Spatial Prediction of Nitrate Concentration Using GIS and ANFIS Modelling in Groundwater

Groundwater contamination by nitrate becomes a major problem in agricultural areas. Nitrate pollution in the groundwater of Coimbatore district of India has been investigated. Seventy-one observation wells within the study area were selected. The samples were collected in three stages with 6 months interval during the years 2011 and 2012. The input for creating an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) model is the average of calcium, electrical conductivity, sodium, chlorides, hardness, potassium and the concentration of nitrate was the output from the model. Results of the best ANFIS model were assessed by deterministic, geostatistical and kernel smoothing methods using GIS. Out of the five models developed, ANFIS model V predicts nitrate concentration with 90% accuracy and less root mean square error (0.0934). The results from model V are given as input in GIS to predict spatial nitrate concentration in groundwater. Kriging method is more accurate in estimating nitrate concentration over the study area.