Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 26, issue 15
Articles | Volume 26, issue 15
https://doi.org/10.5194/hess-26-4033-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-4033-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
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

Viewed

Total article views: 3,758 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,651 1,030 77 3,758 93 100
  • HTML: 2,651
  • PDF: 1,030
  • XML: 77
  • Total: 3,758
  • BibTeX: 93
  • EndNote: 100
Views and downloads (calculated since 16 Mar 2022)
Cumulative views and downloads (calculated since 16 Mar 2022)

Viewed (geographical distribution)

Total article views: 3,758 (including HTML, PDF, and XML) Thereof 3,593 with geography defined and 165 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 23 Nov 2025
Download
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.
Read more
Share