A method for analyzing dynamic response of lake water ecological system under short-term natural disturbance
By combining the rolling window dynamic threshold method and machine learning with the AQUATOX model, the dynamic response of lake aquatic ecosystems under short-term natural disturbances is identified and analyzed. This addresses the shortcomings of existing event identification and control strategies, enables quantitative analysis of zoned control and response mechanisms, and improves the stability of lake water quality.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TSINGHUA UNIVERSITY
- Filing Date
- 2026-05-25
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies lack objective event identification methods when identifying the dynamic response of lake aquatic ecosystems under short-term natural disturbances, making it difficult to quantitatively analyze nonlinear response mechanisms. Furthermore, the control strategies lack the ability to cope with short-term disturbances and are difficult to achieve differentiated control by region.
A rolling window dynamic threshold method is used to identify disturbance events. A box model is constructed by combining a machine learning model and an AQUATOX water ecological process model. The water quality response signal transmission characteristics are quantified by using feature matrices and feature selection methods to identify key driving factors and simulate regulation strategies.
It enables the objective identification of short-term natural disturbance events and the quantitative analysis of nonlinear effects, provides differentiated regulation suggestions for different regions, and enhances the resilience of lake aquatic ecosystems and the control of algal blooms.
Smart Images
Figure CN122414713A_ABST