Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 23, issue 8
Articles | Volume 23, issue 8
https://doi.org/10.5194/hess-23-3405-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-3405-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 8
Research article
 | 
19 Aug 2019
Research article |  | 19 Aug 2019

Improving hydrological projection performance under contrasting climatic conditions using spatial coherence through a hierarchical Bayesian regression framework

Zhengke Pan, Pan Liu, Shida Gao, Jun Xia, Jie Chen, and Lei Cheng

Viewed

Total article views: 3,612 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,079 1,439 94 3,612 238 119 127
  • HTML: 2,079
  • PDF: 1,439
  • XML: 94
  • Total: 3,612
  • Supplement: 238
  • BibTeX: 119
  • EndNote: 127
Views and downloads (calculated since 04 Feb 2019)
Cumulative views and downloads (calculated since 04 Feb 2019)

Viewed (geographical distribution)

Total article views: 3,612 (including HTML, PDF, and XML) Thereof 3,065 with geography defined and 547 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 Nov 2025
Download
Short summary
Understanding the projection performance of hydrological models under contrasting climatic conditions supports robust decision making, which highlights the need to adopt time-varying parameters in hydrological modeling to reduce performance degradation. This study improves our understanding of the spatial coherence of time-varying parameters, which will help improve the projection performance under differing climatic conditions.
Read more
Share