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 were 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 has potential to be used to improve hydrodynamic model simulation by providing distributed Manning's roughness coefficient for respective model domains.