Open Discussion Conclusions from Panel #4, Flood-Induced Dam and Levee Failure

1) The Probabilistic flood hazard analysis (specifically) and probabilistic risk assessment (PRA)

(generally) for dam and levee failure needs a structured evaluation process like the SSHAC 

process. Because the specific analysis often relies on expert assessments which are biased by 

human errors, the PRA analysis should evaluate the comprehensive uncertainties of data and 

modeling.

2) Flood frequency analysis in Bulletin 17B is empirical, being based primarily on observed flood 

data. But, PFHA involves imagining processes by requiring more comprehensive evaluations (as 

described by SSHAC).

3) There are not adequate data on large dam failures. Reliable data on dams, dam components, 

and operations are generally not available to meet specific needs of risk assessments for 

individual dams or even components of dam systems.

a. History shows that large dams seldom fail by flooding alone, but by a combination of 

factors as a system.

b. We need more reliable data on dam/components failures and operations.

c. Better data would enable us to reduce subjectivity significantly in risk analysis and 

decision making.

4) The estimation of dam and levee failures (fragility) is difficult and often subject to bias and 

limited by engineering tools.

5) The use of risk analyses (conducting comprehensive PFHA) is impeded by the lack of engineers 

who are trained and are comfortable with the methods that address probability, systems 

engineering for dams and levees, and risk in high hazard situations.

6) Probability and risk analysis for dams has come a long way in the past 25 years. Statistics on 

dam failure in 1975 (general conclusion that Pfailure=1x10-4

) was not a welcome message to dam 

owners.

7) It is generally believed that the chances of dam failure are low (still around 1x10-4

, not much 

change in 40 yrs), but failures continue to occur. Failures are rarely due to one factor, but often 

the “uncommon combination of not uncommon events”. This needs to be addressed through 

risk analysis of dam systems.

8) In some cases, event trees/fault trees cannot handle complexity of events (e.g. examples from 

Canada and Taum Sauk dam failure events).

9) A lot of problems with data about dam failure events, structure, system and component 

performance:
a. In the past, engineers did not want to talk about failure

b. Failure reports tend to only be produce under regulatory requirement

c. We do not keep track of near-failure incidents which are useful to support risk analyses 

(In case of failures, we need to look at how we can make the data useful and operational 

in the future.)

d. However, some data are available:

i. RMC (Risk Management Center of USACE) may have some information on 

reliability of mechanical/electrical components of dams.

ii. CEATI Dam Safety Interest Group may be another source of similar information.

iii. National Performance of Dams Program at Stanford has data on dam incidents.

10) Question was asked if order of magnitude uncertainty in predicting time of failure meant we 

have a range of 3 min to 30 min or 3 hr to 30 hr? Reply: It is order of magnitude uncertainty 

around predicted time of failure from a given regression equation, so it depends on the size of 

the dam. Point was also made that one big source of uncertainty about failure times is lack of 

accuracy/consistency in eyewitness reports of dam failure times.

11) Recent experience in lab dam breach tests has shown that time of failure (i.e., rate of erosion)

for embankment dams is extremely sensitive to erodibility of soils, which is in turn sensitive to 

compaction processes and conditions during original construction. Tests are now available that 

can evaluate soil erodibility (in lab or in the field). 

12) Historically, dams have done well. The experience worldwide looks good.

13) Tools have recently become available and continue to be developed that will enable us in the 

future to add probability and uncertainty to more nodes in the event trees describing sequences 

of events that lead to dam failure (e.g., process-based erosion and breach models).

14) Analyses should move toward Bayesian methods. Data are not perfect, but sufficiently good to 

have confidence in the analyses performed.

15) In other fields, society tolerates risks that are not considered acceptable in the dam’s arena

potentially develop improved guidance for tolerable risk limits.

16) The state of PRA in dam and levee safety is relatively new compared to other fields, such as 

nuclear power plants, where a 2nd or 3rd generation of PRA’s is already underway.

17) Dam failure analysis has been focused heavily on geotechnical engineering practices, but should 

also incorporate structural, hydrologic, and hydraulic engineering aspects.
18) A major problem occurs when applying prescriptive methodologies in a “design-safe” manner. 

This prohibits thinking “outside the box” and hinders advancement in the field. On the other 

hand, it is costly, risky and challenging to analyze and tackle challenges in a manner outside the 

normal convention.