Articles | Volume 18, issue 12
https://doi.org/10.5194/hess-18-4773-2014
https://doi.org/10.5194/hess-18-4773-2014
Research article
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03 Dec 2014
Research article | Highlight paper |  | 03 Dec 2014

Estimating degree-day factors from MODIS for snowmelt runoff modeling

Z. H. He, J. Parajka, F. Q. Tian, and G. Blöschl

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Cited articles

Andreadis, K. M. and Lettenmaier, D. P.: Assimilating remotely sensed snow observations into a macroscale hydrology model, Adv. Water Resour., 29, 872–886, 2006.
Bach, H., Braun, M., Lampart, G., and Mauser, W.: Use of remote sensing for hydrological parameterisation of Alpine catchments, Hydrol. Earth Syst. Sci., 7, 862–876, https://doi.org/10.5194/hess-7-862-2003, 2003.
Blöschl, G. and Kirnbauer, R.: An analysis of snow cover patterns in a small Alpine catchment, Hydrol. Process., 6, 99–109, 1992.
Blöschl, G., Kirnbauer, R., and Gutknecht, D.: Modelling snowmelt in a mountainous river basin on an event basis, J. Hydrol., 113, 207–229, 1990.
Blöschl, G., Kirnbauer, R., and Gutknecht, D.: Distributed snowmelt simulations in an Alpine catchment.1. model evaluation on the basis of snow cover patterns, Water Resour. Res., 27, 3171–3179, 1991a.
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Short summary
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. Snow density is estimated as the ratio between observed precipitation and changes in the snow volume for days with snow accumulation. DDFS values are estimated as the ratio between changes in the snow water equivalent and difference between the daily temperature and a threshold value for days with snowmelt.