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Potential of Distributed GRACE Measurements to Estimate Spatially Variable Terrestrial Water Storage Changes in the Colorado River Basin. Peter A. Troch and Matej Durcik HWR-SAHRA, University of Arizona Shaakeel Hasan, Remko Uijlenhoet and Ruud Hurkmans Wageningen University. - PowerPoint PPT Presentation
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An NSF Science and Technology CenterSAHRA
Potential of Distributed GRACE Measurements
to Estimate Spatially Variable Terrestrial Water
Storage Changes in the Colorado River Basin
Peter A. Troch and Matej DurcikHWR-SAHRA, University of Arizona
Shaakeel Hasan, Remko Uijlenhoet and Ruud HurkmansWageningen University
An NSF Science and Technology CenterSAHRA
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Support and Acknowledgment
• NSF EAR-Hydrologic Sciences: Sustainability of Semi-arid Hydrology and Riparian Areas (SAHRA; PIs: Jim Shuttleworth, Juan Valdés, Kathy Jacobs)
• US Dept. of the Interior – Bureau of Reclamation: Enhancing Water Supply Reliability in the Lower Colorado River (PI: Kathy Jacobs, Peter Troch)
• WSP-UA (TRIF FY07-11): Tracing Arizona’s Water Reserves from Space
• Andy Wood, 3Tier and Univ. Washington• Dennis Lettenmaier, Sonia Seneviratne
An NSF Science and Technology CenterSAHRA
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Focus Area: Colorado River Basin
• Important water resource in semi-arid southwest of US;
• Global change imposes enormous stress on the basin’s hydrology;
• Assessing climate variability impacts on stream flow requires accurate estimates of terrestrial water storage variability.
An NSF Science and Technology CenterSAHRA
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What is terrestrial water storage (TWS)?
• TWS is the total amount of water stored (surface and subsurface), at a given time, in a river basin;
• TWS is an important indicator of the hydrologic state and defines the basin’s response to atmospheric forcing, e.g.– Snow pack defines (potential) spring runoff– Groundwater storage defines baseflow
• In Colorado River basin, surface reservoir inflow (e.g. Lake Powell) depends on TWS, hence accurate estimates of TWS can help water management & planning
An NSF Science and Technology CenterSAHRA
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Terrestrial Water Storage (TWS) Dynamics
Troch et al., 2007 (EOS)
Wet years 1996-2000 Dry years 2001-2006
http://www.iac.ethz.ch/data/water_balance/
E
SR
WP
Cq
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VIC Simulated Natural Flow
Colorado Basin above Imperial Dam
0
10
20
30
40
Jan-50 Jan-55 Jan-60 Jan-65 Jan-70 Jan-75 Jan-80 Jan-85 Jan-90 Jan-95 Jan-00 Jan-05Date
Ru
no
ff [
mm
/mo
nth
] NF
VIC
Nash-Sutclif fe Eff iciency: 0.85
Colorado Basin at Lees Ferry
0
10
20
30
40
Jan-50 Jan-55 Jan-60 Jan-65 Jan-70 Jan-75 Jan-80 Jan-85 Jan-90 Jan-95 Jan-00 Jan-05Date
Ru
no
ff [
mm
/mo
nth
] NF
VIC
Nash-Sutclif fe Eff iciency: 0.88
An NSF Science and Technology CenterSAHRA
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Near real-time TWS monitoring system
http://voda.hwr.arizona.edu/twsc/sahra/
An NSF Science and Technology CenterSAHRA
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GRACE data processing
• We used Release 04 (RL04) of monthly gravity field for 2003-2006;
• GRACE estimates of surface mass anomalies for the Colorado basin are obtained from the University of Colorado website: http://geoid.colorado.edu/grace/grace.php
• More info on RL04 gravity coefficients conversion into 1-degree maps of equivalent water thickness can be found at http://grace.jpl.nasa.gov/data/mass/ (Chambers, 2006).
• Averages of three data sets (JPL, CSR, GFZ) of solutions up to degree and order 40 are used.
• GRACE estimates of TWS anomalies at 1-degree resolution are compared to VIC estimates and in-situ data of SWE
An NSF Science and Technology CenterSAHRA
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Results
• Basin-average intercomparison between VIC simulated TWS anomalies and GRACE derived mass anomalies;
• Correlation coefficients are generally high, except during 2nd half of 2004.
An NSF Science and Technology CenterSAHRA
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Results (2): 1-degree correlation maps
Total Storage Soil Moisture Snow Storage Groundwater
Total Storage
2003 2004 2005
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Results (3): In-situ correlation maps
• a) Pixels containing surface reservoirs;• b) Pixels containing groundwater wells;• c) Pixels containing stream flow gauges;• d) Pixels containing Snotel sites;• Numbers refer to time lag of maximum correlation.
An NSF Science and Technology CenterSAHRA
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• a) Slope of regression relationship between GRACE and VIC TWS anomalies (>1: VIC overestimates TWS anomalies);
• b) Relationship between slope of regression line and topographic surface roughness (left y-axis) and standard deviation of elevation (right y-axis).
An NSF Science and Technology CenterSAHRA
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Conclusion and Outlook
• Distributed GRACE measurements show great potential to estimate spatially variable terrestrial water storage anomalies in the Colorado River basin;
• Current research efforts focus on using TWS information to improve seasonal to interannual stream flow predictions conditioned by climate variability indicators (See Matt Switanek’s talk at 2:15PM in Room 129B).