Case histories of hydraulic conductivity estimation with induced polarization at the field scale

Abstract

ABSTRACTWe have carried out spectral induced polarization (IP) measurements at three different hydrogeological test sites (Hasloh, Lüdingworth and Kappelen) and estimated hydraulic conductivity using empirical equations previously derived from laboratory measurements. We also reviewed previously published data from another site (Krauthausen). The intention was to explore the potential and practical limitations when applying the method at the field scale. The test sites cover a lithological spectrum from gravel to silt, with a variation in hydraulic conductivity over three orders of magnitude. At each site, hydraulic conductivity was estimated from the real and imaginary conductivity resulting from 2D inversion. We applied the constant phase angle model, where only one frequency, typically around 1 Hz is being used. The uncertainty in ‐estimates arising from inversion ambiguity was assessed by exploring the model space with a control parameter that permits a transition from smooth to blocky models and by using different starting models. At the Kappelen site, this uncertainty is larger than four orders of magnitude but a reasonable lower limit for can be obtained. At the other three sites, the uncertainties are typically one order of magnitude.The IP‐based hydraulic conductivity estimates were compared with K‐values obtained from grain size analyses and pumping tests. At the Hasloh and Lüdingworth sites the results agree within one order of magnitude and at the Kappelen site the derived lower boundary for is consistent with grain size information. At the Krauthausen site, the difference between IP‐based data and the values derived from grain size and pumping tests is significantly larger than the estimated uncertainties, which is probably due to the non‐uniform grain size distribution. The overall results indicate that order of magnitude ‐estimates from IP data at the field scale are realistic targets. However, sites with significant deviations from the empirical equations can exist, emphasizing the recommendation to use a priori information whenever possible.