Articles | Volume 29, issue 4
https://doi.org/10.5194/hess-29-1183-2025
https://doi.org/10.5194/hess-29-1183-2025
Research article
 | 
03 Mar 2025
Research article |  | 03 Mar 2025

Learning from a large-scale calibration effort of multiple lake temperature models

Johannes Feldbauer, Jorrit P. Mesman, Tobias K. Andersen, and Robert Ladwig

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Cited articles

Andersen, T. K., Bolding, K., Nielsen, A., Bruggeman, J., Jeppesen, E., and Trolle, D.: How morphology shapes the parameter sensitivity of lake ecosystem models, Environ. Modell. Softw., 136, 104945, https://doi.org/10.1016/j.envsoft.2020.104945, 2021. a, b, c, d
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Ayala, A. I., Moras, S., and Pierson, D. C.: Simulations of future changes in thermal structure of Lake Erken: proof of concept for ISIMIP2b lake sector local simulation strategy, Hydrol. Earth Syst. Sci., 24, 3311–3330, https://doi.org/10.5194/hess-24-3311-2020, 2020. a, b
Borgonovo, E.: A new uncertainty importance measure, Reliab. Eng. Syst. Safe., 92, 771–784, https://doi.org/10.1016/j.ress.2006.04.015, 2007. a, b
Borgonovo, E., Lu, X., Plischke, E., Rakovec, O., and Hill, M. C.: Making the most out of a hydrological model data set: Sensitivity analyses to open the model black-box, Water Resour. Res., 53, 7933–7950, https://doi.org/10.1002/2017wr020767, 2017. a, b
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Short summary
Models help to understand natural systems and are used to predict changes based on scenarios (e.g., climate change). To simulate water temperature and deduce impacts on water quality in lakes, 1D lake models are often used. There are several such models that differ regarding their assumptions and mathematical process description. This study examines the performance of four such models on a global dataset of 73 lakes and relates their performance to the model structure and lake characteristics.
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