Hydrological time series period superposition prediction model and three improved models

hydrological time series;  forecasting;  Periodic superposition forecasting model (POL);  Trend-cycle superposition combined forecasting model (TPOLC);  Periodic superposition prediction model (AC-POL) with compressed amplitude;  Periodic superposition prediction model (DPI-POL) for inverse dominance period

Hydrological phenomena in nature often imply periodicity, and based on this property, a hydrological time series cycle superposition prediction model was developed. The hydrological time series period superposition prediction model (POL) is introduced, the shortcomings of the hydrological time series period superposition prediction model (POL) in the application under some specific conditions are analyzed, and three improved models are proposed: trend-period superposition combined forecasting model (TPOLC), periodic superposition prediction model with compressed amplitude (AC-POL), and periodic superposition prediction model (DPI-POL) with inverse dominant period. It can be widely used in corresponding types of hydrological time series modeling.