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| Titel |
Spatial variability of temperature for improved snowmelt forecasting |
| VerfasserIn |
J. Eckart, D. E. Reusser, Erwin Zehe, C. Bernhofer |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250030353
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| Zusammenfassung |
| The spatial and temporal variability of snowmelt in a catchment area depends on multiple
processes. The heterogeneity of morphologic, vegetative and climatologic elements
determines snow accumulation and snowmelt. Especially the spatial variability
of temperature and radiation at the meso-scale has a significant influence on these
processes. Therefore, temperature is a substantial input for hydrological modelling
especially for snowmelt, but generally too few measurements are available in a catchment
area for downscaling or regionalisation. A precise description of temperature can
improve snow modelling and snowmelt forecasting.
We test whether the representation of the spatial pattern of temperature can be improved
by geostatistical analysis. While ten climate stations in the vicinity of a 50
km2 catchment constitutes a fairly dense network, the data is still insufficient for standard
geostatic analysis. Generally, about 30 data points for each lag-class are required
for variogram estimation. In order to increase the data base measurements were pooled
over a time period of several hours. The suitability of this spatial information has been
tested for different typical weather situations with snow melting. The results have also
been compared with different standard interpolation methods.The advantage of this
method is the use of geostatistic analysis with a few of measurements as an input for
a hydrological model. A second advantage is the fast and automatic way of downscaling.
The effects of different spatially interpolated temperature patterns are evaluated with
the hydrological response of the snow model (Wasim ETH I, Temperature index melt
modelling). The results discussing the influence of spatial variability of temperature
on modelling of snowmelt events will be presented. |
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