Distribuição espaço-temporal de parâmetros físico-químicos da água subterrânea em duas sub-bacias na Bacia do Rio São Francisco, por meio de Krigagem de Indicadores

Abstract

Groundwater is a natural resource of great importance for the environment, as it represents the largest source of fresh water on planet Earth. It is through this water resource that various activities essential for human survival can be developed, such as irrigation, direct consumption, and livestock watering, among others. However, this resource is difficult to renew and, in a general context, is vulnerable to degradation caused by anthropogenic activities. Furthermore, according to the United Nations Sustainable Development Goals for the year 2030, such as health and well-being, and clean water and sanitation, monitoring water quality is essential for achieving these goals. Therefore, there is a need for monitoring and controlling the quality of groundwater, using tools that facilitate its qualitative and quantitative understanding in both spatial and temporal dimensions, as well as, of course, the identification of contamination and pollution sources. Geostatistics emerges as a viable tool in water resource management, the use of this technique makes it possible to identify unknown variables in areas where sampling is not feasible, given that, being a water resource present beneath the Earth's surface, there are certain difficulties in sampling due to high costs. Through the geostatistical method of indicator kriging, this study aims to create probabilistic maps for the indicators derived from the exceedance values of groundwater quality parameters in sub-basins of the São Francisco Basin, using secondary data provided by the Minas Gerais Water Management Institute, obtained from the Groundwater Quality Monitoring in Minas Gerais. In light of this study, based on the applied methodology, it is observed that there is a significant quantity of samples exceeding the Maximum Permissible Values established by current legislation, and that through estimation by indicator kriging, it is possible to identify critical quality zones and correlate these zones temporally and spatially for each analyzed parameter. Thus, it can be concluded that the results obtained from kriging not only meet all validation stages but also fulfill the initially proposed objectives and are consistent with the geological data of the study area. These results serve as assistance in monitoring and identifying risk areas, but they require complementary data to identify the specific sources of contamination.