March 19, 2024: 1-2PM ET: NRCAN Webinar Series – Manning’s n: High-Resolution Approaches and Challenges in Surface Roughness Modeling for Hydrological Assessment

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Presenter: Heather McGrath

This work explores two methods for generating high-resolution representations of Manning’s roughness coefficients (Manning’s n) for floodplains. First, we test a Voxel/Connection based approach in combination with a with a rule-based table to assign hydraulic roughness values on an unclassified LiDAR point cloud. The second method uses Image Segmentation with a U-Net model trained on land use categories from very high-resolution satellite imagery to predict Manning’s n values for each pixel. While both methods have merits, challenges exist, such as refining reclass tables and addressing incomplete output data in the Image Segmentation approach.