Contrasting spatial and temporal patterns in chlorophyll-a and turbidity in Lake Okeechobee: A satellite perspective

Turbidity (Turb) and chlorophyll-a concentration (Chla) are important water quality indicators in aquatic ecosystems. While spatial and temporal patterns of Chla in the largest lake of Florida (USA), Lake Okeechobee (LO), are well documented, less is known about Turb in this lake. Here, for Ocean Colour and Land Imager (OLCI) imagery, an extreme gradient boost (XGB) model was developed and validated using in situ Turb measurements, showing RMSD (∼10 NTU) ∼50% lower than previously reported values. We estimated Turb distributions between 2016 and 2023, and showed contrasting spatial/temporal patterns between Turb OLCI (5–300 NTU) and Chla OLCI (5–200 mg m −3 ) determined from an existing model. Seasonally, Turb OLCI was typically higher in winter and Chla OLCI higher in summer. Spatially, Turb OLCI was generally higher in offshore regions and Chla OLCI was higher in nearshore regions except during major harmful algal bloom (HAB) events. Such contrasting spatial/temporal patterns, whereby high Chla OLCI was associated with low Turb OLCI and vice versa , are due to different mechanisms driving phytoplankton growth and sediment resuspension. While variability in Chla OLCI reflects biologically mediated processes influenced by light, temperature, and nutrient availability, Turb OLCI is regulated by bottom substrate type and wind-induced turbulence. A moderate correlation ( r ∼ 0.5) was found between wind speed and lake-wide Turb OLCI on a monthly scale. Turbidity limits light for submerged aquatic vegetation and HABs negatively affect this lake system, yet in situ monitoring is often insufficient to identify potentially harmful conditions in near-real time. Satellite-derived Turb OLCI and Chla OLCI time-series can help water management agencies make decisions to better safeguard the environment, public health, and local economies. • Machine learning reduces RMSD for satellite turbidity in Lake Okeechobee by 50%. • OLCI turbidity and chlorophyll-a reveal contrasting spatiotemporal patterns. • Winds are moderately correlated (∼0.5) with lake-wide turbidity on a monthly scale. • Findings provide baseline metrics to support water management strategies. • Online tool delivers near real-time monitoring of lake-wide water quality.