Articles | Volume 18, issue 18
https://doi.org/10.5194/gmd-18-6135-2025
https://doi.org/10.5194/gmd-18-6135-2025
Model evaluation paper
 | 
19 Sep 2025
Model evaluation paper |  | 19 Sep 2025

Evaluating the performance of CE-QUAL-W2 version 4.5 sediment diagenesis model

Manuel Almeida and Pedro Coelho

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Cited articles

Abbaspour, K. C., Rouholahnejad, E., Vaghefi, S., Srinivasan, R., Yang, H. and Kløve, B.: A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model, J. Hydrol., 524, 733–752, https://doi.org/10.1016/j.jhydrol.2015.03.027, 2015. 
Adedeji, I. C., Ahmadisharaf, E., and Sun, Y.: Predicting in-stream water quality constituents at the watershed scale using machine learning. J. Contam. Hydrol., https://doi.org/10.1016/j.jconhyd.2022.104078, 2022. 
Almeida, M. and Coelho, P. S.: An integrated approach based on the correction of imbalanced small datasets and the application of machine learning algorithms to predict total phosphorus concentration in rivers, Ecol. Inform., 76, 102138, https://doi.org/10.1016/j.ecoinf.2023.102138, 2023a. 
Almeida, M. and Coelho, P.: A first assessment of ERA5 and ERA5-Land reanalysis air temperature in Portugal, In. J. Climatol., 43, 6643–6663, https://doi.org/10.1002/JOC.8225, 2023b. 
Almeida, M. and Coelho, P.: Evaluating the performance of CE-QUAL-W2 version 4.5 sediment diagenesis model (Manuscript related material: input data and source code) (1.0.0), Zenodo [data set and code], https://doi.org/10.5281/zenodo.14606105, 2025. 
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Short summary
This study aims to assess the capabilities of the advanced two-dimensional water quality and hydrodynamic model CE-QUAL-W2 v4.5 sediment diagenesis module, focusing on its application to a reservoir in Portugal over a six-year period (2016–2021). Overall, the results suggest that the diagenesis model is better suited for detailed process-based dynamics over extended timeframes, whereas simpler models such as the Hybrid model (combining the zero- and first-order models), are more appropriate for short- to medium-term applications or situations with limited data availability.
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