Robert and Feldbauer, Johannes and Olsson, Freya and Pilla, Rachel M. and Shatwell, Tom and Venkiteswaran, Jason J. and Delany, Austin D. and Dugan, Hilary and Rose, Kevin C. and Read, Jordan S.}},
  booktitle    = {{Environmental modelling & software with environment data news}},
  issn         = {{1873-6726}},
  keywords     = {{Ensemble modeling, Vertical one-dimensional lake model, R package, Calibration, Thermal structure, Hydrodynamics}},
  publisher    = {{Elsevier BV}},
  title        = {{{LakeEnsemblR: An R package that facilitates ensemble modelling of lakes}}},
  doi          = {{10.1016/j.envsoft.2021.105101}},
  volume       = {{143}},
  year         = {{2021}},
}

@misc{12233,
  abstract     = {{The thermal structure in reservoirs affects the development of aquatic ecosystems, and can be substantially influenced by climate change and management strategies. We applied a two-dimensional hydrodynamic model to explore the response of the thermal structure in Germany's largest drinking water reservoir, Rappbode Reservoir, to future climate projections and different water withdrawal strategies. We used projections for representative concentration pathways (RCP) 2.6, 6.0 and 8.5 from an ensemble of 4 different global climate models. Simulation results showed that epilimnetic water temperatures in the reservoir strongly increased under all three climate scenarios. Hypolimnetic temperatures remained rather constant under RCP 2.6 and RCP 6.0 but increased markedly under RCP 8.5. Under the intense warming in RCP 8.5, hypolimnion temperatures were projected to rise from 5 °C to 8 °C by the end of the century. Stratification in the reservoir was projected to be more stable under RCP 6.0 and RCP 8.5, but did not show significant changes under RCP 2.6. Similar results were found with respect to the light intensity within the mixed-layer. Moreover, the results suggested that surface withdrawal can be an effective adaptation strategy under strong climate warming (RCP 8.5) to reduce surface warming and avoid hypolimnetic warming. This study documents how global scale climate projections can be translated into site-specific climate impacts to derive adaptation strategies for reservoir operation. Moreover, our results illustrate that the most intense warming scenario, i.e. RCP 8.5, demands far-reaching climate adaptation while the mitigation scenario (RCP 2.6) does not require adaptation of reservoir management before 2100.}},
  author       = {{Mi, Chenxi and Shatwell, Tom and Ma, Jun and Xu, Yaqian and Su, Fangli and Rinke, Karsten}},
  booktitle    = {{The science of the total environment : an international journal for scientific research into the environment and its relationship with man}},
  issn         = {{1879-1026}},
  keywords     = {{Rappbode Reservoir, Thermal structure, Climate change, CE-QUAL-W2, Selective water withdrawal}},
  number       = {{12}},
  publisher    = {{Elsevier BV}},
  title        = {{{Ensemble warming projections in Germany's largest drinking water reservoir and potential adaptation strategies}}},
  doi          = {{10.1016/j.scitotenv.2020.141366}},
  volume       = {{748}},
  year         = {{2020}},
}