Articles | Volume 23, issue 5
Research article
07 May 2019
Research article |  | 07 May 2019

Process-based flood frequency analysis in an agricultural watershed exhibiting nonstationary flood seasonality

Guo Yu, Daniel B. Wright, Zhihua Zhu, Cassia Smith, and Kathleen D. Holman


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (24 Feb 2019) by Matjaz Mikos
AR by Guo Yu on behalf of the Authors (28 Feb 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (01 Mar 2019) by Matjaz Mikos
RR by Anonymous Referee #1 (24 Mar 2019)
RR by Anonymous Referee #3 (01 Apr 2019)
ED: Publish subject to technical corrections (21 Apr 2019) by Matjaz Mikos
AR by Guo Yu on behalf of the Authors (23 Apr 2019)  Author's response    Manuscript
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 shape flood 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.