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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 #384319

Research Project: Design and Implementation of Monitoring and Modeling Methods to Evaluate Microbial Quality of Surface Water Sources Used for Irrigation

Location: Environmental Microbial & Food Safety Laboratory

Title: Persistent patterns of E. coli concentrations in two irrigation ponds from three years of monitoring

item STOCKER, MATTHEW - Orise Fellow
item Pachepsky, Yakov
item SMITH, JACLYN - Orise Fellow
item Morgan, Billie
item HILL, ROBERT - University Of Maryland
item Kim, Moon

Submitted to: Water, Air, and Soil Pollution
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/10/2022
Publication Date: 10/29/2022
Citation: Stocker, M., Pachepsky, Y.A., Smith, J., Morgan, B.J., Hill, R., Kim, M.S. 2021. Persistent patterns of E. coli concentrations in two irrigation ponds from three years of monitoring. Water, Air, and Soil Pollution.

Interpretive Summary: Testing irrigation water for E. coli concentrations is a standard recommendation to evaluate the microbial quality of irrigation water. In ponds and reservoirs, significant differences may exist between E. coli concentrations in water samples taken at different locations on the same sampling day. Failing to account for areas that tend to have consistently higher or lower E. coli may result in biased microbial water quality conditions and associated risks. The objective of this work was to determine persistent patterns in E. coli distributions across two working farm ponds in Maryland using the mean-relative-difference method. E. coli patterns that persisted over three years reflected pond use practices. E. coli patterns correlated with persistent spatial patterns of physical and biochemical water quality parameters measured in situ with sensors concurrently with the water sampling. This study is useful to water quality management professionals in that it indicates the objective way of establishing sampling strategies to assess the microbial quality of water used for irrigation.

Technical Abstract: Small to medium irrigation ponds provide substantial quantities of water for irrigation in the Mid-Atlantic region. The concentrations of the fecal indicator organism Escherichia coli are used to evaluate the microbial water quality of irrigation sources. Little is known about the spatiotemporal variability of E. coli concentrations in pond water and the possible effects on monitoring and management of the microbial quality of irrigation water from these ponds. The objective of this work was to test the hypotheses that a) spatial patterns of E. coli concentrations exist that are preserved both intra- and inter-annually, and (b) persistent spatial patterns in water quality parameters exist and correlate with persistent patterns of E. coli concentrations. Sampling was conducted biweekly during the summer months in 2016 to 2018 and consisted of taking water quality measurements at 23 and 34 locations in ponds P1 and P2, respectively. Inter-annual variability of E. coli was observed in both ponds as was substantial spatial variability of E. coli concentrations within each year. The mean-relative-difference (MRD) analysis was used to identify temporally stable patterns of E. coli concentrations within the ponds. These patterns found for individual years showed significant positive correlations with each other and with the overall pattern derived from the three-year dataset. Correlation coefficients varied from 0.487 to 0.842 in P1 and from 0.467 to 0.789 in P2 (p < 0.05). MRD patterns of water quality parameters and of E. coli concentrations showed significant correlations. Within the three-year dataset, the highest positive correlations were observed for chlorophyll-a and turbidity while the dissolved oxygen concentrations demonstrated the greatest negative correlations. Results of the present study emphasize the advisability and feasibility of finding temporally stable spatial patterns in microbial water quality within irrigation ponds.