Technical Papers
May 8, 2020

Strategic Assessment of Dam Overtopping Reliability Using a Stochastic Process Approach

Publication: Journal of Hydrologic Engineering
Volume 25, Issue 7

Abstract

Earth-fill dam overtopping could pose significant threats to public safety if the necessary reliability assessments are not taken into consideration in the design process. Dam overtopping is caused by several hydrometeorological random variables, including intensive rainfall, flood or flash flood, and wind coupled with waves. Because random variables are the main effective variables, a stochastic processes can be used to capture the leading failure factors. This study proposes a load-resistance-based approach to assess the reliability of Jamishan Dam, Iran, overtopping by considering several random variables simultaneously. Uncertainty sources such as (1) parameters of the hydrological model (e.g., loss, base flow, and unit hydrograph parameters), (2) hydraulic parameters (coefficient and length of spillway parameters), (3) initial reservoir water level, (4) wave height (e.g., wind setup and wave run-up parameters), and (5) rainfall parameters, are quantified using the Monte Carlo simulation (MCS) technique. Besides, the impact of stochastic sources and dam dimension design on overtopping reliability is considered through two indices, called reliability relative difference index (Rd) and reliability variation index (Rv). The uncertainty of hydrological parameters is quantified using the generalized likelihood uncertainty estimation (GLUE) method, which helps to extract their posterior probability distribution functions (PDFs). Reliability of dam overtopping has negligible sensitivity on the performance measures and behavioral threshold value of the GLUE approach. Results indicate that rainfall depth (Rd=2.04) is the most significant random variable affecting the overtopping reliability, with hydraulic random parameters (Rd=0.1) as the minimum level. Loss parameters (Rd=0.47) have the highest impact on overtopping reliability compared with other hydrological parameters. Overall, the significant of the stochastic sources such as meteorological parameters (e.g., rainfall depth, duration, and pattern), and hydrological parameters (e.g., loss parameters) on dam overtopping should be further studied to obtain reliable perspective for decision makers.

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Acknowledgments

The authors would like to offer their gratitude and appreciation to the editor and reviewers for their constructive comments and modifications.

References

Afshar, A., and M. A. Mariño. 1990. “Optimizing spillway capacity with uncertainty in flood estimator.” J. Water Resour. Plann. Manage. 116 (1): 71–84. https://doi.org/10.1061/(ASCE)0733-9496(1990)116:1(71).
Afshar, A., A. Rasekh, and M. H. Afshar. 2009. “Risk-based optimization of large flood-diversion systems using genetic algorithms.” Eng. Optim. 41 (3): 259–273. https://doi.org/10.1080/03052150802433213.
Anderson, M. L., Z.-Q. Chen, M. L. Kavvas, and A. Feldman. 2002. “Coupling HEC-HMS with atmospheric models for prediction of watershed runoff.” J. Hydrol. Eng. 7 (4): 312–318. https://doi.org/10.1061/(ASCE)1084-0699(2002)7:4(312).
Barth, N. A., G. Villarini, M. A. Nayak, and K. White. 2017. “Mixed populations and annual flood frequency estimates in the western United States: The role of atmospheric rivers.” Water Resour. Res. 53 (1): 257–269. https://doi.org/10.1002/2016WR019064.
Chen, J., P. Zhong, M. Wang, F. Zhu, X. Wan, and Y. Zhang. 2018. “A risk-based model for real-time flood control operation of a cascade reservoir system under emergency conditions.” Water 10 (2): 167. https://doi.org/10.3390/w10020167.
Chen, Y., and P. Lin. 2019. “Bayesian network of risk assessment for a super-large dam exposed to multiple natural risk sources.” Stochastic Environ. Res. Risk Assess. 33 (2): 581–592. https://doi.org/10.1007/s00477-018-1631-0.
Cheng, S.-T., B. C. Yen, and W. H. Tang. 1982. Overtopping risk for an existing dam. Champaign, IL: Univ. of Illinois at Urbana-Champaign.
Chu, X., and A. Steinman. 2009. “Event and continuous hydrologic modeling with HEC-HMS.” J. Irrig. Drain. Eng. 135 (1): 119–124. https://doi.org/10.1061/(ASCE)0733-9437(2009)135:1(119).
El Alfy, M. 2016. “Assessing the impact of arid area urbanization on flash floods using GIS, remote sensing, and HEC-HMS rainfall–runoff modeling.” Hydrol. Res. 47 (6): 1142–1160. https://doi.org/10.2166/nh.2016.133.
Erdik, T., J. Duricic, and P. H. A. J. M. van Gelder. 2013. “The probabilistic assessment of overtopping reliability on Akyayik Dam.” KSCE J. Civ. Eng. 17 (7): 1810–1819. https://doi.org/10.1007/s12205-013-1355-0.
Fluixá-Sanmartín, J., L. Altarejos-García, A. Morales-Torres, and I. Escuder-Bueno. 2019. “Empirical tool for the assessment of annual overtopping probabilities of dams.” J. Water Resour. Plann. Manage. 145 (1): 1–12. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001017.
Gabriel-Martin, I., A. Sordo-Ward, L. Garrote, and L. G. Castillo. 2017. “Influence of initial reservoir level and gate failure in dam safety analysis. Stochastic approach.” J. Hydrol. 550 (Jul): 669–684. https://doi.org/10.1016/j.jhydrol.2017.05.032.
Goodarzi, E., L. T. Shui, M. Mirzaei, and M. Ziaei. 2011. “Evaluation dam overtopping risk based on univariate and bivariate flood frequency analysis.” Hydrol. Earth Syst. Sci. Discuss. 8 (6): 9757–9796. https://doi.org/10.5194/hessd-8-9757-2011.
Goodarzi, E., L. T. Shui, and M. Ziaei. 2013. “Dam overtopping risk using probabilistic concepts—Case study: The Meijaran Dam, Iran.” Ain Shams Eng. J. 4 (2): 185–197. https://doi.org/10.1016/j.asej.2012.09.001.
Gumindoga, W., D. T. Rwasoka, I. Nhapi, and T. Dube. 2017. “Ungauged runoff simulation in Upper Manyame Catchment, Zimbabwe: Application of the HEC-HMS model.” Phys. Chem. Earth Parts A/B/C 100 (Aug): 371–382. https://doi.org/10.1016/j.pce.2016.05.002.
Her, Y., and I. Chaubey. 2015. “Impact of the numbers of observations and calibration parameters on equifinality, model performance, and output and parameter uncertainty.” Hydrol. Processes 29 (19): 4220–4237. https://doi.org/10.1002/hyp.10487.
Hsu, Y.-C., Y.-K. Tung, and J.-T. Kuo. 2011. “Evaluation of dam overtopping probability induced by flood and wind.” Stochastic Environ. Res. Risk Assess. 25 (1): 35–49. https://doi.org/10.1007/s00477-010-0435-7.
Huang, K., L. Ye, L. Chen, Q. Wang, L. Dai, J. Zhou, and V. P. Singh. 2018. “Risk analysis of flood control reservoir operation considering multiple uncertainties.” J. Hydrol. 565 (Aug): 672–684. https://doi.org/10.1016/j.jhydrol.2018.08.040.
Huff, F. A. 1967. “Time distribution of rainfall in heavy storms.” Water Resour. Res. 3 (4): 1007–1019. https://doi.org/10.1029/WR003i004p01007.
Kjeldsen, T. R., H. Ahn, I. Prosdocimi, and J.-H. Heo. 2018. “Mixture Gumbel models for extreme series including infrequent phenomena.” Hydrol. Sci. J. 63 (13–14): 1927–1940. https://doi.org/10.1080/02626667.2018.1546956.
Kuo, J.-T., Y.-C. Hsu, Y.-K. Tung, K.-C. Yeh, and J.-D. Wu. 2008. “Dam overtopping risk assessment considering inspection program.” Stochastic Environ. Res. Risk Assess. 22 (3): 303–313. https://doi.org/10.1007/s00477-007-0116-3.
Kuo, J.-T., B.-C. Yen, Y.-C. Hsu, and H.-F. Lin. 2007. “Risk analysis for dam overtopping—Feitsui Reservoir as a case study.” J. Hydraul. Eng. 133 (8): 955–963. https://doi.org/10.1061/(ASCE)0733-9429(2007)133:8(955).
Kwon, H.-H., and Y.-I. Moon. 2006. “Improvement of overtopping risk evaluations using probabilistic concepts for existing dams.” Stochastic Environ. Res. Risk Assess. 20 (4): 223. https://doi.org/10.1007/s00477-005-0017-2.
Lee, B., and G. J. You. 2013. “An assessment of long-term overtopping risk and optimal termination time of dam under climate change.” J. Environ. Manage. 121: 57–71. https://doi.org/10.1016/j.jenvman.2013.02.025.
Lehbab-Boukezzi, Z., L. Boukezzi, and M. Errih. 2016. “Uncertainty analysis of HEC-HMS model using the GLUE method for flash flood forecasting of Mekerra watershed, Algeria.” Arabian J. Geosci. 9 (20): 751. https://doi.org/10.1007/s12517-016-2771-5.
Lian, Y., and B. C. Yen. 2003. “Comparison of risk calculation methods for a culvert.” J. Hydraul. Eng. 129 (2): 140–152. https://doi.org/10.1061/(ASCE)0733-9429(2003)129:2(140).
Liu, Z., X. Xu, J. Cheng, T. Wen, and J. Niu. 2018. “Hydrological risk analysis of dam overtopping using bivariate statistical approach: A case study from Geheyan Reservoir, China.” Stochastic Environ. Res. Risk Assess. 32 (9): 2515–2525. https://doi.org/10.1007/s00477-018-1550-0.
Mays, L. W. 1999. Hydraulic design handbook. New York: McGraw-Hill.
Paik, K. 2008. “Analytical derivation of reservoir routing and hydrological risk evaluation of detention basins.” J. Hydrol. 352 (1–2): 191–201. https://doi.org/10.1016/j.jhydrol.2008.01.015.
Requena, A. I., L. Mediero Orduña, and L. Garrote de Marcos. 2013. “A bivariate return period based on copulas for hydrologic dam design: Accounting for reservoir routing in risk estimation.” Hydrol. Earth Syst. Sci. 17 (8): 3023–3038. https://doi.org/10.5194/hess-17-3023-2013.
Rossi, F., M. Fiorentino, and P. Versace. 1984. “Two-component extreme value distribution for flood frequency analysis.” Water Resour. Res. 20 (7): 847–856. https://doi.org/10.1029/WR020i007p00847.
Sharafati, A., and H. M. Azamathulla. 2018. “Assessment of dam overtopping reliability using SUFI based overtopping threshold curve.” Water Resour. Manage. 32 (7): 2369–2383. https://doi.org/10.1007/s11269-018-1934-4.
Sharafati, A., R. Yasa, and H. M. Azamathulla. 2018. “Assessment of stochastic approaches in prediction of wave-induced pipeline scour depth.” J. Pipeline Syst. Eng. Pract. 9 (4): 4018024. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000347.
Sharafati, A., and B. Zahabiyoun. 2013. “Stochastic generation of storm pattern.” Life Sci. J. 10 (1): 1575–1583.
Sharafati, A., and B. Zahabiyoun. 2014. “Rainfall threshold curves extraction by considering rainfall-runoff model uncertainty.” Arabian J. Sci. Eng. 39 (10): 6835–6849. https://doi.org/10.1007/s13369-014-1246-9.
Sun, Y., H. Chang, Z. Miao, and D. Zhong. 2012. “Solution method of overtopping risk model for earth dams.” Saf. Sci. 50 (9): 1906–1912. https://doi.org/10.1016/j.ssci.2012.05.006.
Teng, F., W. Huang, and I. Ginis. 2018. “Hydrological modeling of storm runoff and snowmelt in Taunton River Basin by applications of HEC-HMS and PRMS models.” Nat. Hazards 91 (1): 179–199. https://doi.org/10.1007/s11069-017-3121-y.
Thompson, K. D., J. R. Stedinger, and D. C. Heath. 1997. “Evaluation and presentation of dam failure and flood risks.” J. Water Resour. Plann. Manage. 123 (4): 216–227. https://doi.org/10.1061/(ASCE)0733-9496(1997)123:4(216).
Tung, Y.-K., B. C. Yen, and C. S. Melching. 2006. Hydrosystems engineering reliability assessment and risk analysis. New York: McGraw-Hill.
US Bureau of Reclamation. 1987. Design of small dams. Denver: US Bureau of Reclamation.
Wang, F., and Q.-L. Zhang. 2016. “Systemic estimation of dam overtopping probability: Bayesian networks approach.” J. Infrastruct. Syst. 23 (2): 4016037. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000328.
Wang, X., J. R. Frankenberger, and E. J. Kladivko. 2006. “Uncertainties in DRAINMOD predictions of subsurface drain flow for an Indiana silt loam using the GLUE methodology.” Hydrol. Process. Int. J. 20 (14): 3069–3084. https://doi.org/10.1002/hyp.6080.
Yenigun, K., and C. Erkek. 2007. “Reliability in dams and the effects of spillway dimensions on risk levels.” Water Resour. Manage. 21 (4): 747–760. https://doi.org/10.1007/s11269-006-9063-x.
Yu, P.-S., T.-C. Yang, and S.-J. Chen. 2001. “Comparison of uncertainty analysis methods for a distributed rainfall–runoff model.” J. Hydrol. 244 (1–2): 43–59. https://doi.org/10.1016/S0022-1694(01)00328-6.
Zhang, S., and Y. Tan. 2014. “Risk assessment of earth dam overtopping and its application research.” Nat. Hazards 74 (2): 717–736. https://doi.org/10.1007/s11069-014-1207-3.
Zhao, B., Y.-K. Tung, K.-C. Yeh, and J.-C. Yang. 1997. “Reliability analysis of hydraulic structures considering unit hydrograph uncertainty.” Stochastic Hydrol. Hydraul. 11 (1): 33. https://doi.org/10.1007/BF02428424.

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Journal of Hydrologic Engineering
Volume 25Issue 7July 2020

History

Received: Mar 3, 2019
Accepted: Feb 4, 2020
Published online: May 8, 2020
Published in print: Jul 1, 2020
Discussion open until: Oct 8, 2020

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Assistant Professor, Dept. of Civil Engineering, Science and Research Branch, Islamic Azad Univ., Tehran, Iran (corresponding author). ORCID: https://orcid.org/0000-0003-0448-2871. Email: [email protected]; [email protected]
Zaher Mundher Yaseen [email protected]
Lecture, Sustainable Developments in Civil Engineering Research Group, Faculty of Civil Engineering, Ton Duc Thang Univ., Ho Chi Minh City, Vietnam. Email: [email protected]
Ph.D. Student, Integrated Coastal Sciences Program, East Carolina Univ., Greenville, NC 27858-4353. ORCID: https://orcid.org/0000-0003-0589-4552

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