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Recent applications of GRACE gravity data for continental hydrology Andreas Güntner Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences.

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Presentation on theme: "Recent applications of GRACE gravity data for continental hydrology Andreas Güntner Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences."— Presentation transcript:

1 Recent applications of GRACE gravity data for continental hydrology Andreas Güntner Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences

2 Andreas Güntner | GRACE for continental hydrology 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  S: Water storage change P: Precipitation E: Evaporation Q: Runoff ΔS = P - Q - E Only integrative and large-scale measurement of ΔS for hydrology

3 Andreas Güntner | GRACE for continental hydrology 3 11/2011: About 200 ISI paper on GRACE and continental hydrology Water storage variations169 - Total water storage104 - Groundwater25 - Inland glaciers13 - Surface water storage19 - Snow6 Water balance, other variables33 Evaluation of hydrological models31 - Model calibration / data assimilation7 GRACE processing, filtering54 Main focus of GRACE hydrology papers

4 Andreas Güntner | GRACE for continental hydrology 4 11/2011: About 200 ISI paper on GRACE and continental hydrology Studies on water storage variations for particular river basins

5 Andreas Güntner | GRACE for continental hydrology 5 ET = P - Q - ΔS Water cycle components from GRACE data - Resolving for evapotranspiration Ground and/or satellite-based data GRACE

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

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

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

9 Andreas Güntner | GRACE for continental hydrology 9 Water storage variations from time-variable gravity data ΔTWS GRACE = ΔS groundwater + ΔS canopy + ΔS snow + ΔS soil + ΔS lakes + ΔS wetlands + ΔS river GRACE-based total water storage variations ΔTWS GRACE are a composite of various continental water storage compartments

10 Andreas Güntner | GRACE for continental hydrology 10 GRACE hydrology studies with focus on lake water balances 9 studies among 200 ISI papers on GRACE and continental hydrology (11/2011)

11 Andreas Güntner | GRACE for continental hydrology 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 Andreas Güntner | GRACE for continental hydrology 12 GRACE hydrology studies with focus on inland glaciers 13 studies among 200 ISI papers on GRACE and continental hydrology (11/2011)

13 Andreas Güntner | GRACE for continental hydrology 13 GRACE hydrology studies with focus on groundwater storage variations 25 studies among 200 ISI papers on GRACE and continental hydrology (11/2011)

14 Andreas Güntner | GRACE for continental hydrology 14 Water storage variations from time-variable gravity data ΔS groundwater = ΔTWS GRACE + ΔS canopy + ΔS snow + ΔS soil + ΔS lakes + ΔS wetlands + ΔS river Resolving GRACE-based total water storage variations ΔTWS GRACE for single storage compartments 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 Andreas Güntner | GRACE for continental hydrology 15 WaterGAP Global Hydrology model (WGHM) ISBA-TRIP Global Land Data Assimilation System (GLDAS) ΔTWS = ΔS canopy + Δ S snow + Δ S soil + Δ S groundwater + Δ S rivers + Δ S lakes/reservoirs + Δ S wetlands ΔTWS = Δ S canopy + Δ S snow + Δ S soil + Δ S groundwater + Δ S rivers ΔTWS = ΔS canopy + Δ S snow + Δ S soil Soil depth = root zone Soil depth = root zone + deep soil layer Soil depthGLDAS-CLM = 3.43 m GLDAS-MOSAIC = 3.50 m GLDAS-NOAH= 2.00 m GLDAS-VIC= 1.90 m Water storage compartments from hydrological models for GRACE TWS signal separation

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

17 Andreas Güntner | GRACE for continental hydrology 17 Example: Water storage variations in Central Asian Mountains Total study area: 500 000 km²

18 Andreas Güntner | GRACE for continental hydrology 18 Example: Water storage variations in Central Asian Mountains Source: GGHYDRO (Cogley, 2003) Total study area: 500 000 km² Can we estimate glacier mass changes from GRACE?

19 Andreas Güntner | GRACE for continental hydrology 19 1)Selection of GRACE product (processing type and centre, filtering) 2)Compensation for filter effects (smoothing, leakage) Estimating correction function (e.g. rescaling factor) Hydrological models 3)Reduction of unwanted hydrological signal components 4)Analysis of residuals Isolation of single water storage compartments from GRACE TWS data

20 Andreas Güntner | GRACE for continental hydrology 20 Water storage variations in Central Asian Mountains

21 Andreas Güntner | GRACE for continental hydrology 21 1)Selection of GRACE product (processing type and centre, filtering) 2)Compensation for filter effects (smoothing, leakage) Estimating correction function (e.g. rescaling factor) Hydrological models 3)Reduction of unwanted hydrological signal components 4)Analysis of residuals and error assessment Isolation of single water storage compartments from GRACE TWS data Ensemble of GRACE products

22 Andreas Güntner | GRACE for continental hydrology 22 Water storage variations in Central Asian Mountains

23 Andreas Güntner | GRACE for continental hydrology 23 Water storage variations in Central Asian Mountains

24 Andreas Güntner | GRACE for continental hydrology 24 Compensation for filter effects Multiplicative scaling factor derived from least-square adjustment 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 Andreas Güntner | GRACE for continental hydrology 25 Compensation for filter effects: example Central Asia Multiplicative scaling factor derived from least-square adjustment CLMMOSAICNOAHVICISBA-TRIPWGHM G300 1.471.321.181.290.990.98 G500 1.701.511.201.650.951.08 DDK1 1.631.541.231.681.021.17 DDK2 1.551.481.201.750.911.06 DDK3 1.831.631.211.840.851.06 G300/G500: Gauss filter 300/500 km. DDK: Decorrelation filter by Kusche (2007)

26 Andreas Güntner | GRACE for continental hydrology 26 Compensation for filter effects: example Central Asia Multiplicative scaling factor derived from least-square adjustment CLMMOSAICNOAHVICISBA-TRIPWGHM No surface storage G300 1.471.321.181.290.990.981.11 G500 1.701.511.201.650.951.081.45 DDK1 1.631.541.231.681.021.171.58 DDK2 1.551.481.201.750.911.061.23 DDK3 1.831.631.211.840.851.061.45 G300/G500: Gauss filter 300/500 km. DDK: Decorrelation filter by Kusche (2007)

27 Andreas Güntner | GRACE for continental hydrology 27 1)Selection of GRACE product (processing type and centre, filtering) 2)Compensation for filter effects (smoothing, leakage) Estimating correction function (e.g. rescaling factor) Hydrological models 3)Reduction of unwanted hydrological signal components 4)Analysis of residuals and error assessment Isolation of single water storage compartments from GRACE TWS data Ensemble of GRACE products Carefully consider particular region and model differences ´ (e.g., Werth et al. 2009, Longuevergne et al. 2010)

28 Andreas Güntner | GRACE for continental hydrology 28 Reducing GRACE mass variations in Central Asian Mountains by water storage from hydrological models - 7 GRACE products - 5 different filters - 6 different rescaling values for each filter - 6 different LSMs / hydrological models for signal separation → bootstrapping approach

29 Andreas Güntner | GRACE for continental hydrology 29 GRACE mass variations in Central Asian Mountains after reducing for model-based TWS 792 realisation of different plausible GRACE products, rescaling factors and hydrological reduction models Trend -0.2 ± 5.7 mm/a

30 Andreas Güntner | GRACE for continental hydrology 30 GRACE mass variations in Central Asian Mountains after reducing for model-based TWS 792 realisation of different plausible GRACE products, rescaling factors and hydrological reduction models Trend +13.9 mm/a Trend -12.8 mm/a

31 Andreas Güntner | GRACE for continental hydrology 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

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