Chlorophyll-a (Chla), primarily sourced from phytoplankton, serves as a pivotal indicator for water eutrophication. It stands as a fundamental metric for gauging eutrophication levels, biophysical conditions, and primary productivity within lake ecosystems. Focusing on Taihu Lake as the study area, this research utilizes Landsat 8 OLI data alongside measured point data to establish a partial least squares model for inversion via a semi-empirical approach. Preliminary experimental findings indicate that the derived model and parameters effectively capture Chla concentrations in Taihu Lake over the past nine years (2015-2024). Building upon this foundation, the study integrates physical geography and socio-economic factors to analyze trends in Chla concentrations and their underlying causes. Consequently, this paper furnishes a semi-empirical model, parameter scheme, and a comprehensive long-term dataset of Chla concentration dynamics in Taihu Lake, offering robust support for future governance endeavors concerning the lake"s ecological restoration.