Correction of stream quality trends for the effects of laboratory measurement bias

Alexander, Richard B.; Smith, Richard A.; Schwarz, Gregory E.

doi:10.1029/93wr01708

Cited by 7 publications

(3 citation statements)

References 21 publications

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“…For new applications of meta-analysis, Monte Carlo simulations should be conducted to verify the expected behavior of the statistical results. Even minor changes or bias in analytical methods or technique may be detected as a trend in the data and it is important to ask if the quality control is sufficient to detect small changes over time, above and beyond that due to bias (Alexander et al, 1993). For example, if the long term errors (bias) of chemical analyses during the course of the study is on the order of 10 #eq/L, then over a ten year survey the realistic limit of detection for trends is about 1 #eq/L/year.…”

Section: Meta-analysis and Skt Powermentioning

confidence: 99%

Evidence of recovery from acidification in Massachusetts streams

Mattson

Godfrey

Walk

et al. 1997

Water Air Soil Pollut

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Abstract. A ten year survey of water quality in 330 Massachusetts streams was conducted to examine the rate and pattern of recovery from acidification. Meta-analysis was used to combine the results of the 330 non-parametric trend tests into an overall test for trend in a variety of water quality variables including pH, acid neutralizing capacity (ANC), and major inorganic ions. Analysis of trends in the raw data indicates both pH and ANC are increasing. After detrending for variations in stream runoff, we estimate the streams are recovering from acidification at a rate of +0.021 pH units/year and +2.4 tteq/L/year, for pH and ANC respectively. These trends appear to be related to declines in sulfate (-1.8 iLeq/L/year), while base cation trends were mixed. Meta-analysis reveals the trends are not always homogeneous between seasons or between sites.While it is commonly assumed that the low ANC systems are most "sensitive' to changes in acid or base inputs, we found the greatest rates of change in ANC were associated with the high ANC systems. The greatest increases in pH were seen in the low ANC streams as expected. The results also suggest streams respond quickly to changes in precipitation inputs and stream monitoring networks may be valuable as an early detection technique for changes in environmental quality.

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Section: Meta-analysis and Skt Powermentioning

confidence: 99%

Evidence of recovery from acidification in Massachusetts streams

Mattson

Godfrey

Walk

et al. 1997

Water Air Soil Pollut

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“…There is a welldeveloped literature on assessing systematic and random errors on the analysis of trends (e.g. Gilbert, 1987;Alexander et al, 1993;McBride and Smith, 1997). A recent work of Moosmann et al (2005) described how to determine the number of annual samples required to detect trends in nutrient load, depending on monitoring duration, available resources, and the magnitude of the expected trend.…”

Section: Discussionmentioning

confidence: 99%

Uncertainties in selected river water quality data

Rode

Suhr

2007

Hydrol. Earth Syst. Sci.

103

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Abstract.Monitoring of surface waters is primarily done to detect the status and trends in water quality and to identify whether observed trends arise from natural or anthropogenic causes. Empirical quality of river water quality data is rarely certain and knowledge of their uncertainties is essential to assess the reliability of water quality models and their predictions. The objective of this paper is to assess the uncertainties in selected river water quality data, i.e. suspended sediment, nitrogen fraction, phosphorus fraction, heavy metals and biological compounds. The methodology used to structure the uncertainty is based on the empirical quality of data and the sources of uncertainty in data (van Loon et al., 2005). A literature review was carried out including additional experimental data of the Elbe river. All data of compounds associated with suspended particulate matter have considerable higher sampling uncertainties than soluble concentrations. This is due to high variability within the cross section of a given river. This variability is positively correlated with total suspended particulate matter concentrations. Sampling location has also considerable effect on the representativeness of a water sample. These sampling uncertainties are highly site specific. The estimation of uncertainty in sampling can only be achieved by taking at least a proportion of samples in duplicates. Compared to sampling uncertainties, measurement and analytical uncertainties are much lower. Instrument quality can be stated well suited for field and laboratory situations for all considered constituents. Analytical errors can contribute considerably to the overall uncertainty of river water quality data. Temporal autocorrelation of river water quality data is present but literature on general behaviour of water quality compounds is rare. For meso scale river catchments (500-3000 km 2 ) reasonable yearly dissolved load calculations can be achieved using biweekly sample frequencies. For suspended sediments none of the methods invesCorrespondence to: M. Rode (michael.rode@ufz.de) tigated produced very reliable load estimates when weekly concentrations data were used. Uncertainties associated with loads estimates based on infrequent samples will decrease with increasing size of rivers.

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“…Example uses of the data include the analysis of trends in water quality [Smith et al, 1987;Schertz, 1990;Hay and Campbell, 1990;Lettenmaier et al, 1991], the estimation of rates of chemical flux from major watersheds [Smith et al, 1993;Alexander et al, 1996a], and the investigation of relations of water quality to streamflow [Smith et al, 1982], climatic, physiographic, and geologic factors [Biesecker and Leifeste, 1975;Peters, 1984;Lucey and Goolsby, 1993;Alexander et al, 1996a;Clow et al, 1996], and anthropogenic pollutant sources, such as agricultural fertilizers, livestock wastes, atmospheric deposition, and wastewater discharges from sewage treatment plants [Smith and Alexander, 1986;Kramer et al, 1986;Smith et al, 1987;Crawford and Wangsness, 1991;Smith et al, 1993Smith et al, , 1997. The data have also served as baseline information for developing and illustrating many statistical methods for analyzing water resources data [Hirsch et al, 1982;Hirsch and Slack, 1984;Helsel and Gilliom, 1986;Helsel and Cohn, 1988;Hirsch et al, 1991;Alexander et al, 1993;Smith et al, 1997]. The data should provide excellent support for developing and evaluating new statistical methods for interpreting water quality and quantity data, especially methods that can be applied at the regional and national levels.…”

Section: Introductionmentioning

confidence: 99%

Data from selected U.S. Geological Survey national stream water-quality monitoring networks (WQN) on CD-ROM

Alexander¹,

Slack²,

Ludtke³

et al. 1996

Open-File Report

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A nationally consistent and well-documented collection of water quality and quantity data compiled during the past 30 years for streams and rivers in the United States is now available on CD-ROM and accessible over the World Wide Web. The data include measurements from two U.S. Geological Survey (USGS) national networks for 122 physical, chemical, and biological properties of water collected at 680 monitoring stations from 1962 to 1995, quality assurance information that describes the sample collection agencies, laboratories, analytical methods, and estimates of laboratory measurement error (bias and variance), and information on selected cultural and natural characteristics of the station watersheds. The data are easily accessed via user-supplied software including Web browser, spreadsheet, and word processor, or may be queried and printed according to user-specified criteria using the supplied retrieval software on CD-ROM. The water quality data serve a variety of scientific uses including research and educational applications related to trend detection, flux estimation, investigations of the effects of the natural environment and cultural sources on water quality, and the development of statistical methods for designing efficient monitoring networks and interpreting water resources data.

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Correction of stream quality trends for the effects of laboratory measurement bias

Cited by 7 publications

References 21 publications

Evidence of recovery from acidification in Massachusetts streams

Evidence of recovery from acidification in Massachusetts streams

Uncertainties in selected river water quality data

Data from selected U.S. Geological Survey national stream water-quality monitoring networks (WQN) on CD-ROM

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