This study aims at the lack of automatic analysis and extraction of precise road rut boundaries in road maintenance and management and proposes a method of a three-dimensional (3D) rut-contour extraction based on a point cloud watershed algorithm to address the issue. The method first operated the elevation normalization processing for the laser point cloud data of single-lane pavement to eliminate the influence of the transverse slope. The envelope method was employed to estimate the relative depth of the pavement cross-section and generate the relative depth model of the pavement point cloud. This was further utilized to enhance the sag characteristics of rutting grooves and remove the influence of the longitudinal slope of pavement on the watershed algorithm of the point cloud. Then, the rough boundary line of the rut was obtained by calculating the curvature characteristics of the rut boundary. Besides, the road surface was divided into five regions. The point with the maximum relative depth of each cross-section in the corresponding region was selected as the water-injection point set of the point cloud watershed algorithm. Finally, the longitudinal contour of ruts was precisely obtained according to the principle of waterlogging in the watershed algorithm. An experimental analysis was conducted on the S218 provincial road in Pingdu city, Qingdao to verify the corresponding laser point cloud data of the road ruts. The results show that the proposed method can accurately extract the multitype rut boundary, and the root mean square error of the longitudinal boundary of the rutting contour obtained is less than 5 cm. Simultaneously, the root mean square error of the rut depth obtained based on the rut boundary is less than 1.5 mm, while that estimated using the envelope method is greater than 1.5 mm. This demonstrates the higher accuracy of the proposed method. Therefore, the proposed method provides an effective method to extract the 3D contour of ruts for road maintenance and management.