Análise da qualidade da água oceânica (Balneário Cassino - RS), a partir da análise estatística da bactéria Escherichia coli e da variação da concentração da clorofila-a com sensoriamento remoto

Abstract

The quality of coastal ocean water has been analyzed using mathematical techniques combined with remote sensing. These techniques make it possible to evaluate physical, chemical and biological parameters, providing a comprehensive understanding of the environmental impacts in the studied region. Initially, we sought to develop a systemic analysis of the approaches used globally to obtain more detailed knowledge on the topic, considering its use in the study area. In this process, it was observed that the integration of remote sensing with mathematical techniques, such as time series analysis and machine learning algorithms, allows the detection of patterns and trends, identifying risk areas, such as eutrophication zones or high concentrations of pollutants. The combination of systems also contributed to the creation of specific predictive models for studies in coastal regions. Among the approaches analyzed, we chose to use the Google Earth Engine (GEE) platform to obtain the remote sensing data used. In the specific case of Balneário Cassino, the study site, a combination of remote sensing and statistical analyzes was used to evaluate the quality of ocean water in locations adjacent to the arrival of urban rainwater drainage channels on the beach. The images obtained from the GEE platform showed the evolution of the variation in chlorophyll-a (Chl-a) concentration, from 01/2022 to 11/2023, providing significant information about water quality and the environmental factors that influence its composition in the region. Statistical analysis using in-situ data on the presence of the bacteria Escherichia coli (E. coli), provided by Fepam, made it possible to identify critical points of human intervention and sources of water pollution in drainage channels, such as inadequate disposal of solid waste, contamination by chemical products, discharge of illegal sewage and siltation. Therefore, the objective of this study was to investigate the quality of ocean water in Balneário Cassino through spatial analysis based on remote sensing and statistical analysis. To this end, we sought to evaluate studies carried out with remote sensing and multivariate analyzes used globally in the analysis of coastal ocean water quality, represent the sensitive points of arrival of pollutants on the beach through the rainwater drainage (bleeders) network, apply statistical analysis to the data obtained in situ of the E.coli bacteria to determine the point of greatest influence on ocean water quality and represent the variation in Chl-a concentration using remote sensing to analyze water quality at the study site. Therefore, it is expected that this study will contribute to the implementation of environmental management policies that promote environmental conservation in Balneário Cassino, assist in the sustainable management of urban drainage channels and reduce water pollution.