Methodology for Identifying Optimal Locations of Water Quality Sensors in River Systems
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A method to optimally site river water quality sensors is expanded and applied to a case study river to explore the application of mathematical siting methods to the design of river sampling networks. Fecal coliform contamination due to flooded swine waste lagoons was modeled as it moves downstream, and optimal sensor locations are located by minimizing the objective function of the optimization problem. The results of the simulations are analyzed by varying the number of allowed sampling locations and the simulated contamination event. For the case study application, the model suggests three sampling locations along the modeled river section. These three suggested sensing points did not greatly vary in location for different river flows and contamination events, indicating the robustness of the model results for this specific case study. Generally, the application of mathematical contaminant modeling is a useful and systematic approach to aid the design of river water quality monitoring networks.
KeywordsOptimal location Water quality sampling Monitoring Water pollution River systems
The authors thank the additional collaborators who developed the original contaminant model, Aurea Martínez and Miguel A. Vilar. We also thank Martha Absher, assistant dean for Education and Outreach Programs at Duke University, who provided opportunity for this project through the Pratt Research Fellowship program. The financial support provided by Projects MTM2009-07749 and MTM2012-30842 of M.E.C. (Spain) is also gratefully acknowledged.
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