Abstract: Aiming at the different characteristics of water-bloom growing in different seasons，a predicting model combined with wavelet analysis and artificial neural network（WANN） is proposed based on the study in mechanism of water-bloom growing.The model which has great capabilities of both self-study of artificial neural network and multi-resolution analysis power of wavelet，is applied in forecasting water-bloom in lakes and rivers of Beijing in summer.Through the wavelet multi-resolution analysis，the influence is decreased efficiently from unnecessary noise brought by primary data，finally the performance of network is enhanced.Compared with the calculation results，WANN possesses high forecasting accuracy and has better performance than BP model.