Forecasting Hazardous Events and Processes in Hydrological Systems

This study explores the urgent challenge of developing effective approaches for predicting hazardous hydrological phenomena. We highlight essential questions emerging from the analysis of hydrological time series using fractal analysis methods (R/S analysis). The calculation of the Hurst exponent (H) clearly shows that hydrological time series exhibit long-term memory in their dynamics. Nonetheless, the complexity of the hydrological system and the impact of numerous “rhythmic” internal and external factors complicate the development of an adequate forecasting model. This research proposes an additive forecast model for hydrological time series, incorporating both cyclic and stochastic components.