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| Titel |
Estimating degree-day factors from MODIS for snowmelt runoff modeling |
| VerfasserIn |
Z. H. He, J. Parajka, F. Q. Tian, G. Blöschl |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 12 ; Nr. 18, no. 12 (2014-12-03), S.4773-4789 |
| Datensatznummer |
250120540
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| Publikation (Nr.) |
 copernicus.org/hess-18-4773-2014.pdf |
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| Zusammenfassung |
| Degree-day factors are widely used to estimate snowmelt runoff in
operational hydrological models. Usually, they are calibrated on observed
runoff, and sometimes on satellite snow cover data. In this paper, we
propose a new method for estimating the snowmelt degree-day factor
(DDFS) directly from MODIS snow covered area (SCA) and ground-based
snow depth data without calibration. Subcatchment snow volume is estimated
by combining SCA and snow depths. Snow density is estimated to be the ratio
between observed precipitation and changes in the snow volume for days with
snow accumulation. Finally, DDFS values are estimated to be the ratio
between changes in the snow water equivalent and difference between the
daily temperature and the melt threshold value for days with snow melt. We
compare simulations of basin runoff and snow cover patterns using spatially
variable DDFS estimated from snow data with those using spatially
uniform DDFS calibrated on runoff. The runoff performances using
estimated DDFS are slightly improved, and the simulated snow cover
patterns are significantly more plausible. The new method may help reduce
some of the runoff model parameter uncertainty by reducing the total number
of calibration parameters. This method is applied to the Lienz catchment in
East Tyrol, Austria, which covers an area of 1198 km2. Approximately
70% of the basin is covered by snow in the early spring season. |
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