%0 Journal Article %1 https://doi.org/10.1029/2021WR031614 %A Durand, Michael %A Gleason, Colin J. %A Pavelsky, Tamlin M. %A de Prata Moraes Frasson, Renato %A Turmon, Michael %A David, Cédric H. %A Altenau, Elizabeth H. %A Tebaldi, Nikki %A Larnier, Kevin %A Monnier, Jerome %A Malaterre, Pierre Olivier %A Oubanas, Hind %A Allen, George H. %A Astifan, Brian %A Brinkerhoff, Craig %A Bates, Paul D. %A Bjerklie, David %A Coss, Stephen %A Dudley, Robert %A Fenoglio, Luciana %A Garambois, Pierre-André %A Getirana, Augusto %A Lin, Peirong %A Margulis, Steven A. %A Matte, Pascal %A Minear, J. Toby %A Muhebwa, Aggrey %A Pan, Ming %A Peters, Daniel %A Riggs, Ryan %A Sikder, Md Safat %A Simmons, Travis %A Stuurman, Cassie %A Taneja, Jay %A Tarpanelli, Angelica %A Schulze, Kerstin %A Tourian, Mohammad J. %A Wang, Jida %D 2023 %J Water Resources Research %K SWOT discharge, geoinst, hydrology, imported inverse mission problem, remote sensing, %N n/a %P e2021WR031614 %R https://doi.org/10.1029/2021WR031614 %T A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission %U https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021WR031614 %V n/a %X Abstract The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new datasets for both gaged and ungaged basins. SWOT discharge products (available approximately one year after launch) will provide discharge for all river reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge timeseries. We expect that discharge uncertainty will be less than 30\% for two thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge timeseries will be dominated by random error and are expected to be estimated to within 15\% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.

@article{https://doi.org/10.1029/2021WR031614, abstract = {Abstract The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new datasets for both gaged and ungaged basins. SWOT discharge products (available approximately one year after launch) will provide discharge for all river reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge timeseries. We expect that discharge uncertainty will be less than 30\% for two thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge timeseries will be dominated by random error and are expected to be estimated to within 15\% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.}, added-at = {2023-04-03T11:33:24.000+0200}, author = {Durand, Michael and Gleason, Colin J. and Pavelsky, Tamlin M. and de Prata Moraes Frasson, Renato and Turmon, Michael and David, Cédric H. and Altenau, Elizabeth H. and Tebaldi, Nikki and Larnier, Kevin and Monnier, Jerome and Malaterre, Pierre Olivier and Oubanas, Hind and Allen, George H. and Astifan, Brian and Brinkerhoff, Craig and Bates, Paul D. and Bjerklie, David and Coss, Stephen and Dudley, Robert and Fenoglio, Luciana and Garambois, Pierre-André and Getirana, Augusto and Lin, Peirong and Margulis, Steven A. and Matte, Pascal and Minear, J. Toby and Muhebwa, Aggrey and Pan, Ming and Peters, Daniel and Riggs, Ryan and Sikder, Md Safat and Simmons, Travis and Stuurman, Cassie and Taneja, Jay and Tarpanelli, Angelica and Schulze, Kerstin and Tourian, Mohammad J. and Wang, Jida}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/28ce34d1fc087b5fa34a055ae856a7f27/tourian}, doi = {https://doi.org/10.1029/2021WR031614}, eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2021WR031614}, interhash = {d9cc694f083a5551adcc2126c3608b58}, intrahash = {8ce34d1fc087b5fa34a055ae856a7f27}, journal = {Water Resources Research}, keywords = {SWOT discharge, geoinst, hydrology, imported inverse mission problem, remote sensing,}, note = {e2021WR031614 2021WR031614}, number = {n/a}, pages = {e2021WR031614}, timestamp = {2023-04-03T11:33:24.000+0200}, title = {A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021WR031614}, volume = {n/a}, year = 2023 }