Citation:

Johnston, JohnM, S. Ghimire, AND M. Jahne. Data Extraction and Aggregation to Model Microbial Health Risk Associated with Rainwater Harvesting. International Society for Ecological Modelling Global Conference 2023, Scarborough, Ontario, CANADA, May 02 - 06, 2023.

Impact/Purpose:

Harvesting rainwater from rooftops is one way to address the issue of safe and sustainable water resources and increase community climate resilience.  One of the barriers adoption or roof rainwater harvesting by is that there is limited federal guidance due to data gaps on the microbial health risks of roof rainwater harvesting.  This project attempts to fill the data gaps by modeling the health risks based on the pathogen concentrations in animal feces that can contaminate roof harvested rainwater.   The intended audience for this project is regulators and other stakeholders who are interested in rainwater harvesting.

Description:

Harvesting precipitation from rooftops can increase community climate resilience by supplementing water supplies and reducing stormwater runoff.  One of the barriers for implementing rooftop rainwater harvesting in the U.S. is limited risk-based treatment guidance for the use of roof harvested rainwater.  Guidance is limited due to data gaps (e.g., microbial pathogen characterization in rainwater), regional differences, varying roof harvested rainwater infrastructure, materials, and maintenance, as well as the variability of pathogen characteristics (i.e., infection rate, prevalence, intensity, and virulence) in rooftop harvested rainwater. The study’s goal is to develop a robust pathogen characterization dataset for rooftop harvested rainwater as part of a larger effort to quantify the microbial health risks associated with non-potable rainwater use.  The pathogen dataset is used in exposure assessment that models the dose of pathogens people are expose to, which is part of quantitative microbial risk assessment (QMRA) that is a method for quantifying microbial health risks. We created a causal model that assumed a direct relationship between the pathogens in roof harvested rainwater and in the feces of animals on rooftops and conducted a systematic review of pathogens in animal feces.  The data extracted from the literature on the concentration of pathogens in animal feces was not standardized and in many different formats.  We fit the pathogen concentrations from each study to a log normal distribution using statistical and imputation methods.  The distributions were aggregated using a weighted Monte Carlo approach and were used as inputs into the causal model and QMRA to estimate the health risks associated with harvested rainwater.  The calculated health risks are intended to support the development of guidance when using rainwater for non-potable use such as landscape irrigation, garden watering, and vehicle washing.  

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