Mine tailing ponds are environmental hazards because of high susceptibility to leaching and erosion by water and wind. Vegetation establishment is an effective technique to reclaim tailing ponds but requires knowledge of the spatial relationship between the structural composition and physical and chemical properties of soils. In this study we have demonstrated the use of electrical resistivity imaging (ERI), combined with soil chemical analyses, to determine the structural and chemical composition of mine tailing ponds to assess efficient measures of environmental protection. We used a Syscal R1 resistivity meter to generate two- and three-dimensional (2-D/3-D) ERI images from El Lirio and Brunita mine tailing ponds. Soil samples were collected at 1-m intervals to a depth of 15 m, and were analyzed for pH, electrical conductivity and cadmium (Cd), copper (Cu), lead (Pb) and zinc (Zn) contents. Results show that materials in the ponds can be classified into three categories: fine tailings – low ER (150 Ω-m). Our interpretation of the 2-D/3-D ERI images with respect to the historical depositions of materials in the ponds show that at El Lirio, decant water outlet was initially at the center and advanced to the east of the tailing pond as the mining activities progressed. At Brunita, the intermediate ER values on the west side of the pond marked the deposition of coarse waste rock materials released during a pond breakage in 1972. The ERI helped us image the spatial distribution of tailings and its qualitative spatial correlation with chemical properties (i.e., pH, EC, metals content). Low ER values are related to high amounts of Zn, Pb, Cu and Cd. These qualitative relationships underlie the usefulness of the combined geophysical and soil chemical approaches to improve our understanding of the properties of mine tailing ponds in the Sierra Minera (and other parts of the world).

Nonintrusively monitoring the spread of contaminants in real time with a geophysical method is an important task in hydrogeophysics. We have developed a sandbox experiment showing that the self-potential method can locate both the source of leakage and the front of a contaminant plume. We monitored the leakage of a plume of salty water from a hole at the bottom of a small tank located at the top of a main sandbox. Initially, the sand was saturated by tap water. At a given time, a hole was opened at the bottom of the tank, allowing the salty water to migrate by diffusion and buoyancy-driven flow in the main sandbox. The bottom of the sandbox contained a network of 32 nonpolarizing silver-silver chloride electrodes with amplifiers, connected to a multichannel voltmeter. The self-potential response associated withthe migration of the salt plume in the sandbox was recorded over time. A self-potential anomaly was observed with amplitude varying from a few millivolts at the start of the leak to a few tens of millivolts after a few minutes. The self-potential data were inverted using a time-lapse tomographic algorithm to reconstruct the position of the volumetric source current density over time. A positive volumetric source current density was associated with the position of the leak at the bottom of the leaking tank, whereas a negative volumetric source current density was associated with the salinity front moving down inside the sandbox. These poles were well reproduced by performing a finite-element simulation of the problem. Using this information, we estimated the speed of the salt plume sinking inside the sandbox. Therefore, the self-potential method can be used to track, in real time, the position of the front of a contaminant plume in a porous material.