LakeEnsemblR: An R package that facilitates ensemble modelling of lakes

Tadhg N. Moore, Jorrit P. Mesman, Robert Ladwig, Johannes Feldbauer, Freya Olsson, Rachel M. Pilla, T. Shatwell, J. Venkiteswaran, Austin Delany, H. Dugan, K. Rose, J. Read
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引用次数: 16

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 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 files 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, sharing of output files, and improve collaborations between aquatic scientists. We showcase the successful application of LakeEnsemblR for two different lakes.
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LakeEnsemblR:一个R包,用于促进湖泊的集成建模
与单模型应用相比,模型集成有几个好处,但在湖泊建模界并不经常使用。尽管现有模型之间有许多相似之处(强迫数据、hypograph等),但建立和运行多个湖泊模型可能是具有挑战性和耗时的。在这里,我们提出了一个R包,lakakeensemblr,它有助于运行五种不同的一维水动力湖泊模型(FLake, GLM, GOTM, Simstrat, MyLake)的集成。该包需要以标准化格式和单个配置文件进行输入。LakeEnsemblR将这些文件格式化为每个模型所需的输入文件,并提供运行和校准模型的功能。不同模型的输出被编译成一个文件,并支持多种后处理操作。LakeEnsemblR的工作流程标准化可以简化模型基准测试,共享输出文件,并改善水生科学家之间的合作。我们展示了lakakeensemblr在两个不同湖泊的成功应用。
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