Estimation of Manning´s roughness coefficient distribution for hydrodynamic model using remotely sensed land cover features

This research explores the potential of remote sensing techniques to derive distributed Manning´s roughness coefficient (Manning´s n) for the use in hydrodynamic models for numerical simulation of open channel flow in natural channels and flood plains. Normalized Difference Vegetation Index (NDVI) based land use land cover (LU/LC) data was generated using the Landsat 5 Thematic Mapper (TM) and Advance Land Observing Satellite (ALOS) Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) imagery. Manning´s n was obtained from published literature for different features in flood plains and correlated with the remote sensing derived LU/LC features. CCHE2D model, developed by the National Center for Computational Hydroscience and Engineering (NCCHE) at The University of Mississippi, for simulating two dimensional depth-averaged unsteady flow and sediment transport was used to validate the remote sensing derived distributed Manning´s n for channel flow calculation. Results obtained from this research indicate that satellite imagery derived LU/LC data have potential to be used to improve hydrodynamic model simulation by providing distributed Manning´s roughness coefficient for respective model domains.