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Comparison of Seasonal Terrestrial Water Storage Variations from GRACE with in situ Measurements from the High Plains Aquifer Gil Strassberg 1, Bridget.

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Presentation on theme: "Comparison of Seasonal Terrestrial Water Storage Variations from GRACE with in situ Measurements from the High Plains Aquifer Gil Strassberg 1, Bridget."— Presentation transcript:

1 Comparison of Seasonal Terrestrial Water Storage Variations from GRACE with in situ Measurements from the High Plains Aquifer Gil Strassberg 1, Bridget Scanlon 1, Matthew Rodell 2 1 Bureau of Economic Geology 2 Hydrological Sciences Branch, NASA Goddard Space Flight Center Bureau of Economic Geology, March 2007

2 Outline 1.GRACE 2.High Plains Aquifer 3.Data and Methods 4.Results

3 Gravity Recovery and Climate Experiment (GRACE) Two satellites distance ~ 220km Satellites detect changes in Earth's gravity field by monitoring the changes in distance between the satellites as they orbit Earth. Distance ~ 220 km Launch March 2002 Figures from CSR website: http://www.csr.utexas.edu/grace/

4 How it works The positions of the two GRACE satellites change in response to variations in Earth's gravity field Lead satellite pulls away due to gravity change High accuracy device can detect changes within 10 µm Figures from CSR website: http://www.csr.utexas.edu/grace/

5 Can we monitor water storage changes from space? Evaluate the use of GRACE data for estimating water storage changes Use the High Plains Aquifer as a case study “changes in water mass… should be readily detectable in a region the size of the High Plains aquifer ” Satellite Gravity and the Geosphere: Contributions to the Study of the Solid Earth and Its Fluid Envelopes (1997).

6 From gravity to water mass GRACE provides time varying global gravity fields (~30 days) Observed monthly changes in gravity are caused by monthly changes in mass Mass changes are mainly attributed to changes in the distribution of water mass in: Hydrologic reservoirs (soil, groundwater, waterbodies, snow) Oceans Atmosphere Cryosphere (frozen) Figure from GRACE Tellus website: http://gracetellus.jpl.nasa.gov/

7 Terrestrial water storage (TWS) Terrestrial Water Storage includes: Water in reservoirs and rivers Soil moisture Groundwater Snow and Ice Biomass Total mass = TWS + Atmospheric mass Terrestrial mass Atmospheric mass Total mass Estimated from climate models European Center for Medium-Range Weather Forecasts (ECMWF)

8 Estimating Storage Changes GRACE satellites measure monthly gravity changes Gravity changes  Terrestrial Water Storage changes Storage changes in TWS components can be estimated when combined with other data (modeled or measured) Terrestrial water storage Groundwater storage Soil moisture Snow water equivalent Surface water Biomass

9 Previous studies - Illinois Yeh et al (2006) compared GRACE TWS changes in Illinois (200,000 km 2 ) with monitored soil moisture and groundwater GRACE TWS SM + GW + IZ TWS - SM GW + IZ

10 Previous studies – Greenland Ice Sheet Chen et al. (2006) showed melting of the ice sheet in East Greenland Mass changes between April 2002 and November 2005

11 Previous studies – Land Surface Models TWS data is useful for calibration and validation of land surface models Niu et al. (2006) combined GRACE TWS with modeled subsurface water to compare with modeled snow water equivalent in 4 arctic river basins AMSR = Advanced Microwave Scanning Radiometer Model = NCAR Community Land Surface Model (CLM)

12 Other studies GRACE data is used to help monitor and model many large scale processes: Estimation of ET and P-ET over large river basins Continental water cycle and continental ocean discharge Sea level change Water balance in large lakes (e.g. Three-Gorges Reservoir, lake Chad) Climate change Earthquake effects GRACE data capturing changes in the Earth’s gravity field due to the December 2004 Sumatra earthquake (CRS website: http://www.csr.utexas.edu/GRACE/publications/press/ ) http://www.csr.utexas.edu/GRACE/publications/press/

13 Outline 1.GRACE 2.High Plains Aquifer 3.Data and Methods 4.Results

14 High Plains Aquifer Underlies 8 states in the U.S. (~ 450,000 km 2 ) One of the principal aquifers in the U.S. and one of the major agriculture areas of the world (~ 175,000 km 2 cultivated) 27% of irrigated land in the US 30% of the groundwater used for irrigation in the US Highly monitored by Federal and State agencies

15 Irrigation Semi arid conditions (P = 400-700 mm and E = 1500 - 2700 mm) ~50,000 km 2 of irrigated area, ~30% of cultivated area) 23.5 km 3 (19M acre-feet) of water pumped from the aquifer in 2000, with about 95% withdrawn for irrigation Equivalent to 52 mm of water over the entire aquifer area

16 Irrigation and Water Levels Water levels and storage have been declining due to irrigation (average 3.8 m and maximum of 68 m) USGS surveys since 1988 – only in winter Good estimate of groundwater storage (~9200 wells monitored in 2003) million-acre feet Groundwater storage from predevelopment to 2003 Figure from McGuire (2004): http://pubs.usgs.gov/fs/2004/3097/

17 Expected seasonal groundwater signal ~90% of groundwater pumped during summer (May-August) Water levels recover to a “static” level during winter Expect a seasonal signal in groundwater storage Long term trend of decreasing water storage Winter Summer Winter Summer Groundwater storage Long term trend

18 Outline 1.GRACE 2.High Plains Aquifer 3.Data and Methods 4.Results

19 Estimating Groundwater Storage Changes Combine GRACE derived Terrestrial Water Storage (TWS) and modeled Soil Moisture (SM) from a land surface model to estimate groundwater changes Terrestrial water storage Groundwater storage Soil moisture Snow water equivalent Surface water Biomass

20 Terrestrial Water Storage TWS is derived from 3 datasets processed by the GRACE partners. Data represent mass anomalies after taking out atmospheric mass. Data is smoothed with a 400-km Gaussian smoother to isolate the signal. mass anomaly (mm) Maximum TWS anomaly ~ 80 mm Missing data

21 Soil Moisture and TWS Soil moisture was estimated from the Noah land surface model driven by the North American Land Data Assimilation System (NLDAS). 1/8 degree grid over North America High resolution parameters including hourly observation-based precipitation and solar radiation, and detailed soil and vegetation. mm water SWE is negligible

22 Is SWE really negligible? Drilling near Amarillo

23 Soil Moisture Soil moisture from 86 sites Seasonal SM changes were calculated for each site Data were averaged on a 1x1 degree grid Estimated overall SM changes Compared to modeled SM anomalies SM anomaly (mm)

24 Surface water Flat terrain, no major reservoirs Internally drained into ephemeral lakes (playas) ~53,000 playas covering ~0.5% of the land surface area http://www.rw.ttu.edu/torrence/

25 Surface water Use 1/3 second (~10m) DEM to estimate playa depths Sample of 130 playas Average depth = 1.06 m Elevation from 1/3 arc second (~10m) Sample area ~1 m h max h min Depth = h max – h min 0.5% * 1.06 m = 5.3 mm Playa area

26 Biomass Rodell et al. (2005) estimated biomass changes from remotely sensed Leaf Area Index (LAI) Seasonal variations were < 5 mm Figure form Rodell et al (2005)

27 Estimating Groundwater Storage Assimilated water levels from groundwater databases: USGS NWIS, Texas Water Development Board (TWDB), and Kansas WIZARD groundwater database 2,719 wells with seasonal water level changes Water level change between 4-6 2003 and 7-9 2003 Water level changes are calculated per well as differences between seasonal averages

28 Spatial Aggregation of Water Level Changes Water level changes were averaged over a 1x1 degree mesh Based on wells with daily water levels we filter out changes > 4.57 m (15 feet) Water level change Between 4-6 2003 and 7-9 2003 Spatially aggregated water level changes Water level change (m)

29 Variations in Groundwater Storage Convert water level changes to storage changes (Sy = 0.15) Seasonal cycle with an amplitude of ~ 75 mm Compare to changes (winter to winter) from USGS Anomalies of groundwater storage 1 2 Period (winter-winter) Our Analysis USGS (1) 2003-2004 -45 mm-37 mm (2) 2004-2005 -9 mm

30 Outline 1.GRACE 2.High Plains Aquifer 3.Data and Methods 4.Results

31 Groundwater Storage and Soil Moisture Changes of groundwater and soil moisture are same order of magnitude Seasonal variation in SM and GWS

32 TWS vs. Groundwater Storage + Soil Moisture Estimated the TWS uncertainty between 32- 37 mm, mean 34 mm Seasonal TWS change ranged 8-93 mm, mean = 43 mm Changes winter/spring – summer/fall range 40-100, mean = 75 mm

33 Groundwater Storage vs. TWS - Soil Moisture Seasonal TWS-SM change ranged 1-63 mm, mean = 26 mm Changes winter/spring – summer/fall range 30-100, mean = 57 mm Close to estimated discharges of 52

34 Detectability of changes Mean uncertainty in TWS-SM changes = 49 mm Winter/spring – Summer/fall TWS changes detected 4 out of 5 periods Maximum TWS-SM were detected 3 out of 5 periods Uncertainty estimate might be too conservative and will probably be modified Detectible: Uncertainty = 49 < change

35 Summary Seasonal changes in TWS in the High Plains aquifer area are due to changes in soil moisture and groundwater storage (surface water, snow water equivalent, and biomass are negligible) GRACE-derived TWS agreed well with SM + GWS (same magnitude, trends, R = 0.82) Variations in groundwater storage from water level measurements showed a fair agreement with TWS – SM (same trend and magnitude, R = 0.58) TWS changes were detectible in 4 out of 5 periods (winter/spring- summer/fall) TWS-SM changes were detectible in 3 out of 5 periods

36 Future Work Add data for 2006 Include new release of GRACE data Add new soil moisture data Spatial variations Improve uncertainty estimate See how this can be applied in other regions Winter-Spring 2005 SM change Seasonal SM change (mm)

37 Questions?

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