Riptide is a sophisticated yet elegant web application designed to simulate floods all around the globe. Given a location, intensity and duration, Riptide can graphically demonstrate the various effects of a flood. With a user-focused design, anyone is able to learn about the population displaced, and total damage caused by inundation thanks to an intuitive and clean interface. Using topographical and population data from NASA Jet Propulsion Laboratory along with a custom made algorithm, Riptide generates a rendition of coordinates that describe the flow of water after a certain duration.
Follow this link to our Riptide Presentation: https://docs.google.com/presentation/d/1RETNpOlutAkVhuFRoyFCiDfbgYqjcj9PlFVa9uu2xmI/edit?usp=sharing
Front-End: Mrugank Upadhyay & Abbiram Ramanathan
Back-End: Siddharth Gupta & Dev Parikh
Created an aesthetically pleasing, interactive map with search functionality, sliders for elapsed time and flood intensity, and flood simulation Developed an algorithm to determine spread of a flood based on an epicentre, topological data, duration and intensity Determined affects of water damage based on cost of construction and population density
As climate change accelerates the frequency and intensity of floods, understanding how vast amounts of water may harm our infrastructure and people is essential to developing a secure future. Unfortunately, most floods hit developing and underdeveloped nations, those which often lack the resources for emergency preparedness. High-quality flood models have high barriers to entry, making it a luxury for only the nations which can afford it. Our software reduces those barriers as medium-resolution topography data is provided by NASA, we can make models for flood impacts, and provide them to those who need it the most, saving countless lives.
Utilized ReactJS and Mapbox GL to create website components and map Added map search functionality by implementing the Geocoder API Added user controlled sliders by implementing the Slider ReactJS API Added data-driven points to identify flood points using GeoJSON & MapBox GL Feature Collection
Utilized NASA SRTM topology maps in order to create a height map of the area, an algorithm to model water flow. Added population displaced and total damage done, based on population density, and structural engineering of the given city, and it's corresponding boroughs. Stored information in JSON format to be easily parsed by React.
ReactJS MapBox GL JS MapBox Studio NumPy
Implementing a flood simulation overlay with features Curation of relevant and optimal data sets Implementing a server to submit requests from the Map Interface to Back-end algorithm to receive JSON co-ordinate points Developing a realistic algorithm to simulate the spread of water based on topological data