Photos: K. Frey, B. Kiel, L. Mertes Matthews, E. and I. Fung, GBC, 1, 61-86, 1987. Siberia Amazon Ohio.

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Presentation transcript:

Photos: K. Frey, B. Kiel, L. Mertes Matthews, E. and I. Fung, GBC, 1, 61-86, Siberia Amazon Ohio

Virtual Mission First Results Supporting the WATER HM Satellite Concept Doug Alsdorf, Kostas Andreadis, Dennis Lettenmaier, Delwyn Moller, Ernesto Rodriguez, Paul Bates, Nelly Mognard, and the WATER HM Participants Funding from CNES, JPL, NASA’s Terrestrial Hydrology and Physical Oceanography Programs, and the Ohio State University’s Climate, Water, & Carbon Program

Outline What is WATER HM? Potential and limitations of conventional altimetry Measurements of surface water hydraulics: SRTM Measurements of height, slope and estimates of discharge RivWidth measurements of channel widths Data assimilation for estimating discharge

Surface Water ESSP Mission Options KaRIN: Ka-band Radar INterferometer Ka-band SAR interferometric system with 2 swaths, ~50 km each WSOA and SRTM heritage Produces heights and co- registered all-weather imagery Intrinsic resolution: 2 m in azimuth and 10 to 60 m in range Data down-linked via ground stations Courtesy of Ernesto Rodriguez, NASA JPL These surface water elevation measurements are entirely new, especially on a global basis, and thus represent an incredible step forward in hydrology. Courtesy: CNES

Heritage of WATER HM Why Water Heights? Two decades of altimetry missions measuring water surface heights (oceans and surface waters) SRTM covered ~60N to ~60S and recorded surface water elevations Hydrodynamic and continuity equations rely on h, dh/dx, and dh/dt (while other parameters are involved, height is a governing and conclusively proven spaceborne measurement) Publications showing the complexity of water hydraulics Why KaRIN Technology? SRTM demonstrated spaceborne capacity $20M Investment in WSOA toward development of instrument Field studies demonstrating near-nadir Ka-band returns from rivers Who Supports WATER HM? Selected by the U.S. National Academy “Decadal Survey” CNES, NASA, and JPL are all working to ensure the mission is a success Hundreds of participants from five continents. You are most welcome to participate bprc.osu.edu/water Most Importantly: Collegial joint community of physical oceanography and surface water hydrology

Complexity of Wetlands and Oceans ECCO-2 MIT JPL ocean current model Oceans and wetlands have complex patterns of water height changes and related flows. Height changes in both environments are significant whereas velocities are slow and do not necessarily reflect flow at depth. For example, SSH correlates with flow at depth via geostrophic relationship, i.e., flow along contours of constant pressure. Estimating the Circulation and Climate of the Ocean ECCO-2: Menemenus et al., EOS 2005

USGS Coverage: ~7000 gauges WATER HM is Not “Gauging from Space” Birkett, C.M., L.A.K. Mertes, T. Dunne, M.H. Costa, and M.J. Jasinski,Journal of Geophysical Research, 107, Hirsch, R.M., and J.E. Costa, EOS Transactions AGU, 85, , Alsdorf, Rodriguez, Lettenmaier, Reviews of Geophysics, Amazon: 6 M km 2, ~175,000 m 3 /s U.S.: 7.9 M km 2, Mississippi ~17,500 m 3 /s OSTP 2004: “Does the United States have enough water? We do not know.” “What should we do? Use modern science and technology to determine how much water is currently available …” Gauges provide daily sampling, which cannot be matched by a single satellite.

WATER HM is Not “Gauging from Space” Birkett, C.M., L.A.K. Mertes, T. Dunne, M.H. Costa, and M.J. Jasinski,Journal of Geophysical Research, 107, Hirsch, R.M., and J.E. Costa, EOS Transactions AGU, 85, , Alsdorf, Rodriguez, Lettenmaier, Reviews of Geophysics, Amazon: 6 M km 2, ~175,000 m 3 /s U.S.: 7.9 M km 2, Mississippi ~17,500 m 3 /s Satellites should be capable of providing dense spatial coverage. Using a radar altimeter, 16-day repeat, 32% of the rivers and 72% of the world’s large lakes are not sampled. 120 km wide swath, 16 day repeat, samples the entire globe and measures h, dh/dx, and dh/dt. Topex/POSEIDON: ~70 points

Measurements Required: h,  h/  x,  h/  t, and area, globally, on a ~weekly basis  q – Q  x =  h  t L

Hoover Reservoir, Columbus Ohio Alum Hoover 5 km There are hundreds of thousands of reservoirs and lakes around the world, but their storage changes are poorly known. The change in elevations (blue dots compared to red dots) agree with the height of the dam, but the elevation standard deviation for each height measurement is too large. KaRIN will improve this by an order of magnitude, but the SRTM data suggest a great opportunity for a future satellite mission. Kiel, Alsdorf, & LeFavour, PE & RS, 2006 σ = 5.71mσ = 7.41m

Channel Slope and Amazon Q from SRTM LeFavour and Alsdorf, GRL, 2005 Q m 3 /sObservedSRTMError Tupe % Itapeua % Manacapuru % Manning’s n method Channel Geometry from SAR Water Slope from SRTM Bathymetry from In-Situ

Width of the Purus River Manning’s n method RivWidth: Pavelsky & Smith, in press, and AGU 2007 =Q zw n 2z+w 2/3 ( )  h  x 1/2 SRTM DEM =Q w n Z 5/3  h  x ( ) 1/2 Large Width to Depth Rivers “RivWidth” algorithm developed by Tamlin Pavelsky, applicable to any classification.

“RivWidth” of Ohio River Basin Courtesy: J. Partsch

SRTM Elevations of water surfaces can be converted to river flow using Manning’s equation which relates water slope to flow velocity. Ohio River Discharge from the Space Shuttle Cairo, ILOhioview, PA Kiel et al., AGU 2006

Data Assimilation of Synthetic KaRIN Measurements to Estimate Discharge Small ~50 km upstream reach of Ohio River LISFLOOD, hydrodynamic model, provides spatial and temporal simulation domain Nominal VIC simulation provides input to LISFLOOD for “truth” simulation Perturbing precipitation with VIC provides input to LISFLOOD for open-loop and filter simulations KaRIN measurements simulated by corrupting LISFLOOD “truth” water surface heights with expected instrument errors Andreadis et al., GRL, 2007

Assimilation Results: Ohio River Channel Discharge Discharge (m 3 /s)‏ Channel Chainage (km)‏ Apr 1Apr 15 May 1 May 15Jun 1Jun Discharge (m 3 /s)‏ Andreadis et al., GRL, 2007 Discharge time series at downstream edge. Discharge errors relative to “truth”: Open Loop = 23.2% 8 day DA = 10.0% 16 day DA = 12.1% 32 day DA = 16.9% Discharge along the channel, April 13, Data assimilation of the synthetic KaRIN measurements clearly improves the discharge estimate compared to the open loop simulation.

Conclusions WATER HM is an international collaboration of surface water hydrology and physical oceanography, including CNES, NASA, JPL, and many institutes. Conventional altimetry has large coverage gaps, but demonstrates ability of radar to measure heights. SRTM demonstrates capability to measure surface water elevations and slopes, despite large look-angles (>30º) Data assimilation shows great promise for estimating discharge along entire reaches and at various time intervals. You are welcome to join us! bprc.osu.edu/water

Additional Slides

Purus River SRTM Estimated Discharge Based on in-situ gauge data, discharge in this Purus reach is estimated at 8500 m 3 /s (no February 2000 data is available, estimate based on previous years). Slope is assumed constant because SRTM accuracy is insufficient for finer resolution. WATER HM will measure expected slope changes at fine spatial resolution. =Q w n Z 5/3  h  x ( ) 1/2

Required Measurements Simple, Empirical Manning’s Equation Moderate Continuity Equation Complex St. Venant Equations continuity and momentum  q - Q  x =  A  t =  h  x Vel. ( ) 1/2 R 2/3 1 n =Q zw n 2z+w 2/3 ( )  h  x 1/2 z =  (h-bathymetry) h = water surface z = water depth w = channel width Q = (velocity)(z)(w)   Assume dA  w(dz) dz = dh  q - Q  x =  h  t w q = lateral inflow e.g., rain A = cross section g  Q  t  z  t +  Q2Q2  x A 1 A 1 ( ) A + = g(S 0 -S f ) S 0 = bathymetric slope S f = friction or energy slope, i.e., dh/dx Key: All equations depend heavily on knowing the water surface elevation and its changes.

Sensitivity to Satellite Overpass Frequency Additional experiments with 16- and 32-day assimilation frequencies Discharge errors at downstream end, relative to “truth”: 8 day = 10.0%, 16 day = 12.1%, 32 day = 16.9% Apr 1 Apr 15 May 1May 15Jun 1 Jun Discharge (m 3 /s)‏ Andreadis et al., GRL, 2007