Forecasting of Groundwater Level in Multiple Wells using Machine Learning Models

Accurate forecasting of groundwater levels is crucial for sustainable water resource management and environmental planning. This article explores the use of machine learning for accurate groundwater level predictions. In this study three machine learning models including artificial neural network ANN, long-short term memory LSTM and Extreme Gradient Boosting decision tree XGBoost technique were used to predict ground water level. We incorporate deep water surface measurements and meteorological data as key parameters to enhance forecasting accuracy.