Desenvolvimento de um sistema para integração e disponibilização de dados de águas subterrâneas

Abstract

Groundwater is of crucial importance for urban supply in Brazil, owing to its wide availability and low procurement cost. These underground water sources are extensively used as the primary source in various municipalities, as well as in agricultural and industrial production. Understanding the hydrogeological parameters is vital for sustainable management of groundwater exploitation. Despite its extreme importance in the socio-economic and environmental aspect, there is little investment in making this data available. The systems developed for collecting and storing these parameters are often not made available to the public, and those that are suffer from limitations involving outdated data and limited exportation to a restricted quantity of analyses and wells. In this context, the present study aimed to integrate different sources of information on groundwater, centralizing wells data in a system from IAT (Instituto Água e Terra do Paraná), SIAGAS (Sistema de Informação de Águas Subterrâneas), and RIMAS (Rede Integrada de Monitoramento das Águas Subterrâneas). Additionally, tools were developed to utilize the database, inclusive of a Business Intelligence system, an Application Programming Interface, and software to effectuate Piper and Stiff diagrams, ionic balance, and to export the aforementioned data. A case study was executed for the state of Paraná with the objective of analyzing wells with nitrate levels proximate to and exceeding the statutory limit of potability. Therefore, it was feasible to identify a more pronounced presence of nitrate contamination in urban wells, likely attributable to contamination from effluents resultant from sewage network leaks. Accordingly, the work demonstrates the development of a system capable of assisting researchers and decision-makers by providing tools which facilitate an enhanced understanding of groundwater, with diagrams and the capability to process a substantial volume of data, thereby enabling the integration amongst diverse sources of groundwater data.