Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 30, issue 7
Articles | Volume 30, issue 7
https://doi.org/10.5194/hess-30-2013-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-2013-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 30, issue 7
Research article
 | 
14 Apr 2026
Research article |  | 14 Apr 2026

Integrated catchment classification across China based on hydroclimatological and geomorphological similarities using self-organizing map and fuzzy c-means clustering for hydrological modeling

Jiefan Niu, Ke Zhang, Xi Li, and Hongjun Bao

Viewed

Total article views: 1,186 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
885 248 53 1,186 95 49 66
  • HTML: 885
  • PDF: 248
  • XML: 53
  • Total: 1,186
  • Supplement: 95
  • BibTeX: 49
  • EndNote: 66
Views and downloads (calculated since 28 Nov 2024)
Cumulative views and downloads (calculated since 28 Nov 2024)

Viewed (geographical distribution)

Total article views: 1,186 (including HTML, PDF, and XML) Thereof 1,148 with geography defined and 38 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 14 Apr 2026
Download
Short summary
This study developed a new method for classifying catchments, combining machine learning techniques with climate and landscape data. By analyzing catchments across China, we identified six climate regions and 35 unique catchment types, each with distinct streamflow patterns. This classification method improves hydrological predictions, especially in areas lacking direct data.
Read more
Share