ESTIMATING RIVER BATHYMETRY, ROUGHNESS, AND DISCHARGE FROM REMOTE SENSING MEASUREMENTS OF RIVER HEIGHT ON THE RIVER SEVERN, U.K.

摘要

The Surface Water and Ocean Topography (SWOT) satellite is a swath-mapping radar interferometer that will provide water elevations over inland water bodies and over the ocean. Here we present a Bayesian algorithm that calculates a best estimate of river bathymetry, roughness coefficient, and discharge based on measurements of river height and slope. On the River Severn, UK, we use gage estimates of height and slope during an in-bank flow event to illustrate algorithm functionality. We validate our estimates of river bathymetry and discharge using in situ measurements. We first assumed that the lateral inflows from smaller tributaries were known. In this case, an accurate inverse to bathymetry and roughness was obtained giving a discharge RMSE of 10 %. We then allowed the lateral inflows to be unknown; accuracy in the bathymetry estimates dropped in this case, giving a discharge RMSE of 36 %. Finally, we explored the case where bathymetry in one reach was known; in this case, discharge RMSE was 15.6 %.