Abstract: Groundwater level is an indicator of groundwater availability ,groundwater flow and the physical characteristics of the groundwater system. Management of water resources requires input from hydrological studies. This is mainly in the form of estimation of the magnitude of a hydrological parameters. The factors that influence and control the groundwater level fluctuation were determined to develop a forecasting model and examine its potential in predicting groundwater level. Models for prediction of water table depth were developed based on Artificial Neural Networks(ANN) with different combinations of hydrological parameters. The best combination was confirmed with factor analysis. The input parameters for groundwater level forecasting were derived using Time Series Analysis (TSA).Mamom river basin in Trivandrum district was chosen as the study area as its groundwater resources have been used as the main source for drinking and agricultural purposes.