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1.  FHWA Climate Change Resilience Program ◦ Assessment Framework ◦ Transportation Vulnerability  Flash Flood Vulnerability project ◦ Background ◦ Objectives.

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Presentation on theme: "1.  FHWA Climate Change Resilience Program ◦ Assessment Framework ◦ Transportation Vulnerability  Flash Flood Vulnerability project ◦ Background ◦ Objectives."— Presentation transcript:

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2  FHWA Climate Change Resilience Program ◦ Assessment Framework ◦ Transportation Vulnerability  Flash Flood Vulnerability project ◦ Background ◦ Objectives ◦ Key project questions ◦ System-wide vulnerability assessment ◦ Facility-level risk analysis

3  Program Goals:  Advance transportation climate resilience activities  Assist FHWA in building the Vulnerability Framework into an Adaptation Framework   Funded 5 pilot projects in 2010 to test an assessment conceptual model  Funded 19 pilot projects, including Minnesota, in 2013 as part of an effort to test the Framework

4 A guide for transportation agencies to assess vulnerability to climate change and extreme weather events 3 key steps: 1.Define study assets and climate variables 2.Assess vulnerability 3.Incorporate results into decision making *http://www.fhwa.dot.gov/environment/climate_change/adaptation/ resources_and_publications/vulnerability_assessment_framework/

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6 “Climate change vulnerability in the transportation context is a function of a transportation system’s exposure to climate effects, sensitivity to climate effects, and adaptive capacity.” (Vulnerability Framework)  Exposure- whether the asset or system is located in an area experiencing direct impacts of climate change  Sensitivity - how the asset or system fares when exposed to an impact  Adaptive capacity - the systems’ ability to adjust or cope with existing climate variability or future climate impacts

7  Minnesota GO Vision & Statewide Multimodal Transportation Plan identified the risk of flash flooding as a result of changing precipitation patterns due to climate change.  From 1958 to 2011, the Midwest has seen 45% increase in very heavy precipitation (NOAA)

8  Better understand the trunk highway network’s risk from flash flooding  Identify cost-effect options to improve the network’s resiliency  Support the development of Minnesota’s first Transportation Asset Management Plan (TAMP)  Provide feedback to FHWA on the Draft Framework

9  General systems-level vulnerability assessment of the trunk highway network in District 1 and District 6 ◦ Timeline: September 2013 – February/March 2014  Focused facility-level adaptation assessment for specific high-risk facilities identified in the system-level assessment  March 2014 – June/July 2014

10  How is the climate projected to change in the future?  What are acceptable methods for analyzing potential risks caused by those changes?  What are risks identified for future conditions?  What adaptation measure can be put in place to address risks?  How are decisions made on what is the most appropriate course of action?

11  Vulnerability = Structural strength of assets (bridges, road segments, culverts) against projected climate changes (precipitation)  Risk includes two components: 1.The likelihood an event (flash flooding) will occur 2.The magnitude and consequences of climate events

12  High-level screen of trunk highway network  Identify assets at risk from flash flooding ◦ Obtain information on asset condition and features ◦ Gather information on climate projection changes ◦ Rank and prioritize assets based on resiliency and projected climate changes (risk score)  Risk scores will help determine where to prioritize facility level adaptation assessments

13  SimClim Version  A proprietary software developed by Climsystems Ltd., a private firm based in New Zealand  Uses AR4 climate modeling done for the IPCC  Provides ◦ Downscaled maps of projected climate variables ◦ Future precipitation return periods (given a selected emissions scenario)

14  Select weather stations in watersheds based on available data in SimClim ◦ Present-day 100-year 24-hr storm precipitation depths for each station ◦ Year 2100 projected100-year 24-hr storm precipitation depths for each station  Assign weights to each watershed based on the projected % change in the 100-year 24-hr storm ◦ Assets in watersheds where the percentage change in precipitation is higher should be considered at higher risk

15  Obtain present-day 100-year 24-hr storm precipitation depths for each station from SimClim Presently mm. (6.63 in.) for Rochester

16  Obtain year 2100 projected 100-year 24-hr storm precipitation depths for each station from SimClim Projected mm. (9.67 in.) for Rochester (46% increase)

17  Calculate a spatial average of the % change for each watershed  Use the spatial average of the % change as a weight in the risk score calculation  Assets in watersheds where the percentage change in precipitation is higher should be considered at higher risk

18  Assets will be mapped according to risk scores for each District ◦ Maps will help identify which assets to include in the facility-level assessment  System-wide assessment will be an example of method to screen for risks in other parts of the state

19  2 high-risk facilities (one per District) ◦ Determine whether (and which) adaptive actions are economically justified for each at-risk asset  Select 3 climate scenarios to test asset resilience ◦ Conduct hydrology/hydraulic analysis at facilities for each climate scenario  Assess for other potential risks (temperature, etc.)  Develop adaptation options (design alternatives)  Conduct analysis of cumulative benefit/cost values from adaption options

20  Projection out year : Based on remaining asset design life ◦ Projections will be gathered for 20-year increments  Climate model: Same as system-wide assessment  Specific climate variables ◦ Precipitation  Duration TBD by hydrologic location  Full range of return periods (2-500 years) ◦ Temperature (TBD if needed)

21  Scenarios will be used to measure resiliency of the assets  AR5 scenarios ◦ Three climate model scenarios  High – 90 th percentile of projections across all emissions scenarios and models  Medium – 50 th percentile value  Low – 10 th percentile value  Also include a scenario using 90% upper confidence interval limit from NOAA Atlas 14

22  Identify potential changes and make recommendations to the FHWA framework  System-wide vulnerability assessment ◦ Maps will be used as examples of risk screening ◦ Methodology can be recreated in different parts of the state  Facility-level analysis: ◦ Mitigation or adaptation strategies and design details will be listed as recommendations in the final report ◦ Cumulative benefit/cost values from adapting design changes will be an example for future planning and programming


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