Articles | Volume 26, issue 8
https://doi.org/10.5194/hess-26-2221-2022
https://doi.org/10.5194/hess-26-2221-2022
Research article
 | 
29 Apr 2022
Research article |  | 29 Apr 2022

Soil moisture estimation in South Asia via assimilation of SMAP retrievals

Jawairia A. Ahmad, Barton A. Forman, and Sujay V. Kumar

Viewed

Total article views: 3,222 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,494 648 80 3,222 104 70 61
  • HTML: 2,494
  • PDF: 648
  • XML: 80
  • Total: 3,222
  • Supplement: 104
  • BibTeX: 70
  • EndNote: 61
Views and downloads (calculated since 08 Sep 2021)
Cumulative views and downloads (calculated since 08 Sep 2021)

Viewed (geographical distribution)

Total article views: 3,222 (including HTML, PDF, and XML) Thereof 3,073 with geography defined and 149 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
Assimilation of remotely sensed data into a land surface model to improve the spatiotemporal estimation of soil moisture across South Asia exhibits potential. Satellite retrieval assimilation corrects biases that are generated due to an unmodeled hydrologic phenomenon, i.e., irrigation. The improvements in fine-scale, modeled soil moisture estimates by assimilating coarse-scale retrievals indicates the utility of the described methodology for data-scarce regions.