Groundwater Level Prediction using a Neural Network

Abstract

The advance of AI & ML technology has opened new paths in acquiring resources. Nowadays with the rise in global temperatures, the amount of fresh water available for human consumption is on the low. Desert and drought prone areas have it worse off. Finding fresh water is an endeavor requiring resources of manpower and machinery. The existing system of GPR(Ground Penetrating Radar) ,while effective can only be used over small areas which takes up a lot of time and effort.This project illustrates a novel way to find to find the level of groundwater a particular region has accumulated using Neural networks and Machine Learning algorithms by using semi supervised learning based on the dataset of different terrains in that particular region. It utilizes also the dataset of rainfall over that region in the past year. The datasets will together be combined in a neural network to find the area of the region having the most amount of groundwater accumulated. This system proposes a relatively effortless way in finding the availability of groundwater over a particular area.