Harmful algal blooms have negatively affected the aquaculture industry and aquatic ecosystems globally. Remote sensing using satellite sensor systems has been applied on large spatial scales with high temporal resolutions for effective monitoring of harmful algal blooms in coastal waters. However, oceanic color satellites have limitations, such as low spatial resolution of sensor systems and the optical complexity of coastal waters. In this study, bands 1 to 4, obtained from Landsat-8 Operational Land Imager satellite images, were used to evaluate the performance of empirical ocean chlorophyll algorithms using machine learning techniques. Artificial neural network and support vector machine techniques were used to develop an optimal chlorophyll-a model. Four-band, four-band-ratio, and mixed reflectance datasets were tested to select the appropriate input dataset for estimating chlorophyll-a concentration using the two machine learning models. While the ocean chlorophyll algorithm application on Landsat-8 Operational Land Imager showed relatively low performance, the machine learning methods showed improved performance during both the training and validation steps. The artificial neural network and support vector machine demonstrated a similar level of prediction accuracy. Overall, the support vector machine showed slightly superior performance to that of the artificial neural network during the validation step. This study provides practical information about effective monitoring systems for coastal algal blooms.

We evaluated changes in the phytoplankton community in Korean coastal waters during October 2016 and February 2017. Typhoon Chaba introduced a large amount of freshwater into the coastal areas during autumn 2016, and there was a significant negative relationship between salinity and nutrients in the Nakdong estuarine area, particularly in the northeastern area (Zone III; p < 0.001). The abundance of diatom species, mainly Chaetoceros spp., increased after this nutrient loading, whereas Cryptomonas spp. appeared as opportunists when there was relatively low diatom biomass. During winter, biotic and abiotic factors did not differ among the surface, middle, and lower layers (p > 0.01; ANOVA), implying that water mixing by winter windstorms and low surface temperature (due to the sinking of high-density water) physically accelerated mixing of the whole water column. Diatoms predominated under these conditions. Among diatoms, the centric diatom Eucampia zodiacus remained at high density at the inshore area and its abundance had a negative correlation with water temperature, implying that this species can grow at cold temperatures. On the other hand, the harmful freshwater diatom Stephanodiscus hantzschii mainly appeared in conditions with low salinity and high nutrients, implying that it can persist even in the saltwater conditions of the Nakdong Estuary. Our results indicate that hydro-oceanographic characteristics, such as river discharge after an autumn typhoon and winter water turbulence, have major effects on the composition of phytoplankton communities and can potentially affect the occurrence and characteristics of harmful algal blooms in southern Korean coastal waters.

Multiple environmental variables related to ocean currents, freshwater runoff, and upwelling in a coastal area have complex effects on the phytoplankton community. To assess the influence of environmental variables on the phytoplankton community structure during the summer of 2019, we investigated the various abiotic and biotic factors in Korean coastal waters (KCWs), separated into five different zones. Summer environmental factors in KCWs were strongly influenced by Changjiang Diluted Water (CDW) in St. SO (Southern Offshore) 1 and 2, upwelling in St. SI (Southern Inshore) 2–4, and Nakdong River discharge in St. SI 12. In particular, low–salinity water masses (p < 0.05 for nearby locations) of CDW gradually expanded from the East China Sea to southwestern KCWs from June to July. In addition, there were high levels of nutrients following freshwater runoff from the Nakdong River in southeastern KCW, which led to the dominance of Cryptomonas spp. (81%), a freshwater and brackish water algae. On the other hand, upwelling areas in southwestern KCW were dominated by diatoms Skeletonema spp., and are characterized by high phosphate concentrations (p < 0.05) and low temperatures (p < 0.05) compared to nearby locations. Leptocylindrus danicus (20%) was dominant due to the effect of water temperature in the SE (Southeastern area) zone. Low nutrient concentrations were maintained in the East Sea (dissolved inorganic nitrogen (DIN) = 0.39 ± 0.40 μM; dissolved inorganic phosphate (DIP) = 0.09 ± 0.03 μM) and the Yellow Sea (DIN = 0.40 ± 0.07 μM; DIP = 0.04 ± 0.02 μM), which were characterized by low levels of chlorophyll a and dominated by unidentified small flagellates (35, 40%). Therefore, our results indicated that hydro–oceanographic events such as upwelling and freshwater run–off, but not ocean currents, provide nutrients to the euphotic layers of the coastal environment and play important roles in determining the phytoplankton community structure during summer in the KCWs.