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.
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Millions of dollars are spent on dam upgrade works which are often undertaken to meet the flood security requirements. Prioritisation of the dam upgrade work is based on portfolio risk assessments in which dambreak modelling is an integral part. Concurrent design flow hydrographs of tributaries downstream of dam are required for the assessment of the incremental effect of a dam break scenario. The Annual Exceedance Probability (AEP) neutral concurrent tributary flows can be estimated using a bivariate-normal distribution approach.
This paper examines the underlying assumptions made in the application of the bivariate normal distribution approach using observed and design rainfall data for Avon Dam and its downstream tributary catchments. Synthetically generated data was used to illustrate the impact of the log-normal distribution assumption on the AEP neutral concurrent tributary rainfalls. This paper suggests a modification to the bivariate-normal distribution approach to estimate more unbiased AEP neutral concurrent design rainfalls. The use of historical gridded rainfall in the estimation of inter-catchment rainfall correlation is also demonstrated.
Global climate change will amplify existing risks, as well as create new risks for natural and human systems. Recent climate changes have already had widespread impacts on human and natural systems. Dams provide a range of economic, environmental and social benefits including irrigation, flood control, water supply, hydroelectric power, recreation and wildlife habitat and play an important role in human settlement. Adapting into the effects of climate change is vitally important for future management of dams. This paper uses the recent drought and floods in Victoria to illustrate the importance of considering the effects of climate change in design, operations, maintenance and emergency management of dams.
The U.S. Army Corps of Engineers (USACE) Risk Management Center (RMC) developed the Reservoir Frequency Analysis software (RMC-RFA) to facilitate, enhance, and expedite flood hazard assessments within the USACE Dam Safety Program. RMC-RFA is a stochastic flood modeling software that employs advanced statistical and computing techniques, allowing a user to perform a screening-level stage-frequency analysis on a desktop PC with runtimes on the order of seconds to a few minutes. RMC-RFA utilizes an inflow volume-based stochastic simulation framework that treats the seasonal occurrence of the flood event, the antecedent reservoir stage, inflow volume, and the inflow flood hydrograph shape as uncertain variables rather than fixed values. In order to construct uncertainty bounds for reservoir stage-frequency estimates, RMC-RFA employs a two looped, nested Monte Carlo methodology. The natural variability of the reservoir stage is simulated in the inner loop defined as a realization, which comprises many thousands of events, while the knowledge uncertainty in the inflow volume-frequency distribution is simulated in the outer loop, which comprises many realizations.
Stage-frequency curves derived with RMC-RFA are compared to those derived with more complex, precipitation-based simulation frameworks, such as the Monte Carlo Reservoir Analysis Model (MCRAM), the Stochastic Event Flood Model (SEFM), and the Watershed Analysis Tool (HEC-WAT). The inflow volume-based framework employed by RMC-RFA produces stage-frequency curves that strongly agree with the more complex, precipitation-based methods. Furthermore, the results from the alternative methods fall within the RMC-RFA uncertainty bounds, demonstrating its robustness. In this sense, the RMC-RFA simulation framework lends itself to a value of information approach to risk management, where knowledge uncertainty can be efficiently quantified at a screening-level assessment, and then the value of performing more complex and sophisticated studies to reduce uncertainty can be considered.
The assessment of the geological foundations of arch dams is required as part of the asset owner’s safety obligations (ANCOLD 2003). The task is often made difficult due to steep topography where arch dams are commonly constructed. Between 2013 and 2017, GHD was engaged by South Australia Water (SA Water) to examine the geological and geotechnical conditions of the Sturt River Flood Attenuation Dam (South Australia) abutment foundations. The dam was constructed between 1964 and 1966 within the Proterozoic “Sturt Tillite”. The foundations of the dam are characterised by a folded and fractured rock mass which creates complex spatial relationships between discontinuities and outcrop expression, difficult to assess in two-dimensional space. In collaboration with Monash University’s School of Earth, Atmosphere and Environment, a high resolution ortho-photogrammetric survey of the downstream dam abutments was undertaken using an Unmanned Aerial Vehicle (UAV) in areas where traditional mapping could only be obtained by rope access methods. Monash also undertook digital geological mapping of inferred discontinuities based on the UAV imagery. The data was then used to construct a three-dimensional (3D) model of the shape and position of high-persistence discontinuities, potentially critical to abutment stability. In addition to digital data, a low cost, high value field investigation to “ground-truth” the digital data and reviewed existing geological information (including rope access scanline data, foundation mapping and rotary cored boreholes) to develop a holistic understanding of the persistent discontinuities in their geological context.
The rehabilitation of wet tailings storages is likely to become of increasing importance. In a setting of increasing environmental regulation and oversight, the environmental issues inherent in wet tailings storages will increase in visibility. This will translate through to increased regulatory attention, rehabilitation standards and costs. This scenario will necessitate increased engineering ingenuity and approaches to develop cost effective and robust/ defensible outcomes.
This case study of a coal fired power station ash dam rehabilitation compares a conventional (baseline) rehabilitation strategy and the development of a higher land use, with potentially beneficial outcomes for the owner, the community and the environment.
The baseline rehabilitation was a conventional fit-for-purpose rehabilitation approach consistent with the proposed final land use comprising the creation of a stable, open greenspace environment. The higher land use was an aspirational target style rehabilitation, with the assessed highest and best use for the site that was determined to be an industrial land development. While there will be limitations due to the low strength tailings foundation, this higher land use is considered an appropriate stretch target and is a feasible outcome for this site.