RESEARCH ARTICLE 10.1002/2017WR020887 Automated River Reach Definition Strategies: Applications for the Surface Water and Ocean Topography Mission Renato Prata de Moraes Frasson 1 , Rui Wei 1 , Michael Durand 1,2 , J. Toby Minear 3 , Alessio Domeneghetti 4 , Guy Schumann 5 , Brent A. Williams 6 , Ernesto Rodriguez 6 , Christophe Picamilh 7 , Christine Lion 8 , Tamlin Pavelsky 8 , and Pierre-Andr e Garambois 9 1 Byrd Polar and Climate Research Center, Ohio State University, Columbus, OH, USA, 2 School of Earth Sciences, Ohio State University, Columbus, OH, USA, 3 Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA, 4 School of Civil Engineering, University of Bologna, Bologna, Italy, 5 Remote Sensing Solutions, Inc., Monrovia, CA, USA, 6 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA, 7 Department of Hydraulics and Fluid Mechanics, INP – ENSEEIHT, Toulouse, France, 8 Department of Geological Sciences, University of North Carolina, Chapel Hill, NC, USA, 9 ICUBE-UMR 7357 Fluid Mechanics Team, INSA Strasbourg, Strasbourg, France Abstract The upcoming Surface Water and Ocean Topography (SWOT) mission will measure water sur- face heights and widths for rivers wider than 100 m. At its native resolution, SWOT height errors are expected to be on the order of meters, which prevent the calculation of water surface slopes and the use of slope-dependent discharge equations. To mitigate height and width errors, the high-resolution measure- ments will be grouped into reaches (5 to 15 km), where slope and discharge are estimated. We describe three automated river segmentation strategies for defining optimum reaches for discharge estimation: (1) arbitrary lengths, (2) identification of hydraulic controls, and (3) sinuosity. We test our methodologies on 9 and 14 simulated SWOT overpasses over the Sacramento and the Po Rivers, respectively, which we compare against hydraulic models of each river. Our results show that generally, height, width, and slope errors decrease with increasing reach length. However, the hydraulic controls and the sinuosity methods led to better slopes and often height errors that were either smaller or comparable to those of arbitrary reaches of compatible sizes. Estimated discharge errors caused by the propagation of height, width, and slope errors through the discharge equation were often smaller for sinuosity (on average 8.5% for the Sacramento and 6.9% for the Po) and hydraulic control (Sacramento: 7.3% and Po: 5.9%) reaches than for arbitrary reaches of comparable lengths (Sacramento: 8.6% and Po: 7.8%). This analysis suggests that reach definition methods that preserve the hydraulic properties of the river network may lead to better discharge estimates. 1. Introduction Assessing and predicting the availability of freshwater requires comprehensive measurements of river discharge and surface water storage, with sufficient spatial and temporal resolution to resolve the propagation of hydro- logical events through channels, floodplains, and lakes (Alsdorf & Lettenmaier, 2003). The global in situ network of gages does not entirely fulfil these requirements due to its heterogeneous spatial distribution, with varying density among different countries (Alsdorf et al., 2007) combined with data sharing barriers between nations (e.g., Gleason & Hamdan, 2015; Hossain et al., 2014; Sneddon & Fox, 2012; Wolf et al., 1999). With a planned launch in 2021, the upcoming Surface Water and Ocean Topography (SWOT) mission has the potential to fill gaps in the global streamgage network (Pavelsky et al., 2014) by providing freely available and spatially distrib- uted observations of rivers wider than 100 m and lakes with an inundation area in excess of 62,500 m 2 (Bianca- maria et al., 2015; Rodr  ıguez, 2015). The anticipated benefits of this mission for surface water hydrology include: novel insights into the dynamics of water storage changes in lakes, reservoirs, and wetlands, and river discharge (Durand et al., 2010a), better understanding of the global water cycle and runoff processes (Pavelsky et al., 2014), easier monitoring of transboundary rivers (Biancamaria et al., 2011; Gleason & Hamdan, 2015; Hossain et al., 2014), simpler access to observations over remote areas assisting the management of reservoirs (Munier et al., 2015; Solander et al., 2016) and supporting flood modeling and forecasting (Schumann et al., 2010). The core payload in the SWOT satellite is the Ka-band Radar Interferometer (KaRIn), which builds upon the Shuttle Radar Topography Mission (SRTM, described by Farr et al., 2007). SWOT will orbit Earth at an altitude Key Points:  Choice of river segmentation strategies affect the quality of reach- averaged products produced by remote sensing  Reach definition methods based on hydraulic properties of rivers appear to lead to better discharge than reaches of arbitrary lengths  Method for the detection of unlisted hydraulic structures compatible with future SWOT data are proposed and tested Supporting Information:  Supporting Information S1  Data Set S1  Data Set S2  Data Set S3 Correspondence to: R. P. d. M. Frasson, frasson.1@osu.edu Citation: Frasson, R. P. M., Wei, R., Durand, M., Minear, J. T., Domeneghetti, A., Schumann, G., ... Garambois, P.-A. (2017). Automated river reach definition strategies: Applications for the surface water and ocean topography mission. Water Resources Research, 53, 8164–8186. https://doi. org/10.1002/2017WR020887 Received 4 APR 2017 Accepted 12 SEP 2017 Accepted article online 15 SEP 2017 Published online 11 OCT 2017 V C 2017. American Geophysical Union. All Rights Reserved. FRASSON ET AL. AUTOMATED REACH DEFINITION STRATEGIES 8164 Water Resources Research PUBLICATIONS