Seasonal Prediction with Error Estimation of Columbia River Streamflow in British Columbia
Publication: Journal of Water Resources Planning and Management
Volume 129, Issue 2
Abstract
Large-scale climatological states [tropical Pacific sea surface temperatures (SST), Pacific-North American (PNA) atmospheric teleconnection and Pacific Decadal Oscillation (PDO)] and local precipitation data are used to predict the April–August Columbia River streamflow at Donald, British Columbia, Canada. Using predictors up to the end of November in the preceding year, forecasts of the April–August streamflow were made by multiple linear regression (MLR) under a jackknife scheme. A correlation skill of 0.52 is attained using PDO, PNA and SST as predictors, with PDO being the strongest and SST the weakest. When local precipitation is added among the predictors, PDO becomes redundant, and MLR with precipitation, PNA and SST as predictors attained a correlation skill of 0.70. Feedforward neural-network models were used for nonlinear regression, but the results were essentially identical to the MLR predictions, implying that the detectable relationships in the short, 49-sample record are linear. A bootstrap process estimates the relative errors of the MLR predictions.
Get full access to this article
View all available purchase options and get full access to this article.
References
Barnston, A. G., and Livezey, R. E.(1987). “Classification, seasonality and persistence of low-frequency circulation patterns.” Mon. Weather Rev., 115, 1083–1126.
Cayan, D. R., Redmond, K. T., and Riddle, L. G.(1999). “ENSO and hydrological extremes in the western United States.” J. Clim., 12, 2881–2893.
Davison, A. C., and Hinkley, D. V. (1997). Bootstrap methods and their application, Cambridge University Press, Cambridge, U.K.
Efron, B., and Tibshirani, R. J. (1993). An introduction to the bootstrap, Chapman & Hall, New York.
Garen, D. C.(1992). “Improved techniques in regression-based streamflow volume forecasting.” J. Water Resour. Plan. Manage., 118(6), 654–670.
Hamlet, A. F., and Lettenmaier, D. P.(1999). “Columbia River streamflow forecasting based on ENSO and PDO climate signals.” J. Water Resour. Plan. Manage., 125(6), 333–341.
Hsieh, W. W., and Tang, B.(2001). “Interannual variability of accumulated snow in the Columbia basin, British Columbia.” Water Resour. Res., 37, 1753–1759.
Nijssen, B., Lettenmaier, D. P., Liang, X., Wetzel, S. W., and Wood, E. F.(1997). “Streamflow simulation for continental-scale river basins.” Water Resour. Res., 33, 711–724.
Redmond, K. T., and Koch, R. W.(1991). “Surface climate and streamflow variability in the western United States and their relationship to large-scale circulation indices.” Water Resour. Res., 27, 2381–2399.
Smith, T. M., Reynolds, R. W., Livezey, R. E., and Stokes, D. C.(1996). “Reconstruction of historical sea surface temperatures using orthogonal functions.” J. Clim., 9, 1403–1420.
Wilks, D. S. (1995). Statistical methods in the atmospheric sciences, Academic, San Diego.
Yuval(2000). “Neural network training for prediction of climatological time series, regularized by minimization of the generalized cross validation function.” Mon. Weather Rev., 128, 1456–1473.
Yuval(2001). “Enhancement and error estimation of neural network prediction of Niño-3.4 SST anomalies.” J. Clim., 14, 2150–2163.
Information & Authors
Information
Published In
Copyright
Copyright © 2003 American Society of Civil Engineers.
History
Received: Oct 18, 2001
Accepted: Oct 3, 2002
Published online: Feb 14, 2003
Published in print: Mar 2003
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.