Recent applications of GRACE gravity data for continental hydrology

1. Recent applications of GRACE gravity data for continental hydrology Andreas Güntner Helmholtz Centre PotsdamGFZ German Research CentreforGeosciences

2. Water storage variations from time-variable gravity data • Temporal variations of the gravity field of the Earth • Water mass variations on the continents after removal of other mass components ΔS = P - Q - E • S: Water storage changeP: Precipitation • E: Evaporation • Q: Runoff Only integrative and large-scale measurement of ΔS for hydrology

3. 11/2011: About200ISI paper on GRACE and continental hydrology Main focus of GRACE hydrology papers

4. 11/2011: About200ISI paper on GRACE and continental hydrology Studies on water storage variations for particular river basins

5. Water cycle components from GRACE data - Resolving for evapotranspiration ET = P - Q - ΔS Ground and/or satellite-based data GRACE

6. Water cycle components from GRACE data - Resolving for evapotranspiration ET = P - Q - ΔS Hai River Basin, North China (320 000 km²) ETWH: Model-basedET using remote sensing data ETGP: GRACE-based ET Moiwo et al. (2011), Hydr.Sci.J.

7. Atmospheric water balance ΔS = P – Q - ET ΔW = C + ET - P Water cycle components from GRACE data - Resolving for continental runoff Terrestrial water balance Combined atmospheric-terrestrial water balance Q = -ΔW + C- ΔS S Land water storage changeP Precipitation ET Evaporation Q Runoff W Atmospheric water storage change C Water vapour convergence

8. Water cycle components from GRACE data - Resolving for continental runoff Total continental discharge of the Pan-Arctic drainage area + includes ungauged river basins + includes groundwater discharge into oceans Syed et al. (2007), GRL

9. Water storage variations from time-variable gravity data GRACE-based total water storage variations ΔTWSGRACEare a compositeofvariouscontinentalwaterstoragecompartments ΔTWSGRACE=ΔSgroundwater+ ΔScanopy+ΔSsnow+ΔSsoil+ΔSlakes+ΔSwetlands+ΔSriver

10. GRACE hydrology studies with focus on lake water balances • 9 studies among 200 ISI papers on GRACE and continental hydrology (11/2011)

11. GRACE hydrology studies with focus on surface water dynamics(river flow, floodplains, inundation areas) • 15 studies among 200 ISI papers on GRACE and continental hydrology (11/2011)

12. GRACE hydrology studies with focus on inland glaciers • 13 studies among 200 ISI papers on GRACE and continental hydrology (11/2011)

13. GRACE hydrology studies with focus on groundwater storage variations • 25 studies among 200 ISI papers on GRACE and continental hydrology (11/2011)

14. Water storage variations from time-variable gravity data Resolving GRACE-based total water storage variations ΔTWSGRACEforsinglestoragecompartments ΔSgroundwater=ΔTWSGRACE+ ΔScanopy+ΔSsnow+ΔSsoil+ΔSlakes+ΔSwetlands+ΔSriver • Other compartments can usually be estimated based on hydrological / land surface model data only • Other compartments may not be fully accounted for in models • Uncertainties / errors accumulate in the variable of interest

15. Water storage compartments from hydrological modelsfor GRACE TWS signal separation WaterGAPGlobal Hydrology model (WGHM) ΔTWS = ΔScanopy + ΔSsnow+ΔSsoil+ ΔSgroundwater+ΔSrivers + ΔSlakes/reservoirs + ΔSwetlands Soildepth = rootzone ISBA-TRIP ΔTWS =ΔScanopy +ΔSsnow+ΔSsoil+ ΔSgroundwater+ ΔSrivers Soildepth = rootzone + deepsoillayer Global Land Data Assimilation System (GLDAS) ΔTWS =ΔScanopy + ΔSsnow+ΔSsoil Soildepth GLDAS-CLM = 3.43 m GLDAS-MOSAIC = 3.50 m GLDAS-NOAH = 2.00 m GLDAS-VIC = 1.90 m

16. Relevance of deep unsaturated zone water storage for GRACE TWS signal separation Snow Local gravity effect of water storage compartments Station Wettzell / Germany Soil 0-30cm Unsaturated zone Soil 30-150cm Saprolith 1.5 – 11m Groundwater > 11m Hydrological gravity effect Superconducting gravimeter residuals Creutzfeldt et al., 2010, WRR; Creutzfeldt et al., GJI, 2010

17. Example: Water storage variations in Central Asian Mountains Total studyarea:500 000 km²

18. Example: Water storage variations in Central Asian Mountains Total studyarea:500 000 km² Can we estimate glacier mass changes from GRACE? Source: GGHYDRO (Cogley, 2003)

19. Isolation of single water storage compartmentsfrom GRACE TWS data • Selection of GRACE product (processing type and centre, filtering) • Compensation for filter effects (smoothing, leakage) • Estimating correction function (e.g. rescaling factor) • Hydrological models • Reduction of unwanted hydrological signal components • Analysis of residuals

20. Water storage variations in Central Asian Mountains

21. Isolation of single water storage compartmentsfrom GRACE TWS data • Selection of GRACE product (processing type and centre, filtering) • Compensation for filter effects (smoothing, leakage) • Estimating correction function (e.g. rescaling factor) • Hydrological models • Reduction of unwanted hydrological signal components • Analysis of residuals and error assessment Ensemble of GRACE products

22. Water storage variations in Central Asian Mountains

23. Water storage variations in Central Asian Mountains

24. Compensation for filter effects Multiplicativescalingfactorderivedfrom least-squareadjustment • Mainly sensitive to seasonal dynamics • Leakage effects (e.g. phase shifts) are not compensated • Rescaling functions depend on the hydrological model used • Rescaling functions may not apply for the variable of interest

25. Compensation for filter effects: example Central Asia Multiplicativescalingfactorderivedfrom least-squareadjustment G300/G500: Gauss filter 300/500 km. DDK: Decorrelation filter by Kusche (2007)

26. Compensation for filter effects: example Central Asia Multiplicativescalingfactorderivedfrom least-squareadjustment G300/G500: Gauss filter 300/500 km. DDK: Decorrelation filter by Kusche (2007)

27. Isolation of single water storage compartmentsfrom GRACE TWS data • Selection of GRACE product (processing type and centre, filtering) • Compensation for filter effects (smoothing, leakage) • Estimating correction function (e.g. rescaling factor) • Hydrological models • Reduction of unwanted hydrological signal components • Analysis of residuals and error assessment Carefully consider particular region and model differences´ (e.g., Werth et al. 2009,Longuevergne et al. 2010) Ensemble of GRACE products

28. Reducing GRACE mass variations in Central Asian Mountainsby water storage from hydrological models • 7 GRACE products • 5 different filters • 6 different rescalingvaluesforeach filter • 6 different LSMs / hydrologicalmodelsforsignalseparation • → bootstrappingapproach

29. GRACE mass variations in Central Asian Mountains after reducing for model-based TWS Trend-0.2 ± 5.7 mm/a 792 realisationof different plausible GRACE products, rescalingfactorsandhydrologicalreductionmodels

30. GRACE mass variations in Central Asian Mountains after reducing for model-based TWS Trend+13.9 mm/a Trend-12.8 mm/a 792 realisationof different plausible GRACE products, rescalingfactorsandhydrologicalreductionmodels

31. Conclusions and perspectives • Caveats in using single GRACE products, filter and correction methods or hydrological model data sets→ use ensemble approach • Multi-sensor applications of GRACE (in conjunction with, e.g., altimetry, satellite-based snow, soil moisture and ET products) for assessing dynamics of continental hydrology and signal decomposition • Extended use of GRACE to inform structure and parameterization of land surface / hydrological models