Computational Flood Modeling
Like floods themselves, the conversation around flood prevention has an ephemeral nature. The strongest interest in flood prevention and mitigation is right after a flooding event. Yet the best time to mitigate, is before a flood event.
Phase 1
By combining dynamic data streams with predictive modelling, information systems can be used to undertake environmental monitoring and flood predictions.
Data dashboards equipped with computational hydrodynamic flood models and predictive weather models, allow a lean predictive system to monitor landscape level flows.
[Application will take a few moments to initialize.] Disclaimer: Please note that this version is a demonstration of the technology and is not intended for inference. External link: https://northshieldenviro.shinyapps.io/floodmapdemo/ Made through the support of the Okanagan Basin Watershed Board and the Government of British Columbia.
One of the challenges to communicating flood risk is the language. Terms like “100 year flood” are made to describe the probability of the peak flow based on historic data on the river system a.k.a the Flood Return Period. It never speaks to how much water that is. However, communicating to the public can be challenging due to the nature of such terminology. While the unspoken inclusion of probability goes completely unmentioned, it also creates a sense of false reassurance that the “100 year flood” only happens once every 100 years. This tool was designed to overcome this communication barrier. Every simulation is a reality this ideal river system can encounter. Notice how irrespective of the time frame selected, the flood events can occur unpredictably. Flood Return Period is just that; a probability of occurrence, and how much water is expected once every set years is a variable that can change, especially in the face of climate change.