A spatial application of the water poverty index (WPI) in the State of Chihuahua, Mexico
| Autor: | Víctor Manuel Reyes, Alexandra Angéliaume, Martin Paegelow, Frédérique Blot, Marie Zoé Wurtz, María Teresa Alarcón Herrera |
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| Přispěvatelé: | Géographie de l'environnement (GEODE), Université Toulouse - Jean Jaurès (UT2J)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Index (economics)
Poverty 0208 environmental biotechnology Geography Planning and Development 1. No poverty 02 engineering and technology [SHS.GEO]Humanities and Social Sciences/Geography 010501 environmental sciences Management Monitoring Policy and Law 01 natural sciences 6. Clean water Agricultural economics 020801 environmental engineering Water scarcity Water resources Geography 13. Climate action Water poverty Computer software ComputingMilieux_MISCELLANEOUS 0105 earth and related environmental sciences Water Science and Technology |
| Zdroj: | Water Policy Water Policy, IWA Publishing, 2019, 21 (1), pp.147-161. ⟨10.2166/wp.2018.152⟩ |
| ISSN: | 1366-7017 |
| DOI: | 10.2166/wp.2018.152⟩ |
| Popis: | The Water Poverty Index (WPI) standardizes water scarcity diagnostics by considering natural, environmental, and socioeconomic factors which reduce, facilitate, or prevent water access. To integrate these factors, the WPI includes five components: resource, environment (negatively affected by development), capacity, access, and use (positively affected by development). Nevertheless, the place granted to hydrological factors is questioned, and many studies insist on the problematic correlation of WPI with the well-known Human Development Index (HDI). Calculating WPI in the socially heterogeneous and semi-arid context of the State of Chihuahua (Mexico), adapting traditional methodology thanks to geographic information systems (GIS) tools and the corresponding databases, allows discussion of those points. This study uses multi-criteria evaluations from TerrSet software to calculate WPI while preserving specific data precision. In this process, scale calculation and indicator normalization are adapted through raster maps and fuzzy techniques to valorize specific hydrological data. This opens interesting discussions for multidimensional water scarcity diagnostics, since they increase the visibility of diverse water scarcity issues in WPI results. In fact, concentrating socioeconomic factors in corresponding components and valuing GIS alternatives provides a diagnostic different from the HDI and sensitive to hydrological factors. |
| Databáze: | OpenAIRE |
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