We used a database of 237 wells in a 220 square mile study area of central Illinois to create<br>a sand thickness map for groundwater resource planning. This map suffers from uneven data, with<br>clustering in towns and little information in rural areas. The result is a strongly biased data set of<br>varying reliability. In an effort to increase the data density in rural parts of the study area we<br>measured resistivity at 566 locations that were spaced at approximately one-half mile intervals along<br>roadsides. The geophysical data, however, are difficult to interpret without geologic data because<br>resistivity units are only indirectly related to lithologic variables. To use the resistivity data to infer<br>lithologic characteristics, the geophysical data must first be calibrated with lithologic data. We give<br>an example of one method of converting the resistivity data to ameaningful lithologic variable (sand<br>thickness) and then calibrating the resistivity data with the existing lithologic database so that the<br>two data sets can be combined. The result is an improved, more consistently reliable map of<br>cumulative sand thickness that can be used for groundwater resource planning.


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