Access to Water: Advancement of Multidimensional, Multiscalar, and Participatory Methods of Measurement in the Global South

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dc.contributor.authorPrince, Breeanna Carrollen
dc.contributor.committeechairJuran, Lukeen
dc.contributor.committeememberSridhar, Venkataramanaen
dc.contributor.committeememberBukvic, Anamariaen
dc.contributor.departmentGeographyen
dc.date.accessioned2018-06-30T08:03:13Zen
dc.date.available2018-06-30T08:03:13Zen
dc.date.issued2018-06-29en
dc.description.abstractThis project deploys a modified Water Poverty Index (WPI) in villages reconstructed after the 2004 tsunami in southeastern India. While previous measurements of access to water have advanced understandings of waterscape complexities, this modified WPI improves past efforts and deconstructs some of the previous misunderstandings and notions regarding access to water. The traditional WPI is multidimensional and seeks to measure water access in a holistic fashion; the WPI presented here employs this approach, but is adapted to include new place-based indicators (e.g., Secondary Sources). Furthermore, unlike previous iterations of the WPI, our modified index incorporates water quality testing, three weight schemes, and operates at several scales. Ultimately, the construction and arrangement of our modified WPI enables statistical analyses, geospatial analyses, and water poverty mapping -- which are absent in most prior studies-- while still remaining easy to populate and descriptively analyze among non-academicians. Statistical tests of original household level data from a total of 24 villages in Nagapattinam District, Tamil Nadu, and Karaikal District, Puducherry, indicate significant differences between the two districts in indicator scores as well as total WPI score. Additionally, the urban and rural areas within each district were found to be significantly different in level of water poverty, and trends were similar across the three weight schemes. Multiple linear regressions show correlation of independent socioeconomic variables (i.e., Income, Education, and Assets-Networks) with the dependent indicator of Capacity, but not with the other indicators or total WPI score. Global Moran's I tests indicate positive spatial autocorrelation, demonstrating that indicator and WPI scores tend to cluster in space. Overall, the results match what was anticipated, yet serve to challenge commonly held assumptions on urban-rural hierarchies and the role of socioeconomic variables in determining water poverty. The construction, deployment, and analytical potential of this modified WPI can be used by scholars to improve existing conceptualizations and measurements of access to water, while the results can be used by local governments and nonprofits to improve resource allocation and inform spatially-targeted interventions.en
dc.description.abstractgeneralThis study uses a modified, participant-based Water Poverty Index (WPI) to measure access to water among 24 reconstructed villages in Karaikal and Nagapattinam Districts in South India. While following the traditional WPI framework, this WPI modifies previous indicators and includes new indicators such as Secondary Sources, Quality, and Quantity. The modified WPI also supports statistical analyses as well as geospatial analyses and water poverty mapping. Further differentiation of this WPI is that it applies three separate weight schemes to interpret findings. The first weight scheme is the traditional application of equal weights; the second uses best management practices, the engineering and public health literatures, and grounded observations and fieldwork to develop an ‘expert’ weight scheme; and the third ‘survey’ weight scheme adheres to participants’ rankings in terms of which WPI indicators they perceive as most important when dealing with water issues. After indicator and WPI scores were calculated, independent sample t-tests, Wilcoxon Signed Rank tests, and stepwise multiple linear regressions were conducted on all scores. The tests were also conducted at several scales and across the three weight schemes. Results show that Karaikal District significantly outperformed Nagapattinam District, urban Karaikal significantly outperformed rural Karaikal, and rural Nagapattinam significantly outperformed urban Nagapattinam (which defies previous notions of urban-rural hierarchies). The regressions failed to return high R 2 values, indicating that factors such as income and education are not correlated with WPI scores. The results from this tool can be used to aid in interventions by local governments and nonprofits to improve overall resource management.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:16297en
dc.identifier.urihttp://hdl.handle.net/10919/83823en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectWater Povertyen
dc.subjectWater Poverty Indexen
dc.subjectWASHen
dc.subjectWater accessen
dc.subjectPost-Disasteren
dc.subjectIndiaen
dc.titleAccess to Water: Advancement of Multidimensional, Multiscalar, and Participatory Methods of Measurement in the Global Southen
dc.typeThesisen
thesis.degree.disciplineGeographyen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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