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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2018-291
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2018-291
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Jul 2018

Research article | 12 Jul 2018

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Hydrology and Earth System Sciences (HESS).

Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice

Cong Jiang1, Lihua Xiong2, Lei Yan2, Jianfan Dong3, and Chong-Yu Xu2,4 Cong Jiang et al.
  • 1School of Environmental Studies, China University of Geosciences (Wuhan), Wuhan 430074, China
  • 2State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
  • 3Guangxi Water Resources Management Center, Nanning 530023, China
  • 4Department of Geosciences, University of Oslo, P.O. Box 1047 Blindern, N-0316 Oslo, Norway

Abstract. The multivariate hydrologic design under stationary condition is traditionally done through using the design criterion of return period, which theoretically equals to the average inter-arrival time of flood events divided by the exceedance probability of the design flood event. Under nonstationary conditions the exceedance probability of a given multivariate flood event would vary over time. This suggests that the traditional return period concept could not apply to the engineering practice under nonstationary conditions, since by such a definition a given multivariate flood event would correspond to a time-varying return period. In this paper, instead of return period, average annual reliability (AAR) is employed as the criterion for multivariate design, to ensure a given multivariate flood event would correspond to a unique design level under nonstationary conditions. The multivariate hydrologic design conditioned on the given ARR is estimated from the nonstationary multivariate flood distribution constructed by a dynamic C-vine copula, allowing for time-varying marginal distributions and dependence structure. Both the most-likely design event and confidence interval for the multivariate hydrologic design conditioned on the given AAR are identified to provide visual supporting information for designers. The multivariate flood series from the Xijiang River, China are chosen to perform a case study. The results indicate that both the marginal distributions and dependence structure of the multivariate flood series are nonstationary due to the driving force of urbanization and reservoir regulation. The nonstationarities of both the marginal distributions and dependence structure can affect the outcome of the multivariate hydrologic design.

Cong Jiang et al.
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Cong Jiang et al.
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Short summary
We present the methods addressing the multivariate hydrologic design applying to the engineering practice under nonstationary conditions. A dynamic C-vine copula allowing for both time-varying marginal distributions and time-varying dependence structure is developed to capture the nonstationarities of multivariate flood distribution. Then, the multivariate hydrologic design under nonstationary conditions is estimated through specifying the design criterion by average annual reliability.
We present the methods addressing the multivariate hydrologic design applying to the engineering...
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