A neural network model for short term river flow prediction

Reinhard Teschl, Walter Randeu

    Research output: Contribution to journalArticlepeer-review


    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 languageEnglish
    Pages (from-to)629-635
    JournalNatural Hazards and Earth System Sciences
    Publication statusPublished - 2006

    Treatment code (Nähere Zuordnung)

    • Basic - Fundamental (Grundlagenforschung)
    • Theoretical
    • Experimental

    Cite this