Uso do ?ndice de pobreza h?drica (WPI) atrav?s da an?lise de componentes principais

• Main Author: Senna, Larynne Dantas de
• Other Authors: 93953356534
• Language: Portuguese
• Published: Universidade Federal do Rio Grande do Norte 2016
• Subjects: CNPQ::ENGENHARIAS::ENGENHARIA SANITARIA; Escassez h?drica; An?lise multivariada
• Online Access: http://repositorio.ufrn.br/handle/123456789/20244

Submitted by Automa??o e Estat?stica ([e-mail]) on 2016-04-15T20:28:21Z No. of bitstreams: 1 LarynneDantasDeSenna_DISSERT.pdf: 2775430 bytes, checksum: 1f765d0818e89af5941a1275fe961a99 (MD5) === Approved for entry into archive by Arlan Eloi Leite Silva ([e-mail]) on 2016-04-19T23:40:44Z (GMT) No. of bitstreams: 1 LarynneDantasDeSenna_DISSERT.pdf: 2775430 bytes, checksum: 1f765d0818e89af5941a1275fe961a99 (MD5) === Made available in DSpace on 2016-04-19T23:40:44Z (GMT). No. of bitstreams: 1 LarynneDantasDeSenna_DISSERT.pdf: 2775430 bytes, checksum: 1f765d0818e89af5941a1275fe961a99 (MD5) Previous issue date: 2015-06-02 === P ara contribuir no desempenho das pol?ticas e estrat?gias formuladas por comit?s de bacia hidrogr?fica , ?ndices v?m sendo criados na expectativa de expressar as m?ltiplas dimens?es dos recursos h?dricos em u ma forma facilmente interpret?vel. O uso do ?ndice de Pobreza H?drica (WPI) est? se difundindo mundialmente, sendo o mesmo formado pela combina??o dos sub?ndices Recurso, Acesso, Capacidade, Uso e Ambiente. A lgumas cr?ticas quanto ? f orma??o do WPI foram surgindo , de ntre elas destaca - s e a atribui??o de pesos dos sub ?ndices, feita por um processo arbitr?rio atribuindo subjetividade ao crit?rio de sele??o. Ao envolver an?lise estat?stica, quando se considera as caracter?sticas das vari?veis geradas pe la An?lise de Componentes Principais (ACP), verifica - se que a mesma ? capaz de solucionar esse problema . O objetivo deste trabalho ? comparar os resultados do WPI original com o ?ndice gerado atrav?s da An?lise de Componentes Principais (ACP), par a a indic a??o dos pesos dos sub ?ndices aplic?veis na bacia hidrogr?fica do Rio Serid? (RN e PB) . Conclui - se que o uso da An?lise de Componentes Principais na atribui??o do s pesos do ?ndice de Pobreza H?drica permitiu identificar que os sub - ?ndices Recurso, Acesso e Ambiente s?o os mais representativos para a bacia hidrogr?fica do Rio Serid? , e que este novo ?ndice, o WPI?, apresentou faixas de valores mais abra ngentes, permitindo identificar mais facilmente as disparidades entre os munic?pios. Al?m disso, a avalia? ? o dos sub ?ndices na ?rea de estudo tem grande potencial de informar ao tomador de decis?o na gest?o dos recursos h?dricos, as localidades mais cr?ticas e que merecem maiores investimentos nos aspectos analisados, j? que o ?ndice em si n?o permite captar essa informa??o. === To contribute in the performance of policies and strategies formulated by development agencies, indexes have been created in anticipation of expressing the multiple dimensions of water resources in an easily interpretable form. Use of Hydro Poverty Index ( WPI) is spreading worldwide , with the same formed by the combination of sub - indices Resource, access, capacity , use and environment. S ome critics a s to its formation have emerged, a mong them stands out the allo cation of weights of sub - indexes , made by an arbitrary process attributing subjectivity to the selection criteria. By involving statistical analysis, when considering the characteristics of the variables generated by the Principal Component Analysis (PCA), it turns out that it is able to solve this problem. The objective of this study is to compare the results of the original WPI with content generated by Principal Com ponent Analysis (PCA) for the indicati on of the weights of sub - indec es applicable in the Serid? River hydrographic Basin . We conclude that the use of Principal Component Analysis in the allocation of weights of Water Poverty Index has identified the sub - indices Resources, Access and Environment are the most representative for the river basin Serid? , and that this new index, WPI' , presented the most comprehensive ranges of values , allowing more easily identify disparities among municipalities. In addition, t he evaluation of the sub - indec es in the study area has great potential to inform the decision - maker in the management of water resources, the most critical locations and deserve greater investments in the aspects analyzed, as the index itself can not cap ture this information.