A fuzzy rule-based technique is used for modelling the relationship between climatic forcing and droughts in a Central/Eastern European country, Hungary. Two types of climatic forcing-called premises-are considered: Atmospheric circulation patterns (CP) and El Nino Southern Oscillation (ENSO). Both the Hess-Brezowsky CP types and ENSO events influence the occurrence of droughts, but the ENSO signal is relatively weak in a statistical sense. The fuzzy rule-based approach is able to learn the high space-time variability of monthly Palmer Drought Severity Index (PDSI) and results in a proper reproduction of the empirical frequency distributions. The "engine" of the approach, the fuzzy rules, are ascertained from a subset called the learning set of the observed time series of premises (monthly CP frequencies and Southern Oscillation Index) and PDSI response. Then an independent subset, the validation set, is used to check how the application of fuzzy rules reproduces the observed PDSI.
ASJC Scopus subject areas
- Water Science and Technology