Role of data analysis methods selection and documentation in producing comparable information to support water quality management

2000 Spring.Includes bibliographic references (pages 106-115).Water quality monitoring is being used in local, regional, and national scales to measure how water quality variables behave in the natural environment. A common problem, which arises from monitoring, is how to relate information contained in data to the information needed by water resource management for decision-making. This is accomplished through analysis of the monitoring data. However, how the selection of methods with which to analyze the data impacts the quality and comparability of information produced is not well understood. To help understand the connectivity between data analysis methods selection and the information produced to support management, the following tasks were performed: (1) examined the data analysis methods that are currently being used to analyze water quality monitoring data, as well as the criticisms of using those types of methods; (2) explored how the selection of methods to analyze water quality data can impact the comparability of information used for water quality management purposes, and; (3) developed options by which data analysis methods employed in water quality management can be made more transparent and auditable. These tasks were accomplished through a literature review of texts, guidance and journals related to water quality. Then, the common analysis methods found were applied to the New Zealand Water Quality River Network data set. The purpose of this was to establish how information changes as analysis methods change, and to determine if the information produced from different analysis methods is comparable. The results of the literature review and data analysis were then discussed and recommendations made addressing problems with current data analysis procedures, and options through which to begin solving these problems and produce better information for water quality management. It was found that significance testing is the most popular method through which to produce information, yet assumptions and hypotheses are loosely explained and alternatives rarely explored to determine the validity and comparability of the results. Other data analysis methods that might be more appropriate for producing more comparable information were discussed, along with recommendations for further research and cooperative efforts to establish water quality data analysis protocols for producing information for management