Accurate and quick riverbank line detection plays an import role in extracting the region of interest (ROI) for an unmanned surface vehicle (USV). Because of the riverbank line can be used for USV obstacle detection, visual navigation, motion state estimation. Different from the sea line detection, the riverbank line detection is usually affected by water waves, reflection and inverted image, so the background of land river riverbank line detection are more complex and diversified. In this paper, a robust morphological riverbank line method to a different environment is presented. This method includes following steps: First, image pre-processing (Resize, Gaussian blue, Map RGB colour to HSV space); Then, the value channel was operated by the morphological gradient to highlight the edge; subsequently, segmentation of watershed algorithm; finally extracting the riverbank line in classical Sobel operator. Experiment result proves that our morphological approach can boost efficiency and performance significantly in multiple and complex environments. Index Terms -Unmanned surface vehicle; HSV color space;Morphology; Riverbank line detection.