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This study presents an artificial neural network (ANN) model predicting values of sodium adsorption ratio (SAR), residual sodium carbonate, magnesium adsorption ratio, Kellys ratio and percent sodium (%Na) in the groundwater of Nanded tehsil. The 50 groundwater samples were analyzed for different physicochemical parameters such as pH, EC, TDS, Ca, Mg, Na, K, Cl, CO 3 , HCO 3 , SO 4 and NO 3 , for the pre monsoon season 2012. The ANN model is developed through R programming and compared with MS-Excel software. These parameters were used as input variables in the ANN based groundwater quality indices for irrigation suitability prediction. The best back propagation algorithm and neuron numbers were determined for optimization of the model architecture. The resilient backpropagation algorithm with weight back tracking was used for optimization of seven neurons through sensitive analysis. It showed that a network with seven neurons was highly accurate in predicting the irrigation suitability indices. The relative mean squared error, coefficient of determination (R 2) and mean absolute relative error between experimental data and model outputs were calculated. It is observed that is a good agreement between actual data and ANN outputs of groundwater for irrigation suitability indices for training and testing datasets. The spatial distribution maps of measured and predicted values of irrigation indices were prepared using ArcGIS software. Hence, the result confirms that the ANN model is an applied tool to predict the groundwater suitability for irrigation purpose in Nanded tehsil.

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The present study aims to know the groundwater hydrochemistry and its drinking suitability in Kadava river basin through Water Quality Index (WQI) modelling approach. Eighty (80) dug/bore well samples were collected and analysed for the span of dry (pre) and wet (post) monsoon seasons of 2012 by following standard procedures of APHA. According to BIS standard, the parameters, viz., pH, Ca, Mg, Na, Cl, NO 3 , TH and TDS, surpass the threshold limits in both the seasons. It is observed that TDS content in pre-(75%) and post (97.5%)-monsoon seasons is exceeding the desirable limit (500 mg/l). Also, 67.5% (pre-monsoon) and 75% (post-monsoon) of the groundwater samples are beyond the nitrate permissible limit (45 mg/l) of the BIS. The magnesium content in 15 and 37.5% samples is surpassing the permissible limit (100 mg/l) in pre-and post-monsoon seasons. TH content in 15 and 25% samples surpassed the permissible limit (600 mg/l) in pre-and post-monsoon seasons. WQI results demonstrated that 50.0 and 22.5% samples come under good quality of water; 47.5 and 72.5% samples fall in poor water category, while 2.5 and 5.0% samples exhibit very poor category in pre-/ post-monsoon seasons. Hydrochemical characterization based on Durov plot, Chaddha diagram, Gibbs plot and various scatter plots was used to ascertain the types of weathering, influence of rock, precipitation and evaporation, types of reactions, etc., influenced on groundwater composition of the region. The groundwater chemistry is mostly deteriorated due to the influence of agricultural and anthropogenic activities. Spatial variation map of WQI exhibits that groundwater quality is affected mainly in south and few patches in north regions of the study area.