Commuters wade via a waterlogged highway in Mumbai on June 28, 2023.
| Photo Credit: PTI
Like many different cities in India, Mumbai has skilled frequent excessive rainfall occasions resulting in extreme floods and waterlogging in the final decade. However, researchers are unable to observe the flood scenario in real time as a consequence of lack of any system that captures such data. Now, a crew of researchers led by IIT Bombay has discovered a method to obtain this — they turned to Twitter to crowdsource data to identify in real time areas which are water logged after heavy rainfall.
The outcomes of the research, that are but to be peer-reviewed, have been posted in arXiv, a preprint server.
The crew led by Dr. Subimal Ghosh from the Department of Civil Engineering at IIT Bombay used an automatic programme to retrieve flood-related data from Twitter. Using approximate stage of water logging and placement info, they have been capable of present real-time details about flooding in Mumbai. The automated system to gather very important flood-related info from Twitter started final 12 months making it doable to observe floods in real time.
They evaluated the usefulness of crowdsourced flood data for monitoring by utilizing the data of an excessive rainfall occasion on July 5, 2022. They additionally retrieved flood-related tweets from earlier years, and this helped in producing flood maps for heavy rainfall occasions in the previous couple of years.
After the notorious flood of 2005 when Mumbai acquired about 90 cm of rainfall in 24 hours, the Municipal Corporation of Greater Mumbai arrange a community of computerized climate stations (presently at 60 areas). “Besides other information, the automatic weather stations provide rainfall data at 15 minutes interval. But the stations do not provide any information on waterlogging or flooding,” says Prof. Ghosh. “This is where crowdsourced real time flooding data becomes very useful.”
Prof. Ghosh says that climate stations that acquired heavy rainfall and positioned in locations with low elevations usually tend to be flooded. “It is precisely from these locations that we see more tweets related to waterlogging. We have seen consistency of crowdsourced data on flooding being with rainfall data we get from the automatic weather stations,” he says.
While individuals voluntarily share flood-related info on a number of social media platforms, the researchers turned to Twitter to gather crowdsourced data. According to Shrabani Sailaja Tripathy from IIT Bombay and the primary writer of the preprint, apart from being a big database, crowdsourced data out there on Twitter is freely accessible and offers very helpful and pertinent info that can be temporary. “We need information about the location, water logging scenario and approximate water level (ankle, knee or waist) to be able to monitor flooding in real time,” Prof Ghosh says. Extracting info from tweets turns into simpler when customers share info utilizing sure particular hashtags (#MumbaiRains #Mumbaiflood #Mumbaiflooddata).
The researchers educated round 80 volunteers from an NGO final 12 months to work as volunteered geographic info (VGI) members to offer info concerning flood location and water stage. The marketing campaign additionally included open requests to Twitter account holders to grow to be volunteers and supply info by tweeting in a particular format. “Compared with the Twitter dataset, the trained volunteers are very small and spread across the city but they provide very reliable information, and this helps us validity the data retrieved from Twitter,” says Prof. Ghosh.
To forecast floods one or three days in advance, the researchers must know the bottom situation. The info culled from tweets present invaluable details about preliminary floor situations for flood forecasting.
To validate the conclusions drawn from the crowdsourced data, the researchers surveyed six main flood hotspots in Mumbai. Though the venture started final 12 months, they back-tracked flood-related info from crowdsourced data from 2017 to 2022; there have been 75 excessive occasions throughout this era. While there was a lot of flood-related tweets on days with excessive rainfall earlier than the pandemic, the variety of tweets dropped in 2021 and 2022 although the variety of excessive occasions solely elevated. “We were not sure if fewer number of tweets about flooding from four of these hotspots was due to COVID-19 or due to less flooding. We learnt about the mitigation measures undertaken by local authorities, which had resulted in reduced flooding in the four hotspots and was in concordance with fewer tweets from these areas,” he says.
The researchers are creating a portal and an App to gather data from Twitter and the volunteers and make out there flood maps of Mumbai in real time. “We are hopeful of completing it by mid-August. This should help us capture flood-related data in real time for the rest of this monsoon season,” Prof. Ghosh says.
