Flood Routing Efficiency Assessment: an Approach Using Bivariate Copulas

9 pages•Published: September 20, 2018

Matteo Balistrocchi, Roberto Ranzi, Stefano Orlandini and Baldassare Bacchi

Abstract

Flood control reservoirs are widely recognized as effective structural practices in order to mitigate the flood risk in natural watersheds. Nevertheless, the flood frequency distribution in the downstream reach is strongly affected by a certain number of characteristics of the upstream flood hydrographs. When a direct statistical method is utilized, a multivariate approach should therefore be utilized to accurately assess reservoir performances. In this paper, a flood frequency distribution of the routed flow discharge is derived from a bivariate joint distribution function of peak flow discharges and flood volumes of hydrographs entering the reservoir. Such a joint distribution is constructed by using the copula approach. Reservoir performances are also exploited to categorize event severity and to estimate their bivariate return periods. The method is applied to a real-world case study (Sant’Anna reservoir, Panaro River, northern Italy), and its reliability is verified through continuous simulations. Bearing in mind the popularity that design event methods still have in practical engineering, a final evaluation of the performance assessment achievable by simulations of synthetic hydrographs derived from a flood reduction curve is finally proposed.

Keyphrases: bivariate return period, copulas, derived distributions, floods, reservoir, synthetic hydrographs

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 173-181.

Links:	https://easychair.org/publications/paper/nN9f
	https://doi.org/10.29007/bjr1

BibTeX entry

@inproceedings{HIC2018:Flood_Routing_Efficiency_Assessment,
  author    = {Matteo Balistrocchi and Roberto Ranzi and Stefano Orlandini and Baldassare Bacchi},
  title     = {Flood Routing Efficiency Assessment: an Approach Using Bivariate Copulas},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/nN9f},
  doi       = {10.29007/bjr1},
  pages     = {173-181},
  year      = {2018}}

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