Flood Inundation Probability Forecast Jan 2023 - Mar 2023
A predictive model for flood risks in Calgary, Canada, with further application to estimating flood probability for Pittsburgh, PA

GitHub
Floods are one of the most devastating natural disasters, causing widespread damage to communities and infrastructure. As the frequency and intensity of extreme weather events increase, there is a growing need for effective flood risk management strategies. This is where flood inundation analysis comes in.

The purpose of this analysis is to create a predictive model that can estimate the likelihood of flooding in Calgary, Alberta, Canada, based on a range of factors that we have identified as being important. Then we use this model to predict the probability of flood inundation in a comparable city Pittsburgh, Pennsylvania, US, which helps us understand how our model might perform in different contexts.

Ultimately, our goal is that this analysis will provide valuable insights into flood risk management, and help planners make more informed decisions about how to protect their communities from the devastating effects of flooding.



Type: Academic Work | Land use and Environmental Modeling
Group work with Haobing Liu

Role: Data wrangling, Feature Engineering, Exploratory Analysis, Machine Learning - Logistic Regression
Location: Calgary, Canada
Date: January, 2023 - March, 2023








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