Articles | Volume 21, issue 12
https://doi.org/10.5194/hess-21-6425-2017
https://doi.org/10.5194/hess-21-6425-2017
Research article
 | 
18 Dec 2017
Research article |  | 18 Dec 2017

Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

Mary C. Ockenden, Wlodek Tych, Keith J. Beven, Adrian L. Collins, Robert Evans, Peter D. Falloon, Kirsty J. Forber, Kevin M. Hiscock, Michael J. Hollaway, Ron Kahana, Christopher J. A. Macleod, Martha L. Villamizar, Catherine Wearing, Paul J. A. Withers, Jian G. Zhou, Clare McW. H. Benskin, Sean Burke, Richard J. Cooper, Jim E. Freer, and Philip M. Haygarth

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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by Editor and Referees) (08 Sep 2017) by Christian Stamm
AR by Mary Ockenden on behalf of the Authors (16 Oct 2017)  Author's response   Manuscript 
ED: Publish subject to minor revisions (review by editor) (26 Oct 2017) by Christian Stamm
AR by Mary Ockenden on behalf of the Authors (08 Nov 2017)  Author's response   Manuscript 
ED: Publish as is (09 Nov 2017) by Christian Stamm
AR by Mary Ockenden on behalf of the Authors (10 Nov 2017)
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Short summary
This paper describes simple models of phosphorus load which are identified for three catchments in the UK. The models use new hourly observations of phosphorus load, which capture the dynamics of phosphorus transfer in small catchments that are often missed by models with a longer time step. Unlike more complex, process-based models, very few parameters are required, leading to low parameter uncertainty. Interpretation of the dominant phosphorus transfer modes is made based solely on the data.