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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #322755
Title: Predicting microbial water quality with models: over-arching questions for managing risk in agricultural catchments

Author
item OLIVER, DAVID - University Of Stirling
item REANEY, SIM - University Of Durham
item PORTER, KEN - University Of Stirling
item Pachepsky, Yakov
item MUIRHEAD, RICHARD - Agresearch
item COFFEY, RORY - Environmental Protection Agency (EPA)
item KAY, DAVID - Aberystwyth University
item HONG, EUNMI - Oak Ridge Institute For Science And Education (ORISE)

Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/23/2016
Publication Date: 2/25/2016
Citation: Oliver, D., Reaney, S., Porter, K., Pachepsky, Y.A., Muirhead, R., Coffey, R., Kay, D., Hong, E. 2016. Predicting microbial water quality with models: over-arching questions for managing risk in agricultural catchments. Science of the Total Environment. 544:39-47.

Interpretive Summary: Determining the microbial quality of recreational, irrigation and shellfish-harvesting waters is important to ensure compliance with health-related standards and associated legislation. Levels of microbial pollution in environmental matrices are often measured by quantifying faecal indicator organisms. To make sense of, and to support decision making on, multiple sources of faecal material discharges from a range of different activities, catchment scale models are needed that can fairly apportion water quality risks to individual contaminant sources. In this work, we review, summarize, and discuss critical conceptual foundations of microbial water quality modelling, including purpose, selection, data, and use. We also present the short-term and long-term research needs to address uncovered knowledge gaps. Results of this work will be of use to environmental researchers and management professionals in that they provide an overview of the practicality, reliability, and usability of the models that are deployed and will be developed.

Technical Abstract: Determining the microbial quality of recreational, irrigation and shellfish-harvesting waters is important to ensure compliance with health-related standards and associated legislation. Animal faeces represent a significant human health risk, and concentrations of fecal indicator organisms (FIOs) present the qualitative foundation for regulations and guidance on microbial water quality. The application of catchment models to predict microbial water quality, coupled with direct detection and quantification, plays an important role for guiding decision-making associated with the management of water resources. Modelling the fate and transfer of FIOs at different spatial scales poses a considerable challenge to the research and policy community some of the key research questions under investigation by the research community include (a) how do different hydrological pathways in soil, that connect FIO sources to water bodies, vary in space and time across different catchment types and how does this impact on FIO travel times through the environment, (b) to what extent does the probability of FIO die-off vary for different environmental conditions (in different environmental matrices) around the world; (c) how do we integrate FIO behavioral characteristics (e.g. their ability to persist or move in the environment) into model frameworks that are useful for decision-makers; and (d) how will the export of FIOs from the landscape alter under projected climate change and/or land use change? The purpose of this paper is to present the current status of the knowledge base available to answer these questions, and to offer the collective vision of the need and feasibility of advances in watershed water quality. We revisit modeling purposes, modelling approaches, data availability and efficient application of models. Short-term (0-5 years) and long-term (5-10 years) are outlined. The improvements in modelling of catchment microbial dynamics will support our efforts to bridge scales between research and policy making, and will play an important role in helping to understand and address the challenges of protecting food safety and water quality in the face of climate and land use change.