Articles | Volume 9, issue 5
https://doi.org/10.5194/esurf-9-1347-2021
https://doi.org/10.5194/esurf-9-1347-2021
Research article
 | 
11 Oct 2021
Research article |  | 11 Oct 2021

A hybrid data–model approach to map soil thickness in mountain hillslopes

Qina Yan, Haruko Wainwright, Baptiste Dafflon, Sebastian Uhlemann, Carl I. Steefel, Nicola Falco, Jeffrey Kwang, and Susan S. Hubbard

Viewed

Total article views: 2,996 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,078 848 70 2,996 272 48 68
  • HTML: 2,078
  • PDF: 848
  • XML: 70
  • Total: 2,996
  • Supplement: 272
  • BibTeX: 48
  • EndNote: 68
Views and downloads (calculated since 18 Jan 2021)
Cumulative views and downloads (calculated since 18 Jan 2021)

Viewed (geographical distribution)

Total article views: 2,996 (including HTML, PDF, and XML) Thereof 2,734 with geography defined and 262 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
We develop a hybrid model to estimate the spatial distribution of the thickness of the soil layer, which also provides estimations of soil transport and soil production rates. We apply this model to two examples of hillslopes in the East River watershed in Colorado and validate the model. The results show that the north-facing (NF) hillslope has a deeper soil layer than the south-facing (SF) hillslope and that the hybrid model provides better accuracy than a machine-learning model.