Articles | Volume 15, issue 1
Model experiment description paper
11 Jan 2022
Model experiment description paper |  | 11 Jan 2022

Modeling reservoir surface temperatures for regional and global climate models: a multi-model study on the inflow and level variation effects

Manuel C. Almeida, Yurii Shevchuk, Georgiy Kirillin, Pedro M. M. Soares, Rita M. Cardoso, José P. Matos, Ricardo M. Rebelo, António C. Rodrigues, and Pedro S. Coelho

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Cited articles

Almeida, M.: Models source code: CE-QUAL-W2 v3.6, FLake (windows version 1.0), Hostetler and ANN (momentum alg.) – Modeling reservoir surface temperatures for regional and global climate models (Version 1.0), Zenodo [code],, 2021a. 
Almeida, M.: Model input files (hydrometric, water quality and meteorological data sets): CE-QUAL-W2 v3.6, FLake (windows version), Hostetler and ANN (momentum alg.) – Modeling reservoir surface temperatures for regional and global climate models (Version 1.0), Zenodo [data set],, 2021b. 
Almeida, M. C., Coelho, P. S., Rodrigues, A. C., Diogo, P. A., Maurício, R., Cardoso, R. M., and Soares, P. M. M.: Thermal stratification of Portuguese reservoirs: Potential impact of extreme climate scenarios, J. Water Clim. Change, 6, 544–560,, 2015. 
Bates, G. T., Giorgi, F., and Hostetler, S. W.: Towards the simulation of the effects of the Great Lakes on climate, Mon. Weather Rev., 121, 1373–1387,<1373:TTSOTE>2.0.CO;2, 1993. 
Short summary
In this study, we have evaluated the importance of the input of energy conveyed by river inflows into lakes and reservoirs when modeling surface water energy fluxes. Our results suggest that there is a strong correlation between water residence time and the surface water temperature prediction error and that the combined use of process-based physical models and machine-learning models will considerably improve the modeling of air–lake heat and moisture fluxes.