As water quality evaluations continue to expand in number of analytes and frequency of measurements, a challenge arises as how to present these data in a manner that can best be used to guide remedial actions and inform water resource decisions. Graphic artists have developed visualization techniques using colors, textures and layers that enhance people’s accessibility to and understanding of data. However, beyond just visual data enhancement, the use of hierarchically arranged spatial patterns or sequentially arranged temporal patterns can provide a means of discerning trends, anomalies and correlations among water quality parameters that would otherwise be difficult to distinguish. A related approach includes comparing actual water quality patterns with either ideal patterns (generated by models) or abstract patterns (created from theories) as a check on their practicality and relevance to the observed datasets. Finally, assessing the connectivity of water quality patterns as a coherent network, rather than as isolated data points, can expose potential feedback loops, counterintuitive or disproportionate effects, and data limitations. Pattern connectivity is also consistent with a systems interpretation of water quality, which may reveal subtle interactions among the water quality components or parameters. Perhaps the greatest advantage of pattern-based approaches is their usefulness to non-scientists (e.g., managers, stakeholders), who often misinterpret or are confused by the language, symbols, mathematics, and graphics appearing in technical reports and journal articles.