An unofficial SWAT (Soil & Water Assessment Tool) code collection from official historical releases and the scientific community.

Industrial datasets - datasets for evaluating industrial intrusion detection systems on IPAL.

A tool for data preprocess on iTrust SWaT dataset.

The automated workflow for setting up SWAT Models presented in Chawanda et al., 2019 EMS

QGIS Processing provider for SWAT based hydrological modelling

A Python wrapper for executing and calibrating the Soil and Water Assessment Tool (SWAT) in Unix/macOS systems.

This software uses a config file (config.py), which is a settings file, to build and run SWAT+ models. Users can share the config along with their published works to promote transparency as all model options are well documented in the file. Sharing the namelist and data also allows others to reproduce the models from scratch.

NASAaccess is R package that can generate gridded ascii tables of climate (CIMP5) and weather data (GPM, TRMM, GLDAS) needed to drive various hydrological models (e.g., SWAT, VIC, RHESSys, ..etc). The package assumes that users have already set up a registration account(s) with Earthdata login as well as authorizing NASA GESDISC data access. Ple…

An interface for managing SWATPlus input and output files to aid in implementing, and visualizing the impact of land use changes on catchment hydrology in the SWATPlus model

TimeGANs for synthetic data generation in cyber-physical systems using Tensorflow

R scripts for the SWAT model calibration/sensitivity/uncertainty analysis

Oxidized Rust (Idiomatic Rust)

New modules developed for Soil and Water Assessment Tool (SWAT) revision 664

SWAT+ model input data preparation helper

Scripts used to process data and namelist used in Chawanda et al. (2019)

Canadian Great Lakes Weather Data Service for SWAT (Can-GLWS)

A6-MITM is a program which mutates packets using ENIP (Ethernet/IP) and CIP (Common Industrial Protocol) protocols.

Sword World Assistant Tool

Comparative Analysis of Unsupervised Learning Methods for Real-time Anomaly Detection in Industrial Control Systems (ICS)

An approach for anomaly detection in Industrial Control Systems (ICS), using Water Treatment Dataset (SWaT). The implementation incorporates cutting-edge machine learning techniques, including Isolation Forest and Autoencoder models, augmented by Dynamic Time Warping (DTW) algorithm.