Algal Bloom Forecasting using Remote Sensing: Discovering the most predictive data modalities for Algal Bloom Forecasting

An algal bloom is defined as a rapid increase in common algae (phytoplankton) abundance in water bodies and it can occur when a group of certain environmental factors is combined. If the algae populations grow out of control, such algal blooms become problematic and cause damage to the ecosystem, such phenomena are called harmful algal blooms....

Spatio-temporal embedding in deep learning for algal bloom forecasting

The term ”Algal Bloom” refers to the accumulation of algae in a confined geological space. They may harm human health and negatively affect ecological systems around the area. Thus, forecasting algal blooms could mitigate the environmental and socio-economical damages. Particularly, the use of deep learning methods could distinguish underlying...

Improving the Algal Bloom Prediction in the North Sea by Ensemble Kalman Filtering in the GEM/BLOOM Model

The ecological state of the North Sea surface water can be indicated by ocean variables such as the Chlorophyll-a (Chlfa) concentration. Chlfa is the principal photosynthetic pigment and is common to all phytoplankton and can therefore be used as a measure of phytoplankton biomass. The GEM/BLOOM model developed at Deltares is a generic...