Skip to main content
SpringerLink
Log in

Analysis of human risks due to dam-break floods—part 1: a new model based on Bayesian networks

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

Dam breaks have catastrophic consequences for human lives. This paper presents a new human risk analysis model (HURAM) using Bayesian networks for estimating human risks due to dam-break floods. A Bayesian network is constructed according to a logic structure of loss-of-life mechanisms. The nodes (parameters) and the arcs (inter-relationships) of the network are quantified with historical data, existing models and physical analyses. A dataset of 343 dam-failure cases with records of fatality is compiled for this purpose. Comparison between two existing models and the new model is made to test the new model. Finally, sensitivity analysis is conducted to identify the important parameters that lead to loss of life. The new model is able to take into account a large number of important parameters and their inter-relationships in a systematic structure; include the uncertainties of these parameters and their inter-relationships; incorporate information derived from physical analysis, empirical models and historical data; and update the predictions when information in specific cases is available. The application of this model to the study of human risks in a specific dam-break case is presented in a companion paper.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Aboelata MA, Bowles DS (2005) LIFESim: a model for estimating dam failure life loss. Report to Institute for Water Resources, US Army Corps of Engineers and Australian National Committee on Large Dams, Institute for Dam Safety Risk Management, Utah State University, Logan, Utah, USA

  • Abt SR, Wittler RJ, Taylor A, Love DJ (1989) Human stability in a high flood hazard zone. Water Resour Bull 25(4):881–890

    Article  Google Scholar 

  • Au SK (2005) Reliability-based design sensitivity by efficient simulation. Comput Struct 83(14):1048–1061

    Article  Google Scholar 

  • Bern C, Sniezek J, Mathbor GM, Siddiqi MS, Ronsmans C, Chowdhury AMR, Choudhury AE, Islam K, Bennish M, Noji E, Glass RI (1993) Risk factors for mortality in the Bangladesh cyclone of 1991. Bull Would Health Organ 71(1):73–78

    Google Scholar 

  • Boyd E, Levitan M, van Heerden I (2005) Further specification of the dose-Response relationship for flood fatality estimation. Paper presented at the US-Bangladesh workshop on innovation in windstorm/storm surge mitigation construction. National Science Foundation and Ministry of Disaster & Relief, Government of Bangladesh, Dhaka, Bangladesh, 19–21 December, 2005

  • Brown CA, Graham WJ (1988) Assessing the threat to life from dam failure. Water Resour Bull 24(6):1303–1309

    Article  Google Scholar 

  • Clausen L, Clark PB (1990) The development of criteria for predicting dam-break food damages using modeling of historical dam failures. In: White WR (ed) International conference on river flood hydraulics. Wiley, England, pp 369–380 (17–20 September)

  • DeKay ML, McClelland GH (1993) Predicting LOL in cases of dam failure and flash flood. Risk Anal 13(2):193–205

    Article  Google Scholar 

  • Faber MH, Kroon IB, Kragh E, Bayly D, Decosemaeker P (2002) Risk assessment of decommissioning options using Bayesian networks. J Offshore Mech Arct Eng 124(4):231–238

    Article  Google Scholar 

  • Frieser B (2004). Probabilistic evacuation decision model for river floods in the Netherlands. Final report, Delft University of Technology, Delft, Netherlands, 138 p

  • Friis-Hansen A (2000) Bayesian networks as a decision support tool in marine applications. Ph.D. thesis, Technical University of Denmark, Lyngby, Denmark

  • Graham WJ (1999) A procedure for estimating loss of life caused by dam failure. U.S. Bureau of Reclamation, Dam Safety Office, Denver, USA, Report No. DSO-99-06, 44 p

  • Grêt-Regamey A, Straub D (2006) Spatially explicit avalanche risk assessment linking Bayesian networks to a GIS. Nat Haz Earth Syst Sci 6(6):911–926

    Article  Google Scholar 

  • Harrison S (1864) A complete history of the great flood at Sheffield on March 11 & 12, 1864. Sheffield Times, 13, Great Sutton Street, England. Available http://www2.shu.ac.uk/sfca/extra/A%20Complete%20History%20of%20the%20Great%20Flood%20at%20Sheffield.pdf

  • Hugin Expert A/S (2004) Hugin lite. http://www.hugin.com/Products_Services/Products/Demo/Lite/. Accessed 20 Jan 2009

  • IPET (Interagency Performance Evaluation Task Force) (2006) Performance evaluation of the New Orleans and Southeast Louisiana hurricane protection system—volume VII: the consequences, Final draft report, US Army Corps of Engineers, Washington

  • Jensen FV (2001) Bayesian networks and decision graphs. Springer, New York

    Google Scholar 

  • Johnstone WM, Sakamoto D, Assaf H, Bourban S (2005) Architecture, modelling framework and validation of BC hydro’s virtual reality life safety model. In: Vrijling JK et al (eds) Proceedings of the international symposium on stochastic hydraulics, May 23, 24 2005, Nijmegen, the Netherlands

  • Jonkman SN (2007) Loss of life estimation in flood risk assessment: theory and applications. Ph D Thesis, Delft University of Technology, Delft, Netherlands

  • Jonkman SN, Penning-Rowsell E (2008) Human instability in flood flows. J Am Water Resour As 44(4):1–11

    Google Scholar 

  • Jonkman SN, Vrijling JK, Vrouwenvelder ACWM (2008) Methods for the estimation of loss of life due to floods: a literature review and proposal for a new method. Nat Hazards 46(3):353–389

    Article  Google Scholar 

  • Jonkman SN, Maaskant B, Boyd E, Levitan ML (2009) Loss of life caused by the flooding of New Orleans after hurricane Katrina: Analysis of the relationship between flood characteristics and mortality. Risk Anal 29(5):676–689

    Article  Google Scholar 

  • Lee R, Hu PS, Neal D, Ogles MR, Sorensen JH, Trumble DA (1986) Predicting loss of life from floods. Oak Ridge National Laboratory Draft Report. Prepared for the Institute for Water Resources, U.S. Army Corps of Engineers, Washington, 131 p

  • Li L, Wang ZR, Sheng JB, Wang ZS, Peng XH, Zhang SC (2006) Risk assessment and risk management of dams. China Water Power Press, Beijing (in Chinese)

    Google Scholar 

  • Li DQ, Yan LL, Shao DG (2007) Reliability evaluation of embankment dams using Bayesian network. Eng J Wuhan Univ 40(6):24–29 (in Chinese)

    Google Scholar 

  • Lind N, Hartford D, Assaf H (2004) Hydrodynamic models of human instability in a flood. J Am Water Resour As 40(1):89–96

    Article  Google Scholar 

  • Lindell MK, Perry RW (1992) Behavioral foundations of community emergency planning. Hemisphere Press, Washington, DC

    Google Scholar 

  • Lindell MK, Prater CS, Perry RW, Wu JY (2002) EMBLEM: an empirically based large scale evacuation time estimate model. Texas A&M University Hazard Reduction & Recovery Center, College Station

    Google Scholar 

  • McClelland DM, Bowles DS (1999) Life-loss estimation: what can we learn from case histories. In: Proceedings of the Australian committee on large dams (ANCOLD) annual meeting, November 1999, Jindabyne, New South Wales, Australia

  • McClelland DM, Bowles DS (2002) Estimating life loss for dam safety risk assessment—a review and new approach, IWR report 02-R-3. Institute for Dam Safety Risk Management Utah State University, Logan

    Google Scholar 

  • MWR (1981) National inventory of reservoir dam failures. Ministry of Water Resources of the People’s Republic of China (MWR), Beijing (in Chinese)

  • Peng M, Zhang LM (2012a) Breaching parameters of landslide dams. Landslides 9(1):13–31

    Article  Google Scholar 

  • Peng M, Zhang LM (2012b) Analysis of human risk due to dam break floods—part 2: application to Tangjiashan Landslide Dam failure. Nat Haz (companion paper, tentatively accepted)

  • Pistrika AK, Jonkman SN (2010) Damage to residential buildings due to flooding of New Orleans after hurricane Katrina. Nat Hazards 54(2):413–434

    Article  Google Scholar 

  • Priest S, Wilson T, Tapsell S, Penning-Rowsell E, Viavattene C, Fernandez-Bilbao A (2007) Building a model to estimate Risk to Life for European flood events—final report. Integrated flood risk analysis and management methodologies. FLOODsite, http://www.floodsite.net/html/partner_area/search_results3b.asp?docID=265

  • Ramsbottom D, Floyd P, Penning-Rowsell E (2003) Flood risks to people—phase 1. R&D technical report FD2317TR, Department for Environment, Food & Rural Affairs—Flood Management Division, London

  • Rcdr.org.cn (2012) Website of flood control and drought relief in China. http://www.rcdr.org.cn/FX110Search.aspx?sid=213&tid=2&p=1&pid=208 (in Chinese)

  • Reda ALL, Beck MB (1997) Ranking strategies for stormwater management under uncertainty: sensitivity analysis. Water Sci Technol 36(5):357–371

    Article  Google Scholar 

  • RESCDAM (2000) The use of physical models in dam-break flood analysis: rescue actions based on dam-break flood analysis. Final report of Helsinki University of Technology, Helsinki, Finland, 57 p

  • Rogers GO, Sorensen JH (1989) Warning and response in two hazardous materials transportation accidents in the US. J Hazard Mater 22(1):57–74

    Article  Google Scholar 

  • Ru NH, Niu YG (2001) Embankment dam—incidents and safety of large dams. Water Power Press, Beijing (in Chinese)

  • Sharpe EM (1995) Capitalism and calamity; the Mill River Flood of 1874. Dissertation in University of Delaware, Newark

    Google Scholar 

  • Smith M (2006) Dam risk analysis using Bayesian networks. In: Nadim F, Pöttler R, Einstein H, Klapperich H, Kramer S (eds) Proceedings of the 2006 ECI conference on geohazards. ECI symposium series no. 7, Engineering conferences international (ECI), New York. http://services.bepress.com/eci/geohazards/10

  • Straub D, Der Kiureghian A (2010a) Combining Bayesian networks with structural reliability methods: methodology. J Eng Mech 136(10):1248–1258

    Article  Google Scholar 

  • Straub D, Der Kiureghian A (2010b) Combining Bayesian networks with structural reliability methods: application. J Eng Mech 136(10):1259–1270

    Article  Google Scholar 

  • Tsuchiya Y, Kawata Y (1981) Risk to life, warning systems, and protective construction against past storm surges in Osaka Bay. J Nat Disaster Sci 3(1):33–56

    Google Scholar 

  • Tung YK, Wang PY, Yang UC (1993) Water resource projects evaluation and ranking under economic uncertainties. Water Resour Manag 7(4):311–333

    Article  Google Scholar 

  • Wang Y, Cao ZJ, Au SK (2010) Efficient Monte Carlo simulation of parameter sensitivity in probabilistic slope stability analysis. Comput Geotech 37(7–8):1015–1022

    Article  Google Scholar 

  • Watson D, Serrer M, Crookshank N (2001) BC hydro life safety model (Alpha Version): a two-dimensional model for estimating dam breach flood survival probabilities. Technical report. Canadian Hydraulics Centre, Ottawa, Canada, p 46

  • Xu Y (2010) Analysis of dam failures and diagnosis of distresses for dam rehabilitation. Ph.D. thesis, the Hong Kong University of Science and Technology, Hong Kong

  • Xu Y, Zhang LM (2009) Breaching parameters of earth and rockfill dams. J Geotech Geoenviron Eng ASCE 135(12):1957–1970

    Article  Google Scholar 

  • Xu Y, Li M, Zhang LM, Zhang JM (2011a) The progress curve of outflow rate due to dam break. In: Proceedings of the 7th national youth conference on geotechnical engineering. Chinese Geotechnical Society, Beijing, pp 300–305 (in Chinese)

  • Xu Y, Zhang LM, Jia JS (2011b) Diagnosis of embankment dam distresses using Bayesian networks. Part II. Diagnosis of a specific distressed dam. Can Geotech J 48(11):1645–1657

    Article  Google Scholar 

  • Zhai G, Fukuzono T, Ikeda S (2006) An empirical model of fatalities and injuries due to floods in Japan. J Am Water Resour As 42(4):863–875

    Article  Google Scholar 

  • Zhang LM, Xu Y, Jia JS (2009) Analysis of earth dam failures—a database approach. Georisk 3(3):184–189

    Google Scholar 

  • Zhang LM, Xu Y, Jia JS, Zhao C (2011) Diagnosis of embankment dam distresses using Bayesian networks. Part I. Global-level characteristics based on a dam distress database. Can Geotech J 48(11):1630–1644

    Article  Google Scholar 

  • Zhou KF (2006) Study on the analysis method for loss of life due to dam breach. M.S. thesis, Nanjing Hydraulic Research Institute, Nanjing, China (in Chinese)

Download references

Acknowledgments

The authors acknowledge the support from the National Science Foundation of China (Grant No. 51129902), the Ministry of Science and Technology (2009BAK56B05) and the Hong Kong University of Science and Technology.

Author information

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Kowloon, Hong Kong

    M. Peng & L. M. Zhang

Authors
  1. M. Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. L. M. Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to L. M. Zhang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Peng, M., Zhang, L.M. Analysis of human risks due to dam-break floods—part 1: a new model based on Bayesian networks. Nat Hazards 64, 903–933 (2012). https://doi.org/10.1007/s11069-012-0275-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-012-0275-5

Keywords

Search

Navigation