Articles | Volume 23, issue 3
https://doi.org/10.5194/hess-23-1683-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-1683-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Mar 2019
Research article |
| 22 Mar 2019
| 22 Mar 2019
Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice
Cong Jiang
CORRESPONDING AUTHOR
School of Environmental Studies, China University of Geosciences,
Wuhan 430074, China
Lihua Xiong
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
College of Water Conservancy and Hydropower, Hebei University of
Engineering, Handan 056002, China
Jianfan Dong
Guangxi Water Resources Management Center, Nanning 530023, China
Chong-Yu Xu
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Department of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0316 Oslo, Norway
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Manuscript not accepted for further review
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Localized impacts of changing precipitation patterns on surface hydrology are often assessed at a high spatial resolution. Here we introduce a stochastic method that efficiently generates gridded daily precipitation in a future climate. The method works out a stochastic model that can describe a high-resolution data product in a reference period and form a realistic precipitation generator under a projected future climate. A case study of nine catchments in Norway shows that it works well.
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Short summary
We present the methods addressing the multivariate hydrologic design applied to the engineering practice under nonstationary conditions. A dynamic C-vine copula allowing for both time-varying marginal distributions and a 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 applied to the engineering...
