Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
Viewed
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 1,674 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,511
127
36
1,674
11
17
HTML: 1,511
PDF: 127
XML: 36
Total: 1,674
BibTeX: 11
EndNote: 17
Views and downloads (calculated since 05 Feb 2026)
Cumulative views and downloads
(calculated since 05 Feb 2026)
Total article views: 499 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
354
127
18
499
11
17
HTML: 354
PDF: 127
XML: 18
Total: 499
BibTeX: 11
EndNote: 17
Views and downloads (calculated since 29 Jun 2026)
Cumulative views and downloads
(calculated since 29 Jun 2026)
Total article views: 1,175 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,157
0
18
1,175
0
0
HTML: 1,157
PDF: 0
XML: 18
Total: 1,175
BibTeX: 0
EndNote: 0
Views and downloads (calculated since 05 Feb 2026)
Cumulative views and downloads
(calculated since 05 Feb 2026)
Viewed (geographical distribution)
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 1,674 (including HTML, PDF, and XML)
Thereof 1,544 with geography defined
and 130 with unknown origin.
Total article views: 499 (including HTML, PDF, and XML)
Thereof 350 with geography defined
and 149 with unknown origin.
Total article views: 1,175 (including HTML, PDF, and XML)
Thereof 1,175 with geography defined
and 0 with unknown origin.
Global floods pose serious risks, but existing models are too slow for large-scale prediction. We redesigned the Catchment-based Macro-scale Floodplain (CaMa-Flood) model for graphics processing units (GPUs), reformulating irregular river networks, flux updates, and floodplain dynamics into highly parallel algorithms. CaMa-Flood-GPU runs global simulations in hours instead of days with the same accuracy, enabling larger ensembles, better flood-risk analysis, and improved preparedness worldwide.
Global floods pose serious risks, but existing models are too slow for large-scale prediction....