Two-dimensional hydraulic modelling technology has advanced significantly in recent years, providing powerful and flexible tools that are now routinely used for a wide variety of flood risk assessments. Assessing the downstream impacts of catastrophic dam failure represents an extreme test for the accuracy and stability of hydraulic models. Catastrophic dam failure can present an extreme risk to downstream infrastructure and public safety. Hence, it is important to have confidence in the estimated magnitude of potential impacts to design suitable, costeffective mitigation measures. The highly visual output of two-dimensional models adds credibility to their results. However, validation data for extreme hydraulic conditions is rarely available, resulting in uncertainty in the accuracy of model predictions and in the risks associated with dam failure. By validating numerical model results against analytical solutions for cases of simple geometry and also against realworld data, an improved level of confidence can be obtained in the accuracy of the model representation of these extreme hydraulic conditions. In this paper, we assessed the capability of the TUFLOW hydraulic modelling software package to accurately simulate an idealised dam break scenario by comparing the model results to analytical solutions. We also compared the model results for coastal inundation by a tsunami to real-world data from the 2004 Banda Ache (Indonesia) tsunami. The results showed that the HPC solver version of TUFLOW correctly captures the dam break flood fronts and the flood wave propagation and TUFLOW HPC is well suited for dam break flood modelling.
Oroville Dam is located on the Feather River in northern California (USA). At 234.7 m (770-ft) tall, this earth embankment is the tallest dam in the United States. With its 4.3 billion m3 (3.5 million acre-feet) of storage, Lake Oroville is the second largest reservoir in California, supplying water to cities as far south as Los Angeles. The Oroville Dam, reservoir (Lake Oroville), and hydropower plant facility is the flagship of the State Water Project (SWP), which is owned and operated by the State of California, Department of Water Resources (DWR).
The notion of probability and its various interpretations brings numerous opportunities for errors and misunderstandings. This is particularly true of contemporary risk analysis for dams that mostly consider geotechnical, hydraulic, and structural capacities subjected to extreme loads considered as independent evets. In these analyses subjective “degree of belief” probability has a major role, both in the modelling of the risk in the system by means of event trees based on inductive reasoning and in the assignment of probabilities to events in the event tree. There are numerous situations where physically possible conditions are eliminated from consideration in a risk analysis on the basis of probabilities that are judged to be too low to be of relevance. This is despite the fact that the assignment of a probability to a condition means that the occurrence of the event or condition is inevitable sometime, with the added complication that the time of occurrence is unknown and unknowable. Although there is no relationship between a remote probability and the possibility (or credibility) of the occurrence of the event in the event tree, it is quite common for physically feasible conditions to be either eliminated or their importance discounted on the basis of low probability in a risk assessment of a dam. Twenty five years ago, this elimination process might have been referred to as “judicious pruning of the event tree”. In more modern parlance, the elimination process is based on consideration of whether or not the condition or sequence of events is clearly so remote a possibility as to be non-credible or not reasonable to postulate. In contrast to the consideration of extreme loads vs. structural or geotechnical capacities, experience has shown that many dam failures and perhaps the majority of dam incidents do not result from extreme geophysical loads, but rather from operational factors. These incidents and failures occur because an unusual combination of reasonably common events occurs, and that unusual combination of events has a bad outcome. For example, a moderately high reservoir inflow occurs, but nowhere near extreme; the sensor and SCADA system fail to provide early warning for some unanticipated reason; one or more spillway gates are unavailable due to maintenance, or an operator makes an error, or there is no operator on site and it takes a long time for one to arrive; and the pool was uncommonly high at the time. This chain of reasonable events, none by itself particularly dangerous, can in combination lead to an incident or even a failure. This leads to the unnerving conclusions that; our estimates of risk made in terms of best available practice using the best available estimates will be underestimates of the actual risk, and the extent to which we underestimate the risk is unknowable. This paper examines why these improbable events occur and what can be done to prevent them. Some implications with respect to the endeavour of risk evaluation are also considered.
There are a number of software packages that have been developed to conduct Probabilistic Seismic Hazard Assessments (PSHA’s). Each one has advantages and disadvantages. Two such programs are compared; the licenced subscription-based EZ-FRISK software package developed by Fugro USA Land, Inc. and the open-sourced OpenQuake-engine (OQ) software package by the Global Earthquake Model (GEM) Foundation. Both of these packages use the classical PSHA methodology as described by Cornell (1968) and modified by McGuire (1976). Each of these packages offers different advantages; OQ is freely distributed, code based and provides easy access to a number of tools. EZ-FRISK doesn’t rely on command-line tools and instead provides an easy user interface with quick access to plots to check results. EZ-FRISK is computationally faster than the OQ program.
A simple rectangular source model with four sites was used to investigate the degree of agreement between these two software packages. Results indicate that hazard estimates from the two packages agree to within 4% for the two closest sites. At long return periods for the two furthest sites, the difference is larger.
Earthquakes are a well-known threat to the safety of dams. While this threat is subdued for Australian Dams, the potential for earthquake induced failure of a dam requires risk minimisation in the downstream community through monitoring and emergency response procedures. This paper details WaterNSW’s approach to their development of a Seismic Monitoring Strategy which was to align the business and ensure an appropriate post-seismic response.
The strategy also identifies that a proactive approach to seismic instrumentation can be taken to reduce business risk by aiding decision making should a dam be in a damaged post-seismic state.
The interim outcome of implementing the Seismic Monitoring Strategy resulted in a fast emergency
response time and less overreaction/distraction of dam safety resources in insignificant seismic events. There is opportunity for other Australian dam owners to implement similar systems to = WaterNSW and achieve similar results.
The volume-of-fluid (VOF) technique was employed to develop a Computational Fluid Dynamics (CFD) model for comparison to physical measurements available from the Eildon Dam model in Australia for validations purposes. The water surface in the downstream chute of the spillway was observed to be mostly comprised of fully developed aerated flow. The free surface is physically measured as located between the mixing and upper zones, thus investigator judgement is critical to achieve reliable measurements. The mixing zone is also characterized by surface waves to complicate matters even further. A challenge arose to develop a post processing methodology that replicates as closely as possible the measuring technique used by the physical modeller for direct comparison of results, using a novel method which utilises Poisson probability of exceedance applied to the free surface.