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| Titel |
A neural network model for short term river flow prediction |
| VerfasserIn |
R. Teschl, W. L. Randeu |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 6, no. 4 ; Nr. 6, no. 4 (2006-07-14), S.629-635 |
| Datensatznummer |
250003614
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| Publikation (Nr.) |
 copernicus.org/nhess-6-629-2006.pdf |
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| Zusammenfassung |
| This paper presents a model using rain gauge and weather radar data to
predict the runoff of a small alpine catchment in Austria. The gapless
spatial coverage of the radar is important to detect small convective shower
cells, but managing such a huge amount of data is a demanding task for an
artificial neural network. The method described here uses statistical
analysis to reduce the amount of data and find an appropriate input vector.
Based on this analysis, radar measurements (pixels) representing areas
requiring approximately the same time to dewater are grouped. |
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