Monitoring Hydrological Variables from Remote Sensing and Modeling in the Congo River Basin

Abstract

This study intends to integrate heterogeneous remote sensing observations and hydrological modeling into a simple framework to monitor hydrological variables in the poorly gauged Congo River Basin (CRB). It focuses on the possibility of retrieving effective channel depths and discharges all over the basin in near real time (NRT). First, this paper discusses the complexity of calibrating and validating a hydrologic–hydrodynamic model (namely the MGB model) in the CRB. Next, it provides a twofold methodology for inferring discharge at newly monitored virtual stations (VSs, crossings of a satellite ground track with a water body). It makes use of remotely sensed data sets together with in situ data to constrain, calibrate, and validate the model, and also to build a data set of stage/discharge rating curves (RCs) at 709 VSs distributed all over the basin. The model was well calibrated at the four gauges with recent data (Nash-Sutcliffe Efficiency, NSE > 0.77). The satisfactory quality of RCs basin-wide (mean NSE between simulated discharge and rated discharge at VSs, NSE mean = 0.67) is an indicator of the overall consistency of discharge simulations, even in ungauged upstream sub-basins. This RC data set provides an unprecedented possibility of NRT monitoring of CRB hydrological state from the current operational satellite altimetry constellation. The discharges estimated at newly monitored locations proved to be consistent with observations. They can be used to increase the temporal sampling of water surface elevation (WSE) monitoring from space with no need for new model runs. The RC located under the fast sampling orbit of the SWOT satellite, to be flown in 2022, will be used to infer daily discharge in major contributors and in the Cuvette Centrale, as soon as data is released.