This study investigates how remotely sensed data, with a focus on the optical satellite sensors NOAA AVHRR and METEOSAT, can be used in distributed hydrological modeling. The ultimate goal of the study was to develop methods to integrate satellite remote sensing data in large-scale hydrological models by applying state-of-the-art methods to extract relevant hydrological data from the satellite data and by developing new algorithms. A physically based, distributed hydrological model, based on a modified version of the MIKE SHE code, was applied to the Senegal River basin in West Africa, and the effect on the model performance by using remotely sensed data was examined. Results of daily rainfall estimates from METEOSAT data and vegetation dynamics from NOAA AVHRR data used as input to the model and the potential of using a remotely sensed dryness index for validation of the model are reported. The performance of simulated discharge was improved using remotely sensed vegetation dynamics, and marginal improvement in model performance was obtained using remotely sensed precipitation.
- Programområde 2: Vandressourcer