Calibrating macro-scale hydrological models in poorly gauged and heavily regulated basins
Abstract. The calibration of macro-scale hydrological models is often challenged by the lack of adequate observations of river discharge and infrastructure operations. This modelling backdrop creates a number of potential pitfalls for model calibration, potentially affecting the reliability of hydrological models. Here, we introduce a novel numerical framework conceived to explore and overcome these pitfalls. Our framework consists of VIC-Res (a macro-scale model setup for the Upper Mekong River Basin) and a hydraulic model used to infer discharge time series from satellite data. Using these two models and Global Sensitivity Analysis, we show the existence of a strong relationship between the parameterization of the hydraulic model and the performance of VIC-Res – a co-dependence that emerges for a variety of performance metrics we considered. Using the results provided by the sensitivity analysis, we propose an approach for breaking this co-dependence and informing the hydrological model calibration, which we finally carry out with the aid of a multi-objective optimization algorithm. The approach used in this study could integrate multiple remote-sensed observations and is readily transferable to other basins.
Dung Trung Vu et al.
Status: open (until 11 Apr 2023)
- RC1: 'Comment on hess-2023-35', Anonymous Referee #1, 13 Mar 2023 reply
- RC2: 'Comment on hess-2023-35', Andrea Galletti, 17 Mar 2023 reply
Dung Trung Vu et al.
Dung Trung Vu et al.
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Overall, the manuscript could be very helpful in providing a guideline for a calibrating model where almost no in-situ data is available. The authors discussed the in-depth methodology of their proposed calibration, providing a detailed analysis of the impact of parameter tuning on the performance metrics of the model. The authors also provided an analysis of the co-dependence of the hydrological and hydraulic model parameterizations and techniques to break the co-dependency. The central argument presented in the manuscript is using satellite data to infer river discharge against which the model-derived river discharge will be compared and the model recalibrated to achieve the desired accuracy. Sattelite data itself can cause a wide range of uncertainty in the calculation of river cross-section, water surface slope, and so on, especially in the Upper Mekong river basin, which is so complex in topography. The satellite data (used as a proxy of observation for calibration purposes) is prone to uncertainty that eventually impact the parameter tuning. So there's a need to strengthen the discussion by providing a detailed discussion on the uncertainty in the river discharge estimation from satellite data, without which the calibration framework could be questionable. My recommendation is for a major revision with the specific comments and concerns listed below:
1. In the abstract, the authors mentioned that their approach could be readily transferable to another basin. However, the authors did not provide any convincing discussion on how the same framework can be used for another basin. For example, what cautions should other researchers follow when applying the same technique to a highly complex basin with rugged terrain or complex topography? As the estimation of river cross-section and water surface slope could be challenging/more uncertain in some other basin.
2. In section 3.3.1 authors discussed the calibrated model parameters and presented the calibration outcomes later. However, one would expect to see a discussion of the calibration of the most sensitive parameters.
3. As the discussion is so central to the simultaneous calibration of the using RS Discharge (from satellite data). Thus an uncertainty analysis of the estimation of the river cross-section or uncertainty in the RS Discharge from satellite data is extremely necessary. It directly impacts the RS Discharge estimation against which VIC-RES discharge is compared to calculate performance matrices. Thus uncertainty in RS Discharge can substantially impact the calibration process and parameter tuning, fundamentally questioning the Novel technique the authors suggested in that manuscript. I recommend a discussion on uncertainty in RS Discharge estimation and how it may affect the calibration process. Although the author provided some insights in section 4.2.3
4. In section 3.3.2- The authors discussed that they used multiple performance matrices to cover a different aspect of modeling accuracy. However, the use of KGE as a performance metric is also suggested, as it considers bias, correlation, and variability.
5. In Figure 8: could you discuss why there is less variability in 2009-2012 and after that, there is considerable variability, particularly in the low flows?
6. In Figure 9: the timing of the peak is missed in some of the years, e.g., 2007. You can just add a discussion on the sensitivity of different parameter tuning in capturing timing/seasonality or peak. Or which is the most sensitive parameter?
7. Also. How can the hydrological response unit's resolution or size impact calibration? It can impact the calibration substantially. For example, the Lancang river basin is so narrow and elongated. Thus, the use of a coarse hydrological response unit of Coarse-resolution may accurately impact the identification of river grid cells.
8. Figure 2 and 3 can be merged together. Having two figures does not add much value to the discussion.
9. In section 3.2.1: The authors used a regression technique (sixth-degree polynomial) to fit the data point best. However, the author said that is best works for the natural condition of rivers. AS MANUSCRIPT TITLE, the authors mentioned "Heavily Regulated Basin." One would like to know the author’s novel technique for heavily regulated basins. In the suggested numerical framework, I think I do not see any strong linkage of the reservoir operation (like heavy regulation) with the calibration/parameter tuning. Or could you provide an explanation of how your technique is mainly applicable to the heavily regulated basin? Or it may be more justifiable to say Novel calibration technique for the poorly gauged basin.