Abstract Manager

The scale and availability of topographic, hydrologic, and site-specific data is limited for remote transportation infrastructure locations in Northern Ontario. The ability to dynamically model interconnected lakes and watersheds, which features a substantial storage component will drastically improve the accuracy of peak flow estimation. This refinement to peak flow estimation allows a more accurate reflection of hydrologic and hydraulic performance through and around critical transportation infrastructure, while recognizing Ontario Ministry of Transportation drainage design criteria requirements. Through this dynamic modelling process critical infrastructure can have more detailed and accurate results to safeguard against flood events and future climate change. These remote Northern locations experience severe flooding due to not only large watersheds, but climate change as well. With the availability of open data provided by the Province of Ontario and increased accuracy of open-source raster data, this modelling approach yields efficient, effective, and tangible results. This paper explores the approach, applications, and benefits of utilizing direct precipitation flood modelling for isolated regions in Northern Ontario. The application of an integrated hydrologic and hydraulic flood modelling can lead to enhancements in the decision-making process to invest in infrastructure resiliency by enabling more accurate predictions of flood-prone areas, better prioritization of mitigation measures, and proactive emergency response planning.