Preprints
https://doi.org/10.5194/hessd-8-9757-2011
https://doi.org/10.5194/hessd-8-9757-2011
08 Nov 2011
 | 08 Nov 2011
Status: this preprint was under review for the journal HESS. A revision for further review has not been submitted.

Evaluation dam overtopping risk based on univariate and bivariate flood frequency analysis

E. Goodarzi, M. Mirzaei, L. T. Shui, and M. Ziaei

Abstract. There is a growing tendency to assess the safety levels of existing dams based on risk and uncertainty analysis using mathematical and statistical methods. This research presents the application of risk and uncertainty analysis to dam overtopping based on univariate and bivariate flood frequency analyses by applying Gumbel logistic distribution for the Doroudzan earth-fill dam in south of Iran. The bivariate frequency analysis resulted in six inflow hydrographs with a joint return period of 100-yr. The overtopping risks were computed for all of those hydrographs considering quantile of flood peak discharge (in particular 100-yr), initial depth of water in the reservoir, and discharge coefficient of spillway as uncertain variables. The maximum height of the water, as most important factor in the overtopping analysis, was evaluated using reservoir routing and the Monte Carlo and Latin hypercube techniques were applied for uncertainty analysis. Finally, the achieved results using both univariate and bivariate frequency analysis have been compared to show the significance of bivariate analyses on dam overtopping.

E. Goodarzi, M. Mirzaei, L. T. Shui, and M. Ziaei
 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
E. Goodarzi, M. Mirzaei, L. T. Shui, and M. Ziaei
E. Goodarzi, M. Mirzaei, L. T. Shui, and M. Ziaei

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