Abstract

Nowadays, hydrological rainfall-runoff models are routinely used for modelling hydrological balances, the generation of floods, or droughts. For decades numerous rainfallrunoff models have been tested with many calibration procedures and different model structures. However, for rainfall-runoff, it is challenging to find a particular model structure and parameter set that can correctly describe the complicated flow formation processes in diverse physiographic conditions. Improvements to existing rainfall-runoff modelling concepts and data assimilation are therefore continuously being tested. In recent years, remote sensing has played an increasing role in the surveying of hydrological phenomena. Remote sensing of soil moisture data can be very helpful because soil moisture measurements in field conditions are not always straightforward. The quality of remotely sensed data is rising; nowadays, we can routinely start using data with proper spatial and temporal resolutions. In this paper, we have focused on an evaluation of the parametrisation of the soil moisture submodel of the TUW rainfall-runoff model by remotely sensed soil moisture data. We calibrated the TUW model for three selected catchments in Austria with flat hypsometric characteristics using discharges as a criterion. For the calibration, we used both the lumped and semi-distributed model versions of the model and compared the quality of the soil moisture of both versions. Both the lumped and semi-distributed versions performed well in the discharge simulation. In the case of the soil moisture simulation, we achieved slightly better results with the semi-distributed version of the model. Difficulties with accessing the data from the remote sensing are discussed since remote sensing sensors still have problems when clouds and snow cover the catchments.

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