In recent years, frequent occurrences of algal blooms due to environmental changes have
posed significant threats to the environment and human health. This paper analyzes the …

Abstract Long Short-Term Memory (LSTM) has recently emerged as a crucial tool for
scientific research in hydrology and water resources. Despite its widespread use, a …

There is a scarcity of streamflow data owing to the limited availability of gauge networks or
delayed gauging in most parts of the world. To overcome this challenge and reproduce long …

Water distribution networks (WDNs) experience significant water loss due to leaks,
necessitating advanced water leak detection methods. However, machine learning-based …

Accurate predictions of river water quality are vital for sustainable water management.
However, even the powerful deep learning model, ie, long short-term memory (LSTM), has …

Harmful algal blooms (HABs) pose a significant ecological threat and economic detriment to
freshwater environments. In order to develop an intelligent early warning system for HABs …

Intelligent prediction of water quality plays a pivotal role in water pollution control, water
resource protection, emergency decision-making for sudden water pollution incidents …

The algal community structure is vital for aquatic management. However, the complicated
environmental and biological processes make modeling challenging. To cope with this …

An accurate prediction of lake water levels is of great significance to water resource
regulation, flood prevention and mitigation. However, water level fluctuations have been …

The accurate prediction of chlorophyll-a (chl-a) concentration in coastal waters is essential
to coastal economies and ecosystems as it serves as the key indicator of harmful algal …