HR: 14:25h
AN: H33I-04    [Abstracts]
TI: Virtual Mission First Results Supporting the WATER HM Satellite Concept
AU: * Alsdorf, D
EM: alsdorf.1@osu.edu
AF: School of Earth Sciences, Ohio State University, Columbus, OH 43210,
AU: Andreadis, K
EM: kostas@hydro.washington.edu
AF: Civil and Environmental Engineering, University of Washington, Seattle, WA 43210,
AU: Lettenmaier, D
EM: dennisl@u.washington.edu
AF: Civil and Environmental Engineering, University of Washington, Seattle, WA 43210,
AU: Moller, D
EM: delwyn.k.moller@jpl.nasa.gov
AF: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 43210,
AU: Rodriguez, E
EM: ernesto.rodriguez@jpl.nasa.gov
AF: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 43210,
AU: Bates, P
EM: paul.bates@bristol.ac.uk
AF: School of Geographical Sciences, University of Bristol, Bristol, UK 43210,
AU: Mognard, N
EM: nelly.mognard@cnes.fr
AF: Laboratoire d'Etudes en Géophysique et Océanographie Spatiales, CNES, Toulouse, FR 43210,
AU: Participants, W
EM: alsdorf.1@osu.edu
AF: over 200 people from more than 30 countries, earthsciences.osu.edu/water/participants.php, Columbus, 43210,
AB: Surface fresh water is essential for life, yet we have surprisingly poor knowledge of its variability in space and time. Similarly, ocean circulation and ocean-atmosphere interactions fundamentally drive weather and climate variability, yet the global ocean current and eddy field (e.g., the Gulf Stream) that affects ocean circulation is poorly known. The Water And Terrestrial Elevation Recovery Hydrosphere Mapper satellite mission concept (WATER HM or SWOT per the NRC Decadal Survey) is a swath-based interferometric-altimeter designed to acquire elevations of ocean and terrestrial water surfaces at unprecedented spatial and temporal resolutions. WATER HM will have tremendous implications for estimation of the global water cycle, water management, ocean and coastal circulation, and assessment of many water-related impacts from climate change (e.g., sea level rise, carbon evasion, etc.). We describe a hydrological "virtual mission" (VM) for WATER HM which consists of: (a) A hydrodynamic-instrument simulation model that maps variations in water levels along river channels and across floodplains. These are then assimilated to estimate discharge and to determine trade-offs between resolutions and mission costs. (b) Measurements from satellites to determine feasibility of existing platforms for measuring storage changes and estimating discharge. First results demonstrate that: (1) Ensemble Kalman filtering of VM simulations recover water depth and discharge, reducing the discharge RMSE from 23.2% to 10.0% over an 84- day simulation period, relative to a simulation without assimilation. The filter also shows that an 8-day overpass frequency produces discharge relative errors of 10.0%, while 16-day and 32-day frequencies result in errors of 12.1% and 16.9%, respectively. (2) SRTM measurements of water surfaces along the Mississippi, Missouri, Ohio, and Amazon rivers, as well as smaller tributaries, show height standard deviations of 5 meters or greater (SRTM is the heritage for WATER HM). These large errors require several hundred kilometer reach lengths to estimate slope and hence discharge in the empirical Manning's method. Nevertheless, discharge estimates are reasonable and can be within 10% of gauged values. (3) River channel widths are key for determining the capability of WATER HM to resolve flow hydraulics. Automated measurements of channels, as classified in NLCD92 (a 30m product from the USGS Land Cover Institute), show detailed coverage throughout the Ohio River Basin, including channels with annual discharge of 150 cms, draining 12,500 sqkm. (4) Conventional profiling altimetry misses 75% of all lakes in the world because there are hundreds of kilometers between orbital tracks. This is highly problematic for understanding storage changes in Arctic lakes which are disappearing but in a spatially varying, heterogeneous manner.
UR: http://earthsciences.osu.edu/water
DE: 1821 Floods
DE: 1836 Hydrological cycles and budgets (1218, 1655)
DE: 1855 Remote sensing (1640)
DE: 1894 Instruments and techniques: modeling
DE: 1895 Instruments and techniques: monitoring
SC: Hydrology [H]
MN: 2007 Fall Meeting