LAUSR

Abstract Eutrophication of inland freshwater bodies is a major threat to the ecosystem services. Many studies have focused on using surface or near surface phytoplankton biomass to determine trophic status or bloom conditions. However, surface phytoplankton biomass can change quickly due to the vertical migration of phytoplankton. A more appropriate indicator is column integrated biomass which considers the vertical distribution of the phytoplankton. In this study, we estimated the spatial and temporal dynamics of column integrated biomass in a shallow eutrophic lake, Lake Chaohu in China, using a biomass estimation algorithm and fourteen years of satellite data. The built algorithm was validated by in situ datasets with a significant correlation with the coefficient of determination (R2) of 0.89, mean absolute relative difference, MARD = 25.97%, the root-mean-square error, RMSE = 20.17 mg·m−2. We decomposed the temporal dynamics of the satellite-based time series into inter-annual trends, seasonal and irregular behaviors of biomass in different lake sections. We compared these individual dynamics to nutrients, meteorological and climate variables, in particular with respect to ongoing effort to manage nutrients in this complex lake and catchment. Nutrient concentrations were shown to be determinant in the inter-annual trends. Irregular variation of biomass was found to be sensitive to global climate change events (ENSO) which influence regional conditions of precipitation and temperature. By taking the vertical profile of phytoplankton into consideration, the derived temporal and spatial distribution of phytoplankton biomass, rather than surface biomass, provided new sights into lake conditions and were seen to be a good support for lake management efforts.