Related Experiment Video
Updated: Mar 10, 2026

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff
Published on: May 15, 2017
Evaluating pathogen modeling approaches for microbial risk assessment of stormwater in recreational and reuse
Audrey Laiveling1, Corinne Wiesner-Friedman2, Michael Jahne2
1Oak Ridge Institute for Science and Education, 26 Martin Luther King Drive, Cincinnati, OH, 45268, United States.
Abstract:
This study evaluates the use of a human-associated fecal marker (HF183) versus pathogen measurements in quantitative microbial risk assessments (QMRA) for two previously published scenarios: surfer exposure to stormwater-impacted ocean water following wet weather events and stormwater reuse for potable and non-potable activities. Notably, the recreational water study provided a rare opportunity to epidemiologically validate QMRA estimates. Pathogen inputs for risk assessments were estimated using four methods adapted from prior recommendations: pathogen measurements, marker measurements, marker measurements including decay, and a 10% sewage fraction assumption. In the recreational scenario, the pathogen method yielded a median probability of illness (1.8 × 10-2) closest to a concurrent epidemiology study's mean illness rate (1.2 × 10-2); the marker method underestimated illness, but decay inclusion yielded a median illness risk (6.0 × 10-4) within the epidemiology mean's confidence interval. While epidemiological validation data was unavailable for the reuse scenario, log reduction targets (LRTs) were generally within 1 log difference between the pathogen and marker methods, though uncertainty in decay input parameters remains a challenge for marker-based risk assessment. In both scenarios, the 10% sewage fraction method was conservatively protective of human health. Our results demonstrate the potential applicability of human fecal markers in stormwater QMRA while highlighting the need for improved understanding of pathogen-marker source and decay relationships.

