Articles | Volume 23, issue 5
https://doi.org/10.5194/hess-23-2225-2019
© 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-23-2225-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Process-based flood frequency analysis in an agricultural watershed exhibiting nonstationary flood seasonality
Department of Civil and Environmental Engineering, University of
Wisconsin-Madison, Madison, WI 53706, USA
Daniel B. Wright
Department of Civil and Environmental Engineering, University of
Wisconsin-Madison, Madison, WI 53706, USA
Zhihua Zhu
CORRESPONDING AUTHOR
Department of Water
Resources and Environment, Sun Yat-sen University, Guangzhou, 510275, China
Cassia Smith
Department of Civil and Environmental Engineering, Carnegie Mellon
University, Pittsburgh, PA 15213, USA
Kathleen D. Holman
Department of the Interior, Bureau of Reclamation, Denver, CO 80225, USA
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- Exploring multidecadal changes in climate and reservoir storage for assessing nonstationarity in flood peaks and risks worldwide by an integrated frequency analysis approach Y. Zhou 10.1016/j.watres.2020.116265
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Latest update: 14 Dec 2024
Short summary
The relationship between flood severity and probability is a key component of flood risk management, and depends on factors including rainfall, soil wetness, and watershed properties. In this study, we combine radar rainfall data and flood simulations to better understand how these factors
shapeflood frequency. We apply our method to an agricultural watershed in the Midwestern US where the flood properties are changing. Conventional methods will fail to account for these changes.
The relationship between flood severity and probability is a key component of flood risk...