Projects per year
Abstract
his 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.
| Original language | English |
|---|---|
| Pages (from-to) | 629-635 |
| Journal | Natural Hazards and Earth System Sciences |
| Volume | 6 |
| DOIs | |
| Publication status | Published - 2006 |
Treatment code (Nähere Zuordnung)
- Basic - Fundamental (Grundlagenforschung)
- Theoretical
- Experimental
Fingerprint
Dive into the research topics of 'A neural network model for short term river flow prediction'. Together they form a unique fingerprint.-
Radar Applications in Natural Hazards Detection, Prognostics and Warning
Schreiber, H., Paulitsch, H., Teschl, R., Lorentschitsch, K. & Randeu, W.
1/01/95 → 14/05/25
Project: Research area
-
WIIS - Weatherradar Information Systems
Schlemmer, A., Schreiber, H., Teschl, R., Paulitsch, H., Fuchsberger, J., Randeu, W., Steinkellner, A. & Tani, S.
1/01/90 → 31/01/35
Project: Research project
-
INW/WIIS-III - Radar / Flood Water
Teschl, R. & Randeu, W.
1/07/03 → 31/12/06
Project: Research project