Detecting Hydrological Loading Effect (HLE) variations from GRACE/GPS over the Amazon basin. S. Melachroinos1, G. Ramillien2, J-M. Lemoine3, F. Perosanz3, R. Biancale3, P. Tregoning4 1) LEGOS/CNES 14 Av. Edouard Belin, 31400 Toulouse, 2)LEGOS/CNRS 14 Av. Edouard Belin, 31400 Toulouse, 3)GRGS/CNES 14 Av. Edouard Belin, 31400 Toulouse, 4)Earth Physics Research School of Earth Sciences/ Australian National University, Canberra ACT 0200, Australia stavros.melachroinos@cnes.fr Abstract As an aquifer is charged or discharged the effective stress on the pore crustal skeleton changes and may lead to surface elevation variability of the crust. We investigate on the ability of GRACE satellite gravimetry in detecting these time variable Hydrological Loading Effects (HLE) due to regional water storage redistributions. For this purpose, we study radial displacements of the Earth's surface due to hydrological mass load derived from the last GRGS release of 10-day GRACE solutions (08/2002-06/2007, spatial resolution of ~400 km). We predict HLE by the implementation of a spherical harmonics prediction in the spectral domain that take viscous Love numbers into account, as well as by a surface point-wise integration of Green’s functions, girded amplitudes and local phases of equivalent water height (EWH) variations. To validate our predictions of seasonal scale, time-series of these vertical HLE displacements are interpolated and compared to the GPS station network records available in the general Amazon basin. The GPS HLE displacements take into account geocenter variations, and atmosphere/oceanic loading effects. Analysis of errors on estimated changes of vertical displacement are also made and then confronted to the GPS precision. 2. Estimation or radial displacements a) Legendre polynomials and summation over degree eand order (Davis et al. 2004) Where : is the radius of the Earth, the are associated Legendre Polynomials. The annual and semi annual amplitudes for the C and S stokes coefficients are and respectively. b) Equations of motion of Self-gravitating Elastic and Self-gravitating Viscous Spheres (L. M. Cathles 1975, Backus 1967) Where is the perturbation stress related to strain, is the pressure in the material elements within the body, is the elastic displacement 3D vector, and F are the body forces acting on an element of the body balanced by the stresses acting on the surface of that element. 3. GPS data For the GPS data we used the JPL weekly positions in a total period or 4.5 y for the IGS stations KOUR, UNSA and BRAZ . Under processing are the data of the RMBC GPS network shown in Fig. 1 . In the following figures we can see the very good correlation of the GPS time-series and the predicted HLE displacements from the EWH GRACE grids. The apparent jump in Brazilia (BRAZ) station is purely due to the antenna change that took place on Mars 13th 2007. GRACE data In both the GRACE and GPS analyses, ocean and pole tide effects and atmospheric pressure variations are modelled using the FES2004 (Lyard et al. 2006) and the ECMWF models, respectively. The GRACE models are given in spherical harmonics, complete to degree and order 50, every 10 days. Each model is based on 30 days of GRACE data, weighted in the following manner: 0.25 for the first and last 10 days, 0.50 for the middle 10 days. These models do not necessitate any Gaussian filtering prior to their use, since they have been computed with a constraint towards a mean gravity field that optimally reduces the striping of the solutions (Lemoine et al. 2007, Swenson and Wahr, 2006; Davis et al., 2007). Antenna Changement 12 Mars 2007 Dorne Margolin T (TRM29659.00) Harp = 110 mm Zephyr Geodetic (TRM 41249.00) Harp = 53.2 mm Orenoque basin Amazon basin 4. RMS residuals of differences GPS (10-days int. ) – GRACE HLE (10 – days) GPS (BRAZ) – HLE (BRAZ) Elastic model = 0.23 mm RMS Visco- Elastic = 0.27 mm RMS GPS(KOUR) – HLE (BRAZ) Elastic model = 0.17 mm RMS Visco – Elastic = Visco- 0.20 mm RMS GPS (UNSA) – HLE (UNSA) Elastic model = 0.13 mm RMS Visco – Elastic = 0.16 mm RMS Tocantin basin Parana basin Perspectives : Processing or the RMBC network. Extraction of weekly and diurnal GPS positions using GINS (CNES) scientific software. Evaluation of the geocenter motion impact on the GPS time series through the estimation or the translational parameters on the weekly solutions. Study and quantification of the basin related HLE effects on the GPS positions and extraction of this residual motion through their novel modelisation. Evaluation or the re-processed GPS time series residuals. Comparison to the coastal stations for any aliased OTL effects. Comparison to further GRACE GRGS EWH grids for 2008. Acknowledgments We would very much like to thank RMBC for providing the GPS RINEX data of the RMBC permanent network ! ! Fig. 1 : The Rede Brasileira de Monitoramento Continuo (RBMC) GPS network of the Brazilian direction of Geosciences The coefficients of the amplitude of the different constituents can then be plotted in the form of equivalent water height (EWH) anomalies using the following equation (Lemoine et al. 2007): where g stands for mean surface gravity (9.8 m/s^2), G is the gravitational constant (6.72e-11 ), R is the Earth radius (6378136.46 m), pw is the density of water, l is the degree, and k’1 are the load deformation coefficients of degree 1. Fig. 2 :The annual Equivalent Water Height (EWH) variations in mm (up-left) and the radial Hydrological Loading Effect (HLE) issued from the pure Elastic and Visco-Elastic model of the equations of motion reduced to the Runge-Kutta form (up-middle and right). The semi-annual EWH variations in mm (down-Left) and the radial HLE issued from the same models (down-middle and right).