The promise and pitfalls of monitoring harmful algal blooms (HABs) with remote sensing in pond-sized waterbodies

Abstract

Harmful algal blooms (HABs) pose water quality risks, including the depletion of dissolved oxygen and human health impacts. Remote sensing is a proven tool for monitoring HABs, yet knowledge is limited about its effectiveness in pond-sized waterbodies, whose size and shape may preclude multi-spectral platforms with large spatial resolutions and increase the probability of mixed pixels. This comparative limnology case study evaluates whether optical remote sensing is a viable tool to monitor HABs in pond-sized waterbodies. We use Sentinel-2 imagery with previously studied chlorophyll-a and cyanobacteria detection algorithms and performed targeted in situ sampling in four small waterbodies in Boulder, CO, USA, from June to August 2021 to validate the algorithms and better understand underlying biogeochemical processes. The chlorophyll-a algorithm indicated persistent algal growth occurred in all waterbodies, yet only Sombrero Marsh chlorophyll-a expressed a statistically significant relationship with the remote sensing output ( p < 0.0005, r 2 = 0.80). Meanwhile, the cyanobacteria algorithm resulted in false negatives, only showing potential cyanobacteria at Sombrero Marsh despite in situ samples from all waterbodies indicating cyanobacteria were present. Samples from Sombrero Marsh had the highest chlorophyll-a (average = 132.5 µg/L) and percent cyanobacteria (average = 43.5%). These findings suggest that there is uncertainty in relying on remote sensing for monitoring HABs in small waterbodies unless a high concentration of algae is present on the water surface. However, in a resource- and time-limited system, remote sensing can be a useful tool as an initial assessment for monitoring algal blooms.

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