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Numerical modeling of the Cauê Aquifer in the ferruginous geosystems of the Moeda Syncline (Iron Quadrangle, Brazil): Assessing regional impacts of groundwater pumping and predicting future drawdown trends

Wallace Maciel Pacheco Neto; Celina Cenni de Castro Magalhães; Rodrigo Sergio De Paula; Marília Carvalho de Melo; Nilson Guiguer; Breno Alexandre Pereira; Paulo Galvão
Hydrogeology Journal · Vol. 34, Issue 4 · pp. 1093-1110 · 2026

Abstract

Numerical hydrogeological modeling is essential for evaluating current conditions and forecasting future groundwater dynamics in regions heavily affected by iron mining. The Cauê Aquifer, located in the ferruginous geosystems of the Moeda Syncline (Iron Quadrangle, Brazil), is a key water resource for the region. Dewatering of 11 iron mines on the syncline’s eastern limb required pumping approximately 52 million m 3 /year of groundwater in 2019, potentially altering aquifer behavior. This study analyzed hydraulic head and baseflow variations from 1999 to 2019 and predicted water table decline over the following 20 years. Groundwater flow modeling was conducted using FEFLOW, with the workflow including hydrogeological framework setup, steady-state and transient calibration, and simulation of groundwater level lowering. Four hydrogeological units associated with the Cauê Aquifer (Gandarela and Moeda aquifers, and the Batatal Aquitard) were subdivided into four sectors. Steady-state calibration yielded a 7.75% root mean square error (RMSE) for hydraulic head. Transient calibration (1999–2019) indicated a 13.6% baseflow reduction, with average groundwater level declines of 10.4 m in the Cauê Aquifer and 2.2 m in the other units. The south-central region showed the greatest groundwater level decline (11.6 m) and baseflow reduction (21.6%). Simulations for 2019–2039, assuming continued pumping, predicted an additional average groundwater level lowering of 7.4 m, with the south-central region again being the most affected (10.8 m). An average of 7.6% baseflow reduction for the region was also projected. The model effectively represents regional hydrogeological conditions and supports the identification of highly impacted areas for improved groundwater management.

Bibliographic Information

JournalHydrogeology Journal
PublisherSpringer
Publication Date2026-06-01
Publication Year2026
Volume34
Issue4
Pages1093-1110
Document TypeJournal Article
Print ISSN1431-2174
eISSN1435-0157
DOI10.1007/s10040-026-03026-1

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NARA Access Coverage1992-01-01~Current
Journal Homepagehttps://www.springer.com/journal/10040
Publisher PageOpen Publisher Page
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