This repository contains the code for the Canadian Great Lakes Weather Data Service for SWAT (Can-GLWS) application.

Can-GLWS is a Data as a Service (DaaS) platform that allows application users to download SWAT-ready (https://swat.tamu.edu) climate data (historical, climate change scenarios and weather statistics) of a pre-specified region within the Canadian Great Lakes watersheds. The aim of this application is to remove the redundancy associated with SWAT-model weather data preparation. Service / app users simply need to provide / delineate their geographical area of interest (within the Canadian Great Lakes watersheds), and they can subsequently download their desired SWAT-model-ready weather inputs (historical, climate change-related or weather statistics). The area is selected using either i) a map-based interactive polygon drawing tool or ii) user input of a shape file.

Can-GLWS is developed using the R Shiny web framework. Important information regarding the application code is as follows:

• app.R - Contains the R code for the entire application. One of the required packages, i.e., geoshaper, is not available on CRAN. Please refer to https://github.com/RedOakStrategic/geoshaper for installing geoshaper.
• GL_SWAT_all_WGN.csv - Contains a statistical dataset prepared for dissemination using this application.
• Dockerfile - Can-GLWS is hosted as a dockerzied application on a server at University of Guelph. The Dockerfile is provided here as well.

Can-GLWS is currently deployed on a UoG Sever. The large historical and climate change datasets (in SWAT-ready format) being shared with the application are hosted on the server.

Dr. Narayan Shrestha, Dr. Taimoor Akhtar, Uttam Ghimire, Dr. Prasad Daggupati, Dr. Ramesh Rudra, Dr. Pradeep Goel and Dr. Rituraj Shukla, UNIVERSITY OF GUELPH & ONTARIO MINISTRY OF THE ENVIRONMENT, CONSERVATION & PARKS.

The shiny application is developed by Dr. Taimoor Akhtar.

Please Contact Us at: [email protected] for any questions.

If you use our data, application or codes, please cite this repository and its associated DOI.