Articles | Volume 24, issue 2
Hydrol. Earth Syst. Sci., 24, 827–847, 2020
https://doi.org/10.5194/hess-24-827-2020
Hydrol. Earth Syst. Sci., 24, 827–847, 2020
https://doi.org/10.5194/hess-24-827-2020

Research article 24 Feb 2020

Research article | 24 Feb 2020

A data-based predictive model for spatiotemporal variability in stream water quality

Danlu Guo et al.

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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: Publish subject to revisions (further review by editor and referees) (22 Oct 2019) by Christian Stamm
AR by Danlu GUO on behalf of the Authors (15 Dec 2019)  Author's response    Manuscript
ED: Publish subject to technical corrections (20 Jan 2020) by Christian Stamm
AR by Danlu GUO on behalf of the Authors (26 Jan 2020)  Author's response    Manuscript
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Short summary
This study developed predictive models to represent the spatial and temporal variation of stream water quality across Victoria, Australia. The model structures were informed by a data-driven approach, which identified the key controls of water quality variations from long-term records. These models are helpful to identify likely future changes in water quality and, in turn, provide critical information for developing management strategies to improve stream water quality.