Abstract: Diffuse nutrient loads are a common problem in developed and agricultural watersheds. While there has been substantial investment in best management practices (BMPs) to reduce diffuse pollution, there remains a need to better prioritize controls at the watershed scale as reflected in recent US-EPA guidance for watershed planning and Total Maximum Daily Load development. We implemented spatial optimization techniques among four diffuse source pathways in a mixed-use watershed in Northern Vermont to maximize total reduction of phosphorus loading to streams while minimizing associated costs. We found that within a capital cost range of 138 to 321 USD ha-1 a phosphorus reduction of 0.29 to 0.38 kg ha−1 year−1, is attainable. Optimization results are substantially more cost-effective than most scenarios identified by stakeholders. The maximum diffuse phosphorus load reduction equates to 1.25 t year−1using the most cost-effective technologies for each diffuse source at a cost of $3,464,260. However, 1.13 t year−1 could be reduced at a much lower cost of $976,417. This is the practical upper limit of achievable diffuse phosphorus reduction, above which additional spending would not result in substantially more phosphorus reduction. Watershed managers could use solutions along the resulting Pareto optimal curve to select optimal combinations of BMPs based on a water quality target or available funds. The results demonstrate the power of using spatial optimization methods to arrive at a cost-effective selection of BMPs and their distribution across a landscape.
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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).