Elevation-Groundwater Analysis Toolkit (EGAT)
Description
The Elevation-Groundwater Analysis Toolkit (EGAT) provides open-source code, documentation, and sample data for evaluating the interaction between topography, groundwater dynamics, and climate stressors across multiple spatial scales. Developed in Python, EGAT integrates hydrological, climatic, and land use/land cover datasets to quantify groundwater risk patterns and test elevation-centric assumptions in water management. The dataset includes: (i) Python scripts for data preprocessing, groundwater–elevation analysis, and visualization, (ii) a detailed user manual with installation and workflow instructions, and (iii) example datasets comprising DEM subsets, climate data samples, and groundwater monitoring records. While large raw datasets (e.g., Sentinel-2, SRTM DEM, CRU TS) are not included due to size, direct links to open-access repositories are provided. EGAT supports reproducible research in groundwater modeling, enabling users to replicate case studies, adapt workflows for local datasets, and extend the framework to other regions. By publishing this dataset, we aim to promote transparency, reusability, and collaborative development of physics-informed water resource assessment tools.
Files
Steps to reproduce
1. Download the Dataset Access the EGAT dataset package from Mendeley Data (or GitHub archive). Extract the files to a working directory. 2. Install Dependencies Install Python 3.9+ Install required libraries using: pip install -r requirements.txt Optional: Install ArcGIS (ArcMap 10.1+) for GIS-based workflows. 3. Prepare Input Data Download sample DEM, groundwater, climate, and LULC data (links provided in Data Availability). Place these files in the Example_Data/ folder, or update file paths in the scripts. 4. Run EGAT Scripts Execute the main pipeline: python main.py This will process elevation, groundwater, and climate inputs, and generate outputs such as correlation plots, groundwater stress maps, and summary tables. 5. View Outputs Results are saved in the Results/ folder, including maps (GeoTIFF), plots (PNG/PDF), and processed CSV tables. 6. Reproducibility All workflows are documented in the provided README.md and User Manual.
Institutions
- Loyola College
- University of Madras