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Culvert Vulnerability and Prioritization: Reconciling Currently Available Approaches and Data

Thomas A. Wall, Ph.D. Risk & Infrastructure Science Center Argonne National Laboratory TRB International Conference on Transportation System Resilience to Climate Change and Extreme Weather Events Washington, D.C. September 17, 2015

Adjo Amekudzi-Kennedy, Ph.D. School of Civil and Environmental Engineering Georgia Institute of Technology

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Heavy & Extreme Precipitation in the United States

Observed

• Changes in the amount of precipitation falling in heaviest 1% of rain events (increased nationally by 20% during the 20th century[1])

Projected • 20-year event return period projection (A1B):

– 12-15 year return period by mid 21st century[2]

– 6-8 year return period by end of 21st century[2] nationally

Source (both figures): [3]

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Heavy & Extreme Precipitation in the United States

Implications for Highway/Roadway Culverts

• Increased heavy and extreme precipitation in the future could lead to increased runoff and stream flows

• Particularly Vulnerable to Increased Flows – Increase the potential for waterway blockage and

scour[4]

– Hydraulic head pressure exerted on embankment[5]

• Greater Number of Potential Network Failure Points

– Minnesota: 13,120 bridges; 72,414 culverts[6,7]

– New York: 17,420 bridges; 66,533 culverts[6,8]

Source: [10]

Source: [11]

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Risk-Based Adaptation (1)

Review of 29 climate change adaptation frameworks[12]

• Dominant approach: risk-management – Risk: f (likelihood, consequence) – Risk assessment adaptation prioritization

• Difficult to assign probabilistic likelihood to

future climate impacts

• Alternate model: the Catastrophe Model[13,14]

– National Climate Assessment [15]

– Similar to DHS National Infrastructure Protection Plan[17] – Threat, Vulnerability, Consequence

Source: [18]

Source: [13]

Consequence

Threat

Vulnerability

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Risk-Based Adaptation (2)

• Prioritization using three “dimensions” of risk

• Multiple emission scenarios robust outcomes

2. Impact Exposure • Multiple climate scenarios • Multiple time frames

1. Asset Data • Spatial inventory • Condition and functional

performance

3. Asset Vulnerability • Condition and performance of

assets • Magnitude of change in

climate impacts

4. Asset Criticality • Asset importance to the system based upon several criteria

5. Asset Prioritization • Multiple emission scenarios for each timeframe to generate robust outcomes

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Risk-Based Adaptation (2)

• Prioritization using three “dimensions” of risk

• Multiple emission scenarios robust outcomes

2. Impact Exposure • Multiple climate scenarios • Multiple time frames

1. Asset Data • Spatial inventory • Condition and functional

performance

3. Asset Vulnerability • Condition and performance of

assets • Magnitude of change in

climate impacts

4. Asset Criticality • Asset importance to the system based upon several criteria

5. Asset Prioritization • Multiple emission scenarios for each timeframe to generate robust outcomes

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Culvert Failure & Vulnerability

• Culvert failure often stems from “failure of the soil/pipe structure.”[5]

– Piping and seepage – Scour and embankment erosion – Blockage and hydrostatic pressure

• Generalization of culvert failure modes – Embankment-Related[5, 19-23]

– Blockage-Related[5, 24, 25]

• Review of Culvert Inspection and Rating Systems – NBIS Culvert Inspection Manual[27] – Subjective numerical rating scales (e.g., 0 to 9; 1 to 5; low/med/high) – Embankment, blockage, structure

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Culvert Vulnerability & Prioritization – Data (2013)

Minnesota DOT 72,414 items; condition, and functional performance

New York State DOT 66,533 items; condition, and functional performance

Washington State DOT Four select routes given: 10,413; Inventory only

Oregon DOT 3,190 items; functional performance

Culvert Management Practices Vary[27-30]

– No national guidance for culvert management or data collection – Wide variability in types of culvert data and collection practices

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Culvert Vulnerability & Prioritization

Performance-Based Vulnerability Index MnDOT • Yes = 3; No = 1; Percentages assigned to ranges • Items with >3 rating items omitted

NYSDOT • Assigned to 1 - 3 scale (used overall condition scale) • Items with >2 ratings omitted

ODOT • Blockage ratings only • Poorest blockage rating used among those recorded

WSDOT • Location only (Climate impact exposure)

Rating Item Rating Category Rating Scale Sediment Percentage Blockage Percentage Plugged Blockage Yes / No Erosion Embankment Yes / No Piping Embankment Yes / No Inslope Cavity Embankment Yes / No

Rating Item Rating Category Rating Scale Small Culverts

Channel Opening Blockage 1 to 7 Channel Scour Embankment 1 to 7

Large Culverts Channel Waterway Opening Blockage 1 to 7 Channel Erosion and Scour Embankment 1 to 7

Low Medium High < 1.6 1.6 – 2.3 ≤ 2.3

Blockage Rating Item Corresponding Rating Value 1 2 3

Inside Blockage Rating 0% - 30% 30% - 75% > 75% Drift Rating 0% - 25% 25% - 75% > 75% Vegetation Obstruction Rating 0% - 25% 25% - 75% > 75%

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Results

State Vulnerability Total

Culverts 1 2 3 Low Certainty/ Unrated*

MnDOT 63677 87.9% 1766 2.4% 152 0.2% 6819 9.4% 72414 NSYDOT 45203 67.9% 4122 6.2% 336 0.5% 16872 25.4% 66533 ODOT 2119 66.4% 835 26.2% 188 5.9% 48 1.5% 3190

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Conclusions

• Existing Data can be used for network-level vulnerability assessment

• Data completeness

– Problematic as large numbers of assets (culverts) lack sufficient data items/ratings to complete classification

• Data consistency (among agencies)

– Some agencies do not collect extensive data about functional performance of culverts – National guidelines for data collection practices may be more appropriate than national

standards

• Vulnerability assessments – Flexibility is necessary given differences in data collection and inspection practices – National guidance could enable greater consistency state to state (region to region) – Refinement of vulnerability index through weighting, additional indicators

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Questions?

twall@anl.gov

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References 1. Kunkel, K., Brooks, H., Bromirski, P., Cavazos, T., Douglas, A., Emanuel, K., Groisman, P., Holland, G., Knutson, T., Kossin, J., Komar, P., Levison, D., and Smith, R. (2008).

"Observed Changes in Weather and Climate Extremes." Weather and Climate Extremes in a Changing Climate Regional Focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands, T. R. Karl, G. A. Meehl, C. D. Miller, S. J. Hassol, A. M. Waple, and W. L. Murray, eds., U.S. Climate Change Science Program, Washington, DC.

2. Kharin, V. V., Zwiers, F., Zhang, X., and Hegerl, G. C. (2007). "Changes in Temperature and Precipitation Extremes in the IPCC Ensemble of Global Coupled Model Simulations." Journal of Climate, 20, 1419-1444.

3. Walsh, J., D. Wuebbles, K. Hayhoe, J. Kossin, K. Kunkel, G. Stephens, P. Thorne, R. Vose, M. Wehner, J. Willis, D. Anderson, S. Doney, R. Feely, P. Hennon, V. Kharin, T. Knutson, F. Landerer, T. Lenton, J. Kennedy, and R. Somerville, 2014: Ch. 2: Our Changing Climate. Climate Change Impacts in the United States: The Third National Climate Assessment, J. M. Melillo, Terese (T.C.) Richmond, and G. W. Yohe, Eds., U.S. Global Change Research Program, 19-67. doi:10.7930/J0KW5CXT.

4. FHWA (2012). "Bridge Inspector's Reference Manual." F. H. Administration, ed., US Department of Transportation, Washington, DC. 5. Tenbusch, A., Dorwart, B., and Tenbusch, A. F. (2009). "Failing Culverts - The Geotechnical Perspective." Tenbusch and Associates, Lewisville, TX. 6. FHWA (2013). National Bridge Inventory. United States Department of Transportation, Washington, DC. 7. Data provided by MnDOT (2013) 8. Data provided by NYSDOT (2013) 9. Pealer, S. (2012). "Lessons from Irene: Building Resiliency As We Rebuild." Vermont Agency of Natural Resources, Waterbury, VT 10. Delaware County Engineer. Centerburg Road Bridge Replacement DEL-CR48-5.53 (Porter Township. 2013. [cited 2013 April 17]; Available from:

http://www.co.delaware.oh.us/engineer/projects/centerburgbridge.htm 11. Atlanta Journal-Constitution, (2009) “Atlanta flood 2009: Most Captivating Photos,” http://projects.ajc.com/gallery/view/metro/atlanta/best-flood-2009/ 12. Wall, T. A., and Meyer, M. D. (2013). "Risk-Based Adaptation Frameworks for Climate Change Planning in the Transportation Sector: A Synthesis of Practice."

Transportation Research Board Annual Meeting, National Academies, Washington, DC. 13. Grossi, P., and Kunreuther, H. (2005). "Catastrophe Modeling: A New Approach to Managing Risk." Springer, New York, NY. 14. Kunreuther, H. C., and Michel-Kerjan, E. O. (2007). "Climate Change, Insurability of Large-scale Disasters and the Emerging Liability Challenge." NBER Working Paper The

National Bureau of Economic Research, Cambridge, MA. 15. Moss, R., Scarlett, P. L., Kennyey, M. A., Kunreuther, H., Lempert, R., Manning, J., Williams, B. K., Boyd, J. W., Kaatz, L., and Patton, L. (2013). "26. Decision Support:

Supporting Policy, Planning, and Resource Management Decisions in a Climate Change Context." NCADAC Draft Climate Assessment Report, J. M. Melillo, T. Richmond, and G. Yohe, eds., U.S. Global Change Research Program, Washington, D.C.

16. Botzen, W. J. W., and Van Den Bergh, J. C. J. M. (2009). "Managing natural disaster risks in a changing climate." Climate change as environmental and economic hazard, B. Porfiriev, ed., Earthscan, London, 209-225.

17. Department of Homeland Security (2013). "NIPP 2013: Partnering for Critical Infrastructure Security and Resilience." National Infrastructure Protection Plan, Department of Homeland Security, Washington D.C.

18. MacArthur, J., et al., Climate Change Impact Assessment for Surface Transportation in the Pacific Northwest and Alaska, 2012, Oregon Transportation Research and Education Consortium & Washington State DOT: Olympia, WA.

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References (con’t) 19. Stuhff, D. (2007). "Aging Culverts - Problems and Repairs." Utah Department of Transportation, Salt Lake City, UT. 20. Thompson, P. L., and Kilgore, R. T. (2006). "Hydraulic Design of Energy Dissipators for Culverts and Channels, Hydraulic Engineering Circular 14, 3rd

Edition." Federal Highway Administration, Washington, DC. 21. Van Kampen, P. "Culvert Design, Analysis - Talk 2." Proc., Seventeenth Statewide Conference on Local Bridges, New York State Department of

Transportation. 22. WisDOT (2004). "Culverts - Proper Use and Installation." Wisconsin Transportation Bulletin, No. 15, Wisconsin Department of Transportation, Madison,

WI. 23. Schall, J. D., Thompson, P. L., Zerges, S. M., Kilgore, R. T., and Morris, J. L. (2012). "Hydraulic Design of Highway Culverts." Hydraulic Design Series

Number 5, Federal Highway Administration, United States Department of Transportation, Washington, D.C. 24. Bradley, J. B., Richards, D. L., and Bahner, C. D. (2005). "Debris Structures - Evaluation and Countermeasures, Hydraulic Engineering Circular 9, 3rd

Edition." Federal Highway Administration, Washington, DC. 25. Flanagan, S. (2004). "How Culverts Fail." California Board of Forestry and Fire Protection, Monitoring Study Group, Sacramento, CA. 26. Arnoult, D. (1986). "Culvert Inspection Manual." Federal Highway Administration, Washington, D.C. 27. FHWA (2007). "Culvert Management Systems - Alabama, Maryland, Minnesota, and Shelby County." Federal Highway Administration, Washington, DC. 28. Najafi, M., Salem, S., Bhattachar, D., Salman, B., and Patil, R. (2008). "An Asset Management Approach for Drainage Infrastructure and Culverts."

Midwest Regional University Transportation Center, Madison, WI. 29. Wyant, D. C., Beakley, J., Dash, U., Goddard, J. B., Hill, J. J., Katona, M. G., Maher, S. F., McLemore, S. A., O'Fallon, J. D., Roberts, B. C., Thompson, P. L.,

and Zandt, M. V. (2002). "NCHRP Synthesis 303 - Assessment and Rehabilitation of Existing Culverts: A Synthesis of Practice." Transportation Research Board, Washington, DC.

30. FHWA. (2014) “Culvert Management Case Studies: Vermont, Oregon, Ohio and Los Angeles County.” United States Department of Transportation, Washington DC.

31. Department of Defense (DoD) Strategic Environmental Research and Development (SERDP) Grant Number 15 RC02-035

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Climate Impact Exposure

• When attribute or functional performance data is not available, vulnerability could be assessed as function of exposure only

• Precipitation streamflow

– Intensity duration frequency (IDF) curves that account for future climate changes to project streamflow

– Analysis conducted at watershed-level

• Argonne and Washington State University are developing “Next Generation” precipitation and runoff IDF curves for Strategic Environmental Research and Development Program (SERDP) at DoD[31]