Andrea Manconi, T.R. Walter M. Motagh, J. Ruch, M. Shirzaei, R. Wang & J. Zschau Helmholtz Centre GFZ Potsdam, Telegrafenberg, Potsdam (Germany) Deformation sources derived from InSAR analysis at volcanoes: How realistic are the models?

Geodetic data (InSAR) Inversion Volcanic unrest: Inflation/deflation of the magma chamber, dyke/sill intrusion, hydrothermal activity, ring fault dislocation… Surface displacement Interpretation Source depth, volume/pressure change, position, shape, orientation, evolution over time…

Model’s Assumptions - Simplified geometries (points, spheres, rectangular planes, ellipsoidal, etc.) - Earth’s lithosphere is an elastic, isotropic, and homogeneous half-space… Skaergaard, Greenland …however, in nature volcanic plumbing systems and volcanic areas look differently! Gran Canaria, Spain

…differences in the source parameters (Depth and Pressure) are up to 60% depending on the mechanical contrast Manconi et al., 2007 Homogeneous models and layered models may lead to the same fitness of the data, but… (Darwin Volcano, Galápagos, ca. 20 cm uplift between Amelung et al., 2000) LAYEREDLAYERED Pritchard et al., 2004; Trasatti et al., 2005; Newman et al., 2006; Ellis et al., 2007; Crescentini et al., 2007; Masterlark, 2007; Amoruso et al., 2008; etc…

NAPOLI Bay WE ARE HERE ! CAMPI FLEGREI CALDERA View from Vesuvius crater

Long and accurate observation of the surface displacements… SBAS-DInSAR ( , ERS – ENVISAT), M.Manzo, G.Zeni, P. Tizzani, E. Sansosti & R.Lanari

…Standard approach: joint inversion of Asc & Desc data assuming as source a Mogi source. E(km)N(km)d(km)  P(MPa/yr) min max rms=0.3 cm/year

A priori information about the sub-surface structure Chiarabba et al., 2006 Berrino et al., 1998 Judenherc et al.,2004 Zamora et al., 1994

3-D Finite Element models constrained by independent geophysical observations and constraints Forward model considering 20 MPa overpressure (Sartoris,1990) Chiarabba et al., 2006 Low Vp/Vs anomaly 3 km depth Seismicity between 2-4 km depth During unrest, gas chemistry and gravity changes compatible with hydrothermal reservoir ( De Natale et al., 1991, Chiodini et al., 2001; Battaglia et al., 2006) Our FE model

Forward model on a 3D heterogeneous medium E(km)N(km)d(km)  P(MPa/yr) min (+15%) max (+25%) E(km)N(km)d(km)  P(MPa/yr) rms=0.3 cm/year Inversion using Mogi and assuming an “equivalent” homogeneous half-space

Synthetic displacement on 3D Finite Element heterogeneous model (3DHET) Best-fit model assuming an “equivalent” homogeneous half-space (HHS) This procedure retrieves the source location (coordinates and depth) but OVERESTIMATES the pressure changes… INVERSION  P HHS >  P 3DHET 3DHETHHS  P 3DHET The surface displacement U(x,y,0) is linearly related to the source strength  P

If we consider the same source parameters (x, y, z,  P) in both models… “K” represent the factor of amplification or reduction of the surface displacements due to the 3-D heterogeneities 3DHET HHS U 3DHET U HHS < U 3DHET

Applying this “correction factors” to the real data… The inversion of U InSAR * will retrieve pressure changes as they occur in a fully 3D heterogeneous model! InSAR Data “corrected” for the 3D heterogeneity effects “Reality” Similarly to seismology applications, “correction factors” might be calculated for every “station” to take into account the local effects and will be then applied to the real measured data

U InSAR Interpretation 3D FEM Synthetic tests Inversion The source position is not affected (like CF) A priori constraints ?

E(km)N(km)d(km)  P (MPa/yr) min max E(km)N(km)d(km)  P (MPa/yr) min (-40%) max (- 32%) Standard approach “Corrected” dataset

Application to the complete SBAS time series Manconi et al., in preparation

Summary and Conclusion -The use of InSAR data alone to constrain source parameters MAY lead to uncertainties! -The simplified analytical models fit the data…Numerical tests help to understand why! - Good news…under certain conditions we can still use the simplified models (e.g. monitoring)!

Thanks for your attention!

Summary and Conclusions (II) - Viscoelasticity, poroelasticity, lithostatic pressure, topography effects, etc… Numerical models may help to fill the gap between the observation and the models we use for the interpretation Numerical models may help to fill the gap between the observation and the models we use for the interpretation -Independent geophysical data are needed to better constrain the source models and allow to give a more realistic interpretation of the deformation signal

Tensile stress at reservoir’s walls… Sartoris, 1990

In the last years InSAR improved our capability to observe volcanic deformation in space and time… Amelung et al., 2000 Pritchard et al., 2004 Lanari et al., 2004

“Effects of mechanical layering on volcano deformation” Manconi et al., 2007 GJI

…differences in the source parameters (Depth and Pressure) are up to 60% depending on the mechanical contrast Manconi et al., 2007 Homogeneous models and layered models may lead to the same fitness of the data, but… LAYEREDLAYERED

Outline of the talk Outline of the talk - Modeling InSAR data in volcanic areas - Effect of mechanical heterogeneities - Case study: Campi Flegrei (Italy) - Summary and Conclusions

- InSAR: high resolution (in space an time) and accurate representation of the displacement in volcanic areas - Models and procedures used for the interpretation may lead to big uncertainties on the estimation of the source responsible for the ground displacements  Big gap between the accuracy of the observations and of the models!

Point source model: the surface displacement is linear with respect to the pressure change at depth If the position and the geometry is not changing dramatically during the time of observation The inversion of U HHS * will retrieve pressure changes as they were occurred in a fully 3D heterogeneous model!

Standard procedure: Joint inversion of Asc & Desc data assuming as source a Mogi source E(km)N(km)d(km)  P(MPa/yr) min max rms=0.3 cm/year

Applying the “correction factors”, we invert now DATA / K E(km)N(km)d(km)  P(MPa/yr) min (- 40%) max (- 32%) rms=0.3 cm/year

Mogi model