Collaborative Research: Fusion of Tomography Tests for DNAPL Source Zone Characterization: Technology Development and Validation

University Of Arizona, Tucson AZ

Investigators

Abstract

0229717 Yeh Dense Nonaqueous Phase Liquids (DNAPLs) are prevalent at a large number of sites throughout the world. The variable release history and geologic heterogeneity make the distribution of DNAPLs in the source zone complex. These source zones can contribute to long-term groundwater contamination for decades to centuries. Therefore, the spatial distribution, mass, and composition of DNAPLs present in the source zone need to be characterized in great detail so that efficient remediation schemes can be designed. During the last few years, many tracer techniques have been introduced to enhance the characterization of DNAPL source zones. While these tracer techniques allow for the in situ estimation of volume-averaged values of DNAPL saturation, there is an urgent need for the development of a cost-effective technology to characterize the spatial distribution of DNAPLs at high resolutions. The objectives of this proposed study are: 1) to develop a software/hardware package that fuses different types of information using a stochastic approach to provide a cost-effective characterization, monitoring, and predictive tool for the DNAPL source zone, 2) to conduct laboratory experiments to test and verify this proposed technology, and 3) to distribute the results of the research to assist scientists, engineers, and managers to solve DNAPL contamination problems. Intellectual Merit: The proposed new data processing technique, stochastic information fusion, combines different types of measurements taken at different locations over different scales in an iterative manner to provide the best estimate of the DNAPL residual distribution and its uncertainty. Specifically, it analyzes the information derived from hydraulic tomography to identify hydraulic heterogeneity first in three-dimensions. It then improves the estimate of the heterogeneity by incorporating new information acquired from the conservative tracer tomography. Afterward, the improved estimate of hydraulic heterogeneity is used to simulate the hydraulic tomography such that more detailed information about the response of the subsurface becomes available. This new information again is fed back to the technique to update the estimate of hydraulic heterogeneity. The iterative process continues until all available information and measurements are fully utilized in identifying the processes and variables that control the spatial distribution of DNAPLs. Upon completion, the newly derived knowledge of the processes and variables are then combined with data derived from the partitioning tracer tomography to effectively delineate the spatial distribution of DNAPL residual saturation in the source zone. The proposed tomography technique and the stochastic fusion of information algorithm are to be tested and validated in a sandbox. Success of the proposed research advances not only estimation theory in general but also our technologies for characterizing and monitoring the subsurface. Broader Impacts: The proposed stochastic fusion technology can be integrated with different characterization techniques in diverse geological conditions. It is also amenable to all stages of DNAPL source zone characterization including initial screening, site characterization, remediation, and long-term monitoring. A web-based virtual hydraulic/tracer tomography laboratory will be created and be available to any student, educator, practitioner, and researcher around the world. We believe this virtual laboratory will stimulate creativity to revolutionize not only classical subsurface hydrology but also other disciplines of hydrologic sciences. For example, using our stochastic information fusion technology, one may be able to assimilate meteorological information such as lighting and precipitation as alternative excitation sources for tomographic surveys of the subsurface environment at large scalesseeing into the earth.