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Global Assessment Report on Disaster Risk Reduction 2013
From Shared Risk to Shared Value: the Business Case for Disaster Risk Reduction |
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Global Assessment Report on Disaster Risk Reduction 2013
From Shared Risk to Shared Value: the Business Case for Disaster Risk Reduction |
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104 Part I - Chapter 6
In Niger, a 2009 drought caused the loss of approximately 410,000 metric tonnes (MT) of millet—about 13 percent of expected production (IRIN, 2010
IRIN (Integrated Regional Information Netwrs). 2010.,Niger: Southern villages emptying as drought bites., Humanitarian News and Analysis. 6 December 2012.. . Improved modelling of agricultural drought, together with down-scaled climate scenarios put it in a framework that is consistent with risk estimates for other hazards and could reduce uncertainty regarding distribution and intensity of agricultural drought as well as its potential impacts.
A better understanding of the relationship between drought likelihood, food production losses as well as the wider risks to natural capital and social sectors would encourage informed investments by the agribusiness sector and more relevant and effective public policy decisions by governments. Together, these two players—public and private—could be one step ahead of damaging environmental change by limiting the risks associated with countries’ natural capital.
Notes
i Data from World Resources Institute (WRI): Per Capita Emissions:
metric tonnes of CO2 equivalent (mtCO2e) per person. Additional data: Puerto Rico, http://www.epa.gov/ttnchie1/net/2008inventory.html; Hong Kong (Special Administrative Region China), http:// www.epd.gov.hk/epd/english/climate_change/files/ HKGHG_Sectors_201009.pdf; Federal States of Micronesia, http://unfccc.int/ resource/docs/natc/micnc1.pdf.
ii For example, the Rio+20 Natural Capital Summit (http://www. uncsd2012.org/index.php?page=view&type=1000&nr=450&me nu=126) and the WAVES public-private partnership, involving 50 countries and 86 private companies (www.wavespartnership.org). iii The risk reduction index (RRI) is a composite index of underlying capacities and conditions for disaster risk reduction. The environmental degradation rankings are based on a number of proxy indicators such as air pollution, deforestation, desertification, water contamination and water scarcity. For more information on the RRI, please see: http://daraint.org/risk-reduction-index/. iv Based on the Inclusive Wealth Index developed by UNU-IHDP and UNEP (2012). v L3JRC and MODIS MCD45. Although the two global datasets are in agreement regarding the global evaluation of burnt areas, their
evaluation varies significantly depending on region and ecosystems monitored. This can be explained by the different satellite sensors and methodology used; however, it generates uncertainties and is something that needs to be improved in the future.
vi CRED data on: http://www.emdat.be/database. University of Louvain, Belgium. vii Different satellite sensors provide different quantifications of burnt area. viii Agricultural drought is a complex issue that not only depends on rainfall, temperature or soil conditions, but also relates to the specificity of the cultivations as well as irrigation systems. Local, or at least regional, analyses of droughts and drought risk are required to fully understand the drivers of risk as well as the impacts of drought events in each context. IPCC uses the term ‘soil moisture drought’ instead of ‘agricultural drought’ because soil moisture deficits have several additional effects besides those on agro-ecosystems, most importantly on other natural or managed ecosystems (including both forests and pastures) (  Erian et al., 2012 Erian, W., Katlan, B., Ouldbedy, B., Awad, H., Zaghtity, E. and Ibrahim, S. 2012. ,Agriculture Drought in Africa and Mediterranean., Background Paper prepared for the 2013 Global Assessment Report on Disaster Risk Reduction., Geneva,Switzerland. Click here to view this GAR paper. ix http://www.drought.unl.edu/DroughtBasics/TypesofDrought. aspx. x This analysis was carried out using the normalised difference vegetation index, as explained in Erian et al., 2012 Erian, W., Katlan, B., Ouldbedy, B., Awad, H., Zaghtity, E. and Ibrahim, S. 2012. ,Agriculture Drought in Africa and Mediterranean., Background Paper prepared for the 2013 Global Assessment Report on Disaster Risk Reduction., Geneva,Switzerland. Click here to view this GAR paper. xi This figure is based on the changes in the normalised different vegetation index (NDVI) compared with the agricultural seasons ( Erian et al., 2012 Erian, W., Katlan, B., Ouldbedy, B., Awad, H., Zaghtity, E. and Ibrahim, S. 2012. ,Agriculture Drought in Africa and Mediterranean., Background Paper prepared for the 2013 Global Assessment Report on Disaster Risk Reduction., Geneva,Switzerland. Click here to view this GAR paper. xii The left map shows the average location of the March–June 500 mm rainfall isohyets for 1960–1989 (light brown), 1990–2009 (dark brown), and 2010–2039 (predicted, orange). The green polygons in the foreground show the main maize surplus regions; these areas produce most of Uganda’s maize. The blue polygon in the upperright shows the Karamoja region. The right map shows analogous changes for the June–September 500 mm rainfall isohyets |
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