COMPARISON OF FLOOD HAZARD ESTIMATION METHODS FOR DAM SAFETY
Recent years have seen many advances in statistical methods, probabilistic techniques and simulation methods to support the assessment of flood flows. The modeling methods themselves have become increasingly sophisticated. This reflects the increased access to both data and computational power. Approaches that attempt to deal with a varying climate have also started to emerge. As a result, a range of approaches are available to estimate flood flows and each has particular strengths and weaknesses. In association with development of these approaches, dam safety regulations have started to shift towards a risk approach. This change is placing new demands on the estimation of flood hazards, requiring aleatory and epistemic uncertainties to be more explicitly handled.
This project provides a structured review of the available and evolving methods for estimating flood flows, where they are used and, importantly, the assumptions and limitations they contain. The project findings are provided in two task reports. The Task 1 report focuses on how the approaches used to estimate flood flows are influenced by the different regulatory frameworks in place around the world. The second, Task 2 report focuses on the estimation approaches themselves.
Within both Task reports existing and emerging practice has been gathered through a combination of literature review and discussion with owners, regulators, researchers and practitioners across the world, including those in France, England, Canada, Australia, United States of America, Sweden, the Netherlands and Brazil. This close dialogue provides an excellent insight into the methods currently in use, their perceived strengths and weaknesses, and the direction of travel for future developments.
Is available only via the CEATI website
Sayers P. B., Nathan R., Rodda, H., Tomlinson, E., Gippel C, Little, M and Bowles, D (2014). Comparison of Flood Hazard Estimation Methods for Dam Safety. Published by CEATI international, Montreal, Canada.