| Title |
Time Series Analysis of Stream Water Quality by Transfer Function Noise Model |
| Authors |
조정석(Chung Seok Cho),류병로(Byong ro Ryu),한양수(Yang Su Han) |
| Abstract |
The purpose of this study is to develop the stochastic stream water quality model for the intaking station of Kongju city waterworks in the Keum river system. This model was based on the theory of Box-Jenkins multiplicative ARIMA(SARIMA) and the transfer function to simulate changes of water qualities. The water qualities included in the models are BOD of Kongju station and BOD of Yeongi station. The model development was based on the data obtained from Jan. 1985 to Dec. 1996 and followed the typical procedures of the Box-Jenkins method including identification, estimation, and diagnostic check. In the most cases we analyzed a single time series without explicitly using information contained in the related time series. In many forecasting situations, other events will systematically influence the series to be forecasted(the dependent variables), and therefore, there is a need to go beyond a unvariate forecasting model. Thus, we must build a forecasting model that incorporates more than one time series and introduces explicitly the dynamic characteristics of the system. Such a model is called a multiple time series model or transfer function model. The prediction ability of SARIMA model and transfer function noise model were tested using the data collected from Jan. 1997 to May 1998. There were good agreements between the model predictions and the field measurements. Most of the predicted values were located within the 95% confidence limits. The performance of the SARIMA model and the transfer function noise model were examined through comparisons between the historical and generated monthly BOD series. The result reveal that the transfer function noise model lead to the improved accuracy. |