Kim, Tae-Woo, et al. 2017. “Convergence Technique Study on Red Tide Prediction in the Littoral Sea.” Journal of Coastal Research, 2017, 79: 254–258. JSTOR, www.jstor.org/stable/44289518. (Kim et al.  2017)

Harmful algal blooms (HABs) in the ocean cause “red tide”, which impairs the functionality of desalination plants because the microbial matter produces a lot of harmful chemicals that can continue to exist in water post-desalination. This research aims to discover how to reduce the impact of red tide on desalination plants by utilizing a convergence technique. In order to do so, reports of events must be collected, like tidal movements and concentrations of HABs. Most of this data is a combination of remote sensing, monitoring, and modeling, and it must be collected through public or private records, considering that much of that information is available from research by institutes like NOAA. Instead of relying solely on satellite imaging to determine where the HABs are, GIS specialists have started to superimpose the distributions of HABs on top of tidal prediction maps in order to track when and where desalination plants are at high risk of being affected by red tide. The data analysis in this study is the key difference to many research methods in the past, because the convergence of spatio-temporal techniques provides new insight into how to present the distributions of red tide in a new way. The greatest limitation of this technique was relying on satellite imagery in cloudy conditions, in which case it would be more difficult to accurately track the flow of red tide. Regardless, people that manage operations and maintenance of desalination plants will be able to use this technique to make clearer and more informed decisions about the desalination plant and be able to prepare for the impact of HABs in the future.