GNGTS 2018 - 37° Convegno Nazionale

704 GNGTS 2018 S essione 3.2 course, shallow processes, such as runoff, evapo-transpiration and shallow infiltration, act at delta scale causing a loading effect on the Earth’s surface. This mechanism explains great part of the annual and biennial periodic signals observed in the geodetic data. Significant differences are obtained by using or not the hydrological models for retrieving the subsidence velocity. References Bock Y. and Melgar D.; 2016: Physical applications of GPS geodesy: a review . Rep. Prog. Phys., 79 106801 (119 pp). Bondesan M. and Simeoni U.; 1983: Dinamica e analisi morfologica statistica dei litorali del Delta del Po e alle foci dell’Adige e del Brenta . Memorie di Scienze Geologiche, 36 , 1–48. Carminati E., Doglioni C. and Scrocca D.; 2006: I fragili equilibri della Pianura Padana . Le Scienze, 450 , 88–94. Dong D., Fang P., Cheng M.K. and Miyazaki S.; 2002: Anatomy of apparent seasonal variations from GPS-derived site position time series . J. Geophys. Res., 107 (B4). Gelaro R., McCarty W., Suárez M.J., Todling R. et al., 2017; The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) . J. Clim., 30 , 5419-5454. Grinsted A., Moore J.C. and Jevrejeva S.; 2004: Application of the cross wavelet transform and wavelet coherence to geophysical time series . Nonlinear Proc. Geophys., 11 , 561–566. Rodell M., Houser P.R., Jambor U., Gottschalck J. et al.; 2004: The Global Land Data Assimilation System . Bull. Amer. Meteor. Soc. , 85 (3), 381–394. Simeoni U. and Corbau C.; 2009: A review of the Delta Po evolution (Italy) related to climatic changes and human impacts. Geomorphology, 107 (1–2), 64–71. Teatini P., Tosi L. and Strozzi T.; 2011: Quantitative evidence that compaction of Holocene sediments drives the present land subsidence of the Po Delta, Italy . Journal of Geophysical Research: Earth Surface, 116 (B08407). Vitagliano E., Di Maio R., Scafetta N., Calcaterra D. and Zanchettin D.; 2017: Wavelet analysis of remote sensing and discharge data for understanding vertical ground movements in sandy and clayey terrains of the Po Delta area (Northern Italy) . Journal of Hydrology, 550, 386–398. MICROSEISMIC MONITORING OF AN UNSTABLE ROCK FACE: PRELIMINARY EVENT LOCATION Z. Zhang 1 , D. Arosio 2 , A. Hojat 3,1 , L. Zanzi 1 1 Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Milano, Italy 2 Dipartimento di Scienze Chimiche e Geologiche, Università di Modena e Reggio Emilia, Modena, Italy 3 Department of Mining Engineering, Shahid Bahonar University of Kerman, Kerman, Iran Introduction. Microseismic monitoring has been increasingly used in rockfall studies in the last two decades. Event location is one of the basic processes in microseismic monitoring, following signal recording and signal classification. Event location is an interesting field of research that has been investigated in several studies. For instance, Spillmann et al. (2007) used a nonlinear probabilistic localization algorithm based on nested-grid search (Lomax et al. , 2000) to determine the hypocenter parameters. Colombero (2017) also adopted this localization algorithm using the oct-tree importance sampling method (Lomax and Curtis, 2001). Events were routinely located by Helmstetter and Garambois (2010) within a uniform velocity model. In these rockfall-related cases, the location procedure encounters several difficulties: (1) Heterogeneous distribution of P wave velocity; (2) Inaccurate first arrival picking; (3) Undistinguishable P and S waves; (4) Proper localization algorithm. Our research aims at tackling some of the abovementioned difficulties and focuses on Mount San Martino rock cliff (northern Italy), where a microseismic monitoring system has been installed since 2013. An automatic classification scheme is now working on this system to select microseismic events related to the stability of the rock mass. In this work, we present the preliminary results on event location related to trigger tests performed before a tomographic survey and an event location exercise with a uniform velocity model.