Prediction of Water Discharge Through the Foundation of a Rockfill Dam in Brazil
In this work, water discharge through the soil foundation of Corumbá-I rockfill dam is predicted using artificial neural networks and the Box and Jenkins autoregressive approach for time series. The analysis is carried out based on a sequence of water discharges measured through the residual soil foundation near the left dam abutment, during the period between 28/08/1997 and 30/12/2002. Application of neural network techniques for prediction and analysis of data from geotechnical instrumentation may be an invaluable tool for performance monitoring of dams and other civil engineering works. In the case of Corumbá-I dam, the artificial neural networks yielded quite satisfactory results with respect to water discharge behavior, including the dependence of the predicted responses on several other factors such as the reservoir water level and the pore pressure values.
The authors are grateful to Furnas Centrais Elétricas S.A. for allowing full access to data of Corumbá-I instrumentation presented in this work.
- Box, G.E., Jenkins, G.M.: Time Series Analysis. Holden-Day, San Francisco (1970)Google Scholar
- Caproni Jr., N., et al.: Fundação em Solo Residual - Barragem de Corumbá I. XXI Seminário Nacional de Grandes Barragens, Rio de Janeiro (in Portuguese) (1994)Google Scholar
- CBB Comitê Brasileiro de Barragens: Main Brazilian dams (2000)Google Scholar
- Dickey, D.A., Fuller, W.A.: Distribution of the estimates for autoregressive time series with a unit root. J. Am. Stat. Assoc. 74, 427–431 (1979)Google Scholar
- Dorffner, G.: Neural networks for time series processing. Neural Netw. World 6, 447–448 (1996)Google Scholar
- Haykin, S.: Neural Networks - A Comprehensive Foundation. Macmillan College Publishing Company, 696 p. (1994)Google Scholar
- Theil, H.: Applied Economic Forecasting. North-Holland, Amsterdam (1966)Google Scholar