Geostatistical and multi-criteria decision-making models to subsidize a quantitative monitoring network of aquifers intensively used for irrigated agriculture: The case of Urucuia Aquifer System, Brazil

Groundwater monitoring is essential for effective water resource management, enhancing hydrogeological understanding and supporting public policy implementation. In Brazil, systematic groundwater level monitoring started only in the years 2010s, with the Brazilian Geological Survey (SGB) “Integrated Groundwater Monitoring Network” (RIMAS). Among Brazilian aquifers, the Urucuia Aquifer System (UAS) is the most monitored, covering 126,468 km², primarily in the State of Bahia, northeastern Brazil. However, with a density of just 0.0008 wells/km², monitoring remains incipient as compared to international standards. The UAS, a predominantly phreatic aquifer composed by fluvial-eolian Cretaceous sandstones from the Urucuia Group, Sanfranciscan Geological Basin, plays a strategic role in economic and social development, and sustains baseflows in the São Francisco River basin. Rapid agricultural expansion in western Bahia, with increasing groundwater withdrawals, required an improved management through a functional monitoring network. This study developed a multi-criteria model to identify priority areas for expanding the UAS monitoring network. It considered hydrogeological, physiographic, water abstraction, and well availability factors, integrated with geostatistical analysis. Results confirmed the shortages of the current network. Vulnerable areas identified include the western Corrente River basin and the Branco, Rio de Janeiro, and Ondas River sub-basins, which should be prioritized for network expansion. The study highlights the effectiveness of integrated methods for designing monitoring networks, a relatively unexplored approach in Brazil. These findings contribute to improve decision-making process and a deeper understanding of the UAS hydrogeological context, paving the way for better management of groundwater resources in the region.