Prediction of extreme precipitation using a neural network: Application to summer flood occurrence in Moravia

L. Bodri, V. Čermák

Research output: Article

60 Citations (Scopus)

Abstract

Dramatic floods occurred in Central Europe in summer 1997, and Czech Republic has been seriously affected in its eastern part - Moravia. A predictive approach based on modelling flood recurrence may be helpful in flood management. Summer floods are typically characterized by saturated catchment due to long-lasting heavy precipitation followed by a sudden extreme rainfall. In present work an artificial neural network (ANN) model was evaluated for precipitation forecasting. Back propagation neural networks were trained with actual monthly precipitation data from two Moravian meteorological stations for a time period of 38 years. Predicted amounts are of next-month-precipitation and summer precipitation in the next year. The ANN models provided a good fit with the actual data, and have shown a high feasibility in prediction of extreme precipitation.

Original languageEnglish
Pages (from-to)311-321
Number of pages11
JournalAdvances in Engineering Software
Volume31
Issue number5
DOIs
Publication statusPublished - máj. 2000

ASJC Scopus subject areas

  • Software
  • Engineering(all)

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