Ground Water Level Prediction

The groundwater is one of the biggest asset. The continuous decline of underground water is one of the crucial factors that affect the development of economy and society. Based on the availability the water is to be exploited. The population growth and emerging climate change lead to water scarcity problem. This would have increased the demand for ground water. But the groundwater is not distributed equally. In our proposed system we state the annual ground water availability for future use. It can be classified by machine learning algorithms such as logistic regression, random forest and decision tree. The input variables used for modelling is based on the recharge of water and usage of water in various season. The regression task needs less training data set and can achieve good performance. The aim of this paper is to compare and analyse the machine learning algorithm for ground water level along with their accuracy. In this paper the machine learning algorithm is used to classify and detect the ground water availability levels in India.