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Journal of South American Earth Sciences 58 (2015) 1e8

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Journal of South American Earth Sciences

journal homepage: www.elsevier .com/locate/ jsames

Strain rates estimated by geodetic observations in the BorboremaProvince, Brazil

Giuliano Sant'Anna Marotta a, *, George Sand França a, Jo~ao Francisco Galera Monico b,Francisco Hil�ario R. Bezerra c, Reinhardt Adolfo Fuck d

a Observat�orio Sismol�ogico, Instituto de Geociencias, Universidade de Brasília, Brasília, DF, Brazilb Departamento de Cartografia, Faculdade de Ciencias e Tecnologia, Universidade Estadual Paulista Júlio de Mesquita Filho, Presidente Prudente, SP, Brazilc Departamento de Geologia, Centro de Ciencias Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazild Laborat�orio de Geocronologia, Instituto de Geociencias, Universidade de Brasília, Brasília, DF, Brazil

a r t i c l e i n f o

Article history:Received 26 June 2014Accepted 29 December 2014Available online 7 January 2015

Keywords:Borborema ProvinceGeodetic networkSouth American plateSurface strains

* Corresponding author.E-mail address: marotta@unb.br (G.S. Marotta).

http://dx.doi.org/10.1016/j.jsames.2014.12.0060895-9811/© 2015 Elsevier Ltd. All rights reserved.

a b s t r a c t

The strain rates for the Borborema Province, located in northeastern Brazil, were estimated in this study.For this purpose, we used GNSS tracking stations with a minimum of two years data. The data wereprocessed using the software GIPSY, version 6.2, provided by the JPL of the California Institute ofTechnology. The PPP method was used to process the data using the non-fiducial approach. Satelliteorbits and clock were supplied by the JPL. Absolute phase center offsets and variations for both thereceiver and the satellite antennaes were applied, together with ambiguity resolution; corrections of thefirst and second order effects of the ionosphere and troposphere models adopting the VMF1 mappingfunction; 10� elevation mask; FES2004 oceanic load model and terrestrial tide WahrK1 PolTid FreqDe-pLove OctTid. From a multi annual solution, involving at least 2 years of continuous data, the coordinatesand velocities as well as their accuracies were estimated. The strain rates were calculated using theDelaunay triangulation and the Finite Element Method. The results show that the velocity direction ispredominantly west and north, with maximum variation of 4.0 ± 1.5 mm/year and 4.1 ± 0.5 mm/year forthe x and y components, respectively. The highest strain values of extension and contraction were0.109552 � 10�6 ± 3.65 � 10�10/year and �0.072838 � 10�6 ± 2.32 � 10�10/year, respectively. In general,the results show that the highest strain and variation of velocity values are located close to the PotiguarBasin, region that concentrates seismic activities of magnitudes of up to 5.2 mb. We conclude that thecontraction direction of strain is consistent with the maximum horizontal stress derived from focalmechanism and breakout data. In addition, we conclude that the largest strain rates occur around thePotiguar Basin, an area already recognized as one of the major sites of seismicity in intraplate SouthAmerica.

© 2015 Elsevier Ltd. All rights reserved.

1. Introduction

Several studies involving deformation analysis of the earthsurface using geodetic observations have been conducted to un-derstand the dynamics of the strain applied to intraplate regions.Among them, Li et al. (2001) established a model of rigid motion,elasticeplastic and strain for eight intraplate blocks and peripheralareas in China. The model was consistent with the strain parame-ters, obtained using geological and geophysical methods. Calais

et al. (2006) combined independent geodetic solutions, using thecontinuous data from GPS stations covering the central and easternregions of the US and showed that surface deformation in the NorthAmerican Plate interiors is qualitatively consistent with that ex-pected from GIA (Glacial Isostatic Adjustment). They also showedthat, with 95% confidence level, no residual motion was detected inthe New Madrid Seismic Zone. Cloetingh et al. (2006) combinedseismicity data and strain indicators with geodetic and geomor-phological observations to show that the deformation of thenorthern Alpine Foreland is still ongoing and will continue in thefuture. Banerjee et al. (2008) studied three of the major historicintraplate earthquakes (Magnitude > 7.5) that happened in theIndian subcontinent, which, considering the surface velocities

G.S. Marotta et al. / Journal of South American Earth Sciences 58 (2015) 1e82

determined from GPS data, suggest the possibility of significantintraplate deformation with shortening rate from north to south of0.3 ± 0.05 � 10�9/year. Southward motion from 4 to 7 mm/yearlocated over the Shillong plateau, in northeastern India, reflects thefast shortening and danger of a large earthquake associated withactive thrust faults that limit the plateau.

Regarding the South American plate, most field models of activestresses suggest the presence of stress formed predominantly bythe Mid-Atlantic ridge push, collision with the Nazca plate, intra-plate density variations, drag or basal resistance exerted by theasthenosphere, and resistance associated to faults. According toLima (2000), the South American plate is under horizontalcompression and shortening, which can be demonstrated by acompilation of stress data, numerical field models of intraplatestresses and results based on geodetic observations. Based on theprocessing of GPS, SLR and DORIS data collected over the course ofthree years (1994, 1995 and 1996), Norabuena et al. (1998) andCr�etaux et al. (1998) reported that about 10e15 mm/year of crustalshortening occur in the interior of the South American plate, thusindicating that the Andes region is still in a process of continuousformation. Marotta et al. (2013a) estimated deformation betweenpre- and post-seismic periods in Latin America using geodetic ob-servations and from their results it was possible to analyze theinteractions between lithospheric plates from the directions ofcontraction and extension between points located on separateplates.

Turning to the interior of the South American plate, the modelsof strain currently known are derivedmostly from studies involvingseismological and geological data, such as focal mechanisms andbreakouts, according to work presented by Zoback (1992),Assumpç~ao (1992, 1998), Coblentz and Richardson (1996), Limaet al. (1997), Ferreira et al. (1998, 2008), Bezerra et al. (2011),Heidbach et al. (2009), and Lopes et al. (2010a).

Recent studies about strain rates by geodetic observations seekto associate them to known strain models. From the coordinatesand velocities estimated for a grid of points of geodetic network,Marotta et al. (2013b) estimated strain rates for the South Americanintraplate region and suggest that the large superficial motionsoccur in regions with more heterogenous geological structures andmultiple rupture events; that large earthquakes are concentrated inareas with predominantly contraction strain rates, orientedsouthwestenortheast; and, that the change of direction in themovement of the geodetic points in the South American plateshows predominantly tectonic influence with some variations thatcan be attributed to the strain interactions with local geologicalcharacteristics. However, little is known about the relationshipbetween strain rates and stress directions and structures in theupper crust in intraplate areas.

This work aims to determine the strain rates of the BorboremaProvince, northeastern Brazil, from velocity vectors estimated byGPS positioning methods using data of a geodetic network ofcontinuous monitoring. We seek to understand these strain ratesand their relationship with the present-day stress field and thestructural framework of the region.

2. Tectonic strain at the Borborema Province

Brazil is located in the low seismic activity continental intraplateregion of South America. However, there are some regions in Brazilcharacterized as active seismogenic zones, such as the Northeast,which features recurring seismic activity (Takeya et al., 1989;Ferreira et al., 1998; Lopes et al., 2010b; Rossetti et al., 2011) asso-ciated with recent tectonic activity (Fig. 1).

The Borborema Province is located in the eastern margin of theSouth American plate. The coastal areas of the mainland and the

interior comprise a Precambrian crystalline basement overlain byCretaceous and Cenozoic sedimentary basins Almeida et al. (2000).These basins were formed mainly by the reactivation of the shearzones during the breakup of Pangea in the Cretaceous de Castroet al. (2012). The Neogene record consists primarily of the Barrei-ras Formations, of Miocene age, and Quaternary sedimentary de-posits Rossetti et al. (2011).

The Borborema Province constitutes the central part of a wideorogenic belt deformed during the Pan-African/Brasiliano orogeny(750e540 Ma), covering an area of 900 km long and 600 kmwide.Ductile shear zones are among the most striking features of theBorborema Province. They form continental scale structures linkedto Precambrian terrains. In some cases, they mark a collage of largeProterozoic crustal blocks. Several of the major shear zonescontinue in Africa, in a Pangea pre-breakup reconstruction.

Seismological and studies using data from the oil industryfocused on the Borborema Province presented preliminary esti-mates of the stresses in the region. Assumpç~ao (1992) presented acompilation of the lithospheric stress directions for the SouthAmerican continent and the main patterns of the intraplate stressregional field. He also suggested that in northeastern Brazil, seis-micity is characterized mainly by strike-slip earthquakes in theupper crust. A model was proposed for the region where the stressfield would be the result of an overlapping of regional and localstress fields, characterized by EeW-trending compression andNeS-trending extension. Lima et al. (1997) studied the crustalstresses in Brazil and presented a detailed analysis of breakout dataperformed in 541 wells distributed in sedimentary basinsthroughout the country, from which 481 were from basins alongthe continental margin and 60 were from intracratonic basins. Theauthors verified in the Potiguar Basin that average orientation ofmaximum horizontal stresses (SHmax) by breakout is consistentwith the orientation of the maximum horizontal stresses (SHmax)inferred from focal mechanisms around the basin. The breakoutsalso show that (SHmax) is approximately parallel to the northerncoastline. From the results, they suggested that this pattern is alsoconsistent with the model by Assumpç~ao (1992).

In northeastern Brazil, indicated that earthquakes tend to occuraround the border of the Potiguar Basin in the crystalline basement,with strike-slip focal mechanisms at depths between 1 and 12 km(Assumpç~ao, 1998; Ferreira et al., 1998; Bezerra et al., 2007). Thesestudies also suggested that the combination of regional stresses,local flexion effects of thick sediment loads and a presumablyweaker crust, explains the main patterns of seismicity in the area.

While studying a series of earthquakes with local networks,Ferreira et al. (2008) and Lopes et al. (2010a) helped to increase thestress database in Brazil. From the analysis of clusters of seismicactivities along the Pernambuco shear zone, included in the Bor-borema Province, the works showed the reactivation of Pernam-buco shear zone with normal and strike-slip faults, thus indicatingNeS-trending extension and EeW-trending compression.

3. Study area

The study area shown in Fig. 2 consists of the entire regioncovered by a network of geodetic points in the Borborema Province.

Among the points that make up the geodetic network are thosebelonging to Brazilian Continuous GNSS Network (RBMC) (<www.ibge.gov.br>, accessed on 01/02/2013), controlled by BrazilianInstitute of Geography and Statistics (IBGE), and Potiguar GPSNetwork (RGP), controlled by the Federal University of Rio Grandedo Norte (UFRN).

The geodetic points belonging to RBMC, besides being forcivilian use, are also part of the SIRGAS-CON network, which is usedto perform the Geocentric Reference System for the Americas

G.S. Marotta et al. / Journal of South American Earth Sciences 58 (2015) 1e8 3

(SIRGAS). Its definition follows that of IERS ITRS and its realizationare compatible with those of the ITRF (IERS Terrestrial ReferenceFrame).

The geodetic points of RGP (Fig. 2) were deployed for tectonicstudies around the Potiguar Basin, in locations that present recur-rent seismic activity, different lithological types and near activeshear zones.

4. Estimating coordinates and velocities vectors for thepoints of the geodetic network

In this work, daily coordinate were estimated for each selectedpoint in the study area for the period between 2004 and 2010 and,subsequently, these values were combined into a single solution ofcoordinates and velocities for a preset period of time. For this,version 6.2 of the GIPSY software, provided by the JPL of the Cali-fornia Institute of Technology, was used (<https://gipsy-oasis.jpl.nasa.gov/>, 2012).

The Precise Point Positioning (PPP) method (Zumberge et al.,1997; Monico, 2000) by using the module written in Perl calledgd2p.pl (GPS Data 2 Position) was used to process the daily GPSdata. The individual solutions were combined to provide the co-ordinates and velocities of each station. The Reference Frame usedwas IGS 2008 and the reference epoch for the coordinates esti-mation was 2008.0.

Fig. 1. Seismic activity in continental Brazil between 1720 and 2013.Source: <www.obsis.unb.br/websisbra>, 2013.

The processing strategy involved to treat the errors that origi-nated in the satellites, atmosphere, local environment, as well asfrom the characteristics of the station, antenna and receiver, ac-cording to the error source classification described by Seeber(2003) and Monico (2008). Among the information used to cor-rect the aforementioned errors, it should be cited: the use of preciseorbits (non-fiducial) and clocks; absolute phase center offsets andvariations for both the receiver and the satellite antennaes, pro-vided by IGS (International GNSS Service); ambiguity resolution;correction of the first and second order effects of the ionosphereand troposphere model adopting the VMF1 (Vienna MappingFunction 1); 10� elevation mask; FES2004 oceanic load model andterrestrial tide WahrK1 PolTid FreqDepLove OctTid.

In order to determine the strain the tridimensional geocentricCartesian system (X, Y, Z) was transformed to the geocentricgeodetic system (l, f, h) and, from this to the local geodetic system(x, y, z), following methodology described by Monico (2008).

The coordinates of the geocentric geodetic system were usedboth for forming triangular connections between the geodeticpoints, using the Delaunay triangulation, and for defining the ori-gins of the local geodetic system, given by the centroid position ofeach triangle.

Once the origin and points that make up each triangle weredefined, which is called the network, the tridimensional co-ordinates in the local geodetic system were calculated.

Fig. 2. Network of geodetic points in the Borborema Province.

Table 1Period of GPS data used.

Geodetic point GPS data

2004 2005 2006 2007 2008 2009 2010 2011 2012

ALAR X X X X XBRFT X X X X X X XCGPT X X XCHPT X XCRAT X X X X X X X X XPBCG X X X X XPEPE X X X X XPISR X X X XRECF X X X X X X X X XRNMO X X X XRNNA X X X XTGPT X X X

G.S. Marotta et al. / Journal of South American Earth Sciences 58 (2015) 1e84

5. Resulting planimetric strain rates for the geodetic network

From a small plane with dimensions defined according to aCartesian coordinate system, a two-dimensional stress state wasconsidered, oriented so that there are no surface forces in thevertical direction. The Finite ElementsMethodwas used to estimatethe strain rates when considering a plane in a two-dimensionalstress state. According to Deniz and Ozener (2010), this method isadequate to determine the strain parameters independent of thedata, since it uses the relationship of the distance between points orbase lines, for two distinct periods. According to Marotta et al.(2013a), this method applied to a geodetic network does not ac-count for translations, only the strains.

The strain rates determined using the Finite Element methodwas performed for each flat region formed for each plane definedby the Delaunay triangulation.

The linear expression to determine the strain rate 3 resultingfrom a baseline in a network is given by Marotta et al. (2013b):

ε ¼ S0 � SDt$S

(1)

where S and S0 are the planimetric distances between two networkpoints at times 1 and 2, respectively. Dt is the time interval of 1 yearbetween times 1 and 2. To determine S0, the coordinates at time 2,estimated from the coordinate values and velocity vectors at time 1,were used.

Since the analyzed geodetic network was formed by trianglesproperly oriented, we used a general equation to estimate the strainrate resulting in the two-dimensional state as function of the strainparameters (exx, exy, eyy) and azimuth (Az) calculated for each base(Turcotte and Schubert, 2002; Deniz and Ozener, 2010; Marottaet al., 2013a). The principal components of maximum (E1) andminimum (E2) strain rate were also estimated together with itsorientation (b).

ε ¼ exx$cos2 Azþ exy$sin 2Azð Þ þ eyy$sin2Az (2)

E1 ¼ 12

exx þ eyy� �þ

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiexx � eyy� �2 þ 2$exy

� �2q� �(3)

E2 ¼ 12

exx þ eyy� ��

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiexx � eyy� �2 þ 2$exy

� �2q� �(4)

b ¼ arctanexy

E1 � exy

� �(5)

To estimate the accuracy of each step, the Covariance Propaga-tion Law for a given general model Y ¼ F(X) was used (Gemael,1994; Marotta et al., 2013b):

CY ¼ J$CX$JT (6)

Table 2Positions and velocities (V) of the geodetic stations, in m/year.

Geodetic point Geodetic coordinates Velocities (local geodetic system)

l (�) f (�) h (m) Vx (m/yr) sVx (m/yr) Vy (m/yr) sVy (m/yr) Vz (m/yr) sVz (m/yr)

ALAR �36.653420 �9.749223 266.20249 �0.00342 0.00039 0.01171 0.00016 0.00024 0.00042BRFT �38.425538 �3.877446 21.66479 �0.00396 0.00022 0.01129 0.00007 �0.00078 0.00023CGPT �37.301461 �5.806386 108.95806 �0.00387 0.00110 0.01282 0.00039 0.00449 0.00116CHPT �38.299572 �4.418423 26.45550 �0.00577 0.00152 0.00975 0.00051 �0.00152 0.00160CRAT �39.415606 �7.238017 436.02616 �0.00174 0.00018 0.01169 0.00006 �0.00125 0.00019PBCG �35.907138 �7.213676 534.07148 �0.00450 0.00037 0.01164 0.00014 �0.00118 0.00040PEPE �40.506124 �9.384417 369.08498 �0.00362 0.00036 0.01222 0.00014 0.00070 0.00037PISR �42.702759 �9.030692 366.78415 �0.00576 0.00064 0.01159 0.00026 0.00895 0.00064RECF �34.951517 �8.050962 20.11785 �0.00420 0.00017 0.01213 0.00007 �0.00631 0.00018RNMO �37.325465 �5.204233 23.36422 �0.00322 0.00051 0.01382 0.00018 �0.00434 0.00054RNNA �35.207708 �5.836139 45.94238 �0.00358 0.00049 0.01167 0.00018 0.00044 0.00054TGPT �38.040481 �5.919480 158.46580 �0.00472 0.00084 0.01301 0.00030 0.00275 0.00088

G.S. Marotta et al. / Journal of South American Earth Sciences 58 (2015) 1e8 5

where CY is the variance-covariance matrix of Y; J, the Jacobianmatrix formed by the partial derivatives; and Cx, the variance-covariance matrix of X.

Once the strain parameters and subsequently, the principalcomponents of the strain rate were estimated, the latter wascompared with the stress directions known in the region.

6. Results and discussions

The velocity vectors of each one of the 13 geodetic pointslocated in the Borborema Province are described in Table 2 andshown in Fig. 2. The results were estimated using the GPS trackingdata collected continuously over a period of at least two years(Table 1).

Fig. 3. Planimetric velocities (V) of the geodetic stations, i

The results (Table 2 and Fig. 3) show that the velocity direction ispredominantly west and north with maximum variation of4.0 ± 1.5 mm/year and 4.1 ± 0.5 mm/year for the x and y compo-nents, respectively. This variationwas observed between the pointsCHPT and CRAT and the points CHPT and RNMO, where one of themis located on the edge of the Potiguar Basin, near the shear zonesSenador Pompeu, and in regions with higher seismic intensities.

In the vertical component, the maximum velocity variation of15.3 ± 0.7 mm/year was observed between the points PISR andRECF. These points are close to Pernambuco Lineament.

Assuming that all these variations are due to local and regionaltectonic strains, the component values of the strain rate werecalculated (Table 3 and Fig. 4), where the influence of the strains onthe continental crust, more precisely on the Earth surface can be

n mm/year, estimated in the ITRF08 reference frame.

Table 3Strain rates and principal strain components in planimetry.

Network of points triangulated Geodetic coordinates of the barycenter of each network Planimetric analysis

Principal components of strain

l (�) s (�) E1 (10�6/yr) sE1 (10�6/yr) E2 (10�6/yr) sE2 (10�6/yr) b (�) sb (�)

RNMO RNNA BRFT �36.986237 �4.972606 0.001554 0.000005 �0.039037 0.000076 �41.953116 0.140363PISR PEPE CRAT �40.874830 �8.551042 0.011144 0.000005 �0.003966 0.000013 15.517682 0.075426BRFT PISR CRAT �40.181301 �6.715385 0.019700 0.000018 �0.002906 0.000003 �10.571091 0.019565CHPT BRFT CRAT �38.713572 �5.177962 0.017737 0.000045 �0.072838 0.000232 �26.967033 0.152550TGPT CHPT CRAT �38.585220 �5.858640 �0.005518 0.000021 �0.021433 0.000045 �30.090746 0.092771RNMO BRFT CHPT �38.016858 �4.500034 0.109552 0.000365 �0.008175 0.000007 48.698127 0.177530PEPE ALAR CRAT �38.858383 �8.790552 0.003405 0.000005 �0.003518 0.000005 83.647887 0.107769RNMO CHPT TGPT �37.888506 �5.180712 0.024608 0.000044 �0.018514 0.000018 41.743309 0.118347CRAT ALAR PBCG �37.325388 �8.066972 �0.000092 0.000004 �0.007190 0.000005 �47.941522 0.166972CGPT RNNA RNMO �36.611545 �5.615586 0.015327 0.000041 0.001044 0.000008 15.630026 0.263421TGPT CGPT RNMO �37.555802 �5.643366 0.015519 0.000034 0.008622 0.000117 10.969766 0.304666TGPT CRAT PBCG �37.787742 �6.790391 0.011791 0.000025 �0.009352 0.000007 �19.860865 0.019034PBCG ALAR RECF �35.837358 �8.337954 �0.000844 0.000010 �0.001325 0.000006 �2.679201 0.329224CGPT PBCG RNNA �36.138769 �6.285401 0.002676 0.000015 0.001913 0.000022 2.261410 0.323240CGPT TGPT PBCG �37.083027 �6.313181 0.012419 0.000143 0.001553 0.000040 34.313603 0.716995PBCG RECF RNNA �35.355454 �7.033593 0.007046 0.000015 �0.003423 0.000004 48.199594 0.101697

G.S. Marotta et al. / Journal of South American Earth Sciences 58 (2015) 1e86

seen. The values of strain rate and the values of standard deviationare expressed as 10�6/year.

In Table 3, the region formed by the geodetic points RNMO, BRFTand CHPT shows the highest strain value of extension, with0.109552�10�6/year ± 3.65�10�10/year, while the geodetic pointsCHPT, BRFT and CRAT show the highest strain value of contraction,with �0.072838 � 10�6/year ± 2.32 � 10�10/year. In general, theresults in Table 3 and Fig. 5 show that the highest strain values arelocated near the Potiguar Basin, region that concentrates seismic

Fig. 4. Principal compon

activities of magnitudes �5.2 mb (Ferreira et al., 1998, 2008;Bezerra et al., 2011).

The strains, seen by the principal component of strain rates,extend predominantly in the northeast direction. Extensionalstrains are roughly perpendicular to the northern shoreline of theBorborema Province, whereas the contraction strains are roughlyparallel to the coast. To the eastern shoreline of the BorboremaProvince, there is contraction in the perpendicular direction andextension parallel to the coast. Towards the inland of Borborema

ents of strain rates.

Fig. 5. Principal components of strain rates estimated by geodetic observations and strains by focal mechanisms and breakouts.

G.S. Marotta et al. / Journal of South American Earth Sciences 58 (2015) 1e8 7

Province, strain rate values are smaller for both extension andcontraction. It is, therefore, suggested that these small values areassociated with the low density of geodetic points and low con-centration of seismic activity.

The principal components of strain rates were, for purpose ofresult verification, compared to stress directions estimated byinversion of focal mechanisms and breakouts (Fig. 5) compiled fromAssumpç~ao (1992, 1998), Coblentz and Richardson (1996), Limaet al. (1997), Ferreira et al. (1998, 2008), França et al. (2004),Bezerra et al. (2007, 2011) and Lopes et al. (2010a).

Fig. 5 shows that the directions of the strains estimated bygeodetic observations are in agreement with the stress directionsestimated by other instrumental methods, except in places withlower density of geodetic points. However, it is suggested that thegeodetic network, independent of density, can present regionalstrains, which in turn, may bring insight on how strain and stressesinteractions occur in regions with or without seismic activity. Thiscan be confirmed by the good agreement between strain directionsof the principal component of strain rates aligned with the ductileshear zones within the study site, as shown in Fig. 4, where we cansuggest present-day fault reactivation.

7. Conclusion

Based on the coordinates estimated fromGPS data and using theDelaunay triangulation and Finite Element Method, the strain ratesof the geodetic network located in the Borborema Province wereestimated and compared with the stress directions estimated byfocal mechanisms and breakouts.

In the Potiguar Basin region, the vectors of the principal com-ponents of strain presented suggest a direct correlation withseismic events by the behavior of the contractions and extensionsfound in studies involving focal mechanisms and breakout.

Towards the inland in the Borborema Province we conclude thatdespite the lower values compared to the Potiguar Basin, theprincipal components of the strain rates are parallel to the directionof major ductile shear zones in the Borborema Province.

Consequently, the sensitivity of the GPS network is verified andit is conclude that the applied strain distribution originating fromthe terrestrial dynamics, whether local, regional or global, affectsthe geodetic network studied in different ways and, thus, it can beused as a complement in intraplate tectonic studies. We alsoconclude that the methodology presented is consistent with theproposed goals.

Acknowledgments

The authors thank SIRGAS for providing geodetic preliminaryinformation used in the analyses. Thank JPL for providing theversion 6.2 of the GIPSY OASIS software. This research is supportedCNPq/INCT 573713/2008-1. We special thank all technicians fromUnB, USP and UFRN, for their efforts in the field work, maintenanceof equipment, and preliminary readings of data. GSF and JFGMthank CNPq for their PQ grants. Ruth Vidotti Kakogiannos forimprovement of the English.

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