Articles | Volume 22, issue 9
Hydrol. Earth Syst. Sci., 22, 4633–4648, 2018
https://doi.org/10.5194/hess-22-4633-2018
Hydrol. Earth Syst. Sci., 22, 4633–4648, 2018
https://doi.org/10.5194/hess-22-4633-2018

Research article 06 Sep 2018

Research article | 06 Sep 2018

A geostatistical data-assimilation technique for enhancing macro-scale rainfall–runoff simulations

Alessio Pugliese et al.

Viewed

Total article views: 2,532 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,601 888 43 2,532 42 53
  • HTML: 1,601
  • PDF: 888
  • XML: 43
  • Total: 2,532
  • BibTeX: 42
  • EndNote: 53
Views and downloads (calculated since 13 Oct 2017)
Cumulative views and downloads (calculated since 13 Oct 2017)

Viewed (geographical distribution)

Total article views: 2,414 (including HTML, PDF, and XML) Thereof 2,384 with geography defined and 30 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 02 Dec 2021
Download
Short summary
This research work focuses on the development of an innovative method for enhancing the predictive capability of macro-scale rainfall–runoff models by means of a geostatistical apporach. In our method, one can get enhanced streamflow simulations without any further model calibration. Indeed, this method is neither computational nor data-intensive and is implemented only using observed streamflow data and a GIS vector layer with catchment boundaries. Assessments are performed in the Tyrol region.