Determining chlorophyll-a thresholds for characterizing algal bloom conditions: An ocean colour remote sensing...

The Indian coast has been experiencing an increase in algal bloom events over the decades. Owing to the regional and seasonal dynamics of algal biomass (proxy: chlorophyll-a, hereafter chl-a), a multitude of thresholds of chl-a has been defined for different parts of the global seas to determine algal bloom conditions. However, no such clear definition is given for the Indian coastal waters. The current study defined chl-a thresholds to demarcate algal bloom conditions for the coastal waters of India, accounting for the variability at hotspots (in accordance with reported events: secondary data), causative species, and satellite-retrieved long-term trends. The secondary data analysis identified nine bloom hotspots along the east and west coasts of India. Among the blooms, diatoms prevailed the most, compared to dinoflagellates and cyanobacteria. Quartile analysis was employed on satellite-retrieved daily chl-a anomaly to determine specific bloom thresholds. Consequently, these quartile thresholds were utilized to classify various bloom phases, such as the 25^th percentile (Likely to Bloom), 50^th percentile (Bloom), 75^th percentile (Intense Bloom), and 90^th percentile (Extreme Bloom). As per this percentile-based classification, the 'Bloom' category corresponds to a chl-a range of 0.89-0.94 mg m^-3 and 0.76-2.87 mg m^-3, for the identified hotspots along the east and west coasts, respectively. Likewise, during the 'Intense Bloom' phase, the chl-a concentration exceeds 0.99-1.47 and 1.12-4.46 mg m^-3 at the hotspots along the east and west coasts, respectively. The seasonality of blooms revealed an increasing trend during the pre-southwest monsoon period on the central east coast of India. On the west coast, significant upwelling during the southwest monsoon period has been substantiated to be conducive for blooms. This study provides an avenue towards utilization of the threshold criteria in detecting different phases of bloom using satellite data in coastal waters where field observations are limited due to various factors.