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https://doi.org/10.5194/gmd-2024-202
https://doi.org/10.5194/gmd-2024-202
Submitted as: model evaluation paper
 | 
24 Jan 2025
Submitted as: model evaluation paper |  | 24 Jan 2025
Status: this preprint is currently under review for the journal GMD.

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

Manuel Almeida and Pedro Coelho

Abstract. This study set out to assess the performance of the state-of-the-art CE-QUAL-W2 v4.5 sediment diagenesis model. The model was applied to a reservoir in Portugal using observed sediment particulate organic carbon values corresponding to a six-year period (2016–2021). The model was calibrated by comparing its results with 35 observed dissolved oxygen and water temperature profiles, as well as annual total nitrogen, total phosphorus, biochemical oxygen demand, and chlorophyll-a measurements corresponding to three different depths. In addition to model calibration, a sensitivity analysis was also conducted by varying the input particulate organic carbon values and applying a user-specified sediment oxygen model (zero-order model). The results demonstrated the overall effectiveness of the sediment diagenesis model, which accurately simulated dissolved oxygen profiles, nutrient concentrations, and organic matter levels (Dissolved oxygen profiles: NSE = 0.41 ± 0.67; RMSE = 1.73 mg/L ± 0.69), highlighting its potential as an effective tool for simulating lakes and reservoirs and supporting water management processes. The study further suggests that the zero-order model is able to serve as an effective starting point for implementing the sediment diagenesis model, providing an initial estimate for mean reservoir sediment oxygen demand (SOD) values.

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Manuel Almeida and Pedro Coelho

Status: open (until 21 Mar 2025)

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Manuel Almeida and Pedro Coelho
Manuel Almeida and Pedro Coelho

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Short summary
This study aims to assess the capabilities of the advanced CE-QUAL-W2 v4.5 sediment diagenesis model, focusing on its application to a reservoir in Portugal over a six-year period (2016–2021). Our findings indicate that the model performs very well in simulating dissolved oxygen profiles, nutrient concentrations, and organic matter levels.