Journal of Civil and Environmental Engineering

Water Quality Prediction Modeling of Manchar Lake, Pakistan using Machine Learning Algorithms

Abstract

Aqsa Zahid

Lakes serve as a primary source of fresh water for the local communities and play an important role in improving the environmental well-being of an area. However, around the world, the quality of the lakes is continuously degrading due to various natural and manmade activities. To study the water quality parameters of the lake, this study utilizes Manchar Lake as the study area. The main objective of the research was to investigate the application of machine learning algorithms to predict the water quality index and quality parameters, aiming to overcome the limitations of traditional physical monitoring methods. Multiple machine learning algorithms were evaluated based on their performance measures, including accuracy, precision, recall and F1 score metrics. The study identified decision tree, random forest and gradient boosting emerging as the most accurate algorithms for predicting the output. These findings highlight the importance of employing advanced machine learning algorithms for timely and accurate assessment of water quality and the development of management and conservation strategies. Such strategies are important to conserve the ecological integrity of freshwater lakes such as Manchar Lake.