| Design
Quantifying uncertainty The conventional design flood estimation approaches fall short in addressing the full extent of deep uncertainty. It is imperative to take steps to identify underlying those present at various stages of the design flood estimation process. This can be achieved by leveraging new understandings and statistical methods, such as by employing the Bayesian approaches to quantitatively capture the uncertainty, or performing sensitivity experiments across a plausible range of perception
Climate-resilience framework Infrastructure designed by considering the impacts of climate change can offer increased service delivery and reliability, longer productive lifespan, and prolonged investment returns. Climate-resilience is a continuous process that must extend throughout the asset’s lifespan. There is documented evidence that investing in climate-resilience can result in benefits that can outpace costs by several folds. In their work, Islam et al introduce a climate-
precipitation events. A shorter record and incomplete information about storm characteristics introduce uncertainties. To overcome this, regional approaches are preferred for estimating frequency-based flood magnitudes and transposition of climatic variables and storm characteristics for estimating PMP-based floods.
Multi-variate analysis Integrating copula-based multi-variate frequency analysis with the current design flood estimation guidance is crucial to address dependency between various flood characteristics (eg, flood peak, volume, and duration) and compound flooding (eg, joint occurrence of fluvial, pluvial, and coastal foods) in a realistic way.
Incorporating climate change and addressing non-stationarity Global warming is likely to augment the amount of water vapour in the atmosphere and consequently, changes in precipitation characteristics and extreme weather patterns are expected. This makes it important to explore non-stationary techniques for estimating design floods for both small and large dams, levees, and embankments and to develop associated design guidance.
resilience framework tailored for dams and levees. In this, the essence of resilience is encapsulated by threshold capacity, coping capacity, recovery capacity, and adaptive capacity of flood control structures.
US experience Research in the US has also indicated an increased risk
of dam failure due to a changing climate. Analysis of rainfall sequences and events associated with recent hydrologic failures of 552 dams across the country, suggests intensifying precipitation may contribute to increasing failures of dams by overtopping. The decadal rate of dam failures has been
increasing since the 1970s, and with over 90,000 ageing dams still in service, the increasing likelihood of intense rainfall is leading to increased concern about future dam failures. As Hwang and Lall explain in Natural Hazards, conventional dam design criteria requires the spillway to be designed to handle the PMF using the PMP. Most large dams were designed to withstand extreme floods with an implied return period ranging from 104 to 107 years, as estimated by the PMF approach. However dam failures in the last 20 years, and many near failures, suggest more modest return periods for failure. For example, climate conditions during the
Below: Sanford Dam in Michigan, US, several months after failing in 2020. Research has indicated an increased risk of similar events due to more intense rainfall under a changing climate © Bernie Parsons / Shutterstock. com
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