Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> 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.
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