Breakup ice jam prediction methods are desirable to provide early warning and allow rapid, effective ice jam mitigation due to the suddenness with which breakup jams and related flooding occur. However, prediction models are limited to empirical or stochastic models rather than deterministic models because of the difficulties in using deterministic models to forecast the formation of breakup ice jams. Existing ice jam prediction methods range from empirical single-variable threshold-type analyses to statistical methods such as logistic regression and discriminant function analysis. Empirical methods are highly site-specific and tend to over predict jam occurrence. In addition, existing models do not provide quantitative information regarding the risk of errors in prediction, which limits their usefulness in emergency situations. In this paper, existing methods are reviewed and a three-step process to predict breakup ice jams is proposed.

This content is only available via PDF.
You do not currently have access to this content.