Case Studies
May 26, 2018

Mental Models of Navigation Safety to Inform Risk Management Decisions: Case Study on the Houston Ship Channel

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 4, Issue 3

Abstract

The Houston Ship Channel (HSC) is one of the busiest waterway corridors in the United States. Since the channel’s expansion in 2005, concerns have arisen about design deficiencies in the HSC in the area of the Bayport Ship Channel (BSC), especially north of the turn at Five Mile Cut. A mental models expert elicitation exercise was conducted in order to identify safety concerns arising from these design deficiencies and provide qualitative data that can structure analysis of technical data like those from automatic identification system (AIS) databases, which can better connect possible design deficiencies to incident outcomes. The elicitation produced an influence diagram to enable later causal reasoning and Bayesian analysis for the HSC and BSC confluence and nearby areas on the HSC, and helped to prime a comprehensive study of the feasibility of safety and performance modifications on this reach of the HSC.

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Acknowledgments

The authors would like to thank Ned Mitchell for providing the AIS data. Thank you also to George Shephard for assistance in figure reproduction. This work was funded by the U.S. Army Corps of Engineers Dredging Operations and Environmental Research (DOER) Program. Permission was granted by the USACE Chief of Engineers to publish this material. The views and opinions expressed in this paper are those of the individual authors and not those of the U.S. Army or other sponsor organizations.

References

Akhtar, M. J., and Utne, I. B. (2014). “Human fatigue’s effect on the risk of maritime groundings: A Bayesian network modeling approach.” Saf. Sci., 62, 427–440.
Arnsdorf, I., and Murtaugh, D. (2014). “Big ships play Texas chicken in congested Houston channel.” ⟨http://www.bloom-berg.com/bw/articles/2014-02-27/houston-ship-channel-congested-by-u-dot-s-dot-oil-and-gas-boom⟩ (Apr. 1, 2015).
Bates, M. E., Grieger, K. D., Trump, B. D., Keisler, J. M., Plourde, K. J., and Linkov, I. (2016). “Emerging technologies for environmental remediation: Integrating data and judgment.” Environ. Sci. Technol., 50(1), 349–358.
Blaunstein, R., Trump, B., and Linkov, I. (2014). “Nanotechnology risk management: An insurance industry perspective.” Nanotechnology environmental health and safety: Risks, regulation, and management, William Andrew, Norwich, NY, 247–263.
Bostrom, A. (2008). “Lead is like mercury: Risk comparisons, analogies and mental models.” J. Risk Res., 11(1–2), 99–117.
Bostrom, A., Böhm, G., and O’Connor, R. E. (2013). “Targeting and tailoring climate change communications.” Wiley Interdiscip. Rev. Clim. Change, 4(5), 447–455.
Bridges, T., et al. (2012). Increased environmental beneficial use of dredged material: Application of expert mental modeling, U.S. Army Corps of Engineers Technical Note, Vicksburg, MS.
Chu-Agor, M. L., Muñoz-Carpena, R., Kiker, G., Emanuelsson, A., and Linkov, I. (2011). “Exploring vulnerability of coastal habitats to sea level rise through global sensitivity and uncertainty analyses.” Environ. Modell. Software, 26(5), 593–604.
Collier, Z. A., Bates, M. E., Wood, M. D., and Linkov, I. (2014). “Stakeholder engagement in dredged material management decisions.” Sci. Total Environ., 496, 248–256.
Collier, Z. A., Trump, B. D., Wood, M. D., Chobanova, R., and Linkov, I. (2016). “Expertise-driven technology innovation.” Int. J. Bus. Continuity Risk Manage., 6(3), 163–181.
Cullen, A. C., and Frey, H. C. (1999). Probabilistic techniques in exposure assessment: A handbook for dealing with variability and uncertainty in models and inputs, Springer Science & Business Media, New York.
Davis, T. E., and Webb, D. W. (2012). “Navigation study for Bayport Flare improvement.”, U.S. Army Corps of Engineers, Vicksburg, MS.
Dobbins, J., and Langsdon, L. (2012). “Generation of inland waterway trip information using automatic identification system (AIS) data.” Transportation Research Record, National Research Council, Washington, DC.
Dombroski, M., Fischhoff, B., and Fischbeck, P. (2006). “Predicting emergency evacuation and sheltering behavior: A structured analytical approach.” Risk Anal., 26(6), 1675–1688.
Eleye-Datubo, A. G., Wall, A., and Wang, J. (2008). “Marine and offshore safety assessment by incorporative risk modeling in a fuzzy-Bayesian network of an induced mass assignment paradigm.” Risk Anal., 28(1), 95–112.
Fossati, A., Schonmann, P., and Fua, P. (2011). “Real-time vehicle tracking for driving assistance.” Mach. Vis. Appl., 22(2), 439–448.
Frey, C. H., and Patil, S. R. (2002). “Identification and review of sensitivity analysis methods.” Risk Anal., 22(3), 553–578.
Glenn, M. (2015). “Shelter-in-place continues after ship channel collision.” ⟨http://www.chron.com/houston/article/Ships-collided-at-foggy-Ship-Channel-6123633.php⟩ (Mar. 10, 2015).
Goerlandt, F., and Montewka, J. (2015). “A framework for risk analysis of maritime transportation systems: A case study for oil spill from tankers in a ship-ship collision.” Saf. Sci., 76, 42–66.
Gough, D. (2007). “Weight of evidence: A framework for the appraisal of the quality and relevance of evidence.” Res. Pap. Educ., 22(2), 213–228.
Haapasaari, P., Helle, I., Lehikoinen, A., Lappalainen, J., and Kuikka, S. (2015). “A proactive approach for maritime safety policy making for the Gulf of Finland: Seeking best practices.” Mar.Policy, 60, 107–118.
Hall, R. W., and Tsao, H. S. J. (1997). “Automated highway system deployment.” Automated highway systems, Springer, New York, 325–334.
Hänninen, M., and Kujala, P. (2012). “Influences of variables on ship collision probability in a Bayesian belief network model.” Reliab. Eng. Syst. Saf., 102, 27–40.
Hänninen, M., et al. (2013). “Expert elicitation of a navigation service implementation effects on ship groundings and collisions in the Gulf of Finland.” Proc. Inst. Mech. Eng. Part O: J. Risk Reliab., 228(1), 19–28.
Hatch, L., et al. (2008). “Characterizing the relative contributions of large vessels to total ocean noise fields: A case study using the Gerry E. Studds Stellwagen Bank National Marine Sanctuary.” Environ. Manage., 42(5), 735–752.
Howard, R. A., and Matheson, J. E. (2005). “Influence diagrams.” Decis. Anal., 2(3), 127–143.
ITU (International Telecommunications Union). (2014). “Technical characteristics for an automatic identification system using time division multiple access in the VHF maritime mobile frequency band.”, Geneva.
Kiker, G. A., Bridges, T. S., Varghese, A., Seager, T. P., and Linkov, I. (2005). “Application of multicriteria decision analysis in environmental decision making.” Integr. Environ. Assess. Manage., 1(2), 95–108.
Kovacs, D., Thorne, S., and Butte, G. (2017). “Influence of the CHEMM tool on planning, preparedness, and emergency response to hazardous chemical exposures: A customized strategic communications process based on mental modeling.” Mental modeling: Risk management application case studies, M. D. Wood, S. Thorne, D. Kovacs, G. Butte, and I. Linkov, eds., Springer, New York, 105–131.
Kuronen, J., and Tapaninen, U. (2010). Views of Finnish maritime experts on the effectiveness of maritime safety policy instruments, Turun Yliopiston, Turku, Finland.
Lehikoinen, A., Luoma, E., Hänninen, M., Storgård, J., and Kuikka, S. (2012). “Probabilistic risk assessment and decision support tools for the evaluation of oil transport in the Gulf of Finland, North-Eastern Baltic Sea.” Ph.D. dissertation, International Environmental Modelling and Software Society, Fort Collins, CO.
Linkov, I., and Moberg, E. (2011). Multi-criteria decision analysis: Environmental applications and case studies, CRC Press, Boca Raton, FL.
Linkov, I., et al. (2011). “Use of multicriteria decision analysis to support weight of evidence evaluation.” Risk Anal., 31(8), 1211–1225.
Linkov, I., et al. (2012). “Civilian Response Corps Force review: The application of multi-criteria decision analysis to prioritize skills required for future diplomatic missions.” J. Multi-Criteria Decis. Anal., 19(3–4), 155–168.
Linkov, I., Bates, M. E., Trump, B. D., Seager, T. P., Chappell, M. A., and Keisler, J. M. (2013). “For nanotechnology decisions, use decision analysis.” Nano Today, 8(1), 5–10.
Linkov, I., Trump, B., Jin, D., Mazurczak, M., and Schreurs, M. (2014). “A decision-analytic approach to predict state regulation of hydraulic fracturing.” Environ. Sci. Eur., 26(1), 1.
Linkov, I., Varghese, A., Jamil, S., Seager, T. P., Kiker, G., and Bridges, T. (2004). “Multi-criteria decision analysis: A framework for structuring remedial decisions at contaminated sites.” Comparative risk assessment and environmental decision making, I. Linkov and A. B. Ramadan, eds., Springer, Dordrecht, Netherlands, 15–54.
Martins, M. R., and Maturana, M. C. (2013). “Application of Bayesian belief networks to the human reliability analysis of an oil tanker operation focusing on collision accidents.” Reliab. Eng. Syst. Saf., 110, 89–109.
Mazaheri, A., Montewka, J., Kotilainen, P., Sormunen, O.-V. E., and Kujala, P. (2015). “Assessing grounding frequency using ship traffic and waterway complexity.” J. Navig., 68(1), 89–106.
McDaniels, T. L., Gregory, R. S., and Fields, D. (1999). “Democratizing risk management: Successful public involvement in local water management decisions.” Risk Anal., 19(3):497–510.
Menzie, C., et al. (1996). “Special report of the Massachusetts weight-of-evidence workgroup: A weight-of-evidence approach for evaluating ecological risks.” Hum. Ecol. Risk Assess., 2(2), 277–304.
Mitchell, K., and Scully, B. (2014). “Waterway performance monitoring via automatic identification system (AIS) data.” Transp. Res. Rec., 2426, 20–26.
Montewka, J., Ehlers, S., Goerlandt, F., Hinz, T., Tabri, K., and Kujala, P. (2014). “A framework for risk assessment for maritime transportation systems—A case study for open sea collisions involving RoPax vessels.” Reliab. Eng. Syst. Saf., 124, 142–157.
Montewka, J., Weckström, M., and Kujala, P. (2013). “A probabilistic model estimating oil spill clean-up costs–A case study for the Gulf of Finland.” Mar. Pollut. Bull., 76(1–2), 61–71.
Morgan, M. G. (2002). Risk communication: A mental models approach, Cambridge University Press, Cambridge, U.K.
Nerheim, S. W. (2015). “State of the waterway 2015.” ⟨http://www.uscg.mil/vtshouston/docs/sww_2015%20v2.pdf⟩ (Apr. 1, 2015).
NTSB (National Transportation Safety Board). (2012). “Collision of Tankship Elka Apollon with containership MSC Nederland, Houston Ship Channel, Upper Galveston Bay, Texas, October 29, 2011.”, Washington, DC.
Perez, H. M., et al. (2009). “Automatic identification systems (AIS) data use in marine vessel emission estimation.” 18th Annual Int. Emission Inventory Conf., Vol. 14, U.S. Environmental Protection Agency, Clearinghouse for Inventories and Emissions Factors, Research Triangle Park, NC.
Pitana, T., Kobayashi, E., and Wakabayashi, N. (2010). “Estimation of exhaust emissions of marine traffic using automatic identification system data (case study: Madura Strait area, Indonesia).” OCEANS 2010, IEEE, Sydney, 24–27.
Rao, L., Mansingh, G., and Osei-Bryson, K. M. (2012). “Building ontology based knowledge maps to assist business process re-engineering.” Decis. Supp. Syst., 52(3), 577–589.
Salmon, P. M., Cornelissen, M., and Trotter, M. J. (2012). “Systems-based accident analysis methods: A comparison of Accimap, HFACS, and STAMP.” Saf. Sci., 50(4), 1158–1170.
Saltelli, A. (2002). “Sensitivity analysis for importance assessment.” Risk Anal., 22(3), 579–590.
Scully, B., and Mitchell, K. N. (2015). “Archival automatic identification system (AIS) data for navigation project performance evaluation.”, U.S. Army Engineer Research and Development Center, Vicksburg, MS.
Simonse, L. W., Badke-Schaub, P., and LWL, E. (2015). “Business model design through a designer’s lens: Translating, transferring and transforming cognitive configurations into action.” 31st EGOS: European Group for Organisation Studies Colloqium-SGW 65, Athens, Greece.
Suter, G. W., and Cormier, S. M. (2011). “Why and how to combine evidence in environmental assessments: Weighing evidence and building cases.” Sci. Total Environ., 409(8), 1406–1417.
Tetreault, B. (2005). “Use of the automatic identification system (AIS) for maritime domain awareness (MDA).” OCEANS 2005. Proc., MTS/IEEE, Vol. 2, IEEE, New York, 1590–1594.
Trucco, P., Cagno, E., Ruggeri, F., and Grande, O. (2008). “A Bayesian belief network modelling of organisational factors in risk analysis: A case study in maritime transportation.” Reliab. Eng. Syst. Saf., 93(6), 845–856.
Trump, B. D., Linkov, F., Edwards, R. P., and Linkov, I. (2015). “Not a humbug: The evolution of patient-centered medical decision-making.” Evidence Based Med., 20(6), 193–197.
USACE (U.S. Army Corps of Engineers). (1982). “Water resource policies and authorities: Modifications to completed projects.”, Washington, DC.
USACE (U.S. Army Corps of Engineers). (1984). “Hydraulic design of small boat harbors.”, Washington, DC.
USACE (U.S. Army Corps of Engineers). (1995). “Hydraulic design guidance for deep-draft navigation projects.”, Washington, DC.
USACE (U.S. Army Corps of Engineers). (2008). “Coastal engineering manual.”, Washington, DC.
USACE (U.S. Army Corps of Engineers). (2015). “USACE navigation: Meeting America’s maritime transportation needs.” ⟨http://www.usace.army.mil/Portals/2/docs/civilworks/budget/strongpt/fy16sp_navigation.pdf⟩ (Apr. 1, 2015).
USACE (U.S. Army Corps of Engineers). (2016). “Houston ship channel 45-foot expansion channel improvement project (HSC ECIP).” Mega-Study Alternatives Milestone Meeting, Galveston, TX.
U.S. Army. (2016). “District to hold Houston Ship Channel expansion channel improvement project public scoping meeting.” ⟨https://www.army.mil/article/166390/⟩ (Mar. 13, 2017).
U.S. Coast Guard National Data Center. (2015). “Automatic identification system.” ⟨⟩ (Apr. 1, 2015).
Valdez Banda, O. A., Goerlandt, F., Kuzmin, V., Kujala, P., and Montewka, J. (2016). “Risk management model of winter navigation operations.” Mar. Pollut. Bull., 108(1), 242–262.
Waterway Simulation Technology, Inc. (2011). “Ship maneuvering simulation study of alternative channel dimensions and layouts of the Bayport Ship Channel, TX.”, Houston Pilots and Port of Houston Authority, Vicksburg, MS.
Wiley, D., Thompson, M., Pace, R., III, and Levenson, J. (2011). “Modeling speed restrictions to mitigate lethal collisions between ships and whales in the Stellwagen Bank National Marine Sanctuary, U.S.A.” Biol. Conserv., 144(9), 2377–2381.
Wood, M. D., Bostrom, A., Bridges, T., and Linkov, I. (2012). “Cognitive mapping tools: Review and risk management needs.” Risk Anal., 32(8), 1333–1348.
Wood, M., Thorne, S., and Butte, G. (2017a). “Technology infusion and marketing.” Mental modeling: Risk management application case studies, M. D. Wood, S. Thorne, D. Kovacs, G. Butte, and I. Linkov, eds., Springer, New York, 69–82.
Wood, M. D., Thorne, S., Kovacs, D., Butte, G., and Linkov, I. (2017b). Mental modeling approach: Risk management application case studies, Springer, New York.
Yoe, C. (2014). “Transforming water resources planning through SMART planning.” J. Water Resour. Plann. Manage., 02514001.

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Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 4Issue 3September 2018

History

Received: Apr 25, 2017
Accepted: Nov 1, 2017
Published online: May 26, 2018
Published in print: Sep 1, 2018
Discussion open until: Oct 26, 2018

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Research Psychologist, Environmental Laboratory, U.S. Army Engineer Research and Development Center, 696 Virginia Rd., Concord, MA 01742 (corresponding author). ORCID: https://orcid.org/0000-0002-1140-1526. E-mail: [email protected]
Zachary A. Collier [email protected]
Ph.D. Candidate, Dept. of Systems and Information Engineering, Univ. of Virginia, 151 Engineer’s Way, P.O. Box 400747, Charlottesville, VA 22904-4747. E-mail: [email protected]
Todd S. Bridges [email protected]
Senior Research Scientist, Environmental Laboratory, U.S. Army Engineer Research and Development Center, 3909 Halls Ferry Rd., Vicksburg, MS 39180. E-mail: [email protected]
Edmond J. Russo Jr. [email protected]
Deputy District Engineer, U.S. Army Corps of Engineers, Galveston District, 2000 Fort Point Rd., Galveston, TX 77550. E-mail: [email protected]

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