Time Series Analysis of Water Quality Data in Pearl River, China
Publication: Journal of Environmental Engineering
Volume 115, Issue 3
Abstract
A time series analysis approach was applied to model 21 years of mean monthly water quality data in the Guangzhou reach of the Pearl River in southern China. The basic properties of the water quality data time series were determined, time‐ and frequency‐domain analyses were carried out, and the dependent stochastic component was represented by various stochastic models. Synthetic water quality data were generated by using the probability distribution of the independent residuals, and forecasting of future water quality data was done using a Box‐Jenkins‐type difference model. Eighteen years of data were used for model development, while the model performance was compared with the data for the remaining three years. The comparisons were found to be satisfactory.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Akaike, H. (1974). “A new look at the statistical model identification.” IEEE Trans. Autom. Control, 19(6), 716–723.
2.
Box, G. E. P., and Jenkins, G. M. (1976). Time series analysis: forecasting and control. Holden‐Day, San Francisco, Calif.
3.
Carlson, R. F., MacCormick, A. J. A., and Walts, D. G. (1970). “Application of linear random models to four annual stream flow time series.” Water Resour. Res., 6(4), 1070–1078.
4.
Dresnack, R., and Dobbins, W. E. (1968). “Numerical analysis of BOD and DO profiles.” J. Sanit. Engrg. Div., ASCE, 94(5), 789–807.
5.
Falkner, C. H. (1972). “DO prediction model for a long river.” Water Resour. Res., 8(6), 1547–1559.
6.
Finney, B. A., Bowles, D. S., and Windham, M. P. (1982). “Random differential equations in water quality modelling.” Water Resour. Res., 18(1), 122–134.
7.
Gupta, R. K., and Chanhan, H. S. (1986). “Stochastic model of irrigation requirements.” J. Irrig. and Drain Engrg., ASCE, 112(1), 65–76.
8.
Huck, P. M., and Farquhar, G. J. (1974). “Water quality models using Box‐Jenkins method.” J. Envir. Engrg. Div., ASCE, 100(3), 733–753.
9.
Kalman, R. E. (1960). “A new approach to linear filtering and prediction problems.” J. Basic Engrg., 82, 35–45.
10.
Kottegoda, N. T. (1980). Stochastic water resources technology. John Wiley, New York, N.Y.
11.
Ljung, G. M., and Box, G. E. P. (1978). “On measure of lack of fit in time series models.” Biometrika, 65(2), 297–303.
12.
Lohani, B. N., and Wang, M. M. (1987). “Water quality data analysis in Chung Kang River.” J. Envir. Engrg., ASCE, 113(1), 186–195.
13.
McKerchar, A. I., and Delleur, J. W. (1974). “Application of seasonal parametric linear stochastic models to monthly flow data.” Water Resour. Res., 10(2), 246–255.
14.
McMichael, F. C., and Hunter, J. S. (1972). “Stochastic modelling of temperature and flow in rivers.” Water Resour. Res., 8(1), 87–98.
15.
Noakes, D. J., et al. (1988). “Forecasting annual geophysical time series.” Int. J. Forecasting, 4, 103–115.
16.
Ozaki, T. (1976). “On the order determination of ARIMA models.” Appl. Stat., 26(3), 290–301.
17.
Salas, J. D., et al. (1980). Applied modelling of hydrologic time series. Water Resources Publications, Littleton, Colo.
18.
Snedecor, G. W., and Cochran, W. G. (1967). Statistical methods. The Iowa State University Press, Ames, Iowa.
19.
Thomann, R. V. (1967). “Time series analysis of water quality data.” J. Sanit. Engrg. Div., ASCE, 93(1), 1–23.
Information & Authors
Information
Published In
Journal of Environmental Engineering
Volume 115 • Issue 3 • June 1989
Pages: 590 - 607
Copyright
Copyright © 1989 ASCE.
History
Published online: Jun 1, 1989
Published in print: Jun 1989
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.