Using Surface Information for Quantitative Modeling of the Subsurface

Paola Passalacqua, Associate Professor in the Cockrell School of Engineering at the University of Texas at Austin, is starting a new collaborative research project with the University of Minnesota-Twin Cities and the University of Delaware, Using Surface Information for Quantitative Modeling of the Subsurface.

Passalacqua provided an overview of the project: Surface processes and subsurface characterization have traditionally been treated separately and investigated with different tools. However, because the subsurface is a record of surface deposition, we expect correlation between the nature and location of surface and subsurface networks. The link is the interplay of surface kinematics with accommodation, which leads to stacking of 2D surface patterns into the 3D subsurface structure. In river deltas and other channelized systems, a key, unifying concept is that of networks (2D on the surface, 3D in the subsurface) and the patterns of connection they create. While surface connections are important for understanding delta development and evolution, subsurface connectivity is critical in understanding groundwater flow and solute transport. Preferential flowpaths can quickly deliver contaminants to water supply wells, a particularly important problem in densely populated deltas such as the Ganges-Brahmaputra-Meghna Delta (GBMD). Establishing a quantitative link between surface and subsurface patterns would greatly advance our capability to predict subsurface solute transport. This work is relevant to the sustainability of water resources in densely populated deltas such as the GBMD, where high concentrations of arsenic are
widespread in the groundwater of the upper delta, and salinity problems a re pervasive in the lower delta. New understanding of subsurface structure and how it varies across the depositional environments of this and other deltas is critical for sustainable management of high-quality water resources.

The project is sponsored by the National Science Foundation.