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

0610075史蒂文斯该项目是几个“试验台”项目之一，资助评估的问题，需要解决的成本效益设计的环境观测站的研究水文，物理，化学和生物过程之间的相互作用在流域尺度。该项目旨在开发更好和更简单的方法来量化城市地区暴雨径流中的污染物负荷。该计划将使用贝叶斯模型技术，建立易于测量的替代物与主要水质变量之间的关系，并将评估优化采样时间和频率的方法，以尽量减少污染物负荷的不确定性。这个话题在全国范围内引起了相当大的兴趣，因为精确测量城市雨水等来源的负荷的固有成本，这些来源的浓度和流量都受到高频变化的影响。该项目将涉及本科生和研究生，并包括一系列广泛的推广活动，以研究人员，学生和从业人员在大盐湖盆地的水污染问题。该项目的成果可在全国暴雨水管理领域得到重要的实际应用。

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.