Global climate change has led to large fluctuations in lake levels in recent years as
meteorological and hydrological parameters have changed and water use has been …

Water infrastructure integrity, quality, and distribution are fundamental for public health,
environmental sustainability, economic development, and climate change resilience …

Lakes help increase the sustainability of the natural environment and decrease food chain
risk, agriculture, ecosystem services, and leisure recreational activities locally and globally …

Forecasting time series with extreme events has been a challenging and prevalent research
topic, especially when the time series data are affected by complicated uncertain factors …

Water level (WL) forecasting has become a difficult undertaking due to spatiotemporal
fluctuations in climatic factors and complex physical processes. This paper proposes a novel …

The planning and management of water resources are affected by streamflow. The analysis
of the sustainability of water resources has used well-grounded methods such as artificial …

With the rapid development of machine learning (ML) models, the artificial neural network
(ANN) is being increasingly applied for forecasting hydrological processes. However …

Water level prediction is critical for optimizing available water resources and sustainable
use. We propose a new deep learning hybrid model for water level prediction. The model …

It is necessary but difficult to accurately predict the water levels in front of the pumping
stations of an open-channel water transfer project because of the complex interactions …

Estuaries are dynamic environments which are driven by various natural processes like river
discharge, tides, waves, influx of saline water and sediments, etc. These ecosystems are the …