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COMMITTEE ON MODERNIZING PROBABLE MAXIMUM PRECIPITATION ESTIMATION

JAMES SMITH (Chair), Senior Scientist and Professor Emeritus, Princeton University

DANIEL COOLEY, Professor, Colorado State University

JOHN ENGLAND, JR., Lead Civil Engineer, U.S. Army Corps of Engineers

EFI FOUFOULA-GEORGIOU, Distinguished Professor and Samueli Endowed Chair, University of California, Irvine

KATHLEEN D. HOLMAN, Meteorologist, Bureau of Reclamation

SHIH-CHIEH KAO, Senior Research Staff, Oak Ridge National Laboratory

RUBY LEUNG, Battelle Fellow, Pacific Northwest National Laboratory

ROBERT MASON, Extreme Hydrologic Events Coordinator and Senior Science Advisor for Surface Water, U.S. Geological Survey (Retired as of December 31, 2022)

JOHN NIELSEN-GAMMON, Regents Professor and Texas State Climatologist, Texas A&M University

JAYANTHA OBEYSEKERA, Research Professor, Institute of Environment, Florida International University

CHRISTOPHER PACIOREK, Adjunct Professor, University of California, Berkeley

RUSS SCHUMACHER, Professor and Colorado State Climatologist, Colorado State University

Study Staff

STEVEN STICHTER, Study Director, Senior Program Officer, Board on Atmospheric Sciences and Climate (BASC)

JONATHAN M. TUCKER, Program Officer, Water Science and Technology Board (WSTB)

KATRINA HUI, Associate Program Officer, BASC (until June 2023)

HUGH WALPOLE, Associate Program Officer, BASC (until March 2024)

KYLE ALDRIDGE, Senior Program Assistant, BASC (until February 2024)

ANNE MANVILLE, Program Assistant, BASC (February 2024 to present)

Reviewers

This Consensus Study Report was reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise. The purpose of this independent review is to provide candid and critical comments that will assist the National Academies of Sciences, Engineering, and Medicine in making each published report as sound as possible and to ensure that it meets the institutional standards for quality, objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process.

We thank the following individuals for their review of this report:

FAISAL HOSSAIN, University of Washington

KENNETH KUNKEL, North Carolina State University

VENKATARAMAN LAKSHMI, University of Virginia

BILL McCORMICK, Black & Veatch and ASDSO EPIC Task Group

ANGELINE PENDERGRASS, Cornell University

ANDREAS F. PREIN, National Center for Atmospheric Research

MELVIN SCHAEFER, MGS Engineering Consultants

RICHARD SMITH, University of North Carolina

JEFFREY ULLMAN (NAS, NAE), Stanford University

DANIEL WRIGHT, University of Wisconsin

Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations of this report nor did they see the final draft before its release. The review of this report was overseen by GEORGE M. HORNBERGER (NAE), Vanderbilt University, and ANA P. BARROS (NAE), University of Illinois. They were responsible for making certain that an independent examination of this report was carried out in accordance with the standards of the National Academies and that all review comments were carefully considered. Responsibility for the final content rests entirely with the authoring committee and the National Academies.

Acknowledgments

Many individuals assisted the committee in creating this report. The committee would like to thank the following people who gave presentations, participated in panel discussions, or provided some analysis on the National Inventory of Dams.

Kelcy Adamec, Federal Energy Regulatory Commission

Michael Anderson, California Department of Water Resources

Keith Banachowski, Ohio Department of Natural Resources

David Bascom, Federal Emergency Management Agency

Chris Bretherton, University of Washington, Allen Institute for AI

William Collins, Lawrence Berkeley National Laboratory

Pierre Gentine, Columbia University

Kevin Griebenow, Federal Energy Regulatory Commission

Joseph Kanney, U.S. Nuclear Regulatory Commission

Bill Kappel, Applied Weather Associates

Kenneth Kunkel, North Carolina State University

Gary Lackmann, North Carolina State University

Kelly Mahoney, NOAA Physical Sciences Laboratory

David Margo, U.S. Army Corps of Engineers

Bill McCormick, Black & Veatch and ASDSO EPIC Task Group

Daniel McGraw, U.S. Army Corps of Engineers

William McKercher, Mississippi Department of Environmental Quality

Zoran Micovic, BC Hydro

Mark Perry, Colorado Dam Safety

Andreas F. Prein, National Center for Atmospheric Research

Michael Pritchard, Nvidia, jointly at University of California, Irvine

Kevin Quinlan, U.S. Nuclear Regulatory Commission

Contents

SUMMARY

1 NEED AND OPPORTUNITY FOR A MODERNIZED PMP APPROACH

Committee Charge and Statement of Task

Roadmap for Report

2 COMMON UNDERSTANDING OF PMP

Definition

Fundamental Components of PMP

PMP Estimates in the United States

Uses and Users of PMP

Spatial and Temporal Scales for PMP Estimates

PMP and Probable Maximum Floods

3 STATE OF THE SCIENCE AND RECENT ADVANCES IN UNDERSTANDING EXTREME PRECIPITATION

Scientific Advances: Meteorology of Extreme Rainfall

Scientific Advances: Rainfall Data

Numerical Modeling and Computing

Scientific Advances: Climate Change and Extreme Rainfall

Advances: Statistical Methods

PMP as an Upper Bound?

4 CRITICAL ASSESSMENT OF CURRENT PMP METHODS

Overview

PMP Definitions

PMP Data and Methods

Numerical Modeling and PMP

Implications of Climate Change for PMP

Criteria for a Modern PMP Estimation Process

Critical Assessment of Current PMP Methods: Summary

5 RECOMMENDED APPROACH

Overview of a Phased Approach

Core Principles

PMP Definition

Near-Term Enhancements to PMP Estimation

Model-Based PMP Estimation

Model Evaluation Project

Bridging Near-Term and Long-Term Strategies

User Needs

Criteria For Valid/Useful PMP Estimates and Estimation Process

Summary

REFERENCES

APPENDICES

A COMMITTEE MEMBER AND STAFF BIOGRAPHICAL SKETCHES

B HISTORY OF PMP

C DAM CHARACTERISTICS

D CRITERIA FOR A MODERN PMP ESTIMATION PROCESS

E R CODE USED IN REPORT FIGURES 3-5 AND 5-3

Boxes, Figures, and Tables

BOXES

1-1 Statement of Task

2-1 Precipitation Frequency Analysis

2-2 Dam Rehabilitation, Expansion, and Construction

2-3 Risk-Informed Decision Making

2-4 Atmospheric Variables for Estimating Extreme Floods and Probable Maximum Floods

3-1 Storm Types

3-2 Generalized Extreme Value and Generalized Pareto Distributions

4-1 Trading Space for Time

4-2 Annual Exceedance Probability of PMP

TABLES

5-1 Summary of Model Simulation Types, Characteristics, and Purpose to Support the Recommended Approach (Near-Term Enhancements, Model Evaluation Project, and Long-Term Approach)

B-1 Average Percent Change in 10 mi² PMP from HMR 55A over Colorado and New Mexico for Various Locations and Durations

B-2 Summary of Percent Changes in PMP Estimates at 47 Watersheds from HMR 43 to HMR 57

B-3 Summary of Percent Changes in PMP Estimates at 38 Watersheds from HMR 36 to HMR 59

D-1 User Criteria for Valid/Useful PMP Estimates and Estimation Process

FIGURES

S-1 Overview of modernized PMP estimation

2-1 Fundamental components of PMP, including storm catalog, transposition, maximization, and orographic adjustment

2-2 Statewide PMP and precipitation frequency studies for dam safety

2-3 Example dam projects that use PMP for rehabilitations, expansions, and new designs (clockwise from upper left): North Fork Dam, Prado Dam, Gross Dam, Chimney Hollow Dam

2-4 South Carolina rainfall totals for 2–4 October 2015

2-5 Old Mill Pond Dam failure in Lexington, South Carolina, October 2015

2-6 Locations of high-hazard dams

2-7 Locations of currently operable and proposed nuclear reactors

2-8 Example flood hazard curve (maximum reservoir stages) for Lake Okeechobee, Florida

2-9 Empirical cumulative distributions of drainage areas, shown by primary owner type, for high-hazard dams

2-10 (a) Isohyetal (lines of equal rainfall) map and mass curves of the 6–12 May 1943 storm (top) and (b) the storm transposed and rotated to the critical location for the design rainfall of Keystone Dam on the Arkansas River near Tulsa, Oklahoma

2-11 (a) Isohyetal map of the intense 4-hour rainfall and (b) mass curves for the 31 July 1976 Big Thompson, Colorado, storm, showing that the local storm rainfall decreases rapidly over a short distance (in this case 2 mi²)

2-12 Hypothetical example of a 1-mi² nuclear reactor site (not a watershed) to apply locally intense precipitation

2-13 Example spatial distributions of extreme storm rainfall over a watershed (a) 72-hour PMP over the Santa Ana River watershed (Southern California) for the Prado Dam spillway rehabilitation design and (b) spatially distributed extreme rainfall and flood runoff depths, Arkansas River watershed upstream of Pueblo, Colorado

2-14 Diagram of a section showing typical paleoflood features used as paleostage indicators

3-1 Precipitation magnitudes and meteorological causes for the 30 largest 4-day events for an area size of ~50,000 km²

3-2 Left panel: Examples of clouds simulated by SCREAM, a global CPM, at 3.25 km grid spacing and comparison with satellite data. Right panel: Throughput of SCREAM in Simulated Days per day of wall clock time (SDYD) vs. node count on the Frontier (AMD GPUs) and Summit (Nvidia GPUs) demonstrating a throughput of more than 1 SYPD on the exascale Frontier machine

3-3 Observed changes in three measures of extreme precipitation: (a) total precipitation falling on the heaviest 1 percent of days, (b) daily maximum precipitation in a 5-year period, and (c) the annual heaviest daily precipitation amount over 1958–2021

3-4 Illustration of the possible change in intensity of PMP due to climate change, expressed as a percent change per degree of increase of global mean surface temperatures

3-5 Relationships of the upper bound (black curve) and of precipitation depths corresponding to extreme AEPs (green, blue, and red curves for return periods of 104, 105, and 106 years, respectively) to the shape parameter of the extreme value distribution

3-6 Envelope curves (linear and log scales), with world record point rainfall measurements with respect to duration

3-7 Distribution of shape parameter estimates from fitting individual station- and season-specific GEV distributions to GHCN daily precipitation data from stations in the contiguous United States

4-1 Importance of storm transposition and subjectivity: Smethport

4-2 Example basin-average (555 mi²) precipitation frequency curve with uncertainty and design rainfall estimates (horizontal lines) for Whittier Narrows Dam, California

4-3 Example dam safety tolerable risk guideline used in RIDM (FEMA, 2015) illustrating risk estimates for four dams, with different overtopping failure probabilities and consequences

4-4 Examples of envelopment of generalized PMP estimates in time (across durations) and in space (across drainage areas)

5-1 Overview of modernized PMP estimation

5-2 PMP precipitation depth that reflects the new definition

5-3 Sample size needed to achieve reasonable statistical uncertainty (in terms of the standard error) for an AEP depth or the upper bound as a function of the shape parameter value, under the assumptions of extreme value analysis

5-4 Example spatial and temporal scales desired for PMP products at kilometer-scale resolution: (a) mean annual precipitation for a specified climate period over CONUS (4 km), illustrating the scale and coverage desired for PMP estimates; (b) event-scale (24-hour accumulation) spatial distribution of an

Acronyms and Abbreviations