TX-SELECT: A Web-Based Decision Support System for Regional Assessment of Potential E. coli Loads Using a Spatially Explicit Modeling Approach

Shubham Jain

## [1] "Time of last build: 2024-03-14 15:09:19.726506"

This project contains the R code for: Jain, S., Srinivasan R., Helton T.J., and Karthikeyan R. (2024), TX-SELECT: A Web-Based Decision Support System for Regional Assessment of Potential E. coli Loads Using a Spatially Explicit Modeling Approach. Manuscript Under Review.

Summary

TXSELECT (https://tx.select.tamu.edu), is a web-based Decision Support System (DSS), which provides a user-friendly interface to run the SELECT model on Texas watersheds. The DSS includes pre-determined watershed specific inputs that can be readily adjusted within the interface based on user preference and/or stakeholder recommendations, obviating the necessity for expensive GIS tools and data extraction.

Required data

Data required to reproduce the results is available at: https://doi.org/10.18738/T8/FWJVKW

File Descriptions

• run_file.R: Step-by-step code to reproduce TXSELECT files and analysis.
• load_libraries.R: Load all required packages.
• load_data.R: Load all GIS and tabular data required for analysis.
• prep_data.R: Process raw GIS data files and datasets for TXSELECT
• create_TXSELECT_tables.R: Prepare TXSELECT predefined input tables in required format.
• estimate_loads.R: Estimate potential loads in all subwatersheds for manuscript analysis.
• analysis.R: Evaluating potential loads by subwatershed categories
• utils.R: Required functions for plots.
• plots_tables.R: Create plots and tables as shown in the manuscript.
• supplementary: Create plots and tables as shown in manuscript supplementary materials.

Instructions

To run the code, follow these steps:

1. Clone Repository: Clone this GitHub repository to your local machine.

   git clone https://github.com/shubhamjain15/TX-SELECT.git

2. Download data: Download required data from: https://doi.org/10.18738/T8/FWJVKW and save it within the current working directory in folder name “data”. All GIS data from the Texas Data Repository can be saved in the sub-folder “GIS” and all tables from GITHUB can be saved in the sub-folder “tables” to run the code directly.

3. Run R code: Run R scripts in the order as listed in run_file.R.