Method for forecasting blue-green algae water bloom in large-scale shallow lake within 72 hours

A technology of cyanobacteria blooms and prediction methods, which is applied in the direction of testing water, measuring devices, material inspection products, etc., and can solve problems such as errors and errors in prediction results

Inactive Publication Date: 2011-07-27
NANJING INST OF GEOGRAPHY & LIMNOLOGY
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Problems solved by technology

At present, there are instruments for rapid monitoring of cytochrome in water bodies, but these instruments often have large errors w...

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  • Method for forecasting blue-green algae water bloom in large-scale shallow lake within 72 hours
  • Method for forecasting blue-green algae water bloom in large-scale shallow lake within 72 hours
  • Method for forecasting blue-green algae water bloom in large-scale shallow lake within 72 hours

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Embodiment Construction

[0057] The 72-hour cyanobacteria bloom prediction method comprises the following steps:

[0058] 1) Data collection and application

[0059] Including the analysis of the real-time water quality, cyanobacteria biomass and distribution of the waters of Taihu Lake, and the collection of meteorological information data.

[0060] Manual survey: Sampling twice a week during the forecast period. According to historical data, the three bays of North Taihu Lake (Meiliang Bay, Gonghu Bay and Zhushan Bay) are areas where cyanobacteria blooms occur frequently, and Meiliang Bay Gonghu Bay and Gonghu Bay are also water sources and landscape waters. Therefore, the forecast of cyanobacterial blooms in the Taihu Lake region mainly focuses on the bloom status of Meiliang Bay and Gonghu Bay. Set up sampling points near the water intake of each water plant in the two lake areas and in the landscape waters to obtain the concentration of chlorophyll a in the area of ​​concern. chlorophyll a conc...

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Abstract

The invention discloses a method for forecasting blue-green algae water bloom in a large-scale shallow lake within 72 hours. The method comprises the following steps of: building a content forecasting model of chlorophyll a in a water body and a probability forecasting model of water bloom generation according to an in-situ growth rate and drift rate parameters of blue-green algae; analyzing instant content of the chlorophyll a in a monitoring water area; distributing and acquiring meteorological information data in a monitoring period; inputting the built models; and outputting a predicted value of the concentration of the chlorophyll a in the monitoring water area in the next 72 hours and the water area and the probability of water bloom generation. The method disclosed by the invention has the advantages of strong operability, easily acquired parameters used for forecasting and high timeliness, and can be used for rapidly and accurately predicting breakout of the blue-green algae water bloom and forecasting the blue-green algae water bloom in a waterhead site and a vital landscape water area.

Description

technical field [0001] The invention relates to a method for monitoring and forecasting cyanobacteria blooms in short time scales in water areas such as lakes and reservoirs, in particular to a method for predicting 72-hour cyanobacteria blooms in large shallow lakes. Background technique [0002] Cyanobacteria blooms are an environmental problem faced by many countries around the world. In many nutrient-rich lakes or reservoirs, cyanobacteria accumulate in local lakes or reservoir areas and decompose at high temperatures, forming foul odors; especially when cyanobacteria take water from water sources When there is a large amount of accumulation near the mouth, it may cause the deterioration of the water quality of the water source and endanger the safety of water supply. [0003] At present, there is still a lack of effective governance means to completely eliminate this environmental problem, and cyanobacteria blooms will still appear in many lakes and reservoirs in large ...

Claims

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Application Information

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IPC IPC(8): G01N33/18G01N33/00G06F19/00
Inventor 孔繁翔吴晓东张民于洋阳振高俊峰马荣华
Owner NANJING INST OF GEOGRAPHY & LIMNOLOGY
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