Conventional approaches in permafrost monitoring, including thermal measurements, core analyses and borehole geophysical logs, have drawbacks for long-term predictions of permafrost thermal state because of their discrete character and high cost. In order to accurately simulate and forecast thermal regime of the active layer and permafrost at a comparatively lower cost, we combined traditional thermal measurements with surface geophysical acquisitions. The fully coupled inversion scheme used only ground surface temperature data and time lapse geoelectrical measurements to calibrate a heat conduction model. The apparent resistivity data were incorporated into the coupled framework without being inverted separately, thus reducing the uncertainty inevitably associated with inverted resistivity models, especially on challenging permafrost terrain. The fully coupled modeling framework using field data achieved performance comparable to calibration on borehole temperature records, in terms of model fit within 0.6 °C, inversion convergence metrics as well as the predictive performance of the calibrated model.