Disaster Risk Goes Beyond Counting People

Context

The disaster risk financing in India, especially the 16 th Finance Commission, is based on population numbers instead of real hazard exposure, which distorts the allocation of resources. The method compromises adequate preparedness in the high-risk states such as Odisha that are exposed to cyclones and floods, but are underfunded because of the general low figures. The real risk assessment requires a detailed data on the vulnerability and the location-based threats.

Key Arguments for Differentiating People Count from Risk

• Exposure vs. Population: The Intergovernmental Panel on Climate Change (IPCC) refers to exposure as individuals and property in risky regions. A large state which has few exposures or a small state with many exposures (e.g. coastal areas) can be distorted when only headcount is used.
• Multiplicative Formula Fallacies: Risk formulae based on total population tend to inflate the risk scores of large, safe states and to deflate the risk scores of small, high-vulnerability states that require funding the most.
• Multidimensional Vulnerability: Vulnerability and exposure are functions of hazard. The real risk factors are the housing quality, resilience of infrastructure and socioeconomic factors (poverty, accessibility) and not only population density.
• Example of Misallocation: As recent reports indicate, the formula based on headcount and not on exposure to hazards is grossly underestimating the demands of states such as Kerala and Odisha, which experience extreme weather but are not the most populous. 

Core Problem

The total state population is a proxy measure of so-called exposure, which disregards space. High scoring states such as the Uttar Pradesh (scaled 1-25) can be populated in-land although majority of the population may be away of the hazards. Conversely, Odisha has a hazard score of 12, which compares to the 224.2 of Bihar because of the weighting of the population, although it has a coast that is vulnerable to cyclones. This weakness takes us back to old ways of doing things, undoing the gains made on risk-based planning.

Flawed Exposure Metrics

The IPCC clarifies the exposure as individuals in areas of hazard and not a summation of the administration. The formula used in India is comparing safe plateau inhabitants to coastal vulnerable groups, and this is misleading. The factors of vulnerability such as poverty, infrastructure vulnerability and governance are not measured, which increases inequities.

Why Population Counts Fail

Disaster risk = Hazard x Exposure x Vulnerability, according to the world standards. Headcount does not account for demographics such as age, health, and settlement in floodplains or seismic areas. Latin American analyses by UNFPA reveal 19.2% exposure to earthquakes and 15.4% risk of hurricanes connected to spatial data, but not aggregates. This translates to a lack of funding in specific early warnings or robust infrastructure in India.

Real-World Impacts

Odisha intense cyclones are pushed aside against the sheer numbers of Uttar Pradesh. UNDRR cautions that disregard of daily losses due to slow-onset disasters (droughts, epidemics) exacerbates resilience, particularly in climate-prone low-income neighborhoods. Uncontrolled population increase in high-risk areas increases unquantifiable risks.

Proposed Solutions

Experts suggest moving toward a more scientific, data-driven framework: 

• State Disaster Vulnerability Index: The National Disaster Management Authority (NDMA) is expected to issue a yearly index that will be used as the authoritative contribution towards funding.
• Specific Risk Mapping: With the help of BMTPC Vulnerability Atlas and Census block data, define people who live in fact in hazard areas.
• Capitalizing on Existing Data: Use the national family health survey (NFHS-5), Pradhan Mantri Fasal Bima Yojana (PMFBY) and IMD data to create more precise risk profiles.

Path Forward

Use geospatial methods such as satellite maps to accurately expose (e.g., human beings in 1-in-100-year flood prone areas). Combine multi-hazard indices with vulnerability scores, such as socioeconomic data. Finance Commissions ought to give priority to IPCC-congruent measures as opposed to Census totals.

Conclusion

Hazard, Exposure, and Vulnerability are the interaction of Disaster risk. It is only a part of this equation that is captured by counting total population. To become resilient in the real sense, disaster financing should not be about protecting the most numerous, but about those who are most at risk.

Source: The Hindu

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