Towards Developing a Physically Based Ice Jam Flood Early Warning System

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River floods are the most common natural disaster. In Canada, besides open water floods, it is necessary to consider ice jam floods (IJF) since almost all river systems are ice-affected for several months of the year. IJFs are costing Canadians hundreds of millions of dollars each year. Recent IJFs on the Athabasca River at Fort McMurray, AB (spring 2020), and on the Chaudière River in the Beauce region, QC (spring 2017 and 2019) are evidences that despite all the technological advancements in recent years, still our abilities to successfully predict and prepare for these events are limited. In this context, developing an operational IJF Early Warning Systems (IJF-EWS), is an urgent priority for Canadian governments and municipalities so that sustainable flood mitigation measures can be developed. Ice jams are very complex, and therefore, the development of an IJF-EWS that can predict the timing, location and magnitude of ice jams can be successfully achieved if a physically based coupled hydrological-river ice model is developed. Progress has been made in recent years developing this type of models, but the inaccuracy and sparsity of field data during break-up are preventing the improvement and further developments of these models. To address this need, I am proposing an ambitious research program having as a long-term goal to build an operational, transferable and adaptable IJF-EWS. The short-term objectives of the proposed research program are to:   (1) Assess the applicability of ice-affected discharge measurements methods to different river sizes and types (regional aspect) and to adapt these methods for continuous measurements during the ice cover and break-up periods (temporal aspect).   (2) Develop new methods (or adapt existing ones) for continuous measurements of river ice characteristics over longer reaches (spatial aspect).   (3) Develop and validate a coupled hydrological-river ice model to accurately simulate break-up processes (modeling aspect). Three PhD and three MSc students will work on the above objectives. The students will receive training on the use of a wide variety of sophisticated field instrumentation, advanced data processing methods and numerical modelling. Field measurements will be conducted on two rivers over multiple winters. A coupled hydrological-river ice model will be developed in the Delft-FEWS platform using HOOPLA (for hydrology) and River1D (for river ice processes). The coupled model will be validated using multi-year field data. The developed IJF-EWS will have a great impact by providing forecasting information to guide the development of sustainable flood mitigation measures.