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  • 1
    Publication Date: 2023-01-30
    Description: ASCII files reporting the position time-series, in the Adria-fixed reference frame, of GNSS in the Eastern-Southern Alps The columns are: Time, E, N, Se, Sn, Ren, U, Su, Reu, Rnu, site, long, lati, representing, respectively, epoch (in decimal years), displacement in the East component (in mm), displacement in the North component (in mm), uncertainty (one standard deviation) of the East component (in mm), uncertainty (one standard deviation) of the North component (in mm), correlation between the East and North components, displacement in the Up component (in mm), uncertainty (one standard deviation) of the Up component (in mm), correlation between the East and Up components, correlation between the North and Up components, Station ID (four letters), Longitude of the station (°), Latitude of the station (°).
    Keywords: Alps; displacements; GNSS; GPS; time-series
    Type: Dataset
    Format: application/zip, 12.1 MBytes
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  • 2
    Publication Date: 2024-04-20
    Description: ASCII files reporting the position time-series, in the Eurasia-fixed reference frame, of GNSS in the great Alpine area (excluding Switzerland). The columns are: Time, U, Su, site, long, lati, representing, respectively, epoch (in decimal years), displacement in the Up component (in mm), uncertainty (one standard deviation) of the Up component (in mm), Station ID, Longitude of the station (°), Latitude of the station (°).
    Keywords: 0256_GPS; 0257_GPS; 0258_GPS; 0259_GPS; 0261_GPS; 0264_GPS; 0265_GPS; 0266_GPS; 0268_GPS; 0269_GPS; 0270_GPS; 0272_GPS; 0273_GPS; 0275_GPS; 0276_GPS; 0278_GPS; 0279_GPS; 0280_GPS; 0281_GPS; 0282_GPS; 0285_GPS; 0286_GPS; 0291_GPS; 0292_GPS; 0293_GPS; 0294_GPS; 0296_GPS; 0384_GPS; 0386_GPS; 0388_GPS; 0389_GPS; 0391_GPS; 0392_GPS; 0396_GPS; 0397_GPS; 0398_GPS; 0400_GPS; 0401_GPS; 0402_GPS; 0403_GPS; 0404_GPS; 0405_GPS; 1271_GPS; ACCE_GPS; ACOM_GPS; AGDE_GPS; AGDS_GPS; AGEN_GPS; AGNE_GPS; AIGL_GPS; AILT_GPS; ALPE_GPS; Alps; ALSN_GPS; ALST_GPS; ALU2_GPS; AMB2_GPS; AMPE_GPS; AMST_GPS; ANAY_GPS; ANDA_GPS; ANDE_GPS; ANDF_GPS; AO01_GPS; AOST_GPS; ARAN_GPS; ARDN_GPS; ARNA_GPS; ASIA_GPS; ASTI_GPS; ATHI_GPS; ATPU_GPS; AUBG_GPS; AUTN_GPS; AVAL_GPS; AVR1_GPS; AXPV_GPS; BACT_GPS; BADE_GPS; BAJA_GPS; BAL2_GPS; BANN_GPS; BARC_GPS; BBYS_GPS; BEAU_GPS; BEVA_GPS; BEVE_GPS; BFO1_GPS; BIEL_GPS; BLEI_GPS; BLFT_GPS; BLG2_GPS; BLGN_GPS; BLIX_GPS; BLNO_GPS; BOBB_GPS; BODO_GPS; BOLG_GPS; BOLO_GPS; BOLZ_GPS; BOR__GPS; BORC_GPS; BORM_GPS; BOSC_GPS; BOUS_GPS; BOVE_GPS; BRBZ_GPS; BRET_GPS; BREZ_GPS; BRSE_GPS; BRU1_GPS; BSCN_GPS; BTAC_GPS; BUAN_GPS; BUSL_GPS; BUTE_GPS; BZRG_GPS; CACI_GPS; CAEN_GPS; CAFV_GPS; CAKO_GPS; CAMA_GPS; CAMN_GPS; CANL_GPS; CANV_GPS; CARP_GPS; CARZ_GPS; CAST_GPS; CATU_GPS; CAUS_GPS; CBRY_GPS; CDOM_GPS; CEL9_GPS; CELJ_GPS; CERN_GPS; CERV_GPS; CEVY_GPS; CFRM_GPS; CGIA_GPS; CHA9_GPS; CHAM_GPS; CHAS_GPS; CHBL_GPS; CHBS_GPS; CHI9_GPS; CHIA_GPS; CHIV_GPS; CHMX_GPS; CHOD_GPS; CHOT_GPS; CHPH_GPS; CHRM_GPS; CHTL_GPS; CITD_GPS; CJIH_GPS; CKRO_GPS; CLAP_GPS; CLFD_GPS; CLMT_GPS; COAU_GPS; CODR_GPS; COLI_GPS; COLL_GPS; COMO_GPS; CONC_GPS; CPRA_GPS; CPRI_GPS; CREA_GPS; CREI_GPS; CREM_GPS; CRNO_GPS; CRSN_GPS; CSTN_GPS; CSVI_GPS; CT30_GPS; CTAB_GPS; CTB5_GPS; CUOR_GPS; CVSE_GPS; CZNO_GPS; DALA_GPS; DATE/TIME; DELN_GPS; DEMN_GPS; DEVE_GPS; DIJO_GPS; DILL_GPS; displacements; DJON_GPS; DLBG_GPS; DOCO_GPS; DOJX_GPS; DOMS_GPS; DRUS_GPS; EGLT_GPS; ENTZ_GPS; EOST_GPS; ERCK_GPS; ERLA_GPS; ESAB_GPS; ESCO_GPS; Event label; EZEV_GPS; FAEZ_GPS; FDET_GPS; FDOS_GPS; FELT_GPS; FERA_GPS; FERR_GPS; FETA_GPS; FEUR_GPS; FIED_GPS; FJCP_GPS; FLDB_GPS; FLRC_GPS; FRTT_GPS; FUSE_GPS; GANP_GPS; GARD_GPS; GDIJ_GPS; GENO_GPS; GENU_GPS; GIE1_GPS; GLRA_GPS; GNSS; GNSS data; GNSS Receiver; GOD9_GPS; GORI_GPS; GOZZ_GPS; GPS; GRA__GPS; GRAC_GPS; GRAS_GPS; GRAV_GPS; GRAZ_GPS; GRON_GPS; GRZM_GPS; GSR1_GPS; GUAS_GPS; GUIL_GPS; GUMM_GPS; GUSS_GPS; HKBL_GPS; HUEG_GPS; IENG_GPS; ILBO_GPS; ILIB_GPS; IMP3_GPS; ISLA_GPS; ITIM_GPS; JARG_GPS; JENB_GPS; JOAN_GPS; JOUX_GPS; KARL_GPS; KARX_GPS; KIBG_GPS; KLA__GPS; KLAG_GPS; KOE2_GPS; KRBG_GPS; KTZ2_GPS; KUNZ_GPS; LAND_GPS; LANK_GPS; LASP_GPS; LATITUDE; LBUG_GPS; LEBE_GPS; LECC_GPS; LEIB_GPS; LENE_GPS; LEOB_GPS; LEOP_GPS; LERO_GPS; LFAZ_GPS; LGES_GPS; LIN__GPS; LINZ_GPS; LLIV_GPS; LOA9_GPS; LOAN_GPS; LOD0_GPS; LONGITUDE; LOZN_GPS; LRTZ_GPS; LSIE_GPS; LUCE_GPS; LYSH_GPS; MABZ_GPS; MAGA_GPS; MAKS_GPS; MAN2_GPS; MAN9_GPS; MANT_GPS; MARI_GPS; MARO_GPS; MARS_GPS; MARY_GPS; MATR_GPS; MATT_GPS; MAUP_GPS; MAVE_GPS; MDEA_GPS; MEDI_GPS; MELN_GPS; MENA_GPS; MERY_GPS; MGIS_GPS; MGRD_GPS; MICH_GPS; MINE_GPS; MIRA_GPS; MIRE_GPS; MIST_GPS; MLNO_GPS; MLVL_GPS; MNBL_GPS; MOCA_GPS; MODA_GPS; MOGG_GPS; MOGN_GPS; MONB_GPS; MONC_GPS; MONF_GPS; MONV_GPS; MONZ_GPS; MOP2_GPS; MOPI_GPS; MORB_GPS; MORN_GPS; MPRA_GPS; MPRV_GPS; MRGE_GPS; MRON_GPS; MSEL_GPS; MSGT_GPS; MSMM_GPS; MSRT_GPS; MT01_GPS; MT06_GPS; MTMN_GPS; MTRZ_GPS; MUEJ_GPS; MURZ_GPS; NARB_GPS; NAYC_GPS; NERO_GPS; NICA_GPS; NICE_GPS; NOGT_GPS; NOVE_GPS; NOVG_GPS; NOVR_GPS; NVPT_GPS; OATO_GPS; OBE__GPS; OBE4_GPS; OCHS_GPS; ODEZ_GPS; OGAG_GPS; OPMT_GPS; OSTA_GPS; OTER_GPS; PADO_GPS; PALI_GPS; PAM__GPS; PANA_GPS; PARD_GPS; PARM_GPS; PARO_GPS; PARR_GPS; PASS_GPS; PAT2_GPS; PAVI_GPS; PAYR_GPS; PAZO_GPS; PDOM_GPS; PEJO_GPS; PENC_GPS; PERP_GPS; PERX_GPS; PFA2_GPS; PIA1_GPS; PIAC_GPS; POBU_GPS; PORD_GPS; PORE_GPS; POZE_GPS; POZZ_GPS; PREM_GPS; PREX_GPS; PRIE_GPS; PRIJ_GPS; PRNY_GPS; PTRC_GPS; PTUJ_GPS; PUYA_GPS; PUYV_GPS; PZNA_GPS; RABU_GPS; RADO_GPS; RAMS_GPS; RAYL_GPS; REBO_GPS; REGG_GPS; RGNC_GPS; RIJE_GPS; RISO_GPS; RIXH_GPS; ROET_GPS; RONC_GPS; ROSD_GPS; ROV9_GPS; ROVE_GPS; ROVI_GPS; ROVR_GPS; RSPX_GPS; RST2_GPS; RSTL_GPS; SAAL_GPS; SABA_GPS; SALZ_GPS; SAPP_GPS; SAQU_GPS; SARL_GPS; SARN_GPS; SAUN_GPS; SAUV_GPS; SAV2_GPS; SAVI_GPS; SBG2_GPS; SBLS_GPS; SBPO_GPS; SCDA_GPS; SCHI_GPS; SDNA_GPS; SEEF_GPS; SEES_GPS; SERM_GPS; SERR_GPS; SETE_GPS; SEUR_GPS; SEVI_GPS; SGIL_GPS; SGIO_GPS; SHEI_GPS; SHLA_GPS; SILA_GPS; SILL_GPS; SIRT_GPS; SJDV_GPS; SJPL_GPS; SLOG_GPS; SLVT_GPS; SMNE_GPS; SMSP_GPS; SOMB_GPS; SON9_GPS; SOPH_GPS; SORI_GPS; SOUS_GPS; SPER_GPS; SPRN_GPS; SRBO_GPS; SRJV_GPS; STBX_GPS; STBZ_GPS; STEY_GPS; STJ9_GPS; STMA_GPS; STMR_GPS; STPO_GPS; STPS_GPS; STV2_GPS; SUBO_GPS; SUSE_GPS; TAMB_GPS; TANC_GPS; TANY_GPS; TARO_GPS; TARV_GPS; TEOL_GPS; Text file; Text file (File Size); THNV_GPS; Time series; TLIA_GPS; TLMF_GPS; TLSE_GPS; TOIR_GPS; TORC_GPS; TORI_GPS; TRAI_GPS; TRBL_GPS; TRE5_GPS; TRE8_GPS; TRE9_GPS; TREB_GPS; TREN_GPS; TREX_GPS; TRF2_GPS; TRI1_GPS; TRIE_GPS; TRMO_GPS; TRNO_GPS; TROP_GPS; TRYS_GPS; TUBO_GPS; TVSO_GPS; UDI1_GPS; UDI2_GPS; UNUD_GPS; VACO_GPS; VALJ_GPS; VALX_GPS; VARE_GPS; VAUD_GPS; VDOM_GPS; VELO_GPS; VEN1_GPS; VERB_GPS; VERG_GPS; VERO_GPS; VFCH_GPS; VICE_GPS; VIGE_GPS; VILR_GPS; VISN_GPS; VITT_GPS; VLCH_GPS; VLKM_GPS; VMIG_GPS; VNTE_GPS; VOUR_GPS; VSBO_GPS; WAB2_GPS; WEL2_GPS; WEYE_GPS; WIEN_GPS; WLBH_GPS; WOBG_GPS; WOFU_GPS; WT21_GPS; WTZA_GPS; WTZR_GPS; WTZS_GPS; WTZZ_GPS; ZABO_GPS; ZADA_GPS; ZALA_GPS; ZIDF_GPS; ZIM2_GPS; ZIMJ_GPS; ZIMM_GPS; ZOUF_GPS; ZYWI_GPS
    Type: Dataset
    Format: text/tab-separated-values, 545 data points
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  • 3
    Publication Date: 2024-04-20
    Description: ASCII files reporting the daily GNSS vertical ground displacement time series, in the Eurasia-fixed reference frame, from January 2010 to September 2022 of continuous stations located in the Po river basin. The time series are obtained by analyzing the raw GPS observations using the GAMIT/GLOBK (version 10.71) software, following the standard procedures of the repro2 IGS reprocessing scheme (http://acc.igs.org/reprocess2.html). This is part of a large processing effort, including〉4000 stations in the Euro- Mediterranean and African regions (Serpelloni et al., 2022), where sub-networks, made up of 〈50 stations dynamically and optimally selected based on daily data availability, are processed independently with GAMIT and later tied together using common sub-net tie sites and IGb14 core stations using the GLOBK software. This time series are used to study the effect of the drought occurring since 2021 in Northern Italy. The columns of the files are: Time, U, Su, site, long, lati, representing, respectively, epoch (in decimal years), displacement in the Up component (in mm), uncertainty (one standard deviation) of the Up component (in mm), Station ID, Longitude of the station (°), Latitude of the station (°).
    Keywords: ACCE_GPS; AGNE_GPS; ALE9_GPS; ALIN_GPS; ALSN_GPS; AO01_GPS; AOST_GPS; AQNC_GPS; ARGN_GPS; ASOL_GPS; ASTI_GPS; BDZZ_GPS; BERG_GPS; BIEL_GPS; BIEN_GPS; BOBB_GPS; BOR__GPS; BORM_GPS; BRDI_GPS; BREA_GPS; BREN_GPS; BREU_GPS; BRIX_GPS; BUSL_GPS; CAMN_GPS; CANL_GPS; CARP_GPS; CARZ_GPS; CAST_GPS; CATU_GPS; CAVO_GPS; CDVL_GPS; CEL1_GPS; CHA9_GPS; CHIA_GPS; CHRI_GPS; CIMO_GPS; CNC5_GPS; CNV2_GPS; COCL_GPS; CODI_GPS; COLI_GPS; COLL_GPS; COMO_GPS; CONC_GPS; COPX_GPS; CRE1_GPS; CREA_GPS; CREM_GPS; CRSN_GPS; CSLD_GPS; CUNE_GPS; CUOR_GPS; CURN_GPS; CVNE_GPS; DALM_GPS; DARF_GPS; DATE/TIME; DEMA_GPS; DEMN_GPS; DESE_GPS; DEVE_GPS; displacements; DOMS_GPS; Event label; FE01_GPS; FERA_GPS; FERR_GPS; FOS2_GPS; FRUG_GPS; GAVI_GPS; GAZZ_GPS; GNSS; GNSS data; GNSS Receiver; GOZZ_GPS; GPS; GRAV_GPS; GRN1_GPS; GSTN_GPS; GUAS_GPS; IENG_GPS; LATITUDE; LDNS_GPS; LEC1_GPS; LECC_GPS; LGNN_GPS; LOD0_GPS; LOD2_GPS; LODI_GPS; LOMO_GPS; LONGITUDE; LUI9_GPS; LUIN_GPS; LVFR_GPS; MAGA_GPS; MAN3_GPS; MAN9_GPS; MANT_GPS; MARX_GPS; MCAR_GPS; MENA_GPS; MIL2_GPS; MLNO_GPS; MO01_GPS; MO02_GPS; MO03_GPS; MO05_GPS; MODE_GPS; MOGE_GPS; MON8_GPS; MONC_GPS; MOND_GPS; MONF_GPS; MONV_GPS; MONZ_GPS; MOPS_GPS; MORB_GPS; MRGE_GPS; NERO_GPS; NOVA_GPS; NOVR_GPS; NVR2_GPS; NVRA_GPS; OATO_GPS; ORZI_GPS; OSTA_GPS; PALA_GPS; PAMX_GPS; PARM_GPS; PARO_GPS; PAV2_GPS; PAVA_GPS; PAVI_GPS; PERS_GPS; PIA1_GPS; PIAC_GPS; PINE_GPS; PORA_GPS; PR01_GPS; PREM_GPS; PRSE_GPS; PRST_GPS; PTO1_GPS; PTOL_GPS; PVIA_GPS; PVLM_GPS; QUI__GPS; RAMS_GPS; RE01_GPS; REGG_GPS; RONC_GPS; RSPX_GPS; RUMI_GPS; SAV2_GPS; SAVI_GPS; SBPO_GPS; SERR_GPS; SEVI_GPS; SGIP_GPS; SIR2_GPS; SMAR_GPS; SOND_GPS; SONP_GPS; STUE_GPS; SUSA_GPS; TARO_GPS; Text file; Text file (File Size); time-series; TNUS_GPS; TOGR_GPS; TORC_GPS; TORI_GPS; TRNO_GPS; TRTN_GPS; TRVG_GPS; UNF0_GPS; UNFE_GPS; VARE_GPS; VARZ_GPS; VEBG_GPS; VERB_GPS; VERC_GPS; VERL_GPS; VERR_GPS; VIC__GPS; VIGE_GPS; VIGX_GPS; VLFR_GPS
    Type: Dataset
    Format: text/tab-separated-values, 178 data points
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  • 4
    Publication Date: 2019-04-02
    Description: We apply a blind source separation algorithm to the ground displacement time series recorded at continuous Global Positioning System (GPS) stations in the European Eastern Alps and Northern Dinarides. As a result, we characterize the temporal and spatial features of several deformation signals. Seasonal displacements are well described by loading effects caused by Earth surface mass redistributions. More interestingly, we highlight a horizontal, nonseasonal, transient deformation signal, with spatially variable amplitudes and directions. The stations affected by this signal reverse the sense of movement with time, implying a sequence of dilatational and compressional deformation that is oriented normal to rock fractures in karst areas. The temporal evolution of this deformation signal is correlated with the history of cumulated precipitations at monthly time scales. This transient horizontal deformation can be explained by pressure changes associated with variable water levels within vertical fractures in the vadose zones of karst systems. The water level changes required to open or close these fractures are consistent with the fluctuations of precipitation and with the dynamics of karst systems
    Description: Published
    Description: 4413-4430
    Description: 2T. Deformazione crostale attiva
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 5
    Publication Date: 2021-09-17
    Description: Fluctuations in groundwater content may produce surface deformation and affect the elastic properties of the Earth’s crust. In this study we evaluate the temporal variations of the Earth’s crust elastic properties (in the form of relative seismic-velocity variations) in a tectonically active region in northern Italy characterized by the presence of karst systems. In this area, GPS measurements already revealed hydrologically-induced deformation, modulated by changes in groundwater storage. We study the relation of our seismological observations with the geodetic and hydrological results and identify the effects of groundwater-content variations in the seismic-velocity perturbations. Our results show that hydrologically-induced changes in karstic media produce significant seismic-velocity perturbations, therefore its role in tectonic-stress adjustment studies must not be ignored. Depth sensitivity analysis of our results constrain the crustal perturbations to range between 1 and 4 km depth. Results from scattering imaging locate the crustal perturbations along the main karst systems.
    Description: Published
    Description: e2021GL093191
    Description: 7T. Variazioni delle caratteristiche crostali e "precursori"
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 6
    Publication Date: 2021-12-14
    Description: The 2016–2017 Central Italy earthquake sequence struck the central Apennines between August 2016 and October 2016 with Mw ∈ [5.9; 6.5], plus four earthquakes occurring in January 2017 with Mw ∈ [5.0; 5.5]. We study Global Positioning System time series including near- and far-field domains. We use a variational Bayesian independent component analysis technique to separate the post-seismic deformation from signals caused by variation of the water content in aquifers at hundreds of meters of depth and of the soil moisture. For each independent component, realistic uncertainties and a plausible physical explanation are provided. We focus on the study of afterslip on the main structures surrounding the mainshock, highlighting the role played by faults that were not activated during the co-seismic phase in accommodating the post-seismic deformation. We report aseismic deformation occurring on the Paganica fault, which hosted the Mw 6.1 2009 L'Aquila earthquake, suggesting that static stress transfer and aseismic slip influence the recurrence time of nearby (∼50 km further south of the mainshocks) segments. A ∼2–3 km thick subhorizontal shear-zone, clearly illuminated by seismicity, which bounds at depth the west-dipping normal faults where the mainshocks nucleated, also shows aseismic slip. Since afterslip alone underestimates the displacement in the far-field domain, we consider the possibility that the shear zone marks the brittle-ductile transition, assuming the viscoelastic relaxation of the lower crust as a mechanism contributing to the post-seismic displacement. Our results suggest that multiple deformation processes are active in the first 2 years after the mainshocks.
    Description: Published
    Description: e2021JB022200
    Description: 2T. Deformazione crostale attiva
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 7
    Publication Date: 2022-07-05
    Description: In this work we present and discuss new geodetic velocity and strain-rate fields for the Euro-Mediterranean region obtained from the analysis of continuous GNSS stations. We describe the procedures and methods adopted to analyze raw GPS observations from 〉4000 stations operating in the Euro-Mediterranean, Eurasian and African regions. The goal of this massive analysis is the monitoring of Earth’s crust deformation in response to tectonic processes, including plate- and micro-plate kinematics, geodynamics, active tectonics, earthquake-cycle, but also the study of a wide range of geophysical processes, natural and anthropogenic subsidence, sea-level changes, and hydrology. We describe the computational infrastructure, the methods and procedures adopted to obtain a threedimensional GPS velocity field, which is used to obtain spatial velocity gradients and horizontal strain-rates. We then focus on the Euro-Mediterranean region, where we discuss the horizontal and vertical velocities, and spatial velocity gradients, obtained from stations that have time-series lengths longer than 6 and 7 years, which are found to be the minimum spans to provide stable and reliable velocity estimates in the horizontal and vertical components, respectively. We compute the horizontal strain-rate field and discuss deformation patterns and kinematics along the major seismogenic belts of the Nubia-Eurasia plate boundary zone in the Mediterranean region. The distribution and density of continuous GNSS stations in our geodetic solution allow us to estimate the strain-rate field at a spatial scale of ~27 km over a large part of southern Europe, with the exclusion of the Dinaric mountains and Balkans.
    Description: The GNSS data analysis center described in this work is realized and maintained by different founding resources and projects, including EPOS-MIUR, the Department of Italian Civil Protection and Istituto Nazionale di Geofisica e Vulcanologia agreement (Annex A), Programma Operativo Nazionale (PON) GRINT, ILG Minerbio, MISE DGISSEGINGV 2020 agreement, Med-MFC. FP is supported by the project MUSE, funded by the Istituto Nazionale di Geofisica e Vulcanologia (INGV), within which the re-analysis discussed in this work has been developed.
    Description: Published
    Description: 907897
    Description: 2T. Deformazione crostale attiva
    Description: JCR Journal
    Keywords: GNSS data processing ; time series analysis ; horizontal strain rates ; vertical ground velocities ; Euro- Mediterranean region
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
    Publication Date: 2023-10-26
    Description: Changes in continental water storage generate vertical surface deformation, induce crustal stress perturbations, and modulate seismicity rates. However, the degree to which regional changes in terrestrial water content influence crustal stresses and the occurrence of earthquakes remains an open problem. We show how changes in groundwater storage, computed for a ∼1,000 km 2 basin, focus deformation in a narrow zone, causing large horizontal, nonseasonal displacements. We present results from a karstic mountain range located at the edge of the Adria-Eurasia plate boundary system in Northern Italy, where shortening is accommodated across an active fold-and-thrust belt. The presence of geological structures with high permeabilities and of deeply rooted hydrologically active fractures focus groundwater fluxes and pressure changes, generating transient surface horizontal displacements up to 5 mm and perturbations of crustal stress up to 25 kPa at seismogenic depths. The background seismicity rates appear correlated, without evident temporal delay, with groundwater storage changes in the hydrological basin. With no evidence of pore pressure propagation from the hydrologically active fractures, seismicity modulation is likely affected by direct stress changes on faults planes.
    Description: Published
    Description: e2020JB020586
    Description: 2T. Deformazione crostale attiva
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
    Publication Date: 2023-01-16
    Description: We study the time series of vertical ground displacements from continuous global navigation satellite system (GNSS) stations located in the European Alps. Our goal is to improve the accuracy and precision of vertical ground velocities and spatial gradients across an actively deforming orogen, investigating the spatial and temporal features of the displacements caused by non-tectonic geophysical processes. We apply a multivariate statistics-based blind source separation algorithm to both GNSS displacement time series and ground displacements modeled from atmospheric and hydrological loading, as obtained from global reanalysis models. This allows us to show that the retrieved geodetic vertical deformation signals are influenced by environment-related processes and to identify their spatial patterns. Atmospheric loading is the most important process, reaching amplitudes larger than 2 cm, but hydrological loading is also important, with amplitudes of about 1 cm, causing the peculiar spatial features of GNSS ground displacements: while the displacements caused by atmospheric and hydrological loading are apparently spatially uniform, our statistical analysis shows the presence of N–S and E–W displacement gradients. We filter out signals associated with non-tectonic deformation from the GNSS time series to study their impact on both the estimated noise and linear rates in the vertical direction. Taking into account the long time span of the time series considered in this work, while the impact of filtering on rates appears rather limited, the uncertainties estimated from filtered time series assuming a power law plus white noise model are significantly reduced, with an important increase in white noise contributions to the total noise budget. Finally, we present the filtered velocity field and show how vertical ground velocity spatial gradients are positively correlated with topographic features of the Alps.
    Description: Francesco Pintori has been supported by the project “Multiparametric and mUltiscale Study of Earthquake preparatory phase in the central and northern Apennines (MUSE)”, funded by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). Adriano Gualandi has been supported by European Research Council, H2020 Research Infrastructures (TECTONIC, grant no. 835012). This study has been developed in the framework of the projects MUSE and KINDLE, funded by the “Pianeta Dinamico” INGV institutional project.
    Description: Published
    Description: 1541–1567
    Description: 2T. Deformazione crostale attiva
    Description: JCR Journal
    Keywords: 04.03. Geodesy
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 10
    Publication Date: 2024-01-09
    Description: We analyze the interplay between hydrology, deformation and seismicity in the Matese massif, located in the Italian Southern Apennines. We find that this area is characterized by the concurrent action of two hydrologically-driven processes: the first is the deformation detected by GNSS data in the shallowest part (above the elevation of the major springs) of the Earth crust, in phase with the hydrological forcing; the second is the triggering of seismicity at depth with a delay suggesting a downward diffusive process. We study the first process by applying a Principal Component Analysis to the GNSS displacements time series, aiming to identify a common signal describing the largest data variance. We find that the maximum horizontal displacements associated with the first principal component (PC1) are larger than 1 cm in two GNSS sites and the PC1 temporal evolution is well correlated and in phase with the flow of the largest spring of the region, which we consider as proxy of the water content of the massif. This suggests that the main source of horizontal deformation is the water content fluctuations in the shallow portion of the Matese aquifer, in particular within fractures located in correspondence of the main mapped faults. The deformation rates caused by this process are one order of magnitude larger than the tectonic ones. Finally, we infer the second process by observing the correlation between the background seismicity and the spring discharge with a time lag of 121 days. In our interpretation, downward diffusive processes, driven by aquifer water content variations, propagate pore pressure waves that affect the faults strength favoring the occurrence of micro-earthquakes. This is supported by the values of hydraulic diffusivity (1.5 m^2/s) and rock permeability (3.2-3.8⋅10^−13 m^2), which are compatible with what is observed in karstified limestones.
    Description: In press
    Description: OST2 Deformazione e Hazard sismico e da maremoto
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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