This study proposes a method to simulate the images of the future European geostationary sensor dedicated to ocean color sensor: the geostationary ocean color advanced permanent imager (GeoOCAPI), and it demonstrates the sensor capabilities to monitor the water composition throughout the day. The temporal variation of the coastal seascape is obtained from biogeochemical and hydrosedimentary models, the ocean-atmosphere radiance is obtained from the water and atmosphere radiative transfer model. The GeoOCAPI images are simulated with 400-m resolution, 18 spectral bands with associated signal-to-noise ratio (SNR) and with 1-h acquisition frequency, on the Gulf of Lion (Marseille, France) during a pollution event caused by the urban outfall of Cortiou in Marseille. These images describe the water color dynamic in the Gulf of Lion due to the river transport and the urban outfall. The validation with real medium resolution imaging spectrometer (MERIS) images showed that the image simulator was reliable with an average relative error (RE) at 4.76% for visible bands and at 16.51% for near infrared bands. The quasi-analytical algorithm (QAA) inversion method was tested. The suspended particulate matter (SPM) and the colored dissolved organic matter (CDOM) can be retrieved with good accuracy; the error is, respectively, 7.69% and 12.21%. The chlorophyll concentration (chl) is misestimated (58.10%) due to the low concentration in this area (< 1 mg . m(-3)) compared to SPM (> 1g . m(-3)). The study showed that the future geostationary sensor GeoOCAPI will be able to monitor the water composition in coastal areas through the day and detect and monitor an urban outfall discharge.