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Improving Recreational Water Quality Assessments Through Novel Approaches to Quantifying Measurement Uncertainty
Citation:
Rose, J. AND A. GRONEWOLD. Improving Recreational Water Quality Assessments Through Novel Approaches to Quantifying Measurement Uncertainty. Presented at International Association of Great Lakes Research Annual Conference, Toronto, BC, CANADA, May 17 - 21, 2010.
Impact/Purpose:
Presentation material
Description:
Bacteriological water quality in the Great Lakes is typically measured by the concentration of fecal indicator bacteria (FIB), and is reported via most probable number (MPN) or colony forming unit (CFU) values derived from algorithms relating \raw data" in a FIB analysis procedure (e.g. number and volume of sample aliquots, the pattern of positive wells in an MPN-based procedure, or the number of colonies counted on a growth plate in a CFU-based procedure) to the FIB concentration probability distribution. Unfortunately, while this \raw data" contains all of the information necessary to quantify the FIB concentration, it is rarely reported (and commonly discarded) after calculating an MPN or CFU value. Here, we introduce a set of novel probabilistic and Bayesian modeling tools for propagating information regarding FIB con- centration uncertainty from \raw data" in MPN- and CFU-based experiments into model-based water quality forecasts and water quality-based management decisions. Potential benefits of our approach include a more defensible representation of model forecast uncertainty, the ability to combine bacteriological water quality data derived from different testing procedures (while incorporating their unique intrinsic sources of uncertainty and bias), and a potential foundation for establishing new water quality standards based not on method-specific MPN or CFU values, but on a probabilistic representation of the in situ FIB concentration itself.