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: 3,575 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,540 961 74 3,575 87 92
  • HTML: 2,540
  • PDF: 961
  • XML: 74
  • Total: 3,575
  • BibTeX: 87
  • EndNote: 92
Views and downloads (calculated since 16 Mar 2022)
Cumulative views and downloads (calculated since 16 Mar 2022)

Viewed (geographical distribution)

Total article views: 3,575 (including HTML, PDF, and XML) Thereof 3,415 with geography defined and 160 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 22 Oct 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