Automatic calibration of a global flow routing model in the Amazon basin using virtual SWOT data

The Surface Water and Ocean Topography (SWOT) wide swath altimetry mission will provide a global coverage of surface water elevation, which will be used to help correct water height and discharge prediction from hydrological models. Here, the aim is to investigate the use of virtually generated SWOT data to improve water height and discharge simulation using calibration of model parameters (like river width, river depth and roughness coefficient). In this work, we use the HyMAP model to estimate water height and discharge on the Amazon catchment area. Before reaching the river network, surface and subsurface runoff are delayed by a set of linear and independent reservoirs. The flow routing is performed by the kinematic wave equation.. Since the SWOT mission has not yet been launched, virtual SWOT data are generated with a set of true parameters for HyMAP as well as measurement errors from a SWOT data simulator (i.e. a twin experiment approach is implemented). These virtual observations are used to calibrate key parameters of HyMAP through the minimization of a cost function defining the difference between the simulated and observed water heights over a one-year simulation period. The automatic calibration procedure is achieved using the MOCOM-UA multicriteria global optimization algorithm as well as the local optimization algorithm BC-DFO that is considered as a computational cost saving alternative. First, to reduce the computational cost of the calibration procedure, each spatially distributed parameter (Manning coefficient, river width and river depth) is corrupted through the multiplication of a spatially uniform factor that is the only factor optimized. In this case, it is shown that, when the measurement errors are small, the true water heights and discharges are easily retrieved. Because of equifinality, the true parameters are not always identified. A spatial correction of the model parameters is then investigated and the domain is divided into 4 regions where the true corrective factors differ. The automatic calibration procedure leads to a proper estimation of the parameters upstream of the observations. This shows that the corrective parameters should be estimated sequentially over short periods of time and over limited areas when and where observations are available, allowing to take advantage of the global coverage of the SWOT mission.