10693_WANG-ed MLW

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Prediction, prevention and mitigation of harmful algal blooms in the China Sea
Dan Wang
Key Laboratory of Marine Carbon Cycle and Climate Change Research, National Marine
Environmental Forecasting Center, State Oceanic Administration, PR China
E-mail: [email protected]
Ranging from microscopic, single-celled organisms to large seaweeds, harmful algal blooms (HABs)
pose a serious threat to public health, aquatic organisms, commercial fisheries, and the quality of fresh
water lakes, rivers and reservoirs, as well as marine coastal environments. Over the past few decades, the
world’s coastal waters have experienced an increase in the number and type of HAB events. In the China
Sea, every coastal province frequently experienced HAB events and suffered from more and more
serious economic losses and human illness and death in the last decade. A pressing need exists to
understand, monitor, and predict the outbreak of HAB events and to propose the efficient emergent
management methods. In this study, the several kinds of prediction methods are introduced, including
empirical prediction methods, statistical prediction methods, and numerical model prediction methods.
In particular, the common prediction methods used in the national marine environmental operational
forecasting systems for early warning red tide and green tide are proposed to understand the HABs
occurrence mechanism and to promote HAB disaster prevention and mitigation in China. In order to
improve the ability to respond to marine environmental disasters, operational HAB early warning and
forecasting system and advanced emergent disaster mitigation system should be established in China as
soon as possible.
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