Improvement of runoff simulation efficiency using satellite soil moisture data for typical monthly runoff regimes in Austria

Abstract

The availability of remote sensing data opened possibilities for assimilating these into rainfall-runoff models. We examined the quality of the simulated monthly runoff regime in catchments in which the inclusion of a new satellite soil moisture dataset (ASCAT SW1) into the calibration of the TUW rainfall-runoff model outperformed in the model verification the conventional runoff-only calibration in 198 Austrian basins. Using k-means clustering, catchments with similar mean monthly runoff regimes were grouped. Three variants of the multi-objective approach were analysed for each month of the year in Carinthia, Styria and Upper and Lower Austria regions. Improvement in the simulated monthly runoff using the ASCAT data was mainly noticeable in the winter and spring months. The runoff simulation efficiency decreased in the driest summer and autumn months. It has also been confirmed that improvements in the simulations can be expected in the flat river basins compared to the hilly types and in river basins with lower average slopes. The findings refine previous recommendations regarding when hydrological models could benefit from considering information beyond the runoff signatures in their calibration.