An Autocorrelation Correction Analysis to Simulate Daily Streamflow: An Application to the Thames River, London, Ontario, Canada
Chad Shouquan Cheng, EC, Toronto, ON, Canada; and G. Li
An autoregressive error model was applied to simulate daily streamflow volumes for the Thames River, London, Ontario. Meteorological data used in the analysis included daily observations from climate stations located in the Thames River basin for the warm months (April–November) of 1978–2002. The streamflow simulation models were validated using a cross validation procedure, in which each year of the period 1978–2002 was withheld once as an independent dataset for validation of the model. As a result, for the period 1978–2002, 25 models in total were developed. There are significant correlations between daily streamflow volume and model estimations, with all models' R2 greater than 0.7 and RMSEs less than 2.8 m3 s-1 (overall mean and standard deviation: 2.60 and 4.95 m3 s-1, respectively). The corresponding qualities (R2 and RMSE) for model validation were similar to those of model development. The statistical procedure is being extended to other locations in Ontario. This study has further potential to be adapted to analyze extreme rainfall-related flooding risks and some possible impacts of climate change.
Poster Session 4, Weather to Climate Scale Flood Forecasting Posters
Wednesday, 17 January 2007, 2:30 PM-4:00 PM, Exhibit Hall C
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