Abstract: Understanding the relationships between stream water quality, geomorphology, and habitat is essential for effective watershed management. Vermont EPSCoR Streams Project water quality parameters such as total phosphorus (TP), total suspended solids (TSS), E. coli (EC), and total coliforms (TC), are seen as primary risk indicators of environmental and human health. With the Vermont Agency of Natural Resources’ (VTANR) rapid geomorphic assessments (RGA) and rapid habitat assessments (RHA) now completed over most of the state and with the growing base of water quality data, we can begin to compare these datasets. Where strongly correlated, the data could be used as a predictive tool to direct future watershed improvements and inform future monitoring. Using GIS, the Streams Project sites were joined to the VTANR Phase II RHA/RGA reaches. Streams Project water quality data were compared with RGA and RHA total scores as well as their component values. The RGA assesses 4 components: channel degradation, aggradation, widening, and changes in planform. The total RGA score was found to be highly negatively correlated to Average TSS (especially widening), whereas the other water quality parameters show little correlation. The RHA assesses 10 components including substrate and pool characteristics, sediment and channel flow, channel alteration and sinuosity, and stream bank and buffer characteristics. The total RHA score was found to be negatively correlated to total coliform (especially bank stability), whereas total phosphorus was most correlated to channel flow status.
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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).