Counting people is not counting disaster risk

UPSC Syllabus: Gs Paper 3- Disaster and disaster management.

Introduction

Counting total population instead of people exposed to hazards creates a distorted picture of disaster risk. A State may face intense cyclones or floods but still receive less funding if its population is smaller. This weakens disaster preparedness. A proper system must measure where people live and how vulnerable they are, not just how many people exist in a State.

Evolution of Disaster Financing Framework in India

1. Early relief-based approach: Disaster financing began as relief funding from the 2nd Finance Commission through the Margin Money Scheme. It focused only on post-disaster expenditure.
2. Shift to pre-funded mechanisms: The 9th Finance Commission replaced the scheme with the Calamity Relief Fund, giving States funds in advance. This improved preparedness.
3. Creation of national-level funds: The 10th and 11th Finance Commissions set up national funds like the National Calamity Relief Fund with a 75:25 Centre-State contribution.
4. Institutionalisation through law: The Disaster Management Act, 2005 created the NDRF and SDRF, giving a structured system for disaster financing.
5. Reforms under the 14th Finance Commission: Funds were reorganised into the National Disaster Risk Management Fund (NDRMF) and the State Disaster Risk Management Fund (SDRMF), with 80% for response and 20% for mitigation, and allocation based on capacity, exposure, and risk.
6. Expansion under the 15th Finance Commission: The allocation size increased significantly and used an additive Disaster Risk Index combining hazard, exposure, and vulnerability.

Revised Framework of the 16th Finance Commission

1. Higher allocation size: A total of ₹2,04,401 crore is allocated to SDRF, a 59.5% increase over the previous Commission.
2. Shift to multiplicative risk formula: Disaster Risk Index is defined as Hazard × Exposure × Vulnerability, recognising that risk occurs when all three interact.
3. Conceptual correctness: The framework rightly states that hazard alone is not disaster. Disaster occurs only when people and vulnerability are present.
4. Operational weakness: The method used to measure exposure and vulnerability does not reflect actual disaster conditions, leading to distorted results.

Structural Flaws in Measuring Disaster Risk (16th Finance Commission Framework)

1. Faulty measurement of Exposure: Exposure is calculated using total State population scaled from 1 to 25, giving higher scores to populous States like Uttar Pradesh. This ignores people living in hazard zones. Exposure should reflect location-specific risk. The IPCC defines exposure as people in hazard-prone areas, not total population.
2. Distortion due to multiplicative formula: The formula gives advantage to large population States. High population multiplies the score even if hazard is low. Odisha has the highest hazard score of 12, but its population score of 5 reduces its DRI to 79.8. In contrast, Bihar has 224.2 and Uttar Pradesh has 413.2, despite lower hazard exposure.
3. Misrepresentation of Vulnerability: Vulnerability is measured using per capita NSDP. It assumes poorer States are more vulnerable. This ignores housing quality, health systems, and preparedness. Average income hides inequalities within States and does not reflect real vulnerability.
4. Evidence of flawed vulnerability scoring: Kerala faced ₹31,000 crore flood damage in 2018, yet its vulnerability score is only 1.073 due to higher income. Jharkhand, despite high poverty-based vulnerability, loses 0.78 percentage points due to low population score. Overall, 20 States lost funding share, mainly smaller or relatively wealthier States.

Consequences of the Faulty Framework

1. Penalty for disaster-prone States: Odisha, with 574.7 km coastline and strong preparedness, faces a 1.57 percentage point reduction in funding share.
2. Reward for demographic size: States with larger populations gain more funds, even with lower disaster exposure.
3. Undermining preparedness efforts: States investing in early warning systems and evacuation lose incentives due to reduced funding.
4. Misallocation of resources: Funds do not reach areas with highest actual risk, weakening disaster response capacity.
5. Conflict with climate realities: States like Odisha, Andhra Pradesh, Kerala, and Assam face rising climate risks but receive less support.

Way Forward

1. Redefining exposure correctly: Exposure should count people living in hazard zones like coastal belts, flood plains, and seismic regions.
2. Use of scientific data sources: Data from the Building Materials and Technology Promotion Council (BMTPC) Vulnerability Atlas and Census blocks should be used for precise mapping.
3. Creating a composite vulnerability index: Vulnerability should include kutcha housing share, health infrastructure, agricultural dependence, insurance coverage, and early warning systems.
4. Use of existing datasets: Data from the National Family Health Survey (NFHS-5), Pradhan Mantri Fasal Bima Yojana (PMFBY) database, National Health Mission (NHM) surveys, and India Meteorological Department (IMD) records should be used to build a realistic vulnerability profile.
5. Institutionalising standard metrics: The National Disaster Management Authority (NDMA) should be mandated to publish an annual State-level Disaster Vulnerability Index for use in future Finance Commission allocations.
6. Need for methodological continuity: A stable and accepted framework will avoid disputes in each Finance Commission cycle.

Conclusion

Disaster funding must reflect real risk, not total population size. The present system turns risk assessment into a headcount exercise. This weakens support for highly exposed States and discourages investment in preparedness. A shift to hazard-based exposure and multidimensional vulnerability is essential. Without reform, disaster finance will remain misaligned with climate risks and growing disaster frequency.

Question for practice:

Examine how the 16th Finance Commission’s disaster risk assessment framework leads to misallocation of disaster funds in India.

Source: The Hindu