Efficient 3-D data inversion: Soil characterization and moisture monitoring from crosswell GPR at a Vermont test site
Water Resources Research, 34, 1889-1900, 1998
Abstract: We extend our methodology for three-dimensional parameter structure and value estimation and apply it to a Vermont test site. Ground-penetrating radar (GPR) cross-well travel times are inverted for estimation of heterogeneous GPR soil velocities before and after a controlled release of salt water in the unsaturated zone. The method, which is based on an approximation of the extended Kalman filter in conjunction with data-driven zonation, automatically estimates not only distributed zone values but also the number of zones, zone geometry, and zone covariance. Resultant GPR velocity estimates are shown to reduce travel time estimation errors and to be consistent with independent cone penetrometer measurements at all five walls at the site. Comparison of velocity estimates before and after forced injection of salt water is used to detect and visualize soil moisture patterns in three dimensions. By varying the 'cluster tolerance criterion' in the data-driven zonation process, the user can obtain a desired resolution of heterogeneity (number of zones used) in the resultant model.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).