A stream encryption method for water quality monitoring data sequence

Abstract

The invention provides a river water quality monitoring data sequence encryption method. Firstly a regression equation between a pollutant flux and flow is optimized through an LOADEST model, a water quality sequence encrypted for the first time is pre-estimated through high-frequency flow monitoring data, and a fluctuation characteristic of a flow process is transmitted to a water quality process through the regression equation, so that the deficiency that a linear interpolation method cannot describe a fluctuation characteristic of a water quality change process is made up for; secondly the water quality sequence encrypted for the first time is corrected through a Kalman filtering correction model, and a water quality actual measurement value and a water quality estimation value based on the LOADEST model are subjected to data assimilation, so that an error between the final estimation value and the actual measurement value can be effectively reduced and the deficiency of relatively large error of related model interpolation methods is made up for; and finally the obtained encrypted water quality data sequence can not only describe the fluctuation change characteristic of the water quality process between two actual measurement points but also effectively reduce the error between the estimation value and the actual measurement value, so that the defects of an existing method are overcome.

Description

Technical field [0001] The invention relates to the field of water quality monitoring and simulation analysis, in particular to an interpolation and encryption method for river water quality monitoring data. Background technique [0002] Pollution and destruction of the water environment is one of the main problems facing the world today. Monitoring of water quality is the basic method for mastering the quality of river water environment, but it is limited by the current technical and economic level of water quality monitoring methods. The frequency of routine water quality monitoring is usually 1 -3 times / month, of which 1 month / time accounts for the majority. [0003] 1-3 times / month of the actual water quality data sequence, due to the large time span and discrete distribution between data points, it can only reflect the macro change trend of river water quality, and it is difficult to reflect the true change process of water quality. Therefore, in carrying out accurate calcula...

AI Technical Summary

Problems solved by technology

The water quality sequence encrypted by the interpolation method of the correlation model can describe the fluctuation and change characteristics of the water quality process between the two measured points to a certain extent; Inevitably there is an error between the values, and in many cases the error is large, which will also lead to large deviations in the calculation of river pollution load flux and the coupled simulation of water quantity and water quality, and the relevant results are difficult to support water environment management and decision-making

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