Abstract

An absorption-based approach was used to determine surface particulate organic carbon (POC) concentrations in both inland and coastal waters. The improved performance of this approach was based on the specification of local POC absorption characteristics based on dominant POC sources; phytoplankton or detritus based. This specification was made using a new POC-Index (PI), developed and tested across a range of POC (300–10,000 mg/m3) conditions in temporally and spatially heterogeneous inland and coastal waterbodies. The POC model was based on remote sensing reflectance (Rrs, sr−1) in four wavebands: Rrs(751), Rrs(488) and Rrs(R/G), where R is the red band [Rrs(672)] for detritus dominated waters and G is the green band [Rrs(555)] in the phytoplankton dominated waters. The model provided a high R2 (0.74) and relatively low rRMSE (42.0%, N = 136, p < 0.01). Validation with independent datasets from Chaohu Lake and the Yangtze River Estuary produced a larger positive bias (R2 = 0.59, rRMSE = 83%, δ = 634 mg/m3, S = 0.63, I = 1439 mg/m3); nevertheless, the bias was reduced when tuned with local data (R2 = 0.80, rRMSE = 45%, δ = 72 mg/m3, S = 0.81, I = 327 mg/m3). Additionally, HydroLight simulations presented an independent correlation between PI and CDOM conditions and reasonable POC estimates from the new approach developed in this study. The approach was tested using data from Visible Infrared Imaging Radiometer Suite (VIIRS) in a range of optically complex conditions to quantify carbon dynamics. We indicate the advantages and challenges of using this approach in ecosystems where multiple organic carbon sources are present.

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