Prediction and parametric evaluation of water quality on basin of River Brahmani by ANN and GIS

Abstract

Surface water in India flows via 14 main river basins and several medium and small basins. Climate change is influencing precipitation and, as a result, the amount of accessible freshwater, while growing waste water loads are decreasing the quality of surface water and groundwater supplies. Surface water quality is critical and a major environmental problem worldwide. Surface water contamination caused by numerous pollutants is a worldwide issue. The Brahmani River Basin present in Odisha, India, has been chosen for research. From 1991 to 2015, water quality indicators (monthly) were collected and analysed from January to December among the chosen five gauging stations in Odisha. For the analysis, six water quality characteristics are chosen: pH, temperature, dissolved oxygen, biochemical oxygen requirement, electric conductivity, total hardness, and CaCO3. The prediction was performed using an artificial neural network, and the geographical analysis was performed in ArcGIS using the inverse distance weighting approach. For the summer, monsoon, and winter seasons, the coefficient of computation for the artificial neural network among definite and anticipated values of water quality metrics is 1. If current conditions persist, future years will most likely follow a similar trend to the one experienced from 1991 to 2015.