An intelligent estimation model for water quality parameters assessment at Periyakulam Lake, South India

Abstract Water is an essential natural resource for the survival of living beings in the world. Freshwater bodies significantly support ecological and economic activities in each state or country, especially India, which has large number of rivers, lakes, ponds, and wetlands. Notably, lake water is critically polluted due to industrial effluents, encroachment, eutrophication, garbage dumping, poor drainage, and climate changes, which have a severe effect on water quality. Hence, monitoring and assessment of water quality over time is important for minimizing the negative effects to an ecosystem, and it greatly helps to sustain valuable aquatic species. In this chapter, an intelligent estimation model is developed using Kalman filter integrated with a synergistic fibroblast optimization (SFO) algorithm for forecasting water quality parameters. The developed predictive model is evaluated with real-time water samples collected from Ukkadam Periyakulam Lake, Coimbatore, and promising results provide qualitative information to enhance water quality in this lake.