FloPy is a Python package for creating, running, and post‐processing MODFLOW‐based groundwater flow and transport models. FloPy functionality has expanded to support the latest version of MODFLOW (MODFLOW 6) including support for unstructured grids. FloPy can simplify the process required to download MODFLOW‐based and other executables for Linux, MacOS, and Windows operating systems. Expanded FloPy capabilities include (1) full support for structured and unstructured spatial discretizations; (2) geoprocessing of spatial features and raster data to develop model input for supported discretization types; (3) the addition of functionality to provide direct access to simulated output data; (4) extension of plotting capabilities to unstructured MODFLOW 6 discretization types; and (5) the ability to export model data to shapefiles, NetCDF, and VTK formats for processing, analysis, and visualization by other software products. Examples of using expanded FloPy capabilities are presented for a hypothetical watershed. An unstructured groundwater flow and transport model, with several advanced stress packages, is presented to demonstrate how FloPy can be used to develop complicated unstructured model datasets from original source data (shapefiles and rasters), post‐process model results, and plot simulated results.
ListingAnalyst is a Windows® program for viewing the main output file from MODFLOW-2005, MODFLOW-NWT, or MODFLOW-LGR. It organizes and displays large files quickly without using excessive memory. The sections and subsections of the file are displayed in a tree-view control, which allows the user to navigate quickly to desired locations in the files. ListingAnalyst gathers error and warning messages scattered throughout the main output file and displays them all together in an error and a warning tab. A grid view displays tables in a readable format and allows the user to copy the table into a spreadsheet. The user can also search the file for terms of interest.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.