How monsoon damage is forcing India to plug gaps in tracking infra losses

A new database aims to track real losses as monsoons batter roads, power, and telecom, exposing gaps in disaster planning

When water gushes out of river channels, what is the greatest damage it can cause to infrastructure? Despite pictures of torn houses and cars, if roads, telecom towers and power stations remain safe, the scale of loss is not more than 30 per cent of the overall infrastructure assets in the area.

 

In this mega monsoon season billowing over India, these are some slivers of reassuring thought, since India does not have any sequestered sum available to finance such losses. A report written by the New Delhi-based Coalition for Disaster Resilient Infrastructure (CDRI), a global network of countries working to make infrastructure safe, notes: “Roads and railways, telecommunications, and power and energy account for around 80 per cent of the total annual average loss of infrastructure sectors, so strengthening resilience in these sectors will generate an important dividend in most countries.”

 

The report, dated 2023, also notes that while floods and winds damage power plants, landslides impact roads and rail networks more severely. In the current bout of rains, it is not surprising that roads have been the most affected.

 

Once the water recedes, these will be the largest concern for the Centre and the state governments. It is pertinent that till now the country did not have any way to know the extent of these infrastructure losses. This was rectified only as late as March this year. The two-decade-old Disaster Management Act of 2005 was amended in the Budget session of Parliament to set up a “disaster database.” 

 

Safi Ahsan Rizvi, advisor (mitigation) in the National Disaster Management Authority (NDMA), notes that the amendments, widening definitions of disaster, will allow for larger capital works like mapping of glacier lakes. The tragedy at Dharali was due to the overloading of a glacier lake overlooking the village. While the surface of the lake above the Kheer Gad Nallah was snow, it had accumulated massive tons of water underneath which, like the Towering Inferno in real life, came down on the unfortunate residents. “Of the 7,500 such glacial lakes, the NDMA has mapped the risk profile of about 175, so you can guess the scale of work that is needed,” he said. The lake above Dharali had not yet been mapped.

 

The amended provision reads: there shall be a disaster database which will include “disaster assessment, fund allocation detail, expenditure, preparedness and mitigation plan, risk register according to type and severity of risk and such other relevant matters, in accordance with such policy, as may be determined by the Central Government.”

 

This is separate from the funds made available to meet immediate losses for the families of those affected by floods, landslides and other urgent priorities for reconstruction and rehabilitation. Those are supposed to be met from the respective pools of money in the National Disaster Risk Management Fund (NDRMF) and State Disaster Risk Management Funds (SDRMF). These sums are provided by each Finance Commission. Even after the release of Rs 1.39 trillion since FY22, there is a headroom of about Rs 40,000 crore at the end of August this year, from the corpus of Rs 2.28 trillion made available by the 15th Finance Commission for this five-year period.

 

Even this allocation was intuitive rather than based on research. The Commission under NK Singh used a trend line of expenditure by states and the Centre to arrive at the figure of Rs 1.8 trillion.

 

Loss to infrastructure is also difficult to assess since there are few other sources to tabulate the risks. The non-life insurance companies in India often do not cover many of these risks. The Fire and Special Perils cover trails far behind health and motor vehicle insurance, which are more lucrative for these companies.

 

The reluctance is because property insurance, under which these catastrophic risks are slotted, demands reinsurance cover to be bought from the international market by non-life insurance companies. That expenditure cuts into company profits. For FY25, all Indian insurance companies have insured themselves for about Rs 35,000 crore of risks such as floods and catastrophic losses. 

 

“To cut costs, most of them have taken a very long-drawn-out risk model,” said Alok Yagnik, former deputy general manager for reinsurance at the government-run Oriental Insurance Company. The premium scale they use means the reinsurers expect payouts to happen once in a 200-year time frame. The premium is thus very little, said Yagnik. Even the database is only based on those who have taken the insurance cover and does not reflect the estimated loss for any area, including uninsured assets.

 

The Union finance ministry does not have access to any database of climate-induced disasters on infrastructure. The expenditure department depends on data provided by the state governments.

 

Yet the stakes are high. The same CDRI report projects that the annual average loss to infrastructure in India could reach about $8 billion by 2100. This is more than 5 per cent of India’s current annual infrastructure spending at the present run rate.

 

A possible way to finance the scale of the risk is to start the market for Cat Bonds, the acronym for Catastrophic Bonds. These bonds are financial instruments which transfer risks related to catastrophic events like natural disasters to investors. The investors receive high yields but lose their principal if a predefined natural disaster occurs before the bond matures.

 

These market-based systems have become popular in many countries except India. While both the government and insurance companies favour them in principle, they have not taken off. NDMA has pushed for this market to develop, said Rizvi. But since insurance companies mostly do not cover these risks, the market has not been formed.

 

Essentially, the NDMA would issue the bonds as a quasi-sovereign body to keep the yields manageable. The buyers are expected to be long-term investors, including pension and insurance companies. Separate bonds could be issued for disasters in each state since their risk profiles vary. If a disaster strikes, these investors lose, but customising the risks to specific events cuts those losses. Meanwhile, a pool of money grows beyond the fiscal support of states.

 

'India is a multi-hazard geography, needs multi-faceted approach' 

Safi Ahsan Rizvi, advisor (mitigation) in the National Disaster Management Authority (NDMA), speaks in detail to Subhomoy Bhattacharjee about the planning, both past and future, that goes on at the NDMA. Edited excerpts: 

 

Q: Does NDMA have an early assessment of the extent of the loss of infrastructure in the current monsoon season? 

A: It is too early to present an assessment of the damage and loss to infrastructure for the current monsoon season, given that there is still one month left, which is forecast by IMD to witness 109% of the LPA (Long Period Average). In the immediate aftermath of a significant disaster, MHA appoints an Inter Ministerial Committee (IMCT), mostly led, else participated in by NDMA, which travels to the affected region for an immediate assessment of damage and provides a rough estimate. With this as the basis, MHA forms its assessment and allots funds to the States.

 

Q: To what extent has the concept of resilient infrastructure seeped into policy making in India? 

A: Buffeted by 14 formally notified disasters in the schedule to the DM Act of 2005, India is a multi-hazard geography, requiring a multi-faceted approach to building resilience. Some examples - the successful implementation of the National Cyclone Risk Mitigation Programme of Rs 5,000 crore over the past decade has laid cyclone-resilient roads, bridges, underground cabling and created multi-purpose shelters for evacuations. India Rail has built heat- and cold-resilient rail tracks, sleepers and wagons, signalling systems and transmission lines across tens of thousands of kilometres. Metro rails in hot regions like Delhi are capable of emerging from long tunnels with temperatures of 20 degrees Celsius into scorching heat of 48 degrees in peak summer, with services remaining largely unaffected. Similarly, telecommunication lines and towers remain functional in most regions of extreme heat. The resilience problem does arise when high-intensity hazards hit, as in the recent floods and landslides in the north. Efforts to make such public infrastructure more resilient is a multi-ministerial, multi-State, multi-authority task,

 

Q: How can financial instruments like insurance pools or CAT bonds impact the disaster mitigation exercises. To what extent is the Centre and/or the states willing to participate in these projects. 

A: Both nat-cat (natural catastrophe) risk pools and CAT bonds are evolved instruments of disaster risk insurance. Cat bonds are intelligent instruments that expand risk sharing into the very deep-pocketed global financial markets, offering a risk curve, which is entirely different in causation, scale, intensity and probability compared to financial risk curves, hence of great relevance to those pension and hedge funds seeking risk-diversification. NDMA has been involved in discussions with all possible stakeholders in assessing the need for and possibilities of introducing risk pools and cat bonds in India.

 

Q: One understands NDMA has had some major successes in making glacier lakes safer despite the current climate challenges. How did you do it? 

A: It is too early to say that India’s glacial lakes are safer. We have a very long way to go, but we have made a confident start. We have just initiated a process to set up a standardised continuum to assess, monitor, alert, mitigate, prepare and respond to GLOFs (glacial lake outburst floods). NDMA established a CoDRR (Committee on Disaster Risk Reduction) platform for deep discussion with States/UTs, scientific and academic institutions.  Based on NRSC’s Atlas of 2023, which listed about 7,500 glacial lakes, CoDRR listed 195 of these at-risk, classified into four risk-based categories.