Over the last several years, many more contaminants have had a substantial impact on the quality of the water. It directly affects both the environment and human health. The WQI serves as a gauge for effective water management. The fight against water pollution benefits from knowledge about water quality, including how to model it for predictions. Establishing a trustworthy prediction model for river water quality that can determine the index value based on river water quality requirements is the study's main goal. In order to determine which characteristics were important in determining the quality of river water, this study will examine and contrast the performance of many classification models and algorithms. Eleven sample sites have been selected for the data collecting process, which are dispersed among various locations along the river that flows through Kerala and Tamil Nadu. The dissolved oxygen content, temperature, pH, hardness, chloride, and other seven environmental parameters that impact the quality of water are used to calculate the water quality index. Water quality prediction model is developed using supervised machine learning methods, such as logistic regression and support vector repressor. To classify the water quality index, a classification model was created using SVM classifiers. The SVM classifier classifies the water quality index with an accuracy of 83%, whereas the logistic repressor predicts the water quality index well. The developed models performed well in terms of categorization and prediction of the water quality index.
Top1. Introduction
To human beings needs water as the most critical fundamental requirement for life since living organisms need water to sustain their life on earth. Although it hardly has been an object of science fiction, better quality and quantity in the amount of available water on our planet is more important to life on earth than any of the other things we may be able to think about. When the pollution level is moderate, it's common for water-dwelling species to inhabit the area. But when the pollution rises, the oxygen levels in the water decline, resulting in dire consequences. About the quality of environmental water sources such as lakes, rivers, and streams, a high proportion of them has standards that prove their value. Guidelines are applicable not only to bodies of water of all types for all applications and uses.
This harms the plant or the soil therefore distorting the entire ecosystem. Industrial applications also have to have different types of water quality as particular processes are of a different nature mainly for the consumption of humanity. The cheapest methods of getting freshwater like ground, and surface water are the natural waters resources. The human as well as the industrial activities and other environmental actions contaminate natural resources. For instance, irrigation water should not have excessive salinity or contain poisonous substances which can be transferred to plants or soil, thereby destroying the ecosystems.
Industrial water particularly suitable for commercial uses, different properties are desired depending on the nature of the industrial processes. Some of the sources of fresh water which are considered to be low-priced include ground and surface water, they are classified as natural water resources. Yet that sources can be contaminated by human? Industrial activities and other natural processes. The spoiling of water quality at an alarming pace has been caused by the fast industrial development as a result. Even so, infrastructures, unaccompanied by public consciousness, and less clean features considerably alter standards of drinking water. In reality, hazards brought about by polluted water for drinking are so threatening to the health and that of the environment and infrastructures used at large.
According to the World report, some 1.5 million people die annually, due to illnesses caused by diseases related to poor sources of water. It is obviously noted that in developing countries the nation’s 80% of health conditions are as a result of the contaminated water. Each year results in an estimate of five million deaths and 2.5 billion people with diseases. It is advocated not to forget the temporal measurement for anticipating the Water Quality (WQ) types to avoid missing the seasonal differences in the WQ. But the combined model dissimilarity is superior to that of using a single model for prediction of WQ. Methodologies have been proposed that make the prediction and modelling of the WQ. The rapid progress of industrialization has resulted in a marked deterioration of water quality. Inadequate infrastructure, lack of recognition, and unsanitary practices greatly contribute to the decline in the quality of drinking water. This contaminated water poses a serious threat to public health, presenting a multitude of long-term consequences that not only affect our well-being but also harm the environment and our infrastructure. Recent studies conducted in the United States provide evidence to support this alarming issue.
Annually about 2 million people do not receive the deserved outcome of their situation the reason of which can be different. The problem of improper water supply systems contributes to that the figures of severe health conditions, in developing countries, make almost 15 million. Every year around 2.5 billion people adds up to the cases and eventually lose their lives by taking waterborne diseases. To this, statistics show that half a million people annually die from these waterborne illnesses. In human cruelty deaths or even accidents as well as the terrorist attacks are investigated too. Unfortunately, it is not possible to put these innovative techniques out now because it has not been proven that these methods can predict and study water quality (WQ) accurately. As a result, it is essential to explore the temporal characteristics of water quality patterns in view of annual changes not forgetting temporal shifts, so as to understand this critical parameter.