Preprints
https://doi.org/10.5194/hess-2020-17
https://doi.org/10.5194/hess-2020-17

  18 Feb 2020

18 Feb 2020

Review status: this preprint was under review for the journal HESS but the revision was not accepted.

The Heterogeneous Discrete Generalized Nash Model for Flood Routing

Baowei Yan1, Huining Jiang1, Zhengkun Li1, Jun Zhang2, and Wenfa Yang2 Baowei Yan et al.
  • 1School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
  • 2Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan 430010, China

Abstract. The topographic heterogeneity of the rivers has great effects on the river flood routing. The discrete generalized Nash model (DGNM), developed on the basis of the Nash's instantaneous unit hydrograph (IUH), is a lumped model that can't reflect the spatial heterogeneity of the river topography. The heterogeneous DGNM (HDGNM) with a consideration of such heterogeneity has been developed by the conceptual interpretation of the DGNM. Two compositions of the downstream outflow generated by the recession of the old water stored in the river channel and the discharge of the new water from upstream inflow were deduced respectively with the help of the heterogeneous IUH and the corresponding heterogeneous S curve. The HDGNM is finally expressed as a linear combination of the inflows and outflows, whose weight coefficients are calculated by the heterogeneous S curve. The HDGNM expands the application scope, and becomes more applicable, especially in river reaches where the river slopes and cross-sections change greatly. The middle Hanjiang River was selected as a case study to test the model performance. It is suggested that the HDGNM performs better than the DGNM, with higher model efficiency and smaller relative error in the simulated flood hydrographs.

Baowei Yan et al.

 
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Status: closed
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Baowei Yan et al.

Baowei Yan et al.

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