GAR 2015 Main Report

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Part II - Chapter 7

to disaster risk management including probabilistic risk assessment and dialogue with finance and planning ministries (Box 7.8).

7.8 On rigour in science

The extent to which the risk information produced since the adoption of the HFA is really informing development is not well known. Even within the disaster risk management community, new scientific information is not applied consistently.

“. . . In that Empire, the Art of Cartography attained

such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time,

those Unconscionable Maps no longer satisfied, and the Cartographers Guilds produced a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that that vast map was Useless, and not without some Pitilessness was it, that they delivered it up to the Inclemencies of Sun and Winters. In the Deserts of the West, still today, there are Tattered Ruins of that Map, inhabited by Animals and Beggars; in all the Land there is no other Relic of the Disciplines of Geography.” 11

In principle, risk information should provide a critical foundation for raising risk awareness and for informing disaster risk management policies, practices, investments and measures from the local to the global level, including financial

Box 7.8 A policy-maker’s view of understanding risk

A recent initiative towards “Building capacities for increased public investment in integrated climate change adaptation and disaster risk reduction” that will span around 40 countries by the end of 2015 helps countries understand and manage disaster risk in a uniquely comprehensive manner.10 The UNISDR-led and European Commission-supported initiative, in partnership with several international agencies and academic institutions, supports countries through a full package approach for disaster loss accounting, probabilistic risk assessment, economic analysis and policy development.

For example, in Mauritius, a total of 1,105 data cards on disaster loss in 1980-2013 were registered, with total economic losses estimated at US$59 million. Of these losses, 82 per cent were found to be from cyclones alone. The following probabilistic risk assessment therefore calculated the average annual loss and probable maximum loss for tropical cyclonic wind, which were estimated at US$87 million (AAL) and U$1.7 billion (PML) for a 100-year return period.

While these numbers highlighted the need to reduce tropical cyclone risk, in themselves they did not provide any policy guidance. Therefore, a thorough policy review and economic analysis were implemented, and it was found that the country would face difficulties in managing losses from cyclones and earthquakes with return periods of only 62 to 87 years. This pointed to the need for Mauritius to invest in both disaster risk reduction as well as risk financing mechanisms, including insurance.

Probabilistic cost-benefit analyses were then conducted to support concrete and specific decision-making, for example on retrofitting of housing, and a further review of the public finance systems was undertaken. As a result, the government found that there were significant gaps in terms of a coherent risk-sensitive investment policy across all relevant sectors, in particular for critical infrastructure, and that contingency financing mechanisms were underdeveloped. Examining the disaster loss and risk information from the perspective of policy-makers, especially financial planners, in Mauritius, highlighted the importance of a linked approach to disaster risk reduction and resulted in concrete recommendations from the Ministry of Finance.

(Source: UNISDR. For more details, see Annex 3.)

	144 Part II - Chapter 7 to disaster risk management including probabilistic risk assessment and dialogue with finance and planning ministries (Box 7.8). 7.8 On rigour in science The extent to which the risk information produced since the adoption of the HFA is really informing development is not well known. Even within the disaster risk management community, new scientific information is not applied consistently. “. . . In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds produced a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that that vast map was Useless, and not without some Pitilessness was it, that they delivered it up to the Inclemencies of Sun and Winters. In the Deserts of the West, still today, there are Tattered Ruins of that Map, inhabited by Animals and Beggars; in all the Land there is no other Relic of the Disciplines of Geography.” 11 In principle, risk information should provide a critical foundation for raising risk awareness and for informing disaster risk management policies, practices, investments and measures from the local to the global level, including financial Box 7.8 A policy-maker’s view of understanding risk A recent initiative towards “Building capacities for increased public investment in integrated climate change adaptation and disaster risk reduction” that will span around 40 countries by the end of 2015 helps countries understand and manage disaster risk in a uniquely comprehensive manner.10 The UNISDR-led and European Commission-supported initiative, in partnership with several international agencies and academic institutions, supports countries through a full package approach for disaster loss accounting, probabilistic risk assessment, economic analysis and policy development. For example, in Mauritius, a total of 1,105 data cards on disaster loss in 1980-2013 were registered, with total economic losses estimated at US$59 million. Of these losses, 82 per cent were found to be from cyclones alone. The following probabilistic risk assessment therefore calculated the average annual loss and probable maximum loss for tropical cyclonic wind, which were estimated at US$87 million (AAL) and U$1.7 billion (PML) for a 100-year return period. While these numbers highlighted the need to reduce tropical cyclone risk, in themselves they did not provide any policy guidance. Therefore, a thorough policy review and economic analysis were implemented, and it was found that the country would face difficulties in managing losses from cyclones and earthquakes with return periods of only 62 to 87 years. This pointed to the need for Mauritius to invest in both disaster risk reduction as well as risk financing mechanisms, including insurance. Probabilistic cost-benefit analyses were then conducted to support concrete and specific decision-making, for example on retrofitting of housing, and a further review of the public finance systems was undertaken. As a result, the government found that there were significant gaps in terms of a coherent risk-sensitive investment policy across all relevant sectors, in particular for critical infrastructure, and that contingency financing mechanisms were underdeveloped. Examining the disaster loss and risk information from the perspective of policy-makers, especially financial planners, in Mauritius, highlighted the importance of a linked approach to disaster risk reduction and resulted in concrete recommendations from the Ministry of Finance. (Source: UNISDR. For more details, see Annex 3.)	Page 1 Page 10 Page 20 Page 30 Page 40 Page 50 Page 60 Page 70 Page 80 Page 90 Page 100 Page 110 Page 120 Page 130 Page 134 Page 135 Page 136 Page 137 Page 138 Page 139 Page 140 Page 141 Page 142 Page 143 Page 144 Page 145 ->Page 146 Page 147 Page 148 Page 149 Page 150 Page 151 Page 152 Page 153 Page 154 Page 155 Page 156 Page 157 Page 158 Page 160 Page 170 Page 180 Page 190 Page 200 Page 210 Page 220 Page 230 Page 240 Page 250 Page 260 Page 270 Page 280 Page 290 Page 300 Page 310