Method for predicting water area where water bloom of blue algae occurs first next year in large shallow lake

Abstract

The invention discloses a method for predicting the water area where water bloom of blue algae occurs first next year in a large shallow lake, which is characterized by comprising: based on the area and characteristics of water, setting a monitoring point for sampling water and bottom sediment; characterizing the time and spatial distribution of blue algae by using pigment analysis; characterizing the activity of blue algae in all lake areas by using photosynthesis activity and esterase activity of cells; acquiring meteorological data of the lake areas, and determining an effective wind field; and building an ecological dynamic module to predict the area where the water bloom of blue algae occurs first next year. In the method disclosed by the invention, the biomass and growth activity of the blue algae and the effective wind field are regarded as the common triggering factors of the formation of water bloom, the growth and transport of the blue algae and the driving factors of the formation of the water bloom are analyzed to estimate the change law of the ecological pattern of overwintering and resurrection of blue algae, the formation of water bloom of blue algae is predicted from multiple angles, parameters are integrated by the module, and the prediction result is directly displayed in a blue algae biomass contour map mode according to a time sequence.

Description

technical field [0001] The invention relates to a method for early prediction of cyanobacteria blooms in large shallow lakes, in particular to a method for predicting the water area where cyanobacteria blooms first occur in the following year in large shallow lakes, specifically through pigment analysis, algae photosynthesis and activity analysis, and effective wind field Analysis, etc., combined with model predictions, make early predictions for the waters where cyanobacterial blooms will first occur in the next year. Background technique [0002] Since the eutrophication problem of lakes is difficult to fundamentally solve in a short period of time, it is difficult to eliminate the occurrence of annual cyanobacteria blooms in lakes and other water bodies for a long time. The development of cyanobacteria bloom prediction technology will help reduce the ecological hazards and health risks caused by cyanobacteria blooms. [0003] Research at home and abroad mainly focuses on...

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Problems solved by technology

[0004] However, there are no relevant reports on the research on predicting the formation trend of water blooms in the coming year on a longer time scale.

Long-term forecasting needs to consider a series of processes such as the provenance distribution pattern in the overwintering period, the growth and migration of algae in the recovery period, and has higher requirements for weather forecasting, and the issues involved are more complicated than short-term forecasting

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