Journal metrics

Journal metrics

  • IF value: 2.281 IF 2.281
  • IF 5-year value: 2.693 IF 5-year 2.693
  • CiteScore value: 2.43 CiteScore 2.43
  • SNIP value: 1.193 SNIP 1.193
  • SJR value: 0.965 SJR 0.965
  • IPP value: 2.31 IPP 2.31
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 73 Scimago H index 73
Volume 17, issue 7 | Copyright
Nat. Hazards Earth Syst. Sci., 17, 1033-1045, 2017
https://doi.org/10.5194/nhess-17-1033-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Jul 2017

Research article | 06 Jul 2017

River predisposition to ice jams: a simplified geospatial model

Stéphane De Munck1, Yves Gauthier1, Monique Bernier1, Karem Chokmani1, and Serge Légaré2 Stéphane De Munck et al.
  • 1Centre Eau Terre Environnement, Institut National de la Recherche Scientifique (INRS), Québec City, Québec, G1K 9A9, Canada
  • 2Ministère de la Sécurité publique (MSP), Québec City, Québec, G1V 2L2, Canada

Abstract. Floods resulting from river ice jams pose a great risk to many riverside municipalities in Canada. The location of an ice jam is mainly influenced by channel morphology. The goal of this work was therefore to develop a simplified geospatial model to estimate the predisposition of a river channel to ice jams. Rather than predicting the timing of river ice breakup, the main question here was to predict where the broken 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 initially 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 was 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 Québec) were chosen as test sites. The resulting maps were assessed from historical observations and local knowledge. Results show that 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 cases). Results, limitations, and potential improvements are discussed.

Download & links
Publications Copernicus
Download
Short summary
Ice jams emerge from the accumulation of fragmented ice on a specific section of a river, obstructing the channel and restricting the flow. The resulting floods are socioeconomically costly as well as life threatening. When breakup occurs and ice starts to move downstream the river, a key question is, where would the released ice be susceptible to jam? The goal of this work was to develop a simplified geospatial model to estimate the predisposition of a river channel to ice jams.
Ice jams emerge from the accumulation of fragmented ice on a specific section of a river,...
Citation
Share