Cyanobacteria harmful blooms (CyanoHABs) in lakes and reservoirs represent a major risk
for water authorities globally due to their toxicity and economic impacts. Anticipating bloom …

During the past three decades, harmful algal blooms (HAB) events have been frequently
observed in marine waters around many coastal cities in the world including Hong Kong …

Freshwater cyanobacterial harmful algal blooms (cyanoHABs) are a worldwide problem
resulting in substantial economic losses, due to harm to drinking water supplies, commercial …

The rapid emergence of deep learning long-short-term-memory (LSTM) technique presents
a promising solution to algal bloom forecasting. However, the discontinuous and non …

Many studies have attempted to predict chlorophyll-a concentrations using multiple
regression models and validating them with a hold-out technique. In this study commonly …

Toxic cyanobacterial blooms are globally increasing with negative effects on aquatic
ecosystems, water use and human health. Blooms' main driving forces are eutrophication …

Predicting water contamination by statistical models is a useful tool to manage health risk in
recreational beaches. Extreme contamination events, ie those exceeding normative are …

Assessing the key drivers of eutrophication in lakes and reservoirs has long been a
challenge, and many studies have developed empirical models for predicting the relative …

Abstract The Reynolds Functional Groups (RFG) classification scheme is an informative and
widely used method in ecological studies of freshwater phytoplankton. It clusters species …

Cyanobacterial toxic blooms are a worldwide problem. The Río de la Plata (RdlP) basin
makes up about one fourth of South America areal surface, second only to the Amazonian …