Abstract
Abstract. Recent advances in soil moisture remote sensing have produced satellite data sets with improved soil moisture mapping under vegetation and with higher spatial and temporal resolutions. In this study, we evaluate the potential of a new, experimental version of the Advanced Scatterometer (ASCAT) soil water index data set for multiple objective calibrations of a conceptual hydrologic model. The analysis is performed in 213 catchments in Austria for the period 2000–2014. An HBV (Hydrologiska Byråns Vattenbalansavdelning)-type hydrologic model is calibrated based on runoff data, ASCAT soil moisture data, and Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data for various calibration variants. Results show that the inclusion of soil moisture data in the calibration mainly improves the soil moisture simulations, the inclusion of snow data mainly improves the snow simulations, and the inclusion of both of them improves both soil moisture and snow simulations to almost the same extent. The snow data are more efficient at improving snow simulations than the soil moisture data are at improving soil moisture simulations. The improvements of both runoff and soil moisture model efficiencies are larger in low elevation and agricultural catchments than in others. The calibrated snow-related parameters are strongly affected by including snow data and, to a lesser extent, by soil moisture data. In contrast, the soil-related parameters are only affected by the inclusion of soil moisture data. The results indicate that the use of multiple remote sensing products in hydrological modeling can improve the representation of hydrological fluxes and prediction of runoff hydrographs at the catchment scale.
Highlights
Estimating the spatial and temporal variability in water balance components at the regional scale is important for solving a range of practical issues in water resources management and planning and for understanding catchment functioning in terms of how runoff-generation processes interact to produce catchment response
The calibration model performance of three multiple objective calibration variants is presented in Fig. 3 and Table 4
For wQ less than 0.5, the median OSC is between 0.84 to 0.91, which is 5 % to 13 % larger than the median for calibration to runoff only (OSC = 0.79). These results indicate that the simultaneous use of satellite soil moisture (SSM) and satellite snow cover (SSC) in model calibration can improve simulations of soil moisture and snow cover in the calibration period without any significant reduction in runoff model efficiency, for wQ between 0.3 and 0.4
Summary
Estimating the spatial and temporal variability in water balance components at the regional scale is important for solving a range of practical issues in water resources management and planning and for understanding catchment functioning in terms of how runoff-generation processes interact to produce catchment response. Previous studies have demonstrated that multiple objective calibration helps to constrain hydrologic models and, to reduce uncertainty and to improve predictions in hydrological modeling (e.g., Efstratiadis and Koutsoyiannis, 2010). Most of these studies examined the value of constraining hydrologic models by combining different runoff signatures (e.g., by simultaneous calibration of the models to low and high flows or timing) or calibrating hydrologic models to runoff and some additional hydrological variable, such as Published by Copernicus Publications on behalf of the European Geosciences Union
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