Surface Runoff Yield Estimation via Remote Sensing
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Solution Overview
Problem
Current methods for monitoring surface runoff yield in vegetation-covered areas are time-consuming, costly, and limited to small-scale, point-based evaluations, making them unsuitable for large-scale, dynamic, and spatially detailed assessments.
Innovation Solution
A method that combines climate and spatial data to estimate surface runoff yield on a spatial pixel scale using preprocessed data on rainfall, vegetation coverage, evapotranspiration, and water storage, integrated with a water balance equation and remote sensing data to calculate vegetation canopy and litterfall interception water storage, and evapotranspiration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional slope runoff pond monitoring is used, then measurement precision can be achieved, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces the mechanical/physical monitoring system (slope runoff ponds, field measurements) with a remote sensing-based information system. By using satellite or aerial remote sensing data combined with mathematical models, the system calculates surface runoff yield without requiring physical monitoring infrastructure, thereby eliminating time consumption and high costs associated with traditional field monitoring while maintaining measurement precision through integrated data processing and computational algorithms
2Measurement precision
If traditional point-based monitoring is used, then measurement precision is achieved, but spatial representativeness deteriorates
Solution Approach 1:
The patent divides the study area into multiple spatial pixels or grid cells, with each pixel representing a specific spatial unit. By processing remote sensing data at the pixel level and combining it with local climatic and soil data, the system achieves both measurement precision for each pixel and comprehensive spatial representativeness across the entire study area. This segmentation approach allows the model to capture spatial variations in surface runoff yield without relying on single point measurements
Solution Approach 2:
The patent creates a universal monitoring system that can apply the same computational model and data processing framework across different spatial locations and scales. The integrated system combines remote sensing data, climatic data, soil data, and mathematical models into a single versatile platform that can estimate surface runoff yield for any pixel in the study area, making the system adaptable to various spatial representations from local to regional scales
3Reliability
If long-term continuous monitoring is used, then data reliability improves, but system complexity and maintenance requirements increase
Solution Approach 1:
The patent uses remote sensing data as a copy or representation of actual physical conditions rather than directly measuring them through physical infrastructure. By obtaining climatic data, vegetation data, and soil data from remote sensing sources and combining them with mathematical models, the system generates reliable estimates without requiring continuous physical monitoring equipment. This approach reduces system complexity and maintenance requirements while maintaining data reliability through multiple data sources and robust computational algorithms
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables efficient, accurate, and scalable monitoring of surface runoff yield, overcoming traditional method limitations by providing real-time, dynamic data for ecological hydrological research on regional and global scales.
Implementation Method 1
A vegetation canopy interception water storage is calculated based on preprocessed average maximum water holding depth per leaf area, vegetation coverage and leaf area index
Implementation Method 2
A vegetation litterfall interception water storage is calculated based on preprocessed average natural water content, maximum water holding capacity and litterfall accumulation
Implementation Method 3
An annual total vegetation evapotranspiration is then determined by using Zhang's hypothesis based on preprocessed vegetation coverage, annual forest evapotranspiration and annual grassland evapotranspiration
Data Source
AI summary
The present invention relates to a method for determining a surface runoff yield in a vegetation-covered area. The present invention improves and integrates a water conservation model with a Zhang's model based on remote sensing data. The present invention constructs a new method for calculating a surface runoff yield in a vegetation-covered area on a spatial pixel scale based on a water balance equation of the vegetation-covered area. This method utilizes real-time dynamic multi-temporal remote sensing data to calculate a vegetation canopy interception water storage, a vegetation litterfall interception water storage, a soil water storage change, a vegetation water conservation, a vegetation evapotranspiration and a vegetation runoff yield. The method realizes the long-term dynamic estimation of the surface runoff yield in regional and global vegetation-covered areas on a spatial pixel scale. It has the advantages of being efficient, fast, accurate, and applicable to large-scale vegetation-covered areas.