Various noxious and toxic harmful algal blooms (HAB) afflict the Chesapeake Bay, posing threats to human health and natural resources. Knowing where and when to expect these biotic nuisances may help mitigate their effects.
It has long been recognized that certain combinations of physical, chemical, and biotic conditions give rise to "bloom" events. For example, a specific algal bloom may form if a "seed" population exists in a water column when environmental conditions, such as light level and nutrient concentrations, become favorable for that species. Accordingly, if the environmental conditions
necessary for the growth and maintenance of an organism are adequately defined, i.e. its habitat, one should be able to predict the potential occurrence of the organism if one can estimate the relevant conditions.
This program uses a combination of physical modeling, satellite imagery and real time measurements to delineate the extent in time and space of the most likely habitat for HAB in the bay. Because this technique does not attempt to mechanistically "grow" HABs it will never be a precise predictor of the occurrence of HABs. But, by giving Environmental Managers information about areas of most likely occurrence it serves as an aid in focusing their sampling programs and allowing the response to HAB events to be as efficient as possible.
Daily runs of a sophisticated numerical model of the Chesapeake Bay provide oceanographic predictions from which a field estimate of the HAB probability is derived. The model includes the second generation forecast system of Chesapeak Bay for physical variables (link to other page) and a bio-geochemical model of water quality which includes the parameters of nutrients, phytoplankton and zooplankton.
These HAB probability fields are displayed to the public on a website with GIS interfaces.
This project is still in early research and is a collaboration with the University of Maryland, and Maryland Department of Natural Resources.