Work Description

Date: 8 December, 2020

Dataset Title: Profiles of near-surface rock mass strength across gradients in erosion, burial, and time [Data set]

Dataset Creators: K.F. Townsend, M.K. Clark, and D. Zekkos

Dataset Contact: Kirk Townsend kirkft@umich.edu

Funding: EAR-1528576 (NSF), Department of Earth and Environmental Sciences (University of Michigan), Rackham Graduate School (University of Michigan), Evolving Earth Foundation, Geological Society of America

Key Points:
- We present a novel approach to quantify near-surface rock mass strength on depth profiles from surface and subsurface measurements
- The rock mass strength of sandstone units increases with increasing maximum burial depth prior to exhumation
- Rock strength and erosion rate are positively correlated, which we suggest is driven by critical zone residence time and weathering extent

Research Overview:
Rock mass strength is recognized as an important control on landscape morphology and evolution. However, the controls on rock strength in mountainous topography remain poorly characterized, in part because strength remains challenging to quantify at spatial scales relevant to geomorphology. Here we quantify the mechanical properties of rock masses using subsurface S-wave velocities, Schmidt hammer hardness values, and Geological Strength Index (GSI) observations (Hoek and Marinos, 2000). We produce shallow depth profiles of rock mass shear strength using intact rock hardness as measured from a Schmidt hammer, and assessment of the structure and surface conditions of fractures using GSI, using the Hoek and Brown criterion (Hoek and Brown, 1997; Hoek et al., 2002). We apply these techniques to the Western Transverse Ranges, southern California, USA, where gradients in stratigraphic age and erosion rate allow us to evaluate our methodology. We resolve strength differences of 200 kPa to ~5 MPa that appear to be related to diagenetic changes associated with the maximum burial depth of young clastic sedimentary rocks. For rocks of the same lithologic type, stratigraphic age, and inferred burial histories, we resolve smaller differences in strength (300 kPa – 1.5 MPa) that appear to be positively correlated with mean erosion rates. We suggest that the increase in strength with increasing erosion rate reflects decreased residence time in the weathering zone for ranges experiencing faster fault slip rates. These findings demonstrate up to an order of magnitude variability in strength with respect to burial, erosion, and time for lithologically similar rock masses. As such, lithology alone is unlikely to adequately capture the role of rock strength in landscape evolution.

Methodology:
The data are Schmidt hammer rebound values for intact rock hardness, Geological Strength Index (GSI) observations of outcrop structure and surface conditions, raw seismic velocities collected in the field, and analyzed dispersion curves and S-wave velocity profiles.

Seismic data was recorded using a 16-channel Geometrics ES-3000 portable seismometer, and a 24-channel Geometrics Geode portable seismometer, using 4.5 Hz geophones spaced at 1.5 to 3 m intervals. Impulsive sources were produced by striking a 25-cm square, 5-cm thick plastic plate with a 7.2 kg sledge hammer, and shots were stacked 8-10 times to improve the signal-to-noise ratio. Shots were produced from the end of the array at an offset of 15-20% of the total array length to avoid near-field effects. Total line lengths varied from 53 to 78 m. At 10 sites, a second survey was recorded with a smaller geophone spacing of 0.7 to 1.0 m in order to increase the resolution of the S-wave velocity profile near the surface. These shorter surveys were centered over the midpoint of the longer array.

All active seismic surveys were collected with a source interval of 0.125 milliseconds, a record length of 1.0 seconds, and 8 stacks. All passive seismic data was collected with a sample interval of 2.0 milliseconds, a record length of 30 seconds, and a single stack. Twenty 30-second recordings were made for each passive seismic survey.

We generated S-wave velocity profiles from the .dat files using Geometrics SeisImager/SW software (Pickwin Version 5.2.1.3, WaveEq Version 4.0.1.0, 2016). Initial velocity structures with 30 layers were assumed for each site, and the maximum depth of each profile was set to half the longest measured wavelength.

We assessed outcrop fractures and surface conditions in the field using the Geological Strength Index (GSI) of Hoek & Marinos (2000). Schmidt hammer measurements of intact rock hardness were recorded from the same outcrops as the GSI. We used an "Original Schmidt" (type N, manufactured by Proceq). Reported values are the mean of 20 measurements recorded from a horizontal position.

We used the Hoek & Brown (2002) criterion to calculate shear strength depth profiles, assuming that the minimum principal effective stress is the lateral earth pressure. More details on this methodology are presented in the journal article associated with this data set.

Files contained here:
One spreadsheet containing Schmidt rebound and GSI value for each rock mass characterization site, one spreadsheet containing Vs30 of each seismic survey site, a zipped folder with all raw seismic data collected in the field, and a zipped folder with subfolders for each seismic site containing spreadsheets with analyzed dispersion curves and Vs profiles.

- Rockmass_data.xlsx: contains Schmidt hammer rebound values, GSI values, and site information for each outcrop where rockmass data were collected. Site IDs are generally of the format YY-Schmidt-#, where YY refers to the year the data was collected, and # refers to the site number on each fieldwork trip. For example, 19-Schmidt-8 is the eighth site surveys on a trip in 2019. Where more than one fieldwork trip was made in a given year, the month was included in the site ID. Other abbreviations refer to specific locations (HW = Hollywood; MC = Mandeville Canyon; OJ = Ojai; SCI = Santa Cruz Island; SRI = Santa Rosa Island; WC = Willows Canyon; YB = Yerba Buena Canyon).

- Seismic_Sites.xlsx: contains Vs30, maximum depth of seismic profile, and site information for each outcrop where seismic data were collected.cSite IDs are generally of the format YY-Seismic-# or YY-MMM-#, where YY refers to the year the data was collected, MMM is the month the data was collected, and # refers to the site number on each fieldwork trip. For example, 19-Aug-8 is the eighth site surveys on a trip in August 2019.

- Raw_Seismic_Data.zip: contains three subfolders with raw seismic data collected in the field (.dat files). Each subfolder contains data collected during one of three fieldwork campaigns. In the "Seismic_Sites.xlsx" spreadsheet, the "Raw_file_folder" field indicates which of these three folders contain the raw data associated with each site. The "File Numbers, Active Spacing 1", "File Numbers, Active Spacing 2", and "File Numbers, Passive" fields in the "Seismic_Sites.xlsx" spreadsheet indicate the raw data files for each survey type from each site. Data files are compatible with Geometrics SeisImager/SW software.

- Dispersion_Curves.zip: contains subfolders for each seismic site. Each subfolder contains spreadsheets with the processed active-survey dispersion curve and S-wave velocity profile. Dispersion curve spreadsheets are named with the site ID, followed by "Dispersion_Curve.xlsx". These spreadsheets contain two columns: column A contains frequencies (in Hz), and column B contains phase velocities in units of feet per second. If multiple active-source surveys were collected with different geophone spacings from a single site, or if a survey with passive-source data was collected, additional dispersion curve spreadsheets are included with the end of the file name indicating the spacing and survey type (e.g. "_Dispersion_Curve_Active5ft.xlsx"). The "_Dispersion_Curve_Combined.xlsx" file in these folders are the merged dispersion curves used to produce the Vs profile. Vs profile spreadsheets are named with the site ID, followed by "_Vs.csv". These spreadsheets contain four columns: profile depth in units of feet, the Vs at that depth in ft/s, profile depth in units of meters, and Vs in m/s.

Related publication(s):
Townsend, K.F., Clark, M.K., & Zekkos, D. (2020). Profiles of near-surface rock mass strength across gradients in erosion, burial, and time. Journal of Geophysical Research Earth Surface

References:
- Hoek, E., & Brown, E. (1997). Practical estimates of rock mass strength. International Journal of Rock Mechanics and Mining Sciences, 34(8), 1165–1186. https://doi.org/10.1016/S1365-1609(97)80069-X

- Hoek, E., & Marinos, P. (2000). Predicting tunnel squeezing problems in weak heterogeneous rock masses. Tunnels and Tunnelling International, Part 1-2(November), 1–20.

- Hoek, E., Carranza, C., & Corkum, B. (2002). Hoek-brown failure criterion – 2002 edition. Narms-Tac, 267–273. https://doi.org/10.1016/0148-9062(74)91782-3

Use and Access:
This data set is made available under an Attribution Non-Commercial 4.0 International License (CC BY-NC 4.0).

To Cite Data:
Townsend, K.F., Clark, M.K., & Zekkos, D. (2020). Profiles of near-surface rock mass strength across gradients in erosion, burial, and time [Data set]. University of Michigan - Deep Blue.