Water environment pollution source reasoning and tracing method, system, equipment and medium

By constructing a pollution source feature database and using a one-dimensional convolutional neural network and encoder-decoder network, the problem of separating and quantitatively analyzing mixed pollution signals in the water environment was solved, enabling accurate source tracing of known and unknown sources and providing reliable technical support for water environment governance.

CN122045791APending Publication Date: 2026-05-15NINGBO MUNICIPAL ENG CONSTR GROUP
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Patent Information

Application Number
CN202610187682.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-10
Publication Date
2026-05-15

AI Technical Summary

Technical Problem

Existing technologies struggle to accurately analyze mixed pollution signals and dynamically quantify the contributions of each source in complex, multi-source polluted aquatic environments, and are unable to effectively identify unknown pollutant components, leading to distorted or missing source tracing results.

Method used

A pollution source feature database was constructed by using fluorescence spectroscopy analysis and spatiotemporal information acquisition. By combining a one-dimensional convolutional neural network and an encoder-decoder network with embedded spatiotemporal constraints, the known source contribution and unknown source contribution in the mixed signal were separated, and a quantitative contribution vector and spectral signals of unknown pollution components were generated. Source tracing results were generated by mapping geographic information.

Benefits of technology

It achieves efficient and high-precision separation and quantitative analysis of complex mixed signals, accurately identifies known source contributions and unknown components, provides reliable pollution source tracing results, and provides technical support for the treatment and liability determination of non-point source pollution.

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Abstract

The invention relates to a water environment pollution source reasoning and tracing method, system and equipment and a medium. The method comprises the following steps: constructing a pollution source characteristic database containing spectrum fingerprints and spatio-temporal information; performing time sequence enhancement on the mixed spectral signal of the monitoring point to extract stable features; a hydrological model is coupled to dynamically simulate pollutant transport paths and probabilities, and a potential contribution source set with weights is generated; analyzing the mixed signal by adopting a deep unmixing network embedded with space-time constraint, and separating and quantifying known source contribution and unknown pollution components; and finally, generating a visual pollution contribution degree spatial distribution diagram and a quantitative traceability report through geographic information mapping. The method solves the problems that complex mixed signals are difficult to accurately analyze, multi-source contribution is difficult to dynamically quantify and unknown pollution components are difficult to effectively recognize in the prior art, and intelligent and accurate traceability of municipal water environment non-point source pollution is achieved.
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