recent applications of grace gravity data for continental hydrology andreas güntner helmholtz...

Recent applications of GRACE gravity data for continental hydrology

Andreas Güntner

Helmholtz Centre PotsdamGFZ German Research Centre for Geosciences

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: PrecipitationE: EvaporationQ: Runoff

ΔS = P - Q - E

Only integrative and large-scale measurement of ΔS for hydrology


11/2011: About 200 ISI paper on GRACE and continental hydrology

Water storage variations 169

- Total water storage 104

- Groundwater 25

- Inland glaciers 13

- Surface water storage 19

- Snow 6

Water balance, other variables 33

Evaluation of hydrological models 31

- Model calibration / data assimilation 7

GRACE processing, filtering 54

Main focus of GRACE hydrology papers


11/2011: About 200 ISI paper on GRACE and continental hydrology

Studies on water storage variations for particular river basins


ET = P - Q - ΔS

Water cycle components from GRACE data - Resolving for evapotranspiration

Ground and/or satellite-based data GRACE


ET = P - Q - ΔSWater 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


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 changeP PrecipitationET EvaporationQ RunoffW Atmospheric water storage changeC Water vapour convergence

Q = -ΔW + C - ΔS

Combined atmospheric-terrestrial water balance


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



ΔTWSGRACE = ΔSgroundwater + ΔScanopy + ΔSsnow + ΔSsoil + ΔSlakes + ΔSwetlands + ΔSriver

GRACE-based total water

storage variations ΔTWSGRACE

are a composite of various

continental water storage

compartments


GRACE hydrology studies with focus on lake water balances

9 studies among 200 ISI papers on GRACE and continental hydrology (11/2011)


GRACE hydrology studies with focus on surface water dynamics(river flow, floodplains, inundation areas)



GRACE hydrology studies with focus on inland glaciers



GRACE hydrology studies with focus on groundwater storage variations




ΔSgroundwater = ΔTWSGRACE + ΔScanopy + ΔSsnow + ΔSsoil + ΔSlakes + ΔSwetlands + ΔSriver

Resolving GRACE-based total

water storage variations

ΔTWSGRACE 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


WaterGAP Global Hydrology model (WGHM)

ISBA-TRIP

Global Land Data Assimilation System (GLDAS)

ΔTWS = ΔScanopy + ΔSsnow + ΔSsoil + ΔSgroundwater + ΔSrivers + ΔSlakes/reservoirs + ΔSwetlands

ΔTWS = Δ Scanopy +ΔSsnow + ΔSsoil + ΔSgroundwater + ΔSrivers

ΔTWS = ΔScanopy + ΔSsnow + ΔSsoil

Soil depth = root zone

Soil depth = root zone + deep soil layer

Soil depth GLDAS-CLM = 3.43 mGLDAS-MOSAIC = 3.50 mGLDAS-NOAH = 2.00 mGLDAS-VIC = 1.90 m

Water storage compartments from hydrological modelsfor GRACE TWS signal separation


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

Un

satu

rate

d zo

ne


Example: Water storage variations in Central Asian Mountains

Total study area:500 000 km²


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?


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 compartmentsfrom GRACE TWS data


Water storage variations in Central Asian Mountains





Hydrological models


4) Analysis of residuals and error assessment


Ensemble of GRACE products


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


Compensation for filter effects: example Central Asia


CLM MOSAIC NOAH VIC ISBA-TRIP WGHM

G300 1.47 1.32 1.18 1.29 0.99 0.98

G500 1.70 1.51 1.20 1.65 0.95 1.08

DDK1 1.63 1.54 1.23 1.68 1.02 1.17

DDK2 1.55 1.48 1.20 1.75 0.91 1.06

DDK3 1.83 1.63 1.21 1.84 0.85 1.06

G300/G500: Gauss filter 300/500 km. DDK: Decorrelation filter by Kusche (2007)


Compensation for filter effects: example Central Asia


CLM MOSAIC NOAH VIC ISBA-TRIP WGHMWGHM

No surface storage

G300 1.47 1.32 1.18 1.29 0.99 0.98 1.11

G500 1.70 1.51 1.20 1.65 0.95 1.08 1.45

DDK1 1.63 1.54 1.23 1.68 1.02 1.17 1.58

DDK2 1.55 1.48 1.20 1.75 0.91 1.06 1.23

DDK3 1.83 1.63 1.21 1.84 0.85 1.06 1.45

G300/G500: Gauss filter 300/500 km. DDK: Decorrelation filter by Kusche (2007)





Hydrological models


4) Analysis of residuals and error assessment


Ensemble of GRACE products

Carefully consider particular region and model differences

´ (e.g., Werth et al. 2009,Longuevergne et al. 2010)


Reducing GRACE mass variations in Central Asian Mountainsby 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


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


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


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

recent applications of grace gravity data for continental hydrology andreas güntner helmholtz...

Documents

grace hydrology studies

continental hydrology

hydrology andreas gntner

grace data

continental hydrology

continental runoff syed

lake water balances9

isi papers