Climatic data analysis for groundwater level simulation in drought prone Barind Tract, Bangladesh: Modelling approach using artificial neural network

This study presents implementation of non-linear autoregressive model with exogenous inputs (NARX) of Artificial neural network (ANN), used for groundwater level (GWL) simulation to predict its weekly level up to 52 weeks ahead in selected 14 Permanent Hydrograph Stations (PHSs) in the drought prone Barind Tract in the northwestern part of Bangladesh and is considered to be the first attempt of this type in the country. In this regard, the weekly historical time series climatological data (rainfall, temperature, humidity and evaporation) during 1980–2017 have been used as input variables to forecast GWL. Auto-correlation of GWL time series data to find out the dependent relationship between current GWL to the previous level were carried out and cross-correlation between GWL and rainfall…