Integration of Head, Temperature and Concentration Data for Subsurface Delineation Using the Pilot Point Method: Synthetic and Laboratory Studies

Characterization of subsurface heterogeneity is essential for improved understanding groundwater flow, contaminant transport and to propose remediation strategies. To improve the mapping of heterogeneity in hydraulic conductivity ( K ), different data types can be incorporated and analyzed through inverse modeling. In this study, we propose to integrate transient head, temperature and concentration data from coupled heat and salt tracer tests into the inverse model to investigate the performance of these data sets in characterizing K fields using the pilot point method. We first focus on synthetic studies with generated random fields of various level of heterogeneity. The synthetic fields are generated based on a field site in Japan. For the synthetic studies, three coupled heat and salt tracer tests have been conducted. Pumping and injection wells are selected differently for each test to various flow regimes (force gradient at different directions or divergent flow). Hydraulic/tracer tomography analyses will be conducted using these three coupled heat and salt tracer tests. A number of cases that individually or jointly invert these three types of data sets are being considered. After that, we propose to conduct a laboratory sandbox study to further validate the findings obtained from the synthetic studies. Moreover, we would like to investigate the impact of weightings for these transient head, temperature, and concentration data sets on delineating heterogeneity. This research will provide insights in integration of various data sets for improving mapping of K heterogeneity and establish strategies for determining weightings of these data sets.