Satellite ocean color based harmful algal bloom indicators for aquaculture decision support in the southern Benguela

Abstract

The aquaculture industry of southern Africa faces environmental threats from harmful algal blooms (HABs), which have the potential to cause devastating economic losses (Pitcher et al., 2019). Satellite earth observation offers a systematic and cost effective method for operational monitoring of HABs over large areas. Whilst the chlorophyll-a concentration ([Chl-a]) product, often used as a proxy for phytoplankton biomass, can be used to indicate high biomass blooms (elevated biomass against a background signal of 5–10 mgChl m-3), there is a clear need for value-added products that not only alert on bloom presence, but also on the bloom type and persistence. This study demonstrates the identification of different phytoplankton communities that can feasibly be identified in bloom concentrations from space, relevant to the aquaculture industry of South Africa. In terms of water-leaving reflectance, 76 % of the variance in the red and NIR spectral region is significantly positively correlated to phytoplankton abundance, [Chl-a], and the maximum line height (MLH) (defined as the height of the maximum reflectance peak above a baseline between 665 and 753 nm). The MLH is related to dominant phytoplankton types derived from phytoplankton count data, in order to identify thresholds which represent blooms that pose a high hypoxia and/or toxicity risk; whilst 0.0016 < MLH < 0.003 represent low to moderate concern mixed assemblage blooms, MLH > 0.003 has a strong likelihood of indicating high biomass dinoflagellate or Pseudo-nitzschia blooms. These techniques are routinely used by the aquaculture industry in South Africa for decision support and risk mitigation. The high biomass nature of the South African regional waters provide strong assemblage-related spectral variability, which can be exploited with the spectral bands of OLCI and MERIS. Application to these sensors not only ensures future monitoring capability, but also allows the creation of a historical risk climatology that can guide the site selection of industries sensitive to the presence of HABs, such as aquaculture facilities and desalination plants.