the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Jul 2024
Technical Note: Operational calibration and performance improvement for hydrodynamic models in data-scarce coastal areas
Abstract. In this study, we address the challenges posed by data scarcity in hydrodynamic modeling within one of the most vulnerable coastal zones in the world—the Saigon-Dongnai tidal river system in South Vietnam. We investigate calibration strategies for a 1D hydrodynamic model using minimal in-situ data obtained from an existing local monitoring program, which provides 48 hours of measurements per month. To further improve discharge estimation from the 1D model, the coupling of a modified Manning-Strickler (MS) equation is explored. Calibration efforts reveal distinct trends in friction coefficients along the river. The introduction of indirectly measured discharge data significantly improves model performance, particularly for the Saigon River branch. Validation against independent measurements demonstrates promising results, with the coupling of the modified MS equation providing improved discharge estimates. The study underscores the complexities of calibrating hydrodynamic models in data-scarce regions, with recommendations for future modeling endeavors including incorporating more accurate upstream boundary conditions. The long time-series of estimated water level and discharge provided by this study have practical implications for water resource management and decision-making in data-scarce estuarine systems and are provided in open-access for operational use.
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RC1: 'Comment on egusphere-2024-1563', Anonymous Referee #1, 15 Oct 2024
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The study involves the development of a coupled 1D and Manning-Strickler (MS) equation. This framework facilitates computationally efficient and accurate estimation of discharges in the data-scarce tidal river system in South Vietnam. The study also discusses the implications of calibrating the framework using discharge and water-level measurements. Though the concept and the calibration approaches are interesting, the paper could benefit from a detailed revision in terms of content, organization, and clarity. The following points need to be addressed.
- Given that there are several cost-efficient and more accurate modelling approaches, such as the quasi-2D local inertial (Bates et al., 2010; Sridharan et al., 2020) and sub-grid approaches (Neal et al., 2012; Nithila Devi et al., 2024), it is not clear how the proposed method is more computationally efficient and accurate. It would be nice to see a comparison of the proposed approach with a local inertial formulation in terms of accuracy and computational cost.
- For a longer reach, as used in the study, there may be lateral inflows, and it would be ideal to set up a coupled hydrological and hydraulic modelling system. If the authors are not attempting it, then a valid reason can be provided for the same, or this should be mentioned as a limitation. It is also unclear what the intended use of this modelling framework is – real-time forecasting or long-term continuous simulation. Again, for a longer-duration simulation, it is necessary to couple hydrological and hydraulic models.
- The methodology is not clear and difficult to understand. A concise description of the overall framework or the coupling can be provided at the beginning of the methodology section. Is it only the energy slope that has been calculated by the 1D code at the point of interest by the MS equation? If other hydraulic variables are also calculated from the 1D code, it should be mentioned in the methodology flow chart.
- The paper should explicitly state the calibration and validation periods used in the proposed method. This is important as the calibration and validation periods have to be distinct (For example, Bhargav et al., 2024). It is unclear from the text which events from 2016, 2017 and 2022 have been used for calibration and validation.
- With the advent of technologies, getting a high-resolution elevation data set would be possible. Whether the surveyed cross-section has been used to construct the 1D model or a high-resolution dataset has been used to represent the bathymetry is not clearly mentioned in the paper.
- Importantly, if the point of this exercise is to have a good simulation of flooding in urban areas, as mentioned in the article, then the ideal choice would be to use a simplified 2D model that can effectively represent the flood inundation dynamics on the complex urban flood plains. The presence of urban infrastructure, such as buildings, roads, streets, etc., governs flood conveyance and distribution. Also, such a claim requires validation using post-flood depth surveys. A coupled 1D and 2D modelling approach can be preferred in this case. Therefore, the authors need to acknowledge the proposed approach's limitations, constraints and advantages. In the introduction, it is also worthwhile to mention whether the focus is only on discharge estimation.
Specific comments
- The usage of the term indirectly measured discharge in the abstract is misleading.
- The introduction can include a concise literature review of the existing accurate and computationally efficient hydraulic modelling approaches (not just the ones specific to the region). And briefly discuss how the proposed framework stands out from the existing.
- Line 27. How is drought modelling relevant here? Are we looking at continuous simulation across all the seasons?
- Line 34. Please mention the advantage of the proposed method over Camenen et al. (2021) clearly and why it requires continuous water-level data for calibration.
- Line 39. What do you mean by “calibration was not precise?”
- Line 56. What is Mage code? It is suddenly introduced in the text here.
- Lines 60 – 70. These lines look like the conclusion of the study.
- Line 162. Please explain Brent’s algorithm in a sentence or two.
- The results and discussion sections are too wordy. They can be shortened to convey things clearly and concisely.
References
Bates, P. D., Horritt, M. S., & Fewtrell, T. J. (2010). A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. Journal of hydrology, 387(1-2), 33-45.
Bhargav, A. M., Suresh, R., Tiwari, M. K., Trambadia, N. K., Chandra, R., & Nirala, S. K. (2024). Optimization of Manning’s roughness coefficient using 1-dimensional hydrodynamic modelling in the perennial river system: A case of lower Narmada Basin, India. Environmental Monitoring and Assessment, 196(8), 743.
Neal, J., Schumann, G., & Bates, P. (2012). A subgrid channel model for simulating river hydraulics and floodplain inundation over large and data sparse areas. Water Resources Research, 48(11).
Nithila Devi, N., & Kuiry, S. N. (2024). A novel local‐inertial formulation representing subgrid scale topographic effects for urban flood simulation. Water Resources Research, 60(5), e2023WR035334.
Sridharan, B., Gurivindapalli, D., Kuiry, S. N., Mali, V. K., Nithila Devi, N., Bates, P. D., & Sen, D. (2020). Explicit expression of weighting factor for improved estimation of numerical flux in Local Inertial models. Water Resources Research, 56(7), e2020WR027357.
Citation: https://doi.org/10.5194/egusphere-2024-1563-RC1
Data sets
Water discharge and water level output from the MAGE 1D hydrodynamic model for the Saigon and Dongnai rivers, Vietnam, 2016-2022 Francisco Rodrigues Do Amaral et al. https://doi.org/10.23708/KLQMSR
Model code and software
Mage Jean-Baptiste Faure and Theophile Terraz https://gitlab.irstea.fr/jean-baptiste.faure/mage
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