Panorama da qualidade das águas superficiais do estado de Minas Gerais por meio da Análise Exploratória de Dados Espaciais – AEDE

• Ano de defesa: 2024
• Autor(a) principal: Larissa Guarany Ramalho Elias
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; Brasil; ENG - DEPARTAMENTO DE ENGENHARIA SANITÁRIA E AMBIENTAL; Programa de Pós-Graduação em Saneamento, Meio Ambiente e Recursos Hídricos; UFMG
• Palavras-chave em Português: Estatística espacial; Água superficial; Poluição hídrica; Meio ambiente; Água - Qualidade; Poluição da água - Prevenção; Estatística
• Link de acesso: http://hdl.handle.net/1843/75234; https://orcid.org/0000-0002-5808-3617

Water is a limited natural resource, and its use is intrinsically linked to quality. In Minas Gerais, the Institute for Water Management (IGAM) is responsible for monitoring the quality of surface water within the scope of the "Águas de Minas" Project, with the establishment of sampling networks throughout the entire state. Considering the territorial extension of this network and the sampling period, there is a huge amount of data that needs to be dealt with systematically to obtain relevant information that will help to improve water management. In this context, the goal with this research is to analyze and map surface water pollution in the river basins of Minas Gerais. This study will quantify the magnitude of water quality parameters by monitoring station and river basin, as well as determine spatial patterns for the parameters. It will then be possible to understand the problem of water pollution in the state as a whole and provide support for the optimum allocation of investments in monitoring to guarantee the achievement of GSD 6. The database used for this research is IGAM's historical water quality monitoring series, covering the years 2000 to 2021. The methodological steps consisted of creating a database in Excel spreadsheets format, suitable for input into R language software, QuantumGIS and ArcGIS, creating a shape with all the monitoring stations studied, performing descriptive statistics, drawing up distribution maps of the medians of the parameters per station grouped into five ranges of values and spatial statistical analysis of global and local autocorrelation, using Moran's I index. The results made it possible to delineate the sites of greatest degradation of water quality in the state for each of the parameters studied and integratively. In conclusion, the application of local Moran's I is a valuable tool for analyzing water quality since it allows to determinate focal points and areas where the is degradation