Modelling E'coli and Campylobacter in a Pastoral Catchment

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Modelling E.coli and Campylobacter in a Pastoral
Catchment

• Sandy Elliott

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Aim of the research

• Develop a detailed, mechanistic, dynamic model of
  E. coli and Campylobacter for a dairy catchment
  (Toenepi)
• Include host, deposition, transport into streams,
  transport in streams
• Exploratory, ambitious

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Questions for modellers

• Do we understand how microbes are generated and
  transported in the environment?
• Can we predict the sources, pathways, and
  concentrations?
• How effective are mitigations?
• How important are farm sources overall?

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Sources and transport into streams
From Richard Muirhead, Agresearch, 2008
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Stream processes
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Stream network
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Rainfall-runoff model
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Land microbial loss
Excretion onto land
Direct deposition and dairy shed waste discharges
to streams
Irrigation
Overland flow
Wash-off
Cow pats
Infiltration
Decay
Soil mobile water
Drain flow losses
Input to stream reach
Decay and sorption
Loss to immobile water and groundwater
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Stream microbial transport
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Cow infection
Cross-infection
Infected
Un-Infected
Recovery
Infection from stream water
Stream water
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Dose-response relation
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Toenepi application

• Waikato Focus Catchment
• Campylobacter and E. coli monitoring data
  available, storms and baseflow
• Good spatial data already available
• Default model parameters from literature, best
  judgement

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Model subcatchments and reaches
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Soils
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Farms, land units
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Parameters
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More parameters
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and more parameters
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Some early example results
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Flows
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Campylobacter time-series
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E. Coli time-series
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Toenepi Storm DataE. coli, Flow , Turbidity and
Campylobacter
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Flood time series(Campylobacter, 18 Sept 2005)
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Stock removed.
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Some early findings for Campy

• Difficulty predicting concentration time-series
• Shedding rate at high end (1010/cow/day) required
  to get concentrations in stream high enough
• Need ongoing direct inputs to streams to get
  concentrations high enough
• These are accompanied by large diurnal
  concentration swings
• Storm concentration predictions too low. Need to
  increase sources (washoff coefficient, decay,
  shedding)
• Large parameter uncertainty for sensitive
  parameters
• Cows remain mostly infected, even in headwaters,
  for low median infective dose (100).
  Self-perpetuating system.

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Information gaps

• Role of subsurface flow, soil loss
• Role of other animals
• Where does the baseflow and stormflow
  contribution come from!

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Some possible experiments

• Stock removal
• Intensive sampling during a day
• Artificial flow release into Toenepi stream,
  including inert solutes
• Confirm sources in streams during baseflow by
  tracking and forensics