1a. Objectives (from AD-416):
Objective 1: Elucidate and quantify mechanisms and factors of pathogen and indicator bacteria fate and transport from animal sources to irrigation waters. Evaluate the effects of soil and vegetation properties on parameters of pathogen fate and transport with surface runoff to irrigation water sources. Assess contribution of bottom sediments as potential pathogen reservoirs in agricultural landscapes. Research the fate and transport of pathogen and indicator bacteria in irrigation water delivery systems. Objective 2: Develop models and computer-based tools to recommend and implement site-specific diagnostics, monitoring, and prediction of the fate and transport of pathogen and indicator bacteria that affect the microbiological condition of irrigation water. Develop bacteria fate and transport components for USDA-ARS hydrologic models to simulate the effect of bottom sediments, periphyton, and bank soils on microbiological quality of surface waters intended for irrigation. Develop a farm-scale irrigation system model that will use site specific environmental and management data to provide input data for quantitative microbial risk assessment of irrigation waters.
1b. Approach (from AD-416):
An integrated approach including laboratory research, field research on irrigation systems, and mathematical modeling will be used. Experiments and monitoring will be carried out to (a) evaluate the effects of soil and vegetation properties on pathogen fate and transport with surface runoff to irrigation water sources, (b) understand and quantify pathogen and indicator bacteria fate in potential pathogen reservoirs associated with irrigation systems, such as bottom sediments in surface waters, and biofilms in irrigation equipment, and (b) microbial exchange between these reservoirs and flowing or stagnant waters. Mechanistic models will be developed to allow for (a) analyzing possible changes in pathogen and indicator bacteria concentrations along hydrologic pathways from animal sources to fields, and (b) improving resource allocation to monitor pathogen and indicator bacteria occurrence along the pathways.
3. Progress Report:
Research was continued to evaluate biofilm formation in irrigation systems and their impact on irrigation water quality. An irrigation system was assembled consisting of removable coupons in the pipes, allowing for evaluation of E. coli colonization of inner pipe surfaces. It was observed that pipe material affected the extent of biolfilm formation and subsequent release of bacteria into the irrigation flow. This illustrates the need for monitoring water quality at the sprinkler head because microbial water quality assessments based solely on source waters can be misleading. Modeling efforts to evaluate the effect of different land management practices on microbial overland transport from manure/feces to surface waters were continued. Existing models of microbial transport require information on soil and manure properties that may be impractical to obtain. Multiple runs of our microbial transport model KINEROS2/STWIR were conducted; it was observed that the proportion of microbes leaving the field is much more sensitive to rainfall parameters and soil water content than to soil properties and manure parameters. This indicates that it may be feasible to obtain estimates of land management effects on microbial water quality using data from national databases, monitoring networks, and remote sensing. A new model to simulate microbial die-off in cowpats was developed, and successfully tested with data collected from Virginia, Maryland, New Zealand and the United Kingdom. Application of this model supports our previous conclusion that runoff from manured or grazed fields is not the dominant source of high E. coli concentrations found in surface waters. In collaborative work with scientists from Michigan State University, data from six years of plot and field experiments were re-analyzed accounting for survival, resulting in improved model estimates of microbial release. The improved accuracy of these models will contribute to substantial improvement in predictions of microbial quality of irrigation waters. Previous research has shown that vegetated filter strips (VFS) are very effective at minimizing microbial runoff from fields via enhanced infiltration. However, the wide variability observed in experimental data suggests that this is not the only mechanism responsible for microbial retention by VFS. In collaboration with scientists from University of Florida, the role of the brush layer (i.e. trichomes, hairs present on plant stem surfaces) in microbial retention was investigated. Results indicate that the brush layer can have a substantial impact on microbial retention. The selection of VFS plants with a high density of trichomes may enhance the efficiency of vegetated filter strips. A large-scale field experiment was carried out to evaluate the effect of soil conditions on the run off of microorganisms from a manured field. An irrigation system at the USDA-ARS OPE3 research site was used to conduct irrigation events for applied fresh and aged manure.Results will contribute to further validation of the microbial release and transport model STWIR, which is being adopted by EPA and will be linked with the legacy water quality model.
1. Improved capability to estimate microbial water quality. Modeling of microbial water quality is dependent on estimates of microorganisms entering surface waters as well as their subsequent survival. ARS scientists from Beltsville, MD, have created the world’s largest database on E. coli inactivation in surface waters. The data have been analyzed using predictive microbiology to simulate the dependence of E. coli inactivation rates on water temperature for different types of surface waters used in irrigation and recreation. These results will contribute to improved accuracy of microbial water quality models used for assessment and predictions for recreational and irrigation water sources.
Yakirevich, A., Pachepsky, Y.A., Gish, T.J., Guber, A., Shelton, D.R., Cho, K. 2013. Modeling transport of Escherichia coli in a creek during and after artificial high-flow events: Three year study and analysis. Water Research. DOI: 10.1016/j.watres.2013.02.011.