Assessments of Composite and Discrete Sampling Approaches for Water Quality Monitoring |
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Authors: | Rachel Cassidy Phil Jordan Marianne Bechmann Brian Kronvang Katarina Kyllmar Mairead Shore |
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Affiliation: | 1.Agri-Environment Branch,Agri-Food and Biosciences Institute (AFBI),Belfast,Northern Ireland;2.School of Geography and Environmental Sciences,Ulster University,Coleraine,Northern Ireland;3.Agricultural Catchments Programme, Teagasc, Johnstown Castle,Wexford,Ireland;4.NIBIO, Norwegian Institute of Bioeconomy Research,?s,Norway;5.Department of Bioscience,Aarhus University,Silkeborg,Denmark;6.Department of Soil and Environment,Swedish University of Agricultural Sciences,Uppsala,Sweden;7.Wexford County Council,Wexford,Ireland |
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Abstract: | Achieving an operational compromise between spatial coverage and temporal resolution in national scale river water quality monitoring is a major challenge for regulatory authorities, particularly where chemical concentrations are hydrologically dependent. The efficacy of flow-weighted composite sampling (FWCS) approaches for total phosphorus (TP) sampling (n?=?26–52 analysed samples per year), previously applied in monitoring programmes in Norway, Sweden and Denmark, and which account for low to high flow discharges, was assessed by repeated simulated sampling on high resolution TP data. These data were collected in three research catchments in Ireland over the period 2010–13 covering a base-flow index range of 0.38 to 0.69. Comparisons of load estimates were also made with discrete (set time interval) daily and sub-daily sampling approaches (n?=?365 to >1200 analysed samples per year). For all years and all sites a proxy of the Norwegian sampling approach, which is based on re-forecasting discharge for each 2-week deployment, proved most stable (median TP load estimates of 87–98%). Danish and Swedish approaches, using long-term flow records to set a flow constant, were only slightly less effective (median load estimates of 64–102% and 80–96%, respectively). Though TP load estimates over repeated iterations were more accurate using the discrete approaches, particularly the 24/7 approach (one sample every 7 h in a 24 bottle sampler - median % load estimates of 93–100%), composite load estimates were more stable, due to the integration of multiple small samples (n?=?100–588) over a deployment. |
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