Estimating Baseline Flow Resistance Parameters for Remote Sensing River Discharge ( RSQ ) From River Morphology Characteristics

This study demonstrates that flow resistance in rivers, quantified via calibration of a modified Manning's equation, can inform its estimation from channel hydrometric information available from regional or global datasets for a limited set ( N = 14) of rigorously calibrated river reaches in Alaska and with less certainty in a large set ( N = 754) of river reaches across the United States developed from U.S. Geological Survey (USGS) Acoustic Doppler Current Profiler (ADCP) discharge measurements. The channel morphometry datasets tested include the National Aeronautics and Space Administration (NASA) Surface Water and Ocean Topography (SWOT) River Database (SWORD) and U.S. Geological Survey (USGS) Scale Specific Sinuosity (S3) river channel morphometry metrics. Multiple regression prediction models of the baseline (near bankfull) Manning's n flow resistance coefficient were developed from the SWORD and S3 reach data. Significant predictive variables included but were not limited to water‐surface slope, water‐surface variation (width and elevation), the number of active channels, maximum width, sinuosity and along channel meander length. The study points to the possibility of global a priori estimation of flow resistance in rivers for application in remote sensing of river discharge from river morphology, water‐surface width, slope and height measurements made by SWOT and other satellites.