Abstract: In order to predict water quality changes in the future, and to provide the theoretical basis and decision-making processes for protecting the ecological environment of water resource and for the sustainable development in Songhua river basin, a reasonable forecasting model needs to be developed to safeguard quality of drinking, irrigation and industrial water uses from Songhua river basin. To determine the changes of current water quality, and offer scientific methods for managing water quality, we proposed a short time series hybrid forecasting method based on wavelet transform, grey model and autoregressive conditional heteroscedasticity(GARCH). Firstly, the actual measured data ratio has been worked out, and we considered the ratio as the condition to decide whether to use the GM(1,1) as the initial forecast model or not. If the final forecasting has less error than actual measured data and the class of accuracy arrived at 1 level(posterior error ratio≤0.35), then we took the model as the forecast model. Else, we took the grey-wavelet-GARCH as the final forecast model. Secondly, when using the grey-wavelet-GARCH model, we tried to use DB3 to decompose and reconstruct into approximate series and detailed series, and analyzed the approximate series data and tested its ration in condition of grey model until its ratio met required precision(in this paper, the precision was the class of accuracy arrived at 1 level). After that, we used GM(1,1) to forecast the approximate series to find out its future values while the detailed series future values were forecasted by GARCH model. The detailed series had a large fluctuation so it was better to use the GARCH model to forecast it. The GARCH model had advantage in time series forecasting with a large fluctuation. Finally, the sum of the approximate and detailed series future values was used as the final forecast values. In this paper, there were three contamination factors as the key factors to study the water quality, and there were CODMn, DO and NH₃-N. They were selected according to the edition of GB3838-2002(the Environmental Quality Standard for Surface Water). the limit of basic project standard. Items that would exceed the Ⅱ class standard limit of the project were used as the limit for the pollution factors. Considering that CODMn, COD and BOD were related to the content of organic matter in water, and from past research we learned that CODMn is the main pollution factor in Songhua river environment. It reflects the level of aerobic content in water. As such, we chose the CODMn as one of the main pollution factors. The total nitrogen, total phosphorus and dissolved oxygen reflect the eutrophication status. At the same time, dissolved oxygen is also one of the important factors for the solubility of heavy metals and for all kinds of life organisms in water, we chose it as one of the main pollution factors. NH₃-N is the product of microbial decomposition of nitrogen containing organic matter. We selected it as one of the main pollution factors. The model was tested by actual measured data of DO in Fu-Yuan county from first week to 15th week in 2012. The prediction by the model had no significant difference with actually measured data (P=0.001<0.01, errors < 3.39%), showing high accuracy of the model, and the model was suitable for the prediction of water quality changes. After that, we used this model to predict and analyze the three pollution indicators of four counties in Songhua river basin from first week to eighth week in 2013. The forecasting showing that the errors of dissolved oxygen was between 2.96% and 6.11%, CODMn was between 1.75% and 5.1%, and NH₃-N was between 2.37% and 9.77%. The predicted results had less errors to the measured data, and the forecasting was basically in agreement with measured data. This study can provide a reference for the relevant departments to take the reasonable measures to protect the Songhua river.