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Original Articles

Modelling heteroscedasticty of streamflow times series

Modélisation de l'hétéroscédasticité des séries temporelles de débit

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Pages 54-64 | Received 28 Dec 2011, Accepted 04 May 2012, Published online: 30 Nov 2012

Figures & data

Fig. 1 (a) ACF of daily streamflows, (b) ACF of the lag-1 differenced logarithmic daily streamflow, (c) p values of the Ljung-Box of the residuals, and (d) p values of the Engle test for SSRs of the ARIMA (13,1,4) model.

Fig. 1 (a) ACF of daily streamflows, (b) ACF of the lag-1 differenced logarithmic daily streamflow, (c) p values of the Ljung-Box of the residuals, and (d) p values of the Engle test for SSRs of the ARIMA (13,1,4) model.

Fig. 2 p values of the Engle test for SSRs of the ARIMA-PGARCH error model.

Fig. 2 p values of the Engle test for SSRs of the ARIMA-PGARCH error model.

Fig. 3 p values of the Engle test for SSRs of the ARIMA-TGARCH error model.

Fig. 3 p values of the Engle test for SSRs of the ARIMA-TGARCH error model.

Fig. 4 p values of the Engle test for SSRs of the ARIMA-EGARCH error model.

Fig. 4 p values of the Engle test for SSRs of the ARIMA-EGARCH error model.

Fig. 5 Scatter plot of observed against estimated streamflows for different models.

Fig. 5 Scatter plot of observed against estimated streamflows for different models.

Fig. 6 Time series plot of observed and estimated streamflows for different models.

Fig. 6 Time series plot of observed and estimated streamflows for different models.

Table 1  Evaluation criteria for time series models (italics indicate result is significant)

Fig. 7 QQ plots of time series models.

Fig. 7 QQ plots of time series models.

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