Regional groundwater flow and geochemical evolution in the Amacuzac River Basin, Mexico

13. Climate action 0207 environmental engineering 02 engineering and technology 6. Clean water
DOI: 10.1007/s10040-016-1423-x Publication Date: 2016-05-05T06:36:43Z
ABSTRACT
An approach is presented to investigate the regional evolution of groundwater in the basin of the Amacuzac River in Central Mexico. The approach is based on groundwater flow cross-sectional modeling in combination with major ion chemistry and geochemical modeling, complemented with principal component and cluster analyses. The hydrogeologic units composing the basin, which combine aquifers and aquitards both in granular, fractured and karstic rocks, were represented in sections parallel to the regional groundwater flow. Steady-state cross-section numerical simulations aided in the conceptualization of the groundwater flow system through the basin and permitted estimation of bulk hydraulic conductivity values, recharge rates and residence times. Forty-five water locations (springs, groundwater wells and rivers) were sampled throughout the basin for chemical analysis of major ions. The modeled gravity-driven groundwater flow system satisfactorily reproduced field observations, whereas the main geochemical processes of groundwater in the basin are associated to the order and reactions in which the igneous and sedimentary rocks are encountered along the groundwater flow. Recharge water in the volcanic and volcano-sedimentary aquifers increases the concentration of HCO3 –, Mg2+ and Ca2+ from dissolution of plagioclase and olivine. Deeper groundwater flow encounters carbonate rocks, under closed CO2 conditions, and dissolves calcite and dolomite. When groundwater encounters gypsum lenses in the shallow Balsas Group or the deeper Huitzuco anhydrite, gypsum dissolution produces proportional increased concentration of Ca2+ and SO4 2–; two samples reflected the influence of hydrothermal fluids and probably halite dissolution. These geochemical trends are consistent with the principal component and cluster analyses.
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