Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 25, issue 4
Articles | Volume 25, issue 4
https://doi.org/10.5194/hess-25-1689-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-1689-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 4
Research article
 | 
06 Apr 2021
Research article |  | 06 Apr 2021

Data assimilation with multiple types of observation boreholes via the ensemble Kalman filter embedded within stochastic moment equations

Chuan-An Xia, Xiaodong Luo, Bill X. Hu, Monica Riva, and Alberto Guadagnini

Viewed

Total article views: 2,354 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,604 694 56 2,354 63 74
  • HTML: 1,604
  • PDF: 694
  • XML: 56
  • Total: 2,354
  • BibTeX: 63
  • EndNote: 74
Views and downloads (calculated since 04 Dec 2020)
Cumulative views and downloads (calculated since 04 Dec 2020)

Viewed (geographical distribution)

Total article views: 2,354 (including HTML, PDF, and XML) Thereof 2,211 with geography defined and 143 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 01 Jun 2025
Download
Short summary
Our study shows that (i) monitoring wells installed with packers provide the (overall) best conductivity estimates; (ii) conductivity estimates anchored on information from partially and fully screened wells are of similar quality; (iii) inflation of the measurement-error covariance matrix can improve conductivity estimates when a simplified flow model is adopted; and (iv) when compared to the MC-based EnKF, the MEs-based EnKF can efficiently and accurately estimate conductivity and head fields.
Read more
Share