River Flow Prediction Using Liquid Level Sensors and Vegetation Data
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Solution Overview
Problem
Current methods for predicting the flow capacity of ecological river channels with vegetation during flood seasons are largely theoretical and rely on experience rather than actual surveys, leading to deviations and high monitoring costs, especially when vegetation coverage changes significantly.
Innovation Solution
A method and device using a liquid level sensor group to obtain geographic and vegetation data, adjusting the layout strategy based on ecological zone distribution and vegetation parameters, and providing real-time inundation status feedback to correct roughness coefficients for accurate river flow predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring methods are used to observe and survey vegetation inundation status during flood season, then measurement precision is improved, but device complexity and monitoring costs increase significantly
Solution Approach 1:
The patent uses low-cost liquid level sensors instead of expensive traditional monitoring equipment. These sensors are deployed in large quantities (hundreds to thousands per river section) to achieve comprehensive coverage and precise measurement of vegetation inundation status, effectively resolving the contradiction between measurement precision and device complexity through cost-effective sensing solutions
Solution Approach 2:
The patent creates a virtual copy of the physical river environment through digital elevation models, vegetation distribution maps, and hydrological models. This digital twin approach allows for accurate simulation and prediction of flood impacts on vegetation without requiring physical presence of complex monitoring equipment at every location, reducing device complexity while maintaining measurement precision
2Measurement precision
If comprehensive actual surveys are conducted to obtain vegetation and river channel data, then measurement precision is improved, but loss of time and monitoring costs increase
Solution Approach 1:
The patent performs preliminary actions by collecting and processing river channel geographic data, vegetation distribution data, and digital elevation model data during dry seasons or through remote sensing before flood seasons begin. This advance data preparation enables rapid response during floods without requiring time-consuming field surveys during the critical flood period, effectively resolving the contradiction between measurement precision and time loss
Solution Approach 2:
The patent replaces mechanical field survey methods with remote sensing technology, including satellite imagery, aerial photography, and LiDAR. These technologies can rapidly acquire comprehensive river channel and vegetation data over large areas without physical presence, dramatically reducing data collection time while maintaining or improving measurement precision through high-resolution remote sensing capabilities
3Device complexity
If theoretical prediction methods are used for river flow capacity, then device complexity is reduced, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent implements feedback mechanisms where liquid level sensors continuously monitor actual water levels and vegetation inundation status, and this real-time data feeds back to adjust and refine the hydrological models. The system compares predicted flow capacity with actual observations and iteratively improves model accuracy, resolving the contradiction between device complexity and measurement precision through data-driven model optimization
Solution Approach 2:
The patent dynamically changes key parameters in the hydrological models, such as roughness coefficients and vegetation resistance parameters, based on real-time sensor data about vegetation inundation status. By adjusting these parameters according to actual conditions rather than using fixed theoretical values, the system achieves higher prediction precision without requiring overly complex equipment
4Measurement precision
If high-density liquid level sensor groups are deployed to monitor vegetation inundation, then measurement precision is improved, but device complexity and monitoring costs increase
Solution Approach 1:
The patent segments the river into multiple ecological zones based on vegetation distribution and topography, then deploys sensor groups at strategic locations within each zone rather than uniformly across the entire river. This segmentation approach maintains measurement precision for each ecological zone while reducing the total number of sensors needed compared to uniform high-density deployment throughout the entire river system
Data Source
AI summary
A method and device for predicting a flow capacity of an ecological river channel with vegetation are provided. The method includes: obtaining ecological rive channel geographic data during dry season and ecological zone vegetation data; obtaining a layout strategy of a liquid level sensor group based on ecological zone distribution data and ecological zone vegetation data, the layout strategy of the liquid level sensor group reflects an inundation status of emergent vegetation in the ecological zone by rivers during flood season; obtaining a prediction river flow data at a node location of the ecological zone based on a corrected roughness coefficient of the ecological zone and water level data during the flood season, the node location is a position corresponding to a cross section of the water flow. A directional monitoring for a specific zone is formed with the liquid level sensor group.