LONG-TERM ELECTRICAL RESISTIVITY MONITORING AT THE RICE CREEK FIELD STATION, OSWEGO, NEW YORK

Electrical resistivity methods have been used with increasing frequency as an environmental monitoring tool for conductive and/or non-conductive fluids at landfills and hazardous waste sites. A problem with long-term monitoring using this method is the variability of the data with near-surface conditions, such as temperature and moisture changes. These changes may mask the effects of the potential pollutants and render these methods less than ideal for the monitoring job.

A long-term resistivity experiment is being conducted at the Rice Creek Field Station, located in Oswego, NY, to ascertain the impact of near surface conditions on resistivity data with the ultimate goal of being able to remove these effects from the data. Electrical resistivity and weather information were frequently monitored between October 1, 2000 and May 1, 2001. The electrical resistivity data were collected using an offset Wenner technique with 42 electrodes and an a-spacing of 0.5 m. Weather data monitored includes surface and subsurface temperature information to a depth of 1 m, precipitation totals, snow pack, and soil moisture. During the winter in Oswego, the ground is generally unfrozen under a snow pack. The water in the soil is at field capacity, but exceeds field capacity during snow melt as the water trickles down through the soil. Thus the water in the soil changes with temperature in addition to after precipitation.

Visual inspection of the data reveal that precipitation and temperature changes can be tracked by changes in electrical resistivity as the change propagates downwards through the subsurface. Resistivity data from different levels were then mathematically correlated with the various weather-related measurements. The analysis indicates strong correlations between electrical resistivity values and variations in temperature and precipitation. These correlations are denoted by consistent lag times between the weather event and the changes in resistivity at depth. Monitoring will continue with the goal of establishing a filter to remove these effects from the resistivity data.