Study of the effectiveness of Wavelet Genetic Programming model for Water Quality Analysis in the Uttar Pradesh region 

Abstract Water constitutes an essential part of the Earth as it helps in making the environment greener, supporting people to survive and in transporting various nutrients and minerals. But all these factors are drastically impacted due to rising water pollution and its poor sanitation leading to poor water quality. In India, according to the latest survey, due to the excessive use of chemicals by the industries, fertilizers and pesticides by the farmers, various water bodies are getting contaminated, causing a lack of good quality water suitable for consumption. About 2 lakh people die every year due to various diseases caused by consumption of contaminated water. Not only the surface water, groundwater and river water are also getting contaminated. Hence, there is a need to analyze the quality of water in the existing water sources. In this work, a workflow is proposed for analyzing the water quality in selected regions of Uttar Pradesh state. The proposed work uses a hybrid Wavelet Genetic Programming model for analysis and visualization of 13 rivers of Uttar Pradesh region. Prediction of Dissolved Oxygen (DO) level is used as the determinant for water quality assessment. Continuous Wavelet Transform is utilized to decompose the DO dataset and the decomposed DO values are treated as input variables for the model using Morlet wavelet function. The results have proved that the proposed model is suitable for the accurate prediction of DO values.