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  • 1
    Electronic Resource
    Electronic Resource
    WQSTAT II: A WATER QUALITY STATISTICS PACKAGE (1989)
    Oxford, UK : Blackwell Publishing Ltd
    Ground water 27 (1989), S. 0 
    Details
    ISSN: 1745-6584
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geosciences
    Notes: Abstract. Statistical analysis of monitoring data is becoming a necessary part of many ground- and surface-water quality management activities. To meet this need a statistical software package for microcomputers called WQStat II has been designed and produced specifically for water quality applications. The software provides tools for data management, summarizing data characteristics, analyzing trends, comparing medians of two or more groups of data, and evaluating excursions or standards violations. To minimize problems associated with nonnormal data and nondetects, WQStat relies primarily on graphical and nonparametric approaches.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1745-6584.1989.tb01050.x
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    SAMPLING FREQUENCY SELECTION FOR REGULATORY WATER QUALITY MONITORING (1980)
    Oxford, UK : Blackwell Publishing Ltd
    Journal of the American Water Resources Association 16 (1980), S. 0 
    Details
    ISSN: 1752-1688
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Notes: : The selection of sampling frequencies in order to achieve reasonably small and uniform confidence interval widths about annual sample means or sample geometric means of water quality constituents is suggested as a rational approach to regulatory monitoring network design. Methods are presented for predicting confidence interval widths at specified sampling frequencies while considering both seasonal variation and serial correlation of the quality time series. Deterministic annual cycles are isolated and serial dependence structures of the autoregressive, moving average type are identified through time series analysis of historic water quality records. The methods are applied to records for five quality constituents from a nine-station network in Illinois. Confidence interval widths about annual geometric means are computed over a range of sampling frequencies appropriate in regulatory monitoring. Results are compared with those obtained when a less rigorous approach, ignoring seasonal variation and serial correlation, is used. For a monthly sampling frequency the error created by ignoring both seasonal variation and serial correlation is approximately 8 percent. Finally, a simpler technique for evaluating serial correlation effects based on the assumption of AR(1) type dependence is examined. It is suggested that values of the parameter p1, in the AR(1) model should range from 0.75 to 0.90 for the constituents and region studied.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1752-1688.1980.tb03904.x
    Library Location Call Number Volume/Issue/Year Availability
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    Paper (German National Licenses)
    Fulltext
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