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

Model code and software

marcohmer/GMNO: Initial Release M. Ohmer

PySensors: A Python Package for Sparse Sensor Placement (v0.3.3) B. M. de Silva, K. Manohar, E. Clark, B. W. Brunton, J. N. Kutz, and S. L. Brunton

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.