High-Level Project Summary
We developed a machine learning model which predicts the water equivalent thickness of various geographical areas (defined by the GRACE satellite) and provides a better understanding of the locations of underground water supplies and their usability as an alternative to the polluted Ganga River. Being one of the largest water resources in India, the threats the contamination has proposed in the past few years is concerning, especially considering the industrial and agricultural waste being dumped in the tributaries of Ganga. Hence, to prevent further harm, we think it is important to approach this problem with a solution.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
We extracted the data collected from GRACE's database, and cleaned the data using 'pandas'. After pre-processing and training the data, we created a model that predicts the water equivalent thickness (WET) of the various geographical sections in the Ganga Basin. The data we used had WET values (a great way to measure underground water reserves) from the year 2002 to 2021. Based on this data, we have found a line of best fit for the data from Aug 2021 to Aug 2023. While these predictions may not be 100% accurate, they provide us with a proof of concept for other regions and more time, with refinement we can get much better predictions and make use of this data.
For front end, React JS and Node JS, while for backend, numpy, sci kit, learn python, pandas. Along with that, we used Excel and Virtual Studio code.
Space Agency Data
We used data from the GRACE (Gravity Recovery and Climate Experiment) to know the WET values of certain areas in the Ganga Basin, and to hence, train our Machine Learning model.
Hackathon Journey
The devastating news we read about the Ganga River and the associated deaths on the internet inspired us to take or try to take an action towards it.
In this journey, we learnt to work with .nc files and how to use React for frontend.
References
Python - pandas, numpy
Tags
#sustainability
Global Judging
This project has been submitted for consideration during the Judging process.