The U.S. Army Corps of Engineers (USACE) is responsible for flood risk management across the United States. USACE has more than 710 dams and is responsible for more than 24,000 kilometres of levees. Since 2008, USACE projects have prevented more than AU$1.2 Trillion (in 2017 dollars) in damages from flooding. Although some of this came as a result of dozens of smaller floods, much of that protection came during three events within the last five years. From 2010 through 2017, the U.S. has had three major inland floods and two coastal events where federal flood protection exists: in 2010 on the Cumberland River, in 2011 on the Missouri, Ohio, White, and Mississippi Rivers, in 2015 on several rivers in Texas and Oklahoma, and in 2017 along the Gulf Coast of the U.S. and its territories in the Caribbean. For many of these locations, these events produced record rainfall and the flood of record. USACE operated many large facilities on these systems and those systems overall performed as expected. However, USACE also experienced some operational issues, did a substantial amount of flood fighting, had several incidents, and several failures. This paper will describe the flooding experienced in those events, the operations of the flood protection systems, the performance overall, and some of the lessons learned.
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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.
Lessons learned from recent major incidents and related enquiries in Victoria in concert with the adoption
of an all-emergencies all-communities philosophy have informed both the scope and reach of the current
emergency management and dam safety regulatory environment. Victorian dam owners now have a statutory
obligation to implement an all-emergencies all-communities approach to risk assessment at their assets and,
as part of that, to adopt this approach as part of their “business as usual” activities. A major outcome of
this requirement is that for major dams, risk management is now being driven from Board and senior
management level: the implementation of controls and actions is formalised. As a consequence, there is a
better understanding across the organisation of new and emerging risks that require new technologies,
thinking and expertise and an improved appreciation of asset interdependencies and the risk posed to reliant
stakeholders. With other reforms including oversight and audit arrangements in place, the move from “doing
enough” to striving for “good’ industry practice, aided by an improved regulatory regime and statutory
processes, is well established. A brief consideration of the lessons learned from the February 2017 Oroville
dam incident in this context concludes the paper.
Many mapped faults in the south-eastern highlands of New South Wales and Victoria are associated with apparently youthful topography, suggesting that faulting may have played a role in shaping the modern landscape. This has been demonstrated to be the case for the Lake George Fault, and may reasonably be inferred for the poorly characterised Murrumbidgee, Khancoban, Tantangara, Berridale Wrench and Tawonga faults. More than a dozen nearby major faults with similarly youthful topography are uncharacterised. In general, fault locations and extents are inconsistent across different scales of geologic mapping, and rupture lengths, slip rates and other fault behaviours remain largely unquantified. A more comprehensive understanding of these faults is required to support safety assessments for communities and large infrastructure in the region.
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.
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.