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Review and Evaluation of the J100â 10 Risk and Resilience Management Standard for Water and Wastewater Systems

dc.contributor.authorChen, Thomas Ying‐jeh
dc.contributor.authorWashington, Valerie Nicole
dc.contributor.authorAven, Terje
dc.contributor.authorGuikema, Seth David
dc.date.accessioned2020-03-17T18:27:19Z
dc.date.availableWITHHELD_13_MONTHS
dc.date.available2020-03-17T18:27:19Z
dc.date.issued2020-03
dc.identifier.citationChen, Thomas Ying‐jeh ; Washington, Valerie Nicole; Aven, Terje; Guikema, Seth David (2020). "Review and Evaluation of the J100â 10 Risk and Resilience Management Standard for Water and Wastewater Systems." Risk Analysis 40(3): 608-623.
dc.identifier.issn0272-4332
dc.identifier.issn1539-6924
dc.identifier.urihttps://hdl.handle.net/2027.42/154262
dc.description.abstractRisk analysis standards are often employed to protect critical infrastructures, which are vital to a nation’s security, economy, and safety of its citizens. We present an analysis framework for evaluating such standards and apply it to the J100â 10 risk analysis standard for water and wastewater systems. In doing so, we identify gaps between practices recommended in the standard and the state of the art. While individual processes found within infrastructure risk analysis standards have been evaluated in the past, we present a foundational review and focus specifically on water systems. By highlighting both the conceptual shortcomings and practical limitations, we aim to prioritize the shortcomings needed to be addressed. Key findings from this study include (1) risk definitions fail to address notions of uncertainty, (2) the sole use of â worst reasonable caseâ assumptions can lead to mischaracterizations of risk, (3) analysis of risk and resilience at the threatâ asset resolution ignores dependencies within the system, and (4) stakeholder values need to be assessed when balancing the tradeoffs between risk reduction and resilience enhancement.
dc.publisherInforms
dc.publisherWiley Periodicals, Inc.
dc.subject.otherrisk management standard
dc.subject.otherdrinking water system
dc.subject.otherAsset management
dc.titleReview and Evaluation of the J100â 10 Risk and Resilience Management Standard for Water and Wastewater Systems
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBusiness (General)
dc.subject.hlbtoplevelBusiness and Economics
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/154262/1/risa13421_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/154262/2/risa13421.pdf
dc.identifier.doi10.1111/risa.13421
dc.identifier.sourceRisk Analysis
dc.identifier.citedreferenceNational Rural Water Association (NRWA). ( 2002 ). Security and vulnerability selfâ assessment guide for small drinking water systems serving populations between 3300 and 10000. Duncan, OK: National Rural Water Association.
dc.identifier.citedreferenceAle, B. J. M., Hartford, D. N. D., & Slater, D. H. ( 2018 ). The practical value of a life: Priceless, or a CBA calculation? Medical Research Archives, 6 ( 3 ), 1 â 12.
dc.identifier.citedreferenceMerkhofer, M. W., & Keeney, R. L. ( 1987 ). A multiattribute utility analysis of alternative sites for the disposal of nuclear waste. Risk Analysis, 7 ( 2 ), 173 â 194.
dc.identifier.citedreferenceMichaud, D., & Apostolakis, G. E. G. E. ( 2006 ). Methodology for ranking the elements of waterâ supply networks. Journal of Infrastructure Systems, 12 ( 4 ), 230 â 242. https://doi.org/10.1061/(ASCE)1076-0342(2006)12:4(230)
dc.identifier.citedreferenceAlderson, D. L., Brown, G. G., & Carlyle, W. M. ( 2015b ). Operational models of infrastructure resilience. Risk Analysis, 35 ( 4 ), 562 â 586. https://doi.org/10.1111/risa.12333
dc.identifier.citedreferencePA Government Services and Scientech Inc. ( 2002 ). VSAT TM User’s manual (vulnerability selfâ assessment tool). Washington, D.C.: National Association of Clean Water Agencies.
dc.identifier.citedreferencePark, J., Seager, T. P., Rao, P. S. C., Convertino, M., & Linkov, I. ( 2013 ). Integrating risk and resilience approaches to catastrophe management in engineering systems. Risk Analysis, 33 ( 3 ), 356 â 367. https://doi.org/10.1111/j.1539-6924.2012.01885.x
dc.identifier.citedreferencePateâ Cornell, E., & Guikema, S. ( 2002 ). Probabilistic modeling of terrorist threats: A systems analysis approach to setting priorities among countermeasures. Military Operations Research, 7 ( 4 ), 5 â 20. https://doi.org/10.5711/morj.7.4.5
dc.identifier.citedreferencePatéâ Cornell, M. E. ( 1996 ). Uncertainties in risk analysis: Six levels of treatment. Reliability Engineering & System Safety, 54 ( 2 ), 95 â 111. https://doi.org/10.1016/S0951-8320(96)00067-1
dc.identifier.citedreferencePatéâ Cornell, M. E. ( 1999 ). Conditional uncertainty analysis and implications for decision making: The case of WIPP. Risk Analysis, 19 ( 5 ), 995 â 1002. https://doi.org/10.1023/A:1007030913871
dc.identifier.citedreferenceSandler, T. ( 2003 ). Terrorism & Game Theory. Simulation & Gaming, 34 ( 3 ), 319 â 337. https://doi.org/10.1177/1046878103255492
dc.identifier.citedreferenceSandler, T., & Enders, W. ( 2004 ). An economic perspective of transnational terrorism. European Journal of Political Economy, 20 ( 2 ), 301 â 316.
dc.identifier.citedreferenceShirali, G. A., Mohammadfam, I., & Ebrahimipour, V. ( 2013 ). A new method for quantitative assessment of resilience engineering by PCA and NT approach: A case study in a process industry. Reliability Engineering and System Safety, 119, 88 â 94. https://doi.org/10.1016/j.ress.2013.05.003
dc.identifier.citedreferenceShortridge, J., Aven, T., & Guikema, S. ( 2017 ). Risk assessment under deep uncertainty: A methodological comparison. Reliability Engineering and System Safety, 159, 12 â 23. https://doi.org/10.1016/j.ress.2016.10.017
dc.identifier.citedreferenceSociety of Risk Analysis (SRA). ( 2015 ). Society of Risk Analysis Glossary. Society for Risk Analysis. Committee on Foundations of Risk Analysis. McLean, VA.
dc.identifier.citedreferenceSociety of Risk Analysis (SRA). ( 2018 ). Society for risk analysis: Fundamental principles. McLean, VA.
dc.identifier.citedreferenceSpiegler, V. L. M., Naim, M. M., & Wikner, J. ( 2012 ). A control engineering approach to the assessment of supply chain resilience. International Journal of Production Research, 50 ( 21 ), 6162 â 6187. https://doi.org/10.1080/00207543.2012.710764
dc.identifier.citedreferenceUnited States of America Congress. ( 2002 ). U. S. Homeland Security Act of 2002, Pub. L. No. 2135, 2135.
dc.identifier.citedreferenceWhite, R., Burkhart, A., Boult, T., & Chow, E. ( 2016 ). Towards a comparable crossâ sector risk analysis: RAMCAP revisited. In Critical infrastructure protection X (221â 238).
dc.identifier.citedreferenceWhite, R., George, R., Boult, T., & Chow, C. E. ( 2016 ). Apples to apples: RAMCAP and emerging threats to lifeline infrastructure. Homeland Security Affairs, 15, 1 ( 1 ).
dc.identifier.citedreferenceWinkler, R. L. ( 1996 ). Uncertainty in probabilistic risk assessment. Reliability Engineering & System Safety, 54 ( 2â 3 ), 127 â 132. https://doi.org/10.1016/S0951-8320(96)00070-1
dc.identifier.citedreferenceYazdani, A., & Jeffrey, P. ( 2012 ). Applying network theory to quantify the redundancy and structural robustness of water distribution systems. Journal of Water Resources Planning and Management, 138 ( 2 ), 153 â 161. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000159.
dc.identifier.citedreferenceYazdani, Alireza, & Jeffrey, P. ( 2012 ). Water distribution system vulnerability analysis using weighted and directed network models. Water Resources Research, 48 ( 6 ), 1 â 10. https://doi.org/10.1029/2012WR011897
dc.identifier.citedreferenceZhu, S., & Fukushima, M. ( 2009 ). Worstâ case conditional valueâ atâ risk with application to robust portfolio management. Operations Research, 57 ( 5 ), 1155 â 1168. https://doi.org/10.1287/opre.
dc.identifier.citedreferenceAlbores, P., & Shaw, D. ( 2008 ). Government preparedness: Using simulation to prepare for a terrorist attack. Computers and Operations Research, 35 ( 6 ), 1924 â 1943. https://doi.org/10.1016/j.cor.2006.09.021
dc.identifier.citedreferenceAlderson, D. L., Brown, G. G., Carlyle, M. W., & Anthony Cox, L. ( 2013 ). Sometimes there is no â â mostâ vitalâ â arc: Assessing and improving the operational resilience of systems. Military Operations Research, 18 ( 1 ), 21 â 37. https://doi.org/10.5711/1082598318121
dc.identifier.citedreferenceAlderson, D. L., Brown, G. G., & Carlyle, W. M. ( 2015a ). Assessing and improving operational resilience of critical infrastructures and other systems. Bridging data and decisions. Catonsville, MD: Informs. https://doi.org/10.1287/educ.2014.0131
dc.identifier.citedreferenceAlenazi, M. J. F., & Sterbenz, J. P. G. ( 2015 ). Evaluation and comparison of several graph robustness metrics to improve network resilience. In Proceedings of 2015 7th International Workshop on Reliable Networks Design and Modeling, RNDM 2015, 7 â 13. https://doi.org/10.1109/RNDM.2015.7324302
dc.identifier.citedreferenceAmass, S. F. ( 2006 ). The science of homeland security, volume 1. Wast Lafayette, Indiana: Purdue University Press.
dc.identifier.citedreferenceAmerican Society of Mechanical Engineering and Innovative Technologies Institute (ASMEâ ITI LLC). ( 2005 ). RAMCAP TM executive summaryâ A 7 step approach. New York, NY: American Society of Mechanical Engineering.
dc.identifier.citedreferenceAmerican Water Works Association (AWWA), American Society of Mechanical Engineers, American National Standards Institute, and Innovative Technologies Institute LLC. ( 2010 ). J100â 10 RAMCAP TM Standard for risk and resilience management for water and wastewater systems. Denver, CO: American Water Works Association.
dc.identifier.citedreferenceApostolakis, G. E. ( 2004 ). How useful is quantitative risk assessment? Risk Analysis, 24 ( 3 ), 515 â 520.
dc.identifier.citedreferenceArrow, K. J. ( 1950 ). A difficulty in the concept of social welfare. Journal of Political Economy, 58 ( 4 ), 328 â 346.
dc.identifier.citedreferenceAskeland, T., Flage, R., & Aven, T. ( 2017 ). Moving beyond probabilitiesâ Strength of knowledge characterizations applied to security. Reliability Engineering and System Safety, 159, 196 â 205. https://doi.org/10.1016/j.ress.2016.10.035
dc.identifier.citedreferenceAven, T. ( 2017a ). On some foundational issues related to costâ benefit and risk. International Journal of Business Continuity and Risk Management, 7 ( 3 ), 182 â 191.
dc.identifier.citedreferenceAven, Terge, Baraldi, P., Roger, F., & Zio, E. ( 2013 ). Uncertainty in risk assessment: The representation and treatment of uncertainties by probabilistic and nonâ probabilistic methods. Hoboken, NJ: John Wiley & Sons. https://doi.org/10.1016/j.asoc.2014.05.024
dc.identifier.citedreferenceAven, T. ( 2003 ). Foundations of risk analysis. A knowledge and decisionâ oriented perspective. Hoboken, NJ: John Wiley & Sons, Ltd. https://doi.org/10.1198/jasa.2005.s16
dc.identifier.citedreferenceAven, T. ( 2012 ). The risk conceptâ historical and recent development trends. Reliability Engineering and System Safety, 99, 33 â 44. https://doi.org/10.1016/j.ress.2011.11.006
dc.identifier.citedreferenceAven, T. ( 2013 ). Practical implications of the new risk perspectives. Reliability Engineering and System Safety, 115, 136 â 145. https://doi.org/10.1016/j.ress.2013.02.020
dc.identifier.citedreferenceAven, T. ( 2016 ). On the use of conservatism in risk assessments. Reliability Engineering and System Safety, 146, 33 â 38. https://doi.org/10.1016/j.ress.2015.10.011
dc.identifier.citedreferenceAven, T. ( 2017a ). How some types of risk assessments can support resilience analysis and management. Reliability Engineering and System Safety, 167, 536 â 543. https://doi.org/10.1016/j.ress.2017.07.005
dc.identifier.citedreferenceAven, T. ( 2017b ). Improving risk characterisations in practical situations by highlighting knowledge aspects, with applications to risk matrices. Reliability Engineering and System Safety, 167, 42 â 48. https://doi.org/10.1016/j.ress.2017.05.006
dc.identifier.citedreferenceAven, T. ( 2018 ). The call for a shift from risk to resilience: what does it mean? Risk Analysis, 39, 1196 â 1203. https://doi.org/10.1111/risa.13247
dc.identifier.citedreferenceAven, T., & Guikema, S. ( 2015 ). On the concept and definition of terrorism risk. Risk Analysis, 35 ( 12 ), 2162 â 2171. https://doi.org/10.1111/risa.12518
dc.identifier.citedreferenceAven, T., & Reniers, G. ( 2013 ). How to define and interpret a probability in a risk and safety setting. Safety Science, 51 ( 1 ), 223 â 231. https://doi.org/10.1016/j.ssci.2012.06.005
dc.identifier.citedreferenceAven, T., & Renn, O. ( 2009 ). The role of quantitative risk assessments for characterizing risk and uncertainty and delineating appropriate risk management options, with special emphasis on terrorism risk. Risk Analysis, 29 ( 4 ), 587 â 600. https://doi.org/10.1111/j.1539-6924.2008.01175.x
dc.identifier.citedreferenceAyyub, B. M. ( 2014 ). Risk analysis in engineering and economics ( 2nd ed. ). London, UK: CRC Press.
dc.identifier.citedreferenceBrito, A. J., & de Almeida, A. T. ( 2009 ). Multiâ attribute risk assessment for risk ranking of natural gas pipelines. Reliability Engineering and System Safety, 94 ( 2 ), 187 â 198. https://doi.org/10.1016/j.ress.2008.02.014
dc.identifier.citedreferenceBrown, G. G., & Cox, L. A. T. ( 2011 ). How probabilistic risk assessment can mislead terrorism risk analysts. Risk Analysis, 31 ( 2 ), 196 â 204. https://doi.org/10.1111/j.1539-6924.2010.01492.x
dc.identifier.citedreferenceBurkhart, A. ( 2015 ). Lifeline infrastructure risk analysis application. Colorado Springs, CO: University of Colorado at Colorado Springs.
dc.identifier.citedreferenceCox, L. A. ( 2008a ). Some limitations of â risk = threat à vulnerability à consequenceâ for risk analysis of terrorist attacks. Risk Analysis, 28 ( 6 ), 1749 â 1761. https://doi.org/10.1111/j.1539-6924.2008.01142.x
dc.identifier.citedreferenceCox, L. A. ( 2008b ). What’s wrong with risk matrices? Risk Analysis, 28 ( 2 ), 497 â 512. https://doi.org/10.1111/j.1539-6924.2008.01030.x
dc.identifier.citedreferenceCox, L. A. ( 2009 ). Improving riskâ based decision making for terrorism applications. Risk Analysis, 29 ( 3 ), 336 â 341. https://doi.org/10.1111/j.1539-6924.2009.01206.x
dc.identifier.citedreferenceCutler, H., Dillard, M., McAllister, T. P., van de Lindt, J. W., Koliou, M., & Ellingwood, B. R. ( 2018 ). State of the research in community resilience: Progress and challenges. Sustainable and Resilient Infrastructure, 9689, 1 â 21. https://doi.org/10.1080/23789689.2017.1418547
dc.identifier.citedreferenceCutter, S. L. ( 2016 ). Resilience to what? Resilience for whom? Geographical Journal, 182 ( 2 ), 110 â 113. https://doi.org/10.1111/geoj.12174
dc.identifier.citedreferenceCutter, S. L., Barnes, L., Berry, M., Burton, C., Evans, E., Tate, E., & Webb, J. ( 2008 ). A placeâ based model for understanding community resilience to natural disasters. Global Environmental Change, 18 ( 4 ), 598 â 606. https://doi.org/10.1016/j.gloenvcha.2008.07.013
dc.identifier.citedreferenceDepartment of Homeland Security (DHS). ( 2009 ). National infrastructure protection plan. Washington, DC: Department of Homeland Security.
dc.identifier.citedreferenceDixon, L., Lempert, R. J., LaTournette, T., & Reville, R. T. ( 2007 ). The federal role in terrorism insurance: Evaluating alternatives in an uncertain world. Santa Monica, CA: Rand Corporation. https://doi.org/10.4135/9781412950558.n465
dc.identifier.citedreferenceDunn, S., Fu, G., Wilkinson, S., & Dawson, R. ( 2013 ). Network theory for infrastructure systems modelling. Engineering Sustainability, 166, 281 â 292. https://doi.org/10.1680/ensu.12.00039
dc.identifier.citedreferenceFaturechi, R., Levenberg, E., & Millerâ Hooks, E. ( 2014 ). Evaluating and optimizing resilience of airport pavement networks. Computers and Operations Research, 43, 335 â 348. https://doi.org/10.1016/j.cor.2013.10.009
dc.identifier.citedreferenceFlage, R., Aven, T., Zio, E., & Baraldi, P. ( 2014 ). Concerns, challenges, and directions of development for the issue of representing uncertainty in risk assessment. Risk Analysis, 34 ( 7 ), 1196 â 1207. https://doi.org/10.1111/risa.12247
dc.identifier.citedreferenceHaimes, Y. Y. ( 2009 ). On the definition of resilience in systems. Risk Analysis, 29 ( 4 ), 498 â 501. https://doi.org/10.1111/j.1539-6924.2009.01216.x
dc.identifier.citedreferenceHauge, K. H., Blanchard, A., Andersen, G., Boland, R., Einar, B., Howell, D., â ¦ Vikebø, F. ( 2014 ). Inadequate risk assessmentsâ A study on worstâ case scenarios related to petroleum exploitation in the Lofoten area. Marine Policy, 44, 82 â 89. https://doi.org/10.1016/j.marpol.2013.07.008
dc.identifier.citedreferenceHerrera, E. K., Flannery, A., & Krimmer, M. ( 2017 ). Risk and resilience analysis for highway assets. Transportation Research Record: Journal of the Transportation Research Board, 2604 ( 1 ), 1 â 8.
dc.identifier.citedreferenceHoffman, F. O., & Hammonds, J. S. ( 1994 ). Propagation of uncertainty in risk assessments: The need to distinguish between uncertainty due to lack of knowledge and uncertainty due to variability. Risk Analysis, 14 ( 5 ), 707 â 712. https://doi.org/10.1111/j.1539-6924.1994.tb00281.x
dc.identifier.citedreferenceHosseini, S., Barker, K., & Ramirezâ Marquez, J. E. ( 2016 ). A review of definitions and measures of system resilience. Reliability Engineering and System Safety, 145, 47 â 61. https://doi.org/10.1016/j.ress.2015.08.006
dc.identifier.citedreferenceHuysman, M., Madarasz, T., & Dassargues, A. ( 2006 ). Risk assessment of groundwater pollution using sensitivity analysis and worstâ case scenario analysis. Environmental Geology, 50 ( 2 ), 180 â 193.
dc.identifier.citedreferenceJaeger, C. D., Hightower, M. M., & Torres, T. ( 2010 ). Evolution of sandia’s risk assessment methodology for water and wastewater utilities (RAMâ W). In World environmental and water resources congress (Vol. 2010, pp. 3804â 3010).
dc.identifier.citedreferenceKabir, G., Balek, N. B. S., & Tesfamariam, S. ( 2018 ). Consequenceâ based framework for buried infrastructure systems: A Bayesian belief network model. Reliability Engineering and System Safety, 180, 290 â 301. https://doi.org/10.1016/j.ress.2018.07.037
dc.identifier.citedreferenceKaplan, S., & Garrick, B. J. ( 1981 ). On the quantitative definition of risk. Risk Analysis, 1 ( 1 ), 11 â 27.
dc.identifier.citedreferenceKarl, M., Wright, R. F., Berglen, T. F., & Denby, B. ( 2011 ). Worst case scenario study to assess the environmental impact of amine emissions from a CO 2 capture plant. International Journal of Greenhouse Gas Control, 5 ( 3 ), 439 â 447. https://doi.org/10.1016/j.ijggc.2010.11.001
dc.identifier.citedreferenceKerr, D. J., Singh, A., & Motala, I. ( 2015 ). Understanding risk and resilience to better manage water transmission systems. In Pipelines (Vol. 2015, pp. 1772â 1785).
dc.identifier.citedreferenceKoliou, M., van de Lindt, J. W., McAllister, T. P., Ellingwood, B. R., Dillard, M., & Cutler, H. ( 2017 ). State of the research in community resilience: Progress and challenges. Sustainable and resilient infrastructure, 1 â 21.
dc.identifier.citedreferenceKrimgold, F. ( 2012 ). Regional resilience and security for critical infrastructure. In Comparative analysis of technological and intelligent terrorism impacts on complex technical systems (pp. 61â 68).
dc.identifier.citedreferenceLarocca, S., & Guikema, S. ( 2011 ). A survey of network theoretic approaches for risk analysis of complex infrastructure systems. In Vulnerability, uncertainty, and risk: analysis, modeling, and management (pp. 155â 162).
dc.identifier.citedreferenceLarocca, S., Johansson, J., Hassel, H., & Guikema, S. ( 2015 ). Topological performance measures as surrogates for physical flow models for risk and vulnerability analysis for electric power systems. Risk Analysis, 35 ( 4 ), 608 â 623. https://doi.org/10.1111/risa.12281
dc.identifier.citedreferenceLewis, T. G., Darken, R. P., Mackin, T., & Dudenhoeffer, D. ( 2012 ). Modelâ based risk analysis for critical infrastructures. WIT Transactions on Stateâ ofâ theâ Art in Science and Engineering, 54, 3 â 19. https://doi.org/10.2495/978-1-84564-
dc.identifier.citedreferenceLundberg, R., & Willis, H. H. ( 2019 ). Examining the effectiveness of risk elicitations: Comparing a deliberative risk ranking to a nationally representative survey on homeland security risk. Journal of Risk Research, 1 â 15. https://doi.org/10.1080/13669877.2018.1501593
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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