Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 25, issue 2
Articles | Volume 25, issue 2
https://doi.org/10.5194/hess-25-811-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-811-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 2
Research article
 | 
19 Feb 2021
Research article |  | 19 Feb 2021

Determination of vadose zone and saturated zone nitrate lag times using long-term groundwater monitoring data and statistical machine learning

Martin J. Wells, Troy E. Gilmore, Natalie Nelson, Aaron Mittelstet, and John K. Böhlke

Viewed

Total article views: 3,920 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,787 1,036 97 3,920 354 93 123
  • HTML: 2,787
  • PDF: 1,036
  • XML: 97
  • Total: 3,920
  • Supplement: 354
  • BibTeX: 93
  • EndNote: 123
Views and downloads (calculated since 05 May 2020)
Cumulative views and downloads (calculated since 05 May 2020)

Viewed (geographical distribution)

Total article views: 3,920 (including HTML, PDF, and XML) Thereof 3,610 with geography defined and 310 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 05 Dec 2025
Download
Short summary
Groundwater in many agricultural areas contains high levels of nitrate, which is a concern for drinking water supplies. The rate at which nitrate moves through the subsurface is a critical piece of information for predicting how quickly groundwater nitrate levels may improve after agricultural producers change their approach to managing crop water and fertilizers. In this study, we explored a new statistical modeling approach to determine rates at which nitrate moves into and through an aquifer.
Read more
Share