A Framework for Estimating Global River Discharge From the Surface Water and Ocean Topography Satellite Mission

被引:59
作者
Durand, Michael [1 ,2 ]
Gleason, Colin J. [3 ]
Pavelsky, Tamlin M. [4 ]
Frasson, Renato Prata de Moraes [5 ]
Turmon, Michael [5 ]
David, Cedric H. [5 ]
Altenau, Elizabeth H. [4 ]
Tebaldi, Nikki [5 ]
Larnier, Kevin [6 ]
Monnier, Jerome [7 ]
Malaterre, Pierre Olivier [8 ]
Oubanas, Hind [8 ]
Allen, George H. [9 ]
Astifan, Brian [10 ]
Brinkerhoff, Craig [3 ]
Bates, Paul D. [11 ]
Bjerklie, David [12 ]
Coss, Stephen [1 ,2 ]
Dudley, Robert [12 ]
Fenoglio, Luciana [13 ]
Garambois, Pierre-Andre [14 ]
Getirana, Augusto [15 ,16 ]
Lin, Peirong [17 ]
Margulis, Steven A. [18 ]
Matte, Pascal [19 ]
Minear, J. Toby [20 ]
Muhebwa, Aggrey [21 ]
Pan, Ming [22 ]
Peters, Daniel [19 ]
Riggs, Ryan [23 ]
Sikder, Md Safat [21 ]
Simmons, Travis [3 ]
Stuurman, Cassie [5 ]
Taneja, Jay
Tarpanelli, Angelica [24 ]
Schulze, Kerstin [13 ]
Tourian, Mohammad J. [25 ]
Wang, Jida [21 ]
机构
[1] Ohio State Univ, Sch Earth Sci, Columbus, OH 43210 USA
[2] Ohio State Univ, Byrd Polar & Climate Res Ctr, Columbus, OH 43210 USA
[3] Univ Massachusetts, Dept Civil & Environm Engn, Amherst, MA USA
[4] Univ N Carolina, Dept Geol Sci, Chapel Hill, NC USA
[5] CALTECH, Jet Prop Lab, Pasadena, CA USA
[6] CS Corp, Space Dept, Toulouse, France
[7] INSA Toulouse Math Inst Toulosue IMT, Toulouse, France
[8] Univ Montpellier, Inst Agro, G EAU, AgroParisTech,BRGM,CIRAD,IRD,INRAE, Montpellier, France
[9] Virginia Polytech Inst & State Univ, Dept Geosci, Blacksburg, VA USA
[10] NOAA NWS, Ohio River Forecast Ctr, Wilmington, OH USA
[11] Univ Bristol, Sch Geog Sci, Bristol, England
[12] US Geol Survey, New England Water Sci Ctr, Northborough, MA USA
[13] Univ Bonn, Dept Geodesy & Geoinformat, Bonn, Germany
[14] Aix Marseille Univ, INRAE, RECOVER, Marseille, France
[15] NASA Goddard Space Flight Ctr, Hydrol Sci Lab, Greenbelt, MD USA
[16] Sci Applicat Int Corp, Greenbelt, MD USA
[17] Peking Univ, Inst Remote Sensing & GIS, Sch Earth & Space Sci, Beijing, Peoples R China
[18] UCLA, Dept Civil & Environm Engn, Los Angeles, CA USA
[19] Environm & Climate Change Canada, Sci & Technol Branch, Quebec City, PQ, Canada
[20] Univ Colorado Boulder, Cooperat Inst Res Environm Sci, Boulder, CO USA
[21] Kansas State Univ, Dept Geog & Geospatial Sci, Manhattan, KS USA
[22] Univ Calif San Diego, Scripps Inst Oceanog, Ctr Western Weather & Water Extremes, La Jolla, CA USA
[23] Texas A&M Univ, Dept Geog, College Stn, TX USA
[24] CNR, Res Inst Geohydrol Protect, Perugia, Italy
[25] Univ Stuttgart, Inst Geodesy, Stuttgart, Germany
关键词
discharge; hydrology; inverse problem; remote sensing; SWOT mission; STATIONS HYDRAULIC GEOMETRY; AT-A-STATION; DATA ASSIMILATION; SWATH ALTIMETRY; RATING CURVES; SLOPE; UNCERTAINTY; ELEVATION; INFERENCE; NETWORK;
D O I
10.1029/2021WR031614
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1 year after launch) will provide discharge for all river that 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 time series. 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 time series will be dominated by random error and are expected to be estimated 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. Plain Language Summary The Surface Water and Ocean Topography (SWOT) satellite mission was launched on 15 December 2022. SWOT is designed to produce estimates of river discharge on many rivers where no in situ discharge measurements are currently available. This paper describes how SWOT discharge estimates will be created, and their expected accuracy. SWOT discharge will be estimated using simple flow laws that combine SWOT measurements of river water elevation above sea level, river width, and river slope, with ancillary data such as river bathymetry. We expect that discharge uncertainty will be less than 30% for two-thirds of global reaches and will be dominated by a systematic bias. Temporal variations in river discharge time series are expected to be estimated within 15% for nearly all reaches, thus capturing the response of river discharge to rainfall and snowmelt events, including in basins that are currently ungaged, and providing a new capability for scientists to better track the flows of freshwater water through the Earth system.
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页数:31
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