Machine learning-based prediction of harmful algal blooms in water supply reservoirs

Models of Harmful Algal Blooms

Models used to study harmful algal blooms are a subset of those used to examine more general planktonic processes. Most models have been heuristic, examining the likelihood of certain processes generating a harmful algal bloom. Several models have been more closely coupled to field data and have been used to gain insights into the dynamics underlying the observations. As better physical and bio...

Deep-Learning-Based Approach for Prediction of Algal Blooms

Algal blooms have recently become a critical global environmental concern which might put economic development and sustainability at risk. However, the accurate prediction of algal blooms remains a challenging scientific problem. In this study, a novel prediction approach for algal blooms based on deep learning is presented—a powerful tool to represent and predict highly dynamic and complex phe...

Harmful Algal Blooms and Public Health.

The five most commonly recognized Harmful Algal Bloom related illnesses include Ciguatera poisoning, Paralytic Shellfish poisoning, Neurotoxin Shellfish poisoning, Diarrheic Shellfish Poisoning and Amnesic Shellfish poisoning. Although they are each the product of different toxins, toxin assemblages or HAB precursors these clinical syndromes have much in common. Exposure occurs through the cons...

Molecular tools for monitoring harmful algal blooms.

The world's oceans cover 70 % of the Earth's surface, and their dominant populations, both numerically and biomasswise, belong to microscopic protists and prokaryotes. The marine phytoplanktons are major components of both groups and are, by definition, high dispersal taxa with large population sizes. Small photosynthetic organisms are responsible for the bulk of primary production in oceanic a...

Role of in the Global Proliferation of Harmful Algal Blooms