LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Munck, Stéphane; Gauthier, Yves; Bernier, Monique; Chokmani, Karem; Légaré, Serge (2016)
Languages: English
Types: Article
Subjects:
The goal of this work was to develop a simplified geospatial model to estimate the predisposition of any river channel to ice jams. Rather than predicting river ice break up, the main question here was to predict where the broken up ice is susceptible to jam based on the river’s geomorphological characteristics. Thus, six parameters referred to potential causes for ice jams in the literature were selected: presence of an island, narrowing of the channel, high sinuosity, presence of a bridge, confluence of rivers, and slope break. A GIS-based tool has been used to generate the aforementioned factors over regular-spaced segments along the entire channel using available geospatial data. An "Ice Jam Predisposition Index" (IJPI) was calculated by combining the weighted optimal factors. Three Canadian rivers (Province of Quebec) have been chosen as test sites. The resulting maps were assessed from historical observations and local knowledge. Results show 77 % of the observed ice jam sites on record occurred in river sections that the model considered as having high or medium predisposition. This leaves 23 % of false negative errors (missed occurrence). Between 7 % and 11 % of the highly "predisposed" river sections did not have an ice jam on record (false-positive errors). Potential improvements are discussed.
  • No references.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article

Collected from