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

Author:

Durand Michael1ORCID,Gleason Colin J.2ORCID,Pavelsky Tamlin M.3ORCID,Prata de Moraes Frasson Renato4ORCID,Turmon Michael4,David Cédric H.4ORCID,Altenau Elizabeth H.3ORCID,Tebaldi Nikki4ORCID,Larnier Kevin5ORCID,Monnier Jerome6,Malaterre Pierre Olivier7ORCID,Oubanas Hind7,Allen George H.8ORCID,Astifan Brian9,Brinkerhoff Craig2,Bates Paul D.10ORCID,Bjerklie David11ORCID,Coss Stephen1ORCID,Dudley Robert11ORCID,Fenoglio Luciana12ORCID,Garambois Pierre‐André13,Getirana Augusto1415,Lin Peirong16ORCID,Margulis Steven A.17ORCID,Matte Pascal18ORCID,Minear J. Toby19ORCID,Muhebwa Aggrey20ORCID,Pan Ming21,Peters Daniel18,Riggs Ryan22ORCID,Sikder Md Safat20,Simmons Travis2,Stuurman Cassie4,Taneja Jay20,Tarpanelli Angelica23ORCID,Schulze Kerstin12ORCID,Tourian Mohammad J.24ORCID,Wang Jida20ORCID

Affiliation:

1. School of Earth Sciences, and Byrd Polar and Climate Research Center The Ohio State University Columbus OH USA

2. Department of Civil and Environmental Engineering University of Massachusetts Amherst Amherst MA USA

3. Department of Geological Sciences University of North Carolina Chapel Hill NC USA

4. Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

5. Space Department CS Corporation Toulouse France

6. INSA Toulouse—Math. Institute of Toulosue (IMT) Toulouse France

7. G‐EAU Univ Montpellier AgroParisTech BRGM CIRAD IRD INRAE Institut Agro Montpellier France

8. Department of Geosciences Virginia Polytechnic Institute and State University Blacksburg VA USA

9. Ohio River Forecast Center NOAA NWS Wilmington OH USA

10. School of Geographical Sciences University of Bristol Bristol UK

11. New England Water Science Center U.S. Geological Survey Northborough MA USA

12. Department of Geodesy and Geoinformation University of Bonn Bonn Germany

13. INRAE RECOVER Aix‐Marseille University Marseille France

14. Hydrological Sciences Laboratory NASA Goddard Space Flight Center Greenbelt MD USA

15. Science Applications International Corporation Greenbelt MD USA

16. School of Earth and Space Sciences Institute of Remote Sensing and GIS Peking University Beijing China

17. Department of Civil and Environmental Engineering UCLA Los Angeles CA USA

18. Science and Technology Branch Environment and Climate Change Canada Canada QC Canada

19. Cooperative Institute for Research in Environmental Sciences University of Colorado Boulder Boulder CO USA

20. Department of Geography and Geospatial Sciences Kansas State University Manhattan KS USA

21. Center for Western Weather and Water Extremes Scripps Institution of Oceanography University of California San Diego La Jolla CA USA

22. Department of Geography Texas A&M University College Station TX USA

23. Research Institute for Geo‐Hydrological protection National Research Council Perugia Italy

24. Institute of Geodesy University of Stuttgart Stuttgart Germany

Abstract

AbstractThe 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.

Funder

Jet Propulsion Laboratory

Earth Sciences Division

Royal Society

Centre National d’Etudes Spatiales

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3