Workshop on

Probabilistic Flood Hazard Assessment

(PFHA)

PROGRAM

January 29 - 31, 2013, 8:30 a.m.–6:30 p.m. (EST)

U.S. NRC Headquarters Auditorium

11555 Rockville Pike, Rockville, MD 20852
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Program Notes 

The U.S. Nuclear Regulatory Commission’s (NRC’s) Offices of Nuclear Regulatory Research

(RES), Nuclear Reactor Regulation (NRR), and New Reactors (NRO), in cooperation with 

Federal agency partners: U.S. Department of Energy (DOE); Federal Energy Regulatory 

Commission (FERC); U.S. Army Corps of Engineers (USACE); U.S. Bureau of Reclamation 

(BoR); and U.S. Geological Survey (USGS) have developed this “Workshop on Probabilistic 

Flood Hazard Assessment (PFHA).” This is a research workshop devoted to the sharing of 

information on probabilistic flood hazard assessments for extreme events (i.e., annual 

exceedance probabilities much less than 2.0 E-3 per year) from the Federal community. The 

organizing committee has chosen the presenters and panelists who have extensive knowledge 

and experience in the workshop topics. 

Workshop Objectives 

The aim of the workshop is to assess, discuss, and inform participants on, the state-of-thepractice for extreme flood assessments within a risk context with the following objectives: 

• Facilitate the sharing of information between both Federal agencies and other interested 

parties to bridge the current state-of-knowledge between extreme flood assessments and 

risk assessments of critical infrastructures. 

• Seek ideas and insights on possible ways to develop a probabilistic flood hazard 

assessment (PFHA) for use in probabilistic risk assessments (PRA). Flood assessments 

include combinations of flood-causing mechanisms associated with riverine flooding, dam 

and levee safety, extreme storm precipitation, hurricane and storm surges, and tsunami. 

• Identify potential components of flood-causing mechanisms that lend themselves to 

probabilistic analysis and warrant further study (i.e., computer-generated storm events). 

• Establish realistic plans for coordination of PFHA research studies as the follow-up to the 

workshop observations and insights. 

• Develop plans for a cooperative research strategy on PFHA for the workshop partners. 

Focus 

The workshop will focus on the following activities: 

• Understand the flood assessment needs of the participating Federal agencies with respect 

to the evaluation of critical industry infrastructure. 

• Leverage the flood hazard risk assessment studies performed to date to assess the 

applicability and practicality of using probabilistic approaches for extreme flood hazard 

assessments within a risk framework. 

• Discuss research or other activities needed to address identified gaps or challenges in the 

use of PFHA for extreme flood assessments within PRA. 
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• Determine how these PFHA approaches and methods can be best utilized in conjunction 

with more traditional deterministic approaches. 

Workshop Structure 

The workshop is designed to obtain answers to questions posed to the session panelists. Eight 

technical panel sessions will be convened consisting of presentations and discussions by invited 

presenters and panelists. The presenters will inform the workshop attendees on subjects related 

to their expertise regarding the various session themes. Following these presentations, a panel 

discussion will be held, with the session co-chairs acting as moderators. Each session will have 

rapporteurs to collect observations and insights from the presentations and discussions which 

will be summarized for the concluding session. 

The workshop is an NRC Category 2 Public Meeting. At the end of each day, the public will 

have the opportunity to ask questions and to make comments. 

Panel 1: Federal Agencies’ Interests and Needs in PFHA

 Co-Chairs: Nilesh Chokshi, NRC and Mark Blackburn, DOE 

Panel 1 will be a forum to highlight the participating Federal agencies’ interests and needs 

regarding Probabilistic Flood Hazard Assessments (PFHA). The presentations will include NRC 

staff’s perspectives on the development of a PFHA approach within a risk context. Other 

presentations will focus on probabilistic approaches presently used or under development by 

the participating agencies, as well as ongoing efforts to develop consensus standards. 

Panel 2: State-of-the-Practice in Identifying and Quantifying Extreme Flood Hazards 

 Co-Chairs: Timothy Cohn, USGS and Will Thomas, Michael Baker, Jr., Inc. 

Panel 2 focuses on the state-of-the-practice in identifying and quantifying extreme flood hazards 

including their frequency and associated flood conditions within a risk context. Additional 

discussion on how extreme events (i.e., with an annual exceedance probability of much less 

than 2E-3 ranging to 1E-6) not historically observed or normally anticipated (i.e., “black swans”) 

could be estimated. The panel will also discuss uncertainties in the estimation of flood levels 

and conditions. 

Panel 3: Extreme Precipitation Events

 Co-Chairs: John England, BoR and Chandra Pathak, USACE 

Panel 3 focuses on extreme precipitation events and their impacts on flooding due to local or 

watershed-scale responses. Antecedent conditions such as snowpack releases and 

combination of extreme storms (e.g., the possibility of sequential hurricanes or extratropical 

storms) will be included, as well as, various data sources and climate perspectives. 

Panel 4: Flood-Induced Dam and Levee Failures

 Co-Chairs: Tony Wahl, BoR and Sam Lin, FERC 

Panel 4 focuses on defining the current state-of-the-art and –practice, and research needs, 

related to estimating probabilities of failure and flooding associated with dams and levees. 

Presenters will address methods for estimating probabilities of failure, making probabilistic 
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assessments of flood hazards, and determining inflow design floods. The emphasis will be on 

potential failure modes tied to hydrologic events and the associated erosion of 

embankments/foundations, not limited to overtopping failures. 

Panel 5: Tsunamis Flooding 

 Co-Chairs: Eric Geist, USGS and Henry Jones, NRC 

Panel 5 focuses on Probabilistic Tsunami Hazard Analysis (PTHA) as derived from its 

counterpart, Probabilistic Seismic Hazard Analysis (PSHA) to determine seismic ground-motion 

hazards. The Panel will review current practices of PTHA, and determine the viability of 

extending the analysis to extreme design probabilities (i.e., 10-4 to 10-6). In addition to 

earthquake sources for tsunamis, PTHA for extreme events necessitates the inclusion of 

tsunamis generated by submarine landslides, and treatment of the large attendant uncertainty in 

source characterization and recurrence rates. Submarine landslide tsunamis will be a particular 

focus of Panel 5.

Panel 6: Riverine Flooding 

 Co-Chairs: Will Thomas, Michael Baker, Jr., Inc. and 

 Rajiv Prasad, Pacific Northwest National Laboratory 

Panel 6 focuses on riverine flooding including watershed responses via routing of extreme 

precipitation events and antecedent conditions such as snowpack releases. This session is 

linked to Panel 3 and 4. {Flood-induced dam and levee failures will be addressed separately in 

Panel 4.} 

Panel 7: Extreme Storm Surge for Coastal Areas

 Co-Chairs: Donald Resio, Univ. of North Florida and Ty Wamsley, USACE 

Panel 7 focuses on extreme storm surge for coastal areas due to hurricanes, extratropical 

cyclones and intense winter storms. The panel will also discuss seiche flooding on closed or 

semi-closed water bodies. 

Panel 8: Combined Events Flooding 

 Co-Chairs: David Margo, USACE and Joost Beckers, Deltares 

Panel 8 focuses on identifying and evaluating combined event scenarios within a risk-informed 

framework. Combined events can include flooding caused by seismically-induced dam or levee 

failure; flooding caused by combinations of snowmelt, rainfall and ice; flooding caused by 

combinations of coastal and riverine events; basin or system-wide performance and impacts; 

human and organizational factors; and other scenarios. 

Panel 9: Summary of Significant Observations, Insights and Identified Opportunities 

 for Collaboration on PFHA 

 Panel Co-Chairs: Tom Nicholson and Christopher Cook, NRC 

Panel 9 will be a forum to provide summaries of significant observations and insights from the 

previous technical panel presentations and discussions. 

 
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Workshop Contacts: 

Workshop Co-Chair: Thomas Nicholson, NRC/RES Thomas.Nicholson@nrc.gov

Workshop Coordinator: Wendy Reed, NRC/RES Wendy.Reed@nrc.gov

Registration: 

No fee. For security purposes, each workshop attendee must complete and submit a 

registration form prior to the workshop. This form is available on the NRC Public Website under 

“Public Meeting Schedule.” Please e-mail the completed form to 

registrationPFHAworkshop@nrc.gov. All workshop attendees must have two forms of photoidentification for the security review to obtain access to the NRC auditorium. 

General Questions: 

• What aspects of flood-causing mechanisms for extreme events can be assessed in a 

probabilistic manner? What new methods are in development for assessing extreme storm 

precipitation, dam and levee breaches, hurricane and storm surge, tsunami, and riverine 

flooding? What are the extreme probabilities for these methods? 

• How best to quantify uncertainties associated with extreme flood estimates? 

• Are there regions of the United States that would facilitate a more probabilistic approach 

than other regions (e.g., paleoflood analyses)? 

• What is the interrelationship of deterministic and probabilistic approaches, and how can 

insights from both of these approaches be used in a Probabilistic Flood Hazard Assessment 

(PFHA)? 

• How can PFHA be used in risk assessments for critical infrastructures with appropriate 

consideration of uncertainties and state-of-the-art hydrometeorological modeling? 

• How can uncertainties be determined when estimating flood frequencies and magnitudes 

(e.g., storm surge analyses) of extreme events? Should uncertainty analyses be included 

for all flood assessments? 

• How can peer review strategies be used in PFHA? 

• How should flood analysts interact with PRA specialists for incorporating probabilistic 

estimates of extreme flood events in risk assessments? 

Information Needs: 

• Explain the concepts of probabilistic risk assessment as used in evaluating the safety of 

major engineered structures such as nuclear power plants, dams and levees. 

• Relationship between natural and anthropogenic systems, and probabilistic estimates of 

external hazards (i.e., extreme flooding events) within a performance-based, risk-informed 

assessment. 

• Discuss the estimation of hydrologic flood frequencies for these risk assessments. 
6 

• Review existing hydrologic frequency analysis methods and possible way to extend them. 

• Explain the nature of uncertainties in the probabilistic risk assessments, and how they are 

considered in a decision-making context. 

• Review strategies presently used in probabilistic hazard assessments to explore possible 

parallels for establishing a Probabilistic Flood Hazard Assessment (PFHA) strategy that 

augments current approaches for estimating Design Basis Floods. 

• Focus on extreme flood events and hazards for rivers, oceans, lakes, and site flooding due 

to local intense precipitation as identified in NRC’s guidance (i.e., NUREG-0800, Standard 

Review Plan for the Review of Safety Analysis Reports for Nuclear Power Plants: LWR 

Edition). 

 

• Discuss relationship between deterministic methods presently used, and evolving 

probabilistic approaches (e.g., NUREG/CR-7046, “Design-Basis Flood Estimation for Site 

Characterization at Nuclear Power Plants in the United States of America”). 

• Explore issues dealing with hydrometeorological event frequency, magnitude, duration and 

areal distributions for assessing potential consequences within a PFHA. 

• Identify hydrologic hazard models and their potential usefulness in risk assessments. 

• Outline research needs for developing a probabilistic flood hazard assessment strategy for 

extreme flood events within a risk context. 

• Identify existing PFHA strategies, their applications and verification programs. 

Product 

 

A workshop proceedings will be developed and documented as a NRC NUREG/CP (conference 

proceeding) report. This NUREG/CP will document: the presenters’ extended abstracts and/or 

technical papers with references and URLs; panel discussion summaries, and principal 

observations and insights for consideration in developing future PFHA strategies. 

Workshop Organizing Committee 

Tom Nicholson, Richard Raione and Christopher Cook, NRC, Co-Chairs; John England and 

Tony Wahl, BoR; Mark Blackburn, DOE; Tony Cheesebrough and Joel Piper, DHS; Siamak 

Esfandiary, FEMA; Sam Lin and David Lord, FERC; Chandra Pathak, David Margo and Ty 

Wamsley, USACE; Timothy Cohn and Eric Geist, USGS; Donald Resio, University of North 

Florida; Joost Beckers, Deltares; Fernando Ferrante, Joe Kanney, Sunil Weerakkody, Jeff 

Mitman, Nathan Siu and Wendy Reed, NRC. 

Workshop Oversight Committee

Nilesh Chokshi, Deputy Director, NRC/NRO/DSEA; Doug Coe, Deputy Director, 

NRC/RES/RES; NRC Office and Division Directors to review the workshop development.
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Agenda 

Workshop on 

Probabilistic Flood Hazard Assessment 

(PFHA) 

___________________________________________________________________________________

Time: January 29 – 31, 2013, 8:30 a.m. – 6:30 p.m. (EST) 

Location: NRC Headquarters Auditorium, 11555 Rockville Pike, Rockville, MD 20852 

WebStreaming: http://video.nrc.gov

____________________________________________________________________________________

Tuesday, January 29, 2013 

8:30 a.m. Welcome and Introductions

 Brian Sheron, Director, NRC/RES 

 

8:35 Importance of Risk-Informed, Performance-Based Regulations 

 NRC Commissioner George Apostolakis 

9:00 Panel 1: Federal Agencies’ Interests and Needs in PFHA

 Co-Chairs: Nilesh Chokshi, NRC and Mark Blackburn, DOE 

9:10 NRC Staff Needs in PFHA.................................. Fernando Ferrante, NRC 

9:30 Probabilistic Hazard Assessment Approaches: Transferable Methods from 

Seismic Hazard ................................................ Annie Kammerer, NRC 

9:50 Reclamation Dam Safety PFHA Perspective.........................John England, BoR 

10:10 FERC Need for PFHA .....................................................David Lord, FERC 

10:30 Break 

10:40 American Nuclear Society Standards Activities to Incorporate Probabilistic 

 Approaches ......................................................................................... 

 ...............John D. Stevenson, chair of ANS-2.31; Ray Schneider, Westinghouse 

10:55 Panel 1 Discussion: 

 Moderators: Nilesh Chokshi, NRC and Mark Blackburn, DOE 

 Rapporteurs: Chris Cook, NRC (NRO) and Marie Pohida, NRC (NRO) 

 Panelists: Fernando Ferrante, Annie Kammerer and Charles Ader, NRC 

 John England, BoR 

 David Lord and Patrick Regan, FERC 
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Panel Questions

1. What are the roles of deterministic and probabilistic hazard analysis in determining a design 

basis and conducting a risk assessment? How should they complement each other? 

2. What is the status of PFHA? For which flood causing mechanisms PFHAs can be 

conducted? What improvements are needed for their use in a risk assessment? 

3. Given the inherent large uncertainties, how should these be dealt with? 

4. What are the impediments, if any, for other flood causing mechanisms to develop PFHA 

approaches? How they can be overcome? 

5. What are your perceptions about the utility and usefulness of a PFHA for your agency 

missions? 

6. Is formal expert interaction approach like SSHAC a viable approach for PFHA? What 

PFHA specific consideration should be applied? 

7. What are the roles of deterministic and probabilistic hazard analysis in determining a design 

basis and conducting a risk assessment? How should they complement each other? 

8. What is the status of PFHA? For which flood causing mechanisms PFHAs can be 

conducted? What improvements are needed for their use in a risk assessment? How can 

uncertainties be reduced? 

9. What are the impediments, if any, for other flood causing mechanisms to develop PFHA 

approaches? How they can be overcome? 

10. What are your perceptions about the utility and usefulness of a PFHA for your agency 

missions? 

11. Is expert elicitation a viable approach for PFHA? 

12. Given the use of PFHA in the development of Design Basis Flooding determination, what is, 

or should be, the role of Beyond Design Basis Flooding in design and, if required how 

should it be determined? 

11:25 Lunch 

____________________________________________________________________________________

12:20 p.m. Panel 2: State-of-the-Practice in Identifying and Quantifying Extreme Flood 

 Hazards 

 Co-Chairs: Timothy Cohn, USGS and Will Thomas, Michael Baker, Jr., Inc. 

 

12:25 Overview and History of Flood Frequency in the United States.............................. 

 ..........................................................................Will Thomas, Michael Baker Corp. 

12:50 Keynote: Extreme Flood Frequency: Concepts, Philosophy, Strategies .............. 

 ................................................................Jery Stedinger, Cornell University 

1:15 Quantitative Paleoflood Hydrology..................................Jim O’Connor, USGS 

1:40 USACE Methods ............................................ Douglas Clemetson, USACE 

2:05: Hydrologic Hazard Methods for Dam Safety ........................John England, BoR 
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2:30 Panel 2 Discussion: 

 Moderators: Timothy Cohn, USGS and Will Thomas, Michael Baker, Jr., Inc. 

 Rapporteurs: Joseph Giacinto and Mark McBride, NRC (NRO); and 

 Randy Fedors, NRC (NMSS) 

 Panelists: Jery Stedinger, Cornell University 

 John England, BoR 

 Douglas Clemetson, USACE 

 Jim O’Connor, USGS 

Panel Questions 

 

1. How has the federal agency that you have represented approached the problem of 

estimating the risk of extreme floods? 

2. What is the historical basis for statistical estimation procedures employed by your agency? 

3. To what extent are the details of physical processes considered in determining risk of 

extreme floods? 

4. What criteria are employed in evaluating risk estimation procedures employed by your 

agency? 

5. How could data collection and availability be improved for your agency? 

6. What additional data and research are needed to reduce the uncertainty associated with 

extreme flood frequency estimates? 

7. To what extent do operational requirements limit your agency’s ability to employ accurate 

risk estimates? 

8. Do fundamentally different issues arise associated with estimating the 50%, 10%, 1%, 

0.01%, and 0.0001% exceedance events? 

9. Where are the greatest opportunities for improving the way that your agency estimates the 

risk of extreme floods? 

3:00 Break 

____________________________________________________________________________________

3:10 Panel 3: Extreme Precipitation Events

 Co-Chairs: John England, BoR and Chandra Pathak, USACE 

3:10 Introduction of Panel, Objectives, and Questions ................John England, BoR 

3:15 An Observation-Driven Approach to Rainfall and Flood Frequency Analysis Using 

High-Resolution Radar Rainfall Fields and Stochastic Storm Transposition......... 

...............................................................Daniel Wright, Princeton University 

3:40 Regional Precipitation Frequency Analysis and Extremes including PMP – 

Practical Considerations................Mel Schaefer, MGS Engineering Consultants 

4:05 High-Resolution Numerical Modeling As A Tool to Assess Extreme Precipitation 

Events........................................................................Kelly Mahoney, NOAA-ESRL

4:30 Precipitation Frequency Estimates for the Nation and Extremes – A Perspective 

 ............................................................................ Geoff Bonnin, NWS-OHD 
10 

4:50 Extreme Precipitation Frequency for Dam Safety and Nuclear Facilities – A 

 Perspective.......................................................................Victoria Sankovich, BoR 

5:15 Panel 3 Discussion: 

 Moderators: John England, BoR and Chandra Pathak, USACE 

 Rapporteurs: Nebiyu Tiruneh, NRC (NRO) and Brad Harvey, NRC (NRO) 

 Panelists: Daniel Wright, Princeton University 

 Mel Schaefer, MGS Engineering Consultants 

 Kelly Mahoney, NOAA-ESRL 

 Geoff Bonnin, NWS-OHD 

Panel Questions

1. Describe the advancements and improvements in extreme storm rainfall and precipitation 

observations and data bases over the past 30 years. Are there opportunities with radar, 

point observations, reanalysis data sets, and other data that can readily be utilized for 

extreme precipitation analyses, understanding, and applications for critical infrastructure? 

2. Outline the advances in statistical and data processing methods that can be used for 

extreme precipitation frequency estimation. These might include regional precipitation 

frequency, regionalization of parameters, Geographic Information Systems, climatological 

estimation (such as PRISM), and other areas. How might these tools be applied in practice, 

and include uncertainty estimates? 

3. Describe the advances in physical and numerical modeling of extreme precipitation (such as 

the Weather Research and Forecasting Model, WRF) that can give insights into the 

processes and magnitudes of extreme precipitation, including spatial and temporal 

distributions. How can these tools be applied to provide practical limits to extreme 

precipitation magnitudes, spatial and temporal storm patterns, transposition, and other 

extreme storm scaling? 

4. The National Research Council (1994) report on extreme precipitation suggested research 

in several areas, including: radar hydrometeorology and storm catalog, numerical modeling 

of extreme storms in mountainous regions, and estimating probabilities of extreme storm 

rainfalls. Are there existing technical barriers to fully probabilistic extreme storm estimation 

for assessing critical infrastructure, as opposed to Probable Maximum Precipitation? 

6:00 Public Attendees’ Questions and/or Comments 

6:30 Adjourn 

Wednesday, January 30, 2013 

8:30 a.m. Panel 4: Flood-Induced Dam and Levee Failures

 Co-Chairs: Tony Wahl, BoR and Sam Lin, FERC 

8:35 Risk-informed Approach to Flood-induced Dam and Levee Failures...................

................................................David Bowles, RAC Engineers & Economists 
11 

9:00 Dutch Approach to Levee Reliability and Flood Risk ................................. 

 ..................................... Timo Schweckendiek, Deltares Unit Geo-engineering 

9:25 Risk-Informed Decision-Making (RIDM) Approach for Inflow Design Flood (IDF) 

 Selection and Accommodation for Dams: A Practical Application Case Study....... 

 ..................................................................................... Jason Hedien, MWH 

9:50 Break 

10:05 Incorporating Breach Parameter Estimation and Physically-Based Dam Breach 

 Modeling into Probabilistic Dam Failure Analysis...... ............ Tony Wahl, BoR

10:30 USACE Risk Informed Decision Framework for Dam and Levee Safety.............. 

...............................................................................David Margo, USACE 

10:45 Panel 4 Discussion: 

 Moderators: Tony Wahl, BoR and Sam Lin, FERC 

 Rapporteurs: Jacob Philip, NRC (RES); Hosung Ahn, NRC (NRO); and 

 Juan Uribe, NRC (NRR) 

 Panelists: Eric Gross, FERC, Chicago (Dam) 

 Timo Schweckendiek, Deltares Unit Geo-engineering (Levee) 

 Martin W McCann Jr., Stanford University (Dam/Levee) 

 David Margo, USACE (Dam/Levee) 

 Gregory Baecher, University of Maryland (Risk Analysis) 

 Jery Stedinger, Cornell University (Dam) 

 David Bowles, RAC Engineers & Economists (Dam/Levee) 

Panel Questions

1. What does history tell us about the probability of dam/levee failure from various causes? 

• Hydrologic/Hydraulic 

o Overtopping 

o Failure of spillways (concrete lined or earthen/natural rock) or outlet works during 

extreme floods 

o Seepage and piping 

• Mechanical/Operational 

2. What aspects of an event need to have probabilities assigned? 

• Probability of failure itself 

• Probability of flooding of a given severity 

3. There are many different triggers for failure. For example, variability of soils and slope 

protection of embankment dams can be an extreme source of uncertainty. How are the 

failure thresholds reasonably assumed such as the overtopping depth on an embankment 

dam based on its existing conditions? 

4. What can modeling do to help us understand probabilistic aspects of dam/levee failure? 

5. What roles can dam and levee failures play in PFHA or PRA and how can they be 

integrated? (i.e. make an inventory of relevant issues) 

6. Is system behavior (as will be shown in Timo’s presentation) relevant for PFHA? 

7. What level of detail is appropriate for levee reliability modeling in PFHA? 
12 

8. What are the roles of probabilistic safety assessment and probabilistic safety criteria for 

hydrologic safety of dams? 

9. What is different about dam/levee failure impact on downstream as compared to other 

causes of flooding? For example, dam failure releases large quantities of sediment as well as 

water, so debris-flow considerations may be more important than for other flooding causes. 

10. Do we endorse use of probabilistic methods and risk analysis for the following reasons? 

• Less conservatism than modifying dams for extreme loads 

• Levels playing field and considers relative ranking of all PFMs at a facility 

• Provides a means of prioritizing future studies and modifications 

11. Are the below potential improvements and research needs or more? 

• Spillway debris issues 

• Spillway gate failure issues 

• River system failures (coordination with other owners) 

12. What comes after failure? There are, such as: What failure-induced flood parameters or 

consequences may be important for assessing the safety of assets besides water depth or 

flow velocities? (e.g. wave impact, scour holes affecting foundations etc.) 

11:35 Lunch 

____________________________________________________________________________________

12:35 p.m. Panel 5: Tsunami Flooding 

 Co-Chairs: Eric Geist, USGS-Menlo Park, CA and Henry Jones, NRC 

12:40 Probabilistic Tsunami Hazard Analysis ...................... Hong Kie Thio, URS Corp. 

1:05 Recent advances in PTHA methodology................................................................. 

 .............................................................Randy LeVeque, University of Washington 

1:30 Landslide Tsunami Probability ...........................................Uri ten Brink, USGS 

1:55 Modeling Generation and Propagation of Landslide Tsunamis............................... 

 .......................................................................................................Pat Lynett, USC 

2:20 Panel 5 Discussion: 

 Moderators, Eric Geist, USGS and Henry Jones, NRC 

 Rapporteurs: Mark McBride, NRC (NRO) and Randy Fedors, NRC (NMSS) 

 Panelists: Randy LeVeque, University of Washington 

 Uri ten Brink, USGS 

 Pat Lynett, USC 

 Annie Kammerer, NRC 

 Frank González, University of Washington 

 Yong Wei, NOAA/PMEL 

 Tom Parsons, USGS 

 Chuck Real, California Geological Survey 

Panel Questions

1. What input parameters/uncertainties are important to include in PTHA for extreme 

tsunamis? 
13 

2. What are the appropriate probability distributions (as determined by statistical testing and 

model selection) that define uncertainty of input parameters for PTHA? What databases 

exists for earthquakes and landslides to test model distributions and assess uncertainty. 

3. What is the best framework (e.g., logic-tree) for including landslides tsunamis into PTHA, 

given the inherent uncertainties associated with the phenomena? (follow-up to the 2011 

NRC/USGS Woods Hole workshop) 

4. How does a landslide composed of multiple failures generate a tsunami? By constructive 

interference of many small failures, by only failure of a dominant large cohesive block, or by 

hydraulic jump of thick coalesced debris flows from a large area? 

5. How do PTHA techniques currently used in the U.S. differ from implemented in Japan, 

especially with regard to extreme tsunami hazards? 

6. What are the fundamental needs of improving PTHA (e.g. seafloor mapping/sampling, 

paleoseismic/paleotsunami deposit analysis, validation of modeled current velocities, etc.), 

and how should the U.S. move forward to make these improvements (organizationally and 

funding)? 

1. How should the NRC and other organizations work towards verification and consistency of 

PTHA methods? 

2:50 Break 

____________________________________________________________________________________

3:00 Panel 6: Riverine Flooding 

 Co-Chairs: Will Thomas, Michael Baker, Jr., Inc. and 

 Rajiv Prasad, Pacific Northwest National Laboratory 

3:05 Riverine PFHA for NRC Safety Reviews – Why and How?...Rajiv Prasad, PNNL 

3:30 Flood Frequency of a Regulated River - the Missouri River............................ 

 ....................................................................Douglas Clemetson, USACE 

3:55 Extreme Floods and Rainfall-Runoff Modeling with the Stochastic Event Flood 

 Model (SEFM)......................................................Mel Schaefer, MGS Engineering 

4:20 Use of Stochastic Event Flood Model and Paleoflood Information to Develop 

Probabilistic Flood Hazard Assessment for Altus Dam,Oklahoma..................... 

 .......................................................................... Nicole Novembre, BoR 

4:45 Paleoflood Studies and their Application to Reclamation Dam Safety.................. 

............................................................................. Ralph Klinger, BoR 

5:10 Panel 6 Discussion: 

 Moderators: Will Thomas, Michael Baker, Jr., Inc. and Rajiv Prasad, PNNL 
14 

 Rapporteurs: Peter Chaput, NRC (NRO) and Jeff Mitman, NRC (NRR) 

 Panelists: Douglas Clemetson, USACE 

 Nicole Novembre, BoR 

 Ralph Klinger, BoR 

 Jery Stedinger, Cornell University 

 Mel Schaefer, MGS Engineering 

Panel Questions: 

 

1. Runoff simulation-based approaches for riverine PFHA could use either event-based or 

continuous model simulations. What are the strengths and weaknesses of the two 

approaches? What R&D is needed to address weakness/gaps? 

2. How can we best combine flood frequency analysis approaches (including historical 

paleoflood information) with simulation approaches to estimate magnitudes and frequencies 

for extreme flooding events? Is there additional R&D needed in this area? 

3. A full-blown PFHA that includes both sensitivity analysis and uncertainty analysis may be 

very demanding in terms of computational resources (i.e. large numbers of simulations may 

be needed). What approaches are available to provide useful results while minimizing the 

number of simulations that need to be performed? 

4. A full-blown PFHA will also be demanding in terms of workload for the analyst. What 

software tools are available to assist in streamlining the workflow? Is there a significant 

need for new/improved tools? If so, what is the most critical need? 

5. What approaches are available for handling correlations in events/processes that combine 

to generate extreme riverine floods? 

6. In a full-blown PFHA using runoff simulation approach, probability distributions of 

hydrometeorologic inputs and model parameters are needed. What methods or approaches 

are available to estimate these probability distributions? 

7. Uncertainty in runoff simulations can arise because of uncertainties in inputs, model 

parameters, and the model structure. What methods or approaches are available to 

estimate these uncertainties? 

8. How do you validate a runoff model for extreme floods? 

9. How do you think non-stationarity (that has already occurred in the past, e.g., land-use 

changes and may occur in the future, e.g., global climate change) can be accounted for in a 

runoff simulation approach for PFHA? 

6:00 Public Attendees’ Questions and/or Comments 

6:30 Adjourn 
15 

Thursday, January 31, 2013 

8:30 a.m. Panel 7: Extreme Storm Surge for Coastal Areas

 Co-Chairs: Donald Resio, Univ. of N. Florida and Ty Wamsley, USACE 

8:35 Coastal Flood Hazard in the Netherlands......................Joost Beckers, Deltares 

9:00 Recent Work and Future Directions in Coastal Surge Modeling within NOAA....... 

 .............................................................................. Stephen Gill, NOAA 

9:25 FEMA’s Coastal Flood Hazard Analyses in the Atlantic Ocean and Gulf of 

Mexico..................................................................Tucker Mahoney, FEMA 

9:50 Modeling System for Applications to Very-Low Probability Events and Flood 

Response..................................................................Ty Wamsley, USACE 

10:15 Break 

10:30 Coastal Inundation Risk Assessment .......................................................... 

..................................................Jen Irish, Virginia Polytechnic Institute (VPI) 

10:55 Panel 7 Discussion: 

Moderators: Donald Resio and Ty Wamsley 

 Rapporteurs: Mark Fuhrmann, NRC (RES) and Ferrando Ferrante, NRC (NRR) 

 Panelists: Joost Beckers, Deltares 

 Stephen Gill, NOAA 

 Tucker Mahoney, FEMA 

 Jen Irish, VPI 

Panel Questions 

1. Relative to probabilistic hazard prediction, what are some significant advances that your 

group/organization has made in the last few years or expects to complete in the near future? 

2. Relative to probabilistic hazard prediction for NRC, what do you feel could be an important 

contribution by your group/organization? 

3. How should we quantify uncertainty for probabilistic forecasting? 

4. What do you feel are some significant shortcomings/lacks of knowledge that could hamper 

our probabilistic hazard forecasting for the NRC? 

5. How can we quantify the effects of upper limits on probabilistic hazards? 

11:20 Break 

____________________________________________________________________________________

11:25 Panel 8: Combined Events Flooding 

 Co-Chairs: David Margo, USACE and Joost Beckers, Deltares 
16 

11:30 Combined Events in External Flooding Evaluation for Nuclear Plant Sites........... 

 .................................................................... Kit Ng, Bechtel Power Corp. 

11:45 Assessing Levee System Performance Using Existing and Future Risk Analysis 

 Tools ........................................................................Chris Dunn, USACE 

12:00 Seismic Risk of Co-Located Critical Infrastructure Facilities – Effects of 

Correlation and Uncertainty..................... Martin McCann, Stanford University 

12:15 p.m. Lunch 

1:00 Panel 8: Combined Events Flooding (continued)

 

1:00 Storm Surge - Riverine Combined Flood Events.............Joost Beckers, Deltares 

1:15 Combining Flood Risks from Snowmelt, Rain, and Ice – The Platte River in 

 Nebraska ....................................................... Douglas Clemetson, USACE 

1:30 Human, Organizational, and Other Factors Contributing to Dam Failures............ 

 ........................................................................... Patrick Regan, FERC 

1:45 Panel 8 Discussion:

 Moderators: David Margo and Joost Beckers, Deltares 

 Rapporteurs: Michelle Bensi, NRC (NRO) and Jeff Mitman, NRC (NRR) 

 Panelists: Kit Ng, Bechtel Power Corporation 

 Chris Dunn, USACE 

 Martin McCann, Stanford University 

 Joost Beckers, Deltares 

 Douglas Clemetson, USACE 

 Pat Regan, FERC 

Panel Questions 

1. How can a risk informed framework be utilized to identify plausible event combinations that 

are relevant to the flood hazard assessment? 

2. How can we estimate the probabilities and risks associated with event combinations? 

2:30 Break 

____________________________________________________________________________________

2:35 Panel 9: Summary of Significant Observations, Insights, and 

 Identified Opportunities for Collaboration on PFHA 

 Panel Co-Chairs: Tom Nicholson and Christopher Cook, NRC 

 Rapporteurs: Wendy Reed, NRC (RES) and Jacob Philip, NRC (RES) 

2:40 Panel 1 Co-Chairs and Rapporteurs 
17 

2:55 Panel 2 Co-Chairs and Rapporteurs 

3:10 Panel 3 Co-Chairs and Rapporteurs 

3:25 Break 

3:40 Panel 4 Co-Chairs and Rapporteurs 

3:55 Panel 5 Co-Chairs and Rapporteurs 

4:10 Panel 6 Co-Chairs and Rapporteurs 

4:25 Panel 7 Co-Chairs and Rapporteurs 

4:40 Panel 8 Co-Chairs and Rapporteurs 

4:55 Workshop and Public Attendees’ Questions and/or Comments 

6:00 Adjourn 

__________________________________________________________________________

 
18 

[page left intentionally blank] 
19 

ABSTRACTS 

 
20 

[page left intentionally blank] 
21 

Panel 1: Federal Agencies’ Interests and Needs in PFHA 

Co-Chairs: Nilesh Chokshi, NRC and Mark Blackburn, DOE 

Rapporteurs: Chris Cook, NRC (NRO) and Marie Pohida, NRC (NRO) 

Presenters: Commissioner George Apostolakis, NRC 

 Fernando Ferrante, NRC 

 Annie Kammerer, NRC 

 John England, BoR 

 David Lord, FERC 

 John Stevenson, ANS 2.8 Working Group 

 Ray Schneider, Westinghouse 

Panelists: Fernando Ferrante, Annie Kammerer and Charles Ader, NRC 

 John England, BoR 

 David Lord and Patrick Regan, FERC 

 
22 

U. S. Nuclear Regulatory Commission Staff Needs in Probabilistic 

Flood Hazard Assessment 

Fernando Ferrante, Ph. D. 

U.S. Nuclear Regulatory Commission, Washington DC, USA 

The US Nuclear Regulatory Commission (USNRC) is an independent federal agency whose 

mission is to license and regulate the Nation’s civilian use of byproduct, source, and special 

nuclear materials to ensure the adequate protection of public health and safety, promote the 

common defense and security, and protect the environment [1]. In order to support its mission, 

the USNRC performs licensing, rulemaking, incidence response, and oversight activities to 

ensure the safe operation of critical infrastructure, such as large operating commercial nuclear 

reactors, research and test reactors, and nuclear fuel cycle facilities. 

Specific parts in Title 10 of the Code of Federal Regulations [2], which prescribe the 

requirements under the authority of the USNRC, also include consideration of natural 

phenomena such as floods. For example, for commercial nuclear reactors, principal design 

criteria establishing design requirements for structures, systems, and components that provide 

reasonable assurance that the facility can withstand the effects of natural phenomena without 

undue risk to the health and safety of the public are described [3]: 

(1) Appropriate consideration of the most severe of the natural phenomena that have been 

historically reported for the site and surrounding area, with sufficient margin for the 

limited accuracy, quantity, and period of time in which the historical data have been 

accumulated, 

(2) appropriate combinations of the effects of normal and accident conditions with the 

effects of the natural phenomena and 

(3) the importance of the safety functions to be performed. 

Significant regulatory guidance and research has been developed in order to address the 

evaluation of various flooding phenomena and mechanisms such as extreme meteorological 

events (e.g. severe storms, tides, and waves), seiche/tsunami, and dam failures [4 - 9]. 

Understanding the risks posed to the facilities regulated by the USNRC is also important in 

terms of resource allocation (e.g. prioritization of inspections, incident response) and emergency 

planning. It is recognized that, for different natural phenomena, the maturity of available 

methodologies and data for assessing the likelihood of occurrence of hazards that may 

challenge plant safety varies significantly from hazard to hazard and can involve wide 

uncertainty in both the intensity and frequency of the event. 

The USNRC has spent significant resources to develop and incorporate the use of risk 

assessment tools for risk-informed decision-making in a variety of applications related to 

regulatory licensing and oversight [10]. The drivers prompting the staff to use these tools include 

a policy statement on the use of probabilistic risk assessment (PRA) in regulatory activities [11] 

as well as guidance for specific activities (e.g., [12]) where quantitative risk assessments may 

be used in risk-informed regulatory actions. 

In the area of oversight, the USNRC oversees licensees’ safety performance through 

inspections, investigations, enforcement, and performance assessment activities, in which risk 
23 

tools and risk criteria are routinely applied. In particular, the USNRC has established the 

Reactor Oversight Process (ROP) which is the Agency’s program to inspect, measure, and 

assess the safety performance of commercial nuclear power plants and to respond to any 

decline in performance [13]. This includes determining the safety significance of inspection 

findings through a number of risk-informed activities, including the use of PRA models for 

individual reactor that are developed and maintained by Idaho National Laboratory (INL) for use 

by the USNRC [14]. Typically, these models consider a number of potential events that may 

challenge plant safety such as loss of AC power necessary to operate critical equipment and/or 

the loss of capability to cool the nuclear reactor core. As the characteristics of events that may 

challenge plant safety are identified, the capacity of the safety systems designed to protect 

critical functions is evaluated for the conditional probability of failure, thus resulting in an overall 

measure of the available protection with respect to the likelihood of the intervening event. One 

of the commonly used risk measures in PRA models is the core damage frequency (CDF), a 

measure of the likelihood of severe damage to the nuclear fuel used for heat generation in US 

commercial nuclear reactors. 

In many cases, the models are based on events occurring internal to the plant (e.g., random 

equipment failure, operator errors) while less focus has historically been placed on detailed 

modeling of extreme natural phenomena, although some studies evaluating the risk contribution 

of flooding events exist [15 - 21]. Typical CDF results for overall plant risk obtained in USNRC 

risk analysis range from an annualized core damage frequency of 1E-4/year to 1E-6/year for all 

contributing risk scenarios. In the hydrologic community, it has long been recognized that 

estimating the annualized frequency of severe floods tends to be restrained to a great extent by 

the historical record available, with significant effort made in the development of methods and 

approaches to extend frequency estimates beyond typically observed events [22]. The result is 

that there exists significant uncertainty associated to the ranges of interest of USNRC risk 

applications such as the ones described above, where severe flood estimates may range from 

1E-3/year to 1E-6/year and below [23], depending on the quantity and quality of data available 

as well as the refinement of the methodology used to derive such estimates. 

The USNRC has been engaged in risk assessment of natural hazards, such as floods, well 

before the 9.0-magnitude earthquake that struck Japan 2011 on March 11, 2011 that eventually 

lead to extensive damage to the Fukushima Dai-ichi nuclear site. However, the formation of 

Near-Term Task Force (NTTF) to review insights from this event [24] and the subsequent 

activities [25 – 27] that include a reevaluation of potential flooding hazards for nuclear facilities 

regulated by the USNRC have re-focused the review and potential enhancement of the 

treatment and evaluation of very low probability/high consequence events with respect to critical 

infrastructure. 

Coupled with the already existing risk framework and tools used in licensing and oversight for 

commercial nuclear reactors as well as other applications regulated by the USNRC, a 

probabilistic flood hazard assessment (PFHA) effort could provide significant input in the area of 

flood hazard characterization, and the probabilistic treatment of flood protection and mitigation 

strategies with respect to PRAs. In particular, there is a strong interest for further development 

in the following areas in applications related to the risk assessment of nuclear facilities licensed 

and regulated by the NRC: 

• Development of methods to consistently estimate annualized flood frequencies in the 

ranges of interest of USNRC applications with respect to potential contributors to CDF, 

including extrapolations beyond the available historical record. 
24 

• Characterization of a broader spectrum of flood risk contributors, rather than focusing on 

deterministically-derived “worst” case scenarios, in order to capture the impact of 

extreme events as well as less severe but more frequent floods. 

• Consideration of the feasibility of screening methodologies that take into account the 

range of locations of facilities licensed and regulated by the USNRC (i.e., with distinct 

hydrological, meteorological, and geographical characteristics) to identify sites for which 

certain flooding mechanisms may be more applicable and therefore may require more 

detailed risk assessment considerations. 

• Risk assessment of dam failures (including downstream dam failures that may affect the 

availability of water from a large body of water relied on to cool various thermal loads 

during plant operations) on safe operations of nuclear facilities. This would include 

probabilistic treatment of various individual failure mechanisms, such as overtopping, 

internal erosion, spillway and hydro-turbine failures, seismic events, and credible 

combination of events; within the frequency range of interest to USNRC applications. 

• Possible probabilistic treatment of flood protection structures and barriers (including 

temporary barriers), while considering potential for degradation from debris impact, 

erosion, and other effects during severe flooding events. 

• Development of a probabilistic assessment of the capacity of mechanical, structural, and 

electrical systems relied on for safe operation of nuclear facilities to withstand flooding 

impacts, similar to fragility curves typically associated with seismic risk assessments 

(e.g., conditional probability of failure with respect to a specific loading or flood level). 

• Feasibility of operator manual actions during extreme flooding events in a probabilistic 

framework, which may be associated with actions such as the installation of flooding 

protection (e.g., floodgates), construction of barriers (e.g., sandbag barriers), and other 

actions. 

References 

[1] U.S. Nuclear Regulatory Commission. "Information Digest 2012 - 2013," NUREG-1350, 

Volume 24. August 2012. 

[2] U.S. Code of Federal Regulations, Parts 1 - 199, Title 10, “Energy.” 

[3] U.S. Code of Federal Regulations, “Domestic Licensing of Production and Utilization 

Facilities,” Part 50, Appendix A, General Design Criterion 2, Title 10, “Energy.” 

[4] U.S. Nuclear Regulatory Commission. "Standard Review Plan for the Review of Safety 

Analysis Reports for Nuclear Power Plants: LWR Edition," NUREG-0800, Section 2.4.2: Floods, 

Rev. 4. 

[5] U.S. Nuclear Regulatory Commission. "Standard Review Plan for the Review of Safety 

Analysis Reports for Nuclear Power Plants: LWR Edition," NUREG-0800, Section 2.4.3: 

Probable Maximum Flood (PMF) on Streams and Rivers, Rev. 4. 
25 

[6] U.S. Nuclear Regulatory Commission. "Standard Review Plan for the Review of Safety 

Analysis Reports for Nuclear Power Plants: LWR Edition," NUREG-0800, Section 2.4.4: 

Potential Dam Failures, Rev. 3. 

[7] U.S. Nuclear Regulatory Commission. "Standard Review Plan for the Review of Safety 

Analysis Reports for Nuclear Power Plants: LWR Edition," NUREG-0800, Section 2.4.5: 

Probable Maximum Surge and Seiche Flooding, Rev. 3. 

[8] U.S. Nuclear Regulatory Commission. "Standard Review Plan for the Review of Safety 

Analysis Reports for Nuclear Power Plants: LWR Edition," NUREG-0800, Section 2.4.6: 

Probable Maximum Tsunami Hazards, Rev. 3. 

[9] U.S. Nuclear Regulatory Commission. "Design-Basis Flood Estimation for Site 

Characterization at Nuclear Power Plants in the United States of America," NUREG/CR-7046. 

November 2011. ADAMS Accession No. ML11321A195. 

[10] U.S. Nuclear Regulatory Commission. "A Proposed Risk Management Regulatory 

Framework - A report to NRC Chairman Gregory B. Jaczko from the Risk Management Task 

Force," April 2012. ADAMS Accession No. ML12109A277. 

[11] U.S. Nuclear Regulatory Commission. "Use of Probabilistic Risk Assessment Methods in 

Nuclear Activities: Final Policy Statement,” Federal Register, Vol. 60, p. 42622 (60 FR 42622), 

August 16, 1995. 

[12] U.S. Nuclear Regulatory Commission. "An Approach For Using Probabilstic Risk 

Assessment In Risk-Informed Decisions On Plant-Specific Changes To The Licensing Basis," 

Regulatory Guide 1.174, Rev. 1. July 1998. ADAMS Accession No. ML003740133. 

[13] U.S. Nuclear Regulatory Commission. "Reactor Oversight Process," NUREG-1649, Rev. 4, 

December 2006. ADAMS Accession No. ML070890365 

[14] K. D. Russell et al., “Systems Analysis Programs for Hands on Integrated Reliability 

Evaluations (SAPHIRE) Version 5.0,” NUREG/CR-6116. September 2008 

[15] U.S. Nuclear Regulatory Commission, “Perspectives Gained From the Individual Plant 

Examination of External Events (IPEEE) Program – Volume 1,” NUREG-1742. April 2002. 

ADAMS Accession No. ML021270122. 

[16] U.S. Nuclear Regulatory Commission. "Shutdown Decay Heat Removal Analysis of a 

Babcock and Wilcox Pressurized Water Reactor," NUREG/CR-4713. March 1987. 

[17] U.S. Nuclear Regulatory Commission. "Shutdown Decay Heat Removal Analysis of a 

Westinghouse 2-Loop Pressurized Water Reactor," NUREG/CR-4458. March 1987. 

[18] U.S. Nuclear Regulatory Commission. "Shutdown Decay Heat Removal Analysis of a 

General Electric BWR3/Mark I," NUREG/CR-4448. March 1987. 

[19] U.S. Nuclear Regulatory Commission. "Shutdown Decay Heat Removal Analysis of a 

Combustion Engineering 2-Loop Pressurized Water Reactor," NUREG/CR-4710. August 1987. 
26 

[20] U.S. Nuclear Regulatory Commission. "Shutdown Decay Heat Removal Analysis of a 

Westinghouse 3-Loop Pressurized Water Reactor,” NUREG/CR-4762. March 1987. 

[21] U.S. Nuclear Regulatory Commission. "Shutdown Decay Heat Removal Analysis of a 

General Electric BWR4/Mark I," NUREG/CR-4767. July 1987. 

[22] US Bureau of Reclamation, “Guidelines for Evaluating Hydrologic Hazards,” June 2006. 

[23] Jeff Harris et al., “Estimating Probability of Extreme Events,” World Environmental and 

Water Resources Congress 2009: Great Rivers, ASCE. 2009 

[24] U.S. Nuclear Regulatory Commission. “Enhancing Reactor Safety in the 21st Century – The 

Near-Term Task Force Review of Insights From The Fukushima Dai-Ichi Accident,” July 2011. 

ADAMS Accession No. ML111861807 

[25] U.S. Nuclear Regulatory Commission. "Proposed Orders and Requests For Information In 

Response To Lessons Learned From Japan's March 11, 2011, Great Tohoku Earthquake And 

Tsunami," SECY-12-0025. February 22, 2012. ADAMS Accession No. ML12039A103. 

[26] Request for Information Pursuant to Title 10 of the Code of Federal Regulations 

50.54(f) regarding Recommendations 2.1, 2.3, and 9.3, of the Near-Term Task Force 

Review of Insights from the Fukushima Dai-ichi Accident. March 12, 2012. ADAMS 

Accession No. ML12053A340. 

[27] U.S. Nuclear Regulatory Commission. “Guidance for Performing the Integrated Assessment 

for Flooding - Draft Interim Staff Guidance,” JLD-ISG-2012-05, Revision 0 (Draft Issue for Public 

Comment). ADAMS Accession No. ML12235A319. 

 
27 

Probabilistic Hazard Assessment Approaches: 

Transferable Methods from Seismic Hazard 

Annie M Kammerer1

1

US NRC, Office of New Reactors/Office of Nuclear Regulatory Research, 

Rockville, MD 20852 

Quantitative assessment of all natural hazards share common attributes and challenges. These 

include the need to determine the best estimate and uncertainty of the hazard levels, limited 

data, high levels of uncertainty, and the need to include expert judgment in the assessment 

process. Over the last several decades, approaches for assessing seismic hazard have 

matured and current approaches are transferable to other types of hazard. While the level of 

uncertainty in seismic hazard remains high, particularly in low to moderate seismicity regions, 

highly structured methods of expert interaction and model development have been developed 

and applied with success. In 1997, the Senior Seismic Hazard Analysis Committee (SSHAC) 

developed a structured, multilevel assessment framework and process (the “SSHAC process”), 

described in NUREG/CR-6372, “Recommendations for Probabilistic Seismic Hazard Analysis: 

Guidance on Uncertainty and Use of Experts,” that has since been used for numerous natural 

hazard studies since its publication. In 2012, the NRC published NUREG-2117, “Practical 

Implementation Guidelines for SSHAC Level 3 and 4 Hazard Studies,” after studying the 

experience and knowledge gained in the application of the original guidance over the last 

15 years. NUREG-2117 provides more detailed guidelines consistent with the original 

framework described in NUREG/CR-6372, which is more general and high level in nature. 

NUREG-2117 provides an extensive discussion of the Level 3 process, which is well suited to 

the assessment of other natural hazards. 

When seismic hazard assessments are conducted for critical facilities such as nuclear power 

plants, the judgments of multiple experts are required to capture the complete distribution of 

technically defensible interpretations (TDIs) of the available earth science data. The SSHAC 

process provides a transparent method of structured expert interaction entirely focused on 

capturing the center, body, and range (CBR) of the full suite of TDIs of the available data. The 

goal is not to determine the single best interpretation; rather, it is to develop and integrate all 

TDIs into a logic tree framework wherein the weights of the various branches are consistent with 

the level to which the data and information available supports the interpretation. This approach 

leads to greater assurance that the “true” hazard at a site is captured within the breadth of the 

probabilistic seismic hazard assessment (PSHA) results. 

To achieve this, a study following in the SSHAC process goes through a series of steps that can 

be separated into evaluation and integration phases. The fundamental goal of the SSHAC 

Level 3 process is to properly carry out and completely document the activities of evaluation and 

integration, defined as follows: 
28 

Evaluation: The consideration of the complete set of data, models, and methods proposed by 

the larger technical community that are relevant to the hazard analysis. 

Integration: Representing the CBR of TDIs in light of the evaluation process (i.e., informed by 

the assessment of existing data, models, and methods). 

As discussed in detail in NUREG 2117, the process includes a number of well-defined roles for 

participants, as well as three required workshops, each with a specific objective. The evaluation 

process starts by the Technical Integrator (TI) team identifying (with input from resource and 

proponent experts) the available body of hazard-relevant data, models, and methods―including 

all those previously produced by the technical community―to the extent possible. This body of 

existing knowledge is supplemented by new data gathered for the study. The first workshop is 

focused on with the identification of hazard-relevant data, models, and methods. The TI team 

then evaluates these data, models, and methods and documents both the process by which this 

evaluation was undertaken and the technical bases for all decisions made regarding the quality 

and usefulness of these data, models, and methods. This evaluation process explicitly includes 

interaction with, and among, members of the technical community. The expert interaction 

includes subjecting data, models, and methods to technical challenge and defense. Workshop 

#2 provides a forum for proponents of alternative viewpoints to debate the merits of their 

models. The successful execution of the evaluation is confirmed by the concurrence of the 

Participatory Peer Review Panel (PPRP) that the TI team has provided adequate technical 

bases for its conclusions about the quality and usefulness of the data, models, and methods, 

and has adhered to the SSHAC assessment process. The PPRP will also provide guidance on 

meeting the objective of considering all of the views and models existing in the technical 

community. 

Informed by this evaluation process, the TI team then performs an integration process that may 

include incorporating existing models and methods, developing new methods, and building new 

models. The objective of this integration process is to capture the CBR of TDIs of the available 

data, models, and methods. The technical bases for the weights on different models in the final 

distribution, as well as the exclusion of any models and methods proposed by the technical 

community, need to be justified in the documentation. Workshop #3 provides an opportunity for 

the experts to review hazard-related feedback on their preliminary models and to receive 

comments on their models from the PPRP. To conclude the project satisfactorily, the PPRP will 

also need to confirm that the SSHAC assessment process was adhered to throughout and that 

all technical assessments were sufficiently justified and documented. 

References: 

U.S. Nuclear Regulatory Commission, “Recommendations for Probabilistic Seismic Hazard 

Analysis: Guidance on Uncertainty and Use of Experts,” NUREG/CR-6372, Washington, DC, 

1997. 
29 

U.S. Nuclear Regulatory Commission, “A Performance-Based Approach to Define the 

Site-Specific Earthquake Ground Motion,” Regulatory Guide 1.208, Washington, DC, 

March 2007. 

U.S. Nuclear Regulatory Commission, “Practical Implementation Guidelines for SSHAC Level 3 

and 4 Hazard Studies,” NUREG-2117, Washington, DC, 2012. 

 
30 

Bureau of Reclamation Dam Safety 

Probabilistic Flood Hazard Analysis Perspective 

John F. England, Jr.1 and Karen M. Weghorst1

1

U.S. Department of Interior, Bureau of Reclamation 

Flood Hydrology and Consequences Group, 86-68250 

Technical Service Center, Denver, CO 80225 

The Bureau of Reclamation uses risk analysis to assess the safety of dams, recommend safety 

improvements, and prioritize expenditures (Reclamation, 2011). Reclamation has been using 

risk analysis as the primary support for dam safety decision-making for over 15 years, and has 

developed procedures to analyze risks for a multitude of potential failure modes. By definition, 

“risk” is the product of the likelihood of an adverse outcome and the consequences of that 

outcome. The likelihood of an adverse outcome is the product of the likelihood of the loading 

that could produce that outcome and the likelihood that the adverse outcome would result from 

that loading. Risk analysis, from a hydrologic perspective, requires an evaluation of a full range 

of hydrologic loading conditions and possible dam failure mechanisms tied to consequences of 

a failure. 

The Bureau of Reclamation conducts risk analysis at different levels, from screening level 

analyses performed by an individual (with peer review) during a Comprehensive Facility Review 

(CFR), to full blown facilitated team risk analyses, which include participation by “field” 

personnel. One key input to a risk analysis is the loading characteristic; this is generally in the 

form of hydrologic hazard curves or seismic hazard curves for floods and earthquakes. 

Manuals, guidelines, and practical reference material detailing risk analysis methodology for 

dam safety applications based on Reclamation’s experience are available (Reclamation, 2011). 

This presentation provides an overview of the Dam Safety Act, Reclamation’s risk process, and 

risk reduction. Risk analysis at the Bureau of Reclamation has evolved over the years and will 

continue to evolve. 

References: 

Bureau of Reclamation (1999) A Framework for Characterizing Extreme Floods for Dam Safety 

Risk Assessment. Prepared by Utah State University and Bureau of Reclamation, Denver, CO, 

November, 67 p. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/LoganWorkshop.pdf

Bureau of Reclamation (2002) Interim Guidelines for Addressing the Risk of Extreme Hydrologic 

Events. Bureau of Reclamation, Denver, CO, August, 3 p. (England, J.F., principal author). 

ftp://ftp.usbr.gov/jengland/Dam_Safety/pmf_risk_interim_guidance.pdf

Bureau of Reclamation (Reclamation) (2011), Dam Safety Public Protection Guidelines, A Risk 

Framework to Support Dam Safety Decision-Making, Bureau of Reclamation, Denver, Colorado, 

31 p. 

http://www.usbr.gov/ssle/damsafety/documents/PPG201108.pdf

Other reports related to Reclamation's Public Protection Guidelines are here: 
31 

http://www.usbr.gov/ssle/damsafety/references.html

Bureau of Reclamation (Reclamation) (2011) Dam Safety Risk Analysis Best Practices Training 

Manual. Bureau of Reclamation, in cooperation with US Army Corps of Engineers, Denver, CO, 

Aug., version 2.2 

http://www.usbr.gov/ssle/damsafety/Risk/methodology.html

 
32 

FERC Need for Probabilistic Flood Hazard Analysis (PFHA) 

Journey From Deterministic to Probabilistic 

David W. Lord, P.E.1, 

Abstract 

The Federal Energy Regulatory Commission’s (FERC) has a well developed program2

 to 

calculate a deterministic value for the Probable Maximum Flood (PMF) based on the Probable 

Maximum Precipitation (PMP). The PMF determinations are based on the precipitation 

estimates in the applicable Hydro Meteorological Reports (HMR) or increasingly from sitespecific or state wide3

 studies. These site specific or state wide studies use the general 

concepts contained in the HMRs and update and applies them to smaller areas. The 

application of these updated PMP studies have taken out much of the conservatism inherent in 

the HMR estimates of PMP as they have reduced the PMP estimates up to 56 percent4

. The 

significant reduction of historical PMP estimates raises concern on the reasonableness of these 

new estimates. 

Another problem is that the PMP and thus Probable Maximum Flood (PMF) numbers are 

treated as having zero probabilities, i.e., as upper bounds that can’t be exceeded, rather than 

having a relatively low probability. For some interior parts of the country, farther from a warm 

ocean moisture source, PMP estimates are likely to have very low annual exceedance 

probabilities, about 1 X 10-7 or lower. However, in coastal regions closer to warm moisture 

sources, the estimates of the PMP5

 and thus PMF probability may be much higher, possibly 

several orders of magnitude higher, possibly between 1 X 10-3 and 1 X 10-5. This results in both 

uneven treatment between dams, and the possibility of flood risks that have not been 

adequately evaluated because the PMP and resulting PMF is a relatively frequent event. 

Another fundamental issue is that many dam overtopping failure modes are from a combination 

of circumstances, such as trash build-up on spillway gates or inability to open a spillway gate 

 

1 Senior Civil Engineer, Risk-Informed Decision-Making, FERC, Division of Dam Safety and Inspections, Portland 

Regional Office, 503-552-2728, david.lord@ferc.gov

2 Chapter 8 of the FERC Engineering Guidelines 

3

 State wide PMP studies have been approved for Wisconsin and Michigan (EPRI 1993), and Nebraska 

2008. State wide PMP studies are ongoing for Arizona, Ohio and Wyoming. EPAT study for the State of 

Colorado does not follow HMR methodology and has not been approved for developing PMP estimates at 

an FERC Project. 

4

 Reduced the PMP value of the HMR for a 24-hour, 20,000 sq. mi. storm from 6.8 inches to 3.0 inches in 

western Nebraska. 

5

 Schaefer MG, PMP and Other Extreme Storms, Concepts and Probabilities Safety, 1995 ASDSO 

Annual Conference Proceedings, Lexington KY, October 1995. 
33 

during a relatively frequent flood. The frequency of events between 1 X 10-2 and 1 X 10-4 might 

be of greater concern in combination with these events than an extreme flood event. 

The FERC’s modern dam safety program started with implementing regulations in 1981. The 

FERC’s Division of Dam Safety and Inspections (D2SI) has regulatory responsibility for 

approximately 3000 dams and approximately 950 dams classified as high and significant hazard 

potential. The high hazard classification is based on whether generally worst case dam failures 

would have the potential to cause loss of life. Significant hazard dams are reserved for 

economic or sensitive environmental issues. As discussed above, our dam safety program has 

relied on generally conservative deterministic analyses until recently. 

In 2000, D2SI established a Potential Failure Modes Analysis (PFMA) program for all high and 

significant hazard (HSH) dams. In 2009, the Commission adopted a strategic plan to develop a 

probabilistically oriented program, titled Risk-Informed Decision Making (RIDM). D2SI recently 

has initiated development of risk informed engineering guidelines included a Hydrologic Hazard 

Analysis (HHA) chapter. Drafts of these guidelines are to be completed by September 2013. 

You will hear more extensive discussions of flood risks to and from dams later in this workshop. 

Reclamation has a well respected program for developing estimates for Annual Exceedance 

Probabilities (AEP) of extreme precipitation and flood events and for developing resulting 

reservoir exceedance curves. Our new HHA chapter will rely heavily on the current Best 

Practices used by Reclamation. However, we are a regulator and not a dam owner like 

Reclamation, so our guidelines will require us to be able to communicate with hundreds of dam 

owners and dozens of consultants that may or may not have comprehensive knowledge of 

probabilistic hydrologic hazard analyses. 

While Reclamation can make an informed decision based on the information they develop, we 

will have to be able to use information primarily developed by the owners and consultants in 

consultation with our staff. Some of the questions about extreme flood frequency are as follows: 

1. Should the PMP be the upper bound of any frequency estimates of extreme storms? 

2. Are there simple procedures for rare to extreme flood and precipitation frequency estimates 

to judge whether more robust estimates are needed at a dam? 

3. What circumstance, i.e., level of risk would require an owner to develop new flood frequency 

estimates at a dam, i.e., when does a probabilistic estimate augment or replace a 

deterministic estimate? 

4. If the current PMP and PMF estimates are inadequate at a dam, do we complete new 

deterministic estimates, or should we rely only on new probabilistic calculations? 

 
34 

American Nuclear Society (ANS) Standards Current Activities 

ANS-2.8 Status1 

1

Raymond E. Schneider, ANS 2.8 development working group and Westinghouse 

The Status presentation, ANSI/ANS-2.8 WG Status “Determine External Flood Hazards for 

Nuclear Facilities” will present a brief introduction on the background, the objective, the scope, 

the standard for external flood hazards determination, the current status of the ANS-2.8 Working 

Group (WG) Activities and the relationship to the PFHA Workshop. 

 
35 

U.S. Department of Energy and 

Probabilistic Flood Hazard Assessment 

W. Mark Blackburn, P.E.1

1

Director, Office of Nuclear Facility Safety Programs 

U.S. Department of Energy (DOE) 

The U.S. Department of Energy (DOE) has used Probabilistic Flood Hazard Analysis for many 

years. The usage of Probabilistic Flood Hazard Analysis is endorsed in a recently approved 

DOE document called DOE Standard DOE-STD-1020-2012, Natural Phenomena Hazards 

Analysis and Design Criteria for Department of Energy Facilities. This document references a 

1988 paper entitled Preliminary Flood Hazard Estimates for Screening Models for Department 

of Energy Sites by McCann and Boissonnade. This current endorsement has its roots in two 

archived documents: 1) DOE Standard 1022-94, Natural Phenomena Hazards Characterization 

Criteria; and 2) DOE Order 6430.1A, General Design Criteria. All of these documents 

recommended usage of Probabilistic Flood Hazard Analysis for sites which had flood as one of 

the predominant design basis events. Because this technique is used at our sites, we are 

interested in learning about its usage in other agencies which may have similar applications as 

those in DOE. 

 
36 

Panel 2: State-of-the-Practice in Identifying and Quantifying 

 Extreme Flood Hazards 

Co-Chairs: Timothy Cohn, USGS and 

 Will Thomas, Michael Baker, Jr., Inc. 

Rapporteurs: Joseph Giacinto and Mark McBride, NRC (NRO); 

 Randy Fedors, NRC (NMSS) 

Presenters: Will Thomas, Michael Baker, Jr., Inc. 

 Jery Stedinger, Cornell University 

 Jim O’Connor, USGS 

 Beth Faber, USACE 

 John England, BoR 

Panelists: Jery Stedinger, Cornell University 

 John England, BoR 

 Douglas Clemetson, USACE 

 Jim O’Connor, USGS 

 
37 

Overview and History of Flood Frequency in the United States 

Wilbert O. Thomas, Jr.1 

1 Michael Baker, Jr., Inc., Manassas, VA 20110 

Characterizing the frequency of flood peak discharges is essential in designing critical 

infrastructure such as dams, levees, bridges, culverts, and nuclear power plants and in the 

definition of flood plains for land use planning. Estimates of flood frequency are needed for 

gaged and ungaged locations but this discussion is focused primarily on frequency analysis on 

gaged streams with observed flood data. Statistical flood frequency analysis provides the risk of 

structures being overtopped or flood plain areas being inundated. 

Statistical flood frequency analysis in the United States started with a paper by Fuller (1914) 

who analyzed long records of daily flows and peak flows around the world, but particularly from 

the United States. Fuller (1914) developed equations for estimating floods of a given return 

period T as a function of drainage area and is typically credited with having the first published 

formula or equation involving flood frequency (Dawdy et al. 2012). In his 1914 paper, Fuller 

also discussed plotting positions for analyzing flood distributions and suggested plotting at the 

median which later became known as the Hazen plotting position. Fuller (1914) apparently 

used plotting positions for the at-site frequency analysis and then developed equations for 

estimating the T-year flood discharges for ungaged locations. 

Hazen (1914), in his discussion of Fuller’s paper, presented for the first time the concept of 

probability paper and argued for the use of the lognormal distribution as a model of peak flows 

(Dawdy et al., 2012). Hazen (1930) describes his plotting position method in detail in his 1930 

book on “Flood flows” and provides examples of estimating flood discharges for New England 

streams. Hazen’s approach involved plotting flood data on graph paper with the normal 

probability scale on the horizontal axis (percent chance exceedance) and the ratio to the mean 

annual flood on a logarithmic vertical axis (lognormal probability paper) and adjusting for the 

skew in the data. The Hazen plotting position estimates the exceedance probability as (2m1)/2N where m is the order number starting with one as the largest and N is the total number of 

data points. This plotting position assigns a return period of 2N for the largest flood in N years of 

record. 

The use of plotting positions was the prevalent approach for flood frequency analysis in the 

period 1930 to 1967. Beard (1943) developed the median plotting position (m-0.30/N+0.4 with 

m and N as defined above) and this plotting position is still being used by the U.S. Army Corps 

of Engineers (USACE) for graphical display of flood data. In the 1940s, the U.S. Geological 

Survey (USGS) adopted the Weibull plotting position (m/N+1) as described by Kimball (1946) 

for estimating T-year flood discharges (Dalrymple, 1960; Benson, 1962). The USGS approach 

was to plot flood data on Gumbel probability paper with either a logarithmic or arithmetic vertical 

scale for discharge and draw a smooth curve through the data. The graphical procedures 

required significant engineering judgment and there was variation among engineers and 

hydrologists in applying these methods. 

Beard’s 1952 and 1962 publications on “Statistical Methods in Hydrology” documented flood 

frequency procedures being used by USACE in this time period (Beard, 1952, 1962). By 1962 
38 

the USACE was using the log-Pearson Type III method that involved fitting the logarithms of the 

annual peak flows to the Pearson Type III distribution. Foster (1924) introduced the Pearson 

system of frequency distributions to the American engineering profession and applied these 

methods to the study of annual runoff for gaging stations in the Adirondack Section of New 

York. Foster (1924) used the untransformed data but Beard (1962) recommended the use of 

logarithms of the annual peak data. 

In April 1966, the Subcommittee on Hydrology under the Inter-Agency Committee on Water 

Resources (IACWR) published Bulletin No. 13 on “Methods of Flow Frequency Analysis” 

(IACWR, 1966). Five methods of flow frequency analysis currently in common use were 

described: Hazen, Pearson Type III, Gumbel, gamma and graphical distribution-free methods. 

This appears to be the first interagency effort to describe methods for flood frequency analysis. 

Bulletin 13 summarized and described several methods of determining flood frequency but did 

not recommend any particular methods. No testing or comparison of the various methods was 

attempted. 

In August 1966, the 89th Congress passed House Document No. 465 entitled “A Unified 

National Program for Managing Flood Losses”. This document recommended the 

establishment of a panel of the Water Resources Council (WRC) to “present a set of techniques 

for frequency analyses that are based on the best known hydrological and statistical 

procedures”. House Document No. 465 also recommended the creation of a national flood 

insurance program that was eventually created in 1968. In response to House Document No. 

465, the Executive Director of WRC in September 1966 assigned the responsibility for 

developing a uniform technique to the WRC Hydrology Committee. The Hydrology Committee 

established a Work Group on Flow-Frequency Methods comprised of members of 12 Federal 

agencies and two statistical consultants. The work group applied the following six methods at 

10 long-term stations (records greater than 40 years): 

• 2-parameter gamma distribution, 

• Gumbel distribution, 

• log-Gumbel distribution, 

• log-normal distribution, 

• log-Pearson Type III distribution, and 

• Hazen method. 

The work group published Bulletin No. 15 in December 1967 “A Uniform Technique for 

Determining Flood Flow Frequencies” with the recommendation to fit the logarithms of the 

annual peak discharges to a Pearson Type III distribution using the method of moments 

(USWRC, 1967). The reasons for adopting this method were: 

1. Some Federal agencies were already using the log-Pearson Type III distribution (e.g., 

USACE) and computer programs were available. 

2. The log-normal is a special case of both the Hazen and log-Pearson Type III method 

with zero skew. 

3. The log-Pearson Type III distribution utilizes skew as third parameter and it was felt this 

would provide more flexibility and applicability in estimating flood discharges nationwide. 

4. The Hazen method was partially graphical and required more subjectivity in its 

application. 

Manuel Benson, USGS, who chaired the Bulletin 15 work group published a journal article that 

provided additional details on the analyses performed by the work group (Benson, 1968). 
39 

It soon became evident that Bulletin 15 was not as uniform method as originally conceived. 

Some of the reasons were non-uniform treatment of outliers, skew and historical data. In 

January 1972, the Hydrology Committee of WRC initiated review of Bulletin 15 and the need for 

more uniform guidelines. The Work Group on Flood Flow Frequency of the Hydrology 

Committee was comprised of members of 12 Federal agencies. In March 1976, the Hydrology 

Committee of WRC published Bulletin 17 “Guidelines For Determining Flood Flow Frequency”. 

Bulletin 17 recommended the continued use of the log-Pearson Type III distribution with the 

method of moments for parameter estimation (USWRC, 1976). This recommendation was 

based on a study by Beard (1974), who was at the University of Texas, conducted for the work 

group that applied eight combinations of distributions and estimation techniques to annual peak 

discharges at 300 long-term gaging stations (records greater than 30 years). To correct 

problems noted with Bulletin 15, Bulletin 17 recommended the use of a low outlier test for 

censoring low peaks, use of generalized (or regional) skew based on a study by Hardison 

(1974) and a mathematical procedure for adjusting for historical data based on a weightedmoments procedure suggested by Fred Bertle, Bureau of Reclamation. 

Shortly after Bulletin 17 was published, it was noted that there was a discrepancy about the 

order of the historical adjustment and the determination of weighted skew. In June 1977, 

Bulletin 17A, “Guidelines For Determining Flood Flow Frequency”, was published that clarified 

the historical adjustment was to be applied before the weighting of skew (USWRC, 1977). This 

clarification is the only significant difference between Bulletins 17 and 17A. A few editorial 

corrections were also made. 

With time, problems with the Bulletin 17A methodology began to surface. These problems can 

be summarized as follows: 

1. The low-outlier test did not adequately identify all the low outliers. 

2. There was some confusion over the estimation and use of generalized skew. 

3. There were inconsistencies in the use of the conditional probability adjustment for low 

outliers. 

In September 1981, the Hydrology Committee of WRC published Bulletin 17B “Guidelines For 

Determining Flood Flow Frequency” (USWRC, 1981). The Work Group on Revision of Bulletin 

17 of the Hydrology Committee was comprised of members of six Federal agencies: Soil 

Conservation Service, USACE, USGS, National Weather Service, Bureau of Reclamation, and 

the Tennessee Valley Authority. The following technical changes were in Bulletin 17B to correct 

problems noted in Bulletin 17A: 

1. Revised guidelines for estimating and using generalized skew. 

2. A new procedure for weighting generalized and station skew based on research by 

Tasker (1978) and Wallis et al. (1974). 

3. A new test for detection high outliers and a revised test for detection low outliers based 

on research by Grubbs and Beck (1972). 

4. Revised guidelines for the application of the conditional probability adjustment. 

In March 1982 several editorial corrections were made in Bulletin 17B and the guidelines were 

republished by the Hydrology Subcommittee of the Interagency Advisory Committee on Water 

Data (IACWD). The new sponsorship of Bulletin 17B was necessitated by the dissolution of the 

Water Resources Council in the fall of 1982. The Hydrology Subcommittee membership of the 

six Federal agencies remained the same under the two different sponsors. Bulletin 17B, 

“Guidelines for Determining Flood Flow Frequency” that was published in March 1982 by the 
40 

Hydrology Subcommittee of IACWD is still the guidelines used by Federal agencies and most 

state and local agencies for flood frequency analyses for gaged streams (IACWD, 1982). 

In January 2000, a Hydrologic Frequency Analysis Work Group (HFAWG) was formed to 

consider improvements in the current guidelines for hydrologic frequency analysis computations 

(e.g. Bulletin 17B) and to evaluate other procedures for frequency analysis of hydrologic 

phenomena. The HFAWG is a work group under the Hydrology Subcommittee of the Advisory 

Committee on Water Information (ACWI). The HFAWG, the Hydrology Subcommittee and the 

ACWI are all comprised of Federal and non-Federal organizations. This is a change from the 

past where Bulletins 15, 17, 17A and 17B were developed solely by Federal agencies. 

The HFAWG has met several times since January 2000 and the minutes of those meetings are 

on the HFAWG web site http://acwi.gov/hydrology/Frequency/. In November 2005 the HFAWG 

developed a plan for updating Bulletin 17B (see web site for details). The major improvements 

in Bulletin 17B that are being evaluated include: 

• Evaluate and compare the performance of a new statistical procedures the Expected 

Moments Algorithm (EMA) to the weighted-moments approach of Bulletin 17B for 

analyzing data sets with historical information, 

• Evaluate and compare the performance of EMA to the conditional probability adjustment 

of Bulletin 17B for analyzing data sets with low outliers and zero flows, 

• Described improved procedures for estimating generalized (regional) skew, and 

• Describe improved procedures for defining confidence limits. 

During 2012 considerable progress has been made in testing and evaluating the EMA 

procedure and in developing a new test for detecting influential low peaks. A March 2012 report 

titled “Updating Bulletin 17B for the 21st Century” that is posted on the HFAWG web site 

describes the results of testing EMA and current Bulletin 17B techniques. It is anticipated that a 

revised draft version of Bulletin 17B will be developed in 2013. 

In summary, at-site flood frequency techniques have been evolving in the United States over the 

last 100 years. Since the publication of House Document No. 465 in August 1966, the 

emphasis has been on developing a uniform and consistent technique that can be used by all 

Federal agencies. Thomas (1985) and Griffis and Stedinger (2007) describe in more detail the 

evolution of Bulletin 17 to the current Bulletin 17B technique. Ongoing research and testing by 

the HFAWG should result in an improved version of Bulletin 17B in 2013. 

References: 

Beard, L.R., 1943. Statistical analysis in hydrology. ASCE Transactions 108, 1110-1160. 

Beard, L.R., 1952. Statistical methods in hydrology. U.S. Army Corps of Engineers, Civil Works 

Engineer Bulletin 52-24. 

Beard, L.R., 1962. Statistical methods in hydrology. U.S. Army Corps of Engineers, Civil Works 

Investigations Project CW-151, Sacramento, California. 

Beard, L.R., 1974. Flood Flow Frequency Techniques. Center for Research in Water 

Resources, University of Texas, Austin, Texas. 
41 

Benson, M.A., 1962. Evolution of Methods for Evaluating the Occurrence of Floods. U.S. 

Geological Survey Water-Supply Paper 1580-A, 30 p. 

Benson, M.A., 1968. Uniform Flood-Frequency Estimating Methods for Federal Agencies. Water 

Resources Research, Vol. 4, No. 5, 891-908. 

Dalrymple, T., 1960. Flood-Frequency Analyses, Manual of Hydrology: Part 3. Flood-Flow 

Techniques. U.S. Geological Survey Water-Supply Paper 1543-A, 80 p. 

Dawdy, D.R., Griffis, V.W., and Gupta, V.K., 2012. Regional Flood-Frequency Analysis: How 

We Got Here and Where We Are Going. ASCE Journal of Hydrologic Engineering, 17:953-959. 

Foster, H.A., 1924. Theoretical frequency curves and their applications to engineering problems. 

ASCE Transactions 87, 142-203. 

Fuller, W.E., 1914. Flood flows. ASCE Transaction 77, 567-617. 

Griffis, V.W., and Stedinger, J.R., 2007. Evolution of Flood Frequency Analysis with Bulletin 17> 

ASCE Journal of Hydrologic Engineering, Vol. 12, No. 3, 283-297. 

Grubbs, F.E., and Beck, G., 1972. Extension of Sample Sizes and Percentage Points for 

Significance Tests of Outlying Observations. Technometrics. Vol. 14, No. 4, 847-854. 

Hardison, C.H., 1974. Generalized Skew Coefficients of Annual Floods in the United States and 

Their Application. Water Resources Research, Vol. 10, No. 5, 745-752. 

Hazen, A., 1914. Discussion of Flood flows by W.E. Fuller. ASCE Transactions 77, 626-632. 

Hazen, A,. 1930. Flood flows. John Wiley & Sons, New York, New York, 199 p. 

Interagency Advisory Committee on Water Data, 1982. Guidelines For Determining Flood Flow 

Frequency. Bulletin No. 17B of the Hydrology Subcommittee, Office of Water Data 

Coordination, U.S. Geological Survey, Reston, Virginia, 183 p. 

Inter-Agency Committee on Water Resources, 1966. Methods of Flow Frequency Analysis. 

Bulletin 13 of Subcommittee on Hydrology, 42 p. 

Kimball, B.F., 1946. Assignment of frequencies to a completely ordered set of sample data. 

American Geophysical Union Transactions, 110, 849-904. 

Tasker, G.D., 1978. Flood Frequency Analysis with a Generalized Skew Coefficient. Water 

Resources Research, Vol.14, No. 2, 373-376. 

Thomas, W.O., Jr., 1985. A Uniform Technique For Flood Frequency Analysis. ASCE Journal 

of Water Resources Planning and Management, Vol. 111, No. 3, 321-337. 

U.S. Water Resources Council, 1967. A Uniform Technique For Determining Flood Flow 

Frequencies. Bulletin No. 15 of the Hydrology Committee, 15 p. 
42 

U.S. Water Resources Council, 1976. Guidelines For Determining Flood Flow Frequency. 

Bulletin No. 17 of the Hydrology Committee, Washington, DC. 

U.S. Water Resources Council, 1977. Guidelines For Determining Flood Flow Frequency. 

Bulletin No. 17A of the Hydrology Committee, Washington, DC. 

U.S. Water Resources Council, 1981. Guidelines For Determining Flood Flow Frequency. 

Bulletin No. 17B of the Hydrology Committee, Washington, DC. 

Wallis, J.R., Matalas, N.C., and Slack, J.R., 1974. Just a Moment. Water Resources Research, 

Vol. 10, No. 2, 211-219. 

 
43 

Quantitative Paleoflood Hydrology 

Jim O’Connor1

1

U.S. Geological Survey, Oregon Water Science Center, oconnor@usgs.gov; 503-251-3222 

Paleoflood hydrology (Kochel and Baker, 1982) is the reconstruction of the magnitude and 

frequency of past floods using geological or botanical evidence. The following synopsis of 

paleoflood hydrology is derived from Benito and O’Connor (in press). Over the last 30 years, 

paleoflood hydrology has achieved recognition as a new branch of geomorphology and 

hydrology (Baker, 2008), employing principles of geology, hydrology, and fluid dynamics to infer 

quantitative and qualitative aspects of unobserved or unmeasured floods on the basis of 

physical evidence left behind. Flood evidence includes various geologic indicators (flood 

deposits and geomorphic features) and flotsam deposits, as well as physical effects on 

vegetation. Resulting inferences can include timing, magnitude, and frequency of individual 

floods at specific sites or for specific rivers, as well as conclusions regarding the magnitude and 

frequency of channel forming floods. The obvious benefit of paleoflood studies is obtaining 

information on floods from times or locations lacking direct measurements and observations. 

Findings from paleoflood studies support flood hazard assessments as well as understanding of 

the linkages between climate, land-use, flood frequency and channel morphology. 

Paleoflood studies typically take one of two forms: (1) analyses focused on determining 

quantitative information for specific events, such as the timing, peak discharge, and maximum 

stage of an individual flood or floods; and (2) studies investigating more general spatial and 

temporal patterns of flooding, commonly to assess relations among climate, land-use, flood 

frequency and magnitude, and geomorphic response (such as channel morphology or floodplain 

sedimentation and erosion processes). Both types of investigations share approaches and 

techniques, but, in general, studies of specific paleofloods are most typically conducted in 

bedrock or otherwise confined river systems for which preservation of stratigraphic and 

geomorphic records of individual floods are more likely (Kochel and Baker, 1982), although 

many studies have obtained valuable paleoflood information for alluvial rivers (Knox, 1999; 

Knox and Daniels, 2002). Studies relating channel form or floodplain morphology to past flood 

characteristics more typically are conducted for alluvial river corridors, and follow from the 

classic studies of Schumm (1968) and Dury (1973). In general, quantitative information of 

specific events is likely to be most appropriate for assessing risk to nuclear facilities; 

consequently, the emphasis of this section is on studies that can provide specific information on 

the timing, magnitude, and frequency of individual floods. 

Quantitative paleoflood hydrology relies on identification of evidence of flooding in conjunction 

with application of hydrodynamic principles to determine flow magnitude. These two aspects of 

investigation typically lead to four phases of analysis: (1) documentation and assessment of 

flood evidence; (2) determination of paleoflood ages; (3) estimation of flow magnitude, typically 

peak discharge, associated with flood evidence; and (4) incorporation of paleoflood data into the 

flood frequency analysis. The first component is geological and archival, requiring historical 

research, geomorphology, stratigraphy, sedimentology, and the second involves geochronology 

in order to identify and date physical evidence of flooding. The third component requires 

hydraulic analysis to assign a flow magnitude to paleoflood evidence. A common final step is to 

incorporate paleoflood discharge and chronology information into a flood frequency analysis to 
44 

determine peak flows associated to probability quantiles. These paleoflood studies generally are 

more successful and have fewer uncertainties in fluvial systems with resistant boundaries, such 

as bedrock or semi-alluvial channels. These environments, because of stable depositional sites, 

tend to have longer and clearer stratigraphic records of floods—sometimes exceeding several 

thousand years—and have stable boundary conditions, leading to greater confidence in using 

present topography to determine past hydraulic conditions. 

Most paleoflood studies have focused on semiarid and arid regions, although studies have 

successfully extended flood records in humid environments as well (e.g. Fanok and Wohl, 1997; 

Springer and Kite, 1997; Kidson and others, 2005). In general, paleoflood studies extend flood 

records 100s or 1000s of years and commonly provide compelling evidence of flood discharges 

exceeding those of the observation record (Enzel and others, 1993; O’Connor and others, 1994; 

Hosman and others, 2003; Harden and others, 2011). In certain areas, very large floods cluster 

on time scales of decades and centuries, interpreted as a response to climate variability (Ely 

and others, 1993; Knox 2000; Benito and others, 2003a). 

Slackwater Flood Records 

Paleoflood records are derived from physical evidence of flood stage. The best high water 

marks include mud, silt, seed lines and flotsam (e.g. fine organic debris, grass, woody debris) 

that closely mark peak flood stage. This type of evidence typically only persists for weeks, in 

humid climates, to several years, in semiarid and arid climates. But more lasting evidence can 

also be preserved, including fine-textured flood sediment (slack-water flood deposits), gravel 

and boulder bars, silt lines, and erosion features, as well as botanical evidence such as scars 

on riparian trees. Depending on the environment, such evidence can persist for millennia 

(Baker, 1987, 2008; Kochel and Baker, 1988; Webb and Jarrett, 2002). 

The most complete paleoflood records generally result from analysis of stratigraphic sequences 

of fine-grained flood deposits found in slack-water and eddy environments. Slackwater flood 

deposits are fine-grained sedimentary deposits that accumulate from suspension during floods 

(Baker and others, 2002). Slackwater sedimentation areas include flooded valley margins 

subject to eddies, back-flooding, flow separation and water stagnation during high stages. 

Diminished flow velocities in these areas promote rapid deposition of the fine-grained fraction of 

the suspended load. The resulting slack-water flood deposits commonly contain sedimentary 

structures and textures reflecting flow energy, direction and velocities. 

Slack-water depositional environments can be any location of diminished flow velocity or flow 

separation, typically (1) areas of channel widening, (2) severe channel bends, (3) obstacle 

hydraulic shadows where flow separation causes eddies, (4) alcoves and caves in bedrock 

walls, (5) back-flooded tributary mouths and valleys, or (6) high surfaces flanking the channel. In 

narrow bedrock reaches, slackwater flood deposits are commonly found in adjacent caves, 

alcoves or under rock overhangs. 

Paleoflood Chronology 

Developing a flood chronology is key to assessing flood frequency and commonly requires 

numerical age dating of sedimentary flood units and intervening deposits. Numerical dating 

underlies chronologies, typically by radiocarbon and optically simulated luminiscence (OSL). 

Radiocarbon dating is the most common absolute dating tool employed in paleohydrologic work, 

although OSL dating is becoming more common. Organic materials such as wood, charcoal, 

seeds leaf fragments are entrained by floods and commonly deposited in conjunction with 

clastic sediment in slackwater sequences. Additionally, flood deposits may cover vegetation or 
45 

organic cultural materials, as well as in turn be covered by vegetation and organic detritus. All of 

these types of materials can be radiocarbon dated, thereby providing information on the age of 

enclosing or bounding flood deposits. Organic materials most likely to provide high fidelity 

constraints on flood ages are those not likely to have persisted for a long period of time before 

deposition, such as seeds, fine organic detritus, and twigs. Commonly, however, radiocarbon 

dating is performed on charcoal contained within flood deposits, which can persist for hundreds 

or thousands of years prior to incorporation within a flood deposit. 

For most studies, it is assumed that radiocarbon ages from detrital material within flood deposits 

closely approximates the flood date, although the most conservative assumption is that the 

radiometric date provides a maximum limiting age for the enclosing deposit. This is particularly 

the case for radiocarbon dates from detrital charcoal. Dating of in-situ organic materials, such as 

charcoal from ground fires between affected surfaces bracketed by flood deposits, or pedogenic 

carbon between flood deposits, can provide robust constraints on the timing of flood sequences. 

As for most geologic investigations, dating of multiple organic materials and multiple deposits 

within a stratigraphical profile increases confidence in flood age determinations. The 5730 year 

half-life of 14C limits radiocarbon dating to deposits less than 40,000 years. Also, radiocarbon 

dating suffers from significant imprecision for the period 1650 to 1950 AD because of the 

significant fossil fuel burning and introduction of variable amounts of 14C into the atmosphere 

during the industrial revolution. 

The OSL method (Aitken, 1998) is a dating technique which indicates the burial time of 

deposits, principally quartz and feldspar minerals. This approach allows determination of when 

sediment was last exposed to light (“bleached”). For the purposes of dating sequences of flood 

deposits, the general presumption is that the sediment was last exposed to light prior to 

deposition. Sampling and analysis involves several steps of collecting and analysis of sandsized sediment from a target deposit without inadvertent exposure to light. Developments in 

OSL instrumentation are reducing the sample size to individual quartz and feldspar grains. 

Moreover, new analytical protocols have improved the application OSL dating for alluvial 

deposits, resulting in numerical dating with age uncertainties within 5-10%, even for g deposits 

less than 300 years old (Arnold and others, 2009). The technique can be hampered in situations 

in (1) which the proper species of quartz are not present in the deposits, and (2) for floods 

where the transported sediment was not bleached by exposure to light, either because of high 

turbidity levels or because the flood occurred at night. But under appropriate conditions, OSL 

dating can be an important tool, especially for deposits (1) containing little or no organic 

materials, (2) older than the range of radiocarbon dating (>40,000 years), or (3) younger than 

300 years for which radiocarbon dating cannot yield precise results. 

Radiocarbon and OSL dating can be supplemented with analysis of modern radionuclides such 

as Caesium-137 and Lead-210 (Ely and others, 1992). Both of these isotopes were introduced 

into the atmosphere during nuclear bomb testing in the 1950s and their presence in flood 

deposits signifies a post-1950 age. Likewise, human artifacts, such as beer cans (House and 

Baker, 2001), pottery (Benito and others, 2003a), and other archaeological materials can 

provide numeric age constraints on enclosing deposits. 

Dendrochronology has supported several paleoflood studies because of the identifiable 

responses of tree growth to damage of the bark and wood-forming tissues, buds, and leaves, 

and to radial growth following partial up-rooting of the trunk (Yanosky and Jarrett, 2002; Jacoby 

and others, 2008) For situations when flood damage or effects can be related to tree-ring 

chronologies derived from the affected tree or from established regional chronologies, flood 
46 

ages can commonly be determined to the specific year, and in some instances a specific 

season (Sigafoos, 1964; Ruíz-Villanueva and others, 2010). 

Paleoflood Discharge Estimation 

Hydraulic analysis is the basis for discharge estimates for most quantitative paleohydrologic 

studies. In most analyses, discharge estimates follow from the assumption that the elevation of 

paleostage evidence provides a minimum estimate of the maximum stage attained by an 

identified flood. In some situations, deposit elevations may closely approximate the maximum 

flood stage, although this assumption is difficult to verify (Jarrett and England, 2002) except for 

specific investigations of height differences between flood indicators and actual flood water 

depth for modern floods (Kochel 1980, Springer and Kite, 1997, Jarrett and England, 2002; 

House and others, 2002). Uncertainties in the fidelity of paleoflood stage evidence to actual 

maximum stages can be evaluated in conjunction with most discharge estimation procedures. 

A number of formulae and models are available to estimate flood discharge from known water 

surface elevations (O’Connor and Webb, 1988; Webb and Jarrett, 2002), ranging from simple 

hydraulic equations to more involved, multi-dimensional hydraulic modeling. Most paleoflood 

studies assume one-dimensional flow with calculations based on (1) uniform flow equations 

(e.g. Manning equation), (2) critical flow conditions, (3) gradually varied flow models, and (4) 

one dimensional St Venant equations. In complex reaches, multi-dimensional modeling may 

reduce uncertainties associated with reconstructing flood discharge (Denlinger and others, 

2002; Wohl, 2002). As described by Webb and Jarrett (2002), the appropriate approach for a 

particular site depends on local hydraulic conditions. 

Incorporating Paleoflood Information into Flood Frequency Analysis 

Paleoflood information provides tangible information on the occurrence and magnitude of large 

and infrequent floods. Although paleoflood information may not be as precise gaged or 

observed records and are not continuous in the manner of many measurement programs, 

understanding of the timing and magnitude of the largest floods can substantially reduce 

uncertainties in flood quantile estimates when considered in a statistically appropriate manner. 

Several statistical methods have been applied to estimate distribution function parameters for 

paleoflood datasets. The most efficient methods to incorporating imprecise and categorical data 

are: (1) maximum likelihood estimators (Stedinger and Cohn, 1986), (2) the method of expected 

moments (Cohn and others, 1997; England and others, 2003a) and (3) Bayesian methods 

(O’Connell and others, 2002; O’Connell, 2005; Reis and Stedinger, 2005). Some examples of 

employing these techniques for flood frequency analysis using both gaged and paleoflood 

records include O’Connor and others (1994), Bureau of Reclamation (2002), England and 

others (2003b), Levish and others (2003), Hosman and others, (2003), Thorndycraft and others, 

(2005a), England and others (2010), and Harden and others, (2011). In nearly all cases, the 

addition of paleoflood information greatly improves estimates of low probability floods, most 

commonly indicated by markedly narrower confidence limits about flood quantile estimates. 

References Cited 

Aitken, M.J. 1998. An Introduction to Optical Dating. The Dating of Quaternary Sediments by the 

Use of Photon-stimulated Luminescence, Oxford University Press, Oxford, 280 pp. 

Arnold L.J., Roberts R.G., Galbraith R.F., DeLong S.B. 2009. A revised burial dose estimation 

procedure for optical dating of young and modern-age sediments. Quaternary Geochronology 4, 

306-325. 
47 

Baker, V.R.,1987. Paleoflood hydrology and extreme flood events. Journal of Hydrology 96, 79–

99. 

Baker, V.R. 2008. Paleoflood hydrology: Origin, progress, prospects. Geomorphology 101 (1-2), 

1-13. 

Benito, G., Sopeña, A., Sánchez, Y., Machado, M.J., Pérez González, A., 2003a. Palaeoflood 

record of the Tagus River (Central Spain) during the Late Pleistocene and Holocene. 

Quaternary Science Reviews 22, 1737-1756. 

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51 

Hydrologic Hazard Methods for Dam Safety 

John F. England, Jr.1 

1

U.S. Department of Interior, Bureau of Reclamation, 

Flood Hydrology and Consequences Group, 86-68250, 

Technical Service Center, Denver, CO 80225 

Historically, dam design and analysis methods have focused on selecting a level of protection 

based on spillway evaluation flood loadings. Traditionally, the protection level is based on the 

Probable Maximum Flood (PMF). Reclamation uses risk analysis to assess the safety of dams, 

recommend safety improvements, and prioritize expenditures (Reclamation, 2011). Risk 

analysis, from a hydrologic perspective, requires an evaluation of a full range of hydrologic 

loading conditions and possible dam failure mechanisms tied to consequences of a failure. This 

risk approach is in contrast to the traditional approach of using single upper bound, maximum 

events such as the PMF from a risk perspective have no probability of occurrence and resulting 

potential consequences are not clearly defined. 

The flood loading input to a dam safety risk analysis within Reclamation is a hydrologic hazard 

curve that is developed from a Hydrologic Hazard Analysis (HHA). Hydrologic hazard curves 

(HHC) are peak flow and volume probability relationships. These hazard curves are presented 

as graphs and tables of peak flow and volume (for specified durations) versus Annual 

Exceedance Probability (AEP). The range of AEPs that is displayed on these graphs is intended 

to be sufficient to support the decision making needs of the organization. 

The hydrologic load inputs to a risk analysis may consist of peak flows, hydrographs and 

reservoir levels and their annual exceedance probabilities. From a prioritization of resources 

perspective, it is difficult to accomplish dam safety goals from a true or false assessment of 

whether a structure is capable of withstanding a Probable Maximum Flood. Therefore, a single, 

deterministic flood estimate such as the PMF is no longer adequate to evaluate the hydrologic 

safety of a dam. As an alternative, Reclamation has approached prioritization and modification 

needs through estimates of flood magnitudes and volumes and their associated exceedance 

probabilities up to the PMF. This is a risk analysis approach. 

Hydrologic hazard curves provide magnitudes and probabilities for the entire ranges of peak 

flow, flood volume (hydrograph), and reservoir elevations, and do not focus on a single event. 

The peak flow, flood volume, and maximum reservoir level frequency distributions for dams with 

potentially high loss of life might extend to very low probabilities. For dam safety risk 

assessments, flood estimates are needed for AEPs less than 1 in 10,000 (1 x 10-4) to satisfy 

Reclamation's public protection guidelines (Reclamation, 2011). 

Reclamation has developed and applied numerous methods to estimate hydrologic hazard 

curves - extreme flood magnitudes and probabilities for dam safety. These methods can be 

broadly classified into streamflow-based statistical approaches, and rainfall-based with runoff 

statistical approaches. Current hydrologic hazard curve methods used by Reclamation are 

summarized in Table 1, and are generally ranked according to the level of effort involved. 

Methods are described in Swain et al. (2006); improvements to these current methods and other 

tools and approaches are ongoing and may be added as project needs and experience dictates. 
52 

Recent comparisons in California and Colorado have shown relatively close agreement between 

stochastic rainfall-runoff models and paleoflood-based frequency curves in some detailed study 

cases. The methods used and some principles involved in estimating hydrologic hazards are 

presented. 

Table 1. Current methods used by Reclamation to develop hydrologic hazard curves 

Class Method of Analysis and 

Modeling (reference) 

Hydrologic Hazard 

Curve Product 

Risk 

Analysis/Design 

Level1 

Level of 

Effort2 

Streamflowbased statistics 

Peak-flow frequency analysis 

with historical/paleoflood data - 

Graphical method (Swain et al., 

2006) 

peak flow 

frequency, volume 

frequency; 

hydrographs 

CFR, IE Low 

Streamflowbased statistics 

Peak-flow frequency analysis 

with historical/paleoflood data - 

EMA (Cohn et al., 1997) 

peak flow frequency IE, CAS, FD Low 

Streamflowbased statistics 

Peak-flow frequency analysis 

with historical/paleoflood data - 

FLDFRQ3 (O'Connell et al., 

2002) 

peak flow frequency IE, CAS, FD Low 

Streamflowbased statistics Hydrograph Scaling and Volumes 

(England, 2003) 

hydrographs and 

volumes; based on 

peak flow frequency

CFR, IE, CAS, FD Low 

Rainfall-based 

statistics and 

Runoff Transfer 

GRADEX Method (Naghettini et 

al., 1996) 

volume frequency; 

hydrographs IE, CAS, FD Moderate

Rainfall-based 

statistics and 

Rainfall-Runoff 

Australian Rainfall-Runoff 

Method (Nathan and Weinmann, 

2001) 

peak flow and 

hydrographs; based 

on rainfall frequency 

and PMP 

IE, CAS, FD Moderate

Rainfall-based 

statistics and 

Rainfall-Runoff 

Stochastic Event-Based 

Precipitation Runoff Modeling 

with SEFM (Schaefer and Barker, 

2002) 

peak flow 

frequency; 

hydrographs; 

volume frequency; 

reservoir elevation 

frequency 

CAS, FD High 

Rainfall-based 

statistics and 

Rainfall-Runoff 

Stochastic Rainfall-Runoff 

Modeling with TREX (England et 

al., 2006, 2007) 

peak flow 

frequency; 

hydrographs; 

reservoir elevation 

frequency 

CAS, FD High 

1

CFR: Comprehensive Facility Review; IE: Issue Evaluation; CAS: Corrective Action Study; FD: 

Final Design 

2

Low: less than 20 staff days; Moderate: 21-100 staff days; High: more than 100 staff days 

References: 

Bauer, T.R. and Klinger, R.E., 2010. Evaluation of Paleoflood Peak Discharge Estimates in 

Hydrologic Hazard Studies. Report DSO-11-03, Dam Safety Technology Development Program, 

Bureau of Reclamation, Denver, 19 p. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/Bauer-Klinger-paleoflood-peak-discharges-DSO-11-

03.pdf
53 

Bureau of Reclamation (1999) A Framework for Characterizing Extreme Floods for Dam Safety 

Risk Assessment. Prepared by Utah State University and Bureau of Reclamation, Denver, CO, 

November, 67 p. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/LoganWorkshop.pdf

Bureau of Reclamation (2002) Interim Guidelines for Addressing the Risk of Extreme Hydrologic 

Events. Bureau of Reclamation, Denver, CO, August, 3 p. (England, J.F., principal author). 

ftp://ftp.usbr.gov/jengland/Dam_Safety/pmf_risk_interim_guidance.pdf

Bureau of Reclamation (2002) Flood Hazard Analysis - Folsom Dam, Central Valley Project, 

California. Bureau of Reclamation, Denver, CO, January, 128 p. and 4 appendices. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/Folsom_FloodHazard_Report_all.pdf

Bureau of Reclamation (Reclamation) (2011), Dam Safety Public Protection Guidelines, A Risk 

Framework to Support Dam Safety Decision-Making, Bureau of Reclamation, Denver, Colorado, 

31 p. 

http://www.usbr.gov/ssle/damsafety/documents/PPG201108.pdf

Cohn, T.A., Lane, W.L. and Baier, W.G. (1997) An algorithm for computing moments-based 

flood quantile estimates when historical information is available, Water Resour. Res. 33(9), pp. 

2089-2096. 

England, J.F. Jr. (2003) Probabilistic Extreme Flood Hydrographs that Use Paleoflood Data for 

Dam Safety Applications. Bureau of Reclamation, Denver, CO, January, 29 p. 

http://www.usbr.gov/ssle/damsafety/TechDev/DSOTechDev/DSO-03-03.pdf

England, J.F. Jr. (2004) Review of Selected Large Flood Estimates in the United States for the 

U.S. Geological Survey. Bureau of Reclamation, Denver, CO, August, 14 p. and appendices. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/usgs_largefloods_review_report_final.pdf

England, J.F. Jr., (2010) Hydrologic Hazard Analysis. Section 3 in Dam Safety Risk Analysis 

Best Practices Training Manual, Bureau of Reclamation, Denver, CO, 12 p. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/HydrologicHazard_BestPractices_CH03_April2010.pdf

England, J.F. Jr. (2011) Flood Frequency and Design Flood Estimation Procedures in the 

United States: Progress and Challenges, Australian Journal of Water Resources, Institution of 

Engineers, Australia, 15(1), pp. 33-46. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/England-FloodFrequencyUS-2011-AJWR-15-1-authorproof.pdf

England, J.F. Jr., Klawon, J.E., Klinger, R.E. and Bauer, T.R. (2006) Flood Hazard Study, 

Pueblo Dam, Colorado, Final Report, Bureau of Reclamation, Denver, CO, June, 160 p. and 

seven appendices. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/pueblo_floodhazard_finalreport.pdf

England, J.F. Jr., Velleux, M.L. and Julien, P.Y. (2007) Two-dimensional simulations of extreme 

floods on a large watershed. J. Hydrol., 347(1-2), doi:10.1016/j.jhydrol.2007.09.034, pp. 231-

243. 
54 

England, J.F. Jr. and Swain, R.E. (2008) Extreme Flood Probability Estimation for Dam Safety, 

28th United States Society on Dams Annual Conference, April 28-30, 2008, Portland, OR, 12 p. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/england_swain_floodprob_ussd08_final.pdf

Levish, D.R., England, J.F. Jr., Klawon, J.E. and O'Connell, D.R.H. (2003) Flood Hazard 

Analysis for Seminoe and Glendo Dams, Kendrick and North Platte Projects, Wyoming, Final 

Report, Bureau of Reclamation, Denver, CO, November, 126 p. and two appendices. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/NorthPlatteFinalReport.pdf

Nathan, R.J. and Weinmann, P.E. (2001) Estimation of Large to Extreme Floods: Book VI. In 

Australian rainfall and runoff, a guide to flood estimation, the Institution of Engineers, Australia. 

O’Connell, D.R.H., Ostenaa, D.A., Levish, D.R. and Klinger, R.E. (2002) Bayesian flood 

frequency analysis with paleohydrologic bound data. Water Resour. Res. 38(5), 

doi:10.1029/2000WR000028, 14 p. 

Schaefer, M.G., and Barker, B.L. (2002) Stochastic Event Flood Model. In Mathematical models 

of small watershed hydrology and applications, chapter 20, edited by V.P. Singh and D. Frevert, 

Water Resources Publications, Littleton, CO, pp. 707-748. 

Swain, R.E., England, J.F. Jr., Bullard, K.L. and Raff, D.A. (2006) Guidelines for Evaluating 

Hydrologic Hazards, Bureau of Reclamation, Denver, CO, 83 p. 

ftp://ftp.usbr.gov/jengland/Dam_Safety/Hydrologic_Hazard_Guidelines_final.pdf

Vogel, R.M., Matalas, N.C., England, J.F. and Castellarin, A. (2007) An assessment of 

exceedance probabilities of envelope curves. Water Resour. Res. 43 (7), W07403, 

doi:10.129/2006WR005586, 11 p. 

 
55 

Panel 3: Extreme Precipitation Events

Co-Chairs: John England, BoR and Chandra Pathak, USACE 

Presenters: John England, BoR 

 Daniel Wright, Princeton University 

 Mel Schaefer, MGS Engineering Consultants 

 Kelly Mahoney, NOAA-ESRL 

 Geoff Bonnin, NWS-OHD 

 Victoria Sankovich, BoR 

Rapporteurs: Nebiyu Tiruneh and Brad Harvey, NRC (NRO) 

Panelists: Daniel Wright, Princeton University 

 Mel Schaefer, MGS Engineering Consultants 

 Kelly Mahoney, NOAA-ESRL 

 Geoff Bonnin, NWS-OHD 

 
56 

An Observation-Driven Approach to Rainfall and Flood Frequency 

Analysis Using High-Resolution Radar Rainfall Fields 

and Stochastic Storm Transposition 

Daniel Wright

Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544

Spatial and temporal variability in extreme rainfall, and its interactions with land cover and the 

drainage network, is an important driver of flood response. `Design storms,' which are 

commonly used for flood risk assessment, however, are assumed to be uniform in space and 

either uniform or highly idealized in time. The impacts of these and other commonly-made 

assumptions are rarely considered, and their impacts on flood risk estimates are poorly 

understood. We develop an alternate framework for rainfall frequency analysis that couples 

stochastic storm transposition (SST) with “storm catalogs” developed from a ten-year highresolution (15-minute, 1-km2

) radar rainfall dataset for the region surrounding Charlotte, North 

Carolina, USA. The SST procedure involves spatial and temporal resampling from these storm 

catalogs to reconstruct the regional climatology of extreme rainfall. SST-based intensityduration-frequency (IDF) estimates are driven by the spatial and temporal rainfall variability from 

weather radar observations, are tailored specifically to the chosen watershed, and do not 

require simplifying assumptions of storm structure. We are able to use the SST procedure to 

reproduce IDF estimates from conventional methods for small urban watersheds in Charlotte. 

We demonstrate that extreme rainfall can vary substantially in time and in space, with important 

flood risk implications that cannot be assessed using conventional techniques. SST coupled 

with high-resolution radar rainfall fields represents a useful alternative to conventional design 

storms for flood risk assessment, the full advantages of which can be realized when the concept 

is extended to flood frequency analysis using a distributed hydrologic model. A variety of 

challenges remain which complicate the application of SST to larger watersheds and more 

complex settings, but the technique nonetheless represents a robust, observation-based 

alternative for assessing flood risk. 

 
57 

Regional Precipitation-Frequency Analysis 

and Extremes Including PMP – Practical Considerations 

M.G. Schaefer1 

1

MGS Engineering Consultants, Inc. 

Precipitation-Frequency relationships are now being developed for watersheds for use in 

rainfall-runoff modeling of extreme floods extending to Annual Exceedance Probabilities (AEPs) 

of 10-5 and beyond. This capability is made possible by advancements in several technical 

areas including regional-frequency analysis, L-moment statistics, spatial analysis of storms such 

as Isopercental analysis and GIS-based spatial mapping using radar data and ground-based 

precipitation measurements. Methodologies have been developed to derive the precipitationfrequency relationship in a manner that accounts for uncertainties in the various contributing 

components and provides uncertainty bounds for the mean frequency curve. In the frequency 

context, Probable Maximum Precipitation (PMP) becomes just another value on the frequency 

curve, which can be exceeded given the large uncertainties in PMP estimation. 

Experience has been gained in application of regional frequency analysis and development of 

precipitation-frequency relationships at over 20 watersheds in semi-arid to humid climates 

throughout the western US and British Columbia. This presentation will describe experience 

gained about the behavior of precipitation-frequency characteristics which will provide guidance 

and assist judgments in future applications for a range of climatic environments. 

 
58 

High-Resolution Numerical Modeling As A 

Tool To Assess Extreme Precipitation Events 

Kelly Mahoney 

University of Colorado/Cooperative Institute for Research in the Environmental Sciences 

(CIRES) and NOAA Earth Systems Research Lab (ESRL), Boulder, CO 

Weather and climate data is often downscaled to supply estimates, predictions, or projections to 

stakeholders and decision-makers at higher, more useful resolution than that provided by 

contemporary observations and reanalysis datasets. The details of downscaling (e.g., model 

resolution, domain selection, model physics) become of critical importance when addressing 

extreme weather phenomena at a local scale, as such events are often determined by and/or 

sensitive to small-scale processes. Particularly for flood events in complex terrain, it is 

necessary to resolve the details of both the terrain itself as well as driving fine-scale 

atmospheric processes to form a realistic picture of future flood risk. This discussion will briefly 

summarize work that uses high-resolution (1-km) simulations of warm-season intense 

precipitation events in key geographic regions in both the western US and the southeastern US. 

The overall objective of the work is to improve understanding of the factors and physical 

processes responsible for both historical (observed) extreme events, as well as future possible 

extreme events. In the western U.S., historical events such as the Fort Collins, CO flood of July 

1997, are examined as well as select historical events deemed critical to a particular dam’s 

planning purposes. In the Southeast U.S., work is underway to explore the use of highresolution modeling of key cases (e.g., the Tennessee floods of May 2010 and the Atlanta-area 

floods of September 2009) for future use in both forecast improvement and better hydrologicresponse predictions. High-resolution numerical modeling can be a useful tool to address 

questions related to storm maximization methods, probable maximum precipitation (PMP) limits, 

and elevation adjustment strategies -- concepts commonly used for water resources 

management nationwide. For example, is a storm of PMP magnitude physically able to develop 

in a specific region? In regions where paleoflood data do not suggest that floods of such 

magnitude have actually occurred historically, can a model be “forced” to produce such a storm 

following reasonable maximization of key fields? Do such changes reflect realistic possibilities of 

future climate change? Additional potential applications for decision-making in the realm of 

water resources management will be discussed. 

 
59 

Extreme Precipitation Frequency for Dam Safety 

and Nuclear Facilities – A Perspective 

Victoria L. Sankovich1, R. Jason Caldwell1 and John F. England, Jr.1 

1

Bureau of Reclamation, Technical Service Center, Flood Hydrology, Denver, CO 80225 

Federally regulated dams and nuclear power plants are designed to withstand extreme storm 

rainfall events. Some Federal agencies design their structures to the Probable Maximum 

Precipitation (PMP; e.g., Prasad et al. 2011, USACE 1984). Probable maximum precipitation is 

defined, theoretically, as the greatest depth of precipitation for a given duration that is physically 

possible over a given storm area at a particular geographical location at a certain time of year 

(HMR; WMO 2009, Hansen et al. 1982). Each of the hydrometeorological reports [joint efforts 

by the Bureau of Reclamation, National Weather Service, and Army Corps of Engineers, among 

others] have served as the basis for design precipitation estimates in flood design studies of 

critical infrastructure for several decades. These estimates are based on storm data that are 

outdated by up to 40 years. In addition, designing every dam to meet PMP may be a costprohibitive and unnecessary approach depending on the associated hazards downstream. 

In recent years, the Bureau of Reclamation has been utilizing an approach, which incorporates 

regional precipitation frequency analysis (L-moments; Hosking and Wallis 1997) and, at times, 

applies the PMP as an upper limit to the frequency curve (Nathan and Weinmann 2001). 

Nonetheless, there are many valuable concepts from PMP (i.e., storm analysis, storm 

maximization, depth-area-duration analysis, storm transposition), which lend information to the 

decision-making process. For example, observed isohyetal patterns from storms are overlaid on 

the drainage basin of Federal dams to examine rainfall-runoff relationships. Temporal patterns 

of observed rainfall are input into hydrologic models to accurately represent the time distribution 

of precipitation. Recent research by the Bureau of Reclamation into extreme precipitation events 

using storm maximization concepts suggests that events from the past two decades have the 

potential to meet or exceed current PMP estimates (Caldwell et al. 2011; e.g., Hurricane Floyd 

in 1999; Hurricane Fran in 1996). 

Here, we outline the methodology applied at various scales of project requirements through the 

presentation of case studies and recent research efforts at Reclamation. Examples will include: 

application and extrapolation of existing precipitation frequency curves (e.g., England et al. 

2012, Wright et al. 2012a,b); calculation of regional precipitation frequency relationships and 

uncertainty using L-moments (e.g., England et al. 2012, Novembre et al. 2012); development of 

spatial and temporal patterns as input to hydrologic models (Novembre et al. 2012); and, the 

utility of gridded meteorological datasets in hydrologic hazard assessments (Caldwell et al. 

2011). 

References: 

Caldwell, R.J., Sankovich, V.L. and England, J.F. Jr. (2011) Synthesis of Extreme Storm 

Rainfall and Probable Maximum Precipitation in the Southeastern U.S. Pilot Region, for the 

Nuclear Regulatory Commission, Office of Nuclear Regulatory Research. Bureau of 

Reclamation, Denver, CO, December 2011. 
60 

England, Jr., J, F. Dworak, and V. Sankovich, J. Wright, and R. Swain (2012) Hydrologic Hazard 

Analysis Anderson Ranch Dam, Idaho Study. Bureau of Reclamation, Denver, CO, May 2012. 

Hansen, E.M., Schreiner, L.C., and Miller, J.F. (1982) Application of Probable Maximum 

Precipitation Estimates, United States East of the 105th Meridian. Hydrometeorological Report 

No. 52, National Weather Service, National Oceanic and Atmospheric Administration, U.S. 

Department of Commerce, Silver Spring, MD, 168 p. 

Hosking, J.R.M. and Wallis, J.R. (1997) Regional Frequency Analysis - An Approach based on 

L-Moments. Cambridge University Press, 224 p. 

Nathan, R.J. and Weinmann, P.E. (2001) Estimation of Large to Extreme Floods: Book VI in 

Australian Rainfall and Runoff, A Guide to Flood Estimation. the Institution of Engineers, 

Australia. 

Novembre, N., V. Sankovich, R. Caldwell, J. Niehaus, J. Wright, R. Swain, and J. England, Jr. 

(2012) Altus Dam Hydrologic Hazard and Reservoir Routing for Corrective Action Study. Bureau 

of Reclamation, Denver, CO, August 2012. 

Prasad, R., Hibler, L.F., Coleman, A.F., and Ward, D.L. (2011) Design-Basis Flood Estimation 

for Site Characterization at Nuclear Power Plants in the United States of America. Nuclear 

Regulatory Commission NUREG/CR-7046, PNNL-20091, prepared by Pacific Northwest 

National Laboratory, Richland, WA. 

U.S. Army Corps of Engineers (USACE) (1984) HMR52 Probable Maximum Storm (Eastern 

United States), User’s Manual, CPD-46, Revised April, 1987, Hydrologic Engineering Center, 

Davis, CA, 89 p. 

World Meteorological Organization (WMO) (2009) Manual on Estimation of Probable Maximum 

Precipitation (PMP). WMO No. 1045, Geneva, 259 p. 

Wright, J., V. Sankovich, and R. Swain (2011a) Trapped Rock Dam Hydrologic Hazard, for the 

Department of Interior Bureau of Indian Affairs. Bureau of Reclamation, Denver, CO, September 

2011. 

Wright, J., V. Sankovich, and R. Swain (2011b) Tufa Stone Dam Hydrologic Hazard, for the 

Department of Interior Bureau of Indian Affairs. Bureau of Reclamation, Denver, CO, September 

2011. 

 
61 

Panel 4: Flood-Induced Dam and Levee Failures

Co-Chairs: Tony Wahl, USBR and Sam Lin, FERC 

Presenters: David Bowles, RAC Engineers & Economists 

 Timo Schweckendiek, Deltares Unit Geo-engineering 

 Jason Hedien, MWH 

 Tony Wahl, BoR 

 David Margo, USACE 

Rapporteurs: Jacob Philip, NRC (RES); Hosung Ahn, NRC (NRO); and 

 Juan Uribe, NRC (NRR) 

Panelists: Eric Gross, FERC, Chicago (Dam) 

 Timo Schweckendiek, Deltares Unit Geo-engineering (Levee) 

 Martin W McCann Jr., Stanford University (Dam/Levee) 

 David Margo, USACE (Dam/Levee) 

 Gregory Baecher, University of Maryland (Risk Analysis) 

 Jery Stedinger, Cornell University (Dam) 

 David Bowles, RAC Engineers & Economists (Dam/Levee) 

 
62 

Risk-Informed Approach to Flood-Induced Dam and Levee Failures 

David S. Bowlesa,b 

a

RAC Engineers and Economists, Providence, Utah; 

b

Department of Civil and Environmental Engineering, 

Utah State University, Logan, Utah 

There is a growing use of probabilistic risk assessment as a supplement to traditional 

engineering approaches in dam safety decision making in the US and overseas. This is 

referred to as a risk-informed approach in which decision making utilizes information obtained 

from a risk assessment along with other factors, including good engineering practice and 

societal concerns. Thus a risk assessment is not the sole basis for a decision, but rather it 

provides a systematic way of understanding dam failure risk, including the potential 

consequences and associated uncertainties. Dam safety risk assessments are used for 

informing decisions about the extent and type of risk reduction, and the urgency, priority and 

phasing of risk-reduction measures. 

This presentation will commence with a brief overview the ownership and regulation of dams in 

the US. It will then provide an overview of the major steps involved in performing a risk 

assessment for an individual dam. Emphasis will be given to flood-related failure modes but 

reference will also be made to failure modes related to other external and internal hazards and 

human reliability. The requirements for probabilistic flood hazard information will be 

summarized including the effects of spillway gate reliability. Approaches to evaluating the 

adequacy of dam safety, the tolerability of estimates risks and using risk analysis outcomes to 

support dam safety decision making will be provided. An example will be provided for an 

existing dam and for selecting between risk-reduction alternatives. The paper will close with a 

summary of some types of information from probabilistic dam and levee flood analysis that 

might be of value for assessing external hazards for nuclear plants, and some limitations and 

research needs related to probabilistic risk analysis for flood-induced dam and levee failure. 

References 

Applications of Dam Safety Risk Assessment 

• A Risk-based re-evaluation of reservoir operating restrictions to reduce the risk of failure 

from earthquake and piping. In 2010 ANCOLD Conference on Dams, Hobart, Tasmania, 

Australia. (D.S. Bowles, L.R. Anderson, M.E. Ruthford, D.C. Serafini, and S.S. 

Chauhan). 

• Using a Risk-informed Approach to Find a Solution for Spillway Deficiencies with 

Upstream and Downstream Tradeoffs. HydroVision. July 2012. (D.S. Bowles and J. 

Hedien). 

Dam Breach Modeling 

• A Numerical Method for Simulating One-Dimensional Headcut Migration and 

Overstopping Breaching in Cohesive and Zoned Embankments. Water Resources 

Research. Vol. 43(5), W05411, 2007. (Z. Wang and D.S. Bowles). 

• Do Current Breach Parameter Estimation Techniques Provide Reasonable Estimates for 

Use in Breach Modeling? Proceedings of Dam Safety 2004, ASDSO 2004 Annual 
63 

Conference, Phoenix, AZ. September 2004. (S.S. Chauhan, D.S. Bowles, and L.R. 

Anderson). 

• Overtopping Breaches for a Long Dam Estimated Using a Three-Dimensional Model. 

Proceedings of the 2006 USSD Annual Lecture, San Antonio, TX. June 2006. (Z. Wang, 

and D.S. Bowles). (For PDF copy of Poster click here). 

• Three-Dimensional Non-Cohesive Earthern Dam Breach Model. Part 1. Theory and 

Methology. Advances in Water Resources. Vol. 29(10):1528-1545, 2006. (Z. Wang and 

D.S. Bowles). 

• Three-Dimensional Non-Cohesive Earthern Dam Breach Model. Part 2. Validation and 

applications. Advances in Water Resources. Vol. 29(10):1490-1503, 2006. (Z. Wang and 

D.S. Bowles). 

Dam Safety Risk Assessment and Management 

• Summary of USSD Emerging Issues White Paper on Dam Safety Risk Assessment: 

What Is It? Who's Using it and Why? Where Should We Be Going With It? Invited 

Plenary Session Presentation and Paper in Proceedings of the 2003 USSD Annual 

Lecture, Charleston, South Carolina. April 2003. (D.S. Bowles). 

Extreme Flood Estimation 

• A Framework for Characterization of Extreme Floods for Dam Safety Risk Assessments.

Proceedings of the 1998 USCOLD Annual Lecture, Buffalo, New York. August 1998. (R. 

Swain, D.S. Bowles, and D. Ostenaa). 

• A Probability-Neutral Approach to the Estimation of Design Snowmelt Floods. Referred 

paper in Proceedings of the International Hydrology and Water Resources Symposium, 

November 1997. Auckland, New Zealand. (R.J. Nathan and D.S. Bowles). 

Life-Loss Estimation and Evacuation Modeling 

• Consequence Estimation for Critical Infrastructure Risk Management. Proceedings of 

the US Society on Dams 2010 Annual Lecture, Sacramento, CA. April 2010. (J.T. 

Needham, Y. Seda-Sanabria and D.S. Bowles). 

• Life-loss estimation: What can we learn from case histories? ANCOLD Bulletin 113:75-

91, December 1999. (D.M. McClelland and D.S. Bowles). 

• LIFESim: A Model for Estimating Dam Failure Life Loss. Report to Institute for Water 

Resources, US Army Corps of Engineers and Australian National Committee on Large 

Dams by Institute for Dam Safety Risk Management, Utah State University, Logan, Utah. 

2005. (M.A. Aboelata and D.S. Bowles). 

• LIFESim: A Model for Flood Life-Loss Estimation. Proceedings of the Association of 

State Dam Safety Officials "Dam Safety 2008" Conference, Indian Wells, CA. September 

2008. (M. Aboelata and D.S. Bowles). 

• Transportation model for evacuation in estimating dam failure life loss. ANCOLD Bulletin 

128, 2005. (M Aboelata, D.S. Bowles, and A. Chen). 

Portfolio Risk Assessment and Management 

• From Portfolio Risk Assessment to Portfolio Risk Management. ANCOLD Bulletin 

137:13-32, 2008. (D.S. Bowles). 

• Portfolio risk assessment of SA water's large dams.ANCOLD (Australian Committee on 

Large Dams) Bulletin 112:27-39. August 1999. (D.S. Bowles, A.M. Parsons, L.R. 

Anderson, and T.F. Glover). 

Risk Analysis and Probability Estimation 
64 

• Improvements to DAMRAE: A Tool for Dam Safety Risk Analysis Modelling. In: 

Proceedings of the ANCOLD Conference on Dams, Adelaide, South Australia, Australia. 

November 2009. (A. Srivastava, D.S. Bowles and S.S. Chauhan). 

Risk Analysis--Long Dams 

• Baseline Risk Assessment for Herbert Hoover Dike. In ANCOLD Conference on Dams, 

Perth, Western Australia, Australia. October 2012. (D.S. Bowles, S.S. Chauhan, L.R. 

Anderson and R.C. Grove). 

Spillway Gate Reliability 

• Gate Reliability: An Important Part of Dam Safety. Presented at the 2003 USSD Annual 

Lecture, Charleston, South Carolina. April 2003. (Lewin, J., G. Ballard, and D.S. 

Bowles). 

• Gate Reliability Assessment for a Spillway Upgrade Design in Queensland, Australia.

Invited paper at the Workshop on Spillway Reliability, USSD 2005 Annual Conference, 

San Antonio, Texas. (M. Barker, B. Vivian, and D.S. Bowles). 

Tolerable Risk Evaluation and Decision Making 

• Dam safety, economic regulation and society’s need to prioritise health and safety 

expenditures. In Proceedings of the NZSOLD/ANCOLD Workshop on “Promoting and 

Ensuring the Culture of Dam Safety”, Queenstown, New Zealand. November 2007. (J. 

Marsden, L. McDonald, D.S. Bowles, R. Davidson and R. Nathan). 

• Interim Tolerable Risk Guidelines for US Army Corps of Engineers Dams. Proceedings 

of the 2009 USSD Annual Lecture, Philadelphia, Pennsylvania. March. (D.F. Munger, 

D.S. Bowles, D.D. Boyer, D.W. Davis, D.A. Margo, D.A. Moser, P.J. Regan, and N. 

Snorteland). 

• Tolerable Risk for Dams: How Safe is Safe Enough? Proceedings of the 2007 USSD 

Annual Lecture, Philadelphia, Pennsylvania. March. (D.S. Bowles). 

Uncertainty Analysis 

• DAMRAE-U: A Tool for Including Uncertainty in Dam Safety Risk Assessment. In: Dam 

Safety’ 12, ASDSO, Denver, Colorado. September 17, 2012. (A. Srivastava, D.S. 

Bowles and S.S. Chauhan). 

• A Structured Approach to Incorporating Uncertainty into a Dam Safety Risk Assessment. 

Proceedings of the US Society on Dams 2009 Annual Lecture, Nashville, TN. April 2009. 

(D.S. Bowles, S.S. Chauhan, L.R. Anderson, and T.F. Glover). 

 
65 

Dutch Approach to Levee Reliability and Flood Risk 

Timo Schweckendieka,b 

a

Deltares, Unit Geo-engineering, Delft, Netherlands

b

Delft University of Technology, Department of Hydraulic Engineering, Delft, Netherlands

Risk-based approaches in flood defense reliability and flood risk management have a long 

history in the Netherlands, essentially starting right after a coastal flood disaster in 1953, which 

inundated large parts of the Dutch south-western delta and caused more than 1800 fatalities 

and 100.000 inhabitants lost their homes. In the same year, Van Dantzig (1953) came up with 

an economic optimization of dike crest levels comparing the investment cost in flood protection 

with the benefits in terms of risk reduction. The same basic concept is still the basis of flood 

protection standards nowadays. 

More recently, roughly in the last two decades, safety assessment and design of flood defenses 

are moving steadily from semi-probabilistic approaches towards fully probabilistic reliability and 

risk analysis. Probably the best example for the state-of-practice in the Netherlands is the 

VNK2-project (also known as FLORIS, see Jongejan et al., 2013). In the VNK-2 project all 

Dutch polders (dike ring systems of so called “primary flood defenses”) are analyzed in terms of 

probability of failure of the defenses (i.e., levees and hydraulic structures), both on element and 

on system level, as well as in terms of flood risk. For the latter sets of inundation scenarios are 

simulated, the outcomes of which in terms of inundation depth and flow velocities serve as input 

for modeling the expected damage. 

The goal of this presentation is to provide an overview of basic concepts and approaches used 

for analyzing levee reliability and flood risk in the Netherlands. Special attention will be paid to 

aspects that may be relevant to probabilistic risk assessment (PRA) of single facilities such as 

power plants. A major issue here can be the definition of critical flood and failure scenarios 

addressing the conditions which can pose serious hazards to such assets. 

Please find below some references you may find useful and do not hesitate to contact me for 

further information. 

References 

Deltacommissie (2008). Working Together with Water - Findings of the Deltacommissie 2008 - 

Summary and Conclusions. 

Faber, M.H. et al. (2007). Principles of risk assessment of engineered systems. 10th 

International Conference on Application of Statistic and Probability in Civil Engineering 

(ICASP10). 

Jongejan, R.B. et al. (2013). The VNK2-project: a fully probabilistic risk analysis for all major 

levee systems in the Netherlands. IAHS Publication From Risk to Opportunity (in press). 

Jonkman, S.N., et al. (2003). An overview of quantitative risk measures for loss of life and 

economic damage. Journal of Hazardous Materials, vol. 99(1), 1-30. 99(1): 1-30. 
66 

Manen, S.E.V. and Brinkhuis, M. (2005). Quantitative flood risk assessment for polders.

Reliability Engineering and System Safety 90(2-3)): 229–237. 

Rijkswaterstaat (2005). Flood Risks and Safety in the Netherlands (Floris). 

Schweckendiek, T. et al. (2012). Target Reliabilities and Partial Factors for Flood Defenses in 

the Netherlands. Modern Geotechnical Codes of Practice - Code Development and Calibration. 

Taylor and Francis. (in press) 

Schweckendiek, T. et al. (2008). River System Behavior Effects on Flood Risk. Proceedings of 

ESREL 2008, Valencia, Spain. 

Van Dantzig, D. (1953). Economic Decision Problems for Flood Prevention. Econometrica 

24(3): 276-287. 

Van der Most, H. and M. Wehrung (2005). Dealing with Uncertainty in Flood Risk Assessment 

of Dike Rings in the Netherlands. Natural Hazards 2005(36): 191-206. 

Voortman, H.G. (2003). Risk-based design of large scale flood defences. PhD thesis, Delft 

University of Technology. 

Vrijling, J.K., et al. (1998). Acceptable risk as a basis for design. Reliability Engineering and 

System Safety 59: 141-150. 

Vrijling, J.K., Schweckendiek, T. & Kanning, W.: Safety Standards of Flood Defenses. Proc. of 

the 3rd Int. Symp. on Geotechnical Safety and Risk (ISGSR 2011), Munich, Germany, 2011, 

856–890. 

 
67 

Risk-Informed Decision-Making (RIDM) Approach for Inflow Design 

Flood (IDF) Selection and Accomodation for Dams: 

A Practical Application Case Study 

Jason E. Hedien 

MWH Americas, Inc., 175 W. Jackson Blvd., Suite 1900, Chicago, IL, 312-831-3095 

Previous dam safety investigations at two hydroelectric facilities located on the same river in the 

Midwestern United States have identified insufficient spillway capacity to pass the computed 

probable maximum flood (PMF) without overtopping and failing the earth embankments at each 

project. This presentation provides a case study of how risk assessment (RA) and risk-informed 

decision making (RIDM) for hydrologic hazard analysis can be applied to select the inflow 

design flood (IDF) for a particular dam. 

The two hydroelectric facilities considered each consist of a multiple-unit surface powerhouse 

integrated with the dam structures, earth embankment dams utilizing concrete core walls as the 

primary water barrier, concrete gravity and buttress structures, and spillways. The two facilities 

are separated by a distance of approximately 12 river miles and are run-of-river projects. 

Although located in a rural farmland region of the Midwest, both facilities are classified as highhazard dams. Each dam impounds a lake that is heavily utilized for recreation during the 

summer months. The dams are regulated by the Federal Energy Regulatory Commission 

(FERC). 

Per the FERC Engineering Guidelines for the Evaluation of Hydropower Projects, in the event a 

dam cannot safely pass the PMF, the dam should be capable of passing the IDF for the dam. In 

evaluating the options for resolution of the spillway capacity deficiency at the two dams, the 

owner and FERC agreed to investigate the use of RA and RIDM to assist in defining the IDF for 

the dams as an alternative to more traditional incremental hazard justification approaches for 

computing spillway design floods. A risk-based approach allowed for consideration of several 

factors specific to these two dams when determining the IDF. These factors include: both dams 

are run-of-river dams and do not have flood storage capacity in their reservoirs, which does not 

allow for attenuation of the flood hydrograph by storage; the population around the lakes 

impounded by the dams is significantly greater than the population living along the river below 

the dams, which means that there could be more significant consequences to rises in water 

levels upstream of the dams prior to dam failure than to rises in water levels downstream of the 

dams due to dam failure; the population of the area is significantly greater during the summer 

months than the winter months, which means that there is an impact of seasonal population 

differences on the potential for life-loss due to dam failure; and, the winter flood hydrographs are 

significantly greater in magnitude and rise more quickly than the summer flood hydrographs due 

to rain-on-snow causing snow melting along with the lack of vegetative ground cover but frozen, 

wet ground for relatively smaller surface roughness and less infiltration loss to both hydraulically 

and hydrologically attenuate runoff towards the river. The RA also allowed for the examination 

of the effect that failure or non-failure of individual project elements would have on 

consequences. 

The first step in development of the RA for determining the IDF consisted of conducting 

Potential Failure Modes Analyses (PFMAs) in accordance with FERC guidelines. PFMAs 
68 

consist of two workshops to identify and evaluate potential failure modes (PFMs) for a given 

dam, with participants from FERC, the owner, consultants, and specialists. For the dams under 

investigation, the PFMA workshop was followed by a RA workshop involving the same 

participants. The PFMA identified a number of credible PFMs that the RA workshop participants 

agreed should be carried forward into the RA process. These PFMs included: overtopping of 

the earth embankment at various short and high sections of both dams resulting in failure of the 

dam; overtopping of a low abutment area at one dam resulting in failure of the right abutment of 

the dam; and, overtopping of a concrete buttress section at one of the dams resulting in sliding 

failure of that structure. Each of the PFMs identified would be represented in the RA event tree 

established for each of the dams. 

Event trees representing the sequence of events considered to have the potential to lead to 

breaching of each dam and uncontrolled release of the reservoir were developed for each dam. 

Development of the event trees for the dams therefore involved incorporating all PFMs and their 

interrelationships into appropriate positions, or levels, in the event trees. For all PFMs identified 

in the PFMA, the initiating event is a given flood inflow into each of the reservoirs impounded by 

the dams. Thus, the first level in the event tree consisted of the range of possible flood inflows 

to each reservoir up to and including the inflow associated with the PMF. Due to the significant 

difference in their magnitude and characteristics, warm and cold season floods were considered 

separately using the same event tree with the resulting failure probabilities being added to 

estimate the total failure probability. 

Subsequent levels in the event trees included the sequence of events leading to potential 

breaching of the dam and uncontrolled release of the reservoir. These events, or levels, were 

divided into those that result in a potential rise in the reservoir impounded by each dam and 

those associated with the dam failure or breaching process. Events resulting in a potential rise 

in the reservoir impounded by each dam include the flood inflow itself, failure of spillway gates 

to open to pass the flood inflow downstream, and potential blockage of spillway gates by debris 

that hinders passage of flood flow downstream. Events associated in dam failure or breaching 

included overtopping and initiation of erosion of the embankments of each dam, toppling or 

failure of core wall segments due to erosion of the embankments, the initial width of the breach 

when a core wall segment fails, and sliding of the buttress section at one of the dams. 

In the RA each level of the event tree developed for each dam was assigned a conditional 

probability of occurrence, or system response probability (SRP). The SRP for each event to 

include in the event trees was estimated during the RA workshop using information and reports 

available for each dam, historical performance of comparable dams, experience, and 

engineering judgment. The probability of failure, or the potential for overtopping and breaching 

of the dam leading to uncontrolled release of the reservoir, was computed by following all of the 

possible combinations of events and probabilities in the event tree for each dam incorporating 

all PFMs. The event trees were applied using the complete range of warm and cold season 

floods to obtain an estimate of the total annual failure probability (AFP) for each dam 

considering both types of floods as initiating events. 

Consequences evaluated for dam breaches and uncontrolled release of the reservoir 

impounded by each dam included estimated life loss and representative property damage as a 

count of affected structures. Economic consequences associated with monetary estimates of 

property damage and other types of economic losses were not estimated. Estimates of life loss 

and property damage were computed based on the results of breach-inundation model runs 

using a set of dam breach and reservoir release events that cover the full range of warm and 
69 

cold season flood magnitudes for each dam. The number of structures affected by the range of 

flood events resulting from breaching of the dams was estimated using a database of structures 

along the river developed from evaluating aerial surveys and photos. Life loss was estimated 

using the LIFESim methodology (Aboelata and Bowles 2005), a modular life loss modeling 

approach that considers the effectiveness of warning, evacuation and rescue, the submergence 

effects of the flooding and the degree of shelter offered by structures, and the potential for 

survival or life loss in various flood lethality – shelter environments. 

For this RA the probability of dam failure and associated consequences were compared with 

tolerable risk guidelines used by the U.S. Bureau of Reclamation (Reclamation, 2003) and the 

Australian National Committee on Large Dams (ANCOLD, 2003) to assess the significance of 

risks for the baseline risk for the existing dams and various risk reduction alternatives 

considered. The ANCOLD and Reclamation guidelines provided a sampling of widely-used risk 

guidelines currently in use at the time and applied to dams and reservoirs. 

The baseline risk for the dams in their existing conditions was evaluated first. This provided a 

baseline for evaluating the risks associated with the dams in their current state and the potential 

benefits/risks and strength of justification provided by structural or non-structural risk reduction 

measures considered for the dams. Event tree risk models were developed for the dams in 

their existing conditions and used to estimate the probabilities and consequences of each of the 

identified PFMs. The baseline RA results indicated that the dams in their existing condition did 

not meet either the Reclamation tolerable risk guideline for the AFP or the ANCOLD guideline 

for the annual life loss (ALL). Based on these results, the owner and FERC determined that risk 

reduction alternatives should be investigated. 

Investigating the effectiveness of various structural and non-structural risk reduction measures 

to accommodate the selected IDFs was carried out as part of the risk reduction assessment 

(RRA) for the dams. The RRA focused on evaluating the effects of various risk reduction 

measures on the probability of dam failure and associated consequences, including both 

downstream and upstream consequences. The RRA process included the following steps: 

identifying potential risk reduction alternatives for consideration in the RRA at each dam; 

modification of the event trees in the RA model to incorporate risk reduction alternatives 

considered for the RRA; developing new peak reservoir pool elevation – annual exceedance 

probability (AEP) relationships for each risk reduction alternative; evaluating the effect of each 

risk reduction alternative on AFP, number of affected structures, and life-loss estimates relative 

to those resulting from the baseline risk and tolerable risk guidelines developed by the 

Reclamation and ANCOLD; and selecting the preferred risk reduction alternative for further 

design development with the goal of achieving the most reasonable combination of risk 

reduction cost effectiveness with respect to capital cost and on-going operation and 

maintenance costs. 

The evaluation of a number of risk reduction alternatives identified for the two dams concluded 

that adding spillway capacity to each dam by modifying existing structures at each dam to pass 

additional flows downstream before overtopping failure would meet all tolerable risk guidelines 

used for the RA and would lower risk to “as low as reasonably possible” (ALARP). In 

subsequent reviews of the RA results and meetings between FERC and the owner, the 

additional spillway capacity to be added to each dam was increased somewhat so that the 

computed warm season PMF could be safely passed during the summer months, when the 

population that could be impacted by a failure of one of the dams is the greatest. 
70 

Implementation of these spillway capacity additions was accepted by FERC while satisfying 

above referenced tolerable risk guidelines evaluated in the RA. Design and construction of the 

spillway capacity additions at both dams are currently underway. 

The process described in the preceding paragraphs and presented at this workshop provides a 

case study of how RA and RIDM can be applied to select and accommodate the IDF for a 

particular dam. In this case, application of RA and RIDM led to the identification of an IDF and 

spillway capacity improvements that not only are accepted by FERC for selection and 

accommodation of IDFs, but also reduce computed risks to meet tolerable risk guidelines in use 

today. 

 

References 

Aboelata, M. and D.S. Bowles (2005). LIFESim: A Model for Estimating Dam Failure Life Loss. 

Preliminary Draft Report to Institute for Water Resources, US Army Corps of Engineers and 

Australian National Committee on Large Dams. Institute for Dam Safety Risk Management, 

Utah State University, Logan, Utah. December. 

ANCOLD (Australian National Committee on Large Dams) (2003). Guidelines on risk 

assessment. Australian National Committee on Large Dams, Sydney, New South Wales, 

Australia. 

FERC (Federal Energy Regulatory Commission). Engineering Guidelines for the Evaluation of 

Hydropower Projects. 

Reclamation (U.S. Bureau of Reclamation) (2003). Guidelines for achieving public protection in 

dam safety decision-making. Dam Safety Office, Department of the Interior, Denver, Colorado. 

 
71 

Incorporating Breach Parameter Estimation and Physically-Based 

Dam Breach Modeling into Probabilistic Dam Failure Analysis 

Tony L. Wahl 

Bureau of Reclamation, Hydraulics Laboratory, Denver, CO 

Probabilities of dam failure can be modeled through the use of fragility curves that relate the 

chance of failure to the severity of the loading condition. Fragility curves have often been 

developed primarily on the basis of experience and judgment. Physically-based dam breach 

modeling tools now offer the potential to develop failure probability estimates in a more 

analytical way. Models presently available and under continuing development make it feasible 

to incorporate probabilistic flood load estimates, variability of embankment materials, and other 

factors to obtain probabilistic estimates of the likelihood of dam failure as well as breach 

parameters, erosion rates, and outflow hydrographs. 

When a simplified approach is called for, regression equations are still widely used to predict 

breach parameters. Although most breach parameter estimation methods were developed for 

use in a deterministic framework, several recent studies have examined uncertainties in breach 

parameter prediction, and these can provide the basis for developing probabilistic estimates of 

breach parameters. 

References 

Froehlich, D., 2008. Embankment dam breach parameters and their uncertainties. Journal of 

Hydraulic Engineering, 134(12), 1708–1721. 

Hanson, G.J., D.M. Temple, S.L. Hunt, and R.D. Tejral, 2011. Development and 

characterization of soil material parameters for embankment breach. Applied Engineering in 

Agriculture, 27(4):587-595. 

Mohamed, M.A.A. (2002) Embankment breach formation and modelling methods, The Open 

University, England, UK. 

Morris, M.W. (In Prep) Breaching of earth embankments and dams, The Open University, 

England., UK. PhD. Pending examination. 

Morris, M.W., M.A.A.M. Hassan, T.L. Wahl , R.D. Tejral, G.J. Hanson, and D.M. Temple, 2012. 

Evaluation and development of physically-based embankment breach models. 2nd European 

Conference on Flood Risk Management, Nov. 20-22, 2012. Rotterdam, The Netherlands. 

Riley, R.C., 1986. A procedure for evaluating permissible limits of overtopping of vegetated 

earthen embankments. Dam Safety ’86, Proceedings of the 1986 ASDSO Annual Meeting, 

Austin, Texas, October 1986. 

Temple, D. M., G.J. Hanson, M.L. Neilsen, and K.R. Cook, 2005. Simplified breach analysis 

model for homogeneous embankments: Part 1, background and model components. USSD 

Technologies to Enhance Dam Safety and the Environment, 25th Annual USSD Conference, 

Salt Lake City, Utah, June 6-10th 2005. 
72 

Van Damme, M., M. Morris, and M. Hassan. 2012. A new approach to rapid assessment of 

breach driven embankment failures, Flood Risk Management Research Consortium, FRMRC 

Research Report SWP4.4. 

http://web.sbe.hw.ac.uk/frmrc/downloads/FRMRC2_WP4_4_ScienceReport.pdf

Visser, K., G. Hanson, D. Temple, and M. Neilsen, 2012. Earthen embankment overtopping 

analysis using the WinDAM B software. ASDSO 2012, Denver, Colorado, Sept. 16-21, 2012. 

Wahl, T.L., 1998, Prediction of embankment dam breach parameters: a literature review and 

needs assessment. Dam Safety Research Report DSO‐98‐004, U.S. Dept. of the Interior, 

Bureau of Reclamation, Denver, Colorado, July 1998. 

http://www.usbr.gov/pmts/hydraulics_lab/pubs/DSO/DSO-98-004.pdf

Wahl, T.L., 2004. Uncertainty of predictions of embankment dam breach parameters. Journal 

of Hydraulic Engineering, Vol. 130, No. 5, pp. 389-397. 

Xu, Y. and L.M. Zhang, 2009. Breaching parameters for earth and rockfill dams. Journal of 

Geotechnical and Geoenvironmental Engineering, 135(12), December 1, 1957-1970.

 
73 

USACE Risk Informed Decision Framework for Dam and Levee Safety 

David A. Margo, P.E.1

1

U.S. Army Corps of Engineers, Pittsburgh, PA 15222 

USACE is moving from a solely standards based approach for its dam and levee safety 

programs to a portfolio risk management approach. The standards based or essential 

guidelines approach is included in the risk informed approach and decisions will now be risk 

informed. One of the bases for risk informed decisions, including the priority and urgency of risk 

management actions, is a consideration of risk tolerability. Risks may be considered tolerable 

when society is willing to live with the risk to secure certain benefits and the risks are being 

properly managed, reviewed, and reduced further when practicable. 

Risk informed decisions are based on qualitative and quantitative evidence about inundation 

risks, which inundation scenario is generating the risk, and the efficiency and effectiveness of 

options to reduce and manage the inundation risk. The inundation risk arises from one or more 

of the following four scenarios: 1) breach prior to overtopping, 2) overtopping with a breach, 3) 

malfunction of system components due to a variety of causes including human error, or 4) 

overtopping without breach or non-breach risk. Each of these inundation scenarios represents 

a source of inundation risk to people, economic activity, vulnerable ecosystems, cultural 

resources, and other valuable resources and activities. 

Explicit recognition of uncertainties is an essential part of any risk informed decision. A risk 

informed decision to reduce and manage inundation risk is one that considers all available 

information and the confidence in our knowledge and understanding of the risks and the risk 

drivers. Risk informed decisions are made in the USACE dam and levee portfolio process at a 

national level. Both quantitative and non-quantitative factors influence practical decision making 

for the USACE safety programs. 

The following guiding principles, which represent a paradigm shift for USACE, have been 

established for the dam and levee safety programs. 

• Life safety will be held paramount in the risk management decisions made within the 

USACE dam and levee safety programs. 

• The principle of ‘do no harm’ will underpin all actions intended to reduce inundation risk. 

Applying this principle will ensure that proposed actions do not compromise the overall 

safety of the facility during or as a result of implementing a risk management measure. 

• Decisions will be risk informed (not risk based). Risk informed decisions synthesize 

traditional engineering analyses with risk estimation through the application of 

experience based engineering judgment. 

• The urgency and priority of actions will be commensurate with the level of inundation risk 

based on available knowledge. 

• USACE will use a portfolio risk management process to assess and manage the 

inundation risks associated with the USACE portfolio of dams and levees. This process 

supports a national level prioritization to achieve effective and efficient use of available 

resources. 
74 

• The level of effort and scope of risk assessments will be scaled to provide an 

appropriate level of confidence considering the purpose of the risk management 

decision. 

• Execution of inspections, instrumentation, monitoring, operations and maintenance, 

emergency action planning, and other routine activities are an essential part of an 

effective risk management strategy. 

 
75 

Panel 5: Tsunami Flooding 

Co-Chairs: Eric Geist, USGS-Menlo Park, CA and Henry Jones, NRC 

Presenters: Hong Kie Thio, URS Corp. 

 Randy LeVeque, University of Washington (UW) 

 Uri ten Brink, USGS 

 Pat Lynett, USC 

Rapporteurs: Mark McBride, NRC (NRO) and 

 Randy Fedors, NRC (NMSS) 

Panelists: Randy LeVeque, UW 

 Uri ten Brink, USGS 

 Pat Lynett, USC 

 Annie Kammerer, NRC 

 Frank González, UW 

 Yong Wei, NOAA/PMEL 

 Tom Parsons, USGS 

 Chuck Real, California Geological Survey 

 
76 

Probabilistic Tsunami Hazard Analysis 

Hong Kie Thio 

URS Corporation, Los Angeles, CA 90017 

The 2004 Sumatra tsunami disaster has accelerated the development of performancebased solutions to the analysis of tsunami hazard and thus the establishment of a 

probabilistic framework for tsunami hazard analysis. We have developed a method for 

Probabilistic Tsunami Hazard Analysis (PTHA) that closely follows, where possible, the 

methodology of Probabilistic Seismic Hazard Analysis (PSHA) using a hybrid approach. 

Because of the very strong variability of the seafloor depth, which causes very strong 

distortions of the wavefield and thus the wave amplitudes, it is not practical to develop 

analogs to the ground motion prediction equations (GMPE) used in PSHA. Instead, we 

can use numerical models to directly simulate tsunami wave propagation since the 

structure of the oceans, i.e. the bathymetry, is generally well-known. In contrast to the 

deep ocean propagation where the long tsunami waves behave in a linear fashion, the 

nearshore propagation, inundation and runup are highly non-linear and require a far 

greater computational effort. We have therefore split the PTHA analysis into two steps, 

which is somewhat similar to the seismic practice where we often compute probabilistic 

spectra for rock conditions using simple (quasi-) linear relations, and use these as input 

for non-linear analysis of the soil response. 

In the first step, we use the linear behavior of offshore wave propagation to compute 

fully probabilistic offshore waveheights using a library of pre-computed tsunami Green's 

functions for elementary fault elements (usually 50x50 km) from all potential sources. 

This allows us to efficiently perform a integration over a wide range of locations and 

magnitudes, similar to PSHA, and incorporate both epistemic uncertainties, through the 

use of logic trees, and aleatory uncertainties using distribution functions. We have 

developed maps of probabilistic offshore waveheights for the western United States for 

a range of return period between 72 an 2500 years. These maps are very useful to 

compare the hazard between different regions, and also, through disaggregation, 

identify the dominant sources for that particular region and return period. 

The disaggregation results are then used in the next step where we compute inundation 

scenarios using a small subset of events that are representative of the hazard 

expressed by the probabilistic waveheights. This process has enabled us to develop 

probabilistic tsunami inundation maps for the state of California. 

Epistemic Uncertainties 

An important aspect of the probabilistic approach, especially for longer return periods, is 

the proper characterization of the uncertainties. Because tsunamis can still be 

damaging at very large distances, as was demonstrated by the 2004 Sumatra and 2011 

Tohoku earthquakes, it is important to include sources from the entire Pacific Basin for a 

hazard study of the US west coast. Our state of knowledge of these different source 

zones is however highly variable, and in most cases, the record of observations is 
77 

rather short and incomplete. We therefore developed a “generic” source 

characterization based on global scaling relations, plate convergence rates and some 

assumptions regarding stress-drop and seismogenic thickness. This model can be used 

in its entirety for subduction zones for which we have little other information, but is also 

included, as a separate logic tree branch, in cases where we do have more specific 

information on the fault. Depending on the quality of the constraints we have for the 

specific source, such as Cascadia, the relative importance (weight) of the generic model 

is adjusted. As is the case in PSHA, our aim is to strike a balance between empirical 

models, which tend to be incomplete in terms of the length of record and may include 

ambiguous observations, and an imperfect understanding of the behavior and 

recurrence of large tsunamigenic earthquakes. 

Aleatory Uncertainties 

We include aleatory variability for the different elements of the hazard analysis, 

including the source characterization, bearing in mind that the large slip (~50 m) 

observed for the Tohoku earthquake corresponds approximately to the 2 sigma level for 

maximum slip in the global scaling relations. It is therefore important to be cautious with 

the truncation of the aleatory distributions. Whereas GMPE’s in seismic hazard analysis 

automatically include a standard deviation, the numerical approach does not, an we 

therefore have computed a modeling sigma by comparing modeled tsunami 

waveheights with observed ones. Finally, we also include tidal uncertainty by convolving 

the tsunami Green’s functions with the local tidal record and developing a distribution 

function of the maximum waveheights at every step. 

Future work 

We have established a framework for performing probabilistic tsunami hazard analysis, 

which is currently focused on earthquake sources but may also include other types of 

sources such as sub-marine landslides, for which the range of uncertainties is much 

larger. Even for the earthquake problem, there are many important issues outstanding, 

for instance with regard to the very large (M > 9) earthquakes. Accurate characterization 

of the upper end of the magnitude range of a source is often, perhaps somewhat 

counter-intuitively, not very important in seismic hazard since the ground motions tend 

to saturate for very large magnitudes. This is however a critical issue for tsunami hazard 

analysis, and it is very important to understand the limits for these large earthquakes. In 

many cases we may be able to assign a maximum rupture length, simply by considering 

the geometry of the subduction zone, but it is important to understand how the slip 

scales at these very large magnitudes, for which we have very little data. If we assume 

some maximum stress-drop arguments, it is possible to constrain the slip using the fault 

width, but its scaling for large magnitude is also poorly constrained. Likewise, it is 

important to determine how often these events occur, or whether segmented ruptures 

are the main mode of rupture. It is therefore essential to collect more empirical data, in 

particular from paleo-tsunami fieldwork, to extend the tsunami record and provide better 

constraints on or recurrence models. 

 
78 

Recent Advances in PTHA Methodology 

Randall J LeVeque1, Frank I Gonzalez2, Knut Waagan1, 

Loyce M Adams1, and Guang Lin3 

1

University of Washington, Applied Mathematics 

2

University of Washington, Earth and Space Sciences 

3

Pacific Northwest National Laboratory, Computational Sciences and Mathematics 

Probabilistic tsunami hazard assessment (PTHA) techniques have been developed by many 

researchers over the past decade, largely based on the older field of probabilistic seismic 

hazard assessment (PSHA). For surveys see Geist and Parsons (2006) and Geist et al. (2009). 

Recently the PTHA methodology employed in a study of Seaside, OR (Gonzalez et al. 2009) 

has been updated in connection with a recent investigation of tsunami hazards in Crescent City, 

CA. 

The original Seaside methodology uses the following steps: 

(a) Determine a finite set of potential tsunamigenic earthquakes together with annual 

probabilities of occurrence. 

(b) Simulate the tsunami resulting from each, and the resulting inundation in the target 

region of interest. 

(c) Incorporate tidal uncertainty to adjust the probabilities of flooding a given point from each 

event. 

(d) At each point on a fine-scale spatial grid covering the region, construct a "hazard curve" 

giving the annual probability of exceedance as a function of some range of exceedance 

values. 

(e) Determine, for example, the 100-year flood depth by interpolating on this curve to find 

the depth that is exceeded with annual probability 0.01. 

(f) Combine these values obtained from the hazard curves for all spatial points to produce a 

map of the 100-year flood, and contours of the depth that is exceeded with probability 

0.01. 

The updated methodology makes use of the open source GeoClaw software, which uses 

adaptive mesh refinement (AMR) to efficiently solve the tsunami propagation and inundation 

problem, allowing the use of large numbers of potential tsunamis and the possibility of sampling 

from probability density functions of potential earthquakes rather than using a small set of 

characteristic events. Past work in this direction has often used a small number of stochastic 

parameters to characterize the earthquake, such as depth and magnitude (see e.g. Geist and 

Parsons, 2006), which can be very effective for distant sources for which the runup and 

inundation are relatively insensitive to the details of the slip distribution. Recent work has 

focused on exploring the use of a Karhunen-Loeve expansion to represent possible slip 

distributions on an earthquake fault for the nearfield case. This is an expansion in terms of 

eigenfunctions of a presumed covariance matrix for the slip distribution over the fault geometry. 

Guidance on the choice of covariance matrix based on the dimensions of the fault plane and 

earthquake magnitude can be found in work such as that of Mai and Beroza (2002). The 

coefficients in this expansion specify a particular realization of this potential earthquake. If a 
79 

probability density function in the high-dimensional space of coefficients can be determined that 

accurately describes potential earthquakes, then importance sampling and dimension reduction 

techniques can be used to derive hazard curves from this stochastic description of potential 

events. Unfortunately, there is a high degree of epistemic uncertainty that makes it difficult to 

adequately constrain these density functions for regions such as the Cascadia Subduction 

Zone, and more work is needed in this direction. 

The GeoClaw code also allows the direct computation of inundation for different tide stages. 

This allows tidal uncertainty to be handled more accurately than in the Seaside study, where the 

approach of Mojfeld et al. (2007) was used. For each tsunami event studied, inundation is 

typically computed at three tide stages (MLW, MSL, and MHHW). At each spatial point on the 

regional grid, and for each exceedance level, these three simulations can be used to estimate 

the tidal stage that would be necessary for inundation that exceeds the given level. The tide 

record can then be used to compute probabilities that this tide stage or higher will occur when 

the tsunami arrives. For tsunamis that consist of multiple large waves, the wave pattern unique 

to the tsunami can be used to improve on these probabilities. 

Interpretation of the resulting hazard curves and maps can be improved by considering methods 

of plotting the data. Traditional flood maps such as those showing contours of a 100-year flood 

can be supplemented by contour maps of probability for a given exceedance value. These can 

be important in understanding the sensitivity of results to probability level chosen, and will better 

reveal the possibility of much more extreme flooding events that may occur with slightly smaller 

probability. 

Another extension is to study flow velocities, momentum, and momentum flux in addition to flow 

depth. Forces on structures and the destructive capacity of the flow increase with velocity, 

particularly when there is debris carried in the fluid. Hazard maps that only consider depth of 

flow may be inadequate for judging the probability of disaster. 

References: 

F. I. Gonzalez, E L Geist, B. Jaffe, U Kanoglu, et al., 2009. Probabilistic tsunami hazard 

assessment at Seaside, Oregon, for near-and far-field seismic sources. J. Geophys. Res. 

114:C11023. 

E. L. Geist and T. Parsons, 2006. Probabilistic Analysis of Tsunami Hazards, Nat Haz. 37:277 

E. L. Geist, T. Parsons, U. S. ten Brink, and H. J. Lee, 2009. Tsunami Probability, in E. N. 

Bernard and A. R. Robinson (eds.) The Sea. 15:201, Harvard University Press. 

P. M. Mai and G. C. Beroza, A spatial random field model to characterize complexity in 

earthquake slip, 2002. J. Geophys. Res. 107:2308. 

H.O. Mofjeld, F.I. Gonzalez, V.V. Titov, A.J. Venturato, and J.C. Newman, 2007. Effects of tides 

on maximum tsunami wave heights: Probability distributions. J. Atmos. Ocean. Technol. 24:117. 

 
80 

Geological Perspective on Submarine Landslide Tsunami Probability 

Uri S. Ten Brink1

, Jason D. Chaytor1, Daniel S. Brothers1, and Eric L. Geist2

1

U.S. Geological Survey, Woods Hole, MA 02543 

2

U.S. Geological Survey, Menlo Park, CA 94025 

The temporal distribution of earthquakes, other than aftershocks and triggered events, is 

assumed to follow an exponential distribution that is associated with a stationary Poisson’s 

process (e.g., Parsons, 2002; Coral, 2004; Kagan, 2010). The spatial distribution of earthquakes 

is heterogeneous, being concentrated in tectonic plate boundaries and other tectonically-active 

zones, notwithstanding the infrequent intra-plate earthquakes (e.g., Swafford and Stein, 2007). 

Are submarine landslide distributions uniform in time and space? Our knowledge of submarine 

landslide distribution in space is limited by the difficulty of mapping the seafloor at high 

resolution. Nevertheless, our knowledge improves as more bathymetry and high-resolution 

seismic data are being collected. For example, the U.S. Atlantic continental margin from North 

Carolina north is almost completely covered bathymetric data allowing us to map all but the very 

smallest (< 1 km2

) landslide scars. Inferring the temporal distribution of submarine landslide 

distribution is more challenging because of our inability to detect slope failures in real time, the 

considerable work involved in robustly dating landslide features (e.g., Haflidason et al., 2005) 

and sometimes because of the lack of, or technical limitations of recovering, datable material. 

Moreover, landslides, being a destructive process often erase the record of previous slides. 

It is therefore necessary to use indirect arguments to constrain landslide distributions. One such 

argument is the ergodic hypothesis in which the age distribution of landslides around the globe 

can yield the rate of landslide occurrence at a particular location. Caution should be taken in 

using this argument because of the potential differences between seismically-active and 

“passive” (i.e., non-active) margins, and between margins that were influenced by glaciers and 

major river systems and those that were not. Empirical arguments can be made to explain why 

submarine landslides around the world appear to be more common at the end of the last glacial 

maximum (LGM) and the beginning of the Holocene (~20,000-7,000 years) than at present. 

These include the amount of sediment reaching the slope, expected to be higher during low sea 

level when rivers and glaciers discharged at the shelf edge, the amount of sediment delivered to 

the coast by catastrophic draining of glacial lakes and by increase erosion due to wetter 

conditions at the LGM, and the hypothesized increase of seismicity due to unloading of the crust 

by the melting ice caps (Lee, 2009) and due to sediment and water loading of the margin 

(Brothers et al., submitted). Pore pressure increase in slope sediments may have accompanied 

the rapid accumulation of sediments on the continental slope and rise (Flemings et al., 2008 

ESPL, Dugan and Flemings, 2000, Kvalstad et al., 2005). 

Relative dating of landslides can be determined by the cross-cutting relationships between 

landslides scars and submarine canyons (Chaytor et al., 2012). In the Atlantic margin we 

observed scars that have been dissected by canyons while others have blocked canyon flows. 

Our recent work indicates that most submarine canyons along the Atlantic margin are relict and 

last active at the end of the last sea level lowstand but some may still be active to some degree 

today. A better understanding of the oceanographic and sedimentological conditions required to 
81 

incise submarine canyons (e.g., Brothers et al., in revision) will help to date both canyon activity 

and the landslides they intersect. 

Because the vast majority of landslides tsunamis are associated with earthquakes, and because 

tsunami height is scaled with landslide volume, earthquake probability may be used to estimate 

maximum landslide tsunami probability. Volume and area distributions of submarine landslides 

along the Atlantic margin follow lognormal-like or double-Pareto distribution (Chaytor et al., 

2009, ten Brink et al., 2012). These lognormal-like distributions can be simulated (both under 

water and on land) using slope stability analysis and the expected peak spectral acceleration as 

a function of distance from the earthquake source (ten Brink et al., 2009). Therefore, the 

maximum area and volume of a landslide appears to be related to the magnitude of the 

triggering earthquake. This approach predicts that earthquake magnitudes < 4.5 and 

earthquakes located more than 100-150 km from the continental slope are generally incapable 

of generating landslides. This approach can be applied to passive margins with clastic (sand, 

clay) sediments. Some U.S. margins, such as around Puerto Rico and Florida north to South 

Carolina, are composed predominantly of carbonate material. These margins are characterized 

by steep slopes (≤45°), reflecting the strong cohesion of carbonate rocks. Landslide distribution 

along the carbonate rock margin of Puerto Rico was found to be exponential, not lognormal-like 

(ten Brink et al., 2006). This distribution can be explained, if carbonate rocks are weakened by 

fissures that have formed by dissolution. Fissure distribution is random. Therefore landslide size 

will be determined by the available block size during earthquakes shaking which is random, not 

by the earthquake magnitude. While many seismically-active margins are also covered by 

clastic sediments, landslides in these margins may often be much smaller than predicted by 

earthquake magnitude because the frequency of shaking outpaces the rate of sediment 

accumulation along the margin. However, to-date we are not aware of a regional landslide 

distribution study for a seismically active margin. 

Earthquakes are the result of slow stress accumulation, of faults that are preferentially oriented 

within the stress field, and sometime of rheological and compositional condition within the fault 

zone. Analogous conditions exist for landslides. First, for a landslide to occur, uconsolidated 

sediment should be available to fail. It is therefore likely that landslide distribution is not uniform 

in space but is concentrated in regions with thick unconsolidated sediments. Along the Atlantic 

margin it appears that most landslides have occurred offshore New York and New England, 

where glacial processes supplied sediment to the margin, and offshore the Mid-Atlantic region 

where LGM delta fronts are located (Twichell et al., 2009). Because the location and size of 

landslides depends on sediment availability, one can argue that areas that have already failed 

will not fail again as long as additional sediments are not introduced to the margin. Such an 

argument could help identify high hazard vs. low hazard sections of the margin. Landslide 

history in Norway indicates that large landslides such as the Storegga landslide ~7500 years 

ago have also occurred at the end of the previous glacial maximum, but not in the intervening 

period or since ~7500 years ago (Halfidason et al., 2005). However, to date there is no 

systematic study that could confirm this potentially important prediction. A comparison of size 

distribution of landslides in passive and active margins, where seismic activity outpaces 

sediment supply, may provide some constraints. 

Slope stability decreases with increasing slope gradient. Some margins are steeper than others 

owing to pre-existing physiography over which the sediments were deposited. For example, the 

New England-Georges Banks continental slope is steeper than slopes farther south along the 

margin because Mesozoic reefs forming “a wall” at shallow depths beneath the slope (Brothers 

et al., 2013). This must have contributed to the prevalence of landslides in that sector of the 
82 

margin (Twichell et al., 2009). Stability also decreases with increasing pore pressure. 

Therefore, landslides can occur at slopes as low as 0.1°-0.5° (off the mouth of the Mississippi 

Delta, Prior and Coleman, 1978). Large landslide scars are also observed on the open slope of 

the U.S. Atlantic continental rise where the sea floor has gradients of 1°-2° (Twichell et al., 

2009). However, to date there has not been a systematic mapping of pore pressure with 

sediments in the margin to determine the spatial dimensions of high pore pressure regions. It is 

unclear whether these dimensions are larger than a kilometer (Sultan et al., 2010). It is possible 

that canyon incision of the continental slope may lower the regional pore pressure there. Gas 

venting has been recently detected along canyon walls 

(http://www.noaanews.noaa.gov/stories2012/20121219_gas_seeps.html), but it is presently 

unclear how widespread this venting is. 

Phrampus and Hornbach (2012) have proposed that changes in the Gulf Stream in the past 

5,000 years had caused wide spread gas hydrate destabilization, which perhaps caused the 

Cape Fear slide. Based on clustering of many head scarps along the Atlantic margin at the 

expected upper water depth of gas hydrate stability zone, Booth et al. (1993) proposed that gas 

hydrate dissociation promotes slope failure. However, the age of the Cape Fear slide had been 

estimated to be between 27,000-10,000 ago (Rodriguez and Paull, 2000) and our newer highresolution bathymetry maps show no clustering of the head walls at 800 m depth (Twichell et al., 

2009; ten Brink et al., 2012). The depth range of the majority of the mapped head scarps is 

1000-1900 m. Thus, gas hydrate dissociation cannot be linked directly to the generation of 

landslides, although it may contribute to increased pore pressure in some locations. 

 

The rise of salt diapirs is expected to increase the slope gradient in certain locations and may 

even cause slope instability. Rising salt diapirs in the area of Cape Fear and Cape Lookout 

could have destabilized the slope there, but causal connection has so far not been established. 

Some landslides in the Gulf of Mexico, such as the large East Break and DeSoto slides are 

located in areas of salt diapirs. Earthquakes might not have been the cause of these landslides 

because the seismicity rate is very low and historical earthquakes magnitudes are small (< M6). 

An additional challenge to estimating landslide tsunami probability results from the uncertainty in 

the coupling of energy between the sliding mass and the water column. Tsunamis from two 

landslides with identical volumes could have different amplitudes depending on the slide speed 

and bottom friction. Moreover, the suggestion that, in passive margins with clastic sediments, 

landslide area is related to earthquake magnitude implies that a landslide is in fact an aggregate 

of many small slope failures within an area that was subject to a super-critical horizontal 

acceleration. The failure area of the 1929 Grand Banks landslide, which caused a devastating 

tsunami, exhibits patches of failures interspersed with seafloor patches where no failure was 

detected (Mosher and Piper, Submarine Mass Movements, 2007). Both the observation of the 

1929 slide scar and the suggested linkage between landslide size and earthquake magnitude 

calls into question the mechanism by which a tsunami is excited from an aggregate failure: Is 

the tsunami the result of constructive interference of many small failures? Or is it generated 

when convergence of debris flows converge in existing canyon and valley corridors and become 

several hundreds of meters thick? Or is it generated when a debris flow ignites into turbidity flow 

as it undergoes a hydraulic jump? More research is needed into this fundamental question 

References: 
83 

Booth, J.S., O’Leary, D.W., Popenoe, P., Danforth, W.W., 1993, U.S. Atlantic continental slope 

landslides: Their distribution, general attributes, and implications, in, Schwab, W.C., Lee, H.J., 

and Twichell, D.C., eds., Submarine landslides: Selected studies in the U.S. Exclusive 

Economic Zone: U.S. Geological Survey Bulletin no. 2002, p. 14-22. 

Brothers, D.S., ten Brink, U.S., Andrews, B.D. & Chaytor, J.D., 2013 in press, Geomorphic 

characterization of the U.S. Atlantic continental margin, Mar. Geol. 

Brothers, D.S., ten Brink, U.S., Andrews, B.D., Chaytor, J.D., & Twichell, D.C., in revision, 

Sedimentary process flow fingerprints in submarine canyons, Mar. Geol. 

Brothers, D.S., Luttrell, K.M. & Chaytor, J.D., Submitted, Sea level induced seismicity and 

submarine landslide occurrence, Geology. 

Chaytor, J.D., Twichell, D.C., and ten Brink, U.S., 2012. A Reevaluation of the Munson-NygrenRetriever Submarine Landslide Complex, Georges Bank Lower Slope, Western North Atlantic. 

In, Yamada, Y (eds.), Submarine Mass Movements and Their Consequences, Advances in 

Natural and Technological Hazards Research v. 31, Springer, New York, 135-145. 

Chaytor, J. D., ten Brink, U. S., Solow, A. R., and Andrews, B. D., 2009, Size distribution of 

submarine landslides along the U.S. Atlantic Margin and its implications to tsunami hazards. 

Mar. Geol., 264, 16-27. 

Corral, A., 2004. Long-term clustering, scaling, and universality in the temporal occurrence of 

earthquakes. Phys. Rev. Lett. 92, doi: 10.1103/PhysRevLett.1192.108501. 

Dugan, B., and Flemings, P.B., 2000. Overpressure and fluid flow in the New Jersey continental 

slope: implications for failure and cold seeps. Science, vol. 289: 288-291 

Flemings, P. B., Long, H., Dugan, B., Germaine, J., John, C. M., Behrmann, J. H., Sawyer, D. & 

IODP Expedition, 308 Scientists, 2008, Pore pressure penetrometers document high 

overpressure near the seafloor where multiple submarine landslides have occurred on the 

continental slope, offshore Louisiana, Gulf of Mexico. Earth Planet. Sci. Lett., 269, 309-325. 

Haflidason, H., R. Lien, H. P. Sejrup, C. F. Forsberg, and P. Bryn, 2005, The dating and 

morphometry of the Storegga Slide, Mar. Petrol. Geol., 22, 123-136 

Kagan, Y.Y., 2010. Statistical distributions of earthquake numbers: consequence of branching 

process. Geophys. J. Int. 180, 1313-1328. 

Kvalstad, T.J., Andresen, L., Forsberg, C.F., Berg, K., Bryn, P., and Wangen, M., 2005. The 

Storegga slide: evaluation of triggering sources and slide mechanics. Mar. Petrol. Geol., 22: 

244-256 

Lee, H.J., 2009. Timing of occurrence of large submarine landslides on the Atlantic ocean 

margin. Mar. Geol., 53-64. 

Mosher, D., & Piper, D., 2007, Analysis of multibeam seafloor imagery of the Laurentian Fan 

and the 1929 Grand Banks landslide area. In, Lykousis, V et al. (eds.), Submarine Mass 

Movements and Their Consequences, v. 27, Springer, New York, 77-88. 
84 

Parsons, T., 2002. Global Omori law decay of triggered earthquakes: Large aftershocks outside 

the classical aftershock zone. J. Geophys. Res. 107, 2199, doi:2110.1029/2001JB000646. 

Phrampus, B. J., & Hornbach, M. J., 2012, Recent changes to the Gulf Stream causing 

widespread gas hydrate destabilization. Nature, 490(7421), 527-530. 

Prior, D. B., & Coleman, J. M., 1978, Disintegrating retrogressive landslides on very‐low‐angle 

subaqueous slopes, Mississippi delta. Marine Georesources & Geotechnology, 3, 37-60. 

Sultan, N., Marsset, B., Ker, S., Marsset, T., Voisset, M., Vernant, A. M., Bayon, G., Cauquil, E., 

Adamy, J., Colliat, J.L & Drapeau, D., 2010, Hydrate dissolution as a potential mechanism for 

pockmark formation in the Niger delta. . J. Geophys. Res. 115, B08101, doi: 

10.1029/2010JB007453. 

Swafford, L., and Stein, S., 2007, Limitations of the short earthquake record for seismicity and 

seismic hazard studies. Special Papers-Geological Society Of America, 425, 49-58. 

Rodriquez, N. M., & Paull, C. K., 2000, 14C dating of sediments of the uppermost Cape Fear 

slide plain: Constraints on the timing of this massive submarine landslide. In Proceedings ODP, 

Scientific Results, v. 164, 325-327, College Station TX (Ocean Drilling Program). 

ten Brink, U.S., J.D. Chaytor; B.D. Andrews, D.S. Brothers, E.L. Geist, 2012, Updated size 

distribution of submarine landslides along the U.S. Atlantic margin, AGU 90(52), Fall Meet. 

Suppl. Abstract OS43C-1827. 

ten Brink, U.S., Barkan, R., Andrews, B.D., Chaytor, J.D., 2009. Size distributions and failure 

initiation of submarine and subaerial landslides. Earth Planet. Sci. Lett. 287, 31-42. 

ten Brink, U.S., Geist, E.L., Andrews, B.D., 2006. Size distribution of submarine landslides and 

its implication to tsunami hazard in Puerto Rico. Geophys. Res. Lett. 33, 

doi:10.1029/2006GL026125. 

Twichell, D. C., Chaytor, J. D., ten Brink, U. S., and Buczkowski, B., 2009, Geologic Controls on 

the Distribution of Submarine Landslides along the US Atlantic Continental Margin. Mar. Geol., 

4-15. 

 
85 

Statistical Testing of Hypotheses and Assumptions Inherent to 

Probabilistic Tsunami Hazard Analysis (PTHA) 

Eric L. Geist1, Tom Parsons1, and Uri ten Brink2

1

U.S. Geological Survey, Menlo Park, CA 94025 

2

U.S. Geological Survey, Woods Hole, MA 02543 

Probabilistic Tsunami Hazard Analysis (PTHA) methods have recently been derived from the 

well-established Probabilistic Seismic Hazard Analysis (PSHA) method that calculates the 

probability of ground shaking from earthquakes, as originally developed by Cornell (1968). Both 

PSHA and PTHA involve three basic steps: (1) source characterization, including definition of 

source parameter distributions and recurrence rates; (2) calculation of wave propagation and 

attenuation effects from source to site; and (3) aggregation of hazard probabilities at the site 

from all sources considered in the analysis (e.g., Geist and Parsons, 2006; Geist et al., 2009). 

The primary differences between PTHA and PSHA are that distant sources must be considered 

in PTHA, owing to the slow attenuation of tsunami waves in the ocean and that numerical 

propagation models can be used in PTHA, in place of empirical attenuation relationships used in 

PSHA. The standard forms of PTHA involve assumptions, such as sources occurring as a 

Poisson process, that are often untested in practice. Although different hypotheses 

representing epistemic uncertainty can be incorporated into PTHA via a logic-tree framework, 

there are a number of statistical tools available with which we can possibly exclude or confirm 

certain hypotheses, thus reducing epistemic uncertainty. We focus here on statistical tests of 

recurrence distributions, size distributions, dependence among parameters, and the ergodic 

hypothesis. Where standard assumptions may be found to be invalid, new approaches to PTHA 

need to be developed. 

It is often assumed that the recurrence distribution of sources follows an exponential distribution 

associated with a stationary Poisson process. For earthquakes, the inclusion of aftershocks 

and triggered events results in temporal clustering at a greater degree than represented by an 

exponential distribution (e.g., Parsons, 2002; Corral, 2004; Kagan, 2010). For very large 

earthquakes (M≥8.3), non-Poissonian behavior has not been observed, given the amount and 

uncertainty in available earthquake data (Parsons and Geist, 2012). Temporal clustering of 

tsunamis themselves has been demonstrated and tested against a Poisson null hypothesis 

(Geist and Parsons, 2011), though aftershocks sensu stricto account for only a part of the over 

abundance of short inter-event times. Non-Poissonian recurrence distributions can 

approximately be incorporated into standard PTHA methodology, using an apparent Poisson 

rate parameter (Petersen et al., 2007). For landslide sources, there is very little data to test the 

Poisson hypothesis, although if the number of landslide events can be determined from marine 

geophysical data and a basal horizon can be dated, Bayesian techniques can be used to 

determine the most likely rate parameter and its uncertainty (Geist and Parsons, 2010; Geist 

and ten Brink, 2012). Optimally, geologic age-dates of landslides from drill hole samples or 

cores can be used to more accurately obtain recurrence rates and assess various probability 

models using, for example, Akaike’s information criterion (Geist et al., in review). Unfortunately, 

there are very few locations where such data are available. Another issue with landslide 

tsunamis is the long-term dependence of submarine landslide activity with glacial cycle and sealevel rise (Lee, 2009). Nonstationary source rates have yet to be incorporated into PTHA. 
86 

There has been considerable discussion regarding distribution of tsunami source sizes, 

particularly for earthquakes. Competing hypotheses include the characteristic earthquake 

model, in which the largest earthquakes are defined by fault segmentation and the historical 

record, and the Gutenberg-Richter earthquake model, in which earthquake sizes follow a Pareto 

distribution (cf. Parsons and Geist, 2009). Although the characteristic earthquake model is 

commonly used in both PSHA and PTHA, there are a number of studies refuting this model 

(e.g., Kagan and Jackson, 1995; Rong et al., 2003; Parsons et al., 2012), particularly for 

subduction zone earthquakes that generate the majority of the world’s tsunamis. Submarine 

landslides also tend to follow a Pareto distribution like their on-land counterparts (ten Brink et 

al., 2006), although in certain environments, it has been shown that a log-normal distribution is a 

more appropriate model (ten Brink et al., 2009). The Pareto distribution for source sizes can, in 

general, be considered the null hypothesis; other distributions can be tested against the Pareto 

distribution using techniques, for example, reviewed by Clauset et al. (2009). 

Independence is often assumed in PTHA and PSHA among source parameters and their 

uncertainty. It is often difficult to develop methods to accommodate dependent parameters in 

probabilistic analysis. An example in PTHA is combining nearshore tsunami waveforms with 

tidal variations: a source of aleatory uncertainty, since tsunami sources cannot be predicted in 

time. The method of Mofjeld et al. (2007) used in the FEMA Seaside PTHA Pilot Study 

(Tsunami Pilot Study Working Group, 2006) uses the linear combination of the tsunami 

amplitude envelope with site-specific distribution of tidal heights. However, landslide tsunami 

waves can be significantly non-linear, such that differences in antecedent sea level cannot 

simply be added or subtracted to tsunami wave heights computed at a given vertical datum. 

Copula methods, common in many hydrology applications, can be applied to examine this and 

other dependent structures in PTHA. Page and Carson (2006) present an application of copula 

methods in determining earthquake probabilities given uncertainties in the data and models. 

Finally, it can be very useful to assume that spatial variations in source characteristics are 

equivalent to temporal variations at a point under the ergodic hypothesis (Geist et al., 2009). 

For example, in the absence of drill-hole data that samples submarine landslides throughout 

geologic time, one can date submarine landslides expressed at the sea floor over a specified 

region, yielding an occurrence rate for the entire region. However, this assumes a similar 

geologic framework (e.g., clastic vs. carbontate) and morphology (e.g., canyon vs. slope) 

throughout the region. Statistical methods to test whether or not the ergodic hypothesis holds 

under specific conditions (cf. Anderson and Brune, 1999) need to be developed in the context of 

PTHA. 

References: 

Anderson, J.G., Brune, J.N., 1999. Probabilistic seismic hazard analysis without the ergodic 

assumption. Seismol. Res. Lett. 70, 19-28. 

Clauset, A., Shalizi, C.R., Newman, M.E.J., 2009. Power-law distributions in empirical data. 

SIAM Review 51, 661-703. 

Cornell, C.A., 1968. Engineering seismic risk analysis. Bull. Seismol. Soc. Am. 58, 1583-1606. 

Corral, A., 2004. Long-term clustering, scaling, and universality in the temporal occurrence of 

earthquakes. Physical Review Letters 92, doi: 10.1103/PhysRevLett.1192.108501. 
87 

Geist, E.L., Chaytor, J.D., Parsons, T., ten Brink, U., in review. Estimation of submarine mass 

failure probability from a sequence of deposits with age dates. Geosphere. 

Geist, E.L., Parsons, T., 2006. Probabilistic analysis of tsunami hazards. Natural Hazards 37, 

277-314. 

Geist, E.L., Parsons, T., 2010. Estimating the empirical probability of submarine landslide 

occurrence, in: Mosher, D.C., Shipp, C., Moscardelli, L., Chaytor, J., Baxter, C., Lee, H.J., 

Urgeles, R. (Eds.), Submarine Mass Movements and Their Consequences IV. Springer, 

Heidelberg, Germany, pp. 377-386. 

Geist, E.L., Parsons, T., 2011. Assessing historical rate changes in global tsunami occurrence. 

Geophys. J. Int. 187, 497-509. 

Geist, E.L., Parsons, T., ten Brink, U.S., Lee, H.J., 2009. Tsunami Probability, in: Bernard, E.N., 

Robinson, A.R. (Eds.), The Sea, v. 15. Harvard University Press, Cambridge, Massachusetts, 

pp. 93-135. 

Geist, E.L., ten Brink, U.S., 2012. NRC/USGS Workshop Report: Landslide Tsunami Probability, 

p. 635. 

Kagan, Y.Y., 2010. Statistical distributions of earthquake numbers: consequence of branching 

process. Geophys. J. Int. 180, 1313-1328. 

Kagan, Y.Y., Jackson, D.D., 1995. New seismic gap hypothesis: Five years after. J. Geophys. 

Res. 100, 3943-3959. 

Lee, H.J., 2009. Timing of occurrence of large submarine landslides on the Atlantic ocean 

margin. Mar. Geol., 53-64. 

Mofjeld, H.O., González, F.I., Titov, V.V., Venturato, A.J., Newman, A.V., 2007. Effects of tides 

on maximum tsunami wave heights: Probability distributions. Journal of Atmospheric and 

Oceanic Technology 24, 117-123. 

Page, M.T., Carlson, J.M., 2006. Methodologies for earthquake hazard assessment: Model 

uncertainty and the WGCEP-2002 forecast. Bull. Seismol. Soc. Am. 96, 1624-1633. 

Parsons, T., 2002. Global Omori law decay of triggered earthquakes: Large aftershocks outside 

the classical aftershock zone. J. Geophys. Res. 107, 2199, doi:2110.1029/2001JB000646. 

Parsons, T., Console, R., Falcone, G., Murru, M., Yamashina, K., 2012. Comparison of 

characteristic and Gutenberg-Richter models for time-dependent M ≥ 7.9 earthquake probability 

in the Nankai-Tokai subduction zone, Japan. Geophys. J. Int., doi: 10.1111/j.1365-

1246X.2012.05595.x. 

Parsons, T., Geist, E.L., 2009. Is there a basis for preferring characteristic earthquakes over a 

Gutenberg-Richter distribution in probabilistic earthquake forecasting? . Bull. Seismol. Soc. Am. 

99, 2012-2019. 
88 

Parsons, T., Geist, E.L., 2012. Were global M≥8.3 earthquake time intervals random between 

1900-2011? Bull. Seismol. Soc. Am. 102, doi:10.1785/0120110282. 

Petersen, M.D., Cao, T., Campbell, K.W., Frankel, A.D., 2007. Time-independent and timedependent seismic hazard assessment for the State of California: Uniform California 

Earthquake Rupture Forecast Model 1.0. Seismol. Res. Lett. 78, 99-109. 

Rong, Y., Jackson, D.D., Kagan, Y.Y., 2003. Seismic gaps and earthquakes. J. Geophys. Res. 

108, ESE 6-1 - 6-14. 

ten Brink, U.S., Barkan, R., Andrews, B.D., Chaytor, J.D., 2009. Size distributions and failure 

initiation of submarine and subaerial landslides. Earth Planet. Sci. Lett. 287, 31-42. 

ten Brink, U.S., Geist, E.L., Andrews, B.D., 2006. Size distribution of submarine landslides and 

its implication to tsunami hazard in Puerto Rico. Geophys. Res. Lett. 33, 

doi:10.1029/2006GL026125. 

Tsunami Pilot Study Working Group, 2006. Seaside, Oregon Tsunami Pilot Study--

Modernization of FEMA Flood Hazard Maps. U.S. Geological Survey Open-File Report 2006-

1234. 

 
89 

Tsunami Flooding Assessment Using Forecast Tools 

Yong Wei1,2, Vasily Titov1

1. Pacific Marine Environmental Laboratory, NOAA, Seattle, WA 98115 and the 

2. Joint Institute for the Study of Atmosphere and Ocean, University of Washington, 

Seattle, WA 98115 

NOAA's Pacific Marine Environmental Laboratory is developing tsunami modeling tools as part 

of the real-time tsunami forecast system for NOAA’s Tsunami Warning Centers. The models are 

used in combination with the real-time deep-ocean measurements to produce estimates of 

tsunami parameters for coastal locations before the wave reaches the coast (Titov, 2005 and 

2009; Tang et al., 2009 and 2012; Wei et al., 2008 and 2012). This real-time tsunami hazard 

assessment will help to provide an informative and site-specific warning for coastal 

communities. Combined with education and mitigation measures, the tsunami forecast and 

warning will provide an effective means for coastal communities to prevent loss of lives from 

tsunamis. It will also reduce the chances for unnecessary evacuations due to over-warning. 

The modeling tools that have been developed for the real-time forecast could also be used for 

the long-term tsunami hazard assessment, in terms of deterministic (Tang et al., 2009; Uslu et 

al., 2010) or probabilistic (González et al. 2009) approach. The forecast models for ocean-wide 

tsunami propagation and coastal inundation are thoroughly developed and tested to provide the 

best possible accuracy. These models provide an opportunity for unprecedented quality scope 

of tsunami hazard assessment for a particular community along U.S. Pacific and Atlantic 

coastline. Together with PMEL’s model database of tsunami propagation, these models are able 

to relate the PTHA offshore wave height to onshore flooding zones for tsunami hazards 

associated with certain design return period. PMEL is collaborating with URS and ASCE to 

explore methodologies to develop 2,500-year tsunami flooding zones based on max tsunami 

amplitude at 30-m depth obtained through PTHA and their disaggregated tsunami sources. 

Several examples of tsunami hazard assessments using the forecast tools will be presented. 

References: 

González, F.I., E.L. Geist, B. Jaffe, U. Kânoğlu, H. Mofjeld, C.E. Synolakis, V.V. Titov, D. Arcas, 

D. Bellomo, D. Carlton, T. Horning, J. Johnson, J. Newman, T. Parsons, R. Peters, C. Peterson, 

G. Priest, A. Venturato, J. Weber, F. Wong, and A. Yalciner (2009): Probabilistic tsunami hazard 

assessment at Seaside, Oregon, for near- and far-field seismic sources. J. Geophys. Res., 114, 

C11023, doi: 10.1029/2008JC005132. 

Tang, L., V.V. Titov, E. Bernard, Y. Wei, C. Chamberlin, J.C. Newman, H. Mofjeld, D. Arcas, M. 

Eble, C. Moore, B. Uslu, C. Pells, M.C. Spillane, L.M. Wright, and E. Gica (2012): Direct energy 

estimation of the 2011 Japan tsunami using deep-ocean pressure measurements. J. Geophys. 

Res., 117, C08008, doi: 10.1029/2011JC007635 

Tang, L., V. V. Titov, and C. D. Chamberlin (2009), Development, testing, and applications of 

site-specific tsunami inundation models for real-time forecasting, J. Geophys. Res., 114, 

C12025, doi:10.1029/2009JC005476. 
90 

Titov, V.V. (2009): Tsunami forecasting. Chapter 12 in The Sea, Volume 15: Tsunamis, Harvard 

University Press, Cambridge, MA and London, England, 371–400. 

Titov, V.V., F.I. González, E.N. Bernard, M.C. Eble, H.O. Mofjeld, J.C. Newman, and A.J. 

Venturato (2005): Real-time tsunami forecasting: Challenges and solutions. Nat. Hazards, 

35(1), Special Issue, U.S. National Tsunami Hazard Mitigation Program, 41–58. 

Uslu, B., V.V. Titov, M. Eble, and C. Chamberlin (2010): Tsunami hazard assessment for Guam. 

NOAA OAR Special Report, Tsunami Hazard Assessment Special Series, Vol. 1, 186 pp. 

Wei, Y., C. Chamberlin, V.V. Titov, L. Tang, and E.N. Bernard (2012): Modeling of 2011 Japan 

Tsunami - lessons for near-field forecast, Pure Appl. Geophys., doi: 10.1007/s00024-012-0519-

z 

Wei, Y., E. Bernard, L. Tang, R. Weiss, V. Titov, C. Moore, M. Spillane, M. Hopkins, and U. 

Kânoğlu (2008): Real-time experimental forecast of the Peruvian tsunami of August 2007 for 

U.S. coastlines. Geophys. Res. Lett., 35, L04609, doi: 10.1029/2007GL032250. 

 
91 

Probabilistic Tsunami Hazard Mapping in California 

Feasibility and Applications 

Charles R. Real1 and Rick Wilson1 

1

 California Geological Survey, Sacramento, CA 95814 

As part of California’s Tsunami Hazard Mitigation and Preparedness Program, the California 

Geological Survey (CGS) is investigating the feasibility of designating official tsunami hazard 

zones under authority of the Seismic Hazards Mapping Act (California Public Resources Code 

Sec 2731 et seq.) and the generation of other products that would facilitate tsunami hazard 

mitigation and risk reduction throughout coastal communities. Several pilot projects are 

underway which are briefly described. 

Probabilistic Seismic Hazard Analysis (PSHA) is the foundation for estimating earthquakeresistant design loads for engineered structures in California and has been considered in landuse decisions at state and local levels for more than a decade. Probabilistic Flood Hazard 

Analysis (PFHA) forms the basis for the National Flood Insurance Program’s 100- and 500-year 

flood maps and California’s 200-year flood hazard maps (California Government Code Sec 

65300.2 et seq.). A probabilistic approach provides a more quantitative analysis for risk-based 

decision-making when considering likelihood of loss and actions that can be taken to reduce it. 

With a sound theoretical basis (Geist and Parsons, 2006) and recent advances in probabilistic 

tsunami inundation modeling (Thio, 2010; González et al., 2009), it is timely to consider 

application of Probabilistic Tsunami Hazard Analysis (PTHA) to risk-reduction. For example, the 

American Society of Civil Engineer’s Subcommittee on Tsunami Loads and Effects is currently 

considering 100-year and 2500-year events in the development of recommended tsunami 

resilient design provisions for the 2018 International Building Code (ASCE, 2012). However, 

recent worldwide events have brought to question the reliability of PSHA, particularly 

considering the long, variable, and uncertain recurrence times of large earthquakes relative to 

exposure times. High accelerations are often occurring in areas shown as low on hazard maps, 

even for locations having a long seismic history (Peresan, A. and Panza, G.F., 2012; Stein et 

al., 2011). Considering difficulties in estimating tsunami frequency brings to question the 

viability of PTHA, and highlights the need to thoroughly assess the modeling framework and 

reliability of input data before derivative products can have application to public policy. 

With support from the National Tsunami Hazard Mitigation Program (NTHMP), CGS and the 

California Emergency Management Agency are partnered with URS Corporation, the Pacific 

Earthquake Engineering Research Center, and the California Department of Transportation 

(Caltrans) to develop probabilistic tsunami hazard maps for the entire California coastline. Initial 

PTHA results are currently used by Caltrans (a project sponsor for URS work) to evaluate the 

vulnerability of coastal transportation facilities, while also serving as a means to explore prototype products for local land-use planning applications. Work completed thus far has focused on 

the development of a practical PTHA procedure that can be applied to a large region and 

refinement of nonlinear wave propagation methods for estimating on-shore wave heights, 

current velocities, and inundation levels from distant sources (Thio and Sommerville, 2010). 

This work is currently expanding to include the Cascadia Subduction zone and smaller local 

sources offshore southern and central California. The NTHMP Mapping and Modeling 

Subcommittee has recommended California’s program be considered a “national pilot” for PTHA 
92 

mapping, and is actively pursuing including this work in the FY2013-2017 NTHMP Strategic 

Plan. To better understand limitations and uncertainties in PTHA, results from the State project 

for Crescent City, California are being compared with those of an independent, FEMA 

sponsored analysis of Crescent City by Baker/AECOM and the University of Washington. That 

project is evaluating the feasibility of incorporating tsunami into coastal flood hazard mapping for 

the National Flood Insurance Program based on improvements to the methodology used in a 

comprehensive PTHA of Seaside, Oregon (González et al., 2009). A committee of experts has 

been assembled that will evaluate results from the two teams considering the differences in 

source, propagation, and inundation components and probabilistic framework of each model. 

A parallel pilot project is exploring issues related to implementation of PTHA and derivative 

hazard mitigation products. Application of conceptual and prototype products and associated 

policies are being discussed with planning and public works departments in Crescent City, a 

small community with a weak economy, and Huntington Beach, a large affluent community. 

Results are expected to help identify viable mitigation products and policy adjustments that may 

be necessary for tsunami hazard mitigation to work given the socio-economic diversity among 

California’s coastal communities. 

A third project supported under the FEMA’s RISKMAP program is developing high-resolution 

proto-type products for the maritime sector based on high-resolution hydrodynamic modeling of 

tsunami induced surge in five California harbors: San Diego Port and Harbor, Ports of Los 

Angeles and Long Beach, Ventura Harbor, Santa Cruz Harbor, and Crescent City Harbor. The 

goal is to model wave heights and current flow in order to identify zones of high current velocity 

that can be used to develop navigation guides for evacuation and for strengthening port 

infrastructure to reduce tsunami impact. It is anticipated that products will be derived from both 

deterministic and probabilistic hazard analyses. 

In addition to the expert PTHA evaluation panel, California has established a Tsunami Policy 

Working Group, operating under the California Natural Resources Agency, Department of 

Conservation, which is composed of experts in earthquakes, tsunamis, flooding, structural and 

coastal engineering and natural hazard policy from government, industry, and non-profit natural 

hazard risk-reduction organizations. The working group serves a dual purpose, being an advisor 

to the State tsunami program and a consumer of insights from the SAFRR Tsunami Scenario 

project. The latter is a USGS study to evaluate the impact of a magnitude 9.1 mega-thrust 

earthquake occurring along the Aleutian Islands Subduction Zone that presents the greatest 

distant tsunami threat to southern and central California. The working groups’ role is to identify, 

evaluate and make recommendations to resolve issues that are preventing full and effective 

tsunami hazard mitigation and risk reduction throughout California’s coastal communities. 

Committee membership is selected to represent entities responsible for coastal development, 

insurance, local and regional planning, public works, foreign and domestic disaster 

preparedness, recovery and seismic policy. Among those selected are representatives of the 

two cities chosen for the State’s tsunami pilot project. Their participation in working group 

deliberations provides opportunity to bring forth local implementation issues in a forum 

conducive to multidisciplinary resolution, and an opportunity to incorporate a local perspective 

while formulating recommendations. 

Finally, CGS is participating as an Associate member in the ASCE Subcommittee on Tsunami 

Loads and Effects where insights from the aforementioned projects are being brought to bear on 

the development of proto-type products supporting the ASCE 7–2015 recommended provisions 

for the International Building Code. The State participated in a similar role years ago when 
93 

PSHA was introduced into seismic provisions of the building code. Products under 

consideration are a 2,500-year tsunami inundation zone that would trigger the code process for 

high-risk category buildings, and production of a database of offshore wave heights and 

principal tsunami sources along the coast from de-aggregated PTHA that can provide the 

necessary input for site-specific deterministic inundation analyses used to estimate design loads 

for proposed construction projects. The work currently underway to evaluate and verify PTHA 

models is complementary to product and application development, and will facilitate California’s 

adoption of tsunami code provisions when they become available. 

References: 

ASCE 2012. Subcommittee on Tsunami Loads and Effects Workshop, July 27-28, Portland, 

Oregon. 

Geist, E.L. and Parsons, T. 2006. Probabilistic Analysis of Tsunami Hazards, Natural Hazards 

37:277-314. 

González, F.I., Geist, E. L., Jaffe, B., Kânoğlu, U., Mofjeld, H., Synolakis, C.E., Titov, V.V., 

Arcas, D., Bellomo, D., Carlton, D., Horning, T., Johnson, J., Newman, J., Parsons, T., Peters, 

R., Peterson, C., Priest, G., Venturato, A., Weber, J., Wong, F., and Yalciner A. 2009. 

Probabilistic tsunami hazard assessment at Seaside, Oregon, for near- and far-field seismic 

sources. Journ. Geoph. Res. 114:C11023. 

Parasen, A. and Panza, G.F. 2012. Improving Earthquake Hazard Assessments in Italy: an 

Alternative to “Texas Sharpshooting.” Trans. Am. Geoph. Union 93:538. 

Stein, S., Geller, R. and Liu, M. 2011. Bad Assumptions or Bad Luck: Why Earthquake Hazard 

Maps Need Objective Testing. Seism. Res. Letters 82:623-626. 

Thio, H.K. and Sommerville, P. 2010. Probabilistic Tsunami Hazard in California. Pacific 

Earthquake Engineering Research Center, PEER 2010/108. 

 
94 

Panel 6: Riverine Flooding 

Co-chairs: Will Thomas, Michael Baker, Jr., Inc. and 

 Rajiv Prasad, Pacific Northwest National Laboratory 

Presenters: Rajiv Prasad, PNNL

 Douglas Clemetson, USACE 

 Mel Schaefer, MGS Engineering 

 Nicole Novembre, BoR 

 Ralph Klinger, BoR 

Rapporteurs: Peter Chaput, NRC (NRO) and Jeff Mitman, NRC (NRR) 

Panelists: Douglas Clemetson, USACE 

 Nicole Novembre, BoR 

 Ralph Klinger, BoR 

 Jery Stedinger, Cornell University 

 Mel Schaefer, MGS Engineering 

 
95 

Flood Frequency of a Regulated River – The Missouri River 

Douglas J. Clemetson, P.E.1 

1

USACE Omaha District, Omaha, NE 

Following the devastating floods that occurred in 1993 along the lower Missouri River and Upper 

Mississippi River, the Upper Mississippi River Flow Frequency Study (UMRFFS) was initiated. 

As part of this study, the discharge frequency relationships were updated for the Missouri River 

downstream from Gavins Point Dam. Establishing the discharge frequency relationships first 

involved extensive effort in developing unregulated flows and regulated flows for a long term 

period of record at each of the main stem gaging stations. Once the unregulated and regulated 

hydrographs were developed, the annual peak discharges were selected for use in the 

discharge frequency analysis. 

In order to provide a homogenous data set from which frequency analysis could be performed, 

effects of reservoir regulation and stream depletions had to be removed from the historic flow 

record. This produced a data set referred to as the "unregulated flow" data set for the period 

1898-1997. A homogeneous "regulated flow" data set was also developed by extrapolating 

reservoir holdouts and stream depletions to present levels over the period of record 1898-1997. 

Flow frequency analyses were performed on the unregulated flow annual peaks using 

procedures found in Bulletin 17B in order to develop the unregulated flow frequency curves for 

the spring and summer seasons at each gage location. The spring and summer unregulated 

flow frequency curves were combined using the “probability of a union” equation by adding the 

probabilities of the spring flow frequency curve and summer flow frequency curve and 

subtracting the joint probability of flooding occurring from seasons to obtain the annual 

unregulated frequency relationships. Next, the period of record regulated flows were developed 

using existing reservoir regulation criteria and present level basin depletions. 

The annual peaks from the regulated and unregulated data sets were then paired against each 

other in descending order to establish a relationship between regulated and unregulated flow at 

each gage location. The regulated versus unregulated relationships were extrapolated based 

on developing design floods by routing historic flows that were increased by as much as 100 

percent. This relationship was then applied to the unregulated flow frequency curve to establish 

the regulated flow frequency curve. Following the record flooding in 2011, the unregulated flow 

and regulated flow data sets were updated to include the additional period of record 1998-2011 

and comparisons were made to the past studies. It was found that the methodology utilized in 

the 2003 study was robust and no changes to the flow frequency relationships were required 

after the record flooding in 2011. 

References: 

US Army Corps of Engineers, EM1110-2-1415, “Hydrologic Frequency Analysis”, 5 Mar 1993. 

US Army Corps of Engineers, “Upper Mississippi River Flow Frequency Study”, Appendix F – 

Missouri River, Omaha District, November 2003. 

 
96 

Extreme Floods and Rainfall-Runoff Modeling 

with the Stochastic Event Flood Model (SEFM) 

M.G. Schaefer 

MGS Engineering Consultants, Inc. 

Stochastic rainfall-runoff modeling provides a methodology for development of magnitude -

frequency relationships for flood peak discharge, flood runoff volume, maximum reservoir level, 

spillway discharge, and overtopping depths for the dam crest and spillways. The basic concept 

is to use Monte Carlo methods to conduct multi-thousand flood simulations utilizing 

hydrometeorological inputs and watershed model parameters obtained from the historical record 

within the climatic region. Storm magnitude is driven by a precipitation-frequency relationship for 

the watershed and spatial and temporal storm characteristics are simulated using storm 

templates developed from historical storms on the watershed or transposed from sites within the 

climatic region. Hydrometeorological inputs such as: storm seasonality; antecedent soil 

moisture; snowpack depth and density; time-series of 1000-mb air temperature and freezing 

level; and initial reservoir level are treated as variables rather than fixed values in the flood 

simulations. 

The Stochastic Event Flood Model (SEFM) utilizes these concepts to develop flood-frequency 

relationships for flood characteristics such as flood peak discharge and maximum reservoir level 

for use in risk analyses for dams and other facilities. Uncertainties can also be incorporated into 

the flood simulations to allow development of uncertainty bounds. Development of SEFM 

began in 1998 and has continued over the past 15-years. During that time, SEFM has been 

used at over 20 dam and reservoir projects in the western US and British Columbia primarily to 

assess the likelihood of hydrologic loadings from extreme floods. This presentation will provide 

a basic description of the operation of SEFM and results from selected case studies. 

 
97 

Use of Stochastic Event Flood Model and Paleoflood Information 

to Develop Probabilistic Flood Hazard Assessment 

for Altus Dam, Oklahoma 

Nicole J. Novembre, Victoria L. Sankovich, 

Jason Caldwell, and Jeffrey P. Niehaus 

U.S. Department of Interior, Bureau of Reclamation, Technical Service Center, Denver, CO 

A Hydrologic Hazard Analysis (HHA) was completed at the request of the Bureau of 

Reclamation Dam Safety Office (Novembre et al., 2012), as one part of a Corrective Action 

Study for Altus Dam near Altus, OK. This study is designed to provide flood loading and 

reservoir elevation information that is needed in support of a risk assessment to reduce the 

probability of failure under static and hydrologic loading at the dikes. 

The main objectives of this study were: 

1. Collect at-site, detailed paleoflood data with stratigraphy, radiocarbon ages, and 

hydraulic modeling within the basin, to supersede the preliminary estimates used in a 

2001 study. 

2. Develop a precipitation frequency relationship for the drainage area. Develop storm 

temporal and spatial patterns for use in a hydrologic model. 

3. Develop a peak flood frequency curve using Expected Moments Algorithm (EMA). 

4. Develop flood frequency relationships and inflow hydrographs with a stochastic event 

flood model (SEFM) (Schaefer and Barker, 2002; MGS Engineering, 2009). 

5. Route the thousands of hydrographs generated with SEFM through Altus Dam with 

appropriate initial reservoir water surface elevations and provide reservoir water surface 

elevation frequency curves and quantiles for use in risk analysis. 

Paleoflood data were collected on the North Fork Red River near Altus Dam (Godaire and 

Bauer, 2012). Two study reaches, one located upstream of Lake Altus and one located 

downstream of Altus Dam, were used to develop paleoflood data. A non-exceedance bound 

was estimated with a discharge range of 120,000 ft3

/s to 141,000 ft3/s, that has not been 

exceeded in the last 610 to 980 years. Three or more paleoflood events with a discharge of 

26,000 ft3

/s to 36,000 ft3/s, that occurred between 790 and 1240 years ago, were estimated. 

A peak flood frequency curve was developed from streamflow gage data and the paleoflood 

data using the Expected Moments Algorithm (EMA). EMA (Cohn et al., 1997; England et al., 

2003) is a moments-based parameter estimation procedure that assumes the LP-III distribution 

is the true distribution for floods, and properly utilizes historical and paleoflood data. The EMA 

results are presented in Table 3.1 and Figure 3.3. 

A Stochastic Event Flood Model (SEFM) was developed for the Altus Dam watershed. 

Magnitude- frequency rainfall estimates, as well as rainfall storm temporal and spatial patterns, 

were developed as input to the model. The model was calibrated to observed events and used 

to develop estimates of hydrographs for the 2% to 0.001% annual exceedance probability 

events. These hydrographs were routed through Altus Dam to develop reservoir water surface 

elevation frequency curves to be used as part of the risk analysis for Altus Dam. 
98 

The recommended hydrologic hazard curves for risk analysis are the SEFM curves using the 

lower and median precipitation frequency curves (Table 1 and Figure 1). The risk analysis 

should assume that each of these flood frequency relationships and their associated 

hydrographs could occur with equal probability of occurrence. The corresponding reservoir 

elevations (Table 2) were developed using reservoir operating rules provided by Reclamation’s 

Waterways and Concrete Dams Group, therefore, the routing results can be utilized without 

modification to evaluate the potential overtopping failure mode of Altus Dam and dikes. These 

two curves represent equal estimates of the hydrologic hazard for baseline and risk reduction 

alternatives. Extrapolation of these results should be limited to an AEP of 0.001%. The full 

uncertainty of the hydrologic hazard is broader than that depicted in these two curves. 

Uncertainty analysis should consider variations in model parameters, data reliability, and climate 

variability. Further consultation with a flood hydrologist is needed in the selection of inflow flood 

loads for corrective action. 

Table 1: Recommended peak discharge and 15-day volume values. 

Annual 

Exceedance 

Probability 

Return 

Period 

(years) 

Lower Precipitation 

Frequency 

Median Precipitation 

Frequency 

Peak 

Discharge 

(ft3/s) 

15-Day 

Runoff 

Volume 

(ac-ft) 

Peak 

Discharge 

(ft3/s) 

15-Day 

Runoff 

Volume 

(ac-ft) 

1.0% 100 40,000 150,000 48,000 181,000 

0.1% 1000 85,000 329,000 108,000 419,000 

0.01% 10,000 169,000 665,000 223,000 882,000 

0.001% 100,000 292,000 1,098,000 390,000 1,487,000 

Table 2: Recommended reservoir water surface elevation. 

Annual 

Exceedance 

Probability 

Return 

Period 

(years) 

Lower Precipitation 

Frequency 

Median Precipitation 

Frequency 

Routing 

Case 1 

Routing 

Case 2 

Routing 

Case 1 

Routing 

Case 2 

1.0% 100 1560.7 1558.8 1561.3 1559.4 

0.1% 1000 1565.2 1564.5 1567.9 1567.5 

0.01% 10,000 1571.2 1571.1 1572.1 1572.1 

0.001% 100,000 1572.7 1572.7 1573.4 1573.4 
99 

Figure 1: Recommended peak discharge frequency curves. 
100 

Figure 2: SEFM reservoir water surface elevation frequency curves. 

Cohn, T.A., W.L. Lane, and W.G. Baier. 1997. An algorithm for computing moments-based 

flood quantile estimates when historical information is available, Water Resour. Res., 33(9), 

2089–2096. 

England, J.F., Jr., R.D. Jarrett, and J.D. Salas. 2003. Data-based comparisons of moments 

estimators using historical and paleoflood data, J. of Hydrology, 278(4), 172-196. 

Godaire, J.E. and T. Bauer. 2012. Paleoflood Study, North Fork Red River Basin near Altus 

Dam, Oklahoma. Technical Memorandum No. 86-68330-2012-14. Bureau of Reclamation. 

MGS Engineering Consultants, Inc. (MGS Engineering). 2009. General Storm Stochastic Event 

Flood Model (SEFM) - Technical Support Manual, version 3.70, prepared for the Bureau of 

Reclamation, Flood Hydrology Group, Denver, CO, 281 p. 

Novembre, N.J., V.L. Sankovich, R.J. Caldwell, and J.P. Niehaus, 2012. Altus Dam Hydrologic 

Hazard and Reservoir Routing for Corrective Action Study. Bureau of Reclamation Technical 

Service Center, August 2012. 

Schaefer, M.G., and Barker, B.L. 2002. Stochastic Event Flood Model. In Mathematical models 

of small watershed hydrology and applications, chapter 20, edited by V.P. Singh and D. Frevert, 

Water Resources Publications, Littleton, CO, pp. 707-748. 

 
101 

Paleoflood Studies and their Application to Reclamation Dam Safety 

Ralph E. Klinger1 

1

Bureau of Reclamation, Technical Service Center, 

P.O. Box 25007, 86-68330, Denver, CO 80225 

The Bureau of Reclamation manages more than 350 water storage dams in the western U.S. 

that primarily provide water for irrigation. Periodically, each structure is subjected to a 

Comprehensive Review (CR) and the safety of each dam is evaluated on the basis of its current 

condition, past performance, and its projected response to loads that are reasonably expected 

to test the structural integrity of the structure and its various components. The findings of the CR 

are used to assess the potential failure risks and potential for loss of life and property. This risk 

profile allows the Reclamation Dam Safety Office to better manage its available resources to 

reduce risk and meet established public safety guidelines. 

Hydrologic hazards are one of the hazards used in the CR and in the past Reclamation used 

traditional deterministic criteria (i.e., the Probable Maximum Flood) for evaluating dam safety. 

Unfortunately, more than half of the dams in the Reclamation inventory failed to meet these 

criteria and the costs associated with modifying the dams to meet this standard were considered 

prohibitive. By utilizing probabilistic flood hazard analyses (PFHA), the Dam Safety Office could 

better categorize its inventory on the basis risk and prioritize corrective actions. However, using 

the historical record of flooding alone in a PFHA proved inadequate for accurately estimating the 

magnitude of less frequent floods. Because paleoflood data can add information on large 

magnitude floods outside the historical period of record, as well as place outliers in the record 

into temporal context, paleoflood studies have long been recognized as an avenue for 

advancement in evaluating flood hazard. 

Beginning in 1993, the Bureau of Reclamation began incorporating paleoflood data into 

hydrologic hazard estimates. Paleoflood studies were structured to collect the information to 

meet immediate needs for screening-level risk assessments. Larger, more detailed studies were 

developed to reduce uncertainty and provide the Dam Safety Office with the information needed 

to make critical decisions regarding public safety. As the result of almost 20 years of developing 

paleoflood information at more than 150 Reclamation projects - in addition to advances made by 

others in the fields of geochronology, hydraulic modeling, and statistical hydrology - the 

incorporation of paleoflood information has vastly improved Reclamation’s ability to accurately 

estimate flood hazard for its inventory of dams. 

 
102 

Panel 7: Extreme Storm Surge for Coastal Areas

Co-Chairs: Donald Resio, Univ. of North Florida and 

 Ty Wamsley, USACE 

Presenters: Joost Beckers, Deltares 

 Stephen Gill, NOAA 

 Tucker Mahoney, FEMA 

 Ty Wamsley, USACE 

 Jen Irish, Virginia Polytechnic Institute (VPI) 

 Donald Resio, University of North Florida 

Rapporteurs: Mark Fuhrmann, NRC (RES) and 

 Ferrando Ferrante, NRC (NRR) 

Panelists: Joost Beckers, Deltares 

 Stephen Gill, NOAA 

 Tucker Mahoney, FEMA 

 Jennifer Irish, VPI 

 
103 

Coastal Flood Hazard in the Netherlands 

Joost Beckers1, Kathryn Roscoe1, and Ferdinand Diermanse1 

1

Deltares, Delft, The Netherlands 

The Netherlands has a long history of fighting floods. About 60% of the country is flood prone 

and must be protected by levees or dikes. Up to the first half of the 20th century, design dike 

heights were roughly 1 m above the highest measured water level. In 1953, a catastrophic 

storm surge flooded the southern part of the Netherlands. More than 1800 people drowned. In 

response to this tragedy, a national committee was installed who proposed to shorten the 

coastline by building storm surge barriers (the Delta Works) and to further decrease the flood 

hazard by implementing stringent standards for flood protection (Delta Committee 1958). 

Nowadays, the Dutch flood defences along the major water systems (rivers, lakes, sea) 

comprise of a system of dikes (about 3300 km), dunes (about 300 km), storm surge barriers (5) 

and hundreds of hydraulic structures like sluices. These flood defences surround about 100 

areas called dike rings. Each dike ring has been assigned a safety standard, expressed in terms 

of a maximum failure probability or return period. This can be translated into a maximum 

hydraulic load that a structure must be able to withstand. 

The hydraulic load on a structure can be a combination of a water level, wave conditions or 

other conditions, depending on the failure mechanism under consideration. The maximum 

hydraulic load for a given return period is determined by a probabilistic computation that takes 

into account many possible combinations of external forcings that all lead to hydraulic loads on 

the flood defence. The probabilistic methods are based on statistical analyses of hydrologic and 

meteorological measurements and on numerical hydrodynamic and wave growth models. 

The safety assessment procedure will be illustrated by considering the wave overtopping hazard 

for a coastal levee. The probabilistic model that is used evaluates the overtopping discharge 

and probability of occurrence for hundreds of combinations of storm surge and wind induced 

waves. The model uses water level and wind speed statistics that are based on observations 

and that have been extrapolated to exceedance probabilities of 10-5 per year. A non-parametric 

method is used to account for the dependency between wind and water level (De Haan and 

Resnick, 1977). The SWAN wave growth model (Booij et al., 1999) is used to translate the 

offshore wind and water level to nearshore wave conditions. 

References: 

Booij, N., R.C. Ris and L.H. Holthuijsen (1999). A third generation wave model for coastal 

regions, Part I, Model description and validation. J. Geophys. Res., 104, C4, 7649-7666. SWAN 

website: http://www.swan.tudelft.nl 

De Haan, L. and S.I. Resnick (1977). Limit theory for multivariate sample extremes, 

Z.Warscheinlichkeittheorie verw. Gebiete 40, 317-337. 

F.L.M. Diermanse and C.P.M. Geerse (2012), Correlation models in flood risk analysis. 

Reliability Engineering and System Safety 105, pp64-72. 
104 

K. Roscoe, S. Caires, F. Diermanse & J. Groeneweg (2010), Extreme offshore wave statistics in 

the North Sea, FRIAR - WIT Transactions on Ecology and the Environment, Vol 133 

 
105 

Recent Work and Future Directions in 

Coastal Surge Modeling within NOAA 

Stephen K. Gill1 and Jesse C. Feyen2 

1

CO-OPS 

2

Coast Survey Development Laboratory, National Ocean Service, Silver Spring, MD 20874 

NOAA’s mission with respect to coastal storm surges focuses on the protection of life and 

property and on improving the resiliency of coastal communities. The former effort focuses on 

forecasting and warning coastal populations and emergency managers of imminent hazardous 

conditions, while the later addresses the long term risks coastal communities face. In order to 

perform these missions, NOAA relies upon models and observations to assess the hazard, and 

uses a variety of products to communicate the data to the public. 

In order to forecast coastal inundation, NOAA uses multiple models, both operational and 

experimental. The operational model SLOSH (Sea, Lakes, and Overland Surges from 

Hurricanes) is storm surge model that is designed for fast, efficient prediction of surges in order 

to meet critical operational timelines. SLOSH uses several techniques in order to provide 

extremely fast computations, including simplification of nonlinear terms in the governing 

equations, a basic hurricane forcing model, omission of tide and wave effects, small model 

domains, and low resolutions. These efficiencies enable SLOSH to run very quickly and its 

possible to run numerous hurricane tracks in a short time. This capability is used in the 

generation of the Maximum Envelopes of Water (MEOW) used for hurricane evacuation studies, 

which requires more than 10,000 simulations. It is also used to generate storm surge 

probabilities in the P-Surge tool, which runs hundreds of hurricane tracks in real time. P-Surge 

varies the hurricane prediction by taking historical forecast error into consideration, and is able 

to determine the probability of surge reaching a specific height for each forecast cycle. 

NOAA has also recently transitioned the ADCIRC coastal hydrodynamic model to operations for 

predicting storm surges from extratropical storms. High resolution ADCIRC predictions have 

also been evaluated experimentally for their use in real-time tropical cyclone storm surge 

predictions. ADCIRC tends to be higher resolution and has higher physical fidelity than SLOSH 

(e.g., includes tides, rivers, waves). These ADCIRC simulations are more precise than their 

SLOSH counterparts, but because of the cost to run them only a few iterations are possible in 

real-time. This small ensemble of approximately five members can give a sense of the 

uncertainty surrounding a prediction, but isn’t sufficient to determine storm surge probabilities. 

 However, when considering issues of coastal resiliency it is important to validate and compare 

model predictions to observed data records, particularly in light of a changing climate. NOS has 

a long history of observing and analyzing water level conditions. This data has been used to 

perform extreme water level analyses that provide an assessment of the probability of extreme 
106 

conditions occurring. The water level data has also been subject to an analysis of the long-term 

trend due to factors including global sea level rise and vertical land motion. NOS has recently 

upgraded online services to provide updated sea level trends for NOAA long-term tide stations 

and has produced an extreme water levels tool from which exceedance probability levels can be 

obtained. Recently, NOAA produced an assessment of the expected effects of climate change 

and sea level conditions. 

 
107 

FEMA’s Coastal Flood Hazard Analyses 

in the Atlantic Ocean and Gulf of Mexico 

Tucker B. Mahoney 

FEMA – Region IV, Mitigation Division, Risk Analysis Branch, Atlanta, GA 30341

One of the missions of the Federal Emergency Management Agency (FEMA) is to identify and 

map the nation’s 1%-annual-chance flood hazard risk, in support of the National Flood 

Insurance Program (NFIP). Presently, FEMA is undertaking a substantial effort to update the 

Flood Insurance Studies (FIS) and Flood Insurance Rate Maps for the populated coastal areas 

in the United States. These areas are among the most densely populated and economically 

important areas in the nation. 

Coastal flooding on the Atlantic Ocean and Gulf of Mexico coasts is a product of combined 

offshore, nearshore, and shoreline processes. The interrelationships of these processes are 

complex and their relative effects can vary significantly by location. These complexities present 

challenges in mapping a local or regional hazard from coastal flooding sources. Congress’ 

mandate to FEMA to assess and map the 1%-annual-chance flood hazard based on present 

conditions simplifies some of these complexities. As part of the study process, FEMA also 

identifies the 0.2%-annual-chance flood hazard for coastal areas. In some cases, higher 

frequency risks, such as the 2%, 10%, 25% and 50%, will be examined and made available to 

communities for informational purposes. 

The most severe storms, which dominate the coastal 1%-annual-chance flood risk, on the 

Atlantic Ocean and Gulf of Mexico coast can generally be classified as either tropical systems or 

northeasters. Because long term records of water level are spare compared to the risk, FEMA’s 

Guidelines and Specifications require that a probabilistic assessment of storm surge and coastal 

flooding be undertaken where applicable (FEMA, 2007). Ongoing coastal flood risk studies 

utilize the Joint Probability Method-Optimal Sampling (JPM-OS) to statistically model the spatial 

and temporal occurrence and characteristics of tropical systems, typically hurricanes (Resio, 

2007; Toro et al. 2010). For the mid- to north-Atlantic coastline, northeasters also contribute to 

the 1%-annual chance coastal flood risk. The contribution of these storms to the flood hazard 

risk is evaluated using the Empirical Simulation Technique (Scheffner, et al. 1999). 

For each individual storm to be evaluated (be it historical or synthetic), the still water elevation, 

including wave setup, is determined using a two-dimensional hydrodynamic model and a twodimensional wave model. Recent FEMA coastal flood hazard studies utilize the coupled 

SWAN+ADCIRC model to couple together the still water level and wave modeling (Dietrich et al. 

2012). The model mesh typically extends well inland from the coast in order to capture the full 

extent of the storm surge which propagates overland during an extreme event. The smallest 

cell spacing is typically between 50-100 feet and depending on location, the mesh may extend 

to the 30 or 50 feet NAVD88 contour. Results of these simulations are used to statistically 

determine the still water elevation, including wave setup, for a given recurrence interval (i.e. 1%-

annual-chance). 

After determination of the statistical still-water-elevation, the next step is to simulate the 

propagation of waves overland using the one-dimensional model Wave Hazard Analysis for 
108 

Flood Insurance Studies (WHAFIS), which was developed by the National Academy of Sciences 

for this purpose (NAS, 1977). Input for WHAFIS is drawn from the nearshore wave model. 

From the WHAFIS results, FEMA then maps then delineates and maps flood hazard zones on a 

the Flood Insurance Rate Map. 

Although a coastal FIS uses state-of-the-art techniques, improvements are still possible and will 

likely occur in coming years. For example, more research is needed into two-dimensional 

overland wave modeling to truly characterize wave conditions and interactions at a specific 

location. It would be beneficial if variable future conditions, from factors such as shoreline 

change, sea level rise, or changes in climate, and their impact on the flood hazard could be 

accounted for. Lastly, a full uncertainty and error analysis is needed. 

Other federal agencies and scientific bodies may benefit from some of the tools produced by 

FEMA for an updated coastal FIS. For each study, a detailed seamless topographic and 

bathymetric digital elevation model will be created for most locations in the coastal United 

States using the best and most recently available data. A highly detailed, fully attributed 

numerical model mesh will be created for most locations on the Atlantic Ocean and Gulf of 

Mexico coasts and may also be utilized for other flood hazard studies. A mesh can be easily 

modified to add detail to an area of interest or expanded further upland to simulate larger storm 

surges than those encountered during a FEMA coastal flood hazard study. Lastly, the JPM 

framework and variety of input storm conditions may provide useful information to future 

assessments of coastal flood risk with lower probabilities of occurrence. 

References: 

Dietrich, J.C. et al. (2012), “Performance of the Unstructured-Mesh SWAN+ADCIRC Model in 

Computing Hurricane Waves and Surge”, Journal of Scientific Computing, 52 (2), 468-497. 

Federal Emergency Management Agency (2007), “Atlantic Ocean and Gulf of Mexico Coastal 

Guidelines Update”, Final Draft. 

National Academy of Sciences, (1977), “Methodology for Calculating Wave Action Effects 

Associated with Storm Surges”, Washington, D.C. 

Resio, D.T. (2007), White paper on estimating hurricane inundation probabilities, Version 11. 

Scheffner, N.W., et al. (1999), “Use and application of the Empirical Simulation Technique: 

User’s Guide.” U.S. Army Engineer Research Development Center, Vicksburg, MS. Technical 

Report CHL-99-21. 

Toro, G. et al. (2010), “Quadrature-based approach for the efficient evaluation of surge hazard”, 

Ocean Engineering, Volume 37, Issue 1. 

 
109 

Modeling System for Applications to 

Very-Low Probability Events and Flood Response 

Ty V. Wamsley and T. Christopher Massey 

U.S. Army Corps of Engineers, Coastal and Hydraulics Laboratory (CHL), Vicksburg, MS 39183 

Modeling coastal surge in complex regions requires an accurate definition of the physical 

system and inclusion of all significant flow processes. Processes that affect storm surge 

inundation include atmospheric pressure, winds, air-sea momentum transfer, waves, river flows, 

tides, friction, and morphologic change. Numerical models now exist that can properly define 

the physical system and include an appropriate non-linear coupling of the relevant processes. A 

coupled system of wind, wave, circulation, and morphology models has been developed and 

implemented for regions in the Gulf of Mexico, Atlantic, and Great Lakes. The US Army Corps 

of Engineers (USACE) Engineer and Research Development Center’s (ERDC) Coastal Storm 

Modeling System (CSTORM-MS) (Massey et al. 2011) includes a tropical planetary boundary 

layer model, TC96 MORPHOS-PBL (Thompson and Cardone, 1996), to generate the cyclone 

wind and pressure fields. It is also possible to use a variety of other wind products including 

both measured and hindcast winds. The storm surge and current fields are modeled with the 

ocean hydrodynamic model ADCIRC (Luettich et al. 1992) which computes the pressure- and 

wind-driven surge component. The regional and nearshore ocean wave models, WAM (Komen 

et al 1994) and STWAVE (Smith et al 2001) generate the wave fields. The AdH model (Berger 

and Howington 2002) is applied to simulate the nearshore zone where morphology change is 

computed and utilizes the CHL 2-Dimensional nearSHORE (C2SHORE) sediment transport and 

morphology change code through a call to its SEDiment transport LIBrary (SEDLIB). 

A physics-based modeling capability must necessarily link the simulation of winds, water levels, 

waves, currents, sediment transport, and coastal response (erosion, accretion, breaching) 

during extreme events in an integrated system. A flexible and expandable computational 

coupler (CSTORM coupler) utilizes design principles from the Earth System Modeling 

Framework (ESMF) and links the atmosphere, circulation, waves, and morphology models for 

application on desktop computers or high-performance computing resources. The computational 

coupler employs a two-way coupling scheme that not only enhances the represented physics, 

but also results in significant improvements in computational time when compared to file-based 

approaches. A series of integrated graphical user interfaces within the Surface-water Modeling 

System (SMS) allows for convenient setup and execution of these coupled models. 

The ESMF is a set of open source software tools for both building and linking complex weather, 

climate and related models. It has support from many agencies within the Department of 

Defense, the National Oceanic and Atmospheric Administration (NOAA), and the National 

Aeronautics and Space Administration (NASA). In order for models to use ESMF, they need to 

be ESMF compliant which means their computer code is organized into three distinct phases: 

initialization, run and finalization. Models that meet this standard allow for an almost “plug-nplay” capability when being used within an ESMF enabled coupler such as the CSTORM 

coupler. Therefore, the system is well suited for expansion to include effects from urban 

flooding or flood propagation at the facility scale. 
110 

Flood response operations and hazard mitigation during an event requires knowledge not only 

of the ultimate high water elevation, but also the timing of the flood wave. A reasonable 

estimation of the flood hydrograph requires the application of a high resolution model. The 

modeling system described allows for flexible spatial discretizations which enables the 

computational grid to be created with larger elements in open-ocean regions where less 

resolution is needed, and smaller elements can be applied in the nearshore and estuary areas 

where finer resolution is required to resolve hydrodynamic details and more accurately simulate 

the timing of storm surge propagation. However, application of high fidelity modeling such as 

that described above can be time prohibitive in operational mode. The USACE has developed a 

proof-of-concept operational flood prediction system that utilizes pre-computed high fidelity 

simulations stored in a database applying surrogate modeling strategies. This approach 

provides multi-process predictions in seconds for flood hazard assessment and mitigation. 

References: 

Berger, R. C. and Howington, S. E., 2002. Discrete Fluxes and Mass Balance in Finite 

Elements. ASCE Journal of Hydraulic Engineering, Vol 128, No. 1 (Jan) 87-92. 

Komen, G.J., L. Cavaleri, M. Donelan, K. Hasselmann, S. Hasselmann, and P.A.E.M. Janssen. 

1994. "Dynamics and modelling of ocean waves." Cambridge University Press, Cambridge, UK. 

Luettich, R.A., J.J. Westerink, and N.W. Scheffner. 1992. “ADCIRC: an advanced threedimensional circulation model for shelves, coasts and estuaries, report 1: theory and 

methodology of ADCIRC-2DDI and ADCIRC-3DL.” Tech. Rep. DRP-92-6, U.S. Army Corps of 

Engineers. Available at: ERDC Vicksburg (WES), U.S. Army Engineer Waterways Experiment 

Station (WES), ATTN: ERDC-ITL-K, 3909 Halls Ferry Road, Vicksburg, MS, 39180-6199. 

Massey, T.C., Wamsley, T.V., and Cialone, M.A. 2011. “Coastal Storm Modeling – System 

Integration”. Proceedings of the 2011 Solutions to Coastal Disasters, ASCE, 99-108. 

Smith, J.M., A.R. Sherlock, and D.T. Resio. 2001. STWAVE: Steady-State spectral Wave Model 

User’s manual for STWAVE, Version 3.0, ERDC/CHL SR-01-1, U.S. Army Corps of Engineers 

Engineer Research and Development Center, Vicksburg, MS. 

Thompson, E. F. and V. J. Cardone, (1996). “Practical modeling of hurri-cane surface wind 

fields,” ASCE J. of Waterway, Port, Coastal and Ocean Engineering 122(4), 195-205. 

 
111 

Coastal Inundation Risk Assessment 

Jennifer L. Irish 

Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061 

In the last decade, the US has experienced some of its largest surges and hurricane-related 

damages on record. Understanding the risk posed by extreme storm surge events is important 

both for effective evacuation and for future coastal engineering planning, management, and 

design. For the first, effective evacuation in advance of a hurricane strike requires accurate 

estimation of the hurricane surge hazard that effectively conveys risk not only to government 

decision makers but also to the general public. Two primary challenges exist with the current 

structure for surge warning. First, existing computational methods for developing accurate, 

quantitative surge forecasts, namely surge height and inundation stimation, are limited by time 

and computational resources. Second, due primarily to the popularity and wide use of the SaffirSimpson wind scale to convey the complete hurricane hazard, the public’s perception of surge 

hazard is inaccurate. For the second, reliable extreme-value hurricane flooding estimates are 

essential for effective risk assessment, management, and engineering in the coastal 

environment. However, both a limited historical record and the range of, and uncertainty in, 

future climate and sea-level conditions present challenges for assessing future hurricane 

flooding probability. Historical water level observations indicate that sea level is rising in most 

hurricane prone regions, while historical observations of hurricane meteorology indicate decadal 

variation hurricane patterns, to include landfall location and rate of occurrence. Recent studies, 

including those by the Intergovernmental Panel on Climate Change (IPCC), also suggest that in 

the future sea-level rise may accelerate and major tropical cyclones may intensify. Methods will 

be presented for robustly and efficiently quantifying both forecast and extreme-value surge 

statistics, where the later will incorporate sea-level rise and time-varying hurricane conditions. A 

joint probability approach will be used with surge response functions to define continuous 

probability density functions for hurricane flood elevation. Joint probability is assigned based on 

the probability of the hurricane meteorological parameters, such as rate of hurricane landfall, 

central pressure, and storm radius. From a theoretical standpoint, surge response functions are 

scaling laws derived from high-resolution numerical simulations, here with the hydrodynamic 

model ADCIRC. Surge response functions allow rapid algebraic surge calculation based on 

these meteorological parameters while guaranteeing accuracy and detail by incorporating highresolution computational results into their formulation. Thus the use of surge response functions 

yields continuous joint probability density functions. The form of the surge response functions 

allows direct assessment, within the joint probability framework, of alternate probability 

distributions for any hurricane parameter. Uncertainty in the probabilistic estimates will be 

discussed in the context of extreme-value statistics by considering the variability in future 

climate and sea level projections. Here, we use dimensionless scaling and hydrodynamics 

arguments to quantify the influence of hurricane variables and regional geographic 

characteristics on the surge response. In summary, physical attributes of hurricane surge can 

be quantified using forecasted, historical, and hypothetical hurricane track information, and this 

information may be used to more rapidly and accurately convey surge hazard to planners, 

decision makers, and the public. Note: Abstract is modified from those presented at the 

American Geophysical Union Fall Meetings in2011 and 2012. 

 
112 

Uncertainty and Very-Low Probability Estimates 

Donald T. Resio 

CCEC, University of North Florida, 1 UNF Drive, Jacksonville, FL 32224

As a wrap-up to the rest of the presentations of the panel, this brief presentation will discuss 

three potential impacts related to the quantification of hazard probabilities: 1) the role of hybrid 

storms (such as Sandy) in storm populations; 2) the impact of mixed populations in probabilistic 

methods; 3) the influence of uncertainty on expected exceedances; 4) the potential role of upper 

limits on the estimation of very-low probabilities. 

 
113 

Panel 8: Combined Events Flooding 

Co-Chairs: David Margo, USACE and Joost Beckers, Deltares 

Presenters: Kit Ng, Bechtel Power Corporation 

 Chris Dunn, USACE 

 Martin McCann, Stanford University 

 Joost Beckers, Deltares 

 Doug Clemetson, USACE 

 Pat Regan, FERC 

Rapporteurs: Michelle Bensi, NRC (NRO) and Jeff Mitman, NRC (NRR) 

Panelists: Kit Ng, Bechtel Power Corporation 

 Chris Dunn, USACE 

 Martin McCann, Stanford University 

 Joost Beckers, Deltares 

 Doug Clemetson, USACE 

 Pat Regan, FERC 

 
114 

Combined Events in External Flooding Evaluation 

 for Nuclear Plant Sites 

Kit Y. Ng1

1

Bechtel Power Corporation, Geotechnical & Hydraulic Engineering Services, Frederick, 

MD 21703 

The presentation will review the historical and current practices of assessing combined events 

for flooding due to external events at nuclear plant sites. The current industry and regulatory 

guides on the evaluation of combined events flooding including RG 1.59, NUREG/CR-7046, 

NUREG 0800, and ANSI/ANS 2.8-1992 are primarily deterministic based. As stated in ANS 2.8, 

no single flood-causing event is an adequate design base for a power reactor. Combined events 

can be sequential or coincidental occurrences of attendant or causative flood causes. The 

criteria for selecting the set of combined events depend on the location of the plant and the 

characteristics of the flood causing phenomena specific to the site. ANS 2.8 also indicates that 

an average annual exceedance probability less than 1X10-6 is an acceptable goal for selection 

of flood design bases for power reactor plants. This paper examines the fundamentals of 

combined events in the deterministic framework. In addition, it explores the challenges of 

evaluating external flooding in the probabilistic space. 

 
115 

Assessing Levee System Performance Using 

Existing and Future Risk Analysis Tools 

Christopher N. Dunn, P.E., D.WRE1 

1

USACE Hydrologic Engineering Center, Davis, CA 

A process was defined to apply risk analysis methodologies to identify potential system-wide 

hydraulic impacts resulting from modifications to the Sacramento River Flood Control Project 

(SRFCP). This effort demonstrated that existing risk analysis tools can be applied in a systems 

context to reveal responses of one region of a system from perturbations to another region. The 

example application illustrates the complexities and effort required to conduct a system-wide 

risk analysis. US Army Corps of Engineers (USACE) policy, as stated in ER 1105-2-101, "Risk 

Analysis for Flood Damage Reduction Studies" (USACE, 2006a), requires the use of risk 

analysis and its results in planning flood risk management studies and are to be documented in 

principal decision documents. The goal of the policy is a comprehensive approach in which the 

key variables, parameters, and components of flood risk management studies are subject to 

probabilistic analysis. The benefit of the process for the evaluation of proposed modifications to 

the SRFCP is an increased understanding of the potential risk inherent in modification 

alternatives. A second, but no less important goal of this exercise, was to understand more fully 

what is required to advance the current methods and tools for risk management assessments. 

Thus, a major purpose of this effort was to identify and assist the development of methods, 

tools, and guidance for performing and using risk and reliability assessments that match the 

complexity and frequency of the assessments. An introduction to the next generation of flood 

risk analysis tool, HEC-WAT/FRA (Watershed Analysis Tool with the Flood Risk Analysis 

option), is also presented. 

 
116 

Seismic Risk of Co-Located Critical Infrastructure Facilities – 

Effects of Correlation and Uncertainty 

Martin W. McCann, Jr.1 

1

Jack R. Benjamin & Associates, Inc., Menlo Park, CA ; Stanford University, Stanford, CA 

This paper looks at issues associated with estimating risk of seismically initiated failure of dams 

and other critical infrastructure facilities that are co-located with respect to each other and the 

location of future earthquakes. In the case of dams, a seismically initiated failure produces a 

second hazard, the uncontrolled release of the reservoir, which may impact other dams 

downstream or other critical facilities located on the waterway. Dams may be on the same river 

or regionally co-located on different rivers. Failure of one or more dams could lead to serial dam 

failures on a single river; or produce regional consequences on multiple rivers. In the case of 

downstream critical infrastructure that may be located in the floodway and also impacted by the 

same seismic event, the ability to prepare for and respond to potential flood conditions may be 

compromised by the earthquake. This paper looks at the effect of different sources of correlation 

or dependence on the risk to a portfolio of co-located dams and other critical infrastructure 

projects. A parametric study is performed to examine the effect that different sources of 

uncertainty and correlation have on seismic risk analysis results. Sources of uncertainty and 

correlation that are discussed include the epistemic uncertainty in the seismic hazard analysis, 

the inter-event earthquake variability and the intra-event spatial correlation of ground motions in 

the region impacted by the earthquake. The parametric study that evaluates a number of these 

factors are described. The consequences of a seismic event are not limited to dam failure and 

downstream inundation. Since it is far more likely that dams may be damaged (as opposed to 

failing immediately as a result of the earthquake) as a result of the seismic event, the post-event 

period may be critical in terms of during a seismic event, these ‘other’ consequences include 

loss of function (i.e., hydropower production, control of gate systems or other outlets, etc.) as 

reservoirs may need to be lowered following the earthquake in order to prevent a subsequent 

failure (e.g., 1971 Lower San Fernando Dam). 

References: 

Boore D.M., Gibbs J.F., Joyner W.B., Tinsley J.C., and Ponti D.J. 2003. Estimated ground 

motion from the 1994 Northridge, California, earthquake at the site of the interstate 10 and La 

Cienega Boulevard bridge collapse, West Los Angeles, California, Bulletin of the Seismological 

Society of America, 93(6), 2737–2751. 

Chiou, B.S.J. and Youngs, R.R., 2008, An NGA model for the average horizontal component of 

peak ground motion and response spectra, Earthquake Spectra, 24, 173-215. 

Federal Emergency Management Agency (FEMA). 2009. HAZUS-MH MR4: FEMA's Software 

Program for Estimating Losses from Disasters. Earthquake Model, Hurricane Model, and Flood 

Model: technical manuals. National Institute of Building Sciences (NIBS), 

http://www.fema.gov/plan/prevent/hazus/#1. 

Federal Energy Regulatory Commission. 2009. The Strategic Plan – FY 2008-2014. 
117 

Park, J., Bazzurro, J.P., & Baker, J.W. 2007. Modeling spatial correlation of ground motion 

Intensity Measures for regional seismic hazard and portfolio loss estimation. Applications of 

Statistics and Probability in Civil Engineering. Edited by Kanda, Takada and Furuta. London: 

Taylor & Francis Group. 

Reed, J.W., McCann, Jr., M.W., Iihara, J. & Hadid-Tamjed, H. 1985. Analytical techniques for 

performing probabilistic seismic risk assessment of nuclear power plants. 4th International 

Conference on Structural Safety and Reliability. No. III, 253-263. 

Senior Seismic Hazard Analysis Committee. 1997. Recommendations for probabilistic seismic 

hazard analysis: Guidance on uncertainty and use of experts. U.S. Nuclear Regulatory 

Commission, 1997, NUREG/CR-6372. 

 
118 

Storm Surge - Riverine Combined Flood Events 

Joost Beckers1 and Ferdinand Diermanse1 

1

Deltares, Inland Water Systems, Delft, The Netherlands 

River deltas are flat areas between riverine and coastal influences. These deltas are at risk of 

flooding caused by intense rainfall runoff or by a severe storm surge at sea, or by a combination 

the two phenomena. This implies that there is no single design storm, but rather a collection of 

likely and less likely combinations of extreme and less extreme rainstorms and storm surges. 

Together, these combinations constitute the design flood levels. To calculate these flood levels 

requires a probabilistic assessment of all possible hydraulic conditions and associated 

probabilities of occurrence. This is a complex and computationally demanding task, especially if 

the number of combinations is further increased e.g. by the possibility of failure/non-failure of a 

storm surge barrier. In the probabilistic flood hazard assessment, typically hundreds up to 

thousands of combinations of external forcings are considered. The design water level at a 

location of interest is computed for each combination by a hydraulic model. A numerical 

integration over all possible combinations and their probabilities produces the design flood level 

for a given return period. The probability of occurrence of a particular combination should take 

into account the correlation – if any – between the external forcings. Various correlation models 

can be employed to determine the likelihood of each combination of forcing conditions. An 

example will be presented in which a copula function was used. 

References: 

J.V.L. Beckers, F.L.M. Diermanse, A. Verwey, et al. (2012), Design of flood protection in Hong 

Kong, Proceedings of FloodRisk2012 Conference, Rotterdam, November 2012. 

F.L.M. Diermanse and C.P.M. Geerse (2012), Correlation models in flood risk analysis. 

Reliability Engineering and System Safety 105, pp64-72. 

 
119 

Combining Flood Risks from Snowmelt, Rain and Ice – 

The Platte River in Nebraska 

Douglas J. Clemetson, P.E.1 

1

USACE Omaha District, Omaha, NE 

In the past it has been common practice to combine open water and ice-affected flood risks to 

obtain an all-season flood risk. The all-season stage frequency curve is normally computed 

using the “probability of a union” equation by adding the probabilities of the open water stage 

frequency curve and the ice-affected stage frequency curve and subtracting the joint probability 

of flooding occurring from both types of event. This approach works fine for streams in which 

both types of events occur every year. However, for the Platte River in Nebraska, ice-affected 

stages do not occur every year so using this approach would tend to overestimate the frequency 

of flooding. Therefore, an alternative approach was developed and was subsequently adopted 

by FEMA for use in Flood Insurance Studies. 

The alternate approach involves developing a stage-frequency curve using all annual-maximum 

stages that are ice-affected events and a separate stage-frequency curve using all the annualmaximum stages that are open water events during the snowmelt/ice season. Each frequency 

curve is called a “conditional-frequency curve.” The ice-affected conditional-frequency curve is 

“conditioned” in the sense that only annual-maximum peak stages that are ice-affected-related 

are used in the frequency analysis. To obtain the probability of an ice-affected event exceeding 

a given stage in any year, the exceedance probabilities from the conditional- frequency curve 

are multiplied by the fraction of time that ice-affected events produce annual-maximum peak 

stages during the snowmelt/ice season. The open water conditional-frequency curve is 

“conditioned” in the sense that only annual- maximum peak stages that are open water events 

are used in the frequency analysis. To obtain the probability of a open water event exceeding a 

given stage in any year, the exceedance probabilities from the conditional-frequency are 

multiplied by the fraction of time that open water events produce annual-maximum peak stages 

during the snowmelt/ice season. The conditional frequency curves for the snowmelt/ice season 

frequency curve are then combined to obtain the probability of the annual-maximum stage 

exceeding a given stage in any year due to either open water or an ice-affected event during the 

snowmelt/ice season. For the annual-maximum series, the stage-frequency curves for 

snowmelt/ice season and the rainfall season are then combined to obtain the all-season 

frequency curve. 

References: 

US Army Corps of Engineers, EM1110-2-1415, “Hydrologic Frequency Analysis”, 5 Mar 1993. 

US Army Corps of Engineers, “Lower Platte River, Nebraska – Flood Insurance Study”, 

Technical Support Data, July 2003. 

Federal Emergency Management Agency, “Guidelines and Specifications for Flood Hazard 

Mapping Partners”, Appendix F – Guidelines for Ice Jam Analysis and Mapping, April 2003. 

 
120 

Human, Organizational and Other 

Factors Contributing to Dam Failures 

Patrick J Regan1 

1

Principal Engineer – Risk Informed Decision Making, Federal Energy Regulatory Commission 

“We pretend that technology, our technology, is something of a life force, a will, and a thrust of 

its own, on which we can blame all, with which we can explain all, and in the end by means of 

which we can excuse ourselves.” 

(T. Cuyler Young, Man in Nature) 

A review of investigation reports for several recent failures of dams, pipelines and offshore oil 

platforms suggests that there are many human and organizational factors that contribute to 

these failures in addition to the, often more simplistic, “root cause” that generally focuses on a 

single path of component failures and human errors. Among the contributing factors in 

infrastructure failures are : 

1) Organizations being driven by financial performance resulting in decisions being 

made to operate systems near the boundaries of safety; 

2) Organization safety programs focused on personal safety rather than system safety; 

3) A tendency to fixing symptoms of problems rather than determining the underlying 

causes and fixing the fundamental problems; 

4) Organizations that are often complacent about safety due to the low frequency of 

adverse events, arrogant about the probability of an adverse event happening to 

them and ignorant of the real risks inherent in their operations; 

5) Poor communication within, and outside, of organizations; 

6) Organizations focused on meeting the letter of regulatory requirements but ignoring 

the underlying spirit and purpose of the regulations; and 

7) A lack of corporate safety culture in many organizations. 

The criticality of including factors such as those listed above derives from the fact that the way 

our infrastructure systems are built and operated today is significantly different from the way 

similar structures were constructed and operated in the not so distant past. Nancy Leveson, in 

Engineering a Safer World , outlines nine reasons why we need new ways to assess the safety 

of our systems: 

1) Fast pace of technology change 

2) Reduced ability to learn from experience 

3) Changing nature of accidents 

4) New types of hazards 

5) Increasing complexity and coupling 

6) Decreasing tolerance for single accidents 

7) Difficulty in selecting priorities and making tradeoffs 

8) More complex relationships between humans and automation 

9) Changing regulatory and public views of safety 
121 

Leveson also provides considerations for a new accident model to help us understand the 

complex systems that comprise our infrastruture: 

1) Expand accident analysis by forcing consideration of factors other than component 

failures and human errors 

2) Provide a more scientific way to model accidents that produces a better and less 

subjective understanding of why the accident occurred and how to prevent future 

ones 

3) Include system design errors and dysfunctional system interactions 

4) Allow for and encourage new types of hazard analyses and risk assessments that go 

beyond component failures and can deal with the complex role software and humans 

area assuming in high-tech systems 

5) Shift the emphasis in the role of humans in accidents from errors (deviations from 

normative behavior to focus on the mechanisms and factors that shape human 

behavior (i.e. the performance-shaping mechanisms and context in which human 

actions take place and decisions are made. 

6) Encourage a shift in the emphasis in accident analysis from “cause” – which has a 

limiting, blame orientation – to understanding accidents in terms of reasons, i.e. why 

the events and errors occurred 

7) Examine the processes involved in accidents and not simple events and conditions 

8) Allow for and encourage multiple viewpoints and multiple interpretations when 

appropriate 

9) Assist in defining operational metrics and analyzing performance data 

In summary, we must understand the broader system in which our infrastructure operates. That 

system necessarily must include the organizations and people who own operate and maintain 

these facilities. The purpose of this workshop is to explore these concepts. In many cases the 

ability of a nuclear station to withstand a flood involves a complex interaction between two very 

complex systems each of which is also affected by other systems such as the electric grid, the 

road network, communication lines, etc. 
122 

Biographies 

George Apostolakis: The Honorable George Apostolakis was sworn in as a Commissioner of 

the U.S. Nuclear Regulatory Commission (NRC) on April 23, 2010, for a term ending on June 

30, 2014. 

Dr. Apostolakis has had a distinguished career as a professor, an engineer, and risk analyst. He 

is internationally recognized for his contributions to the science of risk assessment for complex 

systems. Before joining the NRC, he was a professor of Nuclear Science and Engineering and a 

professor of Engineering Systems at the Massachusetts Institute of Technology. 

Dr. Apostolakis served as a member of the NRC statutory Advisory Committee on Reactor 

Safeguards (ACRS) from 1995 to 2010. He also served as Chairman of the ACRS in 2001 and 

2002. 

In 2007, Dr. Apostolakis was elected to the National Academy of Engineering for “innovations in 

the theory and practice of probabilistic risk assessment and risk management.” He founded the 

International Conference on Probabilistic Safety Assessment and Management. He served as 

the Editor-in-Chief of the International Journal Reliability Engineering and System Safety. Dr. 

Apostolakis received the American Nuclear Society (ANS) Tommy Thompson Award for his 

contributions to improvement of reactor safety in 1999 and the ANS Arthur Holly Compton 

Award in Education in 2005. He is a Fellow of the ANS and the Society for Risk Analysis. 

Dr. Apostolakis holds a Ph.D. in Engineering Science and Applied Mathematics (awarded in 

1973) and an M.S. in Engineering Science (1970) both from the California Institute of 

Technology. He earned his undergraduate degree in Electrical Engineering from the National 

Technical University in Athens, Greece in 1969. 

Gregory Baecher: Dr. Gregory B. Baecher is Glenn L. Martin Professor of Engineering in the 

Department of Civil and Environmental Engineering, University of Maryland. Dr. Baecher was a 

member of the Interagency Performance Evaluation Task Force (IPET) that performed the risk 

analysis for post-Katrina New Orleans, and is a consultant to the water resources sector on risk 

and safety. He is a member of the National Academy of Engineering and the author of four 

books on risk related to civil infrastructure. 

Joost Beckers: Joost Beckers is a senior researcher at Deltares, an independent research 

institute for water management issues. Joost holds a PhD in computational physics (1999) and 

specialized in hydrology and statistics in his professional career. Before joining Deltares in 

2005, he was employed at the Dutch Institute for Coastal and Marine Management. At Deltares, 

he is mainly active in the field of flood risk assessment, with special expertise in extreme value 

statistics, stochastic modeling and uncertainty. His recent projects involved loss of life risk 

modeling, establishing design water levels for flood protection and developing probabilistic 

models for correlated events. 

W. Mark Blackburn: Mark is a twenty-six year Federal Service employee. Mark is currently 

Director, Office of Nuclear Facility Safety Programs (HS-32) within the DOE Office of Health 

Safety and Security (HSS) with responsibility for developing and maintaining DOE nuclear 

facility safety programs in general facility safety, nuclear materials packaging,, readiness 

reviews, oversight of training in nuclear facilities, the DOE facility representative and safety 

system oversight programs, and nuclear and nonnuclear facility safety for natural phenomena 
123 

hazards, fire protection, maintenance. Prior to this position, he was Acting Director in the Office 

of Nuclear Safety Basis and Facility Design with nuclear safety policy responsibility for general 

nuclear facility safety analysis and design, Specific Administrative Controls, Unreviewed Safety 

Questions, Justifications for Continued Operations, Criticality Safety and Nuclear Material 

Packaging. 

Before joining HSS in July 2009, Mark served in several capacities with the National Nuclear 

Security Administration (NNSA) from September 1990 through July 2009. As part of the 

September 2008 – May 2009 NNSA Acquisition Strategy Team (AST), he was responsible for 

identifying and evaluating contracting options for all NNSA sites. As the Pantex Site Office 

Assistant Manager for Oversight and Assessment and the Chief for Safety, Health, and Quality 

Assurance, he administered programs in occupational safety and health, construction safety, 

assessments, operations quality assurance, and weapons and operations quality related to 

nuclear weapons activities. He also worked as the DOE Albuquerque Operations Office 

Nuclear Materials Transportation Manager and as a nuclear weapons manager and engineer at 

Pantex while gaining a broad management and technical background in operations, safety, 

quality, and business. Prior to Pantex, he held engineering positions with the Department of 

Defense (DOD) in Texas, Kentucky, and Missouri. 

Mark holds a Bachelor’s degree in Industrial Engineering from Mississippi State University and 

completed the DOD Maintainability Engineering Intern program and NNSA Mid-level Leadership 

Development Program (MLDP). As part of the MLDP, he briefed the NNSA Administrator on the 

Pantex Site contractor’s year-end performance evaluation and did a rotation at NNSA 

Headquarters. He is a licensed Professional Engineer in the State of Texas and a Professional 

Member of the American Society of Safety Engineers. 

Geoff Bonnin: Geoff Bonnin is a civil engineer with the National Weather Service (NWS) Office 

of Hydrologic Development. He manages science and technique development for flood and 

stream flow forecasting, and for water resources services provided by NWS. He initiated and 

oversees the development of NOAA Atlas 14, Precipitation Frequency Atlas of the Unites States 

and was lead author of the first three volumes. He was a technical advisor for Engineers 

Australia’s update of their precipitation frequency estimates. 

His primary areas of expertise are in the science and practice of real time flood forecasting, 

estimation of extreme precipitation climatologies including the potential impact of climate 

change, data management as the integrating component of end-to-end systems, and the 

management of hydrologic enterprises. In 2011 he spent several months with the Australian 

Bureau of Meteorology to identify specific techniques and technologies for sharing between the 

Bureau and NWS. 

David Bowles: David S. Bowles, Ph.D., P.E., P.H., D.WRE, F.ASCE and his colleagues since 

1978 have pioneered the development and practical application of risk-informed approaches to 

dam safety management. They have completed individual and portfolio risk assessments for 

more than 800 dams in many countries, ranging from screening assessments to detailed 

assessments with uncertainty analysis. David has assisted with the development of tailored 

frameworks for dam and levee safety risk management for government and private owners, 

regulators and professional bodies in many countries. Clients have included Reclamation, 

USACE, TVA, FERC, BIA, World Bank, WMO, IAEA, EU, ANCOLD, NSW DSC and numerous 

private dam owners. He has conducted risk assessments for the failure of dams affecting a 

nuclear station and currently he advises EPRI on external flooding probabilistic evaluation and 
124 

dam failures. David has served as an expert witness for law suits related to dam and canal 

failures, reservoir operation and hydropower generation, toxic tort, and urban flooding. David 

has provided training programs on six continents and has authored or reviewed numerous 

guidance documents for dam safety risk analysis, assessment and management. He has led 

software development for dam risk analysis (DAMRAE) and life-loss estimation (LIFESim with a 

simplified version in HEC-RAS) for USACE, portfolio risk assessment for a large UK dam owner 

(ResRisk), and real-time reservoir flood operation for Reclamation, USACE and SAFCA. David 

is the Managing Principal of RAC Engineers and Economists and an Emeritus Professor of Civil 

and Environmental Engineering at Utah State University (USU). Previous positions include 

Director of the Institute for Dam Safety Risk Management and Director of Utah Center for Water 

Resources Research at USU, Engineering Department Manager and Branch Manager for Law 

Engineering’s Denver office, and a construction and design engineer for a large international 

contractor based in the UK. 

R. Jason Caldwell: Jason Caldwell is a Meteorologist in the Flood Hydrology and 

Consequences Group in the Technical Service Center (TSC) of the Bureau of Reclamation in 

Denver, Colorado. He has served in the TSC for 2 years, and has worked in the fields of 

meteorology, climatology, and hydrology for over 15 years. His earlier positions were as a 

Hydrometeorological Analysis and Support Forecaster at the Lower Mississippi River Forecast 

Center and climatologist at the South Carolina State Climate Office. He will complete a Ph.D. in 

Civil (Water Resources) Engineering from the University of Colorado in 2013. His principal 

responsibility is providing expert technical advice on gridded meteorological data processing, 

hydrometeorological statistics, and extreme storm analysis to TSC management and staff 

concerning hydrologic issues for Reclamation and other Department of Interior facilities. 

Nilesh Chokshi: Currently, Dr. Nilesh Chokshi is Deputy Director, Division of Site and 

Environmental Reviews in the Office of New Reactors. During his 33 years at the NRC, Dr. 

Chokshi has managed several research and regulatory areas including seismic and structural 

engineering, materials engineering, operating experience risk analysis, and radiation protection. 

He has also been extensively involved in the area of probabilistic risk assessment, particularly in 

the development of external event methodology and the standard. Dr. Chokshi has been ViceChairman of Board of Directors of ASME Codes and Standards Technology Institute; past 

Chairman of CSNI Working Group on Integrity and Aging of Components and Structures; he is a 

member of Advisory Board of International Association of Structural Mechanics in Reactor 

Technology (IASMiRT); and was Chairman of International Scientific Committee of 16th SMiRT 

Conference. Prior to joining the NRC, Dr. Chokshi worked at an architectural/engineering firm 

involved in designs of nuclear power plants. Dr. Chokshi obtained his Ph. D. in the field of civil 

engineering (with specialization in structural engineering) from Rice University and Master=s 

degree from University of Michigan. 

Douglas J. Clemetson: Doug Clemetson serves as the Chief, Hydrology Section, Hydrologic 

Engineering Branch in the Engineering Division of the U.S. Army Corps of Engineers’ Omaha 

District. As Chief of the Hydrology Section, Doug supervises a staff that includes seven 

hydraulic engineers, a meteorologist, a geographer and a student, who prepare the hydrologic 

studies required for the planning, design and operation of all the water resource projects in the 

Omaha District. 

In addition, his staff advises and supports Emergency Management prior to and during flood 

emergencies within the Missouri River Basin. He has extensive experience in flood hydrology, 
125 

water supply hydrology, statistics, watershed modeling, reservoir simulation, extreme storm 

analysis, and flood forecasting. 

During his career, Doug has worked in the Missouri River Division Technical Engineering 

Branch and Reservoir Control Center and has served as an H&H Specialist in the HQUSACE 

Emergency Operations Center following Hurricanes Katrina and Rita in 2005. He has also been 

the leader of the Inflow Flood Methodology Team for the USACE Dam Safety Program; is the 

USACE representative on the federal interagency Extreme Storm Events Work Group; is the 

leader of the USACE Extreme Storm team; and has been a member of the USACE Hydrology 

Committee since 1996 where he currently serves as vice-chairman of the committee. 

Doug earned his bachelor’s degree in Civil Engineering from South Dakota State University in 

1980. He is a registered Professional Engineer in the State of Nebraska, a member of the 

American Society of Civil Engineers, and a member of the Association of State Dam Safety 

Officials. He has been with the Corps of Engineers in Omaha for over 32 years. 

Tim Cohn: Tim Cohn works in the USGS Office of Surface Water where he has co-authored 

more than 25 papers on methods for estimating flood risk and related topics. He previously 

served as USGS Science Advisor for Hazards and as AGU's 1995-96 AAAS Congressional 

Science Fellow in the office of Senator Bill Bradley. Tim holds M.S. and Ph.D. degrees from 

Cornell University and a B.A. from Swarthmore College. 

Christopher Cook: Starting in December 2012, Dr. Cook became chief of the Hydrology and 

Meteorology Branch, Office of New Reactors (NRO), at the Nuclear Regulatory Commission. 

Prior to joining the branch, he also served as chief of the Geoscience and Geotechnical 

Engineering Branch and a senior hydrologist in the Office of New Reactors for a number of 

years. As a hydrologist, Dr. Cook performed numerous technical reviews to support NRC’s 

safety evaluation reports (SER) and environmental impact statements (EIS) associated with 

Early Site Permit (ESP) and Combined License (COL) applications for new nuclear reactors. 

Prior to joining the NRC, Dr. Cook supported the U.S. Nuclear Regulatory Commission as a 

technical reviewer in the area of hydrology while employed at the Pacific Northwest National 

Laboratory (PNNL). He contributed to technical reviews associated with NRC’s safety 

evaluation reports (SER) and environmental impact statements (EIS) on the North Anna, 

Clinton, Grand Gulf, and Vogtle Early Site Permit (ESP) applications. Past research at PNNL 

and the University of California, Davis, focused on multi-dimensional hydrodynamic and water 

quality modeling of surface water systems, including the use of three-dimensional computational 

fluid dynamics (CFD) models. 

Dr. Cook holds a B.S. in Civil Engineering from Colorado State University, a M.S. in Civil 

Engineering from the University of California, Davis, specializing in groundwater hydrology, and 

a Ph.D. from the University of California, Davis, specializing in multi-dimensional hydrodynamic 

and water quality modeling of surface water systems. 

Christopher N. Dunn: Christopher Dunn is the director of the Hydrologic Engineering Center 

(HEC) in Davis, CA with more than 25 years experience. His expertise includes flood damage 

and impact analysis, planning analysis, risk analysis, levee certification, river hydraulics, surface 

water hydrology, storm water management, watershed systems analysis, and ecosystem 

restoration. He was the project manager for HEC’s role in the Sacramento/San Joaquin 

Comprehensive Study and also lead the development of flood damage reduction, ecosystem 

restoration, and system analysis software tools. He has also worked on several international 
126 

projects including water management modeling in Iraq and Afghanistan, training in Japan, and 

collaboration with the USGS on a Learning Center in Turkey. 

John England: John England is a flood hydrology technical specialist with the Bureau of 

Reclamation in Denver, Colorado, USA. Dr. England's research and project interests include 

extreme flood understanding and prediction, rainfall-runoff modeling, flood frequency, 

hydrometeorology, paleoflood hydrology, and risk analysis. For the past 15 years he has 

developed and applied probabilistic flood hazard techniques to evaluate the risk and safety of 

Bureau of Reclamation dams, and has overseen implementation of risk-based techniques for 

the dam safety program. John has numerous publications including journal articles, book 

chapters, conference proceedings, guidelines, technical manuals, and reports. Dr. England 

received his M.S. and Ph.D. in hydrology and water resources from Colorado State University. 

He is a registered Professional Hydrologist with the American Institute of Hydrology, a 

registered Professional Engineer in Colorado, and holds a Diplomate, Water Resource Engineer 

(D.WRE) from the American Academy of Water Resources Engineers (AAWRE). Dr. England 

was awarded the Bureau of Reclamation Engineer of the Year and nominated as one of the top 

10 Federal Engineers in 2008. 

Fernando Ferrante: Fernando Ferrante is currently working as a Reliability and Risk Analyst 

with the U.S. Nuclear Regulatory Commission (US NRC) in the application of probabilistic risk 

assessment (PRA) tools and models to the oversight of operating nuclear reactors in the US. 

His primary focus is on quantitative risk assessments using the SAPHIRE software, as well as 

the development of PRA tools for use in analyzing so-called “external” events (e.g., internal fire, 

seismic and external flooding events). 

Prior to joining the US NRC, Dr. Ferrante worked as a Research Engineer at Southwest 

Research Institute (SwRI) in the Center for Nuclear Waste Regulatory Analysis (CNWRA). His 

responsibilities included prelicensing activities in support of the US NRC High-Level Waste 

program, development of risk-informed, performance-based regulatory guidance and 

performance assessment of a potential nuclear high-level waste repository. 

Dr. Ferrante has a Ph.D. from Johns Hopkins University (2005) in Civil Engineering (thesis topic 

on probabilistic mechanics), MS in Civil Engineering from University of Virginia (2000) and BS in 

Mechanical Engineering from University College London, England (1997). 

Eric Geist: Eric Geist is a Research Geophysicist with the Pacific Coastal & Marine Science 

Center of the U.S. Geological Survey (USGS), where he has worked for 28 years. Throughout 

his career, he has focused on computer modeling of geophysical phenomena, including largescale deformation of the earth in response to tectonic forces and the physics of tsunami 

generation. For the last ten years, he has led research and developed methods for the 

probabilistic analysis of tsunami hazards. Eric has authored over 120 journal articles and 

abstracts, including an article in Scientific American on the devastating 2004 Indian Ocean 

tsunami and a series of review papers on tsunamis for Advances in Geophysics. Eric received 

his BS degree in Geophysics from the Colorado School of Mines and his MS degree in 

Geophysics from Stanford University. 

Eric Gross: Eric Gross has a Bachelor's degree from Rensselaer Polytechnic Institute and a 

Master's in Civil/Water Resources Engineering from the University of Maryland. He is registered 

as a Professional Engineer (Civil) in the State of Maryland. He has been with the Federal 

Energy Regulatory Commission for 10 years and is a member of the FERC's Risk Informed 
127 

Decision Making (RIDM) team. The RIDM Team is tasked with incorporating risk concepts into 

FERC's dam safety program. Currently, he is chairing FERC's Risk Technical Resource Group, 

heading the team writing FERC's guidelines for dam failure consequences determination, and a 

member of the St. Louis River Project canal embankment failure investigation team. He was a 

member of the Taum Sauk Dam failure investigation team, and the lead engineer for FERC's 

first risk informed inflow design flood determination. 

Jason Hedien: Jason Hedien is Vice President and a Principal Geotechnical Engineer and 

Project Manager with MWH. At MWH Jason has over 18 years of experience in the 

management, inspection, analysis and design of dams and hydropower projects, infrastructure 

and waterway/port projects, and wastewater and water supply projects. Jason’s professional 

experience includes conducting deterministic and probabilistic seismic hazard analyses, risk 

assessments, earthquake engineering for dams and civil infrastructure projects, and dam safety 

engineering for the evaluation of dam safety and implementation of dam safety improvements 

for dams and ancillary structures. 

Jennifer L. Irish: Dr. Irish is an associate professor of civil engineering at Virginia Tech with 

expertise in storm surge dynamics, storm morphodynamics, vegetative effects, coastal hazard 

risk assessment, and general coastal engineering. She is a Diplomate of Coastal Engineering 

and licensed Professional Engineer with 18 years of experience. Dr. Irish has published more 

than 30 journal papers. Irish recently received the Department of the Army Superior Civilian 

Service Award (2008) and Texas A&M University’s Civil Engineering Excellence in Research 

Award (2010). Dr. Irish teaches coastal engineering and fluid mechanics and leads research on 

extreme event and climate change impacts at the coast. 

Henry Jones: Henry Jones is a hydrologist in the Division of Site Safety and Environmental 

Analysis of the Office of New Reactors within the U.S. Nuclear Regulatory Commission (U.S. 

NRC). He has worked at the U.S. NRC for 6 years in the Branch of Hydrology and Meteorology. 

Prior to working at the U.S. NRC, Henry Jones served 28 years in the United States Navy as a 

physical oceanographer and meteorologist. His principal responsibility is providing expert 

technical advice to NRC management and staff concerning tsunami and storm surge hydrologic 

issues for NRC-licensed facilities. 

Annie Kammerer: Dr. Annie Kammerer is a senior seismologist and earthquake engineer in 

the Office of Nuclear Regulatory Research at the United States NRC, where she coordinates 

the NRC’s Seismic Research Program. In this role, she is responsible for overseeing research 

on a broad range of seismic topics ranging from seismic and tsunami hazard assessment to 

seismic risk assessments for nuclear facilities. She was project manager and contributing author 

on the NRC’s current guidance on conducting seismic hazard assessments (Regulatory Guide 

1.208 and NUREG 2117). She is also currently the NRC project manger and representative on 

the Joint Management Committee for “Next Generation Attenuation-East” project, which is 

developing ground motion prediction equations for central and eastern North America for use 

with the recently published CEUS SSC for Nuclear Facilities model. She was a member of the 

Participatory Peer Review Panel for the CEUS SSC project. Dr. Kammerer is currently the 

NRC’s technical lead for the seismic walkdowns being conducted at all 104 operating reactors in 

the US as part the NRC’s Post-Fukushima activities. Dr. Kammerer has authored over 3 dozen 

publications, including regulatory guidance, technical reports, journal articles, a book chapter, 

conference proceedings and papers, and an ASCE special publication. She was a contributing 

author on the tsunami guidance contained in IAEA Safety Standard Guide 18. 
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Dr. Kammerer holds three degrees from the University of California, Berkeley, including a BS 

degree in Civil Engineering, a MS degree in Geotechnical Engineering, and a PhD in 

Geotechnical Earthquake Engineering, with minors in Seismology and Structural Engineering. 

Ralph Klinger: Ralph Klinger is a Quaternary Geologist and Geomorphologist at the Bureau of 

Reclamation’s Technical Service Center in Denver, Colorado. He received his B.S. and M.S. in 

Geological Sciences from San Diego State University and his Ph.D. in Geology from the 

University of Colorado, Boulder. He has been involved in studying the geologic record of 

natural hazards throughout the western U.S. for almost 30 years. His principal responsibility at 

Reclamation is to provide technical expertise to the Dam Safety Office and advise the 

engineering staff on seismic and flood hazards and their use in the evaluation of risk. 

Randall LeVeque: Randy LeVeque is a Professor of Applied Mathematics at the University of 

Washington, where he has been on the faculty since 1985. He is a Fellow of the Society for 

Industrial and Applied Mathematics (SIAM) and of the American Mathematical Society (AMS). 

His research is focused on the development of numerical algorithms and software for the 

solution of wave propagation problems. For the the past 10 years he has been working on 

development and application of the GeoClaw software for tsunami modeling and other 

hazardous geophysical flows. 

S. Samuel Lin: S. Samuel Lin, PhD, P.E., D.WRE is a civil engineer specialized in hydrologic 

and hydraulic (H&H) safety and associated risk analyses of hydropower generation dams under 

Federal Energy Regulatory Commission’s jurisdiction. He has been a Federal and State dam 

safety regulator for 24 years. He also worked in a consulting practice as water resources 

engineer specializing in planning and H&H analyses for design of dams. He is presently serving 

on the steering committee for FEMA’s update national guidelines on Selecting and 

Accommodating Inflow Design Flood (IDF) for Dams for hydrologic safety of dams. He also 

serves on ICODS’ Frequency of Extreme Hydrologic Events Guidance Development Task 

Group. He was Chair of the federal interagency Subcommittee on Hydrology (SOH) for 2005-

2007. He is the recipient of the Leadership Recognition and Certificate of Appreciation for 

chairing of the SOH from USGS and ACWI, respectively. 

Tucker B. Mahoney: Tucker Mahoney is a coastal engineer for FEMA, Region IV. Ms. 

Mahoney is the FEMA project manager for coastal Flood Insurance Studies in the southeastern 

United States. She also participates on coastal policy and coastal outreach forums within 

FEMA. Prior to joining FEMA, Ms. Mahoney was a coastal engineer for Moffatt & Nichol, where 

she completed a variety of hydrodynamic and sediment transport modeling studies and related 

construction projects. 

David Margo: David Margo earned a bachelor of science degree in engineering in 1993 and a 

master of science degree in civil engineering in 1995, both from the University of Pittsburgh. He 

has worked for the U.S Army Corps of Engineers for 17 years on various civil works projects. 

His areas of expertise and professional experience include risk analysis for dams and levees, 

flood frequency analysis, surface water hydrology, river hydraulics, and levee certification. 

David has been involved in probabilistic risk studies for a number of dams and levees in the 

USACE portfolio, including the Dallas Floodway and Bluestone Dam. He is also involved in 

methodology and policy development for the USACE dam and levee safety programs and is one 

of the lead developers for the USACE risk informed levee screening tool. 
129 

Martin McCann, Jr.: Dr. McCann received his B.S. in civil engineering from Villanova University 

in 1975, an M.S. in civil engineering in 1976 from Stanford University and his Ph.D. in 1980, 

also from Stanford University. 

His areas of expertise and professional experience includes probabilistic risk analysis for civil 

infrastructure facilities and, probabilistic hazards analysis, including seismic and hydrologic 

events, reliability assessment, risk-based decision analysis, systems analysis, and seismic 

engineering. He currently teaches a class on critical infrastructure risk management in the Civil 

and Environmental Engineering Department at Stanford. 

He has been involved in probabilistic risk studies for critical infrastructure (dams, levees, nuclear 

power plants, ports, chemical facilities) since the early 1980’s. He has performed probabilistic 

flood hazard assessments for a number of Department of Energy sites and commercial nuclear 

power plants. Recently, Dr. McCann led the Delta Risk Management Strategy project that 

conducted a risk analysis for over 1,100 miles of levee in the Sacramento and San Joaquin 

Delta. He was also a member of the U.S. Army Corps of Engineers’ IPET Risk and Reliability 

team evaluating the risk associated with the New Orleans levee protection system following 

Hurricane Katrina. 

Dr. McCann developed the SHIP risk analysis software that is used to perform risk and 

uncertainty calculations for facilities exposed to external hazards. 

He is currently serving on the ANS 2.8 committee that is updating the requirements for the 

assessment of external flood hazards at nuclear facilities. 

Kit Y. Ng: Kit Ng is a senior principal hydraulic and hydrology specialist and also serves as the 

assistant chief of Bechtel Power Corporation’s Geotechnical & Hydraulic Engineering Services 

Group. She has 22 years of industry experience and is the technical lead in Bechtel Power on 

hydrologic and hydraulic design and modeling, specifically on flooding hazard evaluation for 

nuclear power facilities, design of cooling water systems, intake and outfall hydraulic design, 

water resource management, storm water management, site drainage, erosion & sediment 

controls, coastal hydrodynamics and contaminant mixing and transport modeling in both surface 

water and groundwater. Kit has a Ph.D in environmental hydraulics from the California Institute 

of Technology. She has served as the chair for the Computational Hydraulic Committee of 

ASCE/EWRI and is currently a member of the ANSI/ANS 2.8 and 2.31 standard committees on 

design basis flood determination for nuclear facilities and estimating extreme precipitation at 

nuclear facility sites. She is also participating in the new ANS 2.18 standard committee on 

evaluating radionuclide transport in surface water for nuclear power sites. 

Thomas Nicholson: Thomas Nicholson is a Senior Technical Advisor in the Division of Risk 

Analysis of the Office of Nuclear Regulatory Research within the U.S. Nuclear Regulatory 

Commission (U.S. NRC). He has served in the research office for 32 years, and has worked at 

the U.S. NRC for 35 years receiving numerous awards including the U.S. NRC Meritorious 

Service Award for Scientific Excellence. His earlier positions were as a senior hydrogeologist 

and hydrologist in the Offices of Nuclear Regulatory Research, Standards Development and 

Nuclear Reactor Regulation. 

His principal responsibility is providing expert technical advice to NRC management and staff 

concerning radionuclide transport in the subsurface at NRC-licensed facilities. He has 

formulated and directed numerous research studies, as a senior project manager, involving 
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estimation of extreme flood probabilities in watersheds; radionuclide transport in fractured rock; 

and integration of subsurface monitoring and modeling. He presently serves as chair of the 

Extreme Storm Event Work Group under the Federal Subcommittee on Hydrology of the 

Advisory Committee on Water Information. He is the NRC liaison to the Water Science and 

Technology Board of the National Academies of Sciences. 

He holds a B.S. in geological sciences from Pennsylvania State University, and a M.S. in 

geology from Stanford University. At Stanford, he was a student of Professors Ray Linsley and 

Joseph Franzini in the hydrology program completing the core courses in hydrology. He is an 

active member of the American Geophysical Union, American Institute of Hydrology, Geological 

Society of America, International Association of Hydrological Sciences, the International 

Hydrogeologic Society, the National Ground-Water Association and registered Professional 

Geologist. 

Nicole Novembre: Nicole Novembre, P.E., is a hydrologic engineer with the Bureau of 

Reclamation Technical Service Center Flood Hydrology and Consequences Group in Denver, 

Colorado. She has been with Reclamation for 3 years. Previously she spent 2 years in private 

consulting after earning her Hydrology, Water Resources, and Environmental Fluid Mechanics 

M.S. degree from the University of Colorado at Boulder in 2007. Her principal responsibility is to 

develop hydrologic hazard loadings for use in Bureau of Reclamation Dam Safety risk 

assessments. 

Jim O’Connor: Jim O’Connor is a Research Hydrologist at the U.S. Geological Survey Oregon 

Water Science Center in Portland, Oregon, USA. He is a U.S. Pacific Northwest native long 

interested in the processes and events that shape the remarkable and diverse landscapes of 

the region. Following this interest with a Geological Science major at University of Washington 

and M.S. and Ph.D. degrees at University of Arizona (1990), he has spent the last 23 years 

focused on floods, fluvial geomorphology and Quaternary geology, primarily in the western 

United States. 

Chandra Pathak: Dr. Chandra S. Pathak, Ph.D., P.E., D.WRE, F.ASCE, has a distinguished 

career with over 33 years of experience in wide ranging areas of water resources engineering 

that included surface and ground water hydrology and hydraulics, stormwater management, 

wetland, water quality, drought management, GIS, and hydrology, hydraulic and water quality 

computer models. Currently, he is a principal engineer at the US Army Corps of Engineers, 

headquarters at Washington, DC. Before that he was a principle engineer at the South Florida 

Water Management District for twelve years. He is an adjunct professor at Florida Atlantic 

University and Florida International University. Previously, he was a practicing consulting 

engineer in the United States for over twenty years. He obtained a bachelor of technology in 

1976 and a master of engineering in water resources in 1978 and a doctorate in hydrologic 

engineering in 1983 from Oklahoma State University. Since 2006, he has been serving as an 

associate editor of Journal of Hydrologic Engineering. He has numerous presentations, 

speeches, and technical papers to his credit in the areas of water resources engineering. In 

2007, he was awarded Diplomate of Water Resources Engineering and Fellow Member of the 

American Society of Civil Engineers (ASCE). 

Rajiv Prasad: Dr. Prasad has over 20 years of experience as a Civil Engineer. His PhD 

dissertation at Utah State University focused on spatial variability, snowmelt processes, and 

scale issues. He has been employed at the Pacific Northwest National Lab for the last 13 

years. His research has included application of spatially distributed models for water 
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management, watershed process characterization, and impacts from global climate change. Dr. 

Prasad started working on the NRC permitting and licensing reviews since the wave of new 

power reactor applications started around 2003-04. Dr. Prasad has led PNNL’s effort in 

updating NRC’s Standard Review Plan in 2007, developing staff guidance related to tsunamis in 

2009, and revising the technical bases for design-basis flood estimation at nuclear power plant 

site in 2010-11. Currently, Dr. Prasad is leading the PNNL team tasked to provide technical 

bases for a comprehensive probabilistic flood hazard assessment at nuclear power plant sites. 

Charles R. Real: Charles Real is a Registered Geophysicist in California, and has worked in 

the field of earthquake hazards for over 35 years. He is currently a Supervising Engineering 

Geologist with the California Geological Survey, where he helped establish and currently 

manages California’s Seismic Hazard Zonation Program. During his career he has been 

principal investigator for numerous federal grants, and has recently been elected to the Board of 

Directors for the Northern Chapter of the Earthquake Engineering Research Institute. He 

currently Co-chairs a California Tsunami Policy Working Group, focusing on ways to reduce 

coastal communities’ tsunami risk. 

Wendy Reed: Dr. Reed is a radiochemist in the Environmental Transport Branch, Division of 

Risk Analysis of the Office of Nuclear Regulatory Research in the U.S. Nuclear Regulatory 

Commission (U.S. NRC). She has worked at the U.S. NRC for over 3 years. She holds a B.Sc. 

(Honors) and a Ph.D., both in chemistry, from the University of Manchester in the United 

Kingdom. 

Patrick J. Regan: Pat Regan is the Principal Engineer, Risk-Informed Decision-Making in the 

Division of Safety of Dams and Inspections, Office of Energy Projects, Federal Energy 

Regulatory Commission (FERC-D2SI). He has worked in the hydroelectric generation field for 

36 years for a dam owner, as a consultant and since 2000 for FERC-D2SI. He has authored or 

co-authored several papers on use of risk assessment in dam safety and has received both the 

United States Society on Dams Best Paper award and the Association of State Dam Safety 

Officials’ West Region Award of Merit. His principal responsibility is leading the development of 

the FERC’s Risk-Informed Decision-Making program. 

Donald T. Resio: Dr. Resio is the Director of the Taylor Engineering Research Institute and 

Professor of Ocean Engineering within the College of Computing, Engineering and Construction 

at the University of North Florida. He conducted meteorological and oceanographic research for 

over 40 years, leading many efforts that have contributed significantly to improving the 

predictive state of the art for winds, waves, currents, surges, and coastal evolution due to 

storms, along with improved methods for the quantification of risk which incorporate alleatory 

and epistemic uncertainty into a consistent physical framework for coastal hazards. He serves 

as a US delegate to the United Nations’ Joint WMO-IOC Technical Commission for 

Oceanography and Marine Meteorology (JCOMM) in the area of climate effects and the ocean 

and is the co-chair of the UN Coastal Inundation and Flooding Demonstration Project. Before 

coming to UNF, Dr Resio served as Senior Scientist for the ERDC Coastal and Hydraulic Lab. 

Victoria Sankovich: Victoria Sankovich is a Meteorologist in the Flood Hydrology and 

Consequences Group in the Technical Service Center (TSC) of the Bureau of Reclamation in 

Denver, Colorado. She has served in the TSC for over 3 years, conducting extreme precipitation 

and storm research and project work. Ms. Sankovich previously studied cloud/precipitation 

regimes as predicted by numerical weather models using statistical methods. Further, she has 

operational experience as a meteorologist for the U.S. Antarctic Program. This unique 
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opportunity provided a challenging experience to work directly with weather instrumentation, 

including LIDAR, sunshine recorders, snow stakes, and rawinsondes. Her principal 

responsibility is providing expert technical advice on hydrometeorological statistics, including Lmoments, and extreme storm analysis to TSC management and staff concerning hydrologic 

issues for Reclamation and other Department of Interior facilities. 

Mel Schaefer: Mel Schaefer is a Surface Water Hydrologist with a Ph.D. in Civil Engineering 

from the University of Missouri-Rolla. He has over 35-years of experience in hydrologic 

applications primarily in analysis of extreme storms and floods and was head of the Washington 

State Dam Safety program for 8-years. He has developed methodologies for conducting 

regional precipitation-frequency analyses and for stochastic simulation of the spatial and 

temporal characteristics of storms for use in rainfall-runoff modeling of extreme storms and 

floods for watersheds throughout the western US and British Columbia. He is co-developer of 

SEFM, a stochastic flood model for conducting flood simulations for extreme floods. He has 

conducted studies for extreme floods and provided technical assistance to the USBR, USCOE, 

BChydro and hydropower utilities on more than 20 dams in developing probabilistic loadings for 

extreme floods for use in risk analyses for high-consequence dams. 

Ray Schneider: Mr. Schneider is a Fellow engineer for the Westinghouse Electric Company. 

He has more than forty years of experience in the area of Light Water Reactor design and 

safety analysis, with emphasis on risk informed PSA applications, and severe accident analysis. 

Over the past several years, Mr. Schneider has represented the PWROG as a member of 

several NEI task forces, including the NEI Risk based Task Force (RBTF), Risk Informed 

technical Specifications Task Force (RITSTF), Fire Maintenance Rule task Force (MRTF-Fire) 

and the NEI FLEX task force supporting the development of the Programmatic Controls section. 

Mr. Schneider is currently the technical lead for the PWROG supporting the NEI Fukushima 

Flooding Task Force. ,Mr. Schneider also serves on several Standards development 

committees including the ANS/ASME Joint Committee on Nuclear Risk Management (JCNRM), 

ANS/ASME Level 2 PRA Standards working group, and the ANS 2.8 flood hazard development 

working group. He regularly supports PWR Owner’s Groups activities and individual member 

utilities in Level 1 PSA methods and applications development and Severe Accident 

Management related activities, and has been the lead individual responsible for over 60 

owner’s group and individual utility tasks involving PSA methods development, PSA quality 

improvement, maintenance rule implementation, and risk informed applications. 

Mr. Schneider has authored or co-authored over 30 technical publications, and is the recipient 

of a number of awards including: ASME Engineer of the Year Award, Hartford Chapter, and 

several division level George Westinghouse Signature Awards. 

Timo Schweckendiek: Timo Schweckendiek is a researcher and consultant at Deltares since 

2006. His background is hydraulic and geotechnical engineering; he obtained his MSc in Civil 

Engineering from Delft University of Technology, to which he is affiliated now through his PhD 

research on risk-based site investigation for levees. His core fields of expertise are flood risk 

analysis and management and reliability analysis of flood defenses. 

He is member of the Dutch Expertise Network of Flood Protection, an independent advisory 

body to the Dutch government on flood defenses and risk issues. Furthermore, he is a 

Netherlands delegate to the Technical Committee TC304 on "Risk Management in Engineering 

Practice" of the International Society of Soil Mechanics and Geotechnical Engineering 

(ISSMGE). Recently, in November 2012 Timo was co-organizer of the FLOODrisk 2012 

conference held in Rotterdam. 
133 

Jery Stedinger: Dr. Stedinger is Professor of Environmental and Water Resources Systems 

Engineering, School of Civil and Environmental Engineering, Cornell University. Dr. Stedinger 

received a B.A. from the Univ. of California at Berkeley in 1972, and a Ph.D. in Environmental 

Systems Engineering from Harvard in 1977. Since that time he has been a professor in 

Cornell's School of Civil and Environmental Engineering. Dr. Stedinger’s research has focused 

on statistical and risk issues in hydrology and the operation of water resource systems. Projects 

have addressed flood frequency analysis including the use of historical and paleoflood data, 

dam safety, regional hydrologic regression analyses, risk and uncertainty analysis of flood-risk 

reduction projects, climate change modeling, water resource system simulation, and efficient 

hydropower system operation and system design. 

John Stevenson: Dr. Stevenson is a professional engineer, with many years of engineering 

experience including the development of structural and mechanical construction criteria, codes 

and standards used in construction of nuclear power plant and other hazardous civil and 

mechanical structures, distribution systems and components subjected to postulated extreme 

environmental and accident loads as a design basis. 

He is, or has been since 1970, an active member or chairman of American Nuclear Society, 

American Society of Civil Engineers, American Society of Mechanical Engineers, American 

Concrete Institute, American Institute of Steel Construction and the International Atomic Energy 

Agency where since 1975 he has actively participated in the development of a large number of 

International Safety Guides, Tech Docs., and Safety Reports concerning siting, civil and 

mechanical design of nuclear facilities. He currently serves as Chairman of the Technical 

Advisory Committee to the IAEA International Seismic Safety Center. He is a member of the 

ASME Boiler and Pressure Vessel Code Committee, Section III, Nuclear Components, various 

Section III Working Groups, Subgroups and Subcommittees including former Chairman of 

ASME B&PVC Section III, Division 3 Transportation and Storage Containments for Nuclear 

Material and Waste. He is a former member of the ASME Board of Nuclear Codes and 

Standards and is a fellow of the American Society of Mechanical Engineers. He is also a 

member of the ANS Nuclear Facilities Standards Committee and is, or has been, a member or 

Chairman of ANS 2.3, 2.8, 2.10, 2.14, 2.26, 2.31 and 58.16 Standards Working Groups who 

have or are in the process of developing standards in seismic, wind and flood design and safety 

categorization of structures, systems and components located in nuclear facilities. 

His previous work assignments have included Manger of Structural Design and Balance of Plant 

Engineering Standardization for a major nuclear steam system supplier, Manager of Corporate 

Quality Assurance for a major architectural/engineering firm, Founder and President of a 

consulting engineering firm with 5 offices; 2 in the U.S. and 3 in Eastern Europe dedicated to 

safe design of new and existing nuclear facilities. He is currently a Consulting Engineer 

providing outside expert consulting services to various organizations involved in the construction 

of nuclear safety related facilities. 

Dr. Stevenson received his B.S. in Civil Engineering from the Virginia Military Institute in 1954, 

M.S. in Civil Engineering from the Case Institute of Technology in 1962 and Ph.D. in Civil 

Engineering from Case Western Reserve University in 1968. 

Hong Kie Thio: Hong Kie Thio is Principal Seismologist at the Los Angeles office of URS 

Corporation. He joined the company in 1995 after receiving his PhD in Geophysics at Caltech 

and has worked on numerous projects including earthquake source studies, real-time 
134 

earthquake analysis, nuclear monitoring, seismic hazard analysis and tsunami hazard analysis. 

He is currently serving on the ASCE 7 sub-committee on tsunami loads. 

Wilbert O. Thomas, Jr.: Mr. Thomas is a Senior Technical Consultant with Michael Baker Jr., 

Inc. in Manassas, Virginia. He reviews and performs hydrologic analyses for flood insurance 

studies and participates in special projects sponsored by FEMA and other clients such as the 

Maryland State Highway Administration. Mr. Thomas worked for the U.S. Geological Survey 

for 30 years and has worked for Michael Baker, Jr., Inc., since April 1995. Mr. Thomas is a 

registered professional hydrologist with over 47 years of specialized experience in conducting 

water resources projects and analyzing water resources data. Mr. Thomas is the author of 

more than 75 papers and abstracts on a variety of surface water hydrologic topics. As an U.S. 

Geological Survey employee, Mr. Thomas participated in the development of Bulletin 17B, 

Guidelines For Determining Flood Flow Frequency, published in 1982 and still used by all 

Federal agencies for flood frequency analysis for gaged streams. Mr. Thomas is the current 

chair of the Hydrologic Frequency Analysis Work Group (http://acwi.gov/hydrology/Frequency/) 

that is evaluating revisions to Bulletin 17B. 

Tony Wahl: Tony Wahl is a Hydraulic Engineer with 23 years experience in the Bureau of 

Reclamation Hydraulics Laboratory at Denver, Colorado, working in the areas of flow 

measurement and canal control, turbine hydraulics, fish screening, dam breach modeling, and 

laboratory modeling and field testing of hydraulic structures. Since 1995 he has been engaged 

in research related to embankment dam breach modeling. Since about 2004 he has been the 

technical coordinator for an international collaboration through the CEATI Dam Safety Interest 

Group that is focused on developing better methods for modeling embankment dam erosion and 

breach processes. He has led studies to evaluate competing methods for quantifying the 

erodibility of cohesive soils, a key input to newer dam erosion and breach models. Mr. Wahl’s 

recent research also includes physical scale modeling and numerical modeling of breach 

processes associated with canal embankments. Mr. Wahl is a registered professional engineer 

and earned a B.S. and M.S. in Civil Engineering from Colorado State University. In 2005, he 

was selected as the Bureau of Reclamation’s Federal Engineer of the Year. Mr. Wahl is the 

author of more than 90 technical papers and is presently serving on ASCE task committees 

studying flow measurement at canal gates and the uncertainties and errors associated with 

hydraulic measurements and experimentation. 

Ty V. Wamsley: Dr. Ty Wamsley is Chief of the Storm and Flood Protection Division in the 

Coastal and Hydraulics Laboratory at the U.S. Army Engineer Research and Development 

Center in Vicksburg, MS. He leads a team of engineers and scientists in the execution of 

research and development and engineering support services in the areas of storm and flood risk 

reduction project design and maintenance; sediment management; groundwater and watershed 

engineering and management; operation and maintenance of navigation projects; and regionalscale databases and information systems. He has received a Department of the Army Superior 

Civilian Service Award for his leadership and technical contribution to the Corps’ flood and 

storm damage reduction mission. 

Yong Wei: Dr. Yong Wei is a senior research scientist in tsunami modeling, coastal hazard 

mitigation, and geophysical data analysis. He has more than 10 years of research experience 

on tsunami modeling, methodology, and associated geophysics. He has developed extensive 

skills and proficiencies in various computer models dealing with the hydrodynamics of long 

waves. He also specializes in analysis of the tsunami source mechanism from seismic data and 

ocean observations. He joined Pacific Marine Environmental Laboratory and University of 
135 

Washington in 2006. He is currently the leading scientist in NOAA’s tsunami modeling team in a 

multi-year effort to develop high-resolution tsunami inundation models for U.S. coasts. 

Daniel Wright: Daniel Wright is a 4th year Ph.D. candidate in Environmental Engineering and 

Water Resources at Princeton University, focusing on flood risk estimation in urban 

environments. At Princeton, he is also a participant in the Science, Technology, and 

Environmental Policy certificate program, looking at climate and land use impacts on flood 

hazards. He has Bachelor’s and Master’s degrees in Civil and Environmental Engineering from 

the University of Michigan where he focused on water resources engineering. From 2006-2008 

Daniel served as a Regional Sanitation Engineer in the Peace Corps in Monteagudo, and later 

as a hydraulic engineer Daniel at an engineering firm in Concepción, Chile developing lowimpact hydroelectric power projects. He is interested in the intersection of engineering, policy, 

and development in water resources and climate adaptation.