Abstract
Lack of meteorological data challenges applications of the hydrological modeling. Hence, in the ungauged or poorly gauged catchments, where data are not available or too sparse, other alternative data sources can be adopted. This study investigates the most appropriate type of precipitation data among rain gauge, satellite-gauge merging precipitation data using local rain gauge data and satellite precipitation product to predict streamflow in data sparse catchments. First, we analyzed the impact of blended rain gauge density on the performance of the satellite-gauge merging precipitation and modeled streamflow. Secondly, by considering the effect of rain gauge density, the streamflow simulation abilities of these three precipitation data sources were compared using the relationship between the model performance indices with the Areal Mean Precipitation uncertainties. It is found that the applicability of rain gauge data in the medium sized catchments was superior compared to the other two precipitation data. However, in the large river basin (Da river basin), satellite-gauge merging precipitation showed constantly superior streamflow simulation skills than the corresponding gauge only data.
