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Need and Opportunity for a Modernized PMP Approach

High-hazard structures in the United States, including dams and nuclear power plants, have been engineered for more than 75 years to withstand floods resulting from the PMP, a design standard based on the assumption that nature imposes limits on depths of precipitation that are physically possible across the United States (AMS, 2022; Hansen et al., 1982). PMP has remained a successful engineering standard for high-hazard infrastructure in the United States, because failures due to exceedance of flood design criteria are exceedingly rare. However, many of the more than 16,000 high-hazard dams and 50 nuclear power plants in the United States are approaching or exceeding their design lifetime. Failure of any one of these structures will likely result in loss of life and could impose significant economic losses and widespread environmental damage.

The hydrometeorological procedures required for estimating PMP, when developed, represented significant advances in understanding and characterizing extreme rainfall. However, although recent work has advanced many of the details, the fundamental assumptions and principles underpinning PMP estimation have changed little since the 1940s. National efforts to estimate PMP values ceased in 1999, and some regions have not seen updates in more than 60 years. Meanwhile, the risk of extreme precipitation is generally increasing. Therefore, a critical examination of the assumptions and procedures behind PMP estimation is appropriate and a new vision for the future of PMP estimation is timely.

COMMITTEE CHARGE AND STATEMENT OF TASK

At the request of the National Oceanic and Atmospheric Administration (NOAA), the National Academies of Sciences, Engineering, and Medicine has been tasked to critically assess the current procedures used to determine PMP and recommend an updated

prets this task to mean statistical uncertainty of PMP estimates. Characterization of statistical uncertainty is needed for effective implementation of dam and nuclear safety programs through Risk-Informed Decision Making (RIDM) procedures. However, current approaches for PMP estimation are not suitable for characterization of statistical uncertainty, in part because of the sparse datasets employed (Chapter 4). Methods have been developed for assessing sensitivity of PMP estimates to assumptions used in PMP computation (Chapter 4) and for comparing PMP estimates to other data-driven analyses of rainfall extremes. These tools provide useful insights on PMP estimates for decision makers, but they do not enable characterization of statistical uncertainty. Scientific advances that enable characterization of the statistical uncertainty of extreme precipitation estimates are detailed in Chapter 3.

Finally, over the coming decades, dam and nuclear safety programs will grapple with the challenges posed by impacts of climate change. Despite recognition that climate change will likely influence extreme precipitation (Chapter 3), current practice typically excludes consideration of climate change in PMP estimation (Chapter 4).

Since the publication of the 1994 National Academies report on PMP three decades ago (NRC, 1994), significant advances have been made in precipitation data acquisition, hydrometeorological science, numerical weather prediction, statistical methods, and climate modeling, as outlined in this report. Further advances in these areas are on the horizon. These advances will provide the foundation for implementing the major changes that are needed to modernize PMP estimation. This report, in addition to critically assessing the current practice, provides a roadmap of recommendations that NOAA, the scientific community, and the PMP practitioner community may follow to leverage these advances to modernize PMP estimation.

ROADMAP FOR REPORT

This report is organized by five principal chapters:

1. This first chapter provides the motivation for this study and a description of the committee’s task.
2. The second chapter establishes a “common understanding of PMP” by providing a historical summary of the development of PMP and its constituent parts, an overview of the primary PMP uses and users, and a description of the spatial and temporal time scales of PMP estimation.
3. The state of scientific knowledge in fields relevant to PMP, including recent advances, are presented in Chapter 3. These fields include the meteorology of extreme rainfall, rainfall data, numerical modeling and computing, climate change, and statistical methods.
4. A critical assessment of current PMP estimation methods is presented in Chapter 4.
5. The committee’s recommended approach for modernizing PMP estimation is detailed in Chapter 5. The committee recommends a phased approach in which near-term enhancements to current PMP estimation methods is followed by a

1. longer-term model-based PMP estimation method. The transition is facilitated by a proposed Model Evaluation Project.

The report also contains the following appendices, which provide additional context for analyses and recommendations:

• History and evolution of PMP definitions
• Characteristics of dams in the United States
• Criteria for modern PMP estimation

The responses to the four main study tasks can be found in the following sections of this report:

Task 1: Common Understanding of PMP. This task is principally addressed in Chapter 2. Additional details on PMP definitions and methods are provided in the critical assessment in Chapter 4 and Appendix B.

Task 2: Review and assess methods for PMP estimation. Existing approaches are introduced in Chapter 2 and critically reviewed and assessed in Chapter 4. Emerging approaches are principally treated in Chapter 3, with additional detail provided in Chapter 5.

Task 3: Assess data needs and sources for PMP estimation and evaluation, and best practices for transparency and accessibility. Data needs are principally discussed in the Rainfall Data sections in Chapters 3 and 5. Transparency and accessibility are treated in the data section of Chapter 5.

Task 4: Recommend a preferred approach for PMP estimation that incorporates the impacts of climate change and the characterization of uncertainty. Chapter 5 is devoted exclusively to addressing this task.