Articles | Volume 22, issue 5
https://doi.org/10.5194/hess-22-2739-2018
https://doi.org/10.5194/hess-22-2739-2018
Research article
 | 
07 May 2018
Research article |  | 07 May 2018

A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley, California

Katherine M. Ransom, Andrew M. Bell, Quinn E. Barber, George Kourakos, and Thomas Harter

Viewed

Total article views: 4,092 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,831 1,157 104 4,092 94 91
  • HTML: 2,831
  • PDF: 1,157
  • XML: 104
  • Total: 4,092
  • BibTeX: 94
  • EndNote: 91
Views and downloads (calculated since 17 Jan 2018)
Cumulative views and downloads (calculated since 17 Jan 2018)

Viewed (geographical distribution)

Total article views: 4,092 (including HTML, PDF, and XML) Thereof 3,756 with geography defined and 336 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Dec 2024
Download
Short summary
We estimated a probability distribution of nitrogen loading rates for crop and land-use groups from regional groundwater data. Water & natural land use had the lowest estimated rates, while dairy land use had the highest. Most results compare favorably to previous estimates, though mass balance estimates for several crop groups were higher than our model estimates. The information can provide a better assessment of land-use impacts to water quality absent information on farm nutrient management.