Flood Hazard Demographics and NFIP Policy/Claims Analysis · Flood Hazard Demographics and NFIP...
Transcript of Flood Hazard Demographics and NFIP Policy/Claims Analysis · Flood Hazard Demographics and NFIP...
Flood Hazard Demographics and NFIP Policy/Claims Analysis
ASFPM - Hartford, CT
June 2013
Mohan Rajasekar
Mark Crowell
Andy Neal
NFIP – A means of discouraging unwise occupancy of flood prone areas, yet occupancy of these areas has expanded since 1968.
Risks continue to increase - 40 years after the program’s inception, only 20% to 30% of individuals exposed to the flood hazard actually purchase insurance.
The primary challenge: Optimize the NFIP to balance fiscal soundness, affordability of
insurance, adequate coverage for those at risk, floodplain management (reduction of flood hazard vulnerability), economic development, individual freedoms, and environmental concerns.
Problem Statement
2010 Census
Population and Housing Units
Roughly two-thirds of the 27.3 million new U.S. residents between
2000 and 2010 lived in the southern and western states of Texas,
California, Florida, Georgia, North Carolina, Virginia, Nevada, and
Colorado - the “demographics of devastation.”
Map Modernization
Expansion of the digital quilt
Increased Spatial Resolution of Risk Exposure
LandScan
Opportunity Summer 2011
Risk Identification Project Prioritization
Impacted Population & Housing Units
Augmented by Needs Data (CNMS)
Risk Assessment Tangible Improvements in Resolution
Risk Communication Targeted outreach based on Census 2010 Demographic Data
Risk Mitigation, Areas with Large Mitigation Potential
Cost-effectiveness of the Hazard Mitigation Assistance (HMA) grant programs
Evaluate Communities’ Commitment and Adherence to Floodplain Management Best Practices
This study delivered crucial quantitative and geospatial data needed to
analyze the current impact, reach, and future needs of the NFIP
Benefits
How many people currently reside within effective Special Flood Hazard Area (SFHA) ? By CBG using LandScan
How many housing units currently fall within effective SFHA? By CBG
How did the Map Mod program affect the SFHA (increases/decreases)?
How did Map Mod affect the identification of the number of people and structures in the SFHA?
Questions the Study (Part 1) Answered
Where, relative to the SFHA, are NFIP
policies and claims located?
What is the extent of Zone Grandfathering
within the NFIP policy base?
Questions the Study (Part 2) Answered
2009-2010 SFHA DEMOGRAPHICS STUDY
2000 Census Block Groups
Even Population Distribution Assumption
TransAmerica / Core Logic 2005 Pre Map Mod Snap Shot
798 Counties with Sufficient NFHL Coverage for
Comparison with Pre Map Mod
Comparison with 2010 Study
2011 LandScan as Population Source
In Most Areas Provides Sub-Census Block
Level Re-Distribution of Census 2010
Population Data
February 2012 NFHL
1,750 Counties with Sufficient NFHL Coverage
for Comparison with Pre Map Mod
RAMPP 2010 Study
Census 2010 Population Distribution
Region I, 4.6% Region II, 10.2%
Region III, 9.5%
Region IV, 19.5%
Region V, 16.6%
Region VI, 12.3%
Region VII, 4.4%
Region VIII, 3.5% Region IX, 15.3%
Region X, 4.1%
Census 2010 Population Distribution
Distribution of Population within SFHA
Region I, 3.0%
Region II, 9.3%
Region III, 6.2%
Region IV, 37.0%
Region V, 7.6%
Region VI, 19.3%
Region VII, 3.9%
Region VIII, 1.6%
Region IX, 9.7% Region X, 2.3%
Distribution of Population within SFHA
Part 1 Results Tables
Part 1 Results Tables
Effects of Map Mod
Region I, 0.4%
Region II, 14.0%
Region III, 3.1%
Region IV, 29.7%
Region IX, 2.2% Region V, 1.9%
Region VI, 38.2%
Region VII, 5.7%
Region VIII, 2.5%
Region X, 2.3%
Distribution of Population Mapped in to SFHA
Effects of Map Mod
Region I, 0.9%
Region II, 7.7%
Region III, 1.5%
Region IV, 51.8%
Region IX, 12.0%
Region V, 15.6%
Region VI, 3.4%
Region VII, 3.8% Region VIII, 2.5%
Region X, 0.7%
Distribution of Population Mapped out of SFHA
Bottom Up Data Model Design
Automation of Processes to Greatest Extent Practicable
Zonal Statistic Based on Re-Sampled LandScan
Population Totals per Reporting Area Based on Aggregates Zonal
Results
Outputs Include Population, Housing Unit, and Area
Statistics
Part 1 Detail
Discrete, Topologically Flat
Initial Requirements Political Boundaries
Coastal vs. Riverine
Anticipating Congressional Requests and Potential for Further Analysis Census Block Groups
Congressional Districts
Results from Parts 1 and 2 Can be Aggregated or Isolated to Any Reporting Area Resolution, or Combination Thereof
Reporting Areas
Geospatial and geocoding analyses that can
support the assessment of the NFIP’s actuarial
soundness
Geolocation of Nearly 16 Million Points
Policies, Claims, Historic PRPs
Proximity Determinations
Nearest SFHA
Nearest SFHA Type and Coastal vs. Riverine
Part 2 Detail
Part 2 Results Summary Tables
Policy / Effective Zone Match
31 | April 30, 2013
Handling of PII
Geocoding
NFHL
LandScan
Challenges
Personally Identifiable Data
Client Requirements
RAMPP Strategy
Firewall
Data Handling Role Assignments
Disassociation of Location Data from Personal
Information to Allow for More Flexibility During
Certain Phases
Handling of PII
Assumed Levels of Accuracy Limited Clean Up at this Scale
ROOFTOP vs. INTERPOLATED
Standardizing Input Address String from Policy
and Claims Records Highlights Shortcoming in Policy Data Collection Systems
Geocoding
Geocoding Challenges
Clustered or Poorly
Interpolated Location
Returns
Geocoding Summary
Policy Data Geocoding Summary
NFHL Challenges
Tracking Lack of Accurate Coverage Definition
Topology Overlapping Polygons
Slivers
Presumably from LOMR Stitching
Attribution Consistency
Oak Ridge National Laboratory Product
Represents ‘Ambient’ Population Distribution
Population Location by Probability
Multi-Variable Dasymetric Model
Day/Night Data Available
Sub-Block Resolution in Most Areas
Found that Population Totals within Certain Administrative
Boundaries were Inaccurate
2011 LandScan
LandScan
LandScan
Vs Census Block
Vs Census Block Group
BW12 CONSIDERATIONS
Utilizing Study Results to Hotspot and
Understand BW12 Impacts
1) Stakeholder Education
2) Stakeholder Needs
3) Variability of Localized Data Sets
Necessary to consider a ‘standardized’ BW12
approach as an organized analytical framework
comprised of Conceptual, Logical and a Physical
Model rather than a specific turn key application
or a series of individual determinations/concepts.
Defining the Need
A Data Model is an
abstract
representation of
how data and
information are
represented and
accessed
Conceptual Model
Process & Data
Logical Model
Physical Model
Timing of BW12 and Sandy
Completion of the NFHL/NFIP Policy and
Claims Demographic Study
Community Interest in Understanding the
Implications of BW12
The Rebuild App
Current Opportunity
Integrated Adaption Assessment (Conceptual Models)
Questions answered by this task Outcomes
What goals and process will be used to guide the assessment?
What county and community entities will be included in the assessment?
What planning groups will be formed to guide the assessment?
What neighboring county and community entities will we partner with in the assessment?
What will be our stakeholder engagement strategy?
Form adaptation advisory group
Form neighboring partner group
Develop Stakeholder Engagement Plan and
execute throughout
Create transparency website
Questions answered by this task Outcomes
What areas could be better aligned with federal programs to position for federal credits or grants?
What regulatory strategies can be offered to influence the areas of priority?
Develop policy or other strategy
recommendations
Questions answered by this task Outcomes
What is the baseline impact of the BW12 changes? Where are the locations of current policies and historical
NFIP claims? What actions can be taken to lower risk and insurance rates? What actions are likely to be taken based on cost vs. value? Where are the recovery vulnerable areas within the
assessment area?
Create Adaptation GIS geodatabase populated
with source data layers
Add geo-located Policies and Claims data
Add BW12 assessment layers
Evaluate recovery cycle activities
Score value and vulnerability
Rollup scores at the block level
Questions answered by this task Outcomes
What is the baseline of current CRS program activities? What can be done to lower CRS rating and increase NFIP
insurance reductions to the public? What recommendations can be made to decrease flood risk
by increasing insurance policy penetration?
Develop Flood Insurance Coverage Assessment
Report to credit for CRS 372
Develop and prioritize recommendations
Evaluate recommendations and per capita
costs/savings
Questions answered by this task Outcomes
What are the current planned activities within the county? How will these activities affect the value and vulnerability
scores from the BW12 assessment? What additional activities can be undertaken from the BW12
and CRS assessments?
Develop investment activities database
Score and prioritize activities with wide
improvement potential
Perform scenario analysis on larger mitigation
projects in relation to BW12 and CRS affects
Use database results to develop rapid localized
plans/views
Questions answered by this task Outcomes
How can we more holistically approach the allocation of our ongoing activities?
How can we better position for ongoing programmed funding activities?
How can we incentivize private activities to align with our vision?
Develop funding strategy recommendations for
ongoing activities, programmed funding
initiatives, and private activities
Questions answered by this task Outcomes
How will BW12 analysis help individuals? How will BW12 analysis help county planning and
implementation? How can we help educate and inform the public? How can we partner better with our county neighbors?
Develop and present final report
Develop media as designed within the outreach
strategy
Conduct BW12 101 workshop - basics
Conduct BW12 201 workshop – options and
economics
Develop dissemination website
Develop property assessment web apps
ASFPM Showcase (Conceptual Model)
Existing Study Data must be Analyzed for
providing Insights into:
Relative Magnitude of Issues
Hotspots of Interest
Data Collection Efforts Needed
Breadth of Knowledge
Caveat Emptor
Building the Logical Model
Objectives for NC
Provide an assessment of potential rate increases compared to current
policy values in a geospatial format,
Identify target areas or neighborhoods of concern where there may be
patterns of significance or clusters of policies with the potential for very
high actuarial rates.
Identify strategies for reducing the impact of BW12 on current and
future development
Statewide Plan Objectives – Case Example
Framework Organization
Framework intends to represent a flexible model through which a
certain number of required attributes are garnered.
Varying resolutions provide different reporting opportunities
High quality, structure level data is a rarity
Sampling techniques should be developed to model the BW12
Impact trends and used to extrapolate from or recalibrate statewide
results
Step 1: Geocoding and
Conflation
Geocode Policy Data
Match Policy Data to Building Footprints
Integrate Tax Assessor Database
Information
Step 2: Analyze Policy Data
Identify Policy Attributes Relevant to BW12 Actuarial
Rate Triggers
Determine Time Frame for Actuarial
Rate Phase In
Estimate Localized BW12 Financial
Impact
Determine Effects of Revised Map
Maintenance SFHAs
Step 3: Aggregate Results to Political
Boundaries
Census Block Group
Community Sub Basins Custom Boundaries
Provided by NC GTM
Step 4: Review Hotspots for Mitigating the
Impacts of BW12
Map BW12 Financial Impact
Hotspots
Present Mitigation Strategies
• CRS 370
• Property Elevation Collection
• Grants
Provide Recommendations on Limiting Impacts
Recommend Actions for
Potential CRS Rating Gains
Conceptual Model, and Work Breakdown Structure
1. Best case scenario, individual building footprints serve as the highest
resolution units which can be flagged as impacted. Conflation of
actual policy data
a) This includes the ability to perform financial analyses such as actuarial
rate calculations, and averaged annualized lost estimates, accounting for
real world coverage totals.
b) At such a resolution, mitigation strategy scenarios can also be triggered
within the framework at a structure level such as buyout or structure
elevation.
Best Case Scenario
Difficulties and Options
1. Geocoding of Policy, Claims, Repetitive Loss, Severe Repetitive Loss,
Elevation Certificates and Additional Localized Data Sets Such as Known
Locations of Severe Damage as a Result of a Storm.
a) Size of the Study and Ability to Conflate Geocoded Data should
directly influence the route taken within the framework – specifically
the resolution which is chosen as the ‘hub’ for reporting (CBG,
Community etc.).
2. Lack of Policy Data
1. In some jurisdictions, policy data may not be available due to FEMA
denial or a lack of community engagement on the issue.
1. the framework, through the abstractions in the system, can
accommodate an alternate sources such as the tax assessors
database for property locations within the SFHA.
Implications to North Carolina
59 | April 30, 2013
PDF maps identifying hotspots in a few selected areas;
A set of metrics to help guide communities about the benefits in obtaining a better CRS
rating;
Information to help communities identify viable mitigation funds and projects for
mitigation activities;
New Higher Standard actions for communities to help reduce affect from BW12 on
newly-mitigation properties and future development; and
Outreach presentation slides for use by the NCFMP at various meetings with
communities and/or other government agencies.
Community Outreach Toolbox
Mobile-friendly application for mobile web browsers (agnostic of OS type)
Address-based results providing homeowners in BW12 Impacted areas, advice on the
following:
Elevation to reconstruct post-Disaster, or Optionally
Cost impacts of reconstruction
Cost impacts to annual insurance premiums based on various First Floor Elevation (FFE) scenarios
Savings or Losses over a 15 and 30 year period based on various reconstruction scenarios
Qualitative estimate of confidence in the results presented to the user
Option to refine results by allowing users to identify a specific property on a map and by providing their
property’s first floor elevation (FFE) and other building information
Customized/Contextualized Help within App User Interface (UI)
Scalable:
Advisory services for additional areas of interest
Additional tools and features that assist the users with their decisions towards resilience
The Best Defense
Geocoding Service Reverse
Geocoding Service
Advisory Info
Service LAG Service
Advisory Model
Service
ArcTool box 10.1
(GP Rebuild
Tools)
Map Layers
Arc
GIS
Se
rve
r 1
0.1
SQL Server 2012
/SDE
Rebuild Mobile App Geoprocessing Services IIS Web Server
ArcGIS Web
Adaptor
Applications Users (Mobile and Web Browsers)
Clie
nt
ArcGIS Online (AGOL) - Gateway
Map Layers
Application Architecture
Map Service
Web Processing Services
Discoverable on
FEMA AGOL