H. Wu, L. Zhang (PRC), H. Feng, and J. Murphy (USA)
Assessing methods, Monitoring Data, Seawater quality.
Seawater quality assessment is an essential part of marine environmental management. With the advances in automated monitoring technology, more and more automated seawater monitoring equipments are being used in China, and massive data from marine monitoring station have been generated. However, so far only maximum, minimum and average values have been calculated from these data. These summary statistical measures make it difficult to assess and accurately present the complexity of seawater quality. We describe a new methodology for the rapid and efficient analysis of large data sets collected via automated seawater monitoring stations. A comparison among the Index Method, Probability Statistic Method, Set Pair Analysis Method, Matter Element Analysis Method, and Excel software was developed to evaluate their suitability for analyzing automated monitoring data. The findings are that, for those monitoring parameters in the Chinese National Seawater Quality Standard (NSQS), Excel Software conditional command was used directly to treat and analyze the data. For those monitoring parameters not in the Chinese NSQS, a combination of the Probability Statistic Method and Excel software with the “Describe Statistic” Command were employed. Excel software and Probability Statistic method combined were found to be an effective way to assess seawater quality using massive data sets. These two methods are flexible, simple, rapid, and make more efficient use of the power of automated systems to collect large quantities of data. Further, the output can be tailored to better meet the needs of different user group(s) for the information about seawater quality.
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