Groundwater is a crucial resource across agricultural, civil, and industrial sectors. The
prediction of groundwater pollution due to various chemical components is vital for planning …

With the rapid increase in the volume of data on the aquatic environment, machine learning
has become an important tool for data analysis, classification, and prediction. Unlike …

The consumption of water constitutes the physical health of most of the living species and
hence management of its purity and quality is extremely essential as contaminated water …

Integration of the Internet of Things (IoT) into the fields of wastewater treatment and water
quality prediction has the potential to revolutionize traditional approaches and address …

Forecasting water quality parameters helps plan crop selection and irrigation strategies but
is often costly because many parameters are required, particularly in develo** nations …

Artificial intelligence (AI) and machine learning (ML) are novel techniques to detect hidden
patterns in environmental data. Despite their capabilities, these novel technologies have not …

In the present study, multilayer perceptron (MLP) neural network and support vector
regression (SVR) models were developed to assess the suitability of groundwater for …

Ascertaining water quality for irrigational use by employing conventional methods is often
time taking and expensive due to the determination of multiple parameters needed …

An attempt has been adopted to predict the As and NO 3− concentration in groundwater
(GW) in fast-growing coastal Ramsar region in eastern India. This study is focused to …

Groundwater quality is typically measured through water sampling and lab analysis. The
field-based measurements are costly and time-consuming when applied over a large …