Understanding human development, poverty and water scarcity patterns in the Brazilian Semi-arid through cluster analysis
Topics: Arid Regions
, Applied Geography
, Development
Keywords: Water scarcity, human development, poverty, semi-arid
Session Type: Virtual Paper Abstract
Day: Saturday
Session Start / End Time: 2/26/2022 05:20 PM (Eastern Time (US & Canada)) - 2/26/2022 06:40 PM (Eastern Time (US & Canada))
Room: Virtual 56
Authors:
Douglas Sathler, UFVJM
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Abstract
In Brazil, the Semi-arid is the poorest region in the country, where a significant part of
the population is not adapted to drought and fluctuations in rainfall. Based on multivariate
methods, I investigate here the spatial patterns of drought and socioeconomic variables
between 2000 and 2010 within the Brazilian Semi-arid. In this work, I find five well-
defined socio-environment clusters presenting distinct characteristics: developing cluster,
demographic gains cluster, stagnated cluster, socio-environmental challenges cluster and
undeveloped cluster. My results show that there are vast areas in the Brazilian Semi-arid
that demand development strategies and deep structural changes. In the region, I find that
population grows where drought is low, although it does not mean better social conditions within the explored municipalities. Policies for development and poverty alleviation focused essentially on increasing income will not necessarily have an immediate impact on other important social indicators, such as mortality and illiteracy rates. Multidimensional approaches and multiscale interventions considering partnerships
among all levels of government (local, state and federal) are essential to overcome this
vicious cycle linking environment constrains with poverty and low development levels.
Finally, this paper shows that integrating socioeconomic, demographic and
environmental indicators is vital to understanding development patterns throughout the Brazilian Semi-arid.
Understanding human development, poverty and water scarcity patterns in the Brazilian Semi-arid through cluster analysis
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Virtual Paper Abstract
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