A hydrogeochemical approach to the characterization of low-enthalpy geothermal systems: the Scordia – Lentini graben (Sicily, Italy)

We describe the geochemical characteristics of groundwater samples collected in 23 water wells located on the northern margin of the Hyblean plateau (East Sicily). This area, mostly made of highly permeable carbonate rocks, is rich in low temperature (T < 50° C) hydrothermal groundwaters, distributed in an active sismogenetic zone, with several ENE-WSW-directed tectonic structures that drove magma to the surface during Upper Pliocene and Pleistocene. The chemical features suggest complex mixing between rainwater, CO2-rich groundwater, steam-heated groundwater and geothermal brines, as highlighted by Principal Component Analysis (PCA). Some parameters, however, indicate widespread pollution of the aquifers from human activities. Stable isotopes analysis confirms the meteoric origin of groundwater and supports the origin of dissolved CO2 mostly from mantle degassing through deep tectonic faults. Geothermometric estimates, mostly based on quartz and Saturation Indexes geothermometers, suggest minimum reservoir temperature between 100 and 120° C

Assessment of the Geochemical Potential in a Complex Tectonic Environment of South-East Sicily: New Insights From Hydrochemical Data

We analyzed a large dataset (143 water sampling sites, 22 variables) of chemical parameters in local groundwaters from the south-east sector of Sicily, namely the Hyblean plateau, in order to set an original evaluation of its geothermal potential using applied geochemistry. The area was affected by volcanism until about 1.4 Ma. Today, though no active volcanism occurs, it is site of surface gas manifestations of focused degassing to which a mantle source has been attributed. We identified and thence selected the most promising sites (water springs and wells) based both on their main geochemical characteristics and on their calculated equilibrium temperature (resulting in the range between 50 and 140 °C). We then applied Principal Component Analysis (PCA) to this restricted dataset and we were able to discriminate between different sources of solutes, both natural and anthropogenic. Finally, we mapped the factor scores obtained from PCA and we focused on those likely related with geothermal conditions in order to highlight the areas with the highest geothermal potential