Abstract: Global change today is more complex than ever before. Over the last 20 years, countries have faced the pervasive and sometimes destructive impact of globalization. Currently, the impacts of extreme climate variability are taking their toll. Perhaps this is climate change, but irrespective of the name, current climatic conditions are not being kind to people across the world. While the visual impacts of changing weather patterns can be seen everywhere, the hidden impacts are actually more dangerous. In particular, the impact of rising temperatures on the global water cycle is a ticking time bomb to which we must proactively respond. To address this, a multidimensional index-based assessment tool has been developed to identify those at risk from the impacts of climate change on water resources. This paper presents this “Climate Vulnerability Index,” and provides some insights on those populations most at risk.
Keywords: climate adaptation, climate vulnerability, Climate Vulnerability Index, demographic impacts, global change, multi-criteria analysis
Although human society’s success depends on water availability, little has been done to recognize its value within modern socio-political and environmental management systems. The challenge of valuing water as a commodity for production still remains due to theoretical and methodological difficulties as well as theological and philosophical objections. As a way of addressing this issue, this paper presents insight into the importance of water to human well-being through an analysis of how human communities may be vulnerable to shifts in global water availability.
There is little dispute that climate patterns are changing in almost every region of the world. The predicted increases in extreme events seem to be occurring in many countries, including record temperatures and levels of precipitation being recorded on a regular basis (Oki and Kanae, 2006; IPCC, 2007b; UNESCO, 2006). Highly energetic cyclones and hurricanes have created billions of dollars of damage in even the most sophisticated of locations, and loss of life and livelihoods have impacted on millions of people across the world. At the same time, drought induced famine has spread across whole countries in Africa (Fussel, 2010).
Everyone depends on water because water is not only essential for all life on earth, but is also a major factor of production for all industrial activities. Every single item of consumption requires water in its production, and every sector of the economy depends on access to water at a reasonable price. While this has been recognized through the concept of “virtual water” in crops and products. (Allan, 1998), we are still far from properly accounting for our water use. As a result, many fail to recognize their own vulnerability to changes in its availability (Huntingford and Gash, 2005; Parry et al., 2004).
Water related vulnerability exists in both urban and rural areas with increased water stress resulting from population growth and increased economic development. At the same time, climate variability has in some areas reduced water supplies, and expectations are that this will only worsen in the future (Rijsberman, 2006; Rockstrom et al., 2011). Only through good demand management, careful planning of water systems, and reduction of inefficient use will it be possible to reduce the level of human vulnerability to the negative impacts of increased water stress (Tompkins, 2007).
Water and climate are inexorably linked through the laws of physics, chemistry and biology that control planet Earth. Earth System Science has now emerged as a core approach to addressing the challenges of resource management, and evidence is now emerging that climate change is having adverse effects on water systems at the local, national, and regional scales (Randall et al., 2007; Rockstrom et al., 2011; Huntingford and Cox, 2000). Many resources have been spent to understand the biophysical aspects of climate change with complex mathematical models being designed to capture what is known about the world and predict what may happen in future conditions (Nurse, 2011; Oerlemans, 2005; IPCC, 2007). The overall result of this analysis suggests that serious water shortages will confront billions of people over the next 20 years (UNESCO, 2006). Additionally, water stress has now been identified by the scientific community as being a major challenge to human well-being.
In spite of all these efforts, most humans remain extremely vulnerable to climate change. While the image of a subsistence farmer struggling in an arid landscape may capture this concept of vulnerability, the reality is that on every continent people from all levels of society are likely to be effected by climate change (Leichenko and O’Brien, 2008, Fung and New, 2011). A major reason for this high level of vulnerability is the interconnectedness of nations today, where globalization has the effect of amplifying climate impacts across spatial and even temporal scales. In recent years, a number of examples of this have been demonstrated. Floods in Thailand disrupted car production in the United States and computer production in Japan grinded to a halt due to the resulting shortage of components. Bad harvests in grain producing areas of the world led to food price spikes in 2008, causing starvation in many poor countries. Low rainfall in Lesotho caused energy failures in the industrial heartlands of South Africa.
There have been several assessments of global water resources, and many different approaches to water resource modeling (Hoff et al., 2010, Doll, 2009, Islam et al., 2007, Huntingford et al., 2010). Most of these are based on grid-based mathematical models which bring together information on rainfall, evaporation, soil moisture, albedo, wind speed and so on, which provide the best possible estimates of surface and sometimes groundwater availability. These calculations, however, are confounded by lack of information on ground and surface water interactions, horizontal water transfer between aquifers, and accurate data on land cover. Such grid based modeling also has its own methodological disadvantages. This includes the challenge of performing the vast number of calculations required to provide an indication of how the grid square values of the various attributes of the hydrological cycle are linked. While there have been attempts made recently to address this challenge (Vorosmarty et al, 2010), there is still a high degree of uncertainty in the results.
While such approaches provide an indication of the extent and volume of water in different part of this hydrological cycle, they are subject to the usual methodological uncertainties of mathematical modeling as well as further weakened by their deterministic theoretical frameworks. Human use of water resources is certainly not only determined by physical conditions. Throughout the world, there are a myriad of other non-physical factors that determine who has access to water, and how much they can appropriate for practical use. A novel attribute of the approach outlined here is to incorporate social, political and economic dimensions into water resource assessment to provide a more comprehensive insight into the relationship between human societies and global water resources. This is achieved by taking a bottom-up approach where assessments of the human condition are linked to physical water resource quantification. The development of the Water Poverty Index (Sullivan, 2002, Sullivan et al., 2003) demonstrated the practicality of this approach, and remains the most widely cited example of such integrated water resource assessment. The term bottom-up here refers to the idea that this approach starts with people on the landscape, and then links them to the larger scale information provided by hydrological and climate models. Other assessments follow a top-down approach, where information from large scale modeling is made available to policymakers usually without specific linkages to societal factors. Irrespective of the approach used, there is much agreement that human appropriation of water resources is rapidly outstripping the available supply and leading to the unfortunate condition of water stress, where resources cannot meet the water need for food production (Alcamo et al., 2007, FAO, 2005).
Responses to water stress will depend on geographical, technological and social factors, and by examining the distributional impact of water vulnerability, adaptive responses can be better targeted to where the return will be greatest. By identifying geospatial variability in the causes of vulnerability, it is possible to develop site-specific insights to support proactive adaptation measures that are tailored specifically to the needs of the place and the people at risk. Clearly, the causes of vulnerability vary depending on the context, and therefore a flexible suite of solutions can be provided to support appropriate responses (Adger et al., 2005). In this context, one size fits all solutions do not work in the real world. At the same time, the real world is increasingly dogged by seemingly intractable water allocation problems, and so tools to address them are increasingly needed.
In the context of human vulnerability to changes in water resources, it is important to understand the site-specific nature of its causes. In this chapter, an attempt to address this is provided through the application of a multicriteria-based assessment tool referred to as the Climate Vulnerability Index (CVI). This composite index approach is used to explore the multidimensional effects on human society of the impacts of climate change on water resources. Firstly, the geographical distribution of water related vulnerability is presented and then the scale of vulnerability within different social groups is examined.
Building on the earlier work on the Water Poverty Index, the Climate Vulnerability Index (Sullivan et al., 2002, Sullivan and Meigh, 2005) is a composite index based on measurements of Global Impact Factors (GIFs) and calculated as a weighted average as shown in Equation 1:
Here, Xi refers to component i of one of the Global Impact Factors within the CVI structure. This relates to the site-specific location being considered, while r acts as a weighting, representing risks associated with each particular GIF. The Global Impact Factors (GIFs) are the main components of the CVI. These represent dimensions of resource allocation decisions which have been identified as giving rise to vulnerability (Sullivan and Huntingford, 2009). By combining these within a composite index, we obtain a measure that reflects the essence of what it means to be vulnerable in the context of globalization. Each of these GIFs is assessed based on scores for various sub-components. Sub-components (illustrated in Table 1) will depend on the location and available data. While any location can select its own components when comparisons are to be made, the same sub-components must be used.
Weights used in the calculation of the CVI reflect the degree of risk “r” associated with the impact of each of the Global Impact Factors. Weights can either be additive or multiplicative, and these are used to indicate the relative importance of the various components in the calculation. For the purpose of calculating the CVI in this demonstration application at a variety of scales, weights have been kept neutral by assigning them all an equal value of one. In practice, weights are best determined through consultation with local experts and stakeholders, but when comparisons are being made between different places it is important to use the same variables with the same weights. When the weighted average scores of the GIFs and their sub-components are calculated, the results can be mapped for use in deliberative policy development, as shown in Figure 1.
While it is clear that the finest resolution data will bring the most accurate results in any model (Sullivan and Meigh, 2007), often in practice data is limited. In terms of public data, this is usually provided at the national scale and this is what has been used in this analysis. It is important to note that a national representation does not provide any indication of how any characteristic or risk is distributed within a country, either geographically, or on the basis of socio-economic variability within the country. For this approach to be useful to policymakers, vulnerability assessment must ideally consider issues at the sub-national scale (illustrated in Figure 1).
There is no doubt that by combining relevant information through a composite index structure it is possible to target response strategies more effectively. This chapter demonstrates the application of this composite index approach at a national scale, but for the purpose of national policymaking, governments and NGOs would be best informed by assessments made at the sub-national scale based on data with the finest resolution possible. In practice, this may be at the provincial or local government area scale. To demonstrate the applicability of the CVI approach, the above analysis has been applied to publicly available data for 17 variables applied to a total of 148 countries. Countries not included are those where adequate data is not available. Figure 2 shows how the computed scores for the CVI are distributed across the world, and highlights the high degree of vulnerability experienced by people in the African continent compared with those in North America or Europe. Once again it is important to note that these national values may be misleading, and it is valuable to consider the number of people at risk rather than the number of nations. This is demonstrated by the figures provided in Table 2.
In Table 2, the number of people in different vulnerability categories in three continents is considered. From this, we can see that while the degree of vulnerability is much higher in Africa (due mainly to low adaptive capacity and access to finance, etc.) than in Asia or Latin America. There is no doubt that for demographic reasons, the scale of the problem is much worse in Asia. Although over 95% of Africans are in the medium to high and high vulnerability categories, this represents some 670 million people while in Asia only 83% of the population are in those categories, but this represents over 2 billion people. Notably, no population in Latin America are in these categories when measured on the national scale, and the levels of human vulnerability to changes in water resources in Latin America is much lower than in other continents. This is also reflected by the fact that most of the major donor agencies do not put as much priority to assist countries in that region.
Characteristics of countries facing different levels of vulnerability to global change in water resources have been analyzed within the CVI structure. By examining the scores for the individual Global Impact Factors for the countries in each continent it is possible to discern the overarching characteristics of each region which give rise to their overall levels of vulnerability to changes in water resources. For example, in both Asia and Africa resource availability is a major issue mostly due to the high demand in major countries as well as ecological health being a serious threat (mainly from land degradation and pollution). For Africa, both access to resources and capacity to manage them are a major source of vulnerability, and so strategies to reduce vulnerability in that region should be focus on relatively easy ways to increase these GIF scores.
Characteristics, which give rise to higher levels of vulnerability in different places, are illustrated through these regional GIF scores. Illustrated in Figure 3, they show how the most vulnerable places are likely to have problems associated with property rights and access, relatively lower and less reliable resource assets, and a lower degree of human and institutional capacity with a higher geospatial risk. This demonstrates how responses to reduce vulnerability can be targeted to what is most needed. For highly vulnerable places, improvement in resource provision is needed (e.g. more water storage) while at the same time better management and institutional arrangements are needed to improve the very low efficiency of water use. In contrast to this, countries with lower vulnerability will have better water access and management capacity. It is interesting to note that in all categories, there is much scope for improvement in water use efficiency.
In order to investigate how humans will be influenced by future changes in water resources we must consider how the demand for water and its supply may change in the future. Most attention has been focusing on how future water resource supplies may change, but the approach presented here incorporates such potential resource changes into other global changes which are happening concurrently (Leichenko and O’Brien). This is essential if we are to move away from a limited deterministic approach, and take account of the realities of the globalized world in which we must function. To achieve this, scenarios of future change are applied to the values of the current scores on the Global Impact Factors. Explicit account of climate change is incorporated through the use of best available hydro-climatic modeling to adjust the value for Resource Quantification, while other global changes associated with economic and demographic change are applied to the non-hydrological GIFs. Thus, through the use of outputs from the HadCM3 model from the UK Hadley Centre, and the application of UNEP derived Policy First scenarios (UNEP, 2002), we can project how the global impact factors may change over time. For simple illustration of this process, three examples are illustrated in Table 4. This shows how each of the Global Impact Factors will change (2000-2030) with the cumulative effect of these changes usually resulting in an overall worsening of the level of vulnerability (higher CVI values, circled). The example of Nepal included here shows that big improvements in one GIF (in this case, accessibility and property rights) can make a big difference to the future outcome. Using an approach such as this allows us to be more adaptive in our development strategies by taking account not only of the past, but also of the future.
Elderly and young persons are likely to be more vulnerable than others to the impacts of global change. By assessing the scale of exposure for these specific groups to climate and other global impacts, it helps to further understand the distributional impacts of vulnerability to changes in water resources, and the different ways it can be addressed. The extent of this risk to young people is shown in Tables 5 and 6. Both in Africa and Asia, young people must be seen as the priority for adaptation not only because they will be the ones facing future challenges, but simply because of the anticipated scale of the impact in terms of numbers affected.
In addition to age groups, demographic differences can be further analyzed on the basis of gender and geographical distribution. Figures 5 and 6 provide illustrations of this for Asian countries. In four countries in the medium to high vulnerability category, over 40% of the population is below 14 years of age (PNG, Pakistan, Nepal and Cambodia) with almost the same proportion of the Bangladeshi population being in the highly vulnerable category. In contrast to this, three countries in the medium to high vulnerability category (Vietnam, Mauritius and China) have higher than average numbers of older people. Thus, in such countries additional attention must be given to this in terms of adaptive planning.
While national values cannot demonstrate internal variability, they are useful for countries to measure their progress relative to others. Such figures are also important in resource allocation by donor agencies. Figure 7 provides a comparison on five countries in Asia, and through this analysis, the varying challenges faced by different countries can be seen.
In Figure 6, the first thing that can be noticed is that Singapore is highly vulnerable in terms of water resources. For South Korea, resource quantification is also a major source of vulnerability, but to a lesser degree. From the perspective of resource quantification, the least vulnerable of the group is Malaysia. Both Singapore and South Korea have a moderate level of vulnerability associated with resource utilization and efficiency, but in terms of geospatial risks considered here (landslides, flooding, drought and so on), China is most vulnerable, followed by South Korea. For China and Malaysia accessibility and property rights are serious sources of vulnerability, and threats to ecological integrity maintenance exist in all parts of the region. By revealing these differences, policymakers in the respective countries can target their attention where it is most needed.
There is no doubt that the number of people at risk from the impacts of global change on water resources is increasing dramatically. Since the nature of the risks people face varies between countries, there must be different responses with adaptable policies (World Bank, 2009). Given the scale of this problem of human vulnerability associated with water resources, there are some generic approaches which can be useful in many countries. For example, it would clearly be beneficial to many countries to increase efforts to achieve greater water security, both from a supply side (more storage) and from the demand side (demand reduction strategies). In almost every country, there is a need to maximize opportunities and incentives to increase water use efficiency in agriculture, industry and services. Legislation should be strengthened to reduce environmental impacts and ensure ecological integrity is maintained by maximizing the benefits from ecosystem services.
The Climate Vulnerability Index has provided the means by which variability in human vulnerabilities to climate change impacts on water resources can be examined. This facilitates investigation of the factors giving rise to vulnerability in specific locations, and the distributional impacts of this vulnerability within different demographic groups within society. While this chapter has demonstrated the CVI approach at a large regional scale, it is important to recognise that more robust results will be generated from finer resolution application at the sub-national scale. By putting such approaches into practice, more holistic information becomes available for strategic decision making, and targeting of resources to support action. In these times of global change, policymakers would be well advised to address uncertainty and risks from climate and other changes by developing more adaptive approaches to managing all natural resources. By taking an active approach to embedding sustainable development in all aspects of government and private sector activities, countries and their people will be better placed to face the certainty of future change.