ML22257A136

Proceedings of the Seventh Annual Probabilistic Flood Hazard Assessment Research Workshop

ML22257A136
Person / Time
Issue date:	09/30/2022
From:	Thomas Aird, Joseph Kanney, Elena Yegorova NRC/RES/DRA
To:
Yegorova, Elena 301-415-2440
References
RIL 2022-10
Download: ML22257A136 (472)

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RIL 2022-10 PROCEEDINGS OF THE SEVENTH ANNUAL PROBABILISTIC FLOOD HAZARD ASSESSMENT RESEARCH WORKSHOP February 15-18, 2022 Date Published: September 2022 Prepared by:

Elena Yegorova, Tom Aird, Joseph Kanney U.S. Nuclear Regulatory Commission Rockville, MD 20852 Joseph Kanney, NRC Project Manager Research Information Letter Office of Nuclear Regulatory Research

Disclaimer Legally binding regulatory requirements are stated only in laws, NRC regulations, licenses, including technical specifications, or orders; not in Research Information Letters (RILs). A RIL is not regulatory guidance, although NRCs regulatory offices may consider the information in a RIL to determine whether any regulatory actions are warranted.

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ABSTRACT The U.S. Nuclear Regulatory Commission (NRC) Office of Nuclear Regulatory Research (RES) is conducting the multiyear, multi project Probabilistic Flood Hazard Assessment (PFHA)

Research Program to enhance the NRCs risk-informed and performance-based regulatory approach with regard to external flood hazard assessment and safety consequences of external flooding events at nuclear power plants. RES initiated this research in response to staff recognition of a lack of guidance for conducting PFHAs at nuclear facilities that required staff and licensees to use highly conservative deterministic methods in regulatory applications. Risk assessment of flooding hazards and consequences of flooding events is a recognized gap in the NRCs risk-informed, performance-based regulatory framework. The RES Probabilistic Flood Hazard Assessment Research Plan describes the objective, research themes, and specific research topics for the program. While the technical basis research, pilot studies, and guidance development are ongoing, RES has presented annual PFHA research workshops to communicate results, assess progress, collect feedback, and chart future activities. These workshops have brought together NRC staff and management from RES and user offices, technical support contractors, interagency and international collaborators, and industry and public representatives.

These conference proceedings transmit the agenda, abstracts, and presentation slides for the Seventh Annual NRC Probabilistic Flood Hazard Assessment Research Workshop held virtually in February 2022 via web conference software. The workshop took place February 15-18, 2022 and was attended by members of the public; nuclear industry and nuclear industry consultants; NRC technical staff, management, and contractors; and staff from other Federal agencies and academia. The workshop began with an introductory session that included perspectives and research program highlights from RES, the Federal Emergency Management Agency, and international working groups. NRC contractors and staff, as well as invited Federal and public speakers, gave technical presentations (including virtual poster sessions) and participated in various styles of panel discussion. The workshop included eight focus areas:

(1) overview of flooding research programs of the NRC, other Federal agencies, and selected international organizations (2) sensors (3) climate influences on flooding hazards (4) precipitation processes and modeling (5) riverine flooding processes and modeling (6) coastal flooding processes and modeling (7) Duane Arnold derecho operational experience (8) Tornado wind loads in the ASCE/SEI 7-2022 Standard (9) U.S. Army Corps of Engineers National Inventory of Dams and National Levee Database updates iii

TABLE OF CONTENTS 1 INTRODUCTION ................................................................................................................... 1-1 1.1 Background .................................................................................................................... 1-1 1.2 Workshop Objectives ..................................................................................................... 1-2 1.3 Workshop Scope ............................................................................................................ 1-2 1.4 Organization of Conference Proceedings ...................................................................... 1-3 1.5 Related Workshops ........................................................................................................ 1-3 2 WORKSHOP AGENDA ........................................................................................................ 2-1 3 PROCEEDINGS .................................................................................................................... 3-1 3.1 Day 1: Session 1A - Introduction ................................................................................... 3-1 3.1.1 Presentation 1A-1: Opening Remarks ............................................................. 3-1 3.1.2 Presentation 1A-2: NRC Probabilistic Flood Hazard Assessment Research Program Overview ............................................................... 3-5 3.1.3 Presentation 1A-3: Moving FEMA towards Probabilistic Flood Risk Analysis and Probabilistic Flood Hazard Analysis .............................. 3-13 3.1.4 Presentation 1A-4: Committee on the Safety of Nuclear Installations (CSNI) Working Group on External Events (WGEV) .......................... 3-27 3.2 Day 1: Session 1B -Flood & Fire Sensors for Resilient Communities ......................... 3-32 3.2.1 Presentation 1B-1 (KEYNOTE): Flood and Fire Sensors for Resilient Communities ...................................................................................... 3-32 3.2.2 Presentation 1B-2: USACE Instrumentation and Monitoring Program ........... 3-41 3.2.3 Presentation 1B-3: USGS Water Mission Area Observing Systems Research and Development Program ................................................ 3-60 3.2.4 Presentation 1B-4: State and Local Experience in Virginia Implementing IoT Sensors and Data Systems .......................................................... 3-70 3.2.5 Flood & Fire Sensors for Resilient Communities Panel Discussion (Session 1B-5).................................................................................... 3-78 3.3 Day 1: Session 1C - Climate ....................................................................................... 3-82 3.3.1 Presentation 1C-1 (KEYNOTE): Big Stories from the Historic Winter of 2020/21 .............................................................................................. 3-82 3.3.2 Presentation 1C-2: Linking Arctic variability and change with extreme winter weather in the US including the Texas Freeze of February 2021 ................................................................................................... 3-99 3.3.3 Presentation 1C-3: 2021 U.S. Billion Dollar Weather and Climate Disasters in Historical Context including New County-Level Exposure, Vulnerability and Projected Damage Mapping ................ 3-117 3.3.4 Climate Panel Discussion (Session 1C-4) ................................................... 3-134 3.4 Day 2: Session 2A - Precipitation .............................................................................. 3-137 3.4.1 Presentation 2A-1: Uncertainty in Precipitation Frequency Estimates Under Current and Future Climate ................................................... 3-137 3.4.2 Presentation 2A-2 (KEYNOTE): Gridded Surface Weather Data with Uncertainty Quantification - Daymet V4 ........................................... 3-151 3.4.3 Presentation 2A-3: Utility of Weather Types to Improve Nonstationary Frequency Analysis of Extreme Precipitation ................................... 3-164 3.4.4 Presentation 2A-4: Characteristics and Causes of Extreme Snowmelt over the Conterminous United States .............................................. 3-175 3.4.5 Presentation 2A-5: LIP PFHA Pilot Study .................................................... 3-186 iv

3.4.6 Precipitation Panel Discussion (Session 2A-6) ............................................ 3-195 3.5 Day 2: Session 2B - Riverine Flooding ...................................................................... 3-198 3.5.1 Presentation 2B-1 (KEYNOTE): Flood Typing and Application to Mixed Population Flood Frequency Analysis: An Interagency Collaborative Effort ........................................................................... 3-198 3.5.2 Presentation 2B-2: Applying Stochastic Weather Generation and Continuous Hydrologic Simulation for Probabilistic Flood Hazard Assessments .................................................................................... 3-215 3.5.3 Presentation 2B-3: IWRSS Flood Inundation Mapping for Flood Response ......................................................................................... 3-228 3.5.4 Presentation 2B-4: Using HEC-WAT for NRC's PFHA Process .................. 3-238 3.5.5 Riverine Panel Discussion (Session 2B-5)................................................... 3-252 3.6 Day 3: Session 3A - Poster Session ......................................................................... 3-256 3.6.1 Poster 3A-1: Flood Fragility Function Methodology for a Conceptual Nuclear Power Plant......................................................................... 3-256 3.6.2 Poster 3A-2: Quantifying Uncertainty in Hurricane Warning Times to Inform Coastal Hazard PRA ............................................................. 3-261 3.6.3 Poster 3A-3: HEC-WAT Interface and Set Up for the Trinity River PFHA Pilot Project ...................................................................................... 3-268 3.6.4 Poster 3A-4: Riverine Flooding HEC-WAT Pilot Project Dam Break Modeling ........................................................................................... 3-273 3.6.5 Poster 3A-5: Flooding from Below - The Groundwater Emergence Hazard .............................................................................................. 3-283 3.6.6 Poster 3A-6: External Flooding PRA Guidance ........................................... 3-291 3.7 Day 3: Session 3B - Coastal Flooding ....................................................................... 3-297 3.7.1 Presentation 3B-1: An Overview of CSTORM Model Development and Results for the South Atlantic Coastal Study (SACS) ...................... 3-297 3.7.2 Presentation 3B-2: Compound Flood Hazard Assessment using a Bayesian Framework ........................................................................ 3-313 3.7.3 Presentation 3B-3: Coastal Flooding PFHA Pilot Study ............................... 3-325 3.7.4 Presentation 3B-4: Probabilistic Wave Height Hazard Assessment Method at the NPP Site Considering Storm Surge .......................... 3-344 3.7.5 Presentation 3B-5: Comparative Assessment of Joint Distribution Models for Tropical Cyclone Atmospheric Parameters in Probabilistic Coastal Hazard Analysis .............................................. 3-357 3.7.6 Coastal Panel Discussion (Session 3B-6).................................................... 3-369 3.8 Day 4: Session 4A - Duane Arnold Derecho Operational Experience....................... 3-372 3.8.1 Presentation 4A-1: Duane Arnold Energy Center (DAEC) Loss of Offsite Power (LOOP) Due to Derecho........................................................ 3-372 3.8.2 Presentation 4A-2: The NRCs Regional Response to the Duane Arnold Derecho ............................................................................................ 3-379 3.8.3 Presentation 4A-3: Why the Risk of the Extended Loss of Offsite Power Was Almost a Significant Precursor? ............................................... 3-390 3.8.4 Presentation 4A-4: The NRCs Response to the Duane Arnold Derecho Event using the LIC-504 Process ..................................................... 3-397 3.8.5 Duane Arnold OpE Panel Discussion (Session 4A-5).................................. 3-405 3.9 Day 4: Session 4B - ASCE-7 Tornado Wind Loads .................................................. 3-411 3.9.1 Presentation 4B-1: Introduction to Tornado Loads in the New ASCE 7-22 Standard - Including Long Return Period Tornado Hazards Maps with Applications to Nuclear Facilities .................................... 3-411 3.10 Day 4: Session 4C - USACE Dam and Levee Database Updates ........................... 3-428 v

3.10.1 Presentation 4C-1: National Inventory of Dams ........................................... 3-428 3.10.2 Presentation 4C-2: National Levee Database .............................................. 3-434 4 WORKSHOP PARTICIPANTS ............................................................................................. 4-1 5

SUMMARY

AND CONCLUSIONS ....................................................................................... 5-1 5.1 Summary ........................................................................................................................ 5-1 5.2 Conclusions .................................................................................................................... 5-1 6 ACKNOWLEDGMENTS ....................................................................................................... 6-1 vi

1 INTRODUCTION This research information letter (RIL) details the Seventh Annual U.S. Nuclear Regulatory Commission (NRC) Probabilistic Flood Hazard Assessment (PFHA) Research Workshop held virtually from February 15-18, 2022. These proceedings include presentation abstracts and slides. The workshop was attended by members of the public; nuclear industry and nuclear industry consultants; NRC technical staff, management, and contractors; and staff from other Federal agencies and academia.

The workshop began with an introduction from Ray Furstenau, Director, NRC Office of Nuclear Regulatory Research (RES). Following the introduction, staff members from RES and the Federal Emergency Management Agency (FEMA) described their flooding research programs.

Additionally, John Nakoski, RES, provided an overview of external hazard efforts (including flooding) underway by the Nuclear Energy Agency, Committee on the Safety of Nuclear Installations (CSNI), Working Group on External Events (WGEV).

Technical sessions followed the introduction session. Most sessions began with an invited keynote speaker, followed by several technical presentations, and concluded with a panel of all speakers, who discussed the session topic in general. At the end of each day, participants provided feedback and asked generic questions about research related to PFHA for nuclear facilities. At the end of the third day, a virtual poster session was held with each poster presenter being assigned a unique web conferencing room where attendees were free to attend and leave at will.

1.1 Background

The NRC is conducting the multiyear, multi project PFHA Research Program. It initiated this research in response to staff recognition of a lack of guidance for conducting PFHAs at nuclear facilities that required staff and licensees to use highly conservative deterministic methods in regulatory applications. The staff described the objective, research themes, and specific research topics in the Probabilistic Flood Hazard Assessment Research Plan, Version 2014-10-23, provided to the Commission in November 2014 (Agencywide Documents Access and Management System (ADAMS) Accession Nos. ML14318A070 and ML14296A442). The NRC Office of Nuclear Reactor Regulation and the former Office of New Reactors endorsed the PFHA Research Plan in a joint user need request (ADAMS Accession No. ML15124A707). This program is designed to support the development of regulatory tools (e.g., regulatory guidance, standard review plans) for permitting new nuclear sites, licensing new nuclear facilities, and overseeing operating facilities. Specific uses of flooding hazard estimates (i.e., flood elevations and associated affects) include flood-resistant design for structures, systems, and components (SSCs) important to safety and advanced planning and evaluation of flood protection procedures and mitigation.

The lack of risk-informed guidance with respect to flooding hazards and flood fragility of SSCs constitutes a significant gap in the NRCs risk-informed, performance-based regulatory approach to the assessment of hazards and potential safety consequences for commercial nuclear facilities. The probabilistic technical basis developed will provide a risk-informed approach for improved guidance and tools to give staff and licensees greater flexibility in evaluating flooding hazards and potential impacts to SSCs in the oversight of operating facilities (e.g., license amendment requests, significance determination processes, notices of 1-1

enforcement discretion) as well as the licensing of new facilities (e.g., early site permit applications, combined license applications), including proposed small modular reactors and advanced reactors. This methodology will give the staff more flexibility in assessing flood hazards at nuclear facilities so the staff will not have to rely on the use of the current deterministic methods, which can be overly conservative in some cases.

The main focus areas of the PFHA Research Program are to (1) leverage available frequency information on flooding hazards at operating nuclear facilities and develop guidance on its use, (2) develop and demonstrate a PFHA framework for flood hazard curve estimation, (3) assess and evaluate the application of improved mechanistic and probabilistic modeling techniques for key flood-generating processes and flooding scenarios, (4) assess potential impacts of dynamic and nonstationary processes on flood hazard assessments and flood protection at nuclear facilities, and (5) assess and evaluate methods for quantifying reliability of flood protection and plant response to flooding events. Workshop organizers used these focus areas to develop technical session topics for the workshop.

1.2 Workshop Objectives The Annual PFHA Research Workshops serve multiple objectives: (1) inform and solicit feedback from internal NRC stakeholders, partner Federal agencies, industry, and the public about PFHA research being conducted by RES, (2) inform internal and external stakeholders about RES research collaborations with Federal agencies, the Electric Power Research Institute (EPRI), and the IRSN, and (3) provide a forum for presentation and discussion of notable domestic and international PFHA research activities.

1.3 Workshop Scope The scope of the workshop presentations and discussions included the following:

• overview of flooding research programs of the NRC, other Federal agencies, and selected international organizations

• sensors

• climate influences on flooding hazards

• precipitation processes and modeling

• riverine flooding processes and modeling

• coastal flooding processes and modeling

• Duane Arnold derecho operational experience

• Tornado wind loads in the ASCE/SEI 7-2022 Standard

• U.S. Army Corps of Engineers National Inventory of Dams and National Levee Database updates 1-2

1.4 Organization of Conference Proceedings Section 2 provides the agenda for this workshop. The agenda is also available from NRC's Agencywide Documents Access and Management System (ADAMS) at Accession No. ML22061A099.

Section 3 presents the proceedings from the workshop, including abstracts and presentation slides and abstracts for submitted posters.

The summary document of session abstracts for the technical presentations is available at ADAMS Accession No. ML22061A100. The complete workshop presentation package is available at ADAMS Accession No. ML22061A095.

Section 4 lists the workshop attendees and Section 5 summarizes the workshop.

1.5 Related Workshops The NRCs Annual PFHA Research Workshops take place approximately annually at NRC Headquarters in Rockville, MD. The proceedings from the Sixth Annual PFHA Research Workshop (held February 22-25, 2021) have been published as RIL-2022-02. The proceedings from the Fifth Annual PFHA Research Workshop (held February 19-21, 2020) have been published as RIL-2021-01. NRC has published the collected proceedings from the first four workshops, listed below, as RIL-2020-01, available on the agencys public Web site:

• First Annual NRC PFHA Research Workshop, October 14-15, 2015

• Second Annual NRC PFHA Research Workshop, January 23-25, 2017

• Third Annual NRC PFHA Research Workshop, December 4-5, 2017

• Fourth Annual NRC PFHA Research Workshop, April 30-May 2, 2019 In addition, an international workshop on PFHA took place January 29-31, 2013. The workshop was devoted to sharing information on PFHAs for extreme events (i.e., annual exceedance probabilities (AEPs) much less than 2x10-3 per year) from the Federal community. The NRC issued the proceedings as NUREG/CP-302, Proceedings of the Workshop on Probabilistic Flood Hazard Assessment (PFHA), in October 2013 (ADAMS Accession No. ML13277A074).

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2 WORKSHOP AGENDA Day 1 (February 15, 2022) Oral Presentations

• denotes speaker Session 1A: Introduction Chair: Joseph Kanney, NRC/RES 1A-0 Webinar Logistics Kenneth Hamburger*, 10:00 10:10 NRC/RES 1A-1 Opening Remarks Ray Furstenau*, Director, 10:10 10:25 NRC Office of Research 1A-2 NRC PFHA Research Program Tom Aird*, NRC/RES 10:25 10:40 Update 1A-3 Moving FEMA towards Probabilistic David Rosa*, Christina 10:40 11:05 Flood Risk Analysis and Lindemer, Federal Probabilistic Flood Hazard Analysis Emergency Management Agency (FEMA) 1A-4 Committee on the Safety of Nuclear John Nakoski*, NRC/RES 11:05 11:20 Installations (CSNI) Working Group (WGEV Chair) on External Events (WGEV)

Break 11:20 11:35 Session 1B: Sensors Chair: Joseph Kanney, NRC/RES 1B-1 (Keynote) Flood & Fire Sensors for Jeffrey Booth*, Department 11:35 12:00 Resilient Communities of Homeland Security, Science & Technology Directorate 1B-2 USACE Instrumentation and Georgette Hlepas*, 12:00 12:25 Monitoring Program Christopher Schaal*, U.S.

Army Corps of Engineers 1B-3 USGS Water Mission Area R. Russel Lotspeich*, U.S. 12:25 12:50 Observing Systems Research and Geological Survey Development Program 1B-4 State and Local Experience in David Ihrie*, Virginia 12:50 13:15 Virginia Implementing IoT Sensors Innovation Partnership and Data Systems Corporation 1B-5 Sensor Panel Discussion All Presenters 13:15 13:35 Lunch 13:35 14:35 2-1

Session 1C: Climate Chair: Elena Yegorova, NRC/RES 1C-1 (KEYNOTE) Big Stories from the David Novak*, National 14:35 15:05 Historic Winter of 2020/21 Oceanic and Atmospheric Administration, National Weather Service (NOAA/NWS) 1C-2 Linking Arctic variability and change Judah Cohen*1, Laurie 15:05 15:30 with extreme winter weather in the Agel2, Mathew Barlow2, US including the Texas Freeze of Chaim Garfinkel3, Ian White3; February 2021 1Atmospheric and Environmental Research, 2University of Massachusetts Lowell, 3Hebrew University of Jerusalem 1C-3 2021 U.S. Billion Dollar Weather Adam Smith*, National 15:30 15:55 and Climate Disasters in Historical Oceanic and Atmospheric Context including New County-Level Administration, National Exposure, Vulnerability and Centers for Environmental Projected Damage Mapping Information (NOAA/NCEI) 1C-4 Climate Panel Discussion All Presenters 15:55 16:25 1D Day 1 Wrap-up 16:25 16:30 2-2

Day 2 (February 16, 2022) Oral Presentations Session 2A: Chair: Kevin Quinlan, NRC/NRR Precipitation 2A-1 Uncertainty in Azin Al Kajbaf*, Michelle Bensi, Kaye 10:05 10:30 Precipitation Frequency Brubaker; University of Maryland Estimates Under Current and Future Climate 2A-2 (KEYNOTE) Gridded Peter Thornton*, Oak Ridge National 10:30 11:00 Surface Weather Data Laboratory with Uncertainty Quantification - Daymet V4 2A-3 Utility of Weather Types Giuseppe Mascaro*, Arizona State 11:00 11:25 to Improve the University Nonstationary Frequency Analysis of Extreme Precipitation Break 11:25 11:35 2A-4 Characteristics and Joshua Welty*1, Xubin Zeng2; 1U.S. 11:35 12:00 Causes of Extreme Navy Fleet Numerical Meteorology and Snowmelt over the Oceanography Center, 2Univerity of Conterminous United Arizona States 2A-5 LIP PFHA Pilot Study Rajiv Prasad*, Arun Veeramany, 12:00 12:25 Rajesh Singh; Pacific Northwest National Laboratory (PNNL) 2A-6 Precip Panel Discussion All Presenters 12:25 12:55 Lunch 12:55 14:00 2-3

Session 2B: Riverine Chair: Joseph Kanney, NRC/RES Flooding 2B-1 (KEYNOTE) Flood Nancy Barth*1, Michael Bartles2, John 14:00 14:30 Typing and Application to England2, Jory Hecht1, Gregory Mixed Population Flood Karlovits2, William Lehman2; 1U.S.

Frequency Analysis: An Geological Survey (USGS), 2U.S. Army Interagency Corps of Engineers (USACE)

Collaborative Effort 2B-2 Applying Stochastic Joe Bellini*1, Bill Kappel2, Dennis 14:30 14:55 Weather Generation and Johnson2, Doug Hultstrand2; 1Aterra Continuous Hydrologic Solutions, 2Applied Weather Associates Simulation for Probabilistic Flood Hazard Assessments 2B-3 IWRSS Flood Inundation Robert Mason*1, Julia Prokopec*1, 14:55 15:20 Mapping for Flood Adam Barker*2, Cory Winders*3, Response Darone Jones*4; 1U.S. Geological Survey, 2Federal Emergency Management Agency, 3U.S. Army Corps of Engineers, 4National Weather Service 2B-4 Using HEC-WAT for William Lehman*, Gregory Karlovits, 15:20 15:45 NRC's PFHA Process David Ho, Leila Ostadrahimi, Brennan Beam, Sara O'Connell, Julia Slaughter; U.S. Army Corps of Engineers Hydrologic Engineering Center (USACE/HEC) 2B-5 Riverine Panel All Presenters 15:45 16:15 Discussion 2C Day 2 Wrap-up 16:15 16:25 2-4

Day 3 (February 17, 2022) Poster Presentations Session 3A: Posters Chair: Thomas Aird, NRC/RES 3A-1 Flood Fragility Function Joy Shen*, Michelle Bensi, 10:00 11:00 Methodology for a Mohammad Modarres; University of Conceptual Nuclear Power Maryland Plant 3A-2 Quantifying Uncertainty in Somayeh Mohammadi*, Michelle 10:00 11:00 Hurricane Warning Times to Bensi; University of Maryland Inform Coastal Hazard PRA 3A-3 HEC-WAT Interface and Set David Ho*, William Lehman, Brennan 10:00 11:00 Up for the Trinity River Beam, Sara OConnell, Leila PFHA Pilot Project Ostadrahimi; U.S. Army Corps of Engineers, Hydrologic Engineering Center 3A-4 Riverine Flooding HEC-WAT Brennan Beam*, William Lehman, 10:00 11:00 Pilot Project Dam Break Sara OConnell, David Ho, Leila Modeling Ostadrahimi; U.S. Army Corps of Engineers, Hydrologic Engineering Center 3A-5 Flooding from Below - The Kevin M. Befus*1, Patrick L. 10:00 11:00 Groundwater Emergence Barnard2, Peter W. Swarzenski2, Hazard Clifford Voss2; 1University of Arkansas, 2U.S. Geological Survey 3A-6 External Flooding PRA Marko Randelovic*1, Raymond 10:00 11:00 Guidance Schneider*2; 1Electric Power Research Institute (EPRI),

2Westinghouse Company Break 11:00 11:10 2-5

Day 3 (February 17, 2022) Oral Presentations Session 3B: Coastal Chair: Joseph Kanney, NRC/RES Flooding 3B-1 (KeyNote) An Overview of Margaret Owensby*1, Chris Massey1, 11:10 11:40 CSTORM Model Tyler Hesser1, Mary Bryant1, Andrew Development and Results Condon2; 1U.S. Army Corps of for the South Atlantic Engineers (USACE), Engineer Coastal Study (SACS) Research and Development Center, Coastal and Hydraulics Laboratory, 2USACE Jacksonville District 3B-2 Compound Flood Hazard Somayeh Mohammadi*1, Michelle 11:40 12:05 Assessment using a Bensi1, Shih-Chieh Kao2, Scott Bayesian Framework DeNeale2, Joseph Kanney3, Elena Yegorova3, Meredith Carr4; 1Univeristy of Maryland, 2Oak Ridge National Laboratory, 3U.S. Nuclear Regulatory Commission, 4U.S. Army Corps of Engineers, Engineer Research and Development Center, Coastal and Hydraulics Laboratory 3B-3 Coastal Flooding PFHA Victor M. Gonzalez*, Meredith L. 12:05 12:30 Pilot Study Carr, Karlie Wells, Norberto C. Nadal Caraballo; U.S. Army Corps of Engineers, Engineer Research and Development Center, Coastal and Hydraulics Laboratory 3B-4 Probabilistic Wave Height Beom-Jin Kim*, Daegi Hahm, Minkyu 12:30 12:55 Hazard Assessment Kim; Korea Atomic Energy Research Method at the NPP Site Institute Considering Storm Surge 3B-5 Comparative Assessment Ziyue Liu*1, Michelle Bensi1, Meredith 12:55 13:20 of Joint Distribution Models Carr2, Norberto Nadal-Caraballo2; for Tropical Cyclone 1University of Maryland, 2U.S. Army Atmospheric Parameters in Corps of Engineers Engineer Probabilistic Coastal Research and Development Center Hazard Analysis Coastal and Hydraulics Laboratory 3B-6 Coastal Panel Discussion All Presenters 13:20 13:50 3C Day 3 Wrap-up 13:50 14:00 2-6

Day 4 (February 18, 2022) Oral Presentations Session 4A: Duane Arnold Chair: Joseph Kanney, Derecho Operational Experience NCR/RES 4A-1 Duane Arnold Energy Center Terry Brandt*, Nextera Energy 10:00 10:25 (DAEC) Loss of Offsite Power (LOOP) Due to Derecho 4A-2 The NRCs Regional Response to John Hanna*, U.S. Nuclear 10:25 10:50 the Duane Arnold Derecho Regulatory Commission, Region 3 (NRC/R3) 4A-3 Why the Risk of the Extended Christopher Hunter*, U.S. 10:50 11:15 Loss of Offsite Power Was Almost Nuclear Regulatory a Significant Precursor? Commission, Office of Research (NRC/RES) 4A-4 The NRCs Response to the Matthew Leech*, U.S. Nuclear 11:15 11:40 Duane Arnold Derecho Event Regulatory Commission, Office using the LIC-504 Process of Nuclear Reactor Regulation (NRC/NRR) 4A-5 Duane Arnold OpE Panel All Presenters 11:40 11:40 Discussion Break 11:40 11:55 Session 4B: ASCE-7 Tornado Chair: Elena Yegorova, Wind Loads NRC/RES 4B-1 Introduction to Tornado Loads in Marc Levitan*, National 11:55 12:25 the New ASCE 7-22 Standard - Institute of Standards and Including Long Return Period Technology Tornado Hazards Maps with Applications to Nuclear Facilities Lunch 12:25 13:25 Session 4C: USACE Dam and Chair: Joseph Kanney, Levee Database Updates NRC/RES 4C-1 National Inventory of Dams Becky Ragon*, U.S. Army 13:25 13:55 Corps of Engineers 4C-2 National Levee Database Brian Vanbockern*, U.S. Army 13:55 14:25 Corps of Engineers 4D Workshop Wrap-up Discussion 14:25 14:45 2-7

2-8 3 PROCEEDINGS 3.1 Day 1: Session 1A - Introduction Session Chair: Joseph Kanney, NRC/RES/DRA There are no abstracts for this introductory session.

3.1.1 Presentation 1A-1: Opening Remarks Speaker: Raymond Furstenau, Director, NRC Office of Nuclear Regulatory Research 3.1.1.1 Presentation (ADAMS Accession No. ML22061A138) 3-1

3-2 3-3 3-4 3.1.2 Presentation 1A-2: NRC Probabilistic Flood Hazard Assessment Research Program Overview Authors: Thomas Aird, Joseph Kanney, Elena Yegorova, NRC Office of Nuclear Regulatory Research Speaker: Thomas Aird 3.1.2.1 Presentation (ADAMS Accession No. ML22061A137) 3-5

3-6 3-7 3-8 3-9 3-10 3-11 3-12 3.1.3 Presentation 1A-3: Moving FEMA towards Probabilistic Flood Risk Analysis and Probabilistic Flood Hazard Analysis Authors: David Rosa*, Christina Lindemer, Federal Emergency Management Agency (FEMA)

Speakers: David Rosa 3-13

3.1.3.1 Presentation (ADAMS Accession No. ML22061A136) 3-14

3-15 3-16 3-17 3-18 3-19 3-20 3-21 3-22 3-23 3-24 3-25 3-26 3.1.4 Presentation 1A-4: Committee on the Safety of Nuclear Installations (CSNI)

Working Group on External Events (WGEV)

Speaker: John Nakoski, NRC/RES/DRA (WGEV Chair) 3.1.4.1 Presentation (ADAMS Accession No. ML22061A135) 3-27

3-28 3-29 3-30 3-31 3.2 Day 1: Session 1B -Flood & Fire Sensors for Resilient Communities Session Chair: Joseph Kanney, NRC/RES/DRA 3.2.1 Presentation 1B-1 (KEYNOTE): Flood and Fire Sensors for Resilient Communities Author: Jeffrey Booth, Department of Homeland Security, Science & Technology Directorate Speaker: Jeffrey Booth 3.2.1.1 Abstract Flooding and Wildland Fires are the nations leading natural disasters, accounting for the greatest loss of life, property damage and economic impact while threatening the resiliency of communities across the country. Current flood damage is estimated at $5 billion per year and wildland fires annualized losses are estimated to range from $63.5 billion to $285 billion. The human cost is much greater.

The Department of Homeland Security (DHS) has been working with small businesses on the development, evaluation, and commercialization of low-cost Internet of Things (IoT) flood and wildland fire sensors. The goal is to provide earlier alerts, warnings and notifications of rising waters and fire ignitions, allowing communities the ability to better respond, mitigate and possibly prevent catastrophic disasters.

3.2.1.2 Presentation (ADAMS Accession No. ML22061A134) 3-32

3-33 Flood Sensor Technology Video:

https://www.dhs.gov/medialibrary/assets/videos/19974 3-34

3-35 3-36 Wildland Fire Sensor Technology Video:

https://www.dhs.gov/medialibrary/assets/videos/21982 3-37

3-38 3-39 3-40 3.2.2 Presentation 1B-2: USACE Instrumentation and Monitoring Program Authors: Georgette Hlepas, Christopher Schaal, U.S. Army Corps of Engineers Speakers: Georgette Hlepas, Christopher Schaal 3.2.2.1 Abstract USACEs instrumentation and monitoring program monitors over 700 dams and 4,000 miles of levees. As part of USACES advancement in monitoring, this presentation will focus on the MIDAS (Monitoring Instrumentation Data Acquisition System) project, an enterprise-wide instrumentation database. USACE will also provide an overview of their ongoing evaluation of DHS developed Low-Cost IoT Flood Inundation Sensors, and their potential use to complement USACEs monitoring programs.

3-41

3.2.2.2 Presentation (ADAMS Accession No. ML22061A133) 3-42

3-43 3-44 3-45 3-46 3-47 3-48 3-49 3-50 3-51 3-52 3-53 3-54 3-55 3-56 3-57 3-58 3-59 3.2.3 Presentation 1B-3: USGS Water Mission Area Observing Systems Research and Development Program Authors: R. Russell Lotspeich, U.S. Geological Survey Speaker: R. Russell Lotspeich 3.2.3.1 Abstract The USGS has a long history of evaluating water technologies for use in monitoring and research applications carried out to characterize the nations water resources. This is done to verify manufacturer specifications as well as to evaluate technologies for use in new environments and under a range of environmental conditions. Not all technologies are well-suited for all environments and understanding instrument limitations is critical to selecting the best instrument for a given location and to properly interpreting the data generated.

The USGS Water Mission Area (WMA) began receiving congressional appropriations in 2018 to develop a Next Generation Water Observing System (NGWOS) program in select basins across the U.S. This program includes significant investments into evaluating new technologies and transitioning the most promising ones into national operations. Of interest to the program are new and innovative monitoring methods and instrumentation that result in increased efficiencies, accuracy, new data types, and(or) temporal and spatial resolution of water data across networks. Imagery, remote sensing, and artificial intelligence are just a few examples of technologies that are currently being evaluated through the NGWOS program.

The USGS has historically held all the traditional types of water data it provides to the public to a uniform standard for data quality and uncertainty. With advances in technology providing exciting and useful alternative methods for measuring parameters such as water level, water velocity, and water temperature, some of the most promising technologies, unfortunately, do not meet that single standard. Because these data are still of great value to stakeholders and the USGS in defining the temporal and geographic variability in hydrologic conditions, there is a desire to move forward with operational implementation of many of these new systems. So that the new data types and results of new collection methods can be interpreted by end users with as much confidence as the traditional USGS data, the USGS WMA is evaluating systems of data classification that will clearly identify differing levels of quality and uncertainty associated with each new data type, and the NGWOS program is leading this effort.

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3-62 3-63 3-64 3-65 3-66 3-67 3-68 3-69 3.2.4 Presentation 1B-4: State and Local Experience in Virginia Implementing IoT Sensors and Data Systems Authors: David Ihrie, Virginia Innovation Partnership Corporation Speaker: David Ihrie 3.2.4.1 Abstract The Commonwealth of Virginia and local government partners now have increasing experience implementing IoT sensors such as flood and wildfire sensors, and their related data systems and user facing applications This talk provides a description of the journey, lessons learned, and a look towards the future as these increasingly ubiquitous sensors become a primary driver for situational awareness and delivery of services.

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3-72 3-73 3-74 3-75 3-76 3-77 3.2.5 Flood & Fire Sensors for Resilient Communities Panel Discussion (Session 1B-5)

Moderator: Joseph Kanney, NRC/RES/DRA/FXHAB Jeffrey Booth, Department of Homeland Security, Science & Technology Directorate Georgette Hlepas, U.S. Army Corps of Engineers R. Russel Lotspeich, U.S. Geological Survey David Ihrie, Virginia Innovation Partnership Corporation Question:

What are your thoughts about the tradeoffs between using cellular communications for these instrumentation systems versus using a different type of communication system, such as the dedicated radio systems used for emergency management? Because cellular networks can get clogged up in emergencies. What are the tradeoffs of how the sensors would communicate with the databases or to be queried and things like that?

David Ihrie:

I think the actual sensing elements are independent of the radio system for the communications.

Because there are a number of different potential user communities, my preference would be to have a more general type of communications backhaul rather than a single user, like the emergency management. But however that first hop occurs, our experience has been that the integration of the data on the backend and the sharing of that data is much trickier and it's kind of the critical piece. We've experimented with several different types of radios.

Question:

Can you say a little bit more about what different types of radios you have experimented with?

David Ihrie:

Sure. LoRa is one that is, I think, also pretty popular. We are doing some experimentation in the testbed directly with 5G and several mechanisms to kind of extend off the edge of the 5G network into areas without as much coverage. There has been a look at satellite communications. So, I think just a variety.

Jeff Booth:

For the flood sensors, we have done both cellular and LoRa. We had some challenges with LoRa in very steep terrain, granite hills, etc. So, they have both capabilities, in addition to Iridium satellite. But we are testing the next round of wildland fire sensors that will deploy 20 to 50 sensors with the US Geological Survey and the Feather River in California at LoRa sites that they have deployed for some of their monitoring to get a better sense of both the cell and LoRa comparisons.

Georgette Hlepas:

We often have these discussions with water management and geotech instrumentation. What is the best route? For normal operations cellular works just fine without an issue. Our concern is remote projects and those cellular systems not functioning during emergencies and not being 3-78

able to know what is happening at our projects. For those more critical projects, more remote projects, a lot of those are using satellite-based data. We transmit through the GOES satellite system. Thats more reliable for specific areas.

Russel Lotspeich:

We are also utilizing several different technologies for telemetry. Primarily we utilize GOES. The issue with GOES is the lack of bandwidth for things like imagery. So, we keep getting pushed to cellular for these kinds of higher bandwidth requirement data types. Our focus has been on getting data into our national water information system faster and building better web services and API points, so that people can access the data more readily through our system.

We have added alert radios to our system, so our monitoring stations have the ability to use multiple types of telemetry, much like Jeff was describing. If there is a need by a locality to add one of their local radios to our systems, that is not out of the question, but it creates an issue for us to get the data into our system. That is why we still want to rely primarily on GOES.

Question:

Most of the presentations concentrated on deploying the sensors in some sort of a network ahead of time. I was curious has anyone given a lot of thought or have concrete plans for a use case, which would be more like a campaign in response to an event or an evolving situation?

For example, if certain state is in a real drought situation, could there be a campaign to deploy those fire sensors? Or if there has been a particularly wet spring in a certain area and you are worried about snow melt flooding happening in the early summer in a certain area, could there be a campaign to deploy flood sensors?

Jeff Booth:

We have deployed a thousand sensors, mostly flood sensors. And some of our stakeholders did keep several back just for those types of purposes, mostly coastal right now in terms of hurricane and surge. But clearly that is some of what they are concerned about is storm events where they can deploy ahead of time when an unknown event is coming. To follow up after David Ihrie, users are the most creative innovators. One of the more recent use cases with wildland fire sensors was a planned burn or a prescribed burn where one of the performers deployed sensors with a county in Colorado for a prescribed burn just to get some data. They left the sensors there overnight after the fire suppression was performed by the fire department.

Later that night, they got triggered on smoke alerts and they actually notified the fire department an hour before the first 911 call that there was a spark up where it went from smolder to ignition.

So they were able to redeploy the fire department to suppress it. We are finding more and more use cases. Again, it is the creativeness of the users that is really intriguing. We have got a variety of use cases we never planned on for the flood sensors, and now finding more with the fire sensors as well.

David Ihrie:

Following up on the fire sensors, another recent use case that came to light from one of our fire colleagues was after a small wildfire in an area. Often, they need to deploy people and equipment for the next day or two to make sure it does not flare up again. So the idea was to rapidly deploy a couple of these wildfire sensors, not to detect initial ignition, but to check and help make sure that there is no flare up afterwards.

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Georgette Hlepas:

Most of the USACE folks using these sensors are testing in different environments and seeing how they behave and how they react. The great purpose of these is quick deployable when you need something right away and everyone is pretty excited for that use case. We've predetermined, preinstalled these in locations just to see how easy they are to install and how effective they are in different environments, different temperatures, etc. We covered a lot of that in our presentation, but the vast majority of folks agreed that in an emergency this is what we can quickly deploy.

Russel Lotspeich:

We have had what we call a rapid deployment gauge program pretty much since Hurricane Katrina, where we recognized the need to either put out additional monitoring stations during an event. It was primarily focused at coastal events that point in time, but we've also evolved. Now, if a gauge is going to get flooded out due to a flood, were putting these systems out in advance of that happening to maintain data continuity during the event, especially at forecast points. How those systems have been developed in the past are not very cheap. They are not very easy to install. So, we have been looking at ways to improve on those. We are targeting the Intellisense sensor, as well as some other technologies that are out there, for that purpose, as well as potential fixed continuous monitoring. But certainly, the rapid opportunistic deployment of sensors for various different applications is certainly on our map.

Question:

David, you had a couple of slides that did a good job of talking about the question of data sharing and data ownership, as well as the security aspect of using the sensors and sharing the data. Could I get some comments from the other presenters about how that is being handled in your organizations?

Jeff Booth:

So I can answer for S&T. The unique thing about the Science and Technology Directorate is that we dont own the mission. We are the science edge for identifying gaps in the mission and then applying the technology. So from a data sharing standpoint, we aren't the ones that deploy the sensors or operate them. We're basically trying to find the technology to help the user. So from my standpoint it's not that big of an issue for my mission area.

Question:

Then my question to you Jeff would be: what technology best supports the data security and the data sharing? Are you doing research on that?

Jeff Booth:

David alluded to an effort we're doing right now with the Geological Survey on Cyber IoT security issues. In this case we'll use the Stafford County testbed and look at the flood and fire sensors for cyber vulnerabilities. There's a lot of sensors that are readily deployed because of their price points, but they introduce vulnerabilities for networks. So USGS and DHS have been 3-80

discussing some of the vulnerabilities with sensor deployments. We have a kick off meeting this week on that effort to look at some of the cyber vulnerabilities for those sensors.

Russel Lotspeich:

I'm sending a link in the chat (https://www.fedramp.gov). Data sharing, access to data, and data ownership have always been a big issue for the USGS to move forward with the use of any third party data services. The key is this Fedramp program and having fully documented, embedded APIs. We're still working through this. We're also looking at zero trust architecture that David mentioned. We have other cyber security projects that are underway looking at this exact question. How do we get data from these IoT based sensors in a way that doesn't violate any of our federal cyber infrastructure rules. If a vendor is Fedramp certified, this currently gives us somewhat of a green light to move forward, because were moving everything into the cloud anyway. All of our database is moving to the cloud. Once everything is in the cloud, and we can have that handshake, then I think it makes things a lot easier. That has been a significant hurdle up to this point.

Georgette Hlepas:

Security has been a huge concern at the USACE. We had a lot of difficulties trying to find a good way to bring data, especially automated data, from the field into our Corps net. But once we implemented a cloud-based solution, (we have a government owned Amazon cloud system) that's enabled us to do a lot more. We do meet all the government security requirements and make the appropriate handshakes to bring data in. But that cloud-based solution has provided a lot of relief.

We also do work with folks who have to go through the Fedramp certification process, and I chuckle at that because it's a lengthy process. But if there is a third party who is Fedramp certified, it does make it a lot easier, because they have to have met all the security restraints that the DoD has.

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3.3 Day 1: Session 1C - Climate Session Chair: Elena Yegorova, NRC/RES/DRA 3.3.1 Presentation 1C-1 (KEYNOTE): Big Stories from the Historic Winter of 2020/21 Authors: David Novak, National Oceanic and Atmospheric Administration, National Weather Service (NOAA/NWS)

Speaker: David Novak 3.3.1.1 Abstract This review will highlight some of the "big stories" of the 2020-21 historic winter season, including one of the snowiest Octobers on record in the CONUS, an historic early season ice storm in Oklahoma, a December noreaster with 40 of snow in 15 hours1.736111e-4 days <br />0.00417 hours <br />2.480159e-5 weeks <br />5.7075e-6 months <br />, and most, notably, an historic and devastating February cold wave. Winter dryness over the west foreshadowed a devastating drought for the remainder of 2021. Notable events in the early part of the 21-22 season will also be reviewed. These events will be used to illustrate the impacts of extreme winter conditions on society and the national infrastructure, and the weather enterprises efforts in building public readiness for such events. Winter 2020-21 will be best known for the February cold wave - the most destructive and costly winter event to affect the United States in recorded history. The event was responsible for 172 deaths and over $20 Billion in direct losses (nearly doubling the inflation-adjusted cost of the 1993 Superstorm). This talk will review the rare meteorological circumstances of the event, which contributed to cascading failures in the power, water, and transportation infrastructure. In reviewing the events of the 2020-21 season, this presentation will also highlight successes and challenges in building industry readiness for winter weather, including new product and messaging innovations.

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3-84 3-85 3-86 3-87 3-88 3-89 3-90 3-91 3-92 3-93 3-94 3-95 3-96 3-97 3-98 3.3.2 Presentation 1C-2: Linking Arctic variability and change with extreme winter weather in the US including the Texas Freeze of February 2021 Authors: Judah Cohen*1, Laurie Agel2, Mathew Barlow2, Chaim Garfinkel3, Ian White3 1Atmospheric and Environmental Research, 2University of Massachusetts Lowell, 3Hebrew University of Jerusalem Speaker: Judah Cohen 3.3.2.1 Abstract The Arctic is warming at a rate twice the global average and severe winter weather is reported to be increasing across many heavily populated mid-latitude regions, but there isnt yet agreement on whether there is a physical link between the two phenomena. Here I will present observational analysis to show that a lesser-known stratospheric polar vortex (SPV) disruption that involves wave reflection and stretching of the SPV is linked with extreme cold across parts of Asia and North America, including the recent February 2021 Texas cold wave, and has been increasing over the satellite era (post 1980). I will also present numerical modeling experiments forced with trends in autumn snow cover and Arctic sea ice to establish a physical link between Arctic change and SPV stretching and surface impacts. This phenomenon is also active in January 2022 and if time permits, I will present on the weather of January 2022.

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3-101 3-102 3-103 3-104 3-105 3-106 3-107 3-108 3-109 3-110 3-111 3-112 3-113 3-114 3-115 3-116 3.3.3 Presentation 1C-3: 2021 U.S. Billion Dollar Weather and Climate Disasters in Historical Context including New County-Level Exposure, Vulnerability and Projected Damage Mapping Authors: Adam Smith, National Oceanic and Atmospheric Administration, National Centers for Environmental Information (NOAA/NCEI)

Speaker: Adam Smith 3.3.3.1 Abstract NOAA National Centers for Environmental Information (NCEI) released the final update to its 2021 billion-dollar disaster report (www.ncdc.noaa.gov/billions), confirming what much of the nation experienced throughout 2021: another year of frequent and costly extremes. The year came in second to 2020 in terms of number of disasters (20 versus

22) and third in total costs (behind 2017 and 2005), with a price tag of $145 billion. The events included: 1 winter storm/cold wave event (focused across the deep south and Texas); 1 wildfire event (combined impacts of wildfires across Arizona, California, Colorado, Idaho, Montana, Oregon and Washington); 1 drought and heat wave event (summer/fall across western U.S.); 2 flood events (in California and Louisiana); 3 tornado outbreaks (including the December tornado outbreaks); 4 tropical cyclones (Elsa, Fred, Ida and Nicholas); and 8 severe weather events (across many parts of the country, including the December Midwest derecho). The costliest 2021 events were Hurricane Ida ($75 billion), the mid-February Winter Storm / Cold Wave

($24.0 billion), and the Western wildfires ($10.9 billion). Adding the 2021 events to the record that began in 1980, the U.S. has sustained 310 weather and climate disasters where the overall damage costs reached or exceeded $1 billion. The cumulative cost for these 310 events exceeds $2.15 trillion. In broader context, the total cost of U.S. billion-dollar disasters over the last 5 years (2017-2021) is $742.1 billion, with a 5-year annual cost average of $148.4 billion, both of which are new records and nearly triple the 42-year inflation adjusted annual average cost. The U.S. billion-dollar disaster damage costs over the last 10-years (2012-2021) were also historically large: at least $1.0 trillion from 142 separate billion-dollar events. It is concerning that 2021 was another year in a series of years where we had a high frequency, a high cost, and large diversity of extreme events that affect people's lives and livelihoodsconcerning because it hints that the extremely high activity of recent years is becoming the new normal. 2021 marks the seventh consecutive year (2015-21) in which 10 or more separate billion-dollar disaster events have impacted the U.S. The 1980-2021 annual average (black line) is 7.4 events (CPI-adjusted); the annual average for the most recent 5 years (2017-2021) is 17.2 events (CPI-adjusted). To better reflect multi-hazard risk - the Billion-dollar disaster site now provides a new mapping tool that provides county-level information on natural disaster hazards across the United States. This interactive NOAA mapping tool provides detailed information on a locations susceptibility to weather and climate hazards that can lead to billion-dollar disasterssuch as wildfires, floods, drought and heat waves, tornado outbreaks, and hurricanes. The tool expands upon FEMAs National Risk Index to provide a view of a locations risk for, and vulnerability to, single or multiple combinations of weather and climate hazards for every county and county-equivalent in all 50 states: https://www.ncdc.noaa.gov/billions/mapping In addition, the 2021 annual U.S. billion-dollar disaster report is available here: https://www.climate.gov/news-features/blogs/beyond-data/2021-us-billion-dollar-weather-and-climate-disasters-historical 3-117

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3-119 3-120 3-121 3-122 3-123 3-124 3-125 3-126 3-127 3-128 3-129 3-130 3-131 3-132 3-133 3.3.4 Climate Panel Discussion (Session 1C-4)

Moderator: Elena Yegorova, NRC/RES/DRA/FXHAB David Novak, National Oceanic and Atmospheric Administration, National Weather Service Judah Cohen, Atmospheric and Environmental Research Adam Smith, National Oceanic and Atmospheric Administration, National Centers for Environmental Information Question:

Adam, you mentioned that the compound extreme events can be greater than the sum of the parts, so which regions of the country are more prone to the compound extreme events and what kind of events?

Adam Smith:

A few regions of the country have really popped out in recent years and have been really persistent. One would be the Gulf of Mexico, particularly Louisiana, with tropical cyclones, heavy rainfall, flood events, severe convective storm events. Those regions and the economies have really been bombarded by so many events and that lengthens the recovery time. It makes it more difficult to regain the pre-disaster impact status of how efficient the economies and livelihoods were. Certainly that region, but also, as I mentioned in the talk, the Western States, particularly Washington, Oregon, California. There you have got this persistent drought that then links into wildfire seasons. One thing I did not mention during the talk is just the persistent and damaging effects of wildfire smoke as weeks and months pass. That impacts outdoor economies or sensitive health groups. So, you get these chain reactions of hazards and impacts. Those would be the two regions I think that are most profoundly impacted so far in recent analysis.

Question:

Adam, you discussed that the south central and southeast US are experiencing the higher costs of the billion dollar weather events. The paper that you cited is referring to the business as usual scenario - the high emissions scenario. So, should we expect this trend to continue in the changing climate?

Adam Smith:

We also want to put the RCP 4.5 in the mapping. We are working with the authors to get that down scaled to the county level like the RCP 8.5, but what you have seen the data is still the same directional trends in regard to the socioeconomic outcomes, positive or negative, across the same regions. It is just of course more profound at the high emission scenario and it is important to consider. We do not know how policy or technology is going to change over the coming decades, but these are projections that happened to really align surprisingly close to the weather and climate extremes over the last four and a half decades. So I thought that was worth mentioning.

Question:

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Judah, in the beginning you showed a figure concerning confidence and attribution of extreme weather to anthropogenic climate change. I really like that figure. It really stresses the importance of not attributing a single extreme weather event to climate change. Can you comment on that?

Judah Cohen:

There is a group that tries to attribute climate change every single weather event. There are people out there who do that. But I do not. The paper that my talk was based on was not trying to argue that winters are getting more severe or were in this cooling trend. I am really trying to argue is that kind of the orthodoxy that global warming only leads to warmer temperatures and less snowfall is an oversimplification of the impact of climate change on our weather in the United States. I try to argue that there is a thermodynamic influence: increasing greenhouse gases lead to warmer temperatures, warmer oceans especially. So there is a huge heat reservoir that can be released in the winter that leads to warmer weather and, if it is warmer, there is less chance of snow. But there's also this dynamic influence that we as scientists did not consider 10-20 years ago. the pattern of climate change is not universal or homogeneous, but it is heterogeneous and can impact the circulation of the atmosphere. My talk really focused on the polar vortex that can lead to more severe winter weather. As I showed my talk, these stretched polar vortices, where they are elongated or take some of this oval shape, are occurring more frequently. And as I showed with the clustering analysis, that extreme cold is more likely, is more probable, when you have one of these stretch polar vortex events and those are increasing. The probability of getting one of these extreme winter weather events associated with these stretch polar vortex is increasing. Again, I'm not trying to argue, that's the only factor or influence to consider. But it's something that was, I believe, ignored or neglected or just not known about how it should be taken into account of in a more complete picture of how climate change can influence our weather. I do not attribute probabilities like saying the Texas freeze was 50% more likely because of climate change or anything like that. But I do think that because these stretched polar vortex events occur more frequently now than they used to, that it does increase the odds of these severe winter weather events.

Question:

Judah, have you looked at what will happen when all this sea ice melts in the Arctic?

Judah Cohen:

Thats an interesting question. The juxtaposition of the anomalies is important. You want to create a wave, that means you cannot have the temperature change equal everywhere. If all the ice melted and the warming became almost like a donut, centered over the North Pole and pretty much the same magnitude, pretty equal cross the entire Arctic Ocean, then I think everything I described in my talk would become irrelevant pretty much. Because of all that ice melting you would have this constant warming across the whole Arctic Ocean like a donut, you would have no wave. Then again, my whole argument hinges on amplifying waves. The mechanism I am describing is really sensitive to sea ice melting in favorable or preferred regions and not throughout the entire Arctic Ocean. I am trying to argue winters are not warming as fast because we are getting this balancing or offsetting influence from the polar vortex. If all the sea ice melted, and that went away, there could be a real acceleration of winter warming.

Adam Smith:

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There does not appear to be relief on the way as a nation, in terms of protecting the infrastructure and such. This is going to become more important as we go forward, and you cannot take your ball off the winter weather hazard either. Maybe there was hope that maybe a few of these different hazard extremes would fall off [with climate change], but these extreme weather events and the increased exposure that Adam was talking about have to be taken seriously. On the front lines of the National Weather Service we are working on these extreme events every couple of weeks, it seems like. This is just something we are going to have to work into the national infrastructure.

Question:

David you mentioned that extreme weather forecasts are uncertain. What is the low hanging fruit for reducing this uncertainty?

David Novak:

There was recently a study, commissioned by Congress, called the Priorities for Weather Research Study. It was a one-year study looking at the next 10 years. The unsatisfying answer is there is no silver bullet. There is no one thing that is going to make it all better. That report mentions data assimilation, I think, 251 times. That is taking observations and putting them in a format that numerical weather prediction models can see and use well so that you have a better understanding of the initial state. And then the models can project that out into the future. So, getting the observations right and integrating that into the models is very important, but it does not stop there. Post processing, taking into account the different biases that the models have is also super important. Human forecasters understanding the different biases of the models.

Human forecasters working with public safety officials to understand their critical thresholds and providing information in a way that's actionable is also important. So, all along this value chain, we need to make improvements to really prepare for extreme weather events.

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3.4 Day 2: Session 2A - Precipitation Session Chair: Kevin Quinlan, NRC/NRR 3.4.1 Presentation 2A-1: Uncertainty in Precipitation Frequency Estimates Under Current and Future Climate Authors: Azin Al Kajbaf, Michelle Bensi, Kaye Brubaker, University of Maryland, Department of Civil and Environmental Engineering Speaker: Azin Al Kajbaf 3.4.1.1 Abstract Over the past decades, the intensity of precipitation events in the Northeast of the United States has shown an increasing trend. As climate change continues to affect the characteristics and frequency of rainfall events, it is important to account for these changes in the Intensity/Depth Duration Frequency (IDF/DDF) curves used in engineering design and planning. This study develops model-based precipitation frequency estimates under current and projected future climate in Maryland. Specifically, IDF/DDF curves for selected durations from 15 minutes to 48 hours5.555556e-4 days <br />0.0133 hours <br />7.936508e-5 weeks <br />1.8264e-5 months <br /> are developed from statistical analyses of synthetic data from the North American Regional Climate Change Assessment Program (NARCCAP) suite of models. In the NARCCAP suite, 6 regional climate models covering most of North America at a spatial resolution of 50 km are driven by different atmosphere-ocean general circulation models, for a total of 12 climate simulations, both historic and future. NARCCAP synthetic time-series are available at a 3-hour temporal resolution. Machine learning models are used to temporally downscale the NARCCAP time-series to durations as short as 15 minutes. Using the developed time-series, suites of IDF/DDF curves are developed that account for a range of modeling decisions associated with climate model selection and other statistical assumptions. The suites are then used to produce averaged IDF/DDF curves. Graphical tools are developed to comparatively assess the uncertainty associated with climate model selection and the other modeling decisions used to develop IDF/DDF curves. A particular focus is placed on understand differences in drivers of uncertainty under current and future climate conditions.

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3-139 3-140 3-141 3-142 3-143 3-144 3-145 3-146 3-147 3-148 3-149 3-150 3.4.2 Presentation 2A-2 (KEYNOTE): Gridded Surface Weather Data with Uncertainty Quantification - Daymet V4 Authors: Peter Thornton, Oak Ridge National Laboratory Speaker: Peter Thornton 3.4.2.1 Abstract Observation-based estimates of surface weather are necessary inputs for many environmental studies and assessments. When uncertainties associated with surface weather estimates can be quantified, researchers and applications specialists can make informed decisions about the utility and appropriateness of data products to meet project requirements. The purpose of the Daymet gridded daily surface weather products is to provide necessary inputs to a broad range of environmental and ecological applications, while also providing the best possible quantification of uncertainty in those products. This presentation will briefly review the history of Daymet development, and will explore the improvements in algorithm and data processing that led to the recently released Daymet v4. The cross-validation metrics for precipitation and temperature will be described, with a focus on statistics for the spatial and temporal distribution of precipitation frequency and event size distributions. The relationship between surface weather and hydrological processes relevant to flooding hazards will also be discussed.

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3-152 3-153 3-154 3-155 3-156 3-157 3-158 3-159 3-160 3-161 3-162 3-163 3.4.3 Presentation 2A-3: Utility of Weather Types to Improve Nonstationary Frequency Analysis of Extreme Precipitation Authors: Giuseppe Mascaro*, Arizona State University Speaker: Giuseppe Mascaro 3.4.3.1 Abstract Theoretical arguments suggest that extreme precipitation (EP) will increase in a warmer climate.

Climate projections and, in part, observational studies support these arguments, indicating the need to incorporate nonstationarity in EP frequency analysis. Here, a statistical framework is presented that addresses this need through changes in weather type (WT) occurrence. The framework is based on mixed populations of peak-over-threshold (POT) series of EP associated with the dominant WTs in a given region. The Poisson distribution with time-varying parameters is used to model the WT occurrence, while the Generalized Pareto distribution with constant parameters is adopted to model POT series of EP. The value of the proposed method is demonstrated by focusing on the U.S. Midwest, where it has been recently showed that the occurrence of a dominant WT related to heavy precipitation has been increasing since 1949. It is first showed that the statistical uncertainty of the nonstationary framework is comparable to a stationary approach based on the Generalized Extreme Value distribution fitted to annual precipitation maxima, often used in current engineering design. Next, historical and future climate simulations of a set of general circulation models from CMIP6 are used to quantify projected changes in EP frequency in the region, along with the associated uncertainty.

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3-166 3-167 3-168 3-169 3-170 3-171 3-172 3-173 3-174 3.4.4 Presentation 2A-4: Characteristics and Causes of Extreme Snowmelt over the Conterminous United States Author: Joshua Welty*1, Xubin Zeng2 , 1U.S. Navy Fleet Numerical Meteorology and Oceanography Center, 2University of Arizona Speaker: Joshua Welty 3.4.4.1 Abstract Snowmelt is an essential process for the health and sustenance of numerous communities and ecosystems across the globe, though it also presents potential hazards when ablation processes are exceedingly rapid. Using 4-km daily snow water equivalent, temperature, and precipitation data for three decades (1988-2017), here we provide a broad characterization of extreme snowmelt episodes over the conterminous United States in terms of magnitude, timing, and coincident synoptic weather patterns.

Larger-magnitude extreme snowmelt events usually coincide with minimal precipitation and elevated temperatures. However, certain regions, particularly mountainous regions and the northeastern United States, exhibit greater likelihood of extreme snowmelt events during pronounced rain-on-snow events. During snowmelt extremes, snowmelt rate often exceeds precipitation in many regions. Meteorological patterns and associated water vapor transport most directly connected to extreme events over different regions are classified via a machine-learning technique. Over the 30-yr study period, there is a weakly increasing trend in the frequency of extremes, though this does not necessarily signify an increase in snowmelt magnitudes.

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3-177 3-178 3-179 3-180 3-181 3-182 3-183 3-184 3-185 3.4.5 Presentation 2A-5: LIP PFHA Pilot Study Authors: Rajiv Prasad*, Arun Veeramany, Rajesh Singh, Pacific Northwest National Laboratory Speaker: Rajiv Prasad 3.4.5.1 Abstract As part of the U.S. Nuclear Regulatory Commissions (NRCs) Probabilistic Flood Hazard Assessment (PFHA) Research Program, the Pacific Northwest National Laboratory (PNNL) is currently performing a pilot study for probabilistic assessment of local intense precipitation (LIP) flood hazards at nuclear power plants (NPPs). The project includes (1) reviewing existing software packages used to perform LIP flood hazard assessments, (2) reviewing aleatory variability and epistemic uncertainty that influence LIP flood event modeling, (3) performing a LIP probabilistic flood hazard assessment (PFHA) for a hypothetical NPP site, and (4) transferring knowledge to the NRC.

PNNL has completed Tasks 1 and 2 of this project. The findings from these tasks were presented in previous PFHA Workshops. In Task 3, a PFHA was performed for a NPP site. The LIP flood model developed for the post-Fukushima flood hazard reevaluation was leveraged for this study. The LIP flood model was implemented using the FLO-2D' flood simulation software package. The model was first subjected to a sensitivity analysis to determine the major sources of uncertainty in model predictions. The flood hazards were found to be sensitive to two sources: (1) input precipitation (aleatory variability) and (2) surface roughness (epistemic uncertainty). The flood hazards did not show significant variation with respect to initial soil moisture content, saturated hydraulic conductivity, and presence of storm drains.

LIP PFHA simulations are being performed using a stratified sampling approach. The input precipitation is obtained from the National Oceanic and Atmospheric Administration (NOAA) precipitation frequency data server. Point precipitation frequency estimates for annual maximum precipitation at the site were obtained and extrapolated to an annual exceedance probability of 1x10-6. Storm temporal distributions from NOAA Atlas 14 were used to construct storms of 6, 12, 24, and 96-h durations. The relative frequencies of temporal distribution types (peak intensity in various quartiles) were preserved. The NPP sites spatial distribution of surface roughness (represented by Mannings surface roughness coefficient) were preserved. The epistemic uncertainty in surface roughness was represented by a uniform distribution of multipliers applied to the original spatial distribution.

The model runs for the PFHA simulations are being performed on PNNLs high-performance supercomputer. To this end, the FLO-2D' software was tested and modified to run under a Microsoft Windows' emulator on the Linux system. A set of Python scripts are used to sample input parameters, populate input files, perform flood simulations, collect predicted results, and estimate the flood hazard curves. The total probability theorem is applied to estimate the flood hazard curves.

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3-188 3-189 3-190 3-191 3-192 3-193 3-194 3.4.6 Precipitation Panel Discussion (Session 2A-6)

Moderator: Kevin Quinlan, NRC/NRR Azin Al Kajbaf, University of Maryland Peter Thornton, Oak Ridge National Laboratory Giuseppe Mascaro, Arizona State University Joshua Welty, U.S. Navy Fleet Numerical Meteorology and Oceanography Center Rajiv Prasad, Pacific Northwest National Laboratory (PNNL)

Question:

To what degree is the QA/QC of different data sources evaluated and accounted for in Daymet?

Peter Thornton:

For the temperature station observations, we go through a preliminary round of cross validation analysis. We have found that if a station has some questionable quality issues, it tends to stick out as an anomaly in that cross validation approach. So, we have set a pretty generous threshold and we will throw out a station if it exceeds mean absolute error or bias issues in that preliminary cross validation. That ends up being a small fraction of stations that get rejected that way, like less than 1%. Wed like to do something similar for precipitation, but there's so much variability and the daily mean absolute error rates are pretty high for individual precipitation events, which I think anybody familiar with this business is going to understand. So it's been hard to define what those statistics might look like. If you look in our paper, I showed this map of the precipitation mean absolute error as a Thiessen Polygon sort of approach for each station.

There are stations even in the heavily instrumented regions in the US that stick out as having particularly high mean absolute error. We have not yet tried to go in and identify those stations and their particular problems. I'm sure that there are some quality issues with individual stations that, NCEI, hasn't found yet that we might be able to identify that way. We haven't gone through that level of analysis yet. We do summarize our statistics by network and so we can see, on average, whether the different networks are providing absolute errors that are higher or lower.

That's complicated for precipitation as well, because snow observations are just inherently more uncertain.

Question:

How does the Daymet interpolation method for precipitation relate to PRISM?

Peter Thornton:

The Daymet and PRISM methods have both in the literature and in use widely in the community for a long time. They're fundamentally different, and I think there's real value in having both of those methods out there and in use. The PRISM stands for precipitation regressions on independent slopes, and they tend to have an a priori clustering of the observations on topographic facets. They get some real value out of doing that. We, on the other hand, have this Gaussian kernel filtered approach that includes the X-,Y-, and Z-dimension for the 3D regression that gives us a similar kind of answer. A lot of different analysis have shown that there's a lot of similarity between the two approaches. But there are definitely places with extreme precipitation gradients, in particular along the crest of the Cascades, where PRISM is doing a better job. And there are other places where various analyses have shown that the 3-195

Daymet approach is doing better. So, it is kind of a mixed bag there. But I think there is real value in having both approaches out in the community.

Question:

Joshua, for the extreme snow melt was a theoretical maximum melt determined? It would be very interesting to see how close some of those maximum SWE reductions are to a maximum limit.

Joshua Welty:

The simple answer is no, we didn't. I have relatively strong confidence that anywhere approaching the theoretical maximum limit is probably somewhere in the Cascades. If you look at the simple maps we made, a lot of the largest delta SWE magnitudes were generally in the Pacific Northwest, maybe Cascades. That would be the place to start. But no, we didn't identify theoretical maximum limit based on our observational study. But I appreciate the question, that would be really interesting to look at.

Question:

Rajiv, was there any consideration for separating the precipitation aleatory and epistemic uncertainty in the model?

Rajiv Prasad:

A short answer is no. We are only looking at NOAA Atlas 14, for better or worse, for now. But there are epistemic uncertainties related to precipitation. NOAA Atlas 14 basically looks at model parameter estimation errors only. You could extend that in a more comprehensive precipitation frequency analysis that looks at alternative models. For example, you could include alternative statistical distributions that fit extreme precipitation data and then try to look at those in collection as part of the epistemic uncertainty. You could bring that in. Because we are limiting the analysis scope to just the flood at the moment, we did not look at that.

Question:

Regarding precipitation estimates to drive flood hazard assessment modeling, there are several choices: (1) statistical analysis of historical information; (2) mechanistic synthetic approaches such as numerical weather prediction or climate models; and (3) statistical synthetic approaches such as point or multipoint weather generators. What are the strengths and weaknesses of each approach?

Rajiv Prasad:

The way we approach it right now, at least in this project, is to look at NOAA Atlas 14, extrapolated. That is not really satisfactory because NOAA Atlas 14 pretty explicitly says do not do that. Another thing with historical information is that we are, at least in the U.S., limited by record lengths. You can get around that by doing regionalized analysis. The question becomes do we rely on a regional analysis? And how do we translate that back to, at least in the case that we are doing, really, local scale modeling? Are we losing anything in that sense? If we do regionalization, do we lose local features? And how much confidence do we have in those approaches? Synthetic approaches, in terms of weather generators and things like those are 3-196

becoming more popular. We did review a few of them in our earlier reports. They could be a good approach to get to some of those things. Until we actually do an intercomparison of all of these data sources, I dont know. Maybe putting together a flood model and then try to evaluate the predictions from each of those for sites or watersheds where all of these [precipitation estimates] are available might be a good way of seeing what the strengths and weaknesses might be.

Azin Al Kajbaf:

I just wanted to add that with the historical information there are a lot of challenges. In my work there were a lot of missing data. I think each of the things that you have mentioned have their own weaknesses and challenges to work with. With the historical information there is this uncertainty due to missing data or uncertainty that can come from other sources such as the problems with recordings and things like that. Also, the synthetic models are associated with other sources of uncertainty because they are simplifications of natural processes. So, my opinion is that there are strengths and weaknesses to each one and it should be looked at comprehensively to decide in what situation which one is better to work with based on the limitations that we have.

Question:

What is the latency of the Daymet data? How quickly after the valid date/time is it available? Are the different versions made clear?

Peter Thornton:

Historically we've done this annually and it's taken a few months after the end of the year to get it updated. We've recently moved to a monthly experimental low latency data product which is bringing in updates from NCEI GHCNd dataset monthly and turning that around within, usually, a week of the end of the month. A good question about the marking of those changes in the data set. I might get the details here slightly wrong, but typically, we're storing each of those monthly updates so you can go back and see individual months and then at the end of the year we do a complete reprocessing of the entire year and do an update that would be marked as an extension of the main annual time series data set. So yes, in short, you can track that but there's certainly a lot more iterations with those monthly latency updates.

Question:

Joshua, could one take a climate model or an ensemble of models and using your methods develop future SWE maps? And what would be one of the major challenges to do this?

Joshua Welty:

Presumably, yes. Our approach is flexible, so as long as you have a large enough set of inputs, on the order of maybe 1000+ maps, to train the model this is conceivably an option. I think another benefit of the approach is obviously with self-organizing maps. There's some flexibility in that you can try different number of inputs, different neighborhood functions. You can use 500-millibar heights or 500-millibar height anomalies. So, I think the simple answer to the question is yes. I think the main challenge would be how accurate is the model or suite of models you choose. But I think to answer the question is, conceivably, yes. It's a relatively flexible approach, so that would be the hope.

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Question:

Rajiv, there was a question that came in during your presentation about Mannings coefficient and has there been any thought to how that may change with the flood depth, and how that may impact your results?

Rajiv Prasad:

The short answer, when you think about it mechanistically and hydraulically, is yes it can. There are ways in which FLO-2D actually deals with it. They have some empirical ways of adjusting Manning's n when that happens, but I would really like to have a better theoretical understanding of it. The other thing that I haven't seen done, particularly at these local scales industrial Sites, is that you can have the water surface butt up against building walls, etc. So the wetted area as well as the friction on the walls might change, depending on where you are getting inundation. So yes, I think that can be something that we should think about. Surface roughness in this case really applies to all surfaces that the water touches. How do we deal with it? For now, the flood models are implemented in terms the momentum equation formulation that uses Mannings n. Could it be better, or at least can we think about calibrating it better?

Yes, we could, but the challenge there is where do you get datasets that allow you to come up with some form of either calibration to look at your site or understanding theoretically how some of these resistance to flow changes might happen? So open question, good question. I don't have a great answer for that.

3.5 Day 2: Session 2B - Riverine Flooding Session Chair: Joseph Kanney, NRC/RES 3.5.1 Presentation 2B-1 (KEYNOTE): Flood Typing and Application to Mixed Population Flood Frequency Analysis: An Interagency Collaborative Effort Authors: Nancy Barth*1, Michael Bartles2, John England2, Jory Hecht1, Gregory Karlovits2, William Lehman2; 1U.S. Geological Survey (USGS), 2U.S. Army Corps of Engineers (USACE)

Speaker: Nancy Barth 3.5.1.1 Abstract An improved understanding of the frequency and magnitude of floods is critical for the design of transportation and water-conveyance structures as well as insurance studies and floodplain management. Methods for estimating annual exceedance probabilities (AEPs) (or return intervals) in the United States were recently updated in Bulletin 17C.

These methods assume homogeneous flood distributions but acknowledge that floods at a given location can be generated by multiple causal mechanisms, such as snowmelt, intense convective rainfall events, or tropical cyclones, representing a mixed population. Mixed population flood events may not only impact the fit of the flood frequency curve in the range of the observed floods but may also impact the quality of AEP estimates in the upper tail of the flood frequency distribution. The Future Studies section in Bulletin 17C acknowledges shortcomings in the handling of mixed-population 3-198

datasets and highlights the need for additional studies before guidance for conducting mixed-population flood frequency analysis can be confidently developed. Classification of individual events by flood generating mechanisms, or flood type classification, might enable a mixed population analysis. The flood type classifications can be defined in terms of both proximal atmospheric causal mechanisms, such as different storm types, as well as antecedent watershed conditions, such as soil moisture storage and snowpack water content. Currently, the largest national database of annual peak flows, the U.S. Geological Survey (USGS) National Water Information System (NWIS) database, contains little information about the flood type classification for each annual peak-flow event. The U.S. Army Corps of Engineers (USACE) and USGS have begun a multi-year collaborative effort to develop methods for efficiently categorizing flood data stored in NWIS by causal mechanisms. In addition, this collaboration includes the design of a database framework for storing peaks-over-threshold (POT) events. This would ensure that all floods taking place in years with multiple large flood events would also be recorded in the database, including information on the mechanisms that generated them. The POT data could be used for mixed population analyses that includes frequency, duration, and volume.

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3.5.1.2 Presentation (ADAMS Accession No. ML22061A122) 3-200

3-201 3-202 3-203 3-204 3-205 3-206 3-207 3-208 3-209 3-210 3-211 3-212 3-213 3-214 3.5.2 Presentation 2B-2: Applying Stochastic Weather Generation and Continuous Hydrologic Simulation for Probabilistic Flood Hazard Assessments Authors: Joe Bellini*1, Bill Kappel2, Dennis Johnson2, Doug Hultstrand2; 1Aterra Solutions, 2Applied Weather Associates Speaker: Joe Bellini 3.5.2.1 Abstract Applied Weather Associates teamed with Aterra Solutions to complete a stochastic weather modeling study to provide long term meteorological realization for hydrologic modeling, flood frequency analysis, and flood recurrence interval analyses. This utilized a multisite stochastic modeling approach using daily observations of precipitation, temperatures, and snow water equivalent (SWE) from 49 sites in the upper Midwest through the Multi-site Auto-regressive Weather GENerator (RMAWGEN)) framework. Stochastic weather generators are statistical models that simulate realistic or plausible random sequences of atmospheric variables.

Resulting sequences provide meteorological realizations that can be used for risk evaluations and reliability assessments for various systems such as dams and nuclear generating facilities.

Observed precipitation and temperature records were used to calibrate RMAWGEN for the 1949-2019 period. Validation was performed on the calibration period data. Results demonstrate that the model was able to capture spatiotemporal characteristics of observed precipitation and temperature. The model generated 12 iterations of 1,000-years of daily weather sequences of precipitation, temperatures, and SWE. Climate change projections were applied using RCP 4.5 and 8.5 to generate 12 iterations of 1,000-years of future sequences of precipitation, temperatures, and SWE. Weather outputs were used in a continuous simulation hydrologic model built using HEC-HMS. This was calibrated against 3 different years of daily flow data at locations throughout an 88,000 mi2 basin. Normal, wet, and dry years were used for calibration. The final calibrated model was used to simulate runoff for each 12x1000-year simulations, including the three climate change projections. Uncertainty analyses, using a Monte-Carlo framework within HMS, bracketed potential outflow possibilities based on variability in hydrologic inputs identified in the calibration phase. Annual maximum flows were used to characterize probabilistic flood hazards (to as low as a 10-6 annual exceedance probability),

considering a wide range of event parameters such as snow accumulation, spring melt patterns, and rainfall. Results will be used in safety assessments and seasonal flood operation planning.

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3.5.2.2 Presentation (ADAMS Accession No. ML22061A121) 3-216

3-217 3-218 3-219 3-220 3-221 3-222 3-223 3-224 3-225 3-226 3-227 3.5.3 Presentation 2B-3: IWRSS Flood Inundation Mapping for Flood Response Authors: Robert Mason*1, Julia Prokopec*1, Adam Barker*2, Cory Winders*3, Darone Jones*4 1U.S. Geological Survey, 2Federal Emergency Management Agency, 3U.S. Army Corps of Engineers, 4National Weather Service Speaker: Julia Prokopec 3.5.3.1 Abstract Traditionally, flood predictions and forecasts have focused on communicating near-term outlooks for flood-peak stages (water-elevations) and flow rates. But modern geospatial and hydrodynamic modeling techniques permit the rapid conversion of such information into flood inundation maps (FIMs) that communicate fair more effectively the expected area extent and timing of a flood and the physical resources and community populations that will be impacted.

Many agencies at the Federal, State, and local levels have evolved these techniques such they are now deployed routinely, and the resulting maps distributed to emergency management agencies.

Sometimes a diversity of approaches, assumptions, or inputs made by the modelers can result in divergent maps that can confuse users. In 2018, the Integrated Water Resources Science and Services (IWRSS; a consortium of the Federal Emergency Management Agency (FEMA),

National Ocean and Atmospheric Administration (NOAA), U.S. Army Corps of Engineers (USACE), and the U.S. Geological Survey (USGS)) was tasked with developing a process for coordinating Federal, event-based FIMs and establishing an authoritative source for communication of the coordinated FIM to FEMA. The process was codified in a draft playbook that has been exercised and further developed through several recent floods. This presentation will describe the iFIM vision, the evolving playbook, agency roles and products, and efforts to develop a truly integrated and authoritative FIM for the Federal emergency management community.

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3.5.3.2 Presentation (ML22061A120) 3-229

3-230 3-231 3-232 3-233 3-234 3-235 3-236 3-237 3.5.4 Presentation 2B-4: Using HEC-WAT for NRC's PFHA Process Authors: William Lehman*, Gregory Karlovits, David Ho, Leila Ostadrahimi, Brennan Beam, Sara O'Connell, Julia Slaughter U.S. Army Corps of Engineers Hydrologic Engineering Center Speaker: William Lehman 3.5.4.1 Abstract This presentation describes the application of the Nuclear Regulatory Commissions (NRC) Probabilistic Flood Hazard Analysis (PFHA) process through the Hydrologic Engineering Center Watershed Analysis Tool (HEC-WAT). PFHA provides a quantitative relation between of the probability of occurrence (or frequency) and magnitude for various flood hazards. The modeling framework includes hydrologic processes such as infiltration, runoff, discharge routing, reservoir operations, and near-field hydraulic processes. A comprehensive flood hazard assessment comprised probabilistic modeling of individual processes as well as composite modeling of coincident and/or correlated processes. The result is computed flood hazard frequency curves described with uncertainty bounds at various sites across the watershed for many informative variables. HEC-WAT was applied to a pilot watershed to provide a concrete demonstration of methodology to produce the outputs required for PFHA. This pilot project is focused on inland flood riverine flooding mechanisms including upstream dam breaching that may impact Nuclear Power Plants (NPPs).

3.5.4.2 Presentation (ADAMS Accession No. ML22061A119) 3-238

3-239 3-240 3-241 3-242 3-243 3-244 3-245 3-246 3-247 3-248 3-249 3-250 3-251 3.5.5 Riverine Panel Discussion (Session 2B-5)

Moderator: Joseph Kanney, NRC/RES/DRA/FXHAB Nancy Barth, U.S. Geological Survey Joe Bellini, Aterra Solutions Robert Mason, U.S. Geological Survey William Lehman, U.S. Army Corps of Engineers Bill Kappel, Doug Hulstrand, Applied Weather Associates Question:

Nancy, it seemed that from the scope of your presentation that the combinatorics could get out of hand very quickly when you start to combine nonstationarity and the idea of these mixed types. The mixed type could be from different types of storms or it could be coming from changes in the in the watershed over time even if the storm types are the same over a 40-year period. And if the watershed is changing, then you would also need some sort of a mixed model for that. How do you to prioritize or have some sort of target on the number of different mixed types that you think you might tackle?

Nancy Barth:

What we're trying to do is address the question from the highest-level flood attribution for causation. So, we look at those peaks that are directly attributed to atmospheric rivers or snowmelt, the more common primary attributions rather than getting muddied into challenges in the watershed changes. We are trying to keep to more primary causes, more attributable to actual storm typing to get to flood type attributions.

Question:

This question is for Joe Bellini and colleagues. What steps were taken to account for extremes?

For example, such as physically possible storms that weren't seen in the record that was used for calibration. There are certainly plausible physical mechanisms for generating an extreme storm, but it just wasn't there on the record. What sort of steps were taken to account for things like that in the weather generator?

Doug Hultstrand:

To account for events that are not in the observed data itself, we rely on the probabilistic side in that we can sample a storm event, look at its rarity and artificially insert that into the time series.

The methodology we follow is the SCHADEX methodology, which is common in European countries, where you're taking storms that have occurred in and around the basin that are considered to be transpositionable, and transposing those storms based on a frequency realm from where they occurred to the new storm center location. So that's the method. We ultimately selected several big events with 1000+ year return periods, just south of the basins in the Canadian Rockies and transpositioned them just to the north for several locations.

And when I say transposition, we are transposing the storm in probability realm. Then we can artificially insert that precipitation timeseries into the observed timeseries for the proper season.

In this case, they are all June-time events. You can insert those and use the calibrated stochastic model to simulate those upper tail frequency precipitation events. There it becomes an issue. How do you insert?

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Bill Kappel:

The bottom line is that it is a plug and play. Of course there are a lot subjective choices that are made in what storms to move, what values to replace, and where in the time frame to replace.

But in the end, its basically replacing an observed event with a much larger event and rerun the time series with that the larger event as if it had occurred there versus what was observed.

Question:

This question is for all panelists. Have you ever been able to confirm the predicted extreme statistical events by some other independent data?

Doug Hulstrand:

In the realm of looking at extreme events, we do an independent analysis when we're trying to quantify the annual exceedance probability of PMP. We do the regional frequency analysis, which is one independent method, and the second is a storm stochastic storm transposition which is a different method. We do these independently and see how the two methods kind of come together to estimate that probability or exceedance probability.

Joe Bellini:

This may address part of the question, at least for the study we did. As I mentioned in the presentation, we did look at an observed annual maximum flows. We developed the frequency curve using Log-Pearson III, sing observed data, not just stochastic data for higher probability frequencies. That might help address that question.

Question:

Any perspective on the use of paleoflood information in the types of flooding analysis that you're doing?

Joe Bellini:

For our study, prior to the stochastic analysis, we used the Bulletin 17 C method. There were some regional paleoflood studies. We incorporated them as basically historical floods. You set the flow ranges and apply the expected moment algorithm to add to the systematic record. In that case, we had about 150 years of systematic record, and we had some additional historical flood records. We used some regional paleoflood data to set some maximum flows for specific periods of time (approximately 600-1200 CE and 1200-1800 CE), before the historic and systematic record began. That informed the statistical analysis of the annual maximum series, which was independently compared to the stochastic analysis we presented on.

Question:

If someone looks at the different talks in this session in terms of riverine flooding, you notice that there are basically three broad use cases: (1) forecasting; (2) real time event response; and (3) prediction and design. Is there any way that we could sort of integrate these together and have a common set of tools that could be used for all these different use cases? Could you see a 3-253

community model that could address all these uses? Something analogous to the Weather Research and Forecasting (WRF) model developed by the atmospheric sciences community.

Robert Mason:

I don't know that we have a community model that addresses all of the uses, but increasingly we're seeing more and more powerful models that can address multiple uses. It's entirely possible now to do simulations that are for design as well as prediction, and to really use essentially the same chassis, the same elements of the model may be run with slightly different data, but the models are very much the same. We're having conversations within IWRSS about trying to integrate agency models and to do that from two perspectives: one being sort of a design and the other being sort of focus on operations/ forecasting.

William Lehman:

I believe that the community will prevail at some point, and I hope and pray for that day. But you know, everybody has got their turf wars that they live and breathe by. I think that there will always be room for innovation, which means there might be branches and what we need to figure out is how to merge the trunk. The Army Corps of Engineers Watershed Analysis Tool (WAT) and the Corps Water Management System (CWMS) share a common framework for how we sequence events with the WAT being more for planning/design like you were saying and CWMS being more for the real-time response. One thing I will say though is that models are as good as the project that they're built for the reason that they are built. The level of scrutiny on a response or a map to help someone evacuate might be different than a map that is one of 300,000 in a very large uncertainty analysis. What I find is that the scale associated with getting enough events to describe uncertainty sufficiently may be different than getting a really good map for an evacuation. So, to some degree, the models/software themselves may be the same, but the resolution that the model is developed at may differ between applications.

Bill Kappel:

This is always something the public private partnership and being able to utilize and leverage the great work that each these individual agencies and private companies are doing and try to consolidate that into one usable format would be ideal. Its always a matter of how its done.

Everybody has different objectives and agendas, but there certainly should be an overarching framework that can consolidate all this into one aspect and usability. This is a multi-agency thing, right? You have meteorology, climatology and hydrology. All these different aspects trying to solve the same types of problems from different angles. It seems obvious that there should be some kind of overarching, all-encompassing aspect to put all these pieces together and to make them usable for everybody.

Joe Bellini:

In the private sector we've had a variety of entities that we support. It ranges from the dam safety community, to dam owners, to communities with levies, to insurers. Both forecasting and combined tools that can increase the ability for forecasting.

When we write an emergency action plan (EAP) or emergency operation plan for a levee system for operating gates and closure structure and so forth, we do link those plans to tools that are available from the federal agencies. And then also closing the gap between pluvial and fluvial (we work mostly in the realm of interior flooding), there's not a lot of tools available for localized flooding. So there are gaps to be filled, not only for design work, but also for helping 3-254

communities to improve their forecasting ability to take action well in advance of a flood occurring.

Bill Kappel:

We've obviously had lots of conversations and the conversations continue about how to make these things integrate. There's so much work being done, and in so many different areas.

Sometimes there's overlap. Sometimes the work is done in silos where were doing something and somebody else is doing something, and they might not know about it, and vice versa. If there was collaboration between those processes, it would be a much better outcome. For example, just a couple weeks ago during the American Meteorological Society meeting, I was listening to a presentation on some great work being done by UCAR on numerical modeling of PMP estimates and how to bring those together with the deterministic side and the things that have been done over the years by the Weather Service and the Corps of Engineers and private industry. It always comes down to having some leadership and the right people to recognize all the pieces that are out there and figuring out a way to put all the pieces together in a way that's most efficient and usable for the widest range of communities, versus a bunch of work being done individually, and not leveraging off of each otherwhere it makes sense. I don't know the answer to that, but certainly we all recognize it and we have to figure out a way to put those pieces together.

Robert Mason:

I just wanted to mention that even on Monday we had a discussion with NOAA about coupling of our models. The PowerPoint was titled Coupling Our Models and the point of the discussion was not just to say we'll take NWS rainfall and add it to a USGS model.It was that we will take an element of a particular model and try to put that element, perhaps with another element from another agency or yet another supplier. I don't know that we will have a single model, but I think that we will see greater integration of them as we go forward.

Moderator:

So, if I paraphrase your answer to say that maybe interoperability is a more reasonable or maybe a preferable goal than a community model. Would that be a fair statement?

Robert Mason:

I won't say that it's preferable, but I say that it's achievable.

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3.6 Day 3: Session 3A - Poster Session 3.6.1 Poster 3A-1: Flood Fragility Function Methodology for a Conceptual Nuclear Power Plant Authors: Joy Shen*, Michelle Bensi, Mohammad Modarres; University of Maryland Presenter: Joy Shen Abstract: Fragility functions quantify the probability that a structure or component will be damaged or fail at a certain intensity measure (IM) of hazard severity (e.g., flood height). Due to limited experience in external flooding probabilistic risk assessment (PRA) in the nuclear energy sector, flooding fragility function development has not been a practical priority for nuclear power plants (NPPs). As a result, there is a gap in the literature related to flooding fragility assessments to support NPP PRAs. However, recent flooding events at Fukushima Daiichi NPP, Fort Calhoun NPP, and other facilities have highlighted the importance of advancing this field. The poster will present a conceptual, illustrative example of an emergency diesel generator (EDG) building with flood barrier components that act as protective measures during an external flood. In addition, this poster will include a brief description of the fragility function development for flood barriers such as penetration seals, doors, floodgates, and louver covers.

The data gathered from a literature review and the conservative deterministic failure margin (CDFM) method is used to derive fragility parameters. This information is then used to determine damage states and their associated leakage rate as the external flood enters the building as a result of varying degrees of flood protection damage. Leakage rates and internal flood heights are generated from illustrative geometry and representative hazard characteristics.

Poster Material (ML22061A118):

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3-257 3-258 3-259 3-260 3.6.2 Poster 3A-2: Quantifying Uncertainty in Hurricane Warning Times to Inform Coastal Hazard PRA Authors: Somayeh Mohammadi*, Michelle Bensi; University of Maryland Presenter: Somayeh Mohammadi Abstract:

Nuclear power facilities and other critical infrastructure are often located in coastal regions exposed to the effects of tropical cyclones (e.g., hurricanes and tropical storms).

These facilities may employ response strategies that involve actions to install temporary protection or mitigation features. The effectiveness of response strategies may be adversely affected by hardware failures. In addition, there is also a possibility that actions will be unsuccessful due to delayed organizational decision-making, human errors, and differences between the predicted and experienced coastal hazard characteristics. Accurate coastal hazard probabilistic risk assessments for critical infrastructure such as nuclear power facilities must include human reliability assessments that quantify the probabilities that protection and mitigation actions will be unsuccessful. These probabilities depend on the information available to support decisions and the environmental conditions under which actions are performed. A critical input to the human reliability assessment is the time available to perform actions.

However, this estimated time is subject to uncertainty due to uncertainty in hurricane and tropical storm forecasts. This study seeks to quantify the uncertainty in the time available to execute actions that are triggered based on storm advisories. Uncertainty assessments are developed using NOAA GIS datasets related to advisory/forecast and observed storm track data from 2012 to 2020. Specifically, the differences between advisory forecasted track data (e.g., predicted landfall locations and times) at various time points are compared against the final observed track. This provides insights into the likelihood that the time available to perform proceduralized actions triggered by advisory information will be longer or shorter than assumed.

Poster Material (ML22061A117):

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3-262 3-263 3-264 3-265 3-266 3-267 3.6.3 Poster 3A-3: HEC-WAT Interface and Set Up for the Trinity River PFHA Pilot Project Author: David Ho*, William Lehman, Brennan Beam, Sara OConnell, Leila Ostadrahimi U.S. Army Corps of Engineers, Hydrologic Engineering Center Presenter: David Ho Abstract: The Nuclear Regulatory Commissions (NRC) Probabilistic Flood Hazard Analysis (PFHA) utilized Hydrologic Engineering Center Watershed Analysis Tool (HEC-WAT) to provide a quantitative relationship between of the probability of occurrence (or frequency) and magnitude for various flood hazards. HEC-WAT was applied to the Trinity River watershed to demonstrate a method of producing stochastic outputs required for the PFHA. The modeling effort required a number of different applications or plugins to perform the PFHA analysis. This poster will show the Trinity River HEC-WAT interface, how the project was set-up for the modeling, which plugins were added, and how the model order was selected.

Poster Material (ML22061A116):

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3-269 3-270 3-271 3-272 3.6.4 Poster 3A-4: Riverine Flooding HEC-WAT Pilot Project Dam Break Modeling Authors: Brennan Beam*, William Lehman, Sara OConnell, David Ho, Leila Ostadrahimi U.S. Army Corps of Engineers, Hydrologic Engineering Center Presenter: Brennan Beam Abstract:

This poster describes how the Hydrologic Engineering Center's Watershed Analysis Tool (HEC-WAT) is being used to include dam failure in their probabilistic flood hazard assessment (PFHA) process. The technical details associated with viewing a system wide dam failure for a single event using HEC-RAS and HEC-ResSim is the primary focus of the poster.

Poster Material (ML22061A115):

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3-274 3-275 3-276 3-277 3-278 3-279 3-280 3-281 3-282 3.6.5 Poster 3A-5: Flooding from Below - The Groundwater Emergence Hazard Author: Kevin M. Befus*1, Patrick L. Barnard2, Peter W. Swarzenski2, Clifford Voss2 1University of Arkansas, 2U.S. Geological Survey Presenter: Kevin M. Befus Abstract:

Shallow groundwater levels create hidden flood hazards via groundwater emergence. In such areas, thin vadose zones could accentuate compound flooding events, and rising water tables could reach the ground surface and flood low lying areas. Even without groundwater emergence, a shoaling groundwater table can reduce the effectiveness and lifespans of coastal urban and rural infrastructure, such as storm drains, shoreline armoring, and other buried assets, as well as potentially remobilize soil contaminants. Wetter regional climate, more frequent and intense storms, focused urbanization and projected sea-level rise are just a few processes that will likely expand future zones of groundwater emergence in some regions.

Downstream coastal communities and associated infrastructure are most at risk to the compounded effects of prolonged or chronic groundwater emergence. Numerical simulations of the California coastal region illustrate the expansive extent and nuances of shoaling and groundwater emergence hazards today and predict a substantial increase in groundwater-flooded areas with future sea-level rise. Low-lying areas are most vulnerable to flooding hazards from below due to groundwater emergence, as well as to episodic marine overland flooding and quasi-permanent inundation. Overall, societal exposure to shallow and emergent groundwater with rising sea levels was projected to be 6-9 times higher than overland flooding by the end of the century for coastal California. Thus, responsive flood protection policy and infrastructure should account for not only marine overland flooding but also for groundwater flooding from below. Ongoing work will extend these simulations to coastal aquifers across the southeastern United States.

Poster Material (ML22061A114):

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3-284 3-285 3-286 3-287 3-288 3-289 3-290 3.6.6 Poster 3A-6: External Flooding PRA Guidance Author: Marko Randelovic*1, Raymond Schneider*2 1Electric Power Research Institute (EPRI), 2Westinghouse Company Presenter: Marko Randelovic Abstract:

EPRI is currently developing a guidance for performing an external flood PRA for use in the nuclear industry. The guidance establishes a structured framework for treating the spectrum of external flood hazards and provides background materials and examples for the PRA analyst to use. Specifically, the project aids the PRA analyst in:

1) Defining and characterizing the external flood hazard, considering event and plant-specific issues.

2) Estimating external flood hazard frequencies.

3) Developing external flood fragility curves for flood significant Systems, Structures, and Components (SSCs).

4) Preparing an external flood event tree, including consideration of actions preparing the plant for the flood, mitigating the flood hazard, and responding to random and flood-induced failures of initial flood mitigation strategies.

Guidance is being developed to be consistent with expected requirements of the ASME/ANS PRA Standard. To facilitate understanding simple hypothetical example applications illustrate the interface with the probabilistic flood hazard assessment (PFHA), parsing the flood analysis to characteristic event frequencies and the development of various PRA flood event trees and overall quantification overall process. This guidance also includes a potential screening approach for the flood related combined/correlated hazards.

Poster Material (ML22061A113):

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3-292 3-293 3-294 3-295 3-296 3.7 Day 3: Session 3B - Coastal Flooding Session Chair: Joseph Kanney, NRC/RES/DRA 3.7.1 Presentation 3B-1: An Overview of CSTORM Model Development and Results for the South Atlantic Coastal Study (SACS)

Authors: Margaret Owensby*1, Thomas Massey1, Tyler Hesser1, Mary Bryant1, Andrew Condon2 1U.S. Army Corps of Engineers (USACE), Engineer Research and Development Center, Coastal and Hydraulics Laboratory, 2USACE Jacksonville District Speaker: Margaret Owensby 3.7.1.1 Abstract The U.S. Army Corps of Engineers (USACE) South Atlantic Division and the Engineer Research and Development Center (ERDC) have been engaged in a large, multi-year project called the South Atlantic Coastal Study (SACS). Following the precedent of other large coastal studies within the USACE, such as the North Atlantic Coastal Comprehensive Study (NACCS), the SACS study was designed to identify and assess coastal hazards risks in the domain of concern on a regional scale and to support future resilience and sustainability efforts in coastal communities. Probabilistic coastal hazards analysis using a state-of-the-art innovative statistical and probabilistic framework for the comprehensive characterization of storm climatology was applied as part of one component of this study. Modeling was performed using the high-resolution Coastal Storm Modeling System (CSTORM-MS), and advanced joint probability analysis of atmospheric forcing and primary storm responses, including associated aleatory and epistemic uncertainties, was conducted. The study was broken into three domains: 1) the southern U.S. East Coast ranging from the border of North Carolina and Virginia to the southern tip of Florida, 2) the Gulf Coast from the southern tip of Florida to the Mississippi and Louisiana state boundary, and 3) Puerto Rico and the U.S. Virgin Islands. The focus of this presentation is on the South Atlantic (SA) and Gulf of Mexico (GoM) domains, for which 1700 unique synthetic tropical storm events, 15 historical tropical storms, and 70 historical extratropical events were simulated for present-day sea level as well as two sea level rise scenarios. An overview of the CSTORM model development and validation process for the two domains will be given, along with details about the storm suite and water levels. A summary of the modeled results and their inclusion in the Coastal Hazards System (CHS) will also be presented.

3.7.1.2 Presentation (ADAMS Accession No. ML22061A112) 3-297

3-298 3-299 3-300 3-301 3-302 3-303 3-304 3-305 3-306 3-307 3-308 3-309 3-310 3-311 3-312 3.7.2 Presentation 3B-2: Compound Flood Hazard Assessment using a Bayesian Framework Somayeh Mohammadi*1, Michelle Bensi1, Shih-Chieh Kao2, Scott DeNeale2, Joseph Kanney3, Elena Yegorova3, Meredith Carr4 1Univeristy of Maryland, 2Oak Ridge National Laboratory, 3U.S. Nuclear Regulatory Commission, 4U.S. Army Corps of Engineers Engineer Research and Development Center Coastal and Hydraulics Laboratory Speaker: Somayeh Mohammadi 3.7.2.1 Abstract Compound flooding is a topic that has received high attention recently. These types of flood events are caused by the occurrence of more than one flood mechanism, such as storm surge, precipitation, and tides. Compound flood events can cause more severe impacts on societies and the built environment than flood events caused by just a single flood mechanism. In this way, a probabilistic assessment of compound flood hazards is necessary for a realistic assessment of flood hazards. This study focuses on the probabilistic assessment of compound flood hazards caused by the simultaneous occurrence of hurricane-induced surge, precipitation, tide, and antecedent river flow. A Bayesian framework is developed to include these flood drivers in the probabilistic flood hazard assessment for a case study on the Delaware River in Trenton. The inputs to this model include storm parameters (i.e., central pressure deficit, forward velocity, heading direction, radius to maximum wind and landfall location), antecedent river flow, and predicted tidal levels. A series of predictive surrogate models are developed to estimate total river discharge accounting for hurricane-driven surge, antecedent flow, and tides. The proposed model can be used to generate a probability distribution for total river discharge at the time of the storm occurrence in the study area.

Furthermore, the model can be used to generate a hazard curve representing the annual exceedance frequency of total river discharge caused by the hurricane-induced flood mechanisms mentioned earlier.

3.7.2.2 Presentation (ADAMS Accession No. ML22061A111) 3-313

3-314 3-315 3-316 3-317 3-318 3-319 3-320 3-321 3-322 3-323 3-324 3.7.3 Presentation 3B-3: Coastal Flooding PFHA Pilot Study Authors: Victor M. Gonzalez*, Meredith L. Carr, Karlie Wells, Norberto C. Nadal Caraballo U.S.

Army Corps of Engineers, Engineer Research and Development Center, Coastal and Hydraulics Laboratory (USACE/ERDC/CHL)

Speaker: Victor M. Gonzalez 3.7.3.1 Abstract Inundation due to the compound effects of storm surge and rainfall associated with coastal storms can produce widespread damage to coastal infrastructure. A coastal probabilistic flood hazard assessment (PFHA) pilot study is being conducted to demonstrate the application of PFHA to external flooding at a hypothetical nuclear power plant (NPP) location on the Lower Neches River watershed in Texas. Compound flooding hazards being assessed in this study include storm surge, astronomical tide, waves, rainfall, and coincident riverine flooding along with associated uncertainties. The assessment requires the characterization of storm climatology for tropical cyclones (TCs) using the U.S. Army Corps of Engineers (USACE) Coastal Hazards System (CHS) data based on its Probabilistic Coastal Hazard Analysis (PCHA) framework. The PCHA is a probabilistic framework for quantifying coastal storm hazards that includes storm climatology characterization, high-resolution, high-fidelity numeric atmospheric, hydrodynamic, and wave modeling, and advanced joint probability analysis of atmospheric forcing to develop storm hazard curves and uncertainty. The compound probabilistic modeling approach being implemented here incorporates rainfall within the PCHA framework though the use of a physics-based parameterized tropical cyclone rainfall (TCR) model driven by the same atmospheric forcing, allowing concurrent characterization of the compound flooding hazard and associated uncertainties.

Simulation of both coastal and riverine processes driven by TCs will be completed using hydrologic, hydraulic, and hydrodynamic models: synthetic TC rainfall will be applied to a HEC-HMS model of the Neches Watershed and the flow output routed through the inland-coastal boundary through the use of a 2D HEC-RAS model. The compound hazards will be assessed through the application of a loosely coupled HEC-RAS and ADCIRC modeling framework and quantified through the integration of the combined responses, including uncertainty. As the coupled inland and coastal models are being implemented, the impacts of several modeling options are being explored including:

precipitation-based infiltration parameters, antecedent flow conditions, precipitation in the hydraulic model, boundary condition geometry and additional runs of hydrodynamic models for multiple riverine flow conditions.

3.7.3.2 Presentation (ADAMS Accession No. ML22061A110) 3-325

3-326 3-327 3-328 3-329 3-330 3-331 3-332 3-333 3-334 3-335 3-336 3-337 3-338 3-339 3-340 3-341 3-342 3-343 3.7.4 Presentation 3B-4: Probabilistic Wave Height Hazard Assessment Method at the NPP Site Considering Storm Surge Authors: Beom-Jin Kim*, Daegi Hahm, Minkyu Kim Korea Atomic Energy Research Institute (KAERI)

Speaker: Beom-Jin Kim 3.7.4.1 Abstract Due to the influence of recent climate change, typhoon invasions of the Korean Peninsula with extreme rainfall frequently occur. Between August and September 2020, three typhoons, Bavi, Maysak, and Haishen, attack to the Korean Peninsula, and the resulting heavy rains that fell caused flood damage. As typhoons Maysak and Haishen passed east of Korea, the local nuclear power plants were automatically shut down. In order to analyze the wave height, wave period, and wave direction characteristics in the front of the nuclear power plant site, the SWAN model was built in the near sea area through nesting technique. First, based on the data presented in the Deepwater design waves report, wave height, period, and sea wind were estimated according to the return period. Second, the SWAN model was established through SMS and GIS programs based on the sea-depth data around the nuclear power plant site.

Finally, a probability distribution was applied based on the wave height data, the result of the SWAN model for each return period. Based on the result, the probabilistic wave height hazard assessment (PWHA) of the sea around the nuclear power plant site was estimated. The results of this study are expected to be the basis for the waterproofing design of nuclear power plant sites and the planning of various flood prevention measures caused by the combination of external hazard such as local intense precipitation (LIP) and storm surges.

3.7.4.2 Presentation (ADAMS Accession No. ML22061A109) 3-344

3-345 3-346 3-347 3-348 3-349 3-350 3-351 3-352 3-353 3-354 3-355 3-356 3.7.5 Presentation 3B-5: Comparative Assessment of Joint Distribution Models for Tropical Cyclone Atmospheric Parameters in Probabilistic Coastal Hazard Analysis Authors: Ziyue Liu*1, Michelle Bensi1, Meredith Carr2, Norberto Nadal-Caraballo2 1University of Maryland, 2U.S. Army Corps of Engineers Engineer Research and Development Center Coastal and Hydraulics Laboratory Speaker: Ziyue Liu 3.7.5.1 Abstract The United States Army Corps of Engineers (USACE) has developed the Probabilistic Coastal Hazard Analysis (PCHA) framework to extend and advance the joint probability method, which has been used to establish probabilistic coastal hazard curves over the past decade. The PCHA framework requires characterization of the joint distribution of tropical cyclone (TC) atmospheric parameters (i.e., central pressure deficient, forward velocity, radius of maximum wind, and heading direction). While the assumptions made in developing this joint distribution have changed over the years, the current PCHA framework uses a meta-Gaussian copula (MGC) to characterize the dependence among TC atmospheric parameters. However, the MGC has limitations associated with modeling of circular variables such as storm heading direction as well as the degree to which it can capture tail dependence. This research investigates the performance of a series of joint distribution models, including the MGC and alternative models. A particular emphasis is placed on characterizing the dependence between linear and circular variables. Specifically, a von Mises kernel function (VKF) is proposed as an alternative to the Gaussian kernel function (GKF) typically in the calculation of the directional storm recurrence rate (DSRR) representing the probability model of heading direction. This study then builds a series of joint distribution models based on assumptions ranging from independence to full dependence models that consider a range of copula models (e.g., MGC and vine copulas combining linear-circular copulas with Gaussian or Frank copulas). The sensitivity of coastal hazard curves to different joint distribution models is assessed for selected locations around New Orleans, LA (USA). The stability of hazard curves generated using an MGC assumption related to the selection of the zero-degree convention is assessed, along with a comparison of tail dependence between copula models.

3.7.5.2 Presentation (ADAMS Accession No. ML22061A108) 3-357

3-358 3-359 3-360 3-361 3-362 3-363 3-364 3-365 3-366 3-367 3-368 3.7.6 Coastal Panel Discussion (Session 3B-6)

Moderator: Joseph Kanney, NRC/RES/DRA/FXHAB Margaret Owensby, U.S. Army Corps of Engineers Somayeh Mohammadi, University of Maryland Victor Gonzalez, U.S. Army Corps of Engineers Beom-Jin Kim, Korea Atomic Energy Research Institute Ziyue Liu, University of Maryland Question:

For different applications, one might choose different balance between the use of surrogate models versus the use of high-fidelity models. What's the optimum mixture or balance for the types of coastal hazard assessments that you're involved in?

Margaret Owensby:

It really just depends on what you're trying to accomplish with the particular study. The results from the South Atlantic Coastal Study were being used to develop flood maps for different regions and identify risk over a wide regional area. Your approach to that problem would be best assessed probably with high fidelity modeling. But if you're looking at some other problem, you're probably better off using surrogate models.

Question:

Somayeh, do you see any areas in your particular study where you could benefit from a high-fidelity model?

Somayeh Mohammadi:

I should mention that if we want to know where the best balance for use of surrogate and high fidelity models is, we have a limitation because in our case we also were trying to decrease the computational effort. However, there are not always data available that we can use for training a surrogate model. We just could use it for the surge model and For example, our target variable was total river discharge and there was some interactions that could be captured with physical models between precipitation-induced river and discharge and surge. For these types of things we didn't have much data. For surrogate model we need more than 1000 data points and we didn't find this type of data for the area under study. That was one limitation in balancing our work with more surrogate model. But yes, in our work we have made some simplified assumption and were some parts of our work that for sure can be improved by using a high-fidelity model. To capture interactions between precipitation induced discharge and tides and also surge induced discharge since the flow is going different direction, I believe that we can have a very more reliable result if we use more expensive and high-fidelity models.

Victor Gonzalez:

We use surrogate modeling in PCHA to make sure we cover probability space and finely discretize the parameter space of the synthetic storms. This of course allows us to incorporate in a more rigorous way the uncertainty when we generate the hazard curves for the uncertainty.

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Even the probability mass comes from your storms without having to rely on other methods. I think another beneficial aspect of these surrogate models is on the downstream end of your analysis. Once you do a regional study and you need to do a study that is more location based.

Then you would use the surrogate models to help you reduce the number of storms that you need to use. And there are many applications that you want to apply a response-based approach. For example, in computing the response on a per-storm basis, the surrogate modeling can help a great deal. I will end by saying that in the quantification of uncertainty in our study, where we were looking at the logic tree approach to estimating epistemic uncertainty, it would not have been possible to generate as many branches in the logic tree without the use of surrogate models.

Beom-Jin Kim:

High fidelity modeling should come first. Then based on the high fidelity models, I think it is important to create and analyze a simpler model, because high fidelity models can take a long time to simulate. I think simpler models are good in terms of time.

Question:

Has anyone thought about doing a meta study to mine the entire body of simulations that are in the Coastal Hazard System (CHS)? For example to investigate different approaches for modeling the error term or to evaluate different surrogate modeling approaches. Does anyone have any thoughts about that?

Margaret Owensby:

I haven't heard of any efforts to try to use all the data as a whole. I definitely think that's something that could be useful for people to do to use all the different data from the different studies that's available on the coastal hazard system.

Victor Gonzalez:

I think that would be a good idea. I would add that the CHS has been developed across time. It was started after hurricane Katrina. Then there was the Great Lakes Study, then the North Atlantic Study. Some of these studies have evolved over time and there are some differences in the different applications. Methods have evolved over time. One effort that is going on is redoing some of the old studies to have them all apply the same methods. Then that would lend itself well to a meta-analysis type of approach.

Question:

Somayeh, do you have any thoughts about applying some of the machine learning techniques you used in your work to the CHS?

Somayeh Mohammadi:

As much as I could in my work, I tried to. use the CHS. But the critical parts of my work was simultaneous occurrence of different flood mechanism. Related to capturing those physical interaction, I couldn't take that much advantage. For or the surge model. I could.

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Question:

From the presentations and discussions on might conclude that for the compound hazard assessment perhaps we need to do more work on the rainfall.

So, for anyone who's sort of been involved in that aspect, do you have any thoughts about avenues of research that we should be looking at to improve on the rainfall model and how we incorporate it into the compound a flood hazard assessment for coastal regions?

Victor Gonzalez:

I think a first step is applying these models over a regional extent. We are starting to look at this for example, in the Texas region. But with all the issues we've encountered with bias correction and the representativeness of the model, we should probably have a good grasp first of how it applies across the several regions representative of the of the US coastline. There is more research needed in this area.

Question:

Do you think this might be an area where we may want to go to a higher fidelity model? There are some high-fidelity numerical weather prediction models used for forecasting tropical storm rainfall. That would be one more really big, computationally intensive high-fidelity model. But do you think that might be a viable approach.

Victor Gonzalez:

It could be, but the synthetic storms might be an issue, the parameterized synthetic storms. So, yes, if there are better models out there that can be linked to the synthetic storms in a reasonable way, it probably would be worthwhile to pursue.

Somayeh Mohammadi:

Based on the experience that I had in my work, precipitation effects could be from two different aspects. One is estimation of precipitation itself and the other is how precipitation is converted to runoff. For the second part, we always need distributed models for converting precipitation to runoff because we need land characteristic such as different curve numbers. I think that it is really difficult to have surrogate model for this type of distributed models which can give us runoff for precipitation based on precipitation. But the other part which is estimation of precipitation itself. One of the challenges that I had in my work was with that. I also saw that there was a gap for more refined physical based modeling. Again in this part there are two problems. One is related to developing physical models which are showing the relationship between precipitation and different parameters and the other is availability of a training database. Because in probabilistic work we usually did need a big sample of data, a database related to parameters which are showing the physical relationship between its storm parameters and precipitation. Even the database I think is not easily available and having these data sources and more developed physical models that can show the relationship will be helpful.

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3.8 Day 4: Session 4A - Duane Arnold Derecho Operational Experience Session Chair: Joseph Kanney, NRC/RES/DRA 3.8.1 Presentation 4A-1: Duane Arnold Energy Center (DAEC) Loss of Offsite Power (LOOP) Due to Derecho Authors: Terry Brandt*, Nextera Energy Speaker: Terry Brandt 3.8.1.1 Abstract This presentation will give you the initial conditions, timeline of events, and operator actions associated with the Duane Arnold Derecho Event.

3.8.1.2 Presentation (ADAMS Accession No. ML22061A107) 3-372

3-373 3-374 3-375 3-376 3-377 3-378 3.8.2 Presentation 4A-2: The NRCs Regional Response to the Duane Arnold Derecho Authors: John Hanna*, U.S. Nuclear Regulatory Commission Speaker: John Hanna 3.8.2.1 Abstract This presentation, as part of the greater panel on the Duane Arnold derecho, will address Region 3's response to the event including the aspects of immediate event response by the inspection staff, the Management Directive 8.3 event assessment and other regional actions taken. Additionally, risk insights from this event will be shared.

3.8.2.2 Presentation (ADAMS Accession No. ML22061A106) 3-379

3-380 3-381 3-382 3-383 3-384 3-385 3-386 3-387 3-388 3-389 3.8.3 Presentation 4A-3: Why the Risk of the Extended Loss of Offsite Power Was Almost a Significant Precursor?

Authors: Christopher Hunter*, U.S. Nuclear Regulatory Commission Speaker: Christopher Hunter 3.8.3.1 Abstract On August 10, 2020, a severe storm with heavy rains and very strong straight-line winds (called a derecho) resulted in an extended loss of offsite power (LOOP) at Duane Arnold Energy Center (DAEC). The National Weather Service later estimated wind speed peaks were likely near 130 mph, which resulted in extensive damage to offsite power lines and a number of plant structures including the reactor, turbine, and FLEX buildings, and nonsafety-related cooling towers. In addition, the high winds led to an ingress of debris into the essential service water that challenged the system strainers and required operator intervention to maintain adequate cooling to one of the two emergency diesel generators. This presentation will cover the important assumptions, results, and key risk insights from the accident sequencer precursor (ASP) analysis. In addition, a comparison with other recent LOOP precursors due to severe weather will show why the event at DAEC had substantially higher risk that these other events.

3.8.3.2 Presentation (ADAMS Accession No. ML22061A105) 3-390

3-391 3-392 3-393 3-394 3-395 3-396 3.8.4 Presentation 4A-4: The NRCs Response to the Duane Arnold Derecho Event using the LIC-504 Process Authors: Matthew Leech*, U.S. Nuclear Regulatory Commission Speaker: Matthew Leech 3.8.4.1 Abstract When the NRC saw that the risk of the Duane Arnold derecho event was high, the decision was made to perform a LIC-504 analysis to determine if a safety issue risk existed to other power plants in the fleet. The LIC-504 is a risk informed process that the NRC uses to disposition emergent safety issues. This presentation will discuss how the NRC evaluated the risk to a number of other power plants if they experienced a similar event, it will discuss the key insights, and recommendations from the LIC-504.

3.8.4.2 Presentation (ADAMS Accession No. ML22061A104) 3-397

3-398 3-399 3-400 3-401 3-402 3-403 3-404 3.8.5 Duane Arnold OpE Panel Discussion (Session 4A-5)

Moderator: Joseph Kanney, NRC/RES/DRA/FXHAB Terry Brandt, Nextera Energy John Hanna, NRC/Region 3 Christopher Hunter, NRC/RES Matthew Leech, NRC/NRR Question:

Chris, snowpack and salt spray were mentioned for the Pilgrim event. Was there a distinction between what the two weather-related events contributed to the analysis? Seems like for a near-shoreline event that the presence of accumulated salt spray would dominate.

Christopher Hunter:

To be quite frank, I don't know. If you follow Pilgrim, they've had a lot of these ice storms and a lot of these kind of issues where they've gotten these winter storms. They had one just a couple years previously for Winter Storm Nemo. So they had this continual experience. If you look at the history of Pilgrim they have had the most losses of off-site power, I think, of any any plant in the fleet and the majority of them were due to that their switch yard wasnt necessarily fully protected from ice and salt spray. But I can't tell you wehter the salt spray or ice events were the worst.

Question:

Chris, were any reactive inspections done for the ASP analysis shown or for the Waterford hurricane event?

Christopher Hunter:

For Brunswick an MD 8.3 [incident investigaiton] was done, but there were no deterministic questions answered as yes, and so they determined not to perform a special investigaiton (SIT) because none of the questions were answered yes. Even though they weren't required, they did a risk evaluation that came up with a 2 e-5 [CDF], which is basically the same answer that I got because, as I mentioned, the loop transient risk is dominant. At Pilgrim they did an MD 8.3 but they did do an SIT. They they did answer some of the deterministic questions yes. I think it had to do with the repeated switchyard issues, the fact that they they kept on getting these winter ice storm loops. But they also had some additional complications with some of the equipment so they answered yes and so they did do an SIT. With the Waterford event that just occurred, I'm currently working on the ASP analysis now. They did not do an MD 8.3 so there was no SIT performed for that.

Question:

Specific to Duane Arnold, what is the approximate size of debris that can pass through the river water system to the stilling basis? What is the approximate size of the openings for the ESW suction strainers? Was there any indication of suction issues for other pumps that take suction from that stilling basin?

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Christopher Hunter:

At Duane Arnold during the event they had this late inrush of debris. Initially the traveling screens, that are powered by safety-related power, were not not running because they didn't need to. Then they transitioned from not running to slow speed to fast speed. So what happened during the event was debris comes in, and then the traveling screens start to pick up, but already debris is either getting overtopped or bypassed. Eventually the traveling screens were in fast speed and caught up and was preventing debris for coming down and loading the strainers. You can kind of see that from the the differential pressures on the strainers. Train B reached its differential pressure limit of 15 PSID. But the train A strainer peaked at 11 PSID and stopped there. So to me that kind of indicates that it seemed like the traveling screens finally, were going at a fast enough speed to handle the debris. But another issue is the fact of bypassing. I dont know the size of the strainers, but there could be potential issues of bypassing the strainers. You're sending dirty water downstream that could plug heat exchangers or could cause equipment issues. We didn't see any of that during the event, and I think it's kind of an open question on whether that was because the traveling screens caught up and it was no longer sending dirty water down there, and so the amount of debris being bypassed was kind of minimized because the traveling screens are caught up? Or was that just because the debris was small enough to where it wasn't really causing any issues with running the train B diesel generator? So it's an interesting question that we don't really know the anwer, but obviously potentially a more severe event could have led to issues. You know, just bypassing the diesel generator is not necessarily a cure all and it could have caused some problems. But it didn't for Duane Arnold. I don't know if Terry and John or Matt want to jump in on that.

Terry Brandt:

The river water supply system allowed for larger debris to be filtered through. It was not uncommon to see sand pumped by the river water supply pumps into the stilling basin and we had a preventive maintenance that would clean out sand from the bottom of the stilling basin and the openings of the individual heat exchangers in the individual components and the ESW system. I think the opening of the systems were commiserate with the strainer design as to what would be strained out. We did have a procedure that allowed us to to monitor the differential pressure and we had instrumentation that's permanently installed, so we monitored that throughout the event. But I can't give you a design specs of each one of those. I'd have to go back and do some research to find those numbers.

Matthew Leech:

I'd also point out that what I learned during the LIC 504 analysis is all plants are different. They all have slightly different designs for their strainers, traveling screens, and even in terms of the openings, how big the traveling screens and their screens are. And in the design of the strainers, some are self backwashing, some are basket type strainers. All plants have slightly different types of straining systems.

John Hanna:

Terry, several hours into the event, things maybe have stabilized a little bit, but before 24 hours2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br /> or when offsite power was restored, I think we had asked the station about whether there was an intent to pre stage any FLEX equipment. Given that, in our opinion, we thought the threat had really passed, the derecho had gone by and we were thinking maybe pre staging FLEX 3-406

equipment would be advantageous. Specifcally, the phase two equipment because if you had a diesel failure or other equipment issues then it's less time to get that equipment and activate it and use it. But we heard back that there was not a desire or there was no plan to do that. Can you talk about the rationale, the mindset behind the decision not to go that path? To give a little bit of context, especially for those that are not in the industry, when the Fukushima orders came out and we required every licensee to be able to mitigate a Fukushima-type event and institute equipment and procedures, we did hear from the industry that there was a lot of desire to credit that equipment for a non-beyond-design-basis event. Whether it be for flexibility and refueling or maybe flexibility with taking other equipment out of service, that there was a general desire to credit that equipment for non-beyond-design-basis events. So we thought this was an event that FLEX equipment might have been used or credited or pre staged. But for whatever reason Duane Arnold didn't go down that path. Terry, could you speak to the mindset in the decision making there?

Terry Brandt:

We actually had a significant amount of discussions early on in the event with regard to the pre staging of FLEX equipment. If you go back to the initial conditions, we did have a diesel fire pump that was out of service in order to perform some preventive maintenance and we had some testing in progress. A couple of the small, and I would say minor, equipment issues that happened required operator response too. The Duane Arnold staffing at the time allowed for outside of the control room three equipment operators and we maintain a fire brigade with the maintenance organization also. So the FLEX assumptions assume that we have just those people on site. Now we weren't in FLEX assumption. It wasn't 2:00 o'clock in the morning on a Saturday night. It was a normal day shift, so we did have people on site. But the discussions that we had, were, you know, given the fact that we had both CSTs available, that they were undamaged as a suction source with both of our steam driven turbines being operational and in operation, maintaining level and maintaining the core covered very well. Our level was up above 214 inches to facilitate our natural circulation. We felt the need to get our operators out in the field and recover the plant. That would allow us to continue to use plant equipment first and then we could further evaluate the FLEX equipment afterwards. So the discussion initially was regarding maintaining the equipment or getting the equipment back to what we need. And then we go back further. So that was the background of why that decision was made in order to get some of the plant equipment back into a standby readiness state before we further evaluated that.

Question:

If Duane Arnold had not shut down, which of the model modifications that you made might have been rolled into the SPAR model? Or were all the changes you were making just really specific to the particular questions you were trying to get at in the ASP analysis?

Christopher Hunter:

Whenever we're doing this type of analysis there's going to be certain changes made just to support the analysis. There's other changes because we notice issues with the models. So for example, if Duane Arnold would have continued operating, one item that should have went in the model was the ability to initiate fire water in time to support a stuck open relief valve in SBO.

That's the diesel driven fire water pump that Terry was mentioning. Although it was initially inoperable due to maintenance, they could have restored that in pretty short order. Because if you just open up the SPAR model from scratch, and ou run a long duration loop, that was what 3-407

was dominating. So that would be an item that should be accounted for and changed in the permanent model record. Now, some of the other things such as FLEX, we're kind of in a kind of a grey area with FLEX. We still have all the FLEX models turned off, so I don't know if the FLEX modeling would stay in there, but some of that stuff would make sense. Because, whenever you're opening it, and reviewing the FLEX, the final integrated plan, and it would make sense that you would, even if the FLEX credit is turned off, that some of those changes, would be made, so you're not losing that effort. So, next time someone comes in and uses the model, they don't have to make those changes and we're maybe more consistent across our analysis.

Matthew Leech:

During the the LIC-504 analysis when I was working with a group of plants, I did discover some modeling issues that you'll discover when you go in depth into an analysis. Some of them might be very specific just to that one analysis you're doing. But some of the things I found did require changing in the base model of record, not necessarily for derecho. But I found some errors in how service water was modeled or something that could be better modeled in the models. I did feed that back to our vendor, Idaho National Labs, which maintains the model, and I know that upgrades or updates were made to those based on some of those things that we found. So throughout the process we did update some models of record.

Question:

Terry, you mentioned a very early in your talk about monitoring the weather forecast and the watches and the warnings. Where are you getting your weather alerts and watches from? Are you getting specialized forecasts from an enitity geared toward your industry? Or relying on forecasts avaialble to the general public?

Terry Brandt:

We did not have any specific program that would allow us to monitor the weather. So I subscribe to National Weather Service warnings on my cell phone and we had designed our communication such that a cell phone on airplane mode with Wi-Fi was allowed to be used inside of our control room. So I got the weather warnings on my cell phone. That's just being a good steward. What behavior that we would see on site is if a warning or a watch would be issued we'd typically get about two dozen phone calls in the control room to ask us whether or not we were taking actions out of our abnormal operating procedure. So the monitoring from a local weather station, National Weather Service in our case, out of the Quad Cities is what we use to determine the watches and warnings.

Moderator:

A derecho is an example of meso scale convective system where you have large scale organization, more than just a single isolated thunderstorm. You have many thunderstorms that line up together in a large system. There is a convective outlook, produced by the Weather Service Storm Prediction Center. I think they go as far out as maybe four days in advance.

These don't have the same level of definitiveness in terms of a warning. It's a long range view of weather systems of interest that may be coming up. The condvective outlook would be something that would be useful to have somebody subscribing to so you would have some advance warming that the conditions are ripe for things like, large thunderstorms, tornadoes, derecho's and things of that nature.

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Terry Brandt:

Thinking back to it, we did carry the emergency response pagers. Those were subscribed, so we would typically get a page. Wwhether or not it was timely, I can't remember, but we would get a page on the pagers if we had a watch or warning also. We had a couple different methods to be able to get informed of this. In this case, if I remember right, the two-day outlook was fairly clear with not a lot of chance of storms. So this was, to John's point earlier, that this was very fast moving and with very little warning of a storm.

John Hanna:

Terry, following the Robinson event and I'm not sure if you're familiar with that one. It was a major fire, a very risk-sgnificant event. There was an augmented inspection team (AIT) . During the restoration of power to get off the diesels and restoring normal lineup, they actually caused a second event, a high energy arc fault, to occur. Following that event, can you speak towhats changed in terms of offsite power restoration, the care and precautions you take before re-energizing buses? If you're not aware of what the industry overall is doing, maybe what changes Duane Arnold might have made.

Terry Brandt:

I can tell you that during our restoration we reviewed, did a pre job brief and took a very slow and very cautious approach to the restoration, because we knew that we were very stable where we were at with both diesels operating. We took a very cautious approach, used our normal procedures in order to restore power, and actually followed the recommendation of the transmission company, in this case ITC (International Transmission Company), to warm up the transformers and have breakers closed and wait a period of time. In our case we waited 15 minutes just to make sure that everything was going right. We were very stable at that point.

The other point that they [ITC] wanted to make with us, and on which we had very close conversations, is we just had a very significant event. They had just rebuilt some of our lines and they wanted to make sure that they weren't going to introduce anything to the lines by closing the breakers too. So, the Robinson event was not in the forefront of my mind. What was in the forefront of my mind was what we had built into the program from the Robinson event: (1) make sure you understand what you are doing; and (2) make sure you know where your fault is so that you don't reintroduce a fault by re-energizing the exact bus that you had a fault with.

Question: Whats the timeline for ASP analysis and the LIC-504 process? How long after the event were these two processes completed?

Christopher Hunter:

For ASP, the normal process is to start when we get the Licensee Event Report (LER) and complete the analysis in about two months after receiving the LER. For Duane Arnold we started pretty early. We were waiting on the LER before we sent the preliminary analysis out.

We completed the final analysis a little over 5 months from the event date.

Matthew Leech:

LIC-504 started a couple months after the event. We didn't act immediately. The recommendation to do the LIC-504 came in, management looked at it and discussed it and said 3-409

yes, let's go ahead and do it. There is one time metric for the first step of the LIC-504, where we have to decide whether or not we need to take immediate action or prompt action as it's worded.

Do we need to shut the plant down? Do we need to issue some other type of order that would improve safety? There's a time frame for that, usually we want to get that done within 30 days.

We did meet that goal for Duane Arnold. Once that was finished and there was a little bit less urgency, it took us about three more months before the LIC 504 was in a finished status. Thats due to the fact that were not looking at one plant. We were studying about 8 different plants and running that analysis. It took a little bit longer. But I will say there was one thing that the NRC did do in the interim before the ASP and LIC-504 was finished. As we had some information from a risk standpoint from Region III when this event occurred, we did issue some internal operating experience so that our inspectors would know initially what happened and some risk type information to focus on.

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3.9 Day 4: Session 4B - ASCE-7 Tornado Wind Loads Session Chair: Elena Yegorova, NRC/RES/DRA 3.9.1 Presentation 4B-1: Introduction to Tornado Loads in the New ASCE 7-22 Standard

- Including Long Return Period Tornado Hazards Maps with Applications to Nuclear Facilities Authors: Marc Levitan*, National Institute of Standards and Technology Speaker: Marc Levitan 3.9.1.1 Abstract The American Society of Civil Engineers ASCE 7 Standard on Minimum Design Loads and Associated Criteria for Buildings and Other Structures is the national standard referenced in model building codes for determination of dead loads, live loads, and loads caused by environmental hazards such as earthquakes, floods and windstorms. This standard has not included loads caused by tornadoes - until now. The 2022 edition of ASCE 7 has a new chapter with requirements for consideration of tornado loads in the design of certain buildings and other structures. The tornado hazard maps and load methodology in ASCE 7 are the result of a decade of research and development led by the National Institute of Standards and Technology (NIST). Key to the tornado load provisions is a new generation of tornado hazard maps. These maps incorporate advances in the understanding of tornado climatology and regional properties of tornadoes, tornado wind fields, tornado wind speeds, and the very significant effects of target size (and shape) on wind speed risk. The Standard includes a series of 48 maps with design tornado speeds for six return periods (from 1,700 to 10 million years) at eight target sizes each (from point targets to 4 million square feet). The map development process included consideration of epistemic (modeling) uncertainties, with support from the Nuclear Regulatory Commission. This presentation provides an overview of the tornado load requirements in ASCE 7-22 and their development. Tornado maps are a main focus of the talk, including introduction of Appendix G (Long Return Period Tornado Hazard Maps) and the ASCE 7 Hazard Tool, which provides site-specific values for all environmental hazards (including tornadoes) through a webGIS application.

3.9.1.2 Presentation (ADAMS Accession No. ML22061A103) 3-411

3-412 3-413 3-414 3-415 3-416 3-417 3-418 3-419 3-420 3-421 3-422 3-423 3-424 3-425 3-426 3-427 3.10 Day 4: Session 4C - USACE Dam and Levee Database Updates Session Chair: Joseph Kanney, NRC/RES/DRA 3.10.1 Presentation 4C-1: National Inventory of Dams Authors: Becky Ragon*, U.S. Army Corps of Engineers Speaker: Becky Ragon 3.10.1.1 Abstract The National Inventory of Dams (NID), a congressionally authorized database, has served as a central repository of information on dams in the U.S. and its territories since the 1980s. The site has been updated to make it easier to find and share dam-related data. The U.S. Army Corps of Engineers (USACE) maintains the NID and works in close collaboration with federal and state dam safety agencies to obtain accurate and complete information about dams in the database.

The new NID allows agencies to update data in-real time - users can expect fresher data that can be downloaded and shared at any time. The NID also features new information for some dams. USACE is sharing flood inundation maps for its dams in the NID as well as narrative summaries about what their dams do, benefits they provide and risks they pose, and planned and ongoing actions to manage dam risks.

3.10.1.2 Presentation (ADAMS Accession No. ML22061A102) 3-428

3-429 3-430 3-431 3-432 3-433 3.10.2 Presentation 4C-2: National Levee Database Authors: Brian Vanbockern*, U.S. Army Corps of Engineers Speaker: Brian Vanbockern 3.10.2.1 Abstract The National Levee Database (NLD), developed by the U.S. Army Corps of Engineers (USACE), is the focal point for comprehensive information about our nation's levees. The database contains information to facilitate and link activities, such as flood risk communication, levee system evaluation for the National Flood Insurance Program (NFIP), levee system inspections, flood plain management, and risk assessments. The NLD continues to be a dynamic database with ongoing efforts to add levee data from federal agencies, states, and tribes.

3.10.2.2 Presentation (ADAMS Accession No. ML22061A101) 3-434

3-435 3-436 3-437 3-438 National Levee Database: https://levees.sec.usace.army.mil/#/

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RIL 2022-10 4 WORKSHOP PARTICIPANTS Hosung Ahn Thomas Aird Hydrologist Environmental Engineer U.S. Nuclear Regulatory Commission U.S. Nuclear Regulatory Commission Azin Al Kajbaf Steven Alferink Graduate Student Reliability and Risk Analyst University of Maryland U.S. Nuclear Regulatory Commission Ashley Allard Jamila Alsuwaidi Special Agent Senior Safety Assessment Specialist U.S. Nuclear Regulatory Commission United Arab Emirates Federal Authority For Nuclear Regulation Ayhan Altinyollar Christopher Amante Nuclear Safety Officer Research Scientist International Atomic Energy Agency U.S. National Oceanic and Atmospheric Administration Audrey Amphoux Victoria Anderson Electricite de France Technical Advisor Nuclear Energy Institute Luke Aucoin Gregory Baecher Research Physical Scientist Professor, Civil and Environmental U.S. Army Corps of Engineers, Engineer Engineering Research and Development Center University of Maryland James Barbis Lise Bardet Associate Water Resources Engineer Section Head, Hydrogeology, Flood, Wood, PLC Meteorological and Geotechnical Risk Assessment France Institute for Radiological Protection and Nuclear Security Patrick Barnard Laurel Bauer Coastal Geologist Geologist U.S. Geological Survey U.S. Nuclear Regulatory Commission Kevin M. Befus Joe Bellini Assistant Professor Principal Engineer/Vice President University of Arkansas, Department of Aterra Solutions, LLC Geosciences Chris Bender Michelle Bensi Coastal Engineer Assistant Professor, Civil and Environmental Taylor Engineering Engineering University of Maryland 4-1

Amelia Bergbreiter Nathalie Bertrand Civil Engineer Research Engineer U.S. Federal Energy Regulatory Commission France Institute for Radiological Protection and Nuclear Security Joel Bildoeau Paul Blanch Senior Consultant GZA, Inc. Self Dennis Bley Javier Brand Consultant to ACRS Reactor Inspector U.S. Nuclear Regulatory Commission U.S. Nuclear Regulatory Commission Terry Brandt Ralph Branscomb Fleet Online Director Principle Consultant NextEra Energy Yankee Atomic Holding Company Kamry Breard Bud Brock Civil Engineer Dam Safety Engineer ENERCON Federal Services, Inc. New Mexico Office of the State Engineer, Dam Safety Bureau Melanie Brown Brian Brown Chief Engineer - Civil/Seismic Senior Civil Engineer Southern Nuclear California Department of Water Resources Kaye Brubaker Kristy Bucholtz Associate Professor, Civil & Environmental Reliability and Risk Analyst Engineering U.S. Nuclear Regulatory Commission University of Maryland Robert Budnitz Aaron Byrd Research Scientist (retired) Research Civil Engineer Lawrence Berkeley National Laboratory U.S. Army Corps of Engineers, Engineer Research and Development Center Jason Caldwell Mike Calley North American Flood Resiliency Segment Manager, Regulatory Support Department Lead Idaho National Laboratory Wood, PLC Karen Carboni Stef Carelsen Program Manager Senior Inspector Tennessee Valley Authority Netherlands Authority for Nuclear Safety and Radiation Protection Kelly Carignan Lynne Carpenter Sr. Assoc. Scientist Geologist U.S. National Oceanic and Atmospheric U.S. National Forest Service Administration 4-2

Meredith Carr Mary Casto Research Hydraulic Engineer Student Co-op U.S. Army Corps of Engineers, Engineer U.S. Nuclear Regulatory Commission Research and Development Center Laura Chap Sushil Chaudhary Senior Engineer Dam Safety Engineer Atkins New Mexico Office of the State Engineer Dam Safety Bureau Danny Chien Nilesh Chokshi Reactor Systems Engineer Consultant U.S. Nuclear Regulatory Commission Independent consultant A. Egon Cholakian Robert Choromokos P.I. / Visiting Researcher Project Manager Harvard University / NIH / Oxford University Electric Power Resaerch Institute Michael logan Cline Judah Cohen Geologist Principal Scientist U.S. Bureau of Reclamation Atmospheric and Environmental Research paolo contri Christopher Cook SH External Event Safety Section Branch Chief, Instrumentation, Controls, and International Atomic Energy Agency Electrical Engineering U.S. Nuclear Regulatory Commission Bryce Corlett Kevin Coyne Coastal Scientist/Engineer Senior Technical Advisor, PRA Moffatt & Nichol U.S. Nuclear Regulatory Commission Gordon Curran Pedro Diaz Reactor System Engineer Safety analysis specialist U.S. Nuclear Regulatory Commission IDOM Consulting, Engineering, Architecture Richard Deese Jonathan DeJesus Senior Reactor Analyst Reliability and Risk Analyst U.S. Nuclear Regulatory Commission U.S. Nuclear Regulatory Commission Huseyin Demir Scott DeNeale Sr. Engineer Water Resources Engineer INTERA Oak Ridge National Laboratory Jonathan Dillow Claire-Marie Duluc Hydrologist/Surface-Water Specialist Deputy Head, Site and Natural Hazards U.S. Geological Survey Department France Institute for Radiation Protection and Nuclear Safety 4-3

Maria Adriana Dutcec Carville "Billy" Edwards Engineer Supervisory Civil Engineer Romania Institute for Nuclear Research U.S. Federal Emergency Management Agency John England David Esh Lead Civil Engineer - Hydrologic Hazards Senior Risk Analyst U.S. Army Corps of Engineers Risk U.S. Nuclear Regulatory Commission Management Center Randall Fedors Constantinos Frantzis Senior Hydrogeologist PhD Student U.S. Nuclear Regulatory Commission University of Maryland Patrick Frias Raymond Furstenau General Engineer, Civil/Hydraulics Director, Office of Nuclear Regulatory U.S. Deppartment of Energy, Office of Nuclear Research Safety U.S. Nuclear Regulatory Commission Susan Gallier Dennis Galvin Staff Writer Project Manager American Nuclear Society U.S. Nuclear Regulatory Commission Sergio Garcia Lucia Garces Ph.D. Student University of Maryland IDOM Consulting, Engineering, Architecture Emily Gibson Jeanne Godaire Project Engineer Geologist Schnabel Engineering U.S. Bureau of Reclamation Garrett Godbey Victor Gonzalez Risk Based Applications Engineer Research Civil Engineer Enercon U.S. Army Corps of Engineers, Engineer Research and Development Center Emily Granier Kevin Griebenow Operational Planner Civil Engineer U.S. Federal Emergency Management Agency U.S. Federal Energy Regulatory Commission Robyn Griffith Allen Gross Self Risk Analyst U.S. Nuclear Regulatory Commission Christopher Grossman Jin-Ping Gwo Project Manager Systems Performance Analyst U.S. Nuclear Regulatory Commission U.S. Nuclear Regulatory Commission 4-4

Alan Hackerott Samson Haile-Selassie PRA Engineer/Consultant Senior Water Resources Engineer Westinghouse, Inc. California Department of Water Resources Robert Hallowell John Hanna Technical Staff Senior Reactor Analyst Massachusetts Insitute of Technology Lincoln U.S. Nuclear Regulatory Commission Laboratory Salman Haq Kathleen Harris Reactor Engineer Research Civil Engineer U.S. Nuclear Regulatory Commission U.S. Army Corps of Engineers, Engineer Research and Development Center Des Hartford Cynthia Haynes Principal Engineer, Dam Safety Management Investigations Assistant BC Hydro U.S. Nuclear Regulatory Commission Jory Hecht David Heeszel Hydrologist Geophysicist U.S. Geological Survey U.S. Nuclear Regulatory Commission Liv Herdman Moises Hernandez Hydrologist Clinical Pharmacologist U.S. Geological Survey U.S. Air Force Medical Readiness Agency Erich Hester Todd Hilsmeier Associate Professor Risk Analyst Virginia Tech University U.S. Nuclear Regulatory Commission David Ho William Holloway Hydraulic Engineer GIS Unit Lead U.S. Army Corps of Engineers Hydrologic U.S. Federal Emergency Management Engineering Center (USACE/HEC) Agency Lihua Huang Doug Hultstrand China General Nuclear Power Group Senior Hydrometeorologist Applied Weather Associates, LLC Matthew Humberstone Kelly Hunter Risk Analyst Chief Operating Officer U.S. Nuclear Regulatory Commission INTERA Incorporated Christopher Hunter Anastasiia Ilina Sr. Reliability and Risk Engineer Researcher U.S. Nuclear Regulatory Commission Ukraine State Scientific and Technical Center for Nuclear and Radiation Safety (SSTC NRS) 4-5

Mohammad Islam Hugo Jadot Civil Engineer External Events PRA expert U.S. Army Corps of Engineers Electricite de France Albert Janes Weixia Jin External Events Evaluation - Project Manager Vice President- Principal Engineer IDOM Consulting, Engineering, Architecture Moffatt & Nichol Dennis Johnson Dustin Jones Senior Hydrologist Supervising Engineer Aterra Solutions, LLC California Department of Water Resources Darone Jones Ian Jung Director, National Weather Service Water Senior Reliability and Risk Analyst Prediction Operations U.S. Nuclear Regulatory Commission U.S. National Oceanic and Atmospheric Administration Joseph Kanney Shih-Chieh Kao Hydrologist Senior Research Staff U.S. Nuclear Regulatory Commission Oak Ridge National Laboratory Bill Kappel Manoj Kc President/Chief Meteorologist Water Resources Engineer Applied Weather Associates, LLC Michael Baker International Keith Kelson Beom-Jin Kim Paleoflood Technical Lead, Engineering Postdoctoral Researcher Geologist Korea Atomic Energy Research Institute U.S. Army Corps of Engineers Derek Kinder Patrick Koch Hydraulic Engineer Structural Engineer U.S. Army Corps of Engineers Risk U.S. Nuclear Regulatory Commission Management Center Oleksandr Kudrytskyi Michael Kuprenas Researcher Nuclear Engineer Ukraine State Scientific and Technical Center U.S. Navy, Naval Sea Systems Command for Nuclear and Radiation Safety (SSTC NRS)

Aikaterini Kyprioti Kyle Landon PhD Candidate Coastal Engineer University of Notre Dame Moffatt & Nichol Charles Langley Lawrence Lee Executive Director PRA Engineer Public Watchdogs Jensen Hughes 4-6

Matthew Leech William Lehman Reliability and Risk Analyst Sr Risk Analyst U.S. Nuclear Regulatory Commission U.S. Army Corps of Engineers Hydrologic Engineering Center (USACE/HEC)

Shizhong Lei David Leone GeoScience Technical Specialist Associate Principal Canada Nuclear Safety Commission GZA, Inc.

Walter Leschek Bret Leslie Reliability and Risk Engineer Senior Professional Staff- Geologist U.S. Nuclear Regulatory Commission U.S. Nuclear Waste Technical Review Board Camille Levine Dan Levish Graduate Research Assistant Technical Specialist University of Maryland U.S. Bureau of Reclamation Marc Levitan Chang-Yang Li Lead Research Engineer, National Windstorm Sr. Safety and Systems Engineer Impact Reduction Program U.S. Nuclear Regulatory Commission U.S National Institute for Standards and Technology Yueh-Li Li Christina Lindemer Senior Mechanical Engineer Coastal Engineer U.S. Nuclear Regulatory Commission U.S. Federal Emergency Management Agency Tao Liu Ziyue Liu Phd Student Student Virginia commonwealth university University of Maryland Zhegang Ma Pathmathevan Mahadevan Lead Risk Analysis Engineer Civil Engineer Idaho National Laboratory U.S. Federal Energy Regulatory Commission Kelly Mahoney Noel Marc Research Meteorologist Project Manager U.S. National Oceanic and Atmospheric European Commission - Joint Research Administration Centre David Margo Giuseppe Mascaro Lead Civil Engineer Assistant Professor, School of Sustainable U.S. Army Corps of Engineers, Risk Engineering and the Built Environment Management Center Arizona State University Robert Mason Petr Masopust Extreme Hydrologic Events Coordinator Principal Engineer U.S. Geological Survey Aterra Solutions, LLC 4-7

Delza Mas-Penaranda Chris Massey Project Engineer Research Mathematician U.S. Nuclear Regulatory Commission U.S. Army Corps of Engineers Michael Mazaika Steve McDuffie Physical Scientist (Meteorologist) Seismic Engineer U.S. Nuclear Regulatory Commission U.S. Department of Energy Adeljalil Mekkaoui Nate Mentzer U.S. Department of Homeland Security Reactor Inspector U.S. Nuclear Regulatory Commission Philip Meyer Jeffrey Miller Research Engineer Senior PRA Engineer Pacific Northwest National Laboratory Enercon Services, Inc.

Somayeh Mohammadi Jamal Mohmand PhD student PRA Engineer University of Maryland Sandia National Laboratory Celso Moller Ferreira Susmita Mukherjee Roy Associate Professor, Department of Civil, India Atomic Energy Regulatory Board Environmental, and Infrastructure Engineering George Mason University Norberto Nadal-Caraballo jared nadel Senior Research Engineer Senior Resident Inspector U.S. Army Corps of Engineers, Engineer U.S. Nuclear Regulatory Commission Research and Development Center Muthu Narayanaswamy Andy Neal Coastal Engineer Actuary Michael Baker International U.S. Federal Emergency Management Agency Kit Ng Ching Ng Manager of Hydraulics and Hydrology Risk Analyst Bechtel Corp U.S. Nuclear Regulatory Commission Thomas Nicholson Shinsaku Nishizaki Professional Hydrologist Consultant U.S. Nuclear Regulatory Commission (Retired) International Atomic Energy Agency David Novak Nicole Novembre Director, National Weather Service Weather Hydrologic Engineer Prediction Center Brava Engineering, Inc.

U.S. National Oceanic and Atmospheric Administration 4-8

William Orders Jeffrey Oskamp Senior Project Manager Coastal Engineer U.S. Nuclear Regulatory Commission Moffatt & Nichol Margaret Owensby Emmanuel Paquet Research Hydraulic Engineer Hydrologist expert U.S. Army Corps of Engineers, Engineer Electricite de France Research and Development Center Sunwoo Park Tye Parzybok Reliability and Risk Analyst Lead, Integrated Multi-sensor Content U.S. Nuclear Regulatory Commission DTN, LLC Mark Perry Lucie Pheulpin Dam Safety Engineer Research Engineer Colorado Dam Safety France Institute for Radiological Protection and Nuclear Security Jacob Philip Frances Pimentel Civil Engineer Sr. Project Manager U.S. Nuclear Regulatory Commission (Retired) Nuclear Energy Institute Marie Pohida Oleg Ponochovnyi Senior Reliability and Risk Analyst Head of PSA laboratory U.S. Nuclear Regulatory Commission Ukraine State Scientific and Technical Center for Nuclear and Radiation Safety (SSTC NRS)

Chad Pope Michael Powell Professor, Nuclear Engineering PWROG Chairman & APS Chief Operating Idaho State University Officer PWROG/Arizona Public Service Company (APS)

Alvin Prakash Rajiv Prasad Engineer Earth Scientist California Department of Water Resources Pacific Northwest National Laboratory Andreas Prein Lundy Pressley Scientist Reliability and Risk Analyst U.S. National Center for Atmospheric Research U.S. Nuclear Regulatory Commission Jamie Prochno Julia Prokopec Civil Engineer Hydrologist U.S. Federal Emergency Management Agency U.S. Geological Survey Kevin Quinlan Becky Ragon Meteorologist Manager, National Inventory of Dams U.S. Nuclear Regulatory Commission U.S. Army Corps of Engineers 4-9

Marko Randelovic Mayasandra Ravindra Project Manager President Electric Power Research Institute MKRavindra Consulting Vincent Rebour Mehdi Reisi Fard Department Head, Site and Natural Hazard Branch Chief, Performance and Reliability Characterization U.S. Nuclear Regulatory Commission France Institute for Radiological Protection and Nuclear Security William Rhodes Yann Richet Operational Planner Scientific Advisor U.S. Federal Emergency Management Agency France Institute for Radiological Protection and Nuclear Security John Richins David Rosa PhD Student Emergency Management Specialist University of Arkansas U.S. Federal Emergency Management Agency Andrew Rosebrook MarkHenry Salley Senior Reactor Analyst Branch Chief, Fire and External Hazards U.S. Nuclear Regulatory Commission Analysis U.S. Nuclear Regulatory Commission Shane Sandal Tim Sande Senior Reactor Analyst PRA Supervisor U.S. Nuclear Regulatory Commission ENERCON Emiliano Santin John Saxton Statistician Hydrogeologist U.S. Federal Emergency Management Agency U.S. Nuclear Regulatory Commission Tim Schmitt Raymond Schneider Engineering Supervisor Fellow Framatome, Inc. Westinghouse, Inc.

Leo Shanley Jamey Sharlow Principal Engineer Nuclear Support Services Supervisor Jensen Hughes Duke Energy, Harris Nuclear Plant Joy Shen Sahas Shrestha Graduate Research Assistant Engineer University of Maryland at Colleg ePark Michael Baker International Daniyal Siddiqui Hannah Skiles Civil Associate Management Analyst Michael Baker International U.S. Federal Emergency Management Agency 4-10

Curtis Smith Christopher Smith Director, Nuclear Safety and Regulatory Research Geologist Research Division U.S. Geological Survey Idaho National Laboratory Adam Smith Erik Smith Physical Scientist / Applied Climatologist Climate Resilience Analyst U.S. National Oceanic and Atmospheric Electric Power Research Institute Administration Mathini Sreetharan Kristi Steinhilber Senior Engineer, Associate Meteorologist Dewberry, Inc. Applied Weather Associates, LLC Neda Stoeva Stuart Stothoff Associate Nuclear Safety Officer Principal Scientist International Atomic Energy Agency Southwest Research Institute Christian Strack Rajmani Subedi Researcher Water Resources Engineer Gesellschaft für Anlagen- und California Department of Water Resources Reaktorsicherheit (GRS)

Christine Suhonen Michael Sullivan Project Manager GZA, Inc. Self Peter Swarzenski Sarah Tabatabai Research Oceanographer Project Manager U.S. Geological Survey U.S. Nuclear Regulatory Commission Alexandros Alexandros Philip Tarpinian Jr.

Professor, Civil and Environmental Engineering Senior Staff Engineer / PRA Engineer and Earth Sciences Exelon Generation (Constellation)

University of Notre Dame Stewart Taylor Keith Tetter Manager of Geotechnical & Hydraulic Reliability and Risk Analyst Engineering Services U.S. Nuclear Regulatory Commission Bechtel Global Corporation Mark Thaggard Wilbert Thomas Director, Division of Risk Analysis Senior Technical Consultant U.S. Nuclear Regulatory Commission Michael Baker International Arianne Thomas Charles Thompson Regional Hurricane Program Manager Chief, Dam Safety Bureau U.S. Federal Emergency Management Agency New Mexico Office of the State Engineer 4-11

Peter Thornton Joel Tillery Scientist Senior Water Resources Engineer Oak Ridge National Laboratory Freese & Nichols, Inc.

Edgardo Torres Tam Tran Reliability & Risk Analyst Environmental PM U.S. Nuclear Regulatory Commission U.S. Nuclear Regulatory Commission Quentin Travis Jean Trefethen Director of Applied Research Environmental Project Manager WEST Consultants, Inc. U.S. Nuclear Regulatory Commission Amanda Turk Geoff Uhlemann Manager, River Analysis and Decision Support Water Resources Team Leader & Sr. Project Tennessee Valley Authority Manager Michael Baker International Jessica Umana Milton Valentin Technical Assistant Reliability and Risk Analyst U.S. Nuclear Regulatory Commission U.S. Nuclear Regulatory Commission Brian VanBockern Marty Venticinque Data Management Branch Chief - National Meteorologist Levee Database Manager Applied Weather Associates, LLC U.S. Army Corps of Engineers Andrew Verdin Gabriele Villarini Hydrologic Scientist Professor, Civil and Environmental Stantec Engineering University of Iowa Clifford Voss Kent Walker Emeritus Scientist (Hydrogeologist) Dam Safety Program Manager U.S. Geological Survey U.S. Bureau of Reclamation Weijun Wang Zhanxian Wang Sr. Geotechnical Engineer Coastal Engineer U.S. Nuclear Regulatory Commission Moffatt & Nichol Bin Wang Zeechung Wang Sr Technical Specialist Reliability and Risk Engineer GZA, Inc. U.S. Nuclear Regulatory Commission David Watson Jason White Senior Project Manager, Stormwater/Water Physical Scientist/Meteorologist Resources U.S. Nuclear Regulatory Commission AECOM, Inc.

4-12

Thomas Williams Shawn Williams Senior Water Resources Engineer Project Manager Wood, PLC U.S. Nuclear Regulatory Commission Abbie Wilson Daniel Wright Project Manager/Coastal Engineer Assistant Professor Moffatt & Nichol University of Wisconsin-Madison De (Wesley) Wu Madison Yawn Reliability and Risk Analyst Research Physical Scientist U.S. Nuclear Regulatory Commission U.S. Army Corps of Engineers, Engineer Research and Development Center Elena Yegorova Cale Young Meteorologist Senior Reactor Analyst U.S. Nuclear Regulatory Commission U.S. Nuclear Regulatory Commission Xubin Zeng Quinn Zheng Professor, Department of Hydrology and Geoscience Assessment Officer Atmospheric Sciences Canada Nuclear Safety Commission University of Arizona Casey Zuzak Senior Risk Analyst U.S. Federal Emergency Management Agency 4-13

5

SUMMARY

AND CONCLUSIONS 5.1 Summary This report includes the agenda and presentations for the Seventh Annual PFHA Research Workshop, including all presentation abstracts and slides and abstracts for submitted posters.

The workshop was virtually attended by members of the public; NRC technical staff, management, and contractors; and staff from other Federal agencies and academia. Public attendees over the course of the workshop included industry groups, industry members, consultants, independent laboratories, and academic institutions.

5.2 Conclusions As reflected in these proceedings, PFHA is a very active area of research for the NRC and its international counterparts, other Federal agencies, industry, and academia. Readers of this report will have been exposed to current technical issues, research efforts, and accomplishments in this area within the NRC and the wider research community.

The NRC projects discussed in these proceedings represent the main efforts in the first phase (technical basis phase) and second phase (pilot studies) of the NRCs PFHA Research Program. This technical basis phase is nearly complete, and the NRC has initiated a second phase (pilot project phase) that synthesizes various technical basis results and lessons learned to demonstrate development of realistic flood hazard curves for several key flooding phenomena scenarios (site-scale, riverine, and coastal flooding). The third phase (development of selected guidance documents) is an area of active discussion between RES and NRC user offices. The NRC staff looks forward to further public engagement on the second and third phases of the PFHA research program in future PFHA research workshops.

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6 ACKNOWLEDGEMENTS An organizing committee in the NRC RES Division of Risk Analysis, Fire and External Hazards Analysis Branch, planned and executed this workshop with the assistance of many NRC staff.

Organizing Committee Chair: Joseph Kanney Organizing Committee Members: Tom Aird, Sarah Tabatabai, Elena Yegorova, and MarkHenry Salley Workshop NRC Facilitator: Kenneth Hamburger Several NRC offices contributed to this workshop and the resulting proceedings. The organizing committee would like to highlight the efforts of the RES administrative staff, as well as agency publishing staff. The organizers appreciated managerial direction and support from MarkHenry Salley, Mark Thaggard, Christian Araguas, and Ray Furstenau. Managers and staff from the NRC Office of Nuclear Reactor Regulation, Division of Engineering and External Hazards and Division of Risk Analysis, provided valuable support, consultation, and participation.

Members of the Probabilistic Flood Hazard Assessment Research Group:

MarkHenry Salley (Branch Chief), Joseph Kanney (Technical Lead), Tom Aird, Elena Yegorova, and Sarah Tabatabai.

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