This study presents a new method based on three types of deep learning-based models
(DLM) for estimation of water parameters. The DLM models were recurrent neural networks …

Clean water is an indispensable essential resource on which humans and other living
beings depend. Therefore, the establishment of a water quality prediction model to predict …

Accurate water level prediction is one of the important challenges in various fields such as
hydrology, natural disasters, and water resources management studies. In this study, a deep …

Forecasting the water levels in rivers and lakes is critical for flood warnings and water-
resource management. Many soft computing techniques have been implemented for the …

Water pollution is one of the most challenging environmental issues. A powerful tool for
measuring the suitability of water for drinking is required. The Water Quality Index (WQI) is a …

Multifarious anthropogenic activities triggered by rapid urbanization has led to
contamination of water sources at unprecedented rate, with less surveillance, investigation …

The Three Gorges Hydropower Station, the largest in the world, plays a pivotal role in
hydroelectric power generation, flood control, navigation, and ecological conservation. The …

A Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) combined with a
deep learning approach was created by combining CNN and LSTM networks simulated …

Recently, the magnitude and frequency of extreme heavy rains and localized heavy rains
have increased due to abnormal climate, which caused increased flood damage in river …

River water quality monitoring using traditional water sampling and laboratory analyses is
expensive and time-consuming. The application of artificial neural network (ANN) models to …