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

Guo, Danlu; Lintern, Anna; Webb, J. Angus; Ryu, Dongryeol; Bende-Michl, Ulrike; Liu, Shuci; Western, Andrew William

doi:https://doi.org/10.5194/hess-24-827-2020

Articles | Volume 24, issue 2

https://doi.org/10.5194/hess-24-827-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-24-827-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 2

Research article

|

24 Feb 2020

Research article |

| 24 Feb 2020

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

Danlu Guo, Anna Lintern, J. Angus Webb, Dongryeol Ryu, Ulrike Bende-Michl, Shuci Liu, and Andrew William Western

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Final revised paper (published on 24 Feb 2020)
Supplement to the final revised paper
Preprint (discussion started on 23 Jul 2019)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review of hess-2019-342', Anonymous Referee #1, 20 Aug 2019
- AC4: 'Response to Comments from Reviewer #1', Danlu GUO, 16 Oct 2019
RC2: 'Review of hess-2019-342: “A predictive model for spatio-temporal variability in stream water quality” by Guo et al.', Matthias Gassmann, 27 Aug 2019
- AC2: 'Response to Comments from Reviewer #2', Danlu GUO, 16 Oct 2019
RC3: 'Review of "A predictive model for spatio-temporal variability in stream water quality"', Mark Honti, 29 Aug 2019
- AC3: 'Response to Comments from Reviewer #3', Danlu GUO, 16 Oct 2019
RC4: 'review of hess-2019-342', Anonymous Referee #4, 10 Sep 2019
- AC1: 'Response to Comments from Reviewer #4', Danlu GUO, 16 Oct 2019

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

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.