Articles | Volume 24, issue 5
Hydrol. Earth Syst. Sci., 24, 2235–2251, 2020
https://doi.org/10.5194/hess-24-2235-2020
Hydrol. Earth Syst. Sci., 24, 2235–2251, 2020
https://doi.org/10.5194/hess-24-2235-2020

Research article 08 May 2020

Research article | 08 May 2020

Optimal design of hydrometric station networks based on complex network analysis

Ankit Agarwal 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: Reconsider after major revisions (further review by editor and referees) (19 Sep 2018) by Roger Moussa
AR by Anna Mirena Feist-Polner on behalf of the Authors (02 Jan 2019)  Author's response
ED: Referee Nomination & Report Request started (31 Jan 2019) by Roger Moussa
RR by Eric Gaume (18 Feb 2019)
RR by Anonymous Referee #2 (26 Feb 2019)
ED: Reconsider after major revisions (further review by editor and referees) (13 Mar 2019) by Roger Moussa
AR by Ankit Agarwal on behalf of the Authors (14 May 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (31 May 2019) by Roger Moussa
RR by Jon Olav Skøien (01 Aug 2019)
ED: Reconsider after major revisions (further review by editor and referees) (11 Sep 2019) by Roger Moussa
AR by Anna Wenzel on behalf of the Authors (24 Jan 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (04 Feb 2020) by Roger Moussa
RR by Jon Olav Skøien (03 Mar 2020)
ED: Publish subject to minor revisions (review by editor) (11 Mar 2020) by Roger Moussa
AR by Ankit Agarwal on behalf of the Authors (24 Mar 2020)  Author's response
ED: Publish as is (11 Apr 2020) by Roger Moussa
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Short summary
In the climate/hydrology network, each node represents a geographical location of climatological data, and links between nodes are set up based on their interaction or similar variability. Here, using network theory, we first generate a node-ranking measure and then prioritize the rain gauges to identify influential and expandable stations across Germany. To show the applicability of the proposed approach, we also compared the results with existing traditional and contemporary network measures.