LakeEnsemblR: An R package that facilitates ensemble modelling of lakes

被引:22
|
作者
Moore, Tadhg N. [1 ,12 ]
Mesman, Jorrit P. [2 ,3 ]
Ladwig, Robert [4 ]
Feldbauer, Johannes [5 ]
Olsson, Freya [6 ]
Pilla, Rachel M. [7 ]
Shatwell, Tom [8 ]
Venkiteswaran, Jason J. [9 ]
Delany, Austin D. [4 ]
Dugan, Hilary [4 ]
Rose, Kevin C. [10 ]
Read, Jordan S. [11 ]
机构
[1] Ctr Freshwater & Environm Studies, Dundalk Inst Technol, Dundalk, Co Louth, Ireland
[2] Univ Geneva, Dept FA Forel Environm & Aquat Sci, Geneva, Switzerland
[3] Uppsala Univ, Dept Ecol & Genet, Uppsala, Sweden
[4] Univ Wisconsin, Ctr Limnol, Madison, WI 53706 USA
[5] Tech Univ Dresden, Inst Hydrobiol, Dresden, Germany
[6] UK Ctr Ecol & Hydrol, Lancaster Environm Ctr, Lancaster, England
[7] Miami Univ, Dept Biol, Oxford, OH 45056 USA
[8] UFZ Helmholtz Ctr Environm Res, Dept Lake Res, Magdeburg, Germany
[9] Wilfrid Laurier Univ, Dept Geog & Environm Studies, Waterloo, ON, Canada
[10] Rensselaer Polytech Inst, Dept Biol Sci, Troy, NY USA
[11] US Geol Survey, Middleton, WI USA
[12] Virginia Tech, Dept Biol Sci, Blacksburg, VA 24061 USA
基金
美国国家科学基金会; 加拿大自然科学与工程研究理事会;
关键词
Ensemble modeling; Vertical one-dimensional lake model; R package; Calibration; Thermal structure; Hydrodynamics; CLIMATE-CHANGE; WATER-QUALITY; CURRENT STATE; FLAKE MODEL; UNCERTAINTY; ECOSYSTEM; WEATHER; ICE; SIMULATIONS; DYNAMICS;
D O I
10.1016/j.envsoft.2021.105101
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页数:14
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