Tools for Environmental Observatory Design and Implementation: Sensor Networks, Dynamic Bayesian Nutrient Flux Modeling, and Cyberinfrastructure Advancement

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0610075StevensThis project is one of several "test-bed" projects funded to evaluate issues that need to be resolved for cost-effective design of environmental observatories for research on interactions among hydrological, physical, chemical, and biological processes at the watershed scale. This project seeks to develop better and simpler methods to quantify pollutant loadings in storm-water runoff from urban areas. The PIs will use Bayesian modeling techniques to develop relationships between easily measured surrogates and key water quality variables and will evaluate ways to optimize the timing and frequency of sampling to minimize pollutant loading uncertainties. This topic is of considerable interest nationwide because of the inherent costs of accurately measuring loadings from sources like urban storm water, which are subject to high frequency variations in both concentrations and flows. The project will involve both under-graduate and graduate students and includes a broad set of outreach activities to researchers, students and practitioners working water pollution problems in the Great Salt Lake Basin. Results of the project could have important practical applications nationally in the area of storm-water management.