the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improving large-scale river routing models for climate studies: the impact of ESA long-term CCI discharge products on correcting multi-model hydrological simulations
Abstract. Large scale hydrological models like CTRIP and MGB are essential for simulating river dynamics and supporting large-scale climate studies. Their accuracy can be significantly improved through satellite data assimilation. This study leverages 20 years of high-resolution discharge data (2000–2020) from the ESA Climate Change Initiative (CCI) to enhance CTRIP and MGB models via ensemble Kalman Filter frameworks (HyDAS and HYFAA). Applied to the Niger and Congo basins, the models assimilate discharge data derived from altimetry and multispectral imagery, alongside water surface elevation (WSE) anomaly data, to evaluate their impact on model performance.
Discharge assimilation was more effective than WSE anomaly assimilation, as it provided a more direct input for improving model accuracy. Temporal data density was the key factor in reducing bias and enhancing the simulation of seasonal flow patterns, with spatial coverage and data quality also playing important roles. In the Niger Basin, the assimilation of denser discharge data resulted in a significant bias reduction, which should improve the representation of long-term climate trends. Furthermore, the higher temporal resolution allowed for better capture of flow variability, which is crucial for both seasonal climate studies and short-term predictions, such as extreme hydrological events.
The study also emphasizes the trade-offs between data resolution and quality, particularly in the Congo Basin. Future advancements include merging altimetry and multispectral discharge data, improving the discharge retrieval algorithms using SWOT data, and refining data assimilation techniques to improve climate studies and river system modeling in complex, climate-impacted basins.
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RC1: 'Comment on hess-2024-328', Menaka Revel, 22 Dec 2024
- AC1: 'Reply on RC1', Malak Sadki, 11 Feb 2025
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RC2: 'Comment on hess-2024-328', Anonymous Referee #2, 26 Dec 2024
It’s my pleasure to review hess-2024-328 “Improving large-scale river routing models for climate studies: the impact of ESA long-term CCI discharge products on correcting multi-model hydrological simulations” by Malak et al. The authors conducted several numerical experiments using both CTRIP-HyDAS and MGB-HYFAA models to evaluate the impact of assimilating different CCI discharge products on improving discharge simulations in both Niger and Congo river basins. Although the research shows potential for improving large-scale river discharge simulations via DA, current presented structure of the paper and the figures make the paper less readable, and the design of DA experiments can be also enhanced. Accordingly, major revision is recommended. My comments are as follows.
1.The current layout and structure of the paper need significant improvement.
(1) The introduction of data and model should be divided into two separate sections.
(2) It’s strange to include subsection 2.4.2 in the introduction of data and model.
(3) It’s strange to include the discussion (i.e. subsection 4.3) in the section of Results.
(4) The layout should be improved, for instance, there are a large number of blank spaces between pages.
2.The quality of presented figures need significant improvement.
(1) There are too many figures presented in the paper, which I think the authors should try to reduce the number of figures to highlight the main results. For instance, I don’t find the necessary to include the Figures 3-6, and Figures 1-2 and 8 can be merged into one figure.
(2) The quality of most figures should be improved, because it’s difficult to read the text, numerical values and legend presented in most figures.
3.It’s not clear why the authors use both CTRIP and MGB models. Given the fact that the MGB model was already calibrated against in-situ discharge time series, I don’t think it’s fair to compare its performance to the CTRIP that was not calibrated yet. In addition, the input of precipitation for the two models are also different.
4.The design of DA experiments can be further enhanced.
(1) The authors can consider implementing only the MGB model for the DA experiment, and I think the authors can consider two cases, the MGB model with and without calibration, to investigate the impact of calibration on assimilating satellite-based product.
(2) The authors can also consider assimilating the in-situ discharge data from the stations where both in-situ and satellite-based data are available, and the remaining stations can be used for the validation. As such, the subsection 2.4.2 can be included in the section of Results, and the impact of uncertainty of the satellite-based data can be further investigated compared to the performance of in-situ observations.
5.The Introduction can be further improved to review current progress of assimilating discharge data (including those research using in-situ observations) and relevant DA methods.
Citation: https://doi.org/10.5194/hess-2024-328-RC2 - AC2: 'Reply on RC2', Malak Sadki, 11 Feb 2025
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Improving large-scale river routing models for climate studies: the impact of ESA long-term CCI discharge products on correcting multi-model hydrological simulations
by Sadki Malak, Noual Gaëtan, Munier Simon, Pedinotti Vanessa, Verma Kaushlendra, Albergel Clément, Biancamaria Sylvain, and Andral Alice
The authors compared two data assimilation frameworks namely CTRIP-HyDAS and MGB-HYFAA. They performed a few experiments using remotely sensed discharge and water surface elevations from multiple nadir altimetry satellite missions to assimilate into the models in Congo and Niger basins. They assimilated altimetry WSE anomalies (dH), altimetry-based discharge (Qalti), and multispectral image-based discharge (Qmultispec) into two models namely CTRIP and MGB. They further investigate the different observation errors for data assimilation. The authors concluded that assimilating discharge data can effectively improve the discharge simulation of the model. Furthermore, they discussed that the observation error, observation frequency, and spatial extent can influence the accuracy of the assimilated values.
In the era of satellite data, comparing data assimilation methods across large river basins is of immense value. With the launch of satellites such as Surface Water and Ocean Topography (SWOT), the application of advanced data assimilation techniques becomes even more critical.
However, the presentation quality of the manuscript can be further enhanced by improving figure quality, reducing the number of figures, summarizing certain paragraphs, or moving them to the supplementary materials or appendix.
Some comments have been provided to enhance the manuscript.
Major Comments:
Moderate Comments:
Minor Comments:
References:
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