Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/7638
Authors: Bistacchi, A.* 
Griffith, W. A.* 
Smith, S.* 
Di Toro, G.* 
Jones, R.* 
Nielsen, S.* 
Title: Fault roughness at seismogenic depths from LIDAR and photogrammetric analysis
Journal: Pure and Applied Geophysics 
Series/Report no.: /168 (2011)
Issue Date: 2011
DOI: 10.1007/s00024-011-0301-7
Keywords: fualr roughness
Subject Classification04. Solid Earth::04.04. Geology::04.04.06. Rheology, friction, and structure of fault zones 
Abstract: Abstract—Fault surface roughness is a principal factor influencing earthquake mechanics, and particularly rupture initiation, propagation, and arrest. However, little data currently exist on fault surfaces at seismogenic depths. Here, we investigate the roughness of slip surfaces from the seismogenic strike-slip Gole Larghe Fault Zone, exhumed from ca. 10 km depth. The fault zone exploited pre-existing joints and is hosted in granitoid rocks of the Adamello batholith (Italian Alps). Individual seismogenic slip surfaces generally show a first phase of cataclasite production, and a second phase with beautifully preserved pseudotachylytes of variable thickness. We determined the geometry of fault traces over almost five orders of magnitude using terrestrial laser-scanning (LIDAR, ca. 500 to\1 m scale), and 3D mosaics of high-resolution rectified digital photographs (10 m to ca. 1 mm scale). LIDAR scans and photomosaics were georeferenced in 3D using a Differential Global Positioning System, allowing detailed multiscale reconstruction of fault traces in Gocad . The combination of LIDAR and high-resolution photos has the advantage, compared with classical LIDARonly surveys, that the spatial resolution of rectified photographs can be very high (up to 0.2 mm/pixel in this study), allowing for detailed outcrop characterization. Fourier power spectrum analysis of the fault traces revealed a self-affine behaviour over 3–5 orders of magnitude, with Hurst exponents ranging between 0.6 and 0.8. Parameters from Fourier analysis have been used to reconstruct synthetic 3D fault surfaces with an equivalent roughness by means of 2D Fourier synthesis. Roughness of pre-existing joints is in a typical range for this kind of structure. Roughness of faults at small scale (1 m to 1 mm) shows a clear genetic relationship with the roughness of precursor joints, and some anisotropy in the selfaffine Hurst exponent. Roughness of faults at scales larger than net slip ([1–10 m) is not anisotropic and less evolved than at smaller scales. These observations are consistent with an evolution of roughness, due to fault surface processes, that takes place only at scales smaller or comparable to the observed net slip. Differences in roughness evolution between shallow and deeper faults, the latter showing evidences of seismic activity, are interpreted as the result of different weakening versus induration processes, which also result in localization versus delocalization of deformation in the fault zone. From a methodological point of view, the technique used here is advantageous over direct measurements of exposed fault surfaces in that it preserves, in cross-section, all of the structures which contribute to fault roughness, and removes any subjectivity introduced by the need to distinguish roughness of original slip surfaces from roughness induced by secondary weathering processes. Moreover, offsets can be measured by means of suitable markers and fault rocks are preserved, hence their thickness, composition and structural features can be characterised, providing an integrated dataset which sheds new light on mechanisms of roughness evolution with slip and concomitant fault rock production.
Appears in Collections:Article published / in press

Files in This Item:
File Description SizeFormat Existing users please Login
BistacchiEtAlPAGEOPH2011.pdfmain article1.89 MBAdobe PDF
Show full item record

WEB OF SCIENCETM
Citations

64
checked on Feb 10, 2021

Page view(s)

112
checked on Mar 27, 2024

Download(s)

19
checked on Mar 27, 2024

Google ScholarTM

Check

Altmetric