Three‐Dimensional Geostatistical Inverse Analyses of Transient Head and Temperature Data From a Long‐Term Heat Tracer Test

Abstract Improving the accuracy of subsurface heterogeneity characterization remains a key component in better understanding groundwater flow and contaminant transport. Heat tracer tests can provide temperature measurements, in addition to head data, that can be used for mapping heterogeneity. Here, the performance of head and temperature data in characterizing the hydraulic conductivity ( K ) distribution is investigated with a three‐dimensional highly parameterized model using the pilot point method. The performance results are evaluated qualitatively and quantitatively in various aspects, including K fields comparison, head and temperature matches for both model calibration and validation, as well as through identifiability and sensitivity analyses. Results of this study reveal that: (a) K fields obtained by inverting head data show finer details of heterogeneity, while small scale heterogeneity is smoothed when inverting temperature data; (b) combination of heat and temperature data improves the prediction of heat tracer tests; (c) increasing data density yields more heterogeneity information and further improves prediction performance; and (d) identifiability and sensitivity analyses suggest that head and temperature data contain nonredundant information of K heterogeneity. These results jointly suggest that the integration of transient head and temperature data shows promising potential in improving the delineation of subsurface K distribution and obtaining reliable predictions of head responses and heat plume migration.