Climatic Hazards and Advanced Risk Modelling, Co-operators General Insurance Company, Québec, QC, Canada
Centre Eau Terre Environnement, Institut national de la recherche scientifique, Québec, QC, Canada
Sébastien Raymond
Climatic Hazards and Advanced Risk Modelling, Co-operators General Insurance Company, Québec, QC, Canada
Centre Eau Terre Environnement, Institut national de la recherche scientifique, Québec, QC, Canada
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Total article views: 2,669 (including HTML, PDF, and XML)
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2,157
363
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2,669
166
184
HTML: 2,157
PDF: 363
XML: 149
Total: 2,669
BibTeX: 166
EndNote: 184
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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: 3,639 (including HTML, PDF, and XML)
Thereof 3,537 with geography defined
and 102 with unknown origin.
Total article views: 2,669 (including HTML, PDF, and XML)
Thereof 2,573 with geography defined
and 96 with unknown origin.
Total article views: 970 (including HTML, PDF, and XML)
Thereof 964 with geography defined
and 6 with unknown origin.
Modelling floods at the street level for large countries like Canada and the United States is difficult and very costly. However, many applications do not necessarily require that level of detail. As a result, we present a flood modelling framework built with artificial intelligence for socioeconomic studies like trend and scenarios analyses. We find for example that an increase of 10 % in average precipitation yields an increase in displaced population of 18 % in Canada and 14 % in the US.
Modelling floods at the street level for large countries like Canada and the United States is...
