The information content of high-frequency environmental monitoring data signals pollution events in the coastal ocean.

There are an increasing number of coastal ocean observing systems that deploy new technology for environmental sensing and stream these data in near-real-time to end-users (e.g., scientists and coastal managers) via the worldwide web. The temporal resolution, spatial coverage, and accessibility of these data open up new opportunities for better understanding and managing the coastal ocean, but they also present enormous challenges relative to data processing and data interpretation, particularly in cases where these data are to inform rapid management decision making. Here we demonstrate that changes in surf zone water quality at a popular beach in southern California are signaled by changes in the Fisher Information and Shannon Entropy of high frequency (1/4 min(-1)) measurements of salinity and temperature in the surf zone. These results support the hypothesis that the information content of environmental signals, such as salinity and temperature, can be used to identify changes in the water quality of the coastal ocean. More generally, the approach described here-of using information theory indices calculated from monitoring data as real-time indicators of environmental change-is quite general, and may therefore be applicable to other situations where rapid management decisions are based on high-frequency measurements of environmental parameters.