25 May 2018 Interannual variability in the Indian River Lagoon, Florida, measured by a network of environmental sensors
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Abstract
The Indian River Lagoon Observatory (IRLO) is investigating ecological relationships in the Indian River Lagoon (IRL) and how they are impacted by natural and human-induced stressors. An important IRLO component is a network of advanced observing stations: the Indian River Lagoon Observatory Network of Environmental Sensors (IRLON). IRLON has 10 sites in the IRL and St. Lucie Estuary (SLE) to provide real-time, high-accuracy, and high-resolution water quality and weather data through an interactive website. This network enables researchers to follow environmental changes in the IRL, assist resource and planning managers to make informed decisions, model and correlate environmental data to biological, chemical and physical phenomena, and contribute to education and public outreach on the lagoon. Here we contrast two years of water quality conditions in the IRL and SLE. 2016 was a very “wet” year, including nine months of freshwater releases from Lake Okeechobee, which resulted in cyanobacteria blooms, and the nearby passage of Hurricane Matthew, which caused much shorter-term impacts in water quality. 2017 was a “dry” year, a significant drought early in the year, and major water quality parameters were substantially different than in 2016, until the nearby passage of Hurricane Irma. These high-frequency, continuous observatory data enable better quantification and modeling of relationships between environmental factors and biological processes in estuaries with tremendous climate-related interannual variability. This technology enables scientists, managers, educators, students, and the public to directly observe both long-term ecosystem changes and those driven by events, such as freshwater discharges, droughts, storms, and algal blooms.
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M. Dennis Hanisak, Kristen S. Davis, "Interannual variability in the Indian River Lagoon, Florida, measured by a network of environmental sensors", Proc. SPIE 10631, Ocean Sensing and Monitoring X, 106310A (25 May 2018); doi: 10.1117/12.2304609; https://doi.org/10.1117/12.2304609
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