Monitoring hydrological variables from remote sensing and modelling in
the Congo River basin
Abstract
This study intends to integrate heterogeneous remote sensing
observations and hydrological modelling into a simple framework to
monitor hydrological variables in the poorly gauged Congo River basin
(CRB). It focuses on the possibility to retrieve 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 datasets together
with in-situ data to constrain, calibrate and validate the model, and
also to build a dataset of stage/discharge rating curves (RCs) at 709
VSs distributed all over the basin. The model was well calibrated at the
four gages 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,
NSEmean = 0.67) is an indicator of the overall consistency of discharge
simulations even in ungauged upstream sub-basins. This RC dataset
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.