Assessing Flood Preparedness: Cautious or Overconfident?

penelope
INST414: Data Science Techniques
3 min readSep 10, 2024
Photo by Wes Warren on Unsplash.

With NASA recording that the proportion of people across the world living in a flood-prone area has increased by 24% since the start of the 21st century, information on how this population deals with the effects of climate change allows for us to understand what areas need to be targeted with more flood protection education. Not only do floods harm those who live there, but according to the National Oceanic and Atmospheric Administration (NOAA) floods are responsible for over $20 billion in damage. Taking advantage of September being National Preparedness Month, I used data from the Federal Emergency Management Agency (FEMA)’s 2023 National Household Survey (NHS) to give myself a better idea of how prepared people believe they are based on the number of preparedness measures they have taken.

The spreadsheet I filtered to answer my question was very rich in data and provided demographic information which could result in an interesting next step as to which specific populations could be more heavily at risk for a lack of flood preparedness. However, for this analysis I compared the percentages of American households who had completed disaster preparedness activities against their peers who had not . With these percentages I was able to gauge how confident each population was on their preparedness against the likelihood the household is aptly prepared.

When conducting analysis on any national survey it is important to note that we only have access to the information that was collected by surveyors. They in turn were only able to collect data on households that were home at the time of canvassing. This wide array in demographics gives us a diverse understanding of the nation’s preparedness in relation to floods, but also faces issues such as knowledge of the English language and understanding of study specific terminology. As such, while the government has cleaned the data to their standards, I decided to focus on figures that I felt were most uniform and most commonly answered. Given more time and work put into both reviewing the data and the problems facing Americans due to increased risk of natural disaster- a more detailed and robust analysis could be made.

The table above displays the perceived likelihood of being prepared in comparison to the number of preventative measures that have been taken. Key takeaways would be the decrease in expected likelihood of preparedness as the number of actions taken to aid during disasters increases and the number of respondents that report their efforts have not aided in quelling their fears in the event of a flood. Those who had taken one action were also more confident in their current preparedness, whereas those who had performed 3 or more actions were more hesitant to rank themselves as highly. Around the board we have a high number of participants that ‘Don’t Know’ their current preparedness status.

Taking this preliminary exploratory analysis into consideration, further research can be conducted to give FEMA and other organizations a more detailed understanding of where they should target their resources and education to reach those who are least likely to be prepared in a flood scenario.

Github repository of my analysis done via Python code and FEMA data set used can be found here. All facts and figures mentioned in this article were taken from the Department of Homeland Security’s website which include FEMA resources.

FEMA and the Federal Government cannot vouch for the data or analyses derived from these data after the data have been retrieved from the Agency’s website.

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