This study， focused on the area of Beibu Gulf， explores the remote sensing inversion method for chlorophyll concentration based on the Sentinel-3A satellite's OCLI water color sensor. The study partitions the Beibu Gulf by using measured spectral data and then combines the measured chlorophyll-a concentration with Sentinel-3A remote sensing data of which aims to build the remote sensing inversion model for chlorophyll-a concentration. The results show that （1） the remote sensing reflectance curves exhibit distinct partition characteristics， dividing the area into nearshore， transitional， and offshore water types based on the spectral features； （2） Different water types require different inversion factors for model construction， and all of them got relatively good fitted result. Among them， the fitted inversion factor is R_rs（764.375）/R_rs（681.25） that could be used in the nearshore water， for the transitional water， ［1/R_rs（620）-1/R_rs（708.75）］/R_rs（753.75） is the most suitable， and for the offshore water， R_rs（708.75）-R_rs（764.375） achieves the best fitting performance， with corresponding R² values of 0.67， 0.80， and 0.8， respectively； （3） The partitioning method effectively improves the applicability and accuracy of the remote sensing inversion model for chlorophyll concentration in the Beibu Gulf. This study successfully realizes the remote sensing inversion of chlorophyll concentration in the Beibu Gulf by using a partitioning model based on Sentinel-3A satellite's OCLI data. The result provides the important scientific support for the remote sensing monitoring of chlorophyll concentration in the Beibu Gulf， and enhances the management and protection of marine ecological environments.