Tide tables can be a useful tool for sea-level forecasting in many areas. Slovenian operational
service for hydrological forecasts at the Environmental Agency of the Republic of Slovenia
frequently deploys tide tables alongside least square harmonic analysis to predict maximum sea
levels in the Gulf of Trieste. Meteorological influences such as pressure gradient, wind stress and
induced basin eigenoscillations (seiches) along the main axis of the Adriatic basin have repeatedly
been proven as important factors influencing the sea level in the Gulf of Trieste. They are, however,
only indirectly included in the harmonic analysis which in itself requires a large number of
carefully tuned model parameters in order to make useful short-range forecasts. A number of recent
reports show that an artificial neural network (ANN) can greatly improve sea level forecasts,
providing we supply it with suitable input variables (ie. previous water levels, air pressure, wind
speed, wind direction, tide charts etc.) We report on an ANN-based analysis of the recent storm
surge and flooding events at the Slovenian coast in the beginning of December 2008. The ANN
model compares favourably with the currently used conventional forecasting methods.
|
