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Analysis and modelling of discharge and suspended sediment time series is of great importance in hydrology and water management. Discharge and suspended sediment time series are the result of complex physical processes and characterized by non-stationarity. Wavelet transform enables representation of non-stationarities in time-frequency domain, decomposition and reconstruction of series and de-noising of series, and therefore represents powerful tool for analysis of hydrological time series. Overview of mentioned wavelet transform advantages is given in this paper with focus on discharge and suspended sediment time series, presented through: (i) multi-temporal scale analysis of series variability; (ii) multi-scale trend analysis; (iii) prediction and forecasting of series with wavelet based hybrid black-box models, and (iv) wavelet-aided simulation of synthetic series.