HGS RESEARCH HIGHLIGHT – Modeling fate and transport of E. coli in a small watershed with grazing lands around a pond
Pachepsky, Y. A., Yakirevich, A., Widmer, J., Stocker, M., Hill, R. L., Coffin, A., & Dunn, L. (2024). Modeling fate and transport of E. coli in a small watershed with grazing lands around a pond. https://agu.confex.com/agu/agu24/meetingapp.cgi/Paper/1622936
“The non-calibrated [HydroGeoSphere] model could tolerably simulate E. coli concentration patterns and time of peak events in most of the pond’s sampling locations.”
Pachepsky, Y. A., Yakirevich, A., Widmer, J., Stocker, M., Hill, R. L., Coffin, A., & Dunn, L. (2024). Modeling fate and transport of E. coli in a small watershed with grazing lands around a pond. https://agu.confex.com/agu/agu24/meetingapp.cgi/Paper/1622936
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Summary:
This research investigates the fate and transport of E. coli in a small watershed with grazing lands surrounding a pond, using HydroGeoSphere (HGS) to develop a mechanistic numerical model. Understanding how E. coli moves through surface and subsurface water systems is crucial for managing microbial contamination risks in agricultural watersheds, where livestock activities can significantly impact water quality.
The study was conducted in a 0.45 km² watershed in Georgia, USA, which is used for cow grazing. Researchers collected data from July 2021 to October 2023, monitoring E. coli concentrations in cowpats and pond water. Observations included cow movements and time spent in the pond, as these behaviors directly influence microbial loading into the water system. By integrating real-world data with numerical simulations, the study examined E. coli release, transport, and inactivation under varying environmental conditions.
HGS played a central role in modelling the watershed system, utilizing its fully integrated surface-subsurface flow capabilities. The model incorporated the Richards equation for three-dimensional transient subsurface flow and a two-dimensional diffusive wave equation for surface water flow. Microbial transport was simulated through advection-dispersion equations, incorporating linear sorption and temperature-dependent inactivation. The researchers also implemented boundary conditions reflecting precipitation, evapotranspiration, and bacterial loading from cowpats, ensuring a realistic representation of watershed hydrology and microbial dynamics.
The results indicated that the non-calibrated model effectively captured E. coli concentration patterns and peak events in most sampling locations. However, seasonal variations affected model performance, with discrepancies noted during autumn months. One key finding was that direct E. coli loading from cows in the pond was two orders of magnitude greater than contributions from surface runoff, highlighting the significant role of livestock behavior in microbial contamination. Simulated scenarios demonstrated that E. coli concentrations in the pond varied based on hydrological conditions, microbial decay rates, and bacterial loading from grazing areas.
By leveraging HGS’s advanced modelling capabilities, the study provides critical insights into microbial contamination processes in agricultural watersheds. The research underscores the importance of accounting for both surface and subsurface transport mechanisms when assessing microbial water quality risks. These findings can inform watershed management strategies, helping to develop targeted interventions that minimize microbial contamination from livestock and improve water quality in similar environments.
Research Motivation:
Grazing lands are sources of fecal microorganisms that can reach various water bodies, impacting their quality and adversely affecting their potential uses. Water runoff during and after rainfall events is a key factor in microbial transport, carrying animal waste from pastures into water sources used for irrigation and recreation. Public health concerns regarding the fate and transport of pathogenic microorganisms, as well as indicator organisms like Escherichia coli, highlight the importance of understanding microbial contamination in these systems.
Ponds are essential water sources in rural agricultural environments, with an estimated 2.5 to 4 million ponds used in the United States for irrigation, recreation, livestock watering, and post-harvest processing. Cattle ponds, in particular, serve as drinking and cooling stations for livestock during hot days, ensuring a perennial water supply. The microbiological quality of these water bodies is a critical concern since they are directly linked to animal drinking water and irrigation. Contaminated water raises concerns about potential microbial exposure for both livestock and crops, yet the microbial quality of cattle ponds and the factors influencing it remain poorly understood.
Despite the importance of microbial water quality in agricultural ponds, little attention has been given to modelling these systems. Mechanistic mathematical modelling provides a valuable tool for predicting surface water quality and assessing various sources of environmental contamination. Given the complexity of hydrogeological and hydrochemical processes, the researchers selected HydroGeoSphere (HGS) as the foundation for the site-specific model. HGS employs a fully coupled numerical approach, allowing for the simultaneous simulation of surface and variably saturated subsurface flow, solute transport, and heat transfer.
The results of this work provide valuable insights for consultants and environmental management professionals. They demonstrate an effective approach for obtaining moderately accurate forecasts of microbial water quality in cattle ponds without requiring extensive and resource-intensive data collection for model calibration.
Abstract:
Microbial contamination of surface water is a concern for public health. Grazing lands are sources of fecal microorganisms that can infect water bodies, impact water quality, and adversely affect potential water use. Water runoff during and after rainfall events are essential factors causing microbial migration from animal waste on pastures. Understanding the mechanisms of microbial transport with surface/subsurface flow is imperative to predict surface water contamination and to assign management strategies.
This research aimed to develop and test a comprehensive numerical model to simulate watershed-scale surface/subsurface water flow, bacteria release from cowpats, their fate, and transport to a pond. Accounting for the complexity of hydrogeological and microbiological processes, we used components of the HydroGeoSphere (HGS) software as a basis for our model. The Richards equation simulates three-dimensional transient subsurface flow in a variably saturated porous medium. The two-dimensional depth-averaged diffusive wave equation describes surface water flow. The subsurface and surface flow equations are fully coupled. Microbial transport is described by 3D and 2D coupled advection-dispersion equations in the subsurface and surface, respectively. Linear sorption and inactivation of bacteria are taken into account.
The model was used to simulate bacterial transport at a small watershed (area ~0.45 km2) within a commercial pond in the Tifton (Georgia, USA) area. The pond was extensively monitored for three years. The bacteria concentrations remained at relatively high levels throughout the study. Simulations accounted for the possible effects of the extended lag phase, concentration-dependent E. coli die-off in waters with high dissolved organic matter content, and the presence of indigenous E. coli within the clayey bottom sediment functioning as a satisfactory bacterium habitat.