Quantifying Variability in Four US Streams Using a Long-Term Data Set: Patterns in Water Quality Endpoints.

Temporal and spatial patterns of variability in aquatic ecosystems can be complex and difficult to quantify or predict. However, understanding this variability is critical to making a wide range of water quality assessment and management decisions effectively. Here we report on the nature and magnit...

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Publicado en:Environmental Management Vol. 57; no. 2; pp. 368 - 389
Autores principales: McLaughlin, Douglas, Flinders, Camille
Formato: Journal Article
Publicado: Springer Nature Feb2016
Acceso en línea:Ver este registro en EBSCOhost
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          McLaughlin, Douglas
          Flinders, Camille
        affil: National Council for Air and Stream Improvement, A-114 Parkview Campus, Western Michigan University Kalamazoo 49008 USA
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      ab: Temporal and spatial patterns of variability in aquatic ecosystems can be complex and difficult to quantify or predict. However, understanding this variability is critical to making a wide range of water quality assessment and management decisions effectively. Here we report on the nature and magnitude of spatial and temporal variation observed in conductivity, total phosphorus, and total nitrogen during a 15-year study of four US stream systems receiving pulp and paper mill effluent discharges. Sampling locations included mainstem sites upstream and downstream of effluent discharge, as well as tributary sites. In all four stream systems, variability in conductivity as measured by the coefficient of variation was typically in the range of 10-50 %, and was as low or lower than the variability in nutrient endpoints. The effect of effluent discharge was relatively minor overall, except in some site-specific instances. Some relatively large differences between tributary and mainstem variability were also observed. Flow variation tended to have a more consistent and larger effect on conductivity variation compared to the nutrient endpoints. After removing flow effects, significant relatively complex trends over time were observed at several sites. Changes in variability during the study also were observed. This paper highlights the importance of long-term studies to accurately characterize water quality variability used in water quality management decision-making.
      pubtype: Academic Journal
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    language: English
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