Data for "The influence of fault geometrical complexity on surface rupture length"

This repository contains the data generated in and some data from the FDHI database (Sarmiento et al., 2021) required to run the scripts used in our publication "The effect of fault geometrical complexity on surface rupture length".

Table of contents:

File/directory
File type
Notes
References (if applicable)

geometrical_complexity_shapefiles_v1.zip
Shapefiles

Shapefiles for the breached and unbreached geometrical features in Rodriguez Padilla et al. 202X. The name of each file is the geometrical feature, followed by whether the feature is breached or unbreached, followed by the name of the event the feature was mapped from.

Example: stepover_breached_Borrego.shp

Note some shapefiles are empty because that feature type was not observed for a given event. 

Rodriguez Padilla et al. (202X)

Sarmiento et al. (2021) https://www.risksciences.ucla.edu/nhr3/fdhi/databases

Regional_maps.zip
Shapefiles
Shapefiles for each regional fault map (Qfaults for US, NZAFD for New Zealand, AFEAD for Asia and the Middle East, and GEM for remaining regions)
USGS and CGS, Langridge et al. (2016), Bachmanov et al. (2021), Styron and Pagani (2020)

event_rupture_shp.zip
Shapefiles
Shapefiles with the primary ruptures for each of the events as mapped in the FDHI database

Sarmiento et al. (2021) https://www.risksciences.ucla.edu/nhr3/fdhi/databases

data_FDHI.xlsx
Spreadhsheet
Event information, including magnitude, date, displacement distribution, etc. from the FDHI database. The data that is compiled in the spreadsheet can be accessed from the appendices of the FDHI database.

Sarmiento et al. (2021)

https://www.risksciences.ucla.edu/nhr3/fdhi/databases

reflines_FDHI.zip
Shapefiles

ECS reference lines for each event from the FDHI database (Sarmiento et al., 2021) in shapefile format

Sarmiento et al. (2021)

https://www.risksciences.ucla.edu/nhr3/fdhi/databases

geometries.csv
Spreadsheet

Feature geometries, including lengths, widths, angles, and other measured attributes, generated using the Matlab code measure_EQgates.m in Github repository https://github.com/absrp/passing_probabilities_EQgates

This csv file also serves as the input for the Jupyter Notebook for estimating passing probabilities and event likelihoods.

Rodriguez Padilla et al. (202X)