Forward-Inverse Coupling for Water Pollutant Source Detection
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Solution Overview
Problem
Existing methods for sudden water pollutant source detection in complex river systems face challenges due to non-unique pollutant sources, differing data attributes, and insufficient time-interspace representation, leading to low accuracy in results that rely on single data sources.
Innovation Solution
A method and system utilizing forward-inverse coupling, which involves building a one-dimensional forward water quality simulation model, applying an inverse optimization source-detection model, grouping solutions, and updating them using Bayesian probability to merge multi-sourced information and improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single data source is used for pollutant source detection, then the detection process is simple, but the detection accuracy is low due to non-unique sources and insufficient time-interspace representation
Solution Approach 1:
The patent merges multiple data sources including satellite remote sensing data, ground monitoring data, and model simulation data to comprehensively identify pollutant sources. This combination of diverse data sources resolves the contradiction by improving detection accuracy through multi-source information fusion while managing the increased complexity through systematic data integration frameworks.
Solution Approach 2:
The patent introduces temporal and spatial dimensions by incorporating time-series monitoring data and spatial distribution information from multiple locations. This multi-dimensional approach enhances detection accuracy by providing comprehensive time-interspace representation of pollutant dispersion patterns, transforming the detection process from single-point snapshots to continuous spatiotemporal analysis.
2Measurement precision
If multiple monitoring indexes are used to improve detection accuracy, then the detection accuracy improves, but the data processing complexity increases
Solution Approach 1:
The patent segments the complex detection process into distinct modules: data acquisition from multiple indexes, data preprocessing, model simulation, source identification, and result validation. Each monitoring index is processed through standardized segmentation steps, which manages the complexity of handling multiple indexes while maintaining high detection accuracy through systematic analysis of each parameter.
Solution Approach 2:
The patent develops a universal data processing framework that handles multiple monitoring indexes (such as pH, dissolved oxygen, chemical oxygen demand) through a common analytical approach. This multi-functional system processes diverse water quality parameters using unified algorithms and models, improving detection accuracy across different pollutant types while reducing overall data processing complexity through standardization.
Data Source
AI summary
The present disclosure refers to a method and a system of sudden water pollutant source detection by forward-inverse coupling, including: building an one-dimensional forward water quality simulation model of a river way according to acquired mechanical parameters and water quality parameters; according to the one-dimensional forward water quality simulation model of the river way, measuring and calculating each monitoring index by using an inverse optimization source-detection model; by constructing the one-dimensional forward water quality simulation model of the river way, using the inverse optimization source-detection model for measurement and calculation; and performing the Bayesian updating, in order to realize multi-information fusion. The present disclosure may reasonably control and use different observation information, and combine the redundancy or complementarity of multi-sourced information in space or in time to obtain consistent interpretation of the measured object, thus overcoming the uncertainty of the water environment, improving the accuracy of water pollutant source detection.