Coastal, benthic communities, such as coral reefs, are at particular risk due to poor water quality caused by hurricanes. In addition to the physical impacts from wave action and storm surge, hurricanes bring significant rainfall resulting in increased runoff from land. Hurricanes Irma and Maria caused record or near-record floods at many locations across Puerto Rico and resulted in major impacts on coastal and benthic ecosystems from heavy rainfall and river discharge. In this study, we use imagery from the moderate resolution Visible Infrared Imaging Radiometer Suite (VIIRS) satellite to quantify the impacts of hurricanes Irma and Maria, which struck Puerto Rico during September 2017, on the water quality of the coastal waters of Puerto Rico using the chlorophyll-a (Chl-a) and the diffuse attenuation coefficient at 490 nm (K_d490) products. The objectives include: (1) quantify the water quality and light attenuation after the hurricanes; (2) compare this event to the climatology of these parameters, and 3) evaluate long-term exposure and exceedances of various coastal areas to low levels of turbidity. The Chl-a inner shelf values increased in 2017 during the months of June (8% above baseline), July (17%), August (5%), September (8%), October (19%), and November (28%) when compared to 2012–2016 baseline data. The values for Chl-a concentration reached and exceeded 0.45 µg/L by August 2017 and persisted above that value until December 2017. The K_d490 inner shelf values for 2017 increased (in percent) for the months of June (4% above baseline), July (9%), August (10%), September (5%), October (12%), and November (7%) when compared to 2012–2016 baseline data. The values of K_d490 in August, September, and December 2017 were the highest seen during 2012–2017. Even with the limitations of spatial resolution and loss of data to cloud cover, the 6-year imagery time-series analysis can provide a useful evaluation of the effects of these two hurricanes on the coastal water quality in Puerto Rico, and quantify the exposure of benthic habitats to higher nutrient and turbidity levels.

Hyperspectral remote sensing reflectance was measured for a series of phytoplankton cultures as the first step in determining major taxon in an algal bloom by remote sensing. Two common bloom-forming species: Dinophyta, the dinoflagellate Prorocentrum minimum, and Cyanophyta, the cyanobacteria Synechococcus sp. were grown as mono cell cultures. Optical spectral measurements were taken from the cultures during logarithmic growth phases with progressive dilutions and culture mixtures. The primary objective of this study was to obtain base line reflectance spectra which can be used as references for remote sensing of algal blooms. Furthermore, the derivative analysis was applied to the reflectance spectra to explore the spectral features that can be used to identify phytoplankton taxon. Results showed that spectral reflectance correlated with phytoplankton biomass. Applying mathematical operators to the spectra of mono cell cultures corresponded to observed spectra of culture mixtures. Our results further corroborate previous findings that for some cases, remote sensing reflectance (Rrs) can be used to identify the primary taxon in algal blooms