Software

This repository contains the code needed to reproduce the D-Claw simulation presented in Karasözen and others (2025). D-Claw is numerical software package for simulating granular-fluid flows (George and others, 2025; George & Iverson, 2014; Iverson & George, 2014). This code simulates a landslide generated tsunami scenario in which one of the Surprise Inlet landslides described by...

This release introduces the ocelote package. The package includes routines to run assessments, manage assessment metadata, and upload assessments to Amazon S3 and ScienceBase. The package consists of the following commands: * authenticate s3: Acquires, tests, and stores credentials for S3 uploads * authenticate sciencebase: Acquires, tests, and stores credentials for ScienceBase uploads...

This is a permanent record of all current and former versions of the PWFDF data specification. The spec describes: the organization of assessments on ScienceBase, ScienceBase metadata unique to the collection, and the files, data, and metadata contained within individual assessments.

D-Claw is a software library for the simulation of dense granular flows over spatially variable topography. D-Claw builds on clawpack, is written in Fortran, and has a python wrapper. The code is hosted on code.usgs.gov and mirrored on github. D-Claw is supported on Linux/Unix only.

This release allows users to select the CRS of exported files, and to specify alternate configuration files. The release also updates wildcat’s backend for compatibility with pfdf 3+. Documentation: https://ghsc.code-pages.usgs.gov/lhp/wildcat/ Release Notes: https://ghsc.code-pages.usgs.gov/lhp/wildcat/resources/release-notes/1.1.0.html

This release adds the `data` package, which provides routines to download commonly used datasets from the internet. The release also provides pfdf tutorials as Jupyter Notebooks, improves array broadcasting in the `gartner2014` and `staley2017` modules, and introduces the `RasterMetadata` class (which manages raster metadata without loading data arrays to memory). Documentation: https:/...

Grfin Tools (an acronym of Growth + flow + inundation) is a set of software tools for portraying areas potentially impacted by runout from landslides or inundation from geophysical mass-flows (such as debris flows) with or without growth as they travel. Grfin Tools allows users to assess the effects of a wide range of factors that can influence mobility. The software also enables runout

This repository contains the code needed to reproduce computations presented in Barnhart and others (under review). This readme contains instructions for reproducing results and a list of the git hashes for each source repository used. Computation for this manuscript was done on the U.S. Geological Survey Denali High Performance Computer (Falgout and others, 2024). Barnhart, K.R., George...

Digger is a python package that provides a number of pre- and post-processing tools for landslide runout modeling. Many aspects of digger have been tailored for use with the D-Claw model. It may also be useful for initializing and postprocessing the results of other runout models. D-Claw requires input files and generates output files in very specific formats. Simulation output generates...

Wildcat is a software tool to assess and map post-wildfire debris-flow hazards. The package can be run from the command line or within Python. This 1.0.0 release includes the core routines to: * Preprocess input datasets, * Design stream segment networks, * Estimate debris-flow hazards and rainfall thresholds, and * Export results to common GIS formats (such as Shapefiles and GeoJSON)...

This release introduces the core statsgo-cog package. This package provides functions to convert soil data fields in the STATSGO archive from shapefiles to cloud optimized GeoTiffs (COGs). The package contains 3 main commands: * download: Downloads the STATSGO shapefile archive from ScienceBase * merge: Merges the shapefile archive into a single shapefile spanning all of the continental...

This release substantially improves support for working with datasets in a mix of coordinate reference systems. The release also introduces new classes for working with spatial metadata, adds confidence intervals to the Gartner 2014 volume model, adds support for additional unit systems, and improves the user experience when filtering the stream segments in a network.