Monitoring water levels by integrating optical and synthetic aperture radar water masks with lidar DEMs

Abstract:

The ability to map and monitor wetland and lake open water extent and levels across the landscape allows improved estimates of watershed water balance, surface storage and flood inundation. The study presents open water classifications over the wetland dominated Sheppard Slough watershed east of Calgary in western Canada using parallel temporal imagery captured from the RapidEye and RadarSat satellites throughout 2013, a year of widespread and costly flood inundation in this region. The optical and SAR-based temporal image stacks were integrated with a high-resolution lidar DEM in order to delineate regions of inundation on the DEM surface. GIS techniques were developed to extract lidar-derived water surface elevations and track the spatio-temporal variation in pond and lake water level across the watershed. Water bodies were assigned unique identifiers so that levels could be tracked and linked to their associated watershed channel reach. The procedure of optical image classification through to merging of individual water bodies into watershed channel topology and extracting reach water levels has been automated within python scripts. The presentation will describe: i) the procedures used; ii) a comparison of the SAR and optical classification and water level extraction results; iii) a discussion of the spatio-temporal variations in water level across the Sheppard Slough watershed; and iv) a commentary on how the approach could be implemented for web-based operational monitoring and as simulation initialisation inputs for flood inundation model studies.