Cascading Risk Takers has received the following awards and nominations. Way to go!
We developed a demo of a user interface to showcase the cascading effects caused by flood occurrence and the damage caused to infrastructure. When you click on a city, we show possible floods for that area, and then show the infrastructure damage data in various categories.
As we read more about flood occurrences, the Sendai framework for disaster risk management, our team really empathized with the damage caused by the floods. We were particularly drawn to the cascading effects of a natural disaster, and in this case, a flood occurrence.
We decided to compute, predict, monitor and showcase the data of infrastructural damage caused by the cascading effect of a flood occurrence, which might be ignored if we just examined the direct damage caused by a flood. For example, the damage caused by a flood will have a negative effect on sanitation, or the disruption of communication will further delay rescue teams to get to a location, which in turn will increase the population that will be displaced.
The idea is to predict a flood that will occur for a particular city, and based on the magnitude of the flood damage, we wanted to get the population data to measure number of people displaced, number of households to measure power disruption, damage to historic sites, and other metrics that will help city officials to take steps to decrease the exposure and vulnerability of infrastructure to flood damage.
The ideal solution would look like this:
We used the Leaflet api to load water levels of rivers in the UK (that's the only dataset that worked for us), and also the water level data of Wax Lake in LA. The plan was to predict the probability of flood occurrence based on the rising water levels in the rivers and lakes.
Data used:
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1801
Next steps are to use the population data surrounding these particular rivers and lake, to predict population displacement. We would do the same for other infrastructure data available for those surrounding areas.
https://vimeo.com/464855677
https://github.com/khaifahmi99/nasa-hackathon
https://cascading-risk-takers.web.app/
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1801
https://www.epimorphics.com/working-with-flood-data-in-qgis/
https://github.com/khaifahmi99/nasa-hackathon
Additional research done by our team member on water levels, CO2 and Sustainable Economy:
https://docs.google.com/document/d/1OB9WKAcRJINdl0fCsfLey01-Vjrbw7RGYCMWYfBe92w/edit?usp=sharing
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