Stormwater Depth Sensors with Tidal Backflow Decoupling
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Solution Overview
Problem
Stormwater management systems face challenges in distinguishing between stormwater and tidal backflow contributions to overflow events, making it difficult to accurately predict and manage system capacity and address security, safety, and health concerns.
Innovation Solution
A system and method that utilizes fluid depth sensors and tidal sensors to generate models that decouple tidal effects from stormwater measurements, allowing for the separation of tidal and stormwater components in drainage systems, enabling accurate prediction and detection of flow events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If water depth sensors are used to monitor stormwater drainage systems, then measurement of water depth is achieved, but the ability to distinguish between stormwater and tidal backflow contributions is lost
Solution Approach 1:
The patent segments the water depth measurement into two distinct components: stormwater contribution and tidal backflow contribution. By using multiple sensors (stormwater sensors and tidal sensors) and separating their measurements, the system can identify and quantify each source independently, resolving the contradiction between measuring water depth and identifying its source.
Solution Approach 2:
The patent introduces tidal sensors as intermediary devices that specifically measure tidal backflow conditions. These sensors act as mediators between the stormwater drainage system and the tidal influences, providing separate data that can be used to distinguish tidal effects from stormwater events.
2Device complexity
If tidal backflow is not accounted for, then system simplicity is maintained, but accuracy in predicting overflow events deteriorates
Solution Approach 1:
The patent implements preliminary action by continuously monitoring tidal conditions using tidal sensors and pre-calculating tidal backflow contributions. This allows the system to anticipate and prepare for tidal influences before they affect stormwater drainage, improving overflow prediction accuracy without requiring complex real-time adjustments.
Solution Approach 2:
The patent applies dynamics by making the monitoring system adaptable to varying tidal conditions. The system dynamically adjusts its predictions and alerts based on real-time tidal data, allowing it to maintain high accuracy across different tidal regimes while managing system complexity through automated responses.
3Loss of information
If multiple sensors are deployed to distinguish stormwater and tidal contributions, then source identification improves, but device complexity increases
Solution Approach 1:
The patent applies universality by designing sensor devices that can perform multiple functions. The stormwater sensors and tidal sensors are integrated into a unified monitoring system that can identify, measure, and differentiate between multiple water sources, reducing the need for separate dedicated systems for each function.
Solution Approach 2:
The patent uses copying by creating virtual representations of tidal conditions through computational models that replicate tidal backflow behavior. These digital copies allow the system to analyze and distinguish tidal effects from stormwater events without requiring additional physical sensors in every possible location.
Data Source
AI summary
The invention is directed towards decoupling tidal effects from time-series depth measurements. A drainage sensor includes a fluid depth sensor. The drainage sensors are positioned at monitoring points in a drainage system. Stormwater flows into an input of the drainage system. A tidal depth sensor is positioned in a tidal body of water near an output of the drainage system. During period of high tide, tidal water backflows into the output of the drainage system. The decoupling is accomplished by generating a model of tidal backflow patterns based on data from the drainage sensors and the tidal sensor. The model accounts for a lag time between the tidal data measurements and measurements of the drainage sensors. The model is be used to predict the contribution of tidal backflow effects to stormwater data.