Articles | Volume 25, issue 2
https://doi.org/10.5194/hess-25-945-2021
https://doi.org/10.5194/hess-25-945-2021
Research article
 | 
24 Feb 2021
Research article |  | 24 Feb 2021

Diagnosis toward predicting mean annual runoff in ungauged basins

Yuan Gao, Lili Yao, Ni-Bin Chang, and Dingbao Wang

Download

Interactive discussion

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

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (11 Oct 2020) by Fuqiang Tian
AR by Dingbao Wang on behalf of the Authors (18 Nov 2020)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (30 Nov 2020) by Fuqiang Tian
RR by Anonymous Referee #1 (09 Dec 2020)
RR by Anonymous Referee #2 (15 Jan 2021)
ED: Publish as is (22 Jan 2021) by Fuqiang Tian
AR by Dingbao Wang on behalf of the Authors (22 Jan 2021)  Manuscript 
Download
Short summary
Mean annual runoff prediction is of great interest but still poses a challenge in ungauged basins. The purpose of this study is to diagnose the data requirement for predicting mean annual runoff in ungauged basins based on a water balance model, in which the effects of climate variability are explicitly represented. The performance of predicting mean annual runoff can be improved by employing better estimation of soil water storage capacity including the effects of soil, topography, and bedrock.