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Title: Advancing models of microbial water quality across scales : from statistical to process-based approaches
Author: Neill, Aaron J.
ISNI:       0000 0004 8498 5053
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2019
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Impaired microbial water quality poses a significant public health risk as ingestion of faecal pathogens in contaminated waters can lead to severe gastrointestinal illness in humans. This thesis aimed to advance models of microbial water quality across scales in order to further process understanding and inform management. At the catchment scale, spatial-streamnetwork models fitted to long-term concentrations of E. coli measured at 10 sites in the 52 km2 Tarland Burn had significant value in making robust, catchment-wide predictions of concentrations through accounting for spatial autocorrelation in observations. This facilitated identification of potential "hot spots" of contamination. Accounting for hydrological connectivity potential of arable and pasture land did not change model performance, however, probably reflecting the importance of localised chronic sources of E. coli. At the landscape scale, parsimonious tracer-aided hydrological models increased confidence in simulated hydrological processes underpinning predictions of faecal indicator organism (FIO) dynamics in streams. This allowed hillslope-riparian zone connectivity to be identified as a key control on summer faecal coliform (FC) loads in the Bruntland Burn (3.2 km2) and suggested that under-predictions in winter reflected inadequate microbial rather than hydrological process conceptualisation. Finally, a newly-developed agent-based model (MAFIO) coupled to a spatially-distributed tracer-aided model showed promise in simulating transfers of E. coli from livestock to streams via the processes of direct deposition, overland flow transport and seepage from degraded soils at the sub-field scale in the Tulloch Burn (0.42 km2). Furthermore, MAFIO could provide management-relevant insights into spatio-temporal dynamics of source areas, transfer mechanisms and livestock types contributing E. coli to the stream. Whilst this thesis focused on microbial water quality, the modelling techniques considered likely have value in overcoming limitations in water quality models more generally, and collectively reinforce the need to consider different approaches as part of a suite of tools available for informing management.
Supervisor: Soulsby, Chris ; Tetzlaff, Doerthe ; Strachan, Norval J. C. ; Hough, Rupert ; Avery, Lisa Sponsor: Scottish Goverment's Hydro Nation Scholars Programme
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Water quality ; Water ; Water quality biological assessment ; Nonpoint source pollution