An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 2: Application to a small agricultural catchment

Aaron J. Neill* (Corresponding Author), Doerthe Tetzlaff, Norval J. C. Strachan, Rupert L. Hough, Lisa M. Avery, Marco P. Maneta, Chris Soulsby

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
3 Downloads (Pure)


The new Model for the Agent-based simulation of Faecal Indicator Organisms (MAFIO) is applied to a small (0.42 km2) Scottish agricultural catchment to simulate the dynamics of E. coli arising from sheep and cattle farming, in order to provide a proof-of-concept. The hydrological environment for MAFIO was simulated by the “best” ensemble run of the tracer-aided ecohydrological model EcH2O-iso, obtained through multi-criteria calibration to stream discharge (MAE: 1.37 L s-1) and spatially-distributed stable isotope data (MAE: 1.14-3.02‰) for the period April-December 2017. MAFIO was then applied for the period June-August for which twice-weekly E. coli loads were quantified at up to three sites along the stream. Performance in simulating these data suggested the model has skill in capturing the transfer of faecal indicator organisms (FIOs) from livestock to streams via the processes of direct deposition, transport in overland flow and seepage from areas of degraded soil. Furthermore, its agent-based structure allowed source areas, transfer mechanisms and host animals contributing FIOs to the stream to be quantified. Such information is likely to have substantial value in the context of designing and spatially-targeting mitigation measures against impaired microbial water quality. This study also revealed, however, that avenues exist for improving process conceptualisation in MAFIO (e.g. to include FIO contributions from wildlife) and highlighted the need to quantitatively assess how uncertainty in the spatial extent of surface flow paths in the simulated hydrological environment may affect FIO simulations. Despite the consequent status of MAFIO as a research-level model, its encouraging performance in this proof-of-concept study suggests the model has significant potential for eventual incorporation into decision support frameworks.
Original languageEnglish
Article number110905
Number of pages18
JournalJournal of Environmental Management
Early online date13 Jul 2020
Publication statusPublished - 15 Sept 2020

Bibliographical note

Software and data availability

The source code for MAFIO as used in this work is available via the University of Aberdeen PURE repository: The source code for EcH2O-iso is available at:

The Tulloch Burn datasets used in this study are available from the lead author on request.


Funding for this work from the Scottish Government’s Hydro Nation Scholars Programme is gratefully acknowledged. Many thanks to Audrey Innes, Jonathan Dick, Claire Tunaley and Bernhard Scheliga for their assistance in analysing the isotope samples. In addition, thanks to Allan Sim, Duncan White and, in particular, Claire Abel and Adam Wyness for instruction and training on microbiological sampling and analysis techniques. Simulations with EcH2O-iso and MAFIO were undertaken on the Maxwell high performance computing cluster funded by the University of Aberdeen. Sylvain Kuppel and Aaron Smith are thanked for their assistance in troubleshooting occasional issues with EcH2O-iso.


  • Diffuse pollution
  • E. coli
  • EcH2O-iso
  • Microbial water quality
  • Tracer-aided modelling
  • Water quality modelling
  • EcH(2)O-iso
  • RISK
  • E. COLI
  • EcH O-iso


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