The water quality index (WQI) model is a popular tool for evaluating surface water quality. It
uses aggregation techniques that allow conversion of extensive water quality data into a …

There has been an unsettling rise in the river contamination due to the climate change and
anthropogenic activities. Last decades' research has immensely focussed on river basin …

Monitoring water quality is essential for protecting human health and the environment and
controlling water quality. Artificial Intelligence (AI) offers significant opportunities to help …

To optimize the water quality index (WQI) assessment model, this study upgraded the
parameter weight values and aggregation functions. We determined the combined weights …

Groundwater quality appraisal is one of the most crucial tasks to ensure safe drinking water
sources. Concurrently, a water quality index (WQI) requires some water quality parameters …

To ensure safe drinking water sources in the future, it is imperative to understand the quality
and pollution level of existing groundwater. The prediction of water quality with high …

The present study was carried out using artificial neural network (ANN) model for predicting
the sodium hazardness, ie, sodium adsorption ratio (SAR), percent sodium (% Na) residual …

Water quality prediction plays an important role in environmental monitoring, ecosystem
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …

River water quality assessment is one of the most important tasks to enhance water
resources management plans. A water quality index (WQI) considers several water quality …

The health and quality of the Danube River ecosystems is strongly affected by the nutrients
loads (N and P), degree of contamination with hazardous substances or with oxygen …