Seagrass meadows are declining at alarming rates globally due to both anthropogenic activities and natural threats. Seagrasses play key ecological roles in coastal ecosystems as primary producers and providers of habitat and environmental structure. Therefore, mapping seagrass beds is indispensable for the effective monitoring and management of coastal vegetated habitats. In contrast to direct sampling techniques and optical remote sensing, active hydroacoustic techniques are relatively inexpensive and efficient for the detection of seagrass. We used a single beam echosounder to detect the spatial and temporal distribution characteristics of the eelgrass Zostera marina L. in an important overwintering habitat for the whooper swan Cygnus cygnus (Swan-Lake lagoon), northern China. We also distinguished echograms of the macroalgae Chaetomorpha linum K. and outlined its threat to seagrass. We also propose a method for calculating the accuracy of interpolation analyses. Results showed that: (1) The distribution of seagrass in Swan Lake varies with seasons, with maximum distribution area in summer. The maximum distribution area of seagrass beds in Swan Lake was 199.09 ha–231.67 ha, accounting for 41.48%–48.26% of the area of Swan Lake; (2) C. linum is a growing threat for seagrass beds of Swan-lake, with distribution area as high as 129.28 ha in May 2018. The invasion and competition by C. linum against seagrass beds could be one of the reasons for the decline in seagrass beds in Swan-Lake; (3) Topo to Raster has the highest interpolation accuracy and is the most conservative among three interpolation methods. Topo to Raster was the most suitable interpolation method for the sonar detection of seagrass beds. The findings may facilitate the application of sonar technology in seagrass monitoring and provide data for the formulation of appropriate seagrass bed management and restoration strategies and policies.