Utilizing Property-Level Datasets to Interpret Coastal...
Transcript of Utilizing Property-Level Datasets to Interpret Coastal...
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Utilizing Property-Level Datasets to Interpret Coastal Flood Risk
Betsy Hayden and Curtis Smith
April 1st, 2015
![Page 2: Utilizing Property-Level Datasets to Interpret Coastal ...coastalgeotools.org/wp-content/uploads/Hayden.pdfsurge) + (surge 2015 + SLR surge – ground) × 0.55 . Example – Option](https://reader035.fdocuments.in/reader035/viewer/2022063021/5fe580b8b89a8e61d4710e44/html5/thumbnails/2.jpg)
Overview
– Background
– Approach
– Example
– Limitations
– Applications & Next Steps
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Overview
– In a nutshell:• GIS tools to compute the risk to
coastal flooding at individual structures
• Highlights vulnerable structures in a tangible way
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Background
– Toolset initially developed for internal QC of flood mapping
– Thought experiment to explore new applicationsApril 20, 2015 Page 4Utilizing Property-Level Datasets to
Interpret Coastal Flood Risk
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Background
– Many sources for information on flooding and sea level rise• FEMA Flood Maps• USACE SLR Calculator• NOAA SLR Viewer• Climate Central’s Surging Seas
Platform
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Background
– Few maps combine probabilistic flooding with sea level rise estimates
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Background
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– Four components to coastal storms
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Background
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– Superimpose SLR onto storm surge (bathtub method)
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– When water depth increases, wave heights can also increase
Background
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Approach
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– Data requirements:• Flood elevation• Spatial representation of
properties• Topographic dataset• SLR Estimate
– Public availability
Utilizing Property-Level Datasets to Interpret Coastal Flood Risk
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Approach
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– Extract topographic information at individual properties
– Determine the lowest grade at property
Utilizing Property-Level Datasets to Interpret Coastal Flood Risk
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Approach
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– Extract flood information at individual properties
– Add SLR prediction
– Estimate added wave contribution
Utilizing Property-Level Datasets to Interpret Coastal Flood Risk
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– Conservative estimate of wave height contribution based on water depth• Wave contribution = up to 55% of water depth
Approach
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wave height = 0.55 x water depth
water depth
Depth-limited
wave
Estimated sea level rise
Stillwater
Utilizing Property-Level Datasets to Interpret Coastal Flood Risk
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Approach
– Options for representing waves in SLR predictions:1. Exclude wave contribution2. Uniform increase in wave height3. Depth limited analysis based on new stillwater4. Proportional increase in wave height
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Example
– Estimated Relative Sea Level Change (NOAA High) for 2065 = 3.29 feet
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Example – Option 1
BFE2065= BFE2015+ SLRsurge
= BFE2015 + 3.29 feet
Bathtub approach
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Example – Option 2
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BFE2065= BFE2015 + SLRsurge + SLRwave
= BFE2015 + 3.29 feet + 1.8 feet
Double bathtub approach
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Example – Option 3
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BFE2065= (surge2015 + SLRsurge) + (surge2015 + SLRsurge – ground) × 0.55
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Example – Option 4
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BFE2065= (surge2015 + SLRsurge) + proportional wave contribution
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Example - Comparison
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Example - Comparison
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Differences highlighted by concentrating on one area
Each option shows different BFE
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Example - Comparison
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Differences highlighted by concentrating on one area
Sheltered area, depth limited BFE not expected
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Example – Bigger Picture
– Analyzing affect of SLR on storm waves just one application• Structures flooded by MHHW + SLR• 0.2% coastal flooding at critical facilities• 1% flood depth
– Cross-reference with census information, social vulnerability
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Limitations
– Approach doesn’t capture:• Non-linear effects• Wave runup• Wave setup
– Dependent on quality of spatial data
– Public usage
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Applications
– Community resilience planning
– Benefit-cost analysis incorporating SLR
– Land development
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Next Steps
– Compare estimates to wave modeling• Evaluate performance in developed vs. undeveloped areas• Evaluate performance in sheltered vs. open coast
– Brainstorm how to adapt for future development
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