Abstract
Minas Gerais is one of the 27 federative units of Brazil; it is the fourth state with the largest territorial area and the second in number of inhabitants. Since 1997, the monitoring of the surface water quality of the State of Minas Gerais has been carried out. In this study, generalized regression models were constructed to determine the correlation between the Water Quality Index (WQI) and the sanitary and socioeconomic variables: Municipal Population, Human Development Index (HDI), Gini Index, Percentage of Vulnerables to Poverty (Poverty), Monthly Per Capita Income, Percentage of Inadequate or Poor Sanitation. In addition to the sanitary and socioeconomic variables listed, it also used year of water quality monitoring, altitude of the monitoring point, and distance from the monitoring point to the urban center of the municipality. The results from the generalized models showed that the variables year, altitude, Gini Index, monthly per capita income, and poor sanitation variables were positively associated with WQI. In other words, high values of each variable increased WQI, while population variables HDI and poverty were negatively related to WQI, that is, a high population value, HDI, or poverty implies a low WQI value. Socioeconomic variables such as HDI, Gini Index, poorness, or poor sanitation percentage present the coefficients with the largest modulus. Thus, among the socioeconomic variables studied, these are the ones that most contribute to the variability of WQI. The year and altitude variables have positive regression coefficients, indicating that when these variables increase, WQI also increases. The positive correlation with the year shows that the surface water quality of Minas Gerais improved during the monitoring years.
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The authors are grateful to IGAM for providing water quality monitoring data.
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Ezequiel Dias Foundation provided financial support to the project.
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Pataca, L.C.M., Pedrosa, M.A.F., Zolnikov, T.R. et al. Water quality index and sanitary and socioeconomic indicators in Minas Gerais, Brazil. Environ Monit Assess 192, 476 (2020). https://doi.org/10.1007/s10661-020-08425-9
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DOI: https://doi.org/10.1007/s10661-020-08425-9