Use of CUSUM methods for water-quality monitoring in storages

R. Mac Nally, B.T. Hart

    Research output: Contribution to journalArticle

    18 Citations (Scopus)

    Abstract

    There is a variety of methods used for monitoring environmental variables for the detection of ‘unacceptable' levels, such as for compliance conditions. In this paper, we consider the utility of a statistical technique used for many years in industrial process controlcumulative sum or CUSUMin monitoring water-quality trends within large storages such as reservoirs. By using simulations and realistic values for total phosphorus concentrations, we show the sensitivity of CUSUM schemes to six kinds of trends in quality through time. The six trends are as follows:  (a) on target; (b) off target; (c) midpoint (halfway between a and b); (d) ramping change (increasing from a to b over 5 years); (e) weakly autocorrelated series; and (f) strongly autocorrelated series. We study the performance of the CUSUM method in relation to ‘average run lengths' (ARLs) before a warning is triggered and the probabilities of spurious warnings (type-I statistical errors) or failing to detect changes in water quality that are deemed to be unsatisfactory. We conclude that in reasonably buffered systems, such as large storages, the CUSUM technique may be a potentially important way of monitoring water quality that also permits rapid response to serious increases in nutrient concentrations.
    Original languageEnglish
    Pages (from-to)2114-2119
    Number of pages6
    JournalEnvironmental Science and Technology
    Volume31
    Issue number7
    DOIs
    Publication statusPublished - 1997

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    Water quality
    water quality
    Monitoring
    monitoring
    environmental monitoring
    Phosphorus
    Nutrients
    compliance
    phosphorus
    nutrient
    simulation
    method
    trend
    detection
    industrial process
    Compliance

    Cite this

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    title = "Use of CUSUM methods for water-quality monitoring in storages",
    abstract = "There is a variety of methods used for monitoring environmental variables for the detection of ‘unacceptable' levels, such as for compliance conditions. In this paper, we consider the utility of a statistical technique used for many years in industrial process controlcumulative sum or CUSUMin monitoring water-quality trends within large storages such as reservoirs. By using simulations and realistic values for total phosphorus concentrations, we show the sensitivity of CUSUM schemes to six kinds of trends in quality through time. The six trends are as follows:  (a) on target; (b) off target; (c) midpoint (halfway between a and b); (d) ramping change (increasing from a to b over 5 years); (e) weakly autocorrelated series; and (f) strongly autocorrelated series. We study the performance of the CUSUM method in relation to ‘average run lengths' (ARLs) before a warning is triggered and the probabilities of spurious warnings (type-I statistical errors) or failing to detect changes in water quality that are deemed to be unsatisfactory. We conclude that in reasonably buffered systems, such as large storages, the CUSUM technique may be a potentially important way of monitoring water quality that also permits rapid response to serious increases in nutrient concentrations.",
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    Use of CUSUM methods for water-quality monitoring in storages. / Mac Nally, R.; Hart, B.T.

    In: Environmental Science and Technology, Vol. 31, No. 7, 1997, p. 2114-2119.

    Research output: Contribution to journalArticle

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    AU - Mac Nally, R.

    AU - Hart, B.T.

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    AB - There is a variety of methods used for monitoring environmental variables for the detection of ‘unacceptable' levels, such as for compliance conditions. In this paper, we consider the utility of a statistical technique used for many years in industrial process controlcumulative sum or CUSUMin monitoring water-quality trends within large storages such as reservoirs. By using simulations and realistic values for total phosphorus concentrations, we show the sensitivity of CUSUM schemes to six kinds of trends in quality through time. The six trends are as follows:  (a) on target; (b) off target; (c) midpoint (halfway between a and b); (d) ramping change (increasing from a to b over 5 years); (e) weakly autocorrelated series; and (f) strongly autocorrelated series. We study the performance of the CUSUM method in relation to ‘average run lengths' (ARLs) before a warning is triggered and the probabilities of spurious warnings (type-I statistical errors) or failing to detect changes in water quality that are deemed to be unsatisfactory. We conclude that in reasonably buffered systems, such as large storages, the CUSUM technique may be a potentially important way of monitoring water quality that also permits rapid response to serious increases in nutrient concentrations.

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