Articles | Volume 26, issue 15
Research article
05 Aug 2022
Research article |  | 05 Aug 2022

Spatiotemporal optimization of groundwater monitoring networks using data-driven sparse sensing methods

Marc Ohmer, Tanja Liesch, and Andreas Wunsch


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-69', Anonymous Referee #1, 28 Mar 2022
  • RC2: 'Comment on hess-2022-69', Anonymous Referee #2, 05 May 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (28 May 2022) by Mauro Giudici
AR by Marc Ohmer on behalf of the Authors (31 May 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (09 Jun 2022) by Mauro Giudici
RR by Hugo Loaiciga (26 Jun 2022)
RR by Anonymous Referee #2 (06 Jul 2022)
ED: Publish as is (09 Jul 2022) by Mauro Giudici
Short summary
We present a data-driven approach to select optimal locations for groundwater monitoring wells. The applied approach can optimize the number of wells and their location for a network reduction (by ranking wells in order of their information content and reducing redundant) and extension (finding sites with great information gain) or both. It allows us to include a cost function to account for more/less suitable areas for new wells and can help to obtain maximum information content for a budget.