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Publication Additional Information Download
Publication Type
Journal Article
Authorship
Williams, B. S., Das, A., Johnston, P., Luo, B., & Lindenschmidt, K. E.
Title
Measuring the skill of an operational ice jam flood forecasting system
Year
2021
Publication Outlet
International Journal of Disaster Risk Reduction, 52, 102001.
DOI
https://doi.org/10.1016/j.ijdrr.2020.102001
Citation
Williams, B. S., Das, A., Johnston, P., Luo, B., & Lindenschmidt, K. E. (2021). Measuring the skill of an operational ice jam flood forecasting system. International Journal of Disaster Risk Reduction, 52, 102001. https://doi.org/10.1016/j.ijdrr.2020.102001
Abstract
Though mitigation measures and research have increased over the last few decades, ice jams and associated flooding continue to be one of the most underestimated disasters in many northern countries. Operational ice jam flood forecasting systems are becoming one of the more prominent tools used in mitigating ice-related flood risk within Canada. Several forecasting systems have been adopted across the country and forecasters are constantly looking to improve the accuracy and consistency of their systems. The Lower Red River in Manitoba has been the subject in discussion of many ice jam related studies, and a data-driven ice-jam hazard forecasting system is currently in use at this site. This system differs from hydrologic model driven forecasting systems used for other ice jam prone rivers across Canada. This study focuses on identifying the methodology of the data driven ice jam flood forecasting system, along with the methodology of the forecasting procedures. Furthermore, the effectiveness of the data driven forecasting system is measured and assessed for the Lower Red River's 2020 breakup season.

Program Affiliations
GWF: Global Water Futures
Project Affiliations
GWF-IMPC: Integrated Modelling Program for Canada
Publication Stage
Published
Additional Information
IMPC
Download Links
https://doi.org/10.1016/j.ijdrr.2020.102001
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