APPLICATION OF NUMERICAL AND EMPIRICAL MODELS FOR GROUNDWATER LEVEL FORECASTING

Abstract

Groundwater flow modelling is necessary for sustainable management of groundwater resources. Numerical and empirical models can be effectively used for modelling of groundwater flow. The specific boundary conditions, hydrogeological variables and complex aquifer structures are the pre requisite for numerical models but empirical models entirely depends on the data available for input and output parameters. This paper aims to compare the effectiveness of the numerical model using MODFLOW and empirical model Radial Basis Function Neural Network (RBFNN) developed for forecasting the groundwater levels of Athiyannoor Block Panchayath of Trivandrum district, which is categorized as semi critical zone due to the rapid decline in groundwater level. The groundwater flow model was developed with weekly groundwater level data during January 2014 to December 2014. Model was calibrated using trial and error method and groundwater levels at 10 observation wells were simulated. Using the simulated model, groundwater levels were predicted and validated from January 2015 to March 2015. The inputs to the RBFNN model includes weekly groundwater recharge, evapotranspiration, pumping rate in the pumping wells and groundwater levels in these wells at the previous time step. The trained RBFNN model is then validated. The predicted groundwater levels by numerical model and RBFNN models were compared with the observed groundwater levels during the validation period. The performance characteristics of both models indicate that RBFNN model is better than numerical model using MODFLOW for weekly groundwater level forecasting.