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Development of a Watershed-to-Very-Near-Shore Model for Pathogen Fate and Transport

Development of a Watershed-to-Very-Near-Shore Model for Pathogen Fate and Transport. Sheridan K. Haack Atiq U. Syed Joseph W. Duris USGS, Lansing, MI. Setting. Little Calumet River/Burns Ditch Indiana. Significant local/regional interest and historical data Previous studies by Center PIs

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Development of a Watershed-to-Very-Near-Shore Model for Pathogen Fate and Transport

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  1. Development of a Watershed-to-Very-Near-Shore Model for Pathogen Fate and Transport Sheridan K. Haack Atiq U. Syed Joseph W. Duris USGS, Lansing, MI

  2. Setting Little Calumet River/Burns Ditch Indiana • Significant local/regional interest and historical data • Previous studies by Center PIs • NOAA SF6 transport study, 2005 • May affect beaches at which USEPA/CDC conducted recent epidemiology studies • Definitely affects beaches where Richard Whitman has developed predictive models • Contributes to portion of Lake Michigan being modeled by Phanikumar Mantha • Watershed is modestly sized, with variable land use • Tractable for initial model development • Different land uses likely yield different pathogens • Of particular interest for local E. coli TMDL issues (urban vs nonpoint sources)

  3. Rationale • One of overall goals for CEGLHH is to develop models to predict coastal microbiological (particularly, pathogen) water quality • Most current models of microbial fate and transport use E. coli • E. coli doesn’t represent many (most?) pathogens • Temporal and spatial variability in types and source loadings of pathogens poorly accounted for • In-stream and very-near-shore hydrologic processes that influence pathogen transport poorly understood

  4. Overall Objectives • Acquire information on selected pathogens in a CEGLHH focus watershed • Occurrence • Relation to conventional and emerging (chemicals, pathogen genes) measures of water quality • Develop a model of watershed-to-very-near-shore transport of these pathogens that can be linked to other models and research within CEGLHH

  5. Correlation between precipitation event and indicator bacteria concentrations, based on contingency tables using flow pattern categories, and bacteria counts from individual sub-basins. Sampling Took Place Under Three Hydrologic Conditions

  6. Preliminary Correlation Analysis • Two Groups of Samples: • Fecal coliforms/E. coli >enterococci • 20 samples: 15/20 downstream, 3 esp, 1 stx1 • Fecal coliforms/E. coli < enterococci • 25 samples: 18/25 upstream, 7 esp, 6 stx1, • Currently conducting a variety of multivariate analyses to relate patterns of bacterial and gene occurrence to • PO4, NO3, NH3, SO4, Turbidity, Color, Dissolved Oxygen, pH, Specific Conductance, and Temperature • Spatial patterns and land use • Conducting more detailed analyses for 9 samples

  7. Preliminary Correlation Analysis Red = primary wastewater chemicals (Glassmeyer et al. 2005)

  8. 15 14 13 Preliminary Correlation Analysis • For base flow and rising hydrograph conditions, chemistry of sites 12 and 14 most closely linked • Linkage between watershed and beach through channel subject to backwater from lake • Needs more accurate gauging • Did not sample during a CSO event • How would such water mix near the mouth and what does it carry? • AHTN (musk fragrance) predictor of WWTP effluents, and our own studies shown esp more probable • AHTN significantly correlated with Cl 12

  9. Watershed Model • PURPOSE: to predict loading rates for chemical constituents and bacteria from point and non-point sources into Lake Michigan • Flow Model for the study area developed and in process of calibration and sensitivity analysis • on a continuous basis using daily time steps • USDA/ARS, Soil Water Assessment Tool (SWAT) Model • Database includes: • DEM of the study area, • Delineated watershed boundaries, • NHD stream network, • Land use data, • Soils data, • Point source discharges, and • Weather data, which includes precipitation, temperature, solar radiation, wind speed, and relative humidity

  10. Preliminary Results Showing Computed and Observed Flow in the Study Area SWAT model daily mean flow results compared to the observed flow at the Porter gaging station (04094000). SWAT model daily mean flow results compared to the observed flow at the Portage gaging station (04095090), near Lake Michigan.

  11. Highlights • Genes indicating pathogenic E. coli and enterococci are frequently detected in the watershed • In the absence of CSOs • Patterns of detection are complex and must be linked to some predictable or measureable factor • esp-AHTN-Cl is one possibility • Watershed model is well-developed and can account for point-source flows (WWTP and CSO)

  12. Challenges • Continued analysis of factors associated with gene occurrence • Sampling of a CSO event • Improved measurement of flow dynamics at the Burns Ditch/Lake interface • Linkage of watershed flow model to Lake Michigan Circulation Model

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