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Peter A. Troch and Matej Durcik HWR-SAHRA, University of Arizona
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An NSF Science and Technology Center SAHRA 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
description
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
Transcript of Peter A. Troch and Matej Durcik HWR-SAHRA, University of Arizona
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
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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.
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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
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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
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Near real-time TWS monitoring system
http://voda.hwr.arizona.edu/twsc/sahra/
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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
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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.
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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.
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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).
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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).
