Use of probability-based sampling of water-quality indicators in supporting development of quality criteria

• Published in: ICES journal of marine science Vol. 65; no. 8; pp. 1421 - 1427
• Main Authors: Nelson, Walter G., Brown, Cheryl A.
• Format: Journal Article
• Language: English
• Published: Oxford University Press 01.11.2008
• Subjects: Adjustment; Criteria; Estuaries; Extrapolation; Indicators; Marine; National Coastal Assessment; probability-based sampling; Regional; regional water quality; Sampling; upwelling; water quality criteria; water quality indicators; INE, USA, Oregon, Yaquina Bay; INE, USA, Oregon; National Coastal Assessment; regional water quality; water quality indicators; upwelling; water quality criteria; probability-based sampling
• DOI: 10.1093/icesjms/fsn158
• ISSN: 1054-3139

Nelson, W. G., and Brown, C. A. 2008. Use of probability-based sampling of water-quality indicators in supporting development of quality criteria. – ICES Journal of Marine Science, 65: 1421–1427.Intensive, site-based data are typically used to establish protective water-quality criteria, but may only exist for few systems in a region. We examine whether or not water-quality indicator data collected from large-scale, probability-based assessments can support the development of regional quality criteria. Because such indicators may be subject to high natural variation over short time-scales, a key question is whether survey values will be sufficiently similar to site-based sampling to merit use in extrapolating quality criteria spatially. Median values for dissolved inorganic nitrogen, phosphorus, and Chl a for dry-season data collected within Yaquina Bay (OR, USA) over a 7-year period were compared with dry-season datasets collected from two studies comprising 6 and 14 Oregon estuaries, respectively. A second, reduced dataset (August–September only) was compared with data from 38 estuaries within the same ecoregion. All comparisons were made for marine and riverine salinity zones. Medians for Yaquina Bay were higher than those from the comparison surveys. Stochastic variation of coastal upwelling during sampling appears to cause the contrasts. Further work is required to define upwelling-based adjustments for regional, probability-based survey data before they can be used in regulatory applications. However, even without adjustment, these data may help in determining the appropriate regional context for quality criteria.