You are here:
Addressing Uncertainty in Fecal Indicator Bacteria Dark Inactivation Rates
Citation:
GRONEWOLD, A., L. Myers, J. SWALL, AND R. T. Noble. Addressing Uncertainty in Fecal Indicator Bacteria Dark Inactivation Rates. WATER RESEARCH. Elsevier Science Ltd, New York, NY, 45(2):652-664, (2011).
Impact/Purpose:
Fecal contamination is a leading cause of surface water quality degradation in the United States (Mostaghimi et al., 2002; Noble et al., 2003a) and through out the world (Ashbolt et al., 1993; Ghinsberg et al., 1994). Roughly 20% of all total maximum daily load (TMDL) assessments approved by the United States Environmental Protection Agency (USEPA) since 1995, for example, address water bodies with unacceptably high fecal indicator bacteria (FIB) concentrations (a proxy for the measurement of fecal contamination-associated pathogens), the highest percentage of any pollutant category (for more on the TMDL program and fecal contamination TMDLs, see National Research Council, 2001; Houck and Environmental Law Institute, 2002; Benham et al., 2006).
Description:
Fecal contamination is a leading cause of surface water quality degradation. Roughly 20% of all total maximum daily load assessments approved by the United States Environmental Protection Agency since 1995, for example, address water bodies with unacceptably high fecal indicator bacteria (FIB) concentrations (a proxy for the concentration of pathogens found in fecal contamination from warm–blooded animals), the highest percentage of any pollutant category. Such water quality assessments are often based on model forecasts which assume that a pollutant is lost or removed from the water column at a certain rate. In efforts to reduce human health risks in threatened water bodies, regulators enforce limits on easily–measured FIB concentration metrics, including most probable number (MPN) and colony forming unit (CFU) values. Accurate assessment of the risks associated with the threat of fecal contamination depends on propagating uncertainty surrounding “true” FIB concentrations into MPN and CFU values, decay rates, model forecasts, and management decisions. Here, we explore how empirical relationships between FIB decay rates and extrinsic factors might vary depending on how uncertainty in MPN values is expressed. Using water quality samples from the Neuse River Estuary in eastern North Carolina, we compare Escherichia coli (EC) and Enterococcus (ENT) decay rates derived from two statistical models of first–order loss; a conventional model employing ordinary least-squares (OLS) regression with MPN values, and a novel Bayesian model utilizing the pattern of positive wells from an IDEXX Quanti-TrayR/2000 test kit. We find that the Bayesian analysis provides as good an explanation of the observed data variability, and more precise estimates of the EC and ENT first-order decay rates when compared to the conventional model. Our results suggest a new strategy for reducing uncertainty in model-based water resource management decisions, and for developing more robust relationships between environmental factors and FIB decay rates.
URLs/Downloads:
j.watres.2010.08.029
GRONEWOLD 10-013 FINAL JOURNAL ARTICLE..PDF (PDF, NA pp, 1178 KB, about PDF)