Flood events are the main danger around the world. According to Moody 2024 report, more than 2.3 billion people are exposed to floods every year. In India, more than 600 million people are threatened by coastal or inland floods. However, there is no comprehensive data on the risk of flood exposure to vulnerable communities, especially in the global south.
The new study tried to bridge this gap by analyzing satellite images of informal settlements or apartments in 129 countries with low and medium incomes and comparing them with maps of 343 well documented large floods.
The study found that India had the largest population of the slum in the world living in vulnerable settlements in floodplains-more than 158 million, more than in Russia, most of which concentrated in the natural flood delta of the Ganga River.
Watch | India has the highest number of slum clusters in areas susceptible to floods: Study
The largest concentrations and the largest number of such people are in South Asian countries; Northern India leads in absolute numbers, followed by Indonesia, Bangladesh and Pakistan. Other remarkable “hotspots” include Rwanda and its neighborhood, North Morocco and the coastal region of Rio de Janeiro.
In total, 33% of informal settlements, which are around 445 million people living in 908,077 households, lie in the global south that have already been exposed to floods. Earth, such as India and Brazil, also have a disproportionately high number of NIV settlements, although they have also suffered many large floods.
Studies, Published in natural cities In July, it emphasizes the lack of risk management strategies that prefer vulnerable communities, including those that have already experienced floods beyond the approaches at the population level.
Risk and settlement
Scientists classified human settlements such as rural, suburban and urban and found that Latin America and Caribbean had a high degree of urbanization (80%), and therefore there were more than 60% of settlements in urban areas. Sub -Saharan Africa, on the other hand, had the lowest urbanization rate and almost 63% of informal settlements were rural. In Sierra Leone and Liberia, most of the population of informal settlements hosted.
In India, at the time of the study, 40% of the inhabitants of the slum lived in urban and suburban areas.
People settle or are forced to settle in floods for a combination of factors, including access to jobs, social vulnerabilities and financial restrictions. In India and Bangladesh, the low -lying gangetic delta and the large national population contribute to the number.
The study also emphasized inequalities in access to resources and thus the local reaction to floods. These vulnerable residents also suffer from loss of jobs and access to services among the indirect consequences of floods.
It has been found that the vulnerability of exposed populations depends on socio -economic factors, such as the level of education and institutional factors such as flood insurance.
The authors of the study wrote that both the inhabitants of the slum and the inhabitants of Non-Slum live in floodplains around the world, but for various reasons. In richer regions, such as Europe, subsidized for flood insurance in high -risk areas supports the suitability of floodplains such as Beachfronts and water views.
There are also infrastructure, such as fees, to protect people and houses. In the global south, however, the flood zones offer cheaper land and housing and catch households in more vulnerable areas.
The data show that non -formal settlements also have clear bias towards settling in floods, while slum residents are 32% more likely to settle at lower lower costs, as evidenced by cities such as Mumbai and Jakarta. In fact, the higher the risk of floods, the higher the chance that people will settle there.
“In cities like Bengalur, there is certainly a very strong correlation between informal settlements and their vulnerability towards the floods,” said Aysha Jennath, research for climate and postdoToToToToje at the Indian Institute for Human settlements, Bengalur.
“Locations susceptible to floods are not preferred by large builders for closed communities or IT parks, so these areas are available for migrant workers and informal settlements because they are cheaper.”
Informal settlements in such urban areas are usually tin, tent or tarpaulin housing, with rent paid owners through soil suppliers (“TheKedars”).
SDG term
Scientists have determined the need to negotiate the risk of the vulnerability of the flood for poorer populations because the UN agenda is approaching the UN agenda for the UN Agenda for Sustainable Development Objectives (SDG). Objectives number 17, including the removal of poverty and hunger, the use of clean water and hygiene and to take climate measures. All UN Member States are asking for vulnerable communities.
The study also expressed the importance of adopting an approach to a person (a place focused on a place) to improve insufficient infrastructure.
Data shows large concentrations of settlements in smaller areas, indicating gaps in the area of housing, infrastructure and basic services. Often even defended communities ensure areas susceptible to floods and push vulnerable communities into areas with higher risks that worsen by infrastructure failure and drainage deficiency, Jennath said.
“Real Estate plays a huge role in how these informal settlements appear.”
Finally, scientists also discussed the need for the government to cooperate with communities instead of banking only on traditional disasters readiness. Improving skills in areas such as hygiene, waste management and installation of drainage systems could improve resistance not only floods but also other risks such as infectious diseases, while providing jobs.
“These data based on the data emphasize the excessive flood exhibition that faces the inhabitants of the slum in the global south and emphasize the need for fair and fair management of flood adaptations,” they wrote.
The findings are also proof of the concept of using machine learning, which can process large amounts of data, for analyzing satellite images and extraction of nuance knowledge, such as socio -economic data built into the population density. As tracking, the authors said they were planning to study time processes such as slum expansion, climate change and human migration to effectively predict the future flood risk.
Sandhya Ramesh is a freelance journalist.
