Tag Archives: disaster risk

India’s Need for Disaster Risk Reduction: Can it Turn a Plan into Action?

This was the first time I’d ever heard a Prime Minister praising the benefits of “risk mapping.” Mid-morning on Thursday November 3 in a vast tent in the heart of New Delhi, the Indian Prime Minister, Narendra Modi, was delivering an introductory address to welcome four thousand delegates to the 2016 Asian Ministerial Conference on Disaster Risk Reduction.

Modi mentioned his own personal experience of disaster recovery after the 2001 Gujarat earthquake in which more than 12,000 people died, before presenting a ten-point plan of action in response to the 2015 Sendai Framework for disaster risk reduction. There were no guarantees of new regulations or changes in policy, but three of his ten points were particularly substantive.

First there was a call for appropriate protections to be applied to all government sponsored construction of infrastructure or housing against the relevant hazards at that location. Second he called for “work towards” achieving universal “coverage” (insurance if not by name?) against disasters– from the poorest villager to big industries and state governments. Third he called for standardized hazard and risk mapping to be developed not only for earthquake but for other perils: chemical hazards, cyclones, all varieties of floods and forest fires.

More Economic Development Means More Exposure to Risk

India is at a development threshold, comparable to that reached by Japan at the end of the 1950s and China in the 1990s. Rapid economic growth has led to a dramatic expansion of building and value in harm’s way and there now needs to be a significant compensatory focus on measures to reduce risk and expand protections, whether through insurance systems or flood walls.  Development in India has been moving too fast to hope that adequate building standards are being consistently followed – there are not enough engineers or inspectors.

The Chennai floods at the end of 2015 have come to highlight this disaster-prone landscape. Heavy end-of-year monsoonal downpours fell onto saturated ground after weeks of rainfall, which were then ponded by choked drainage channels and illegal development, swamping hundreds of thousands of buildings along with roads and even the main airport. The city was cut off and economic losses totaled billions of U.S. dollars, with more than 1.8 million people being displaced.

Sorting out Chennai will take co-ordinated government action and money: to implement new drainage systems, relocate or raise those at highest risk and apply flood zonations. Chennai provides a test that Disaster Risk Reduction really is a priority, as Mr. Modi’s speech suggested. The response will inevitably encounter opposition, from those who cannot see why they should be forced to relocate or pay more in their taxes to construct flood defenses.

The one community notably missing from Prime Minister Modi’s call to action was the private sector, even though a pre-conference session the day before, organized by Federation of Indian Chambers of Commerce (FICCI), had identified that 80% of construction was likely to be privately financed.

I gave two talks at the conference – one in the private sector session – on how modelers like RMS have taken a lead in developing those risk maps and models for India, including high resolution flood models that will help extend insurance. Yet armed with information by which to differentiate risk and identify the hot spots, the government may need to step in and provide its own coverages for those deemed too high risk by private insurers.

Auditing Disaster Risk Reduction with Cat Models

In a side meeting at the main conference I presented on the need to have independent risk audits of states and cities, to measure progress in achieving their disaster risk reduction goals, in particular when it comes to earthquake mortality – for which experience from the last few decades gives no perspective on the true risk of potentially large and destructive future earthquakes happening in India – this is where probabilistic catastrophe models are invaluable. The Nepal earthquake of 2015 has highlighted the significant vulnerability of ordinary brick and concrete buildings in the region.

I came away seeing the extraordinary opportunity to reduce and insure risk in India, if ten-point lists can truly be converted into co-ordinated action.

Meanwhile as a test of the government’s resolve in the days leading up to the conference, Delhi was shrouded in its worst ever smog: a toxic concoction of traffic fumes, coal smoke, and Diwali fireworks, enriched to extremely dangerous levels in micro-particles, a smog so thick and pervasive that it seeped inside buildings, so that several attendees asked why the toxic smog was not itself being classified and treated as a true “manmade disaster.”

Disasters Without Borders

On November 24 and 25, 2015 the first Scientific Symposium was held in London to discuss science for policy and operations for the new “Disaster Risk Management Knowledge Centre.” The Centre was launched by the European Commission in September this year to help member states respond to emergencies and to prevent and reduce the impact of disasters. The Centre will offer EU countries technical and scientific advice, provide an online repository of relevant research results, and create a network of crisis management laboratories. RMS was the only catastrophe modeler invited to present to the meeting.

Jointly organized by the UK Met Office and the European Commission, the symposium exposed some of the tensions between what countries can do on their own and where they require a supranational European institution. The British government contingents were particularly keen to show their leadership. The UK Cabinet Office co-ordinates inputs across government departments and agencies to manage a national risk register, identifying the likelihood and potential impact of a wide range of threats facing the country: from an Icelandic volcanic eruption to a storm surge flood to a terrorist incident. The office of the Chief Government Scientist then leads the response to the latest disaster, reporting directly to the Prime Minister.

These were not responsibilities the UK would ever consider transferring to a new European institution, because they go right to the heart of the function of a government—to protect the people and the national interest. However no single country can provide total management of events that run across borders, in particular when it is the country upstream that is controlling what heads your way, as with water storage dams. For this a Europe wide agency will be vital. The Centre will be most useful for the smaller European countries, unable to sustain research across the full range of hazards, or monitor activity around the clock. However do not expect the larger countries to share all their disaster intelligence.

Where does RMS fit into this picture? As described at the London symposium, probabilistic models will increasingly be key to making sense of potential disaster impacts and for ensuring organizations don’t become fixated on planning against a single historical scenario. RMS has more experience of probabilistic modeling than any other European science or government agency, in particular in areas such as the modeling of floods and flood defenses or for multi-hazard problems.

Two ideas with the potential for RMS leadership got picked up at the symposium. For an intervention such as a new flood defense, the results of the probabilistic model become used to define the “benefits”—the future losses that will not happen. A versatile model is required in which the user can explore the influence of a particular flood defense or even see the potential influence of climate change. Second we can expect to see a move towards the risk auditing of countries and cities, to show their progress in reducing disaster casualties and disaster impacts, in particular as part of their Sendai commitments. We know that risk cannot be defined based only on a few years of disaster data—the outcomes are far too volatile. Progress will need to be defined from consistent modeling. Catastrophe modeling will become a critical tool to facilitate “risk-based government”:  from measuring financial resilience to targeting investment in the most impactful risk reduction.

Measuring Disaster Risk for Global UN Goals

A dispiriting part of the aftermath of a disaster is hearing about the staggering number of deaths and seemingly insurmountable economic losses. Many of the disaster risk reduction programs that implement disaster prevention and preparedness capabilities are helping to create more resilient communities. These worthwhile programs require ongoing financing, and their success must be measured and evaluated to continue to justify the allocation of limited funds.

There are two global UN frameworks being renewed this year:

Both frameworks will run for 15 years. This is the first time explicit numerical targets have been set around disaster risk, and consequently, there is now a more pressing need to measure the progress of disaster risk reduction programs to ensure the goals are being achieved.

The most obvious way to measure the progress of a country’s disaster risk reduction would be to observe the number of deaths and economic losses from disasters.

However, as we have learned in the insurance industry in the early 1990s, this approach presents big problems around data sampling. A few years or even decades of catastrophe experience do not give a clear indication of the level of risk in a country or region because catastrophes have a huge and volatile range of outcomes. An evaluation that is purely based on observed deaths or losses can give a misleading impression of success or failure if countries or regions are either lucky in avoiding (or unlucky in experiencing) severe disaster events during the period measured.

A good example is the 2010 Haiti earthquake, which claimed more than 200,000 lives and cost more than $13 billion. Yet for more than 100 years prior to this devastating event, earthquakes in Haiti had claimed fewer than 10 lives.

Haiti shows that it is simply not possible to determine the true level of risk from 15 years of observations for a single country. Even looking at worldwide data, certain events dominate the disaster mortality data, and progress cannot be measured.

Global disaster-related mortality rate (per million global population), 1980–2013 (From Setting, measuring and monitoring targets for disaster risk reduction: recommendations for post-2015 international policy frameworks. Source: adapted from www.emdat.be)

A more reliable way to measure the progress of disaster risk reduction programs is to use a probabilistic methods, which rely on a far more extensive range of possibilities, simulating tens of thousands of catastrophic events. These can then be combined with data on exposures and vulnerabilities to output metrics of specific interest for disaster risk reduction, such as houses or lives lost. Such metrics can be used to:

  • Measure disaster risk in a village, city, or country and how it changes over time
  • Analyze the cost-benefit of mitigation measures:
    • For a region: For example, the average annual savings in lives due to a flood defense or earthquake early warning system
    • For a location: For example, choosing which building has the biggest reduction in risk if retrofitted
  • Quantify the impact of climate change and how these risks are expected to vary over time

In the long term, probabilistic catastrophe modeling will be an important way to ensure improved measurement and, therefore, management of disaster risk, particularly in countries and regions at greatest risk.

The immediate focus should be on educating government bodies and NGOs on the valuable use of probabilistic methods. For the 15 year frameworks which are being renewed this year, serious consideration should be given on how to implement a useful and practical probabilistic method of measuring progress in disaster risk reduction, for example by using hazard maps. See here for further recommendations: http://www.preventionweb.net/english/professional/publications/v.php?id=39649 

2015 is an important year for measuring disaster risk: let’s get involved.