Use of remotely sensed precipitation and leaf area index in a distributed hydrological model

Abstract Remotely sensed precipitation from METEOSAT data and leaf area index (LAI) from NOAA AVHRR data is used as input data to the distributed hydrological modelling of three subcatchments (82,000 km 2 ) in the Senegal River Basin. Further, root depths of annual vegetation are related to the temporal and spatial variation of LAI. The modelling results are compared with results based on conventional input of precipitation and vegetation characteristics. The introduction of remotely sensed LAI shows improvements in the simulated hydrographs, a marked change in the relative proportions of actual evapotranspiration comprising canopy evaporation, soil evaporation and transpiration, while no clear trend in the spatial pattern could be found. The remotely sensed precipitation resulted in similar model performances with respect to the simulated hydrographs as with the conventional raingauge input. A simple merging of the two inputs did not result in any improvement.

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