Calculating a Water Poverty Index

Sullivan, Caroline A

doi:10.1016/s0305-750x(02)00035-9

Cited by 665 publications

(467 citation statements)

References 17 publications

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“…Another important interaction includes adaptation practices that increase sensitivity, which is also considered under sensitivity analysis. Sensitivity and adaptive capacity analysis are conducted separately using a weighted balance approach (Sullivan 2002) in which each sub-component contributes to the overall index equally albeit with a varying number of sub-components. For sensitivity analysis, the sensitivity of each variable was calculated first using simple averages as shown in Eq.…”

Section: Calculating Sensitivity and Adaptive Capacitymentioning

confidence: 99%

Livelihood vulnerability assessment to climate variability and change using fuzzy cognitive mapping approach

Singh

Nair

2014

Climatic Change

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Existing studies in the context of assessing vulnerability to climate variability and change delineate, rather inadequately, interconnected interactions occurring within the climate-human-environment interaction space. Besides, studies documenting stakeholders' perceptions regarding climate change induced vulnerabilities are limited in terms of providing indicators for decision-making. This paper aims at constructing a livelihood vulnerability index for climate variability and change capturing interconnected interactions based on peoples' perceptions while providing indicators for evidence based decision-making. A semi-quantitative fuzzy cognitive mapping (FCM) approach has been deployed to capture peoples' perceptions of climate induced perturbations and adaptations. This approach helps quantify stakeholders' perspectives while capturing interconnected interactions in order to estimate livelihood vulnerability to climate variability and change of poor agro-pastoralists in the Bhilwara, a district in Western India. Combining the FCM approach with a sustainable livelihood framework warrants an understanding of assets sensitive to climate variability and change along with those serving as adaptive capacities. The findings of this study confirm that financial and natural assets are most susceptible to harm while organisational and financial assets provide resilience against climate variability and change. The results suggest that livelihood vulnerability of agropastoralists lie in the range of being 'vulnerable' to climate variability and change while varying across three seasons summer, winter, and rainfall.

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Section: Calculating Sensitivity and Adaptive Capacitymentioning

confidence: 99%

Livelihood vulnerability assessment to climate variability and change using fuzzy cognitive mapping approach

Singh

Nair

2014

Climatic Change

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“…The process adopted to compute the composite index followed a balanced weighted average approach (Sullivan 2002;Hahn et al 2009), where major factor values equally contributed to the CCVI value. In this approach, major factors were maintained evenhanded despite difference in quantity of sub-factor indicators for each major factor.…”

Section: Index Computationsmentioning

confidence: 99%

An Index to Determine Vulnerability of Communities in a Coastal Zone: A Case Study of Baler, Aurora, Philippines

Orencio

Fujii

2012

AMBIO

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A coastal community vulnerability index (CCVI) was constructed to evaluate the vulnerability of coastal communities (Buhangin, Pingit, Reserva, Sabang, and Zabali) in the municipality of Baler, Aurora, Philippines. This index was composed of weighted averages of seven vulnerability factors namely geographical, economic and livelihood, food security, environmental, policy and institutional, demographic, and capital good. Factor values were computed based on scores that described range of conditions that influence communities' susceptibility to hazard effects. Among the factors evaluated, economic and livelihood, policy and institutional and food security contributed to CCVI across communities. Only small variations on CCVI values (i.e., 0.47-0.53) were observed as factor values cancelled out one another during combination process. Overall, Sabang received the highest CCVI, which was contributed mainly by geographical and demographic factors. This technique to determine factors that influenced communities' vulnerability can provide information for local governments in enhancing policies on risk mitigation and adaptation.

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“…However, Hanemann [9] presents a very convincing argument about why water should be considered an economic commodity. Going a step further, Sullivan [10] and Lawrence, Meigh and Sullivan [11] calculate a water poverty index for the world. The measure provides an understanding of the impact of water deprivation on increase in poverty.…”

Section: Introductionmentioning

confidence: 99%

Inequality in Access to Improved Water Source: A Regional Analysis by Theil Index

Sinha¹,

Rastogi²

2015

TEL

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This study applies Theil's second measure for looking into inequality in access to improved water source. This index allows inequalities to be broken up within and between groups. An analysis of 188 countries for the period 1990-2012 demonstrates three observations: first, decline in inequality in access to improved water source is characterized by both within-group and between-group inequality elements; second, between-group inequalities are at present the key contributor of the entire inequality scenario; and lastly, an inclusive study on within-group inequalities divulges the significant role played by Central and South American and Middle East countries towards increase in inequalities and countries pertaining to North America, Asia and Oceania, Africa, and Europe towards decline in inequalities.

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Calculating a Water Poverty Index

Cited by 665 publications

References 17 publications

Livelihood vulnerability assessment to climate variability and change using fuzzy cognitive mapping approach

Livelihood vulnerability assessment to climate variability and change using fuzzy cognitive mapping approach

An Index to Determine Vulnerability of Communities in a Coastal Zone: A Case Study of Baler, Aurora, Philippines

Inequality in Access to Improved Water Source: A Regional Analysis by Theil Index

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