Flood Risk Assessment Using Geospatial Elevation Curves
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Solution Overview
Problem
Current flood risk assessment methods are inadequate in accurately determining flood frequencies and elevations, leading to uncertainties in insurance premium calculations and flood loss mitigation, particularly as they rely on outdated or incomplete data and do not account for variations in flood zones and property vulnerabilities.
Innovation Solution
The development of a system that uses geospatial data and flood maps to derive flood frequency versus flood elevation curves, allowing for the interpolation and extrapolation of flood elevations and frequencies, thereby improving the accuracy of flood risk assessments by integrating digital elevation models and hydrologic methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional flood risk assessment methods using FEMA special flood hazard areas are used, then the assessment process is simple and easy to implement, but the measurement precision of flood risk is insufficient
Solution Approach 1:
The patent segments the continuous floodplain into discrete elevation zones by generating multiple flood elevation lines at different frequencies (e.g., 10-year, 50-year, 100-year, 500-year floods). Each zone between adjacent elevation lines represents a distinct risk level, transforming the binary SFHA classification into a multi-granularity zonation system that provides more precise spatial differentiation of flood risk.
Solution Approach 2:
The patent introduces a new dimensional approach by creating flood elevation lines perpendicular to the flood source (river centerline or coastal line) at regular intervals, adding an elevation dimension to the traditional flood zone mapping. This dimensional expansion allows properties to be classified not just by whether they are inside or outside SFHAs, but by their specific elevation relative to multiple flood frequency thresholds.
2Measurement precision
If flood elevation lines are generated at regular intervals perpendicular to flood source, then the measurement precision of flood frequency and elevation is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system performs self-service by automatically generating flood elevation lines and calculating flood frequencies using the established mathematical relationships between elevation, distance from flood source, and flood frequency. The computer system autonomously processes the geospatial data, digital elevation models, and hydrologic parameters to produce the flood risk assessment without requiring manual measurement or adjustment of each elevation line.
Solution Approach 2:
The patent replaces manual field surveys and hydraulic modeling with a computational system that uses digital elevation models, geospatial data, and automated algorithms to generate flood elevation lines. The mechanical and manual processes of traditional flood mapping are substituted with computer-based calculations that efficiently process large datasets and produce consistent, repeatable results.
3Loss of information
If properties are classified only by inside or outside SFHA, then the ease of operation is maintained, but the loss of information about flood frequency variations occurs
Solution Approach 1:
The patent applies local quality by assigning different flood frequency characteristics to different spatial zones within the floodplain. Instead of treating all properties inside SFHAs uniformly, the system identifies that properties closer to the flood source (within the first elevation interval) experience higher flood frequencies and greater risk, while properties farther away experience lower frequencies. This localized differentiation preserves the nuanced information about flood frequency variations across the floodplain.
Solution Approach 2:
The patent changes the classification parameter from a binary SFHA designation to a multi-level system based on elevation intervals and corresponding flood frequencies. Properties are reclassified according to their specific elevation zone (e.g., between 10-year and 50-year elevation lines, or between 50-year and 100-year elevation lines), transforming the single parameter of SFHA membership into multiple parameters including elevation zone, flood frequency, and distance from flood source.
Data Source
AI summary
In various embodiments, points from flood maps (e.g., geospatial flood risk zoning maps) may be used in generating a flood frequency versus flood elevation curve for reducing the uncertainty in the flood risk assessment. In some embodiments, geospatial flood elevation lines for flood elevation lines at different flood frequency levels may be defined based on elevation datasets where there are inconsistencies between the elevation datasets and flood maps that were generated. The flood frequency versus flood loss curve may be derived based on the computed flood frequency versus flood elevation curve, digital elevation datasets, and collected damage curve. In some embodiments, the flood risk rating may also be derived and a flood risk assessment report may be generated.