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Landscape lake Bayesian water quality risk prediction method

A prediction method and Bayesian model technology, applied in general water supply conservation, special data processing applications, instruments, etc., can solve problems such as inaccurate prediction of mechanism models, achieve good prediction accuracy and reduce algal blooms.

Inactive Publication Date: 2017-01-04
TIANJIN UNIV
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Problems solved by technology

[0003] In order to solve the problems existing in the prior art, the present invention provides a Bayesian water quality risk prediction method for landscape lakes, which overcomes the inaccurate prediction of mechanism models in the assessment and management of landscape lake water bodies in the prior art

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  • Landscape lake Bayesian water quality risk prediction method
  • Landscape lake Bayesian water quality risk prediction method
  • Landscape lake Bayesian water quality risk prediction method

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Embodiment Construction

[0023] The method for predicting the risk of eutrophication of landscape lakes of the present invention will be described in detail below in conjunction with the embodiments and accompanying drawings.

[0024] The eutrophication risk prediction method of the landscape lake of the present invention comprises the following steps:

[0025] 1) For data monitoring and collection, it is composed of several telemetry and remote transmission terminals, which are used to collect relevant physical and chemical index data of the landscape lake inflow and outflow monitoring points. Indicators to be monitored and collected include: ammonia nitrogen, nitrate nitrogen, phosphate, chlorophyll and dissolved oxygen concentration;

[0026] 2) The data is transmitted to the server through the communication system; the physical and chemical index data monitored online and the basic process conditions are stored in the database in time series. Establish a server to control the data monitoring and ...

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Abstract

The invention relates to a landscape lake Bayesian water quality risk predication method. A landscape lake eutrophication risk probability prediction model is established by virtue of combined utilization of a dynamic model equation and a Bayesian statistics method. Verification shows that the model has good prediction accuracy (accuracy is higher than 80%), so that a researcher can timely and accurately predict landscape lake water eutrophication when facing landscape lake entry water quality change. By comparing with landscape lake water quality prediction distribution situation under different entries, nitrogen and phosphorus nutrient salt concentration is pointed out to be a main factor influencing landscape lake eutrophication risk, and by combining risk calculation, response measures for different entry landscape lake eutrophication risk grades are preliminarily formulated, so that a reasonable measure can be adopted when a landscape lake faces eutrophication risk, landscape lake water quality is guaranteed, and algae bloom caused by eutrophication is reduced. The method provided by the invention also can provide some reference for landscape lake water quality management.

Description

technical field [0001] The invention relates to the establishment of a method for predicting the risk of eutrophication of landscape lakes, in particular to a method for predicting the risk of eutrophication of landscape lakes using a Bayesian method, which can provide a basis for the water quality of influent water in landscape lakes. Background technique [0002] Eutrophication is usually a process in which a large amount of pollutants are discharged into the water body to accelerate the production of organic matter (especially algae). Eutrophication is becoming more and more serious in rivers, lakes and seas all over the world and leads to the deterioration of the water environment, especially in landscape lakes. In order to prevent phytoplankton blooms caused by eutrophication, the assessment and management of landscape lake water bodies are very important. In the assessment and management of landscape lake water, the mechanism model is used to explain the ecological pro...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G06N7/00
CPCG16C20/70G06N7/01Y02A20/152
Inventor 成龙彭森杨立焜吴卿赵新华
Owner TIANJIN UNIV
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