<div class="csl-bib-body">
<div class="csl-entry">Tong, R., Parajka, J., Széles, B., Greimeister-Pfeil, I., Vreugdenhil, M., Komma, J., Valent, P., & Blöschl, G. (2022). The value of satellite soil moisture and snow cover data for the transfer of hydrological model parameters to ungauged sites. <i>Hydrology and Earth System Sciences</i>, <i>26</i>(7), 1779–1799. https://doi.org/10.5194/hess-26-1779-2022</div>
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dc.identifier.issn
1027-5606
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/128072
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dc.description.abstract
The recent advances in remote sensing provide opportunities for estimating the parameters of conceptual hydrologic models more reliably. However, the question of whether and to what extent the use of satellite data in model calibration may assist in transferring model parameters to ungauged catchments has not been fully resolved. The aim of this study is to evaluate the efficiency of different methods for transferring model parameters obtained by multiple-objective calibrations to ungauged sites and to assess the model performance in terms of runoff, soil moisture, and snow cover predictions relative to existing regionalization approaches. The model parameters are calibrated to daily runoff, satellite soil moisture (Advanced Scatterometer - ASCAT), and snow cover (Moderate Resolution Imaging Spectroradiometer - MODIS) data. The assessment is based on 213 catchments situated in different physiographic and climate zones of Austria. For the transfer of model parameters, eight methods (global and local variants of arithmetic mean, regression, spatial proximity, and similarity) are examined in two periods, i.e., the period in which the model is calibrated (2000-2010) and an independent validation period (2010-2014). The predictive accuracy is evaluated by the leave-one-out cross-validation. The results show that the method by which the model is calibrated in the gauged catchment has a larger impact on runoff prediction accuracy in the ungauged catchments than the choice of the parameter transfer method. The best transfer methods are global and local similarity and the kriging approach. The performance of the transfer methods differs between lowland and alpine catchments. While the soil moisture and snow cover prediction efficiencies are higher in lowland catchments, the runoff prediction efficiency is higher in alpine catchments. A comparison of the model transfer methods, based on parameters calibrated to runoff, snow cover, and soil moisture with those based on parameters calibrated to runoff, only indicates that the former outperforms the latter in terms of simulating soil moisture and snow cover. The performance of simulating runoff is similar, and the accuracy depends mainly on the weight given to the runoff objective in the multiple-objective calibrations.
en
dc.description.sponsorship
Fonds zur Förderung der wissenschaftlichen Forschung (FWF)
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dc.language.iso
en
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dc.publisher
Copernicus Publications
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dc.relation.ispartof
Hydrology and Earth System Sciences
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
soil moisture
en
dc.subject
satellite data
en
dc.subject
snow cover
en
dc.title
The value of satellite soil moisture and snow cover data for the transfer of hydrological model parameters to ungauged sites