HR: 09:40h
AN: H51N-07 INVITED    [Abstracts]
TI: High Resolution Water Quality Monitoring: New Equipment, New Data, New Insights
AU: * Jordan, P
EM: p.jordan@ulster.ac.uk
AF: University of Ulster, School of Environmental Sciences, Coleraine, BT52 1SA, Ireland
AU: Arnscheidt, J
EM: j.arnscheidt@ulster.ac.uk
AF: University of Ulster, School of Environmental Sciences, Coleraine, BT52 1SA, Ireland
AU: McGrogan, H
EM: hj.mcgrogan@ulster.ac.uk
AF: University of Ulster, School of Environmental Sciences, Coleraine, BT52 1SA, Ireland
AB: Monitoring nutrient transfers in river catchments is often constrained by the need to analyse water samples in the laboratory. This can result in coarse sampling regimes that bias datasets to low flow or high flow periods depending on the sophistication of the sampling method. Subsequent statistical interpolation and extrapolation methods to estimate annual nutrient transfers rely on concentration-flow relationships that are often unpredictable and usually under-estimate observed loads. Coupled with this limitation is an inability to discern subtle patterns that may be un-sampled or overlooked as analytical ‘noise'. Here we present results from a novel and robust catchment monitoring method in an investigation of the magnitude, processes and patterns of total phosphorus (TP) transfers measured at high resolution. Bank-side TP analysers in the Irish border region extract and analyse TP in water samples on a 10 min time-step in 3x5km2 sub-catchments of the Blackwater River. Other, complimentary, water quality and hydrometeorological parameters are also measured continuously using standard and established equipment. The datasets provide a time-integrated series that can establish observed annual TP loads for catchment management. Additionally, storm related transfers from diffuse sources are fully captured and indicate periods of nutrient ‘wash-out' and relationships with frontal and convective precipitation. Low flow TP transfers indicate impacts from rural point-sources and also diurnal changes due to processes that are only partially understood. The datasets can also be used to validate interpolation methods from coarser sampling regimes and provide unsurpassed time-series validation for catchment water quality models.
DE: 1804 Catchment
DE: 1806 Chemistry of fresh water
DE: 1848 Monitoring networks
DE: 1871 Surface water quality
DE: 1895 Instruments and techniques: monitoring
SC: Hydrology [H]
MN: 2007 Fall Meeting