An unofficial SWAT (Soil & Water Assessment Tool) code collection from official historical releases and the scientific community.
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Updated
Nov 29, 2023 - Fortran
An unofficial SWAT (Soil & Water Assessment Tool) code collection from official historical releases and the scientific community.
A tool for data preprocess on iTrust SWaT dataset.
A Python wrapper for executing and calibrating the Soil and Water Assessment Tool (SWAT) in Unix/macOS systems.
QGIS Processing provider for SWAT based hydrological modelling
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…
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.
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
R scripts for the SWAT model calibration/sensitivity/uncertainty analysis
TimeGANs for synthetic data generation in cyber-physical systems using Tensorflow
SWAT+ model input data preparation helper
RU - Лучший ботнет сносер, на хосте держиться около двух ста аккаунтов телеграмм , которые отправляют жалобу на тот или иной аккаунт , так же канал и чат , на бот , и на канал , даже закрытый. Данный сносер может снести аккаунты за менее чем 3 минуты с долгой отлёгой, так же с носит закрытые телеграмм каналы , но за более длительное время.
New modules developed for Soil and Water Assessment Tool (SWAT) revision 664
Canadian Great Lakes Weather Data Service for SWAT (Can-GLWS)
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.
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