AIMS: To characterize and model spatial variations in faecal-indicator organism concentrations in watercourses draining a large rural catchment during the bathing season. METHODS AND RESULTS: Presumptive coliform (PC), presumptive Eschericia coli (PE) and presumptive enterococci (PEnt) concentrations were determined under base- and high-flow conditions at 24 monitoring points in the Rheidol/Ystwyth catchment, Wales. Relationships with land use and topographic variables within their 'subcatchments' were investigated. Geometric mean (GM) concentrations typically increase more than 10-fold at high flow. The proportion of improved pasture within subcatchments explains 81.6, 73.0 and 85.8%, respectively, of the variance in high-flow GM PC, PE and PEnt concentrations. Distributed modelling suggests that organisms derived from more distant parts of subcatchments may be lost through die-off and sedimentation along watercourses at base flow, although not at high flow. Reductions in concentrations are also evident downstream of reservoir impoundments. CONCLUSIONS: Large rural catchments may contribute substantially to faecal indicator loadings in coastal waters. Indicator concentrations can be modelled successfully using land use and topographic data. SIGNIFICANCE AND IMPACT OF THE STUDY: Development of a modelling approach that provides valuable insight into faecal indicator sources and the transport and survival of these organisms within large catchments.
AIMS: To characterize and model spatial variations in faecal-indicator organism concentrations in watercourses draining a large rural catchment during the bathing season. METHODS AND RESULTS: Presumptive coliform (PC), presumptive Eschericia coli (PE) and presumptive enterococci (PEnt) concentrations were determined under base- and high-flow conditions at 24 monitoring points in the Rheidol/Ystwyth catchment, Wales. Relationships with land use and topographic variables within their 'subcatchments' were investigated. Geometric mean (GM) concentrations typically increase more than 10-fold at high flow. The proportion of improved pasture within subcatchments explains 81.6, 73.0 and 85.8%, respectively, of the variance in high-flow GM PC, PE and PEnt concentrations. Distributed modelling suggests that organisms derived from more distant parts of subcatchments may be lost through die-off and sedimentation along watercourses at base flow, although not at high flow. Reductions in concentrations are also evident downstream of reservoir impoundments. CONCLUSIONS: Large rural catchments may contribute substantially to faecal indicator loadings in coastal waters. Indicator concentrations can be modelled successfully using land use and topographic data. SIGNIFICANCE AND IMPACT OF THE STUDY: Development of a modelling approach that provides valuable insight into faecal indicator sources and the transport and survival of these organisms within large catchments.