Water Hyacinth (Eichhornia crassipes) locally known as Nile Rose has been recognized as an invasive aquatic weed that poses significant ecological and socio-economic threats to freshwater ecosystems. In this study the detection of Water Hyacinth and the mapping of its spatial distribution within the Tigris River in Baghdad Province, Iraq, were carried out using three spectral vegetation indices namely CI Green, EVI, and NDVI derived from Sentinel-2 MSI imagery A total of 48 cloud-free Sentinel-2 MSI scenes acquired during the summer season of 2024 (June–September) were processed using the Google Earth Engine (GEE) platform River surface delineation was performed using the MNDWI index (> 0.05), and a 30-meter riparian buffer and floating vegetation island detection procedure were applied to define the final analysis mask Each spectral vegetation index was classified into five land cover classes to quantify the spatial extent of Water Hyacinth. Accuracy assessment was conducted using approximately 150 ground truth validation points, and it was recorded that the CI Green index achieved the highest Overall Accuracy (90.07%, κ = 0.8758 – Almost Perfect) outperforming EVI (80.79%, κ = 0.7601) and NDVI (47.33%, κ = 0.3421) It was further recorded that the CI Green index detected a total Water Hyacinth area of 0.1642 km² representing 4.93% of the analyzed river corridor. The results confirmed that the CI Green index is the most reliable spectral vegetation index for Water Hyacinth detection in the Tigris River and demonstrated the effectiveness of Sentinel-2 MSI imagery with a spatial resolution of 10 meters for aquatic weed monitoring in urban river systems.