Abstract
Abstract. Manual approaches for analyzing fault scarps in the field or with existing software can be tedious and time-consuming. Here, we introduce an open-source, semiautomated, Python-based graphical user interface (GUI) called the Monte Carlo Slip Statistics Toolkit (MCSST) for estimating dip slip on individual or bulk fault datasets that (1) makes the analysis of a large number of profiles much faster, (2) allows users with little or no coding skills to implement the necessary statistical techniques, (3) and provides geologists with a platform to incorporate their observations or expertise into the process. Using this toolkit, profiles are defined across fault scarps in high-resolution digital elevation models (DEMs), and then relevant fault scarp components are interactively identified (e.g., footwall, hanging wall, and scarp). Displacement statistics are calculated automatically using Monte Carlo simulation and can be conveniently visualized in geographic information systems (GISs) for spatial analysis. Fault slip rates can also be calculated when ages of footwall and hanging wall surfaces are known, allowing for temporal analysis. This method allows for the analysis of tens to hundreds of faults in rapid succession within GIS and a Python coding environment. Application of this method may contribute to a wide range of regional and local earthquake geology studies with adequate high-resolution DEM coverage, enabling both regional fault source characterization for seismic hazard and/or estimating geologic slip and strain rates, including creating long-term deformation maps. ArcGIS versions of these functions are available, as well as ones that utilize free, open-source Quantum GIS (QGIS) and Jupyter Notebook Python software.
Highlights
The field of tectonic geomorphology is increasingly employing computer-based algorithms for displaying and analyzing digital topographic data (Whittaker et al, 2008; Kirby and Whipple, 2012; Zhou et al, 2015; Whipple et al, 2016)
In this paper we introduce a new Python-based graphical user interface (GUI), the Monte Carlo Slip Statistics Toolkit (MCSST), that streamlines and improves on the approach for calculating slip statistics from fault scarps present in highresolution digital elevation models (DEMs)
The MCSST allows users to quickly and accurately estimate fault slip across several faults imaged in DEMs
Summary
The field of tectonic geomorphology is increasingly employing computer-based algorithms for displaying and analyzing digital topographic data (Whittaker et al, 2008; Kirby and Whipple, 2012; Zhou et al, 2015; Whipple et al, 2016). Several relatively complete and distinct sets of computational tools and libraries exist for completing an array of complex topographic and fault zone analysis at the fault zone and outcrop scale (e.g., SPARTA, Structure-fromMotion) (Westoby et al, 2012; Bemis et al, 2014; Hodge et al, 2019), including those that attempt to resolve the full 3-D slip vector (Mackenzie and Elliot, 2017) These toolboxes are important because fault zones can be extraordinarily complex and require methods for systematically estimating net slip and slip rates across them (Fossen and Rotevatn, 2016). Where original landform geometries are known or can be inferred, fault scarp profiles from GPS surveys or transects across high-resolution digital elevation models (DEMs) can be used to characterize components of fault slip (DeLong et al, 2010; Spencer, 2010; Klimczak et al, 2018). A detailed user manual that lays out step-bystep usage of these tools and discusses how the underlying functions and algorithms work is included as a Supplement and within the code repository
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