Monitoring Coastal Water Body Health with Sentinel-2 MSI Imagery

The Australian New South Wales Estuary health assessment and biodiversity monitoring program' has set state-wide targets for estuary health. A selection of water bodies is being monitored by in situ chlorophyll a concentration and turbidity measurements, indicators for water quality. We investigate whether the current monitoring program can benefit from the use of remote sensing derived data, analyzing chlorophyll a and water clarity estimates by the C2RCC and ACOLITE products based on Sentinel-2 MSI imagery for three lakes along the New South Wales coast. The C2RCC and ACOLITE products were partly successful in predicting chlorophyll a concentration and water clarity. Estimates based on Sentinel-2 MSI imagery were in the range of in situ measurements. However, results varied across years and lakes, and a significant correlation could not be found in every case. It is likely that the physical differences between the systems, such as nutrient input, tannins, and suspended algae/sediment matrix, influence the output of the algorithm. This may preclude the application of a one size fits all' monitoring approach, given the importance of local ecological phenomena in both influencing remote sensing observations and the nature of appropriate targets. However, the design of a monitoring program that incorporates remote sensing provides a way forward.

Automated summary

The Australian New South Wales Estuary health assessment and biodiversity monitoring program has set state-wide targets for estuary health. In this study, the use of remote sensing derived data for monitoring water quality indicators in selected lakes along the coast was investigated. The results showed that the remote sensing products were partly successful in predicting chlorophyll a concentration and water clarity, but varied across years and lakes. It is likely that the physical differences between the systems influence the algorithm's output, suggesting the need for a tailored monitoring approach.