H41E-1364
How well Can We Classify SWOT-derived Water Surface Profiles?

Thursday, 17 December 2015
Poster Hall (Moscone South)
Renato P. M. Frasson, Byrd Polar and Climate Research Center, Columbus, OH, United States, Rui Wei, Ohio State University Main Campus, Columbus, OH, United States, Christophe Picamilh, INP - ENSEEIHT, Hydraulics and Fluid Mechanics, Toulouse, France and Michael T Durand, Ohio St Univ-Earth Sciences, Columbus, OH, United States
Abstract:
The upcoming Surface Water Ocean Topography (SWOT) mission will detect water bodies and measure water surface elevation throughout the globe. Within its continental high resolution mask, SWOT is expected to deliver measurements of river width, water elevation and slope of rivers wider than ~50 m. The definition of river reaches is an integral step of the computation of discharge based on SWOT’s observables. As poorly defined reaches can negatively affect the accuracy of discharge estimations, we seek strategies to break up rivers into physically meaningful sections. In the present work, we investigate how accurately we can classify water surface profiles based on simulated SWOT observations. We assume that most river sections can be classified as either M1 (mild slope, with depth larger than the normal depth), or A1 (adverse slope with depth larger than the critical depth). This assumption allows the classification to be based solely on the second derivative of water surface profiles, with convex profiles being classified as A1 and concave profiles as M1. We consider a HEC-RAS model of the Sacramento River as a representation of the true state of the river. We employ the SWOT instrument simulator to generate a synthetic pass of the river, which includes our best estimates of height measurement noise and geolocation errors. We process the resulting point cloud of water surface heights with the RiverObs package, which delineates the river center line and draws the water surface profile. Next, we identify inflection points in the water surface profile and classify the sections between the inflection points. Finally, we compare our limited classification of simulated SWOT-derived water surface profile to the “exact” classification of the modeled Sacramento River. With this exercise, we expect to determine if SWOT observations can be used to find inflection points in water surface profiles, which would bring knowledge of flow regimes into the definition of river reaches.