Remote sensing provides a unique opportunity to inform and constrain a hydrological
model and to increase its value as a decision-support tool. In this study, we
applied a multi-mission approach to force, calibrate and validate a
hydrological model of the ungauged Ogooué river basin in Africa with
publicly available and free remote sensing observations. We used a
rainfall–runoff model based on the Budyko framework coupled with a Muskingum
routing approach. We parametrized the model using the Shuttle Radar
Topography Mission digital elevation model (SRTM DEM) and forced it using
precipitation from two satellite-based rainfall estimates, FEWS-RFE (Famine
Early Warning System rainfall estimate) and the Tropical Rainfall Measuring
Mission (TRMM) 3B42 v.7, and temperature from ECMWF ERA-Interim. We combined
three different datasets to calibrate the model using an aggregated objective
function with contributions from (1) historical in situ discharge
observations from the period 1953–1984 at six locations in the basin,
(2) radar altimetry measurements of river stages by Envisat and Jason-2 at 12
locations in the basin and (3) GRACE (Gravity Recovery and Climate
Experiment) total water storage change (TWSC). Additionally, we extracted CryoSat-2
observations throughout the basin using a Sentinel-1 SAR (synthetic aperture
radar) imagery water mask and used the observations for validation of the
model. The use of new satellite missions, including Sentinel-1 and CryoSat-2,
increased the spatial characterization of river stage. Throughout the basin,
we achieved good agreement between observed and simulated discharge and the
river stage, with an RMSD between simulated and observed water amplitudes at
virtual stations of 0.74 m for the TRMM-forced model and 0.87 m for the
FEWS-RFE-forced model. The hydrological model also captures overall total
water storage change patterns, although the amplitude of storage change is
generally underestimated. By combining hydrological modeling with
multi-mission remote sensing from 10 different satellite missions, we obtain
new information on an otherwise unstudied basin. The proposed model is the
best current baseline characterization of hydrological conditions in the
Ogooué in light of the available observations