Design-Basis Flood 

Estimation for Site 

Characterization at Nuclear 

Power Plants in the United 

States of America 

Office of Nuclear Regulatory Research 

NUREG/CR-7046 

PNNL-20091 
DISCLAIMER: This report was prepared as an account of work sponsored by an agency of the U.S. Government. 

Neither the U.S. Government nor any agency thereof, nor any employee, makes any warranty, expressed or

implied, or assumes any legal liability or responsibility for any third party’s use, or the results of such use, of any

information, apparatus, product, or process disclosed in this publication, or represents that its use by such third

party would not infringe privately owned rights.

AVAILABILITY OF REFERENCE MATERIALS

IN NRC PUBLICATIONS

NRC Reference Material

As of November 1999, you may electronically access

NUREG-series publications and other NRC records at

NRC’s Public Electronic Reading Room at 

http://www.nrc.gov/reading-rm.html. Publicly released

records include, to name a few, NUREG-series

publications; Federal Register notices; applicant,

licensee, and vendor documents and correspondence;

NRC correspondence and internal memoranda;

bulletins and information notices; inspection and

investigative reports; licensee event reports; and

Commission papers and their attachments.

NRC publications in the NUREG series, NRC

regulations, and Title 10, Energy, in the Code of

Federal Regulations may also be purchased from one

of these two sources.

1. The Superintendent of Documents

 U.S. Government Printing Office

 Mail Stop SSOP

 Washington, DC 20402–0001

 Internet: bookstore.gpo.gov

 Telephone: 202-512-1800

 Fax: 202-512-2250

2. The National Technical Information Service

 Springfield, VA 22161–0002

 www.ntis.gov 

 1–800–553–6847 or, locally, 703–605–6000

A single copy of each NRC draft report for comment is

available free, to the extent of supply, upon written

request as follows:

Address: U.S. Nuclear Regulatory Commission

 Office of Administration 

 Publications Branch

 Washington, DC 20555-0001

E-mail: DISTRIBUTION.RESOURCE@NRC.GOV 

Facsimile: 301–415–2289 

Some publications in the NUREG series that are 

posted at NRC’s Web site address

http://www.nrc.gov/reading-rm/doc-collections/nuregs 

are updated periodically and may differ from the last

printed version. Although references to material found

on a Web site bear the date the material was accessed,

the material available on the date cited may

subsequently be removed from the site.

Non-NRC Reference Material

Documents available from public and special technical

libraries include all open literature items, such as

books, journal articles, and transactions, Federal

Register notices, Federal and State legislation, and

congressional reports. Such documents as theses,

dissertations, foreign reports and translations, and

non-NRC conference proceedings may be purchased

from their sponsoring organization.

Copies of industry codes and standards used in a

substantive manner in the NRC regulatory process are

maintained at—

The NRC Technical Library 

Two White Flint North

11545 Rockville Pike

Rockville, MD 20852–2738

These standards are available in the library for 

reference use by the public. Codes and standards are

usually copyrighted and may be purchased from the

originating organization or, if they are American

National Standards, from—

American National Standards Institute

11 West 42nd Street

New York, NY 10036–8002

www.ansi.org 

212–642–4900

Legally binding regulatory requirements are stated

only in laws; NRC regulations; licenses, including

technical specifications; or orders, not in 

NUREG-series publications. The views expressed

in contractor-prepared publications in this series are

not necessarily those of the NRC.

The NUREG series comprises (1) technical and

administrative reports and books prepared by the

staff (NUREG–XXXX) or agency contractors

(NUREG/CR–XXXX), (2) proceedings of

conferences (NUREG/CP–XXXX), (3) reports

resulting from international agreements

(NUREG/IA–XXXX), (4) brochures

(NUREG/BR–XXXX), and (5) compilations of legal

decisions and orders of the Commission and Atomic

and Safety Licensing Boards and of Directors’

decisions under Section 2.206 of NRC’s regulations

(NUREG–0750).
Design-Basis Flood 

Estimation for Site 

Characterization at Nuclear 

Power Plants in the United 

States of America 

Manuscript Completed: December 2010 

Date Published: November 2011 

Prepared by 

Rajiv Prasad 

Lyle F. Hibler 

Andre M. Coleman 

Duane L. Ward 

Pacific Northwest National Laboratory 

P.O. Box 999 

Richland, WA 99352 

John D. Randall, NRC Project Manager 

Thomas J. Nicholson, NRC Technical Monitor 

NRC Job Code N6575 

Office of Nuclear Regulatory Research 

NUREG/CR-7046 

PNNL-20091 

iii 

ABSTRACT 

The purpose of this document is to describe approaches and methods for estimation of the designbasis flood at nuclear power plant sites. Chapter 1 defines the design-basis flood and lists the U.S. 

Nuclear Regulatory Commission’s (NRC) regulations that require estimation of the design-basis 

flood. For comparison, the design-basis flood estimation methods used by other Federal agencies 

are also described. A brief discussion of the recommendations of the International Atomic Energy 

Agency for estimation of the design-basis floods in its member States is also included. 

Chapter 2 introduces the concept of hierarchical hazard assessment (HHA) and its application to 

estimation of the design-basis flood at nuclear power plant sites. The HHA consists of a series of 

progressively refined methods that increasingly use site-specific data to demonstrate whether the 

plant structures, systems, and components important to safety are adequately protected from the 

adverse effects of severe floods. The HHA method is illustrated by an example. 

Chapter 3 introduces the concept of alternative conceptual models that are used to characterize the 

severe flooding scenarios at and near the site. The individual flood-causing hydrologic and 

hydrodynamic mechanisms are also described along with the potentially adverse effects they may 

cause at the site. A description of the HHA method as applied to several of these flooding 

mechanisms is provided. A brief discussion of combined events is also included. 

Chapter 4 briefly describes two analytical approaches, the deterministic and the probabilistic, used in 

standard engineering practice for estimation of design-basis floods. The current NRC approach for 

estimation of design-basis floods uses the deterministic approach. 

Chapter 5 describes the NRC’s quality assurance criteria for simulation models and provides a 

description of criteria used in selection of simulation models. A discussion of uncertainty in input 

data and model parameters is provided. A brief discussion of validation of model-derived estimates 

is also included. This chapter also provides a discussion of probabilistic approaches to estimation of 

flood hazard assessment and outlines the components of a formal Probabilistic Flood Hazard 

Assessment (PFHA) approach. 

Chapter 5 also includes a brief summary of the findings of the fourth assessment report on climate 

change prepared by the Intergovernmental Panel on Climate Change. A brief note is made 

regarding incorporation of the effects of climate change in estimation of the design-basis floods at 

nuclear power plant sites. Some future directions for further refinement of design-basis flood 

estimation methods are also provided. 

Chapter 6 provides a few specific recommendations for further research. Two of these are worth 

noting. Incorporation of more recent site-specific datasets to demonstrate the validity of estimated 

design-basis flood and available margins would provide additional assurance regarding safety. 

Development of a comprehensive PFHA methodology that leverages existing techniques in areas of 

hydrologic and hydraulic simulation, accounting for uncertainty in model inputs and parameters, and 

probabilistic flood frequency analysis can provide an extremely useful tool for risk-informed designbasis flood estimation at nuclear power plant sites. 

The report also contains nine appendices. One of these appendices describes currently available 

hydrometeorological datasets and geographical information system techniques that are useful in 

data preprocessing and synthesis of model inputs. Seven of the other appendices describe the flood 

estimation techniques for various flood-causing mechanisms. The last appendix describes some 

limitations of the unit hydrograph approach frequently used in estimation of design-basis floods and 

recommends a method for adjusting unit hydrographs to make them more appropriate for estimation 

of extreme floods. 

v 

TABLE OF CONTENTS 

Section Page

ABSTRACT .................................................................................................................................. iii

LIST OF FIGURES ......................................................................................................................vii

LIST OF TABLES .........................................................................................................................vii

EXECUTIVE SUMMARY ..............................................................................................................ix

ACKNOWLEDGMENTS ............................................................................................................ xiii

ACRONYMS AND ABBREVIATIONS ......................................................................................... xv

1 DESIGN-BASIS FLOOD ................................................................................................ 1-1

1.1 Definition of a Design-Basis Flood ................................................................................. 1-1

1.2 Design-Basis Flood Estimation Methods Adopted by Other Federal Agencies ............. 1-2

1.2.1 U.S. Army Corps of Engineers ....................................................................................... 1-3

1.2.2 Bureau of Reclamation ................................................................................................... 1-4

1.2.3 U.S. Department of Energy ............................................................................................ 1-4

1.3 Federal Energy Regulatory Commission ....................................................................... 1-5

1.4 Design-Basis Flood Estimation Guidelines of the International Atomic Energy Agency 1-6

2 THE HIERARCHICAL HAZARD ASSESSMENT APPROACH ...................................... 2-1

3 CAUSATIVE MECHANISMS FOR DESIGN-BASIS FLOODS ....................................... 3-1

3.1 Alternative Conceptual Models ...................................................................................... 3-1

3.2 Local Intense Precipitation ............................................................................................. 3-1

3.2.1 Flood Generated by Local Intense Precipitation and Its Effects..................................... 3-1

3.2.2 Hierarchical Hazard Assessment Applied to a Local Intense Precipitation-Generated 

Flood .............................................................................................................................. 3-2

3.3 Flooding in Rivers and Streams ..................................................................................... 3-3

3.3.1 Estimating the PMF and Its Effects ................................................................................ 3-3

3.3.2 Hierarchical Hazard Assessment Applied to PMF ......................................................... 3-4

3.4 Dam Breaches and Failures ........................................................................................... 3-5

3.4.1 Hierarchical Hazard Assessment Applied to Dam Breaches and Failures ..................... 3-5

3.5 Storm Surge ................................................................................................................... 3-6

3.5.1 Hierarchical Hazard Assessment Applied to PMSS ....................................................... 3-8

3.6 Seiche ............................................................................................................................ 3-9

3.7 Ice-Induced Flooding ...................................................................................................... 3-9

3.8 Flooding Resulting from Channel Migration or Diversion ............................................. 3-10

3.9 Combined-Effects Flood ............................................................................................... 3-10

4 APPROACHES .............................................................................................................. 4-1

4.1 Deterministic Analyses ................................................................................................... 4-1

4.2 Probabilistic Analyses .................................................................................................... 4-3

5 DESIGN-BASIS FLOOD HAZARD ESTIMATION METHODS ....................................... 5-1

5.1 Alternative Conceptual Models ...................................................................................... 5-1
vi 

5.2 Quality Assurance Criteria for Simulation Models .......................................................... 5-3

5.3 Selecting Simulation Models to Use ............................................................................... 5-3

5.4 Accounting for Uncertainty in Input and Model Parameters for Estimation of DesignBasis Flood Hazards ...................................................................................................... 5-5

5.5 Validation ....................................................................................................................... 5-6

5.6 Reconciling Deterministic and Probabilistic Notions in the Context of Design-Basis 

Flood Estimation ............................................................................................................ 5-6

5.7 Effects of Climate Variability on Design-Basis Flood Estimation.................................... 5-9

6 FUTURE DIRECTIONS ................................................................................................. 6-1

7 REFERENCES ............................................................................................................... 7-1

8 GLOSSARY ................................................................................................................... 8-1

APPENDIX A HYDROLOGICAL DATA SOURCES .................................................................. A-1

APPENDIX B FLOODING FROM LOCAL INTENSE PRECIPITATION: A CASE STUDY ....... B-1

APPENDIX C DATA PREPARATION AND WATERSHED MODELING SETUP ..................... C-1

APPENDIX D FLOODING FROM DAM BREACHES AND FAILURES: A CASE STUDY ....... D-1

APPENDIX E FLOODING FROM STORM SURGES: A CASE STUDY ................................... E-1

APPENDIX F FLOODING FROM A SEICHE: A CASE STUDY ............................................... F-1

APPENDIX G FLOODING FROM ICE-INDUCED EVENTS: A CASE STUDY ....................... G-1

APPENDIX H COMBINED-EFFECT FLOODS ......................................................................... H-1

APPENDIX I UNIT HYDROGRAPHS AND NONLINEAR HYDROLOGIC RESPONSE ............. I-1
vii 

LIST OF FIGURES 

Figure Page

2-1. Flowchart Demonstrating the HHA Applied to Flood Hazards from a PMF Event ......... 2-3 

5-1. A Hypothetical Nuclear Power Plant Site Location with Respect to a Creek, a 

River, Two Bays, and an Ocean (map elements are not to scale) ................................. 5-2

LIST OF TABLES 

Table Page

3-1. Types of Tropical Storms and the Saffir-Simpson Scale Describing the Categories of 

Hurricanes... .................................................................................................................. 3-7

.

ix 

EXECUTIVE SUMMARY 

The last revision of Regulatory Guide 1.59 was published by the U.S. Nuclear Regulatory 

Commission (NRC) in 1977. Since that time, flood estimation techniques have significantly 

advanced. The availability of more accurate datasets and advent of new analysis 

methodologies such as geographical information systems has facilitated rapid processing of 

large, spatially distributed datasets in the estimation of input for newer classes of hydrologic, 

hydraulic, and hydrodynamic models. This report attempts to collect relevant information that 

can be used in the estimation of design-basis floods at nuclear power plant sites. 

The experience gained by the staff at Pacific Northwest National Laboratory over the last few 

years while assisting the NRC staff in the review of Early Site Permits and Combined License 

Applications has resulted in the development of new and efficient techniques that are expected 

to provide substantial gains in the accuracy and reliability of the estimates of design-basis 

floods. 

The NRC regulations require a safety analysis to demonstrate that structures, systems, and 

components (SSCs) important to safety of a nuclear power plant are adequately protected from 

the adverse effects of flooding. This report describes a new approach, the hierarchical hazard 

assessment (HHA) approach, tailored to the estimation of design-basis flood hazard metrics at a 

given site. The HHA is a stepwise, progressively refined series of analyses that is aimed at 

demonstrating that the SSCs important to safety are adequately protected from the adverse 

effects of severe floods expected at the site. 

At the start of the estimation of design-basis flood hazards, it is very useful to list clearly all 

plausible flooding mechanisms that are capable of generating a severe flood at the site. It is 

also readily recognized that several scenarios of a particular flooding mechanism can affect the 

site; for example, precipitation-generated floods may occur in a river adjacent to the site as well 

as in a tributary that flows past the site. Multiple scenarios resulting from alternative conceptual 

models of flooding from other mechanisms should also be investigated. 

It may be possible to determine that some alternative conceptual models of flooding are 

demonstrably less conservative than others and therefore more detailed analyses of those 

scenarios may not be necessary. At the same time, enumeration of all plausible alternative 

conceptual models provides additional assurance that the complete range of possible scenarios 

at the site is adequately accounted for. 

This report briefly discusses the probabilistic approaches to estimation of design-basis floods. 

However, the deterministic approach currently in use is recommended for the near future 

because of two reasons: the lack of an overall framework that fully implements a Probabilistic 

Flood Hazard Assessment (PFHA) and to ensure consistency with current practices. 

Nevertheless, several advances can be recommended at this time. Availability of large, 

spatially distributed datasets and tools for rapid processing of these datasets provides an 

opportunity to refine the representation of modeling elements in the drainage basin and to 

parameterize more accurately the models currently used in practice. The availability of more 

than 30 years of additional data since the last revision of Regulatory Guide 1.59 also provides a 

longer and more robust validation dataset. Advances in computing speeds and availability of 

specialized software also reduce the time required for analysis, allowing the examination of 

multiple scenarios and thereby helping to reduce uncertainty in estimates of design-basis flood 

hazards. 
x 

The report contains nine appendices, seven of which present examples of flood estimation from 

various mechanisms. Only flood-simulation models currently accepted and widely used have 

been employed in the development of these examples. However, these examples should not 

be construed to be the only or even the most appropriate approach for estimation of designbasis flood hazard metrics at a particular site. Often, site-specific conditions greatly influence 

not only parameter choices but also the selection of the simulation models themselves. Some 

of these issues are discussed in Chapter 5 of this report. 

Recently, debate has focused on the projected climate change in the latter parts of the 

twenty-first century and what these projections mean to the estimation of design-basis flood 

hazards at sites where nuclear power plants may be expected to be in operation during the 

same period. Chapter 5 summarizes the findings of the Intergovernmental Panel on Climate 

Change fourth assessment report of 2007. Several hydroclimatic changes are projected for the 

United States. However, the complete effect of these projected changes on flood-causing 

mechanisms has not been investigated in detail at various spatial scales needed for site 

characterization at nuclear power plants. For example, surface temperature and precipitation 

are both projected to increase in eastern North America. The North Atlantic is also projected to 

be warmer. The effects of these changes on synoptic and monsoon patterns that govern 

precipitation have not been studied yet. It is possible that these changes would result in a 

different climate where current estimates of extreme precipitation may not hold true. In absence 

of any definitive studies, this report recommends that the projected changes be incorporated in 

the estimation of design-basis flood hazard as sensitivity studies. The results of these 

sensitivity studies should be used to determine and clearly report the margin available between 

the selected design basis and the (uncertain) site characteristic related to each flood hazard 

metric. 

Probabilistic flood assessment has the benefit of clearly articulating the exceedance frequency 

of a selected design basis. Therefore, it facilitates a risk-informed approach to decision-making. 

Several components of PFHA already exist and have matured over the past few decades. 

However, the near-future need is to develop an overall framework where these techniques can 

be integrated into a comprehensive PFHA tool. 
xi 

PAPERWORK REDUCTION ACT STATEMENT 

This NUREG does not contain information collection requirements and, therefore, is not subject 

to the requirements of the Paperwork Reduction Act of 1995 (44 USC 3501, et seq.). 

PUBLIC PROTECTION NOTIFICATION 

The NRC may not conduct or sponsor, and a person is not required to respond to, a request for 

information or an information collection requirement unless the requesting document displays a 

currently valid Office of Management and Budget control number. 

xiii 

ACKNOWLEDGMENTS 

The authors sincerely acknowledge technical discussions, guidance, and suggestions provided 

by Mr. Lance Vail, Dr. Mark Wigmosta, and Dr. Michael Fayer of PNNL. Technical comments 

provided by Mr. Goutam Bagchi, Dr. Hosung Ahn, Dr. Henry Jones, Dr. Nebiyu Tiruneh, Dr. 

Christopher Cook, Dr. Ann Kammerer, Dr. Fernando Ferrante, Mr. Thomas Nicholson, 

Ms. Melanie Galloway, Dr. John Randall, and Dr. Joseph Giacinto, all of NRC; Dr. John England 

of the U.S. Bureau of Reclamation, and Dr. Donald Resio of the U.S. Army Corps of Engineers 

helped improve this report. 

Financial support from the Office of Nuclear Regulatory Research of the NRC is gratefully 

acknowledged. Preparation of this report would have been impossible without the continued 

guidance and support of Dr. John Randall, the NRC Project Manager, and 

Mr. Thomas Nicholson, the NRC Technical Monitor. 

Project management support from Ms. Janie Vickerman and Ms. Julie Hughes that kept this 

project sustained during difficult periods, is also acknowledged. 

Excellent editorial support from Mr. Cary Counts, Ms. Susan Ennor, Ms. Jennifer Blake, and Ms. 

Meghan Spanner made this report possible. 

xv 

ACRONYMS AND ABBREVIATIONS 

oC degree(s) Celsius (or Centigrade) 

oF degree(s) Fahrenheit 

ac acre(s) 

ACRS Advisory Committee on Reactor Safeguards 

ADCIRC Advanced Circulation 

ANS American Nuclear Society 

ANSI American National Standards Institute 

CFR Code of Federal Regulations 

cfs cubic (foot)feet per second 

D-A-D depth-area-duration (curves) 

DEM Digital Elevation Model 

DHSVM Distributed Hydrology Soil-Vegetation Model 

DOE U.S. Department of Energy 

EHW envelop of high water 

EM Engineer Manual 

ER Engineer Regulation 

ESP Early Site Permit 

ESRI Environmental Systems Research Institute 

FEMA Federal Emergency Management Agency 

FERC Federal Energy Regulatory Commission 

FSAR Final Safety Analysis Report 

FTP file transfer protocol 

GDC General Design Criteria 

GIS Geographic Information System 

HEC-HMS Hydrologic Engineering Center Hydrologic Modeling System 

HEC-RAS Hydrologic Engineering Center River Analysis System 
xvi 

HHA hierarchical hazard assessment 

HMR Hydrometeorological Report 

hr hour(s) 

HUC Hydrologic Unit Code 

IAEA International Atomic Energy Agency 

IACWD Interagency Advisory Committee on Water Data 

in. inch 

IPCC Intergovernmental Panel on Climate Change 

LULC Land Use/Land Cover 

km kilometer(s) 

km2

 square kilometer(s) 

kPa kilopascal(s) 

kt knot(s) 

m meter(s) 

mi2

 square mile(s) 

mb millibar 

MEOW maximum envelope of water 

mi mile(s) 

min minute(s) 

mm millimeter(s) 

MOM maximum of the MEOWs 

MRLC Multi-Resolution Land Characteristics Consortium 

MSL mean sea level 

NCDC National Climatic Data Center 

NED National Elevation Dataset 

NHD National Hydrography Dataset 

NLCD National Land Cover Database 
xvii 

NOAA National Oceanic and Atmospheric Administration 

NRC U.S. Nuclear Regulatory Commission 

NRCS Natural Resources Conservation Service 

NWS National Weather Service 

OBE operating basis earthquake 

PC performance category 

PDF probability density function 

PFHA Probabilistic Flood Hazard Assessment 

PMF probable maximum flood 

PMH probable maximum hurricane 

PMP probable maximum precipitation 

PMS probable maximum seiche 

PMSS probable maximum storm surge 

PMT probable maximum tsunami 

PMWS probable maximum windstorm 

PRA Probabilistic Risk Assessment 

SCS Soil Conservation Service 

SLOSH Sea, Lake, and Overland Surges from Hurricanes 

SRTM Shuttle Radar Topographic Mission 

SSCs structures, systems, and components 

SSE safe shutdown earthquake 

UH unit hydrograph 

URL uniform resource locator 

USACE U.S. Army Corps of Engineers 

USGS United States Geological Survey 

WMO World Meteorological Organization 

WMS Watershed Modeling System 
xviii 
1-1 

1 DESIGN-BASIS FLOOD 

Nuclear power plants need to be protected from the adverse effects of flooding. To assist in 

determining the potential for adverse flooding effects, the U.S. Nuclear Regulatory Commission 

(NRC) provides guidance for estimating design-basis floods in Regulatory Guide 1.59 (NRC 

1977). 

1.1 Definition of a Design-Basis Flood 

A design-basis flood is a flood caused by one or an appropriate combination of several 

hydrometeorological, geoseimic, or structural-failure phenomena, which results in the most 

severe hazards to structures, systems, and components (SSCs) important to the safety of a 

nuclear power plant. 

Title 10 of the U.S. Code of Federal Regulations (CFR) 52.79(a)(1)(iii) states that a Final SafetyAnalysis Report, which is part of the Combined Operating License application process for 

nuclear power plants, must address: 

The seismic, meteorological, hydrologic, and geologic characteristics of the 

proposed site with appropriate consideration of the most severe of the natural 

phenomena that have been historically reported for the site and surrounding area 

and with sufficient margin for the limited accuracy, quantity, and time in which the 

historical data have been accumulated. 

10 CFR 52.17(a)(1)(vi) includes a similar statement for Early Site Permit applications. 

10 CFR 52.79(a)(4)(i) states that the minimum design requirements for the principal design 

criteria are established by 10 CFR Part 50, Appendix A, General Design Criteria for Nuclear 

Power Plants. 

General Design Criterion 2 (GDC 2), Design bases for protection against natural phenomena, in 

Appendix A to 10 CFR Part 50, Domestic Licensing of Production and Utilization Facilities, 

states: 

Structures, systems, and components important to safety shall be designed to 

withstand the effects of natural phenomena such as earthquakes, tornadoes, 

hurricanes, floods, tsunami, and seiches without loss of capability to perform 

their safety functions. The design bases for these structures, systems, and 

components shall reflect: (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. [Emphases in bold added by the authors.] 

The requirements imposed by GDC 2 for determining a design-basis flood are (1) consideration 

of the most severe historical event with sufficient margin, (2) consideration of combinations of 

ambient conditions with flood-inducing natural phenomena, and (3) consideration of the 

importance of safety functions affected by flooding. GDC 2 also requires that SSCs important to 

safety must be able to perform their safety functions without loss of capability during a designbasis flood. 
1-2 

GDC 44, Cooling water, requires an ultimate heat sink to transfer heat from SSCs important to 

safety. The ultimate heat sink must remain functional under normal and accident conditions, 

including the design-basis flood. 

10 CFR 100.20 requires nuclear power plant site evaluation to include meteorological, 

hydrological, seismic, and geologic characteristics that may affect the acceptability of a site for a 

stationary power reactor. 10 CFR 100.20 also requires evaluation of the nature and proximity of 

man-related hazards such as dams. 

In the past, NRC adopted the concept of a “probable maximum event,” for estimating design 

bases. The probable maximum event, which is determined by accounting for the physical limits 

of the natural phenomenon, is the event that is considered to be the most severe reasonably 

possible at the location of interest and is thought to exceed the severity of all historically 

observed events. For example, a probable maximum flood (PMF) is the hypothetical flood 

generated in the drainage area by a probable maximum precipitation (PMP) event. The 

probable maximum storm surge (PMSS) is generated by the probable maximum hurricane 

(PMH) or the probable maximum windstorm (PMWS). These events are defined by the 

American National Standards Institute (ANSI) and American Nuclear Society (ANS) in 

ANSI/ANS-2.8-1992 (ANS 1992). Similar concepts exist for a probable maximum tsunami 

(PMT), which is not covered in this report. González et al. (2007) and Prasad (2009) discussed 

PMT hazards at nuclear power plant sites in the United States. The PMP is assumed to be a 

theoretical maximum and its estimation uses no associated probability distribution. In standard 

practice, estimating the PMF from the PMP involves some subjectivity and also uses no 

probabilistic basis. 

More recently, probabilistic methods have also gained acceptance for determining design-basis 

events. The advantage of probabilistic methods is that an estimate of the probability-ofexceedance of the selected design basis can be made. This capability enables clear 

articulation of the level of risk that an SSC important to safety encounters during its operation. 

The emphasis, therefore, is not on determining the worst-case scenario as a basis for design, 

but to state the level of risk a chosen design would face. 

1.2 Design-Basis Flood Estimation Methods Adopted by Other 

Federal Agencies 

This section briefly describes the methods adopted by Federal agencies other than NRC for 

determining a design-basis flood. The U.S. Army Corps of Engineers (USACE), the Bureau of 

Reclamation (Reclamation), and the Federal Energy Regulatory Commission (FERC) estimate 

design-basis floods when designing and conducting safety assessments of flood-control 

structures, dams, water-supply infrastructure, and levees. The U.S. Department of Energy 

(DOE) estimates design-basis floods to help ensure the safety of SSCs at its facilities, and the 

Federal Emergency Management Agency (FEMA) determines design-basis floods so it can plan 

for emergency actions following a severe flooding event. 

The methods recommended by USACE, Reclamation, DOE, and FERC for estimating designbasis floods are described in the following sections. 
1-3 

1.2.1 U.S. Army Corps of Engineers 

USACE publishes a series of Engineer Regulations (ERs) and Engineer Manuals (EMs) 

(USACE 2009). The most relevant of these publications for estimating design-basis floods are 

as follows: 

• EM 1110-2-1420 (Hydrologic Engineering Requirements for Reservoirs) 

• EM 1110-2-1417 (Flood-Runoff Analysis) 

• EM 1110-2-1406 (Runoff from Snowmelt) 

• EM 1110-2-1411 (Standard Project Flood Determinations) 

• EM 1110-2-1416 (River Hydraulics) 

• EM 1110-2-1100 (Coastal Engineering Manual) 

• EM 1110-2-1612 (Ice Engineering) 

• ER 1110-8-2(FR) (Inflow Design Flood for Dams and Reservoirs) 

• EM 1110-2-1603 (Hydraulic Design of Spillways) 

• EM 1110-2-1605 (Hydraulic Design of Navigation Dams) 

• EM 1110-2-3600 (Management of Water Control Systems) 

• EC 1165-2-210 (Water Resources Policies and Authorities – Water Supply Storage and 

Risk Reduction Measures for Dam Safety). 

USACE regulations currently state that dams for which failures may result in potential loss of 

human life must be designed safely to pass a flood inflow into the reservoir estimated from the 

PMP (USACE 1991). However, USACE is now using Probabilistic Risk Assessment (PRA) and 

risk analysis to assess the design adequacy and potential failure of dams and levees (USACE 

2010). Hydrologic hazard estimates, which include flood probabilities up to the maximum event, 

are used as inputs to risk analysis. Extreme flood probability methods currently used by 

USACE are described by USACE (2008a) and summarized by Brunner and Gee (2009). 

USACE typically uses generalized rainfall criteria from National Weather Service (NWS) 

Hydrometeorological Reports (HMRs) (e.g., Schreiner and Riedel 1978). However, in drainage 

basins where unusual conditions exist or where generalized criteria may not provide refined 

estimates of rainfall, special hydrometeorological studies may be performed. 

USACE (1991, 1997) transforms rainfall to runoff using unit hydrographs and loss rates that are 

favorable for rapid watershed response. The peak discharges of unit hydrographs derived from 

observed flood events that are smaller than the PMF should be increased 20 to 50 percent. The 

water-surface elevation in a reservoir prior to the arrival of a PMF is assumed to be at the full 

pool level. USACE also considers an antecedent precipitation event prior to the arrival of the 

PMP event. USACE (1994) describes the process of using unit hydrographs including several 

synthetic hydrographs, but cautions that unit hydrographs intended for estimating large flood 

events such as the PMF should be derived from large historical flood events. It suggests that in 

certain cases, it is appropriate to modify the unit hydrograph to account for the shorter travel 

time expected for larger floods. 

A portion of precipitation falling on the drainage basin does not contribute to direct runoff 

because of interception that is eventually evaporated from canopies, depression storage that 

eventually infiltrates, and evapotranspiration. The rate of precipitation loss during a PMF event 
1-4 

should be the most severe that is reasonable for the storm magnitude (USACE 1994). Loss 

rates observed or estimated from large historical flood events may be used if the 

hydrometeorological condition prevailing during these storms can be shown to represent severe 

conditions. USACE (1994) recommends that no losses be considered when the ground may be 

frozen at the start of the flood event. A similar argument may also be made for saturated soil 

conditions. 

1.2.2 Bureau of Reclamation 

Reclamation oversees, manages, and maintains over 350 large dams, reservoirs, and 

appurtenant facilities in the western United States as part of its responsibility to develop and 

conserve the nation’s water resources. The Reclamation Dam Safety Program is responsible 

for overseeing the safety assessments and potential modifications of existing dams, and for new 

dams. Reclamation uses risk analysis to prioritize financial resources on new and existing 

dams within Reclamation's inventory (Reclamation 2003). Reclamation's Public Protection 

Guidelines provide two risk criteria for assessing the safety of dams: potential loss of life and 

annual failure probability (Reclamation 2003). Reclamation's Best Practices in Dam Safety Risk 

Analysis (Reclamation 2010) describes in detail the technical methods for dam safety 

assessments that are used by Reclamation staff to assess the loads, structural response, 

consequences, and risk. 

To assess a particular existing or new structure, Reclamation estimates the full probability 

distribution of hazards such as floods or earthquakes. Reclamation uses a suite of methods to 

estimate hydrologic hazard curves, which portray peak flows and volumes for a range of annual 

exceedance probabilities (Swain et al. 2006). Reclamation's policy is to use the PMF, as 

determined by the PMP, as the physical upper limit for hydrologic hazard curves (Reclamation 

2002). 

Reclamation has published a set of three design manuals for design, analysis, and investigation 

for constructing dams: Design of Small Dams, Third Edition (Reclamation 1987), Design of 

Gravity Dams (Reclamation 1976), and Design of Arch Dams (Reclamation 1977). 

Reclamation's design floods are selected based on the estimated risk at the site of interest. 

These risk estimates include all site and watershed characteristics, specific structural 

characteristics of the site or facility, and downstream consequences. In some cases, the PMF is 

selected as the design basis flood. PMF methods used by Reclamation are described in 

Cudworth (1989) and supersede methods described by Reclamation (1987). The loss rates 

used during the PMF event should be the lowest rates that are consistent with soil types of the 

watershed. The unit hydrograph approach is typically used to estimate PMF events, and is 

selected from site-specific or regional extreme floods (Cudworth 1989). 

1.2.3 U.S. Department of Energy 

DOE designs, constructs, and operates its facilities so that workers, the general public, and the 

environment are protected from hazards caused by natural phenomena (DOE 2002). DOE’s 

flood design and evaluation criteria are established to ensure that safety-related SSCs meet a 

set of performance goals. Four performance categories, PC 1 through PC 4, are used. The 

mean hazard annual probabilities-of-exceedance for PC 1, PC 2, PC 3, and PC 4 are 2x10-3, 

5x10-4, 1x10-4, and 1x10-5, respectively. For the categories PC 2 through PC 4, site-specific 

flood hazard analyses are required. The hazard analyses are carried out in a probabilistic 

framework. The design-basis flood is determined from the mean flood hazard curve and the 

target hazard probability-of-exceedance (DOE 1995). 
1-5 

DOE identifies the sources of flooding (e.g., river flooding and local intense precipitation) and 

the flood hazards (e.g., hydrostatic and hydrodynamic forces) that may affect a site or an 

individual SSC. Flooding sources that should be investigated for estimating the design basis 

include river flooding, dam failure, levee or dike failure, local intense precipitation, storm surge, 

seiche, snow, and tsunami. Combinations of flooding events also are analyzed (e.g., river 

flooding combined with wind waves). For each SSC, the design-basis flood is defined in terms 

of a peak hazard level (such as the depth or discharge for river flooding combined with wind 

waves) and the corresponding loads (such as hydrostatic and hydrodynamic forces for river 

flooding combined with wind waves). 

A site-specific probabilistic flood-hazard assessment is accomplished in two steps (DOE 1995). 

First, a flood-screening analysis is performed to determine the magnitude of flood hazards for 

an SSC, and then a comprehensive flood-hazard assessment based on the results of the 

screening is completed. The screening analysis is performed to determine whether the site can 

be considered a dry site as defined by ANS (1992). 

The screening analysis consists of the following four steps: 

1. Compile historical peak discharges. 

2. Estimate the probability-of-exceedance for peak discharges. 

3. Estimate the stage-discharge relationship from historical flood data or hydraulic analysis. 

4. Transform the peak discharge frequency distribution to a stage frequency distribution to 

evaluate the probabilities-of-exceedance for selected grade elevations. 

The comprehensive flood hazard assessment may be performed using statistical methods, 

probabilistic hydrologic modeling, and paleohydrologic analysis. Some of these methods are 

described by the National Research Council (1988). 

1.3 Federal Energy Regulatory Commission 

The FERC, in part, licenses and inspects private, municipal, and state hydroelectric projects. 

FERC’s engineering guidelines for evaluation of dams and hydropower projects contain 

procedures for estimation of PMF (FERC 2001). FERC guidelines use the runoff generated by 

the PMP in the drainage basin to estimate the inflow PMF for the project reservoir. Use of the 

most recent HMR is recommended unless an approved site-specific PMP study is available. 

Use of the computer program HMR52 (BOSS International 1988) is recommended for 

estimation of PMP hyetographs for subbasins. The inflow PMF is routed through the reservoir 

and outlet works to estimate the outflow PMF and the maximum PMF water-surface elevation at 

the dam. 

The guidelines (FERC 2001) do not consider failure of upstream dams during development of 

the PMF at a downstream project. The PMF is routed through upstream dams assuming they 

remain intact. However, consideration of the failure of upstream dams during a PMF is 

recommended. 

The guidelines (FERC 2001) use the unit hydrograph approach for runoff generation. Use of 

unit hydrographs already developed during previous local, State, or Federal studies is 

recommended. Previously developed unit hydrographs should be validated against the largest 

historical flood. Development of new unit hydrographs is suggested if the available unit 

hydrographs were not derived using current precipitation-runoff data, do not accurately 

reproduce large historical floods, or changes in basin characteristics have occurred since the 
1-6 

development of the unit hydrographs. The guidelines specifically warn against use of small 

floods for development of unit hydrographs that are intended for use in estimation of the PMF. 

Frequency analysis of historical floods is recommended for selection of significant floods for 

development of unit hydrographs. 

For ungauged drainage basins, the guidelines (FERC 2001) recommend using synthetic unit 

hydrographs from existing or new regional studies. If sufficient data are not available to develop 

synthetic unit hydrographs, empirical unit hydrographs such as Snyder, Clark, or Natural 

Resources Conservation Service (NRCS) are recommended. The guidelines require 

justification of coefficients of empirical unit hydrographs. 

For estimating the PMF, FERC (2001) recommends that the initial loss, which generally reflects 

interception and depression storage in the drainage basin, should be set to zero. The 

guidelines recommend estimating continuing loss rates, which reflects the effect of infiltration, 

from soil properties, but caution against unrealistically high estimates of loss rates. For 

drainage basins where estimated loss rates cannot be validated, loss rates should be set to 

minimum recommended values (FERC 2001). 

The guidelines (FERC 2001) also recommend the use of certain conditions concurrent with the 

PMP, similar to combined events described by ANS (1992). These concurrent conditions 

include existence of a 100-year snowpack in appropriate areas of the drainage basin, air 

temperature sequences, and average monthly base flow. 

1.4 Design-Basis Flood Estimation Guidelines of the International 

Atomic Energy Agency 

If it receives a request, the International Atomic Energy Agency (IAEA) assists its member 

states in determining potential sites for and designs of nuclear power plants. The IAEA 

publishes a series of documents that describe the fundamentals (the basic principles that 

ensure safety), standards (the basic requirements that must be met to ensure safety), guidance 

(recommendations based on international experience that help meet standards), and practices 

(examples and methods). 

IAEA Safety Guide NS-G-3.5 (IAEA 2003) describes the design-basis flood as “... a series of 

parameters that maximize the challenge to plant safety as a consequence of a flood.” The 

parameters may consist of maximum water level, maximum dynamic effects on flood-protection 

structures, or maximum rate of rise of water levels. 

For coastal sites, IAEA (2003) recommends evaluation of PMSS, PMT, probable maximum 

seiche (PMS), and wind-wave effects considered independently or in combination. 

Conservatively high ambient water levels should be considered, including those related to tides, 

sea-level anomalies, and lake levels. 

For river sites, IAEA (2003) recommends evaluation of offsite precipitation-induced floods 

routed to the site; snowmelt floods; floods caused by seismic or hydrologic failures of natural or 

artificial structures; floods caused by obstruction of a river channel by landslides, ice jams, or 

debris; floods caused by large waves in water basins resulting from landslides or volcanic 

activity; floods caused by changes in natural channels; floods caused by wind waves on large 

rivers or estuaries; and floods caused by increased groundwater levels induced by earthquakes. 

Combinations of dependent events are also recommended for careful evaluation. 
1-7 

IAEA (2003) recommends that deterministic and probabilistic methods for evaluating the designbasis flood should be considered complementary. The estimated flood hazard should be 

compared to historical data to verify that the specified design basis exceeds the historical 

extreme by a substantial margin. 

2-1 

2 THE HIERARCHICAL HAZARD ASSESSMENT APPROACH 

The applicant for an NRC license or permit performs a safety analysis to demonstrate that 

(1) hazards from natural phenomena would not adversely affect the functioning of the plant’s 

safety-related SSCs (see NRC 2007b for description of safety-related SSCs), or (2) the affected 

safety-related SSCs are adequately protected against the adverse effects of the natural 

phenomena. In this report, we describe hazard assessment for floods. 

First, for the selected site of a nuclear power plant, the causal phenomena or mechanisms that 

could lead to flooding should be identified. Flood-causing mechanisms refer to the set of those 

hydrometeorological, geoseismic, or structural failure phenomena that may produce a flood at or 

near the site. The geographical area that is relevant for each flood-causing mechanism should 

be identified. This geographical area, generally termed the vicinity of the site or site region (or 

just “the vicinity”), depends on the nature of the flood-causing mechanism being considered. 

Floods generated in the vicinity because of the hydrometeorological, geoseismic, or structural 

failure may propagate to the site. For example, the vicinity for a PMF in a river that flows by a 

site may consist of the entire watershed of the river upstream of the site. For a site located near 

coastal regions, an ocean or a large lake also may be included in the vicinity if tsunamis or 

storm surges that occur in them might propagate to the site. 

An inspection of historical data may reveal the flood-causing mechanisms that should be 

considered for a site. For example, an inspection of air temperature data may suggest the 

potential for formation of ice jams or dams, the subsequent collapse of which may generate a 

flood. More relevant are an inspection of the hydrology, topography, morphology, and geology 

and the presence of any water-control structures in the vicinity of the site (e.g., a site located on 

the banks of a river should be investigated for the PMF in the river; a site that has several 

upstream dams should be analyzed for floods from single and cascading dam failures). 

Typically, flood-causing mechanisms that should be considered include local intense 

precipitation, flooding in rivers and streams, flooding from upstream dam breaches or failures, 

flooding from storm surges or seiches, flooding from tsunamis, flooding from ice-induced events, 

and flooding from channel diversions toward the site. 

The hierarchical hazard assessment (HHA) is a progressively refined, stepwise estimation of 

site-specific hazards that evaluates the safety of SSCs with the most conservative plausible 

assumptions consistent with available data. The HHA process starts with the most conservative 

simplifying assumptions that maximize the hazards from the probable maximum event for each 

natural flood-causing phenomenon expected to occur in the vicinity of a proposed site. The 

focus of this report is on flood hazards. If the site is not inundated by floods from any of the 

phenomena to an elevation critical for safe operation of the SSCs, a conclusion that the SSCs 

are not susceptible to flooding would be valid (ANS 1992), and no further flood-hazard 

assessment would be needed. 

However, if the level of assessed hazards results in an adverse effect or exposure to any safetyrelated SSC, a more site-specific hazard assessment should be performed for the probable 

maximum event. Several iterations of the flood-hazard assessment, each based on inclusion of 

additional site-specific data, may be needed to demonstrate that the assessed hazards from the 

probable maximum event are still based on conservative assumptions yet do not adversely 

affect the safety-related SSCs. Under these conditions, the reasonable assurance criterion for 

safety, as stated above, is demonstrated. 
2-2 

If the iterative process identifies a situation that is considered the most site-specific based on 

available data and still results in exposure of or adverse effects to the safety-related SSCs, 

flooding protection measures should be employed to protect the affected SSCs as described in 

NRC Regulatory Guide 1.59 (NRC 1977). Regulatory Guide 1.102 (NRC 1976) identifies the 

types of flooding protection acceptable to NRC. A certain level of subjectivity is involved in 

determining the level of conservatism associated with a simplifying assumption, and also in 

what may be considered a site-specific scenario. Engineering judgment and the practices of 

Federal agencies, such as USACE, the Reclamation, the NRCS, and others, may be useful in 

these considerations. 

The HHA approach should be carried out for each flood-causing mechanism for a proposed site. 

The design-basis flood is the event that results in the most severe hazard to the safety-related 

SSC. It should be noted here that depending on the locations of safety-related SSCs, the 

design-basis flood for a particular SSC may be different from design-basis floods for other 

SSCs. For example, the containment building located in the powerblock area may be exposed 

to the most severe hazard from the local intense precipitation-generated flood, and at the same 

site, a safety-related cooling-water intake may be exposed to the most severe hazard from a 

PMT or PMSS. The design bases for the containment building then should be derived from the 

local intense precipitation-generated flood, while the bases for the cooling-water intake would be 

derived from the PMT or PMSS. 

Regulatory Guide 1.102 (NRC 1976) states that safety-related SSCs should be protected both 

from static and dynamic effects of floods. Therefore, the static and dynamic loadings of floods 

generated by each flood-causing mechanism should be considered to determine the design 

bases for each safety-related SSC. 

The steps involved in the HHA approach for estimating the design-basis flood are summarized 

below. 

1. Identify flood-causing phenomena or mechanisms by reviewing historical data and 

assessing the geohydrological, geoseismic, and structural failure phenomena in the 

vicinity of the site and region. 

2. For each flood-causing phenomenon, develop a conservative estimate of the flood from 

the corresponding probable maximum event using conservative simplifying assumptions. 

3. If any safety-related SSC is adversely affected by flood hazards, use site-specific data to 

provide more realistic conditions in the flood analyses while ensuring that these 

conditions are consistent with those used by Federal agencies in similar design 

considerations. Repeat Step 2; if all safety-related SSCs are unaffected by the 

estimated flood, or if all site-specific data have been used, specify design bases for each 

using the most severe hazards from the set of floods corresponding to the flood-causing 

phenomena. 

The steps of HHA can also be illustrated using a flowchart. Figure 2-1 shows the steps 

involved, decision points, and ultimate alternative outcomes of the HHA for flood water-surface 

elevation from a PMF event. 
2-3 

Figure 2-1. Flowchart Demonstrating the HHA Applied to Flood Hazards from a PMF 

Event 

An example of how HHA is applied based on Figure 2-1 is described below. The flood-causing 

mechanism considered is the PMF in the drainage basin upstream of the site. For 

demonstration, it was assumed that the site is located on an impoundment on the stream, and 

the safety-related SSCs are located at a grade elevation above the normal water-surface 

elevation in the impoundment. 

1. The PMP for the drainage basin upstream of the site was estimated by applying relevant 

data from National Oceanic and Atmospheric Administration (NOAA) NWS (HMRs) to 

obtain a set of PMP rainfall hyetographs for each subbasin.

2. The PMF in the drainage basin upstream of the site was estimated by conservatively 

assuming that no precipitation losses occur during the PMF event and that the runoff 

generated in any part of the drainage basin is instantaneously translated through the 

channel network and arrives at the site without delay. Both of these are simplifying 

assumptions (loss rates need not be determined and channel routing need not be 

performed) and are conservative as well (no loss maximizes the volume of runoff and no 

delay maximizes the peak discharge). The inflow hydrograph into the reservoir is 

therefore calculated simply by multiplying the hyetograph ordinates for each subbasin by 

its corresponding area and converting the resulting volume into a discharge over the 

time step. Further, it was conservatively assumed that the inflow hydrograph would not 

be attenuated as it passed through the reservoir, and the water-surface elevation in the 

reservoir corresponding to the peak discharge at the dam and spillway was estimated 

using a broad-crested weir discharge equation. The resulting water-surface elevation in 

the reservoir exceeded the site grade. 

Estimate PMP.

Use most conservative assumptions to build 

runoff generation and routing models:

PMF with no loss and instantaneous translation.

Estimate PMF discharge and 

water surface elevation.

Does PMF

water-surface elevation at the 

site exceed critical elevations 

of SSCs?

No

Yes

Are any sitespecific data available to specify

loss rates or runoff models consistent 

with practices of other Federal 

agencies?

Use site-specific data to 

refine runoff generation 

and routing models.

No

Yes

Stop. Safety of the 

SSCs demonstrated.

Stop. Flooding 

protection to exposed 

SSCs must be provided.
2-4 

Because the safety-related SSC would be inundated by the flood estimated under 

extremely conservative conditions, in the second iteration the analysis was made more 

site-specific by introducing reservoir routing, while keeping all other assumptions the 

same. The initial water-surface elevation in the reservoir was assumed to be at the fullpool level. Site-specific reservoir storage-elevation-discharge data were used in the 

reservoir routing. The reservoir routing of the inflow hydrograph reduced the peak 

discharge at the dam and spillway and resulted in a water-surface elevation that was 

lower than that computed previously. However, the site was still inundated, although to 

a lesser degree. 

In the third iteration, the assumption of instantaneous translation of the runoff from each 

subbasin to the reservoir was replaced by runoff generation according to site-specific 

unit hydrographs adjusted to account for non-linear basin response during large floods 

approaching the PMF (see Section 2.2). The unit hydrographs reduced the peak 

discharges from those computed in the first iteration and introduced a time delay or lag 

between the time when runoff was generated in each subbasin and when it arrived in the 

channel network. The inflow hydrograph was routed through the reservoir as in the 

second iteration. The resulting peak water-surface elevation at the site was now below 

the site grade. Because all safety-related SSCs are located at the site grade, the site is 

dry under the stillwater effects of the PMF. Notice that two conservative assumptions in 

the PMF analysis still remain: (1) no precipitation loss and (2) no channel routing. 

Therefore, the PMF is estimated using a conservative and a relatively simple approach. 

Coincident wind waves should now be estimated at the site based on the longest fetch 

length and a 2-year wind and added to the PMF stillwater elevation at the site. If the 

combined-effects flood water-surface elevation does not exceed the site grade, the site 

has been demonstrated to be dry. If the combined-effects flood water-surface elevation 

exceeds the site grade, more site-specific data may be used to characterize channel 

routing or specify an appropriate yet conservative precipitation loss rate. 

3. If the site were determined to be dry, specification of no other design bases for flood 

hazards from a PMF event would be needed. If the site were determined to be wet even 

after using all available site-specific data, flooding protection options should be specified 

for affected safety-related SSCs. 
3-1 

3 CAUSATIVE MECHANISMS FOR DESIGN-BASIS FLOODS 

Several flooding mechanisms or causes, and reasonable combinations of those mechanisms or 

causes, should be investigated to estimate the design-basis flood at nuclear power plant sites. 

These mechanisms or causes are described in this chapter. 

3.1 Alternative Conceptual Models 

Before investing a significant effort involving the simulation of a design-basis flood at a site, it is 

useful to articulate clearly the alternative conceptualizations of the hydrometeorological 

phenomena and how they may affect the site. These alternative conceptualizations of causative 

mechanisms are called alternative conceptual models for the site, and they should be described 

for all flooding mechanisms. Alternative conceptual models also clearly demonstrate why a 

particular conceptualization may be more conservative than another. Alternate conceptual 

models also clearly demonstrate the need for site-specific data and the use of site-specific data 

in establishing more refined site-specific models. Therefore, alternative conceptual models form 

the basis of the HHA approach. As described in Chapter 4, the three iterations performed 

during the example design-basis flood estimation are simply a set of alternative conceptual 

models. Each alternative conceptualizes the flood-generation mechanism in the drainage basin 

above the site with a different level of complexity. The alternative conceptual model that 

ultimately specified the design basis also was clearly demonstrated to be conservative when the 

assessment was completed. 

The need for site-specific data is expected when estimating a design-basis flood. The diverse 

set of publicly available data compiled by Federal and State agencies that is relevant for 

estimating design-basis floods is described in Appendix A. 

3.2 Local Intense Precipitation 

Local intense precipitation is a measure of the extreme precipitation at a given location. The 

duration of the event and the support area are needed to qualify an extreme precipitation event 

fully. Generally, the amount of extreme precipitation decreases with increasing duration and 

increasing area. 

The PMP values for areas of the United States east of the 105th meridian are presented in 

HMRs 51 (Schreiner and Riedel 1978) and 52 (Hansen et al. 1982). The 1-hr, 2.56-km2

 (1-mi2) 

PMP was derived using single-station observations of extreme precipitation, coupled with 

theoretical methods for moisture maximization, transposition, and envelopment. HMR 52 

recommended that no increase in PMP values for areas smaller than 2.56 km2

 (1 mi2) should be 

considered over the 1-hr, 2.56-km2

 (1-mi2) PMP. The local intense precipitation is, therefore, 

deemed equivalent to the 1-hr, 2.56-km2

 (1-mi2) PMP at the location of the site. 

3.2.1 Flood Generated by Local Intense Precipitation and Its Effects 

The elevation of the site, or the site grade, is irrelevant for mitigation of flooding from local 

intense precipitation. The runoff carrying capacity of the site grading design and the 

performance of any active or passive drainage system would determine the depth and velocity 

of surface runoff at the site. Typically, any active drainage systems should be considered nonfunctional at the time of the local intense precipitation event. The surface runoff would be 
3-2 

carried off from the immediate powerblock area to any adjoining drainage channels 

through overland flow and then be carried away from the site to a natural creek or stream. 

The runoff losses should be ignored during the local intense precipitation event to maximize the 

runoff from the event. The powerblock area where safety-related SSCs are located may be 

subdivided into sub-areas that drain in different directions depending on the site grading design. 

The hydraulic parameters that affect the depth and velocity of flow should be chosen carefully 

and should be consistent with values used in standard engineering practice by Federal agencies 

and other authorities responsible for similar design considerations. The reasons for parametervalue choices should be properly documented. 

Hydrologic and hydraulic simulation models accepted in standard engineering practice by 

Federal agencies and other authorities responsible for similar design considerations may be 

used to estimate the time history of runoff and its hydraulic characteristics during an event. At 

the time this report was written, hydrologic and hydraulic simulation models developed, 

described, and maintained by the Hydrologic Engineering Center (HEC) of the USACE were 

acceptable to NRC (USACE 2008a, b). Considerations involved in the choice of a simulation 

model are described in more detail in Chapter 5 of this report. Although this report uses HEC 

models to illustrate the estimation of floods generated by local intense precipitation at nuclear 

power plant sites, appropriate justification for selection of methods, data, and models would 

depend on site-specific circumstances (see Sections 5.3 and 5.4). 

If a flood generated by local intense precipitation is determined to be the design basis, each 

safety-related SSC that may be exposed to the static and dynamic effects of the flood should 

have openings and doors located above the highest water-surface elevation attained during the 

event. In addition, the safety-related SSCs should be able to withstand the dynamic effects of 

the flood (e.g., drag forces). If either of the above conditions is not met, flooding protection for 

affected safety-related SSCs should be considered and described. If flooding protection is 

needed for safety-related SSCs, the rate of rise of the flood waters also should be determined to 

establish available lead times. 

3.2.2 Hierarchical Hazard Assessment Applied to a Local Intense PrecipitationGenerated Flood 

Appendix B provides an example of the method used to estimate flooding in a hypothetical 

passive site drainage network during a local intense precipitation event. This section describes 

how the example provided in Appendix B should be applied in the HHA framework using 

alternative conceptual models of the site drainage. 

The simplest and most conservative conceptual model for site drainage is to assume that no 

active components remain functional and even the passive site drainage network is 

compromised. This conceptual model corresponds to Case 3 described in Appendix B. The 

method described there should be used to determine the highest water-surface elevation during 

the local intense precipitation event. If the estimated water-surface elevation does not affect 

any safety-related SSCs, it can be concluded that the plant would be safe from the effects of the 

local intense precipitation event. 

If the water-surface elevation estimated using Case 3 does result in adverse effects to one or 

more safety-related SSCs, and site constraints would not allow for adequate modifications to the 

grading or placement of the SSCs, the conceptual model described in Case 2 could be used. 

However, a clearly articulated justification, supported by site-specific hydrometeorological data, 

would be needed to demonstrate that the passive site drainage network would not be 
3-3 

completely blocked by debris or otherwise compromised during the local intense precipitation 

event. Once the justification has been documented, the methods used in Case 2 may be used 

to estimate the water-surface elevation during the local intense precipitation event. 

If the water-surface elevation estimated using Case 2 results in adverse effects on one or more 

safety-related SSCs, the methods described in Case 1 may be used. However, 

hydrometeorological evidence suggests it is extremely rare that the passive site drainage 

network would remain completely unblocked during a local intense precipitation event. 

Therefore, use of this conceptual model is not recommended. Instead, the site grade and the 

drainage network may need to be redesigned. 

3.3 Flooding in Rivers and Streams 

The PMF in rivers and streams adjoining the site should be determined by applying the PMP to 

the drainage basin of these rivers and streams. The PMF is defined by ANSI/ANS-2.8-1992 

(ANS 1992) as “... the hypothetical flood (peak discharge, volume, and hydrograph shape) that 

is considered to be the most severe reasonably possible, based on comprehensive 

hydrometeorological application of PMP and other hydrologic factors favorable for maximum 

flood runoff such as sequential storms and snowmelt.” 

3.3.1 Estimating the PMF and Its Effects 

The estimation of PMP for different zones of the United States has been described by NOAA 

NWS in its series of HMRs. The PMP is a deterministic estimate of the theoretical maximum 

depth of precipitation that can occur at a time of year over a specified area. A rainfall-to-runoff 

transformation function and an accounting of the runoff aggregation by the topographic and 

drainage or stream network characteristics in addition to certain watershed properties are 

needed to estimate the PMF hydrograph. Simulation models called “hydrological models” 

typically use the time history of PMP precipitation as input and estimate the PMF runoff 

hydrograph given a set of watershed parameters that describe precipitation losses, rainfall-torunoff transformation, antecedent streamflow conditions, and travel time within the stream 

network. 

A PMF hydrograph obtained from hydrological models provides only a time history of discharge 

or streamflow within the stream network. To obtain the hydraulic parameters of the PMF, such 

as velocity and depth, another class of models usually called “hydraulic models” is used. The 

hydraulic models use the PMF hydrographs estimated by hydrological models at key locations, 

a set of physical properties of the stream network such as longitudinal and cross-sectional 

geometry, stream reach connectivity, channel roughness, and initial conditions within the stream 

network to estimate PMF flow velocities and depths (or equivalently, the flood water-surface 

elevation). 

The hydraulic properties estimated by the hydraulic model are used then to specify the PMF 

characteristics near the site. If the water-surface elevation in the river or stream adjacent to the 

site exceeds the design site grade, the static and dynamic effects of the PMF may adversely 

affect safety-related SSCs. The affected SSCs should be protected from the most severe 

hazards, or the site grade should be redesigned. Regulatory Guide 1.102 (NRC 1976) 

describes the types of flooding protection acceptable to the NRC. 

At the time this report was written, hydrologic and hydraulic simulation models developed, 

described, and maintained by the USACE HEC were acceptable to the NRC. Considerations 

that should be applied when choosing a simulation model are described in more detail in 
3-4 

Chapter 5 of this report. Although this report uses HEC models to illustrate the estimation of 

floods in river and streams that may affect nuclear power plant sites, appropriate justification for 

selection of methods, data, and models would depend on site-specific circumstances 

(see Sections 5.3 and 5.4). 

If the PMF is determined to be the design basis, each safety-related SSC that may be exposed 

to the static and dynamic effects of the PMF should have its openings and doors located above 

the highest water-surface elevation attained during the event. In addition, the safety-related 

SSCs should be able to withstand the dynamic effects of the PMF (e.g., drag forces). If either of 

the above conditions is not met, flooding protection for affected safety-related SSCs should be 

considered and described. If flooding protection is needed for safety-related SSCs, the rate of 

rise of the flood waters also should be determined to establish available lead times for 

responding to floods. 

3.3.2 Hierarchical Hazard Assessment Applied to PMF 

Appendix C provides an example of how to estimate the PMF at a hypothetical nuclear power 

plant site. An example of the use of alternative conceptual models within the HHA framework to 

estimate the design-basis flood from a PMF is provided in Section C.4. Appendix C contains 

additional discussions regarding alternative conceptual models that should be investigated 

(see discussion of scenarios in Section C.4). 

The most commonly accepted way of specifying a rainfall-runoff transformation function 

accepted is the unit hydrograph approach, which was proposed by Sherman (1932). The unit 

hydrograph is defined as the direct runoff hydrograph that results from a unit depth of spatially 

and temporally uniform rainfall excess in the drainage basin over a specific duration (Pilgrim and 

Cordery 1993). 

The theory behind the unit hydrograph approach is based on two assumptions: (1) the drainage 

basin is a lumped system in that no spatial variability in rainfall input or losses is allowed, and 

(2) the direct runoff discharge hydrograph for rainfall excess values other than the unit depth 

can be obtained simply by scaling the unit hydrograph ordinates by the rainfall excess value. 

The direct runoff hydrograph from a sequence of rainfall excess depth is calculated by 

superimposing the individual responses from each of the individual pulses of rainfall excess. 

Because of the linearity assumption, unit hydrographs of other durations can be estimated 

readily if a unit hydrograph of a given duration is available (Chow et al. 1988). 

Unit hydrographs can be estimated from observed rainfall and runoff data (Chow et al. 1988). 

For ungauged drainage basins, empirical relationships based on characteristics of the drainage 

basin have been developed to estimate synthetic unit hydrographs (e.g., NRCS 1985; 

Nash 1960; Snyder 1938; Clark 1945). Standard hydrology texts, such as Chow et al.’s (1988), 

contain descriptions of these methods. More recent research has attempted to derive unit 

hydrographs from geomorphic characteristics of the drainage basin (Rodriguez-Iturbe and 

Valdes 1979; Gupta et al. 1980; Rodriguez-Iturbe and Rinaldo 1997). 

One vexing problem remains when using unit hydrographs to estimate the PMF. By definition, 

the PMF is an extremely rare event, with virtually no possibility of being exceeded. Therefore, 

unit hydrographs derived from observed rainfall and runoff data, or those based on empirical 

relationships, do not represent hydrometeorological conditions that would prevail during a flood 

as large as the PMF. The hydraulic efficiency of drainage networks is expected to increase 

during a PMF event, and the flood discharge is certain to overflow the banks of drainage 

channels and occupy large areas of the floodplain. For these reasons, the drainage basin 
3-5 

response during a PMF event is expected to be much different from that assumed during the 

derivation of the unit hydrographs, violating the linearity assumption in the theory. At the very 

least, the unit hydrographs should be derived from floods that are among the largest on record 

and that approach the magnitude of the PMF. Pilgrim and Cordery (1993) describe a set of 

adjustments that may be made to unit hydrographs derived from floods smaller than the PMF. 

The recommended adjustments to peak discharge and lag time (i.e., the time to peak discharge) 

are a 5-to-20-percent increase for the peak discharge and a 33-percent reduction in the lag 

time. 

3.4 Dam Breaches and Failures 

Flood waves resulting from severe breaches of upstream dams, including domino-type or 

cascading dam failures, should be evaluated for the site. Water-storage or water-control 

structures (such as onsite cooling or auxiliary water reservoirs and onsite levees) that may be 

located at or above the safety-related site grade should also be evaluated. In cases of failure of 

earthen levees or embankments onsite, the effects of sediment being carried with the flood 

wave should also be determined. 

Dam failure scenarios, particularly those related to cascading dam failures, should be carefully 

analyzed and documented to establish that the most severe of the possible combinations has 

been accounted for. Typically, two scenarios of upstream dam failure should be considered: 

(1) failure of individual dams and (2) cascading or domino-like failures of dams. Appendix D 

provides an example of cascading combinations and methods for estimating the geometric 

characteristics of dam breaches. 

3.4.1 Hierarchical Hazard Assessment Applied to Dam Breaches and Failures 

The simplest and most conservative dam-breach induced flood may be expected to occur under 

the assumption that (1) all dams upstream of the site are assumed to fail during the PMF event 

regardless of their design capacity to safely pass a PMF and (2) the peak discharge from 

individual dam failures reach the site at the same time. In this scenario, the peak discharges of 

all individual flood waves from the failures, augmented by PMF inflows, arrive at the site at the 

same time. This scenario is clearly the most conservative because (1) PMF is augmented by 

release of stored water within the reservoirs and (2) differences in travel time for the peak 

discharges from individual dam failures to reach the site is ignored. 

If the flood water-surface elevation in the stream adjacent to the site from the most conservative 

scenario described above when combined with wind-induced waves is below the safety-related 

site grade, no further analysis would be necessary. If the safety-related site grade is exceeded, 

site-specific data may be used to specify progressively more refined scenarios of dam failures: 

1. Investigate the failures of only a subset of all the upstream dams while assuming that 

peak discharges of individual dam-failure induced floods reach the site at the same time. 

A justification that the remaining dams would not fail under PMF scenarios should be 

provided. 

2. The most severe cascading failure combination should be investigated (see Appendix D 

for an example). This scenario may require setting up the USACE Hydrologic 

Engineering Center River Analysis System (HEC-RAS) model or another hydraulic 

model input with site-specific data related to channel geometry and bathymetry and 

reservoir stage-storage-discharge relationships. Manning’s roughness coefficients also 

would be needed as input. An example of this approach is provided in Appendix D. 
3-6 

Although this report uses HEC models to illustrate the estimation of floods from dam breaches 

and failures that may affect nuclear power plant sites, appropriate justification for selection of 

methods, data, and models would depend on site-specific circumstances (see Sections 5.3 and 

5.4). 

If the dam-failure induced flood is determined to be the design basis, each safety-related SSC 

that may be exposed to the static and dynamic effects of the flood should have openings and 

doors located above the highest water-surface elevation attained during this event. In addition, 

the safety-related SSC should be able to withstand the dynamic effects of the flood (e.g., drag 

forces). If either of the above conditions is not met, flooding protection for affected safetyrelated SSCs should be considered and described. If flooding protection is needed for safetyrelated SSCs, the rate of rise of the flood waters also should be determined to establish 

available lead times. 

Sunny-day failure of dams, which are characterized by an absence of a concurrent extreme 

flood, may produce the highest flood elevations depending on the relative location of the dam, 

water-surface elevation in the reservoir, and the critical elevations of safety-related SSCs. 

These dam failures may occur due to failures of embankment material or foundation such as 

those due to piping through the embankment or liquefaction of foundation during seismic 

events. Sunny-day failures of dams could result in single or multiple cascading failures 

depending on the configuration of the water-storage facilities. The possibility of these failures 

should be carefully evaluated to ensure that all plausible mechanisms for flooding from dam 

breaches and failures at and near a site are considered. 

3.5 Storm Surge 

Storm types are defined by NOAA according to the maximum sustained wind speed. The 

maximum sustained wind speed is defined as the highest 1-minute average wind speed within 

the storm at a height of 10 m (33 ft). 

Tropical storms in the Atlantic Ocean start as tropical disturbances, which are weather systems 

with an apparently organized convection around a low pressure center and movement that is 

sustained for a day or more. As the central pressure drops, the weather system can sustain 

faster winds and develop into a tropical depression that is characterized by maximum sustained 

wind speeds up to 61 km/hr (38 mph, 33 kt). The weather system strengthens into a tropical 

storm if the maximum sustained winds reach speeds of 63 to 117 km/hr (39 to 73 mph, 34 to 63 

kt). Further strengthening of the storm categorizes it as a hurricane. As shown in Table 2.1, the 

Saffir-Simpson hurricane intensity scale (Simpson and Riehl 1981) is used by NOAA to describe 

the severity of hurricanes in five categories. The use of central pressure as a defining 

characteristic was discontinued in the 1990s. 

Storm surge is the rise in offshore water elevation caused principally by the shear force of the 

hurricane winds acting on the surface. A secondary rise in water surface is also caused by the 

lowering of the air pressure within the hurricane. In the past, the Saffir-Simpson scale also was 

used to describe expected storm surges from hurricanes of different categories. Irish et al. 

(2008) point out that while the use of Saffir-Simpson scale is appropriate for wind damage, its 

use as an indicator for storm surge is not. Using numerical simulations of idealized hurricanes, 

they showed that storm intensity, bottom slope, and storm size are important factors in storm 

surge generation at the coastline. Simulated storm surge increased with storm size for a given 

storm intensity (Irish et al. 2008). 

 
3-7 

Table 3-1. Types of Tropical Storms and the Saffir-Simpson Scale Describing the 

Categories of Hurricanes 

Type and Category Wind Speed km/hr (mph, kt) Central Pressure kPa (mb, in. Hg)

Tropical Depression (TD) < 62 (< 39, 34) 

Tropical Storm (TS) 63–117 (39-73, 34–63) Hurricane 

Category 1 (H1) 118–153 (74–95, 64–82) > 98 (> 980, 28.94) 

Category 2 (H2) 154–177 (96–110, 83–95) 96.5–98 (965-980, 28.50–28.94) 

Category 3 (H3) 178–209 (111–130, 96–113) 94.5–96.5 (945-965, 27.91–28.50) 

Category 4 (H4) 210–249 (131–155, 114–135) 92–94.5 (920-945, 27.17–27.91) 

Category 5 (H5) >250 (> 155, 135) < 92 (< 920, 27.17) 

 

NOAA NWS Technical Report 23 (NWS 23) (Schwerdt et al. 1979) provides methods for 

estimating PMH wind fields. The study that was the basis for this report was funded jointly by 

NRC and USACE. The PMH is defined as a hypothetical steady-state hurricane having a 

combination of values of meteorological parameters that will give the highest sustained wind 

speed that can probably occur at a specified coastal location. The term steady state is meant to 

indicate that there is no change in the value of hurricane wind-field parameters during at least 

the last several hours before the PMH makes landfall. Appendix E contains an example of how 

the PMH wind field is estimated using the NWS 23 procedure (Schwerdt et al. 1979). 

Once the PMH wind field is estimated, it should be input into a coastal hydrodynamics 

simulation model that predicts the water-surface rise, or the PMSS, from the shear forces 

imparted by the wind field. NOAA NWS has developed such a model, the Sea, Lake, and 

Overland Surges from Hurricanes (SLOSH). Details of the SLOSH model are described by 

Jelesnianski et al. (1992). The SLOSH model was used in this study to illustrate one way of 

predicting the PMSS for a hypothetical location (see Appendix E). 

Since NWS 23 (Schwerdt et al. 1979) was published, advances in the understanding of 

hurricane wind fields (Holland 1980; Powell et al. 2003) have occurred and more detailed data 

and models (Mukai et al. 2002; Westerink et al. 2008; Bunya et al. 2010) have become 

available. These advances allow more detailed and accurate simulations of storm surges 

because they are based on more recent understanding of the physics of the hurricane-storm 

surge processes; resolve the spatial heterogeneity in bathymetry, topography, and hydrologic 

characteristics; and can explicitly account for coastal structures that may impede or enhance the 

movement of storm surge inland. The Federal Emergency Management Agency (FEMA) 

currently uses the USACE Advanced Circulation (ADCIRC) model (Westerink et al. 2008; Bunya 

et al. 2010) for preparing flood insurance maps along the eastern Atlantic and Gulf of Mexico 

coasts (FEMA 2010). 

Although this report uses SLOSH to illustrate the estimation of PMSS at nuclear power plant 

sites, appropriate justification for selection of methods, data, and models would depend on sitespecific circumstances (see Sections 5.3 and 5.4). Design-basis floods that result from PMSS 

at sites located some distance inland from the coastline would need to account for the 

interaction of the PMSS with estuaries and river channels, coastal structures, and roads and 

levees. These issues should be documented to provide assurance that an appropriate model 

and supporting data are used for the site. 

Similar to other simulation models (see Section 5.4), uncertainty in inputs, parameters, and 

model physics apply to storm surge models also. NWS 23 provides ranges of PMH parameters. 

Combinations of these parameters should be used to simulate multiple scenarios in estimation 

of PMSS. More recent studies have used a formal joint probability framework to estimate the 
3-8 

distribution and spatial properties of storm surge in the Gulf of Mexico (Resio et al. 2009; Irish 

et al. 2009). These methods are still being developed and may require significant effort to 

implement at specific sites, although some research is also being carried out that may help in 

reducing the burden (Irish et al. 2009). Some of the issues discussed here can also be 

addressed in a formal probabilistic flood hazard assessment, as described in Section 5.6, and 

are recommended for future research. 

3.5.1 Hierarchical Hazard Assessment Applied to PMSS 

As with the other flood-causing mechanisms described above, the HHA should be applied to 

flooding from PMSS. However, the application of HHA to PMSS is less straightforward because 

there are few parameters that need adjustment. The factors that may change the PMSS watersurface elevation at the site are (1) the ambient tide level for coastal and streamside locations 

and (2) the ambient flood water-surface elevation for the streamside locations. These 

two factors are accounted for in combined events criteria described below. It is not recommend 

that the parameters of the SLOSH model be varied because they have been set to values that 

result in an acceptable predictive accuracy for the U.S. Gulf and the Atlantic Coasts. 

For a given location however, the PMH has three variable parameters: (1) the forward speed 

(T), (2) the radius of maximum winds (R), and (3) the track direction (θ). Because of uncertainty 

in these parameters, the NWS 23 estimation procedure provides a range of values for these 

parameters of the PMH wind field. 

The NOAA NWS also defines two terms related to the maximum expected water-surface 

elevation. The maximum envelope of water (MEOW) is defined as the maximum water-surface 

elevation at any given location during simulation of the storm surge from a given hypothetical 

hurricane characterized by storm category, track direction, forward speed, and tide level. 

Therefore, the MEOW at any given location can be thought of as the peak of the water-surface 

elevation hydrograph for a specific hurricane. 

MEOWs can be generated for several hypothetical hurricanes of a specific storm category by 

varying the track direction, forward speed, and tide level. The maximum of these water-surface 

elevations at any given location is called maximum of the MEOWs (MOM). Because there are 

five storm categories defined by the Saffir-Simpson scale, five MOMs exist for any given 

location. 

The PMH does not have a Saffir-Simpson category assigned to it. However, MEOWs for a 

PMH can still be generated by simulating the PMSS for a specific set of T, θ, and R. Because 

each of these three parameters of the PMH wind field has a range associated with it, a set of 

hypothetical PMSS simulations can be performed for a given location by varying the 

three parameters over their stated ranges. From each of these PMSS simulations, a MEOW 

can be obtained for the site location. The maximum of these MEOWs, therefore, is a PMH 

MOM. 

The approach adopted in this report is to estimate the PMH MOM for the site location 

(see Appendix E) and then use it as an estimate of the PMSS. 

If the PMSS is determined to be the design basis, each safety-related SSC that may be 

exposed to the static and dynamic effects of the flood should have openings and doors located 

above the highest water-surface elevation attained during this event. In addition, the safetyrelated SSCs should be able to withstand the dynamic effects of the flood (e.g., drag forces). If 

either of the above conditions is not met, flooding protection for affected safety-related SSCs 
3-9 

should be considered and described. If flooding protection is needed for safety-related SSCs, 

the rate of rise of the flood waters also should be determined to establish available lead times. 

3.6 Seiche 

A seiche is defined as an oscillation of the water surface in an enclosed or semi-enclosed body 

of water initiated by an external cause (Wüest and Farmer 2003; Scheffner 2008). Once 

started, the oscillation may continue for several cycles; however, over time it gradually decays 

because of friction. 

The period of oscillation of seiches can vary from a few minutes in bays to more than 10 hours 

in the Great Lakes; resonance may occur in Great Lakes for periods between 2 to 10 hours 

(Scheffner 2008). 

In the HHA framework, the first step is to determine whether a seiche in a nearby lake or 

reservoir can potentially lead to flooding at the site. A method for determining if a seiche can be 

initiated by an external meteorological or seismic forcing for basins of simple geometry is 

described in Appendix F. However, significant errors may be introduced when determining 

fundamental oscillation periods if a complex basin geometry and bathymetry is represented by 

an idealized rectangular basin of constant depth. 

For lakes and bays that have irregular geometries and variable bathymetries, numerical, longwave hydrodynamic modeling may be the only viable solution. If the margin between the site 

grade and the normal water level in an adjacent waterbody subject to seiches is small, 

numerical modeling may need to be used to assess the flooding hazard from severe seiches. 

Scheffner (2008) describes model selection criteria and references to an example. Another 

example is described by Stevens and Lawrence (1997). 

If a seiche is determined to be the design basis, each safety-related SSC that may be exposed 

to the static and dynamic effects of the flood should have openings and doors located above the 

highest water-surface elevation attained during this event. In addition, the safety-related SSCs 

should be able to withstand the dynamic effects of the flood (e.g., drag forces). If either of the 

above conditions is not met, flooding protection for affected safety-related SSCs should be 

considered and described. If flooding protection is needed for safety-related SSCs, the rate of 

rise of the flood waters also should be determined to establish available lead times. 

3.7 Ice-Induced Flooding 

Ice jams and ice dams can form in rivers and streams adjacent to a site and may lead to 

flooding by two mechanisms: (1) collapse of an ice jam or a dam upstream of the site can result 

in a dam breach-like flood wave that may propagate to the site and (2) an ice jam or a dam 

downstream of a site may impound water upstream of itself, thus causing a flood via backwater 

effects. 

While it is possible to assess whether a site may possess hydroclimatic conditions that are 

precursors to ice-jam or ice-dam formation (see Appendix G), it is not possible to predict the 

exact location and severity (e.g., the width, height, and volume) of the ice blockage accurately. 

Therefore, it is not possible, at this time, to predict a probable maximum ice jam or dam 

accurately. Alternatively, it is recommended that historical records of ice jams and dams be 

searched to determine the most severe historical event in the vicinity of the site. 
3-10 

In the HHA framework, it may be possible to determine whether a flood caused by another 

flood-causing mechanism at or near the site may exceed that resulting from an ice event. If 

such an alternative and bounding flood is found, no further analysis for the ice-induced flood is 

necessary. If such a bounding flood is not found for the site, methods described in Appendix G 

should be used to estimate the flood water elevation and other associated hazards for the most 

severe historical ice jam or ice dam event. Because this event is not a probable maximum 

event, but merely the most severe historically observed event, care should be exercised in 

specifying a significant margin between the estimated maximum flood water-surface elevation 

and the site grade. 

If an ice event is determined to be the design basis, each safety-related SSC that may be 

exposed to the static and dynamic effects of the flood should have openings and doors located 

above the highest water-surface elevation attained during the event. In addition, the safetyrelated SSC should be able to withstand the dynamic effects of the flood (e.g., drag forces). If 

either of the above conditions is not met, flooding protection for affected safety-related SSCs 

should be considered and described. If flooding protection is needed for safety-related SSCs, 

the rate of rise of the flood waters also should be determined to establish available lead times. 

3.8 Flooding Resulting from Channel Migration or Diversion 

Natural channels may migrate or divert either away from or toward the site. The relevant event 

for flooding is diversion of water towards the site. There are no well-established predictive 

models for channel diversions. Therefore, it is not possible to postulate a probable maximum 

channel diversion event. Instead, historical records and hydrogeomorphological data should be 

used to determine whether an adjacent channel, stream, or river has exhibited the tendency to 

meander towards the site. 

Relevant data sources for this investigation include channel form, historical topographic maps, 

soil types, geologic characteristics, and other morphological parameters. Because most 

channel diversion occurs during high flows when the stream or river overflows its banks, flood 

data, particularly stage, may also prove useful in the determination. 

Generally, stream channels that are steeply incised, have limited floodplains, and are located in 

geologic formations relatively resistant to erosion would not be expected to be susceptible to 

channel diversion. If a site is indeed subject to such an event, the site generally should be 

determined to be unsuitable for a nuclear power plant. 

Man-made channels, canals, diversions, and levees used for conveyance of water and flood 

protection may also be located near the site. During extreme floods, these facilities can fail and 

result in diversion of water towards the site. Therefore, all water-conveyance and water-storage 

facilities near the site should be carefully evaluated to ensure their effects are accounted for in 

determination of the design-basis flood at the site. 

3.9 Combined-Effects Flood 

The ANS states that a single flood-causing event is inadequate as a design basis for power 

reactors (ANS 1992). Dependent events can occur concurrently (e.g., precipitation, snowpack, 

and wind waves; high tides, and storm surges). Currently, the design-basis flood at a nuclear 

power plant site is estimated from deterministic approaches that use the notion of a probable 

maximum event. Despite the term “probable,” probable maximum events are thought to 

approach the physical limits of the phenomena, are deterministic in nature, and are thought to 
3-11 

exceed all historical occurrences of the phenomena. There are no consistent, well-established 

methods for estimating the probability-of-exceedance of probable maximum events. 

Because of their extreme nature, probable maximum events from two separate phenomena 

should not be combined unless they are clearly dependent or result from a common cause. For 

example, seismic events should not be combined with precipitation events. An exception 

occurs for PMF and PMH for relatively small drainage basins in regions where the PMP may 

result from a hypothetical and maximized hurricane event. Wind waves are almost always 

combined with other flood-causing mechanisms. Details of the combinations are provided in 

Appendix H. 

The combination that results in the most severe flood hazard to the safety-related SSCs is used 

to specify the design basis. It is worth noting here that different flood hazards may occur from 

different combinations. For example, the maximum water-surface elevation, and consequently 

the maximum hydrostatic force, may result from a PMF combined with wind waves, but the 

maximum hydrodynamic force may result from fast-moving waters of a PMT. Therefore, designbasis events should be chosen for each case to establish sufficient safety margins for each of 

the most severe loadings possible. 

Because events can occur in combination, a formal probabilistic flood hazard assessment 

approach can provide a more consistent treatment of combination of events that are consistent 

with local and regional hydrometeorological characteristics. An extended discussion of this 

subject is not the focus of this report. 

4-1 

4 APPROACHES 

This chapter describes the two analytical approaches used in standard engineering practice for 

estimating design-basis floods: deterministic analysis and probabilistic analysis. The emphasis 

is placed on methods used to estimate design-basis floods at nuclear power plant sites, but the 

conceptual bases for these models are generally applicable for other purposes also. 

Because the safety-related SSCs of a nuclear power plant may be exposed to a range of floodrelated hazards, the term “design-basis flood” should more accurately be thought of as a set of 

“design-basis flood hazards.” Some of these hazards include hydrostatic and hydrodynamic 

forces, erosion and deposition potential, and impacts from debris carried by a flood. It also is 

important to note that individual, worst-case flood hazards may result from different flooding 

mechanisms. Therefore, it may not be appropriate to focus on a single “design-basis flood;” 

rather, the design should consider the worst-case hazards resulting from all appropriate 

combined-effects floods that are relevant for a site and the nuclear power plant SSCs. 

The deterministic approach, currently used for nuclear power plant sites in the United States, is 

based on the premise that floods can be estimated from a set of empirical or physical prediction 

relationships. Often, a combination of empirical and physical relationships also may be used in 

a flood-prediction model. Usually, deterministic approaches try to predict the flood hazards for a 

hypothetical worst-case hydrometeorological event. For example, predicting the PMF in stream 

and rivers uses the PMP as input along with hydrological conditions in the affected drainage 

area aim to maximize runoff from the PMP. The hazards caused by the PMF and those caused 

by other flood-causing mechanisms would then be used as the set of hazards from which the 

design bases should be selected. 

As its name indicates, the second approach uses probabilistic techniques to estimate the flood 

hazards corresponding to a specified probability-of-exceedance. The probabilistic techniques 

are based on an assumption that extreme floods follow a probability distribution whose 

parameters can be estimated within a certain degree of confidence from past observations. The 

estimated probability distribution of the extreme flood then may be used to derive the probability 

distribution of the individual hazards caused by extreme floods. The probability distributions of 

the individual hazards may then be used to select a design basis corresponding to a selected 

probability-of-exceedance. Because historical data for extreme events are limited by the extent 

of the observed record, probabilistic techniques may be subject to significant uncertainty in the 

estimated hazard magnitudes. 

4.1 Deterministic Analyses 

Deterministic analyses to predict floods often use empirical and physical prediction relationships 

implemented into flood simulation models. The predictions are “deterministic” in the sense that 

given a particular set of inputs, the prediction is always the same and uncertainty in inputs and 

model parameters are generally not considered explicitly. Consequently, to gain confidence in 

model predictions for estimating design-basis flood hazards, the parameters of the model may 

need to be calibrated using data on large historical floods and then validated on comparatively 

large flood events not used in the calibration. 

The simplest of the deterministic flood prediction models is the rational method, which is based 

on the following formula: 

ܳ௧ ൌܥ·݅௧ · ܣ) 1 (
4-2 

where Qt is the flood discharge at the outlet (dimension of [L3

T-1]) at time t, it is the precipitation 

intensity (dimension of [LT-1]), and A is the contributing drainage area (dimension of [L2

]). The 

term C is the dimensionless runoff coefficient that embeds the effects of precipitation losses, 

runoff generation, and watershed transformation processes within itself. Notice that it and Qt are 

time series (i.e., precipitation hyetograph and discharge hydrograph, respectively). It is worth 

noting here that the rational method assumes that the precipitation is spatially uniform over the 

drainage area A, and the precipitation excess (precipitation minus losses) is instantaneously 

transformed into runoff. The rational method may be used for small, urban, or mostly 

impervious drainage areas to estimate the flood discharge conservatively. 

More complicated deterministic hydrologic models can be thought of as variations of the rational 

method where the effects of hydrological processes are conceptualized in more detailed submodels. For example, if the drainage area is large enough that spatial uniformity of precipitation 

is not a valid assumption, the drainage area may be subdivided into several subbasins that are 

small enough to justify the assumption of uniformity of rainfall within themselves. This approach 

essentially leads to “spatially distributed” hydrological models where inputs (e.g., precipitation 

and air temperature) and model parameters (e.g., runoff coefficient) vary among the subbasins. 

If the drainage area were divided into n subbasins with each having its own precipitation input 

and runoff coefficients, the rational method may be implemented using the following formula: 

ܳ௧ ൌ ∑ ܳ௧௝ ௡

௝ୀଵ ௝ ൌ ∑ ൫ܥ · ௝݅௧௝ · ܣ௝൯ ௡

௝ୀଵ (2) 

where the subscript j refers to the jth subbasin and ܣ ൌ ∑ ܣ௡ ௝

௝ୀଵ is the total drainage area ([L2

]). 

The model now needs estimates of precipitation and runoff coefficients for each subbasin. 

However, precipitation excess is still transformed instantaneously into runoff regardless of the 

distance between a particular subbasin and the outlet. The variation in the travel time for each 

subbasin’s runoff to reach the outlet also can be accounted for by staggering the runoff 

generated from each subbasin in time; in effect accounting for channel routing. Accounting for 

these individual complexities in the runoff generation and delivery processes quickly becomes 

so complicated that closed-form expressions of the discharge at the outlet, such as those 

described above, are not possible. Therefore, more complicated hydrologic models are 

assembled from modular mathematical and numerical representations of hydrological process 

descriptions. However, deterministic models assume that inputs are perfectly known and 

contain no measurement errors, the model parameters (e.g., the runoff coefficient) can be 

measured perfectly or estimated, and the process representations do not change with scale, 

either in space or in time. 

Deterministic models, depending on their complexity, require data to estimate parameters 

accurately. Therefore, these models should be used carefully to ensure consistency with 

available site-specific data. 

The rational method and its variations described above are typically referred to as empirical 

models, which are derived from observations that the rate of discharge at the outlet of the 

drainage basin may be approximately proportional to the rate of rainfall. Another class of 

deterministic models also exists. These models, called physically-based process models, 

describe the physics of the hydrological processes and assemble these descriptions into the 

model. Typically, hydrological processes are described mathematically on a small spatial scale, 

and model parameters may be estimated based on experiments at the laboratory scale or the 

field scale. Hydrological processes commonly included in such models include partitioning of 

precipitation into rain or snow, interception of precipitation by vegetation canopy, snow 

accumulation and melt on the surface, infiltration of snowmelt or through-fall (i.e., rainfall that is 

not intercepted by the vegetative canopy) into the soil, evapotranspiration, surface runoff 
4-3 

generation, recharge of deep soil layers and base-flow generation, and channel routing to the 

outlet of the basin. An example of such a model is the Distributed Hydrology Soil-Vegetation 

Model (Wigmosta et al. 1994, 2002; Doten et al. 2006). However, these models are used 

mostly for research purposes and require an extensive amount of site-specific data. 

Simpler process models that strike a balance between the extreme simplicity of the rational 

method and the relative complexity of the physically-based process models have been widely 

used also. These models are called lumped-parameter models. The process descriptions are 

developed and implemented on a subbasin scale, and variations in model parameters among 

subbasins are allowed. Typical components of these models include accounting for 

precipitation losses, a transformation function (to estimate the runoff response from the 

subbasin for a given precipitation excess), a description of channel-network connectivity, effects 

of possible dams or other water-control structures, and channel routing. The most widely used 

lumped-parameter model is the USACE Hydrologic Engineering Center Hydrologic Modeling 

System (HEC-HMS) (USACE 2008b; 2009b). More details of the HEC-HMS model and its 

application to estimating design-basis flood hazards are given in Appendix C. 

The hydrologic models described above assist in estimating the discharge hydrographs at 

points of interest. The hazards from flooding also require development of estimates of the 

hydraulic properties of the design-basis flood discharge (e.g., the water-surface elevation in the 

river, velocity of the flow in the river near the site, hydrodynamic forces, etc.). To estimate these 

properties, hydraulic models that describe the dynamics of discharge in the river or stream need 

to be used. Hydraulic models are usually implemented to solve simplified forms of the 

governing equations for gradually varied, unsteady flow in open channels (Chow 1959). The 

most widely used of these models is the USACE HEC-RAS (USACE 2008a; 2009c). More 

details of the HEC-RAS model and its application to estimating design-basis flood hazards are 

given in Appendix D. Depending on the particular configuration of the stream reaches being 

modeled, hydraulic models require geometry and hydraulic data, including channel cross 

sections, channel roughness data, and reservoir stage-storage-discharge data. 

4.2 Probabilistic Analyses 

Probabilistic models for estimating design-basis floods are generally based on approaches that 

characterize the extreme flood as a random event, describe the properties of this random 

phenomenon using probability distributions, and use these probability distributions to estimate 

extreme floods corresponding to a specified probability-of-exceedance (Stedinger et al. 1993). 

The two key components of the probabilistic models are (1) the historical flood data and (2) the 

probability distribution used to describe the historical flood data. Typically, the historical record 

of annual maximum instantaneous peak discharge at the site of interest, usually measured by a 

United States Geological Survey (USGS) streamflow gauge, is used to estimate the probability 

distribution of extreme floods. Because the random variable of interest—the peak discharge—is 

represented as a continuous variable, a continuous probability distribution is appropriate. 

Probability distributions may be represented by a closed-form, parametric probability density 

function (PDF) or by a data-centric, nonparametric PDF. Parametric PDFs use a functional form 

or an equation to represent the shape of the distribution. For example, the normal distribution is 

represented by the following PDF (Haan 1977): 

݂ሺݔሻ ൌ ଵ

ఙ √ଶగ

 ݁ି ሺೣషഋሻమ

మ ഑మ (3) 
4-4 

where x is the random variable, μ is the mean, and σ is the standard deviation of the random 

variable. Because the parameters μ and σ control the location and the shape of the normal 

distribution, respectively, they are also referred to as the location and scale parameters of the 

distribution. 

A continuous PDF must satisfy two conditions: (1) the integral of the PDF over all possible 

values of the random variable must equal 1, and (2) its value corresponding to all values of the 

random variable must be non-negative. 

A nonparametric PDF cannot be expressed in a function form such as that shown above. 

Usually, nonparametric PDFs are constructed by placing a kernel at each observation of the 

random variable (Adamowski 1985; Lall et al. 1993). The main advantages of using 

nonparametric PDFs are (1) consistency with data, (2) robustness with respect to outliers, and 

(3) flexibility in shape, especially multi-modality. At this time, nonparametric methods are not 

applied frequently in standard engineering practice. Although the data-centric nature of the 

nonparametric methods makes them an attractive alternative, a specific disadvantage is their 

limited ability to extrapolate beyond observed data (Lall et al. 1993). The extrapolation problem 

is severe if the chosen kernel used to estimate the PDF is truncated (i.e., has non-zero densities 

only for a limited range of values of the random variable). For this reason, applications of 

nonparametric PDFs reported in the flood-frequency literature use kernels that have unlimited 

support (e.g., the normal, the Cauchy, and the extreme value type I distributions [Lall et al. 

1993]). 

Bulletin 17B of the Hydrology Subcommittee of the Interagency Advisory Committee on Water 

Data (IACWD) describes a method for estimating probability distributions for annual peak 

discharges in the United States (IACWD 1982). The method is based on fitting a parametric 

PDF, the log Pearson type-III PDF, to the annual maximum instantaneous peak discharge. The 

method was developed assuming stationarity (i.e., the assumption that relationships existing 

among variables at present will stay the same) and, therefore, does not account for trends, such 

as those resulting from climate variability and change. The method also assumes that input 

data are homogeneous; therefore, IACWD (1982) recommends careful examination of data to 

identify watersheds where changes may have occurred (e.g., urbanization or construction of 

dams, levees, and diversions) or to identify whether the annual peak discharge may be 

produced by multiple mechanisms (e.g., by rainstorms, snowmelt, or a combination of the two). 

The procedure recommended by IACWD (1982) consists of the following steps: 

1. Perform logarithmic transformation of annual peak discharge data. 

2. Estimate sample mean, standard deviation, and coefficient of skew from transformed 

data. 

3. Identify high and low outliers (if outliers are found, they should be removed and the 

statistics in Step 2 should be recomputed) and compute the weighted coefficient of 

skew. 

4. Compute the coordinates of the frequency curve corresponding to selected probabilitiesof-exceedance. 

5. Compute the confidence limits for the frequency curve. 

IACWD (1982) also describes adjustments for data where some annual peak discharges may be 

zero (this condition is expected in arid drainage basins that may have no flow during certain years). 

The USGS has developed a computer program, PeakFQ, that implements the methods described in 

Bulletin 17B (Flynn et al. 2006). The IACWD (1982) method is currently used in engineering 

practice. 
4-5 

The log Pearson type-III probability distribution fit to the observed annual peak-discharge data can 

be used to estimate the flood discharge for the selected probability-of-exceedance that the design 

basis would be based on. However, the method yields only a single discharge and the associated 

confidence band on that discharge, and not a time series. A deterministic hydraulic model may need 

to be used to estimate the hazards from this discharge. For example, the HEC-RAS program could 

be set up for the stream reach near a proposed site to estimate the hydraulic properties of a steadystate discharge equal to that obtained from the above procedure. In fact, such a procedure often is 

used not only for the estimated flood discharge but also for the range of annual peak discharges to 

create distributions of the hazards resulting from those flood discharges. Essentially, the 

deterministic hydraulic model acts as a “transformation function” that converts the distribution of the 

flood discharge into the distributions of the associated hazards. However, careful application of this 

approach is required because the deterministic hydraulic model itself may contain uncertainties (e.g., 

the parameters of the model may not be known perfectly). Therefore, the uncertainties in the 

estimated design-basis flood discharge would be compounded by uncertainties in the 

“transformation function,” and the confidence band on the design-basis flood hazard may be larger 

than that on the design-basis flood discharge. Some of these issues are described in Chapter 5. 

Relatively short observation history of streamflow complicates the accurate determination of 

frequency distribution of extreme floods. To augment recorded history of streamflow, paleo-flood 

data can be used in frequency estimation of extreme floods (England et al. 2003; Swain et al. 2004; 

Griffis and Stedinger 2007). Uncertainty in the estimates of the paleo-flood discharges as well as 

dating of these events complicates the analysis (O’Connell et al. 2002; England et al. 2003). 

Because paleo-flood events may have occurred in the distant past, the assumption of stationarity 

typically used in frequency analysis, also needs to be carefully evaluated. Indeed, some of the 

paleo-events may have occurred under different climate conditions or when the 

hydrogeomorphology of the drainage basin was significantly different from present-day conditions. 

These factors may require non-stationary statistical models to account for changing conditions that 

influence extreme floods (O’Connell et al. 2002). In the context of the determination of design-basis 

floods at nuclear power plant sites, the operational life of the plant should be considered, which may 

include recent past, present, and near future time periods. Use of paleo-flood data should be 

carefully evaluated to ensure that use of these data is consistent with estimation of design-basis 

flood at the site. 

Monte-Carlo techniques can also be used to estimate the frequency distribution of extreme floods 

(Schaefer and Barker 2002; USACE 2005). These techniques were also recommended by the 

National Research Council (1988). The idea behind these techniques is to use a hydrologic 

simulation model for transforming a range of hydrometeorological inputs sampled from their joint 

distributions to predict corresponding peak discharges. The predicted peak discharges can then be 

used to derive the frequency distribution of extreme floods. One of the advantages of these 

methods is that uncertainty in inputs, model parameters, and antecedent conditions can be explicitly 

considered. 

The design-basis flood at the site can be selected from the frequency distribution of extreme floods. 

The selection criteria can be based on selecting a probability-of-exceedance of the flood hazard or

on the risk to which the safety-related SSCs may be exposed. The latter approach is recommended 

by the NRC (2007a). Although probabilistic risk assessment for external flooding has been carried 

out at several nuclear power plant sites, detailed methodology and guidance are currently not 

available (ASME 2009). These topics are not discussed further in this report, but are recommended 

for future research, evaluation, and adoption by the NRC. 

5-1 

5 DESIGN-BASIS FLOOD HAZARD ESTIMATION METHODS 

This chapter describes a systematic approach to estimation of a design-basis flood at a nuclear 

power plant site. We describe the process of developing alternative conceptualizations of the 

hydrology in the vicinity of the site that results in a set of alternative conceptual models, 

described below, for each of the relevant flooding mechanisms. The safety of the SSCs from 

floods caused by the relevant flooding mechanisms should be demonstrated using the HHA 

approach described in Chapter 2 of this report. The NRC has established quality assurance 

criteria for nuclear power plants in Appendix B of 10 CFR Part 50. Any numerical simulation 

models that may be used for determination of the design-basis flood hazards are covered under 

these criteria. 

This chapter also describes uncertainties in inputs and model parameters that may affect the 

estimation of design-basis flood hazards. The effects of climate variability, especially those 

related to long-term change predictions, are described. We present some approaches to 

account for these effects in estimation of flood hazards at the time of permitting and licensing. 

5.1 Alternative Conceptual Models 

Before using a simulation model to estimate flood hazards at a site, it is very useful to develop 

alternative conceptualizations for each of the flooding mechanisms. These conceptualizations 

result in a set of alternative descriptions that cover the gamut of possible ways in which a flood 

may present hazards to SSCs. It is convenient to illustrate by an example. 

Figure 5-1 shows the location of a hypothetical nuclear power plant site with respect to a creek, 

a river, two bays, and an ocean. For each of the flooding mechanisms listed below, some 

possible ways a flood can present hazards to this site are identified: 

• Local intense precipitation 

– Runoff generated in contributing areas N and E and the powerblock area drained via 

the passive drainage channels around the powerblock area 

• Flooding in rivers and streams 

– PMF in the river flowing west of the site 

– PMF in the creek flowing offsite 

• Dam failures 

– Flooding in the river flowing west of the site caused by a single upstream dam failure 

– Flooding in the river flowing west of the site caused by cascading upstream dam 

failures 
5-2 

Figure 5-1. A Hypothetical Nuclear Power Plant Site Location with Respect to a Creek, 

a River, Two Bays, and an Ocean (map elements are not to scale) 

• Storm surge and seiche 

– Floods caused by PMH-induced storm surges in Bays 1 and 2 

– Seiches in Bays 1 and 2 

• Tsunamis 

– Near- and far-field tsunamis that may propagate toward the two bays and run up to 

the site through the two bays 

– A tsunami-induced bore that may propagate upstream in the river from Bay 1 

• Ice-induced floods 

– Flood from the collapse of an upstream ice dam or ice jam formation in the river 

– Flood from the backwater effects of a downstream ice dam or ice jam formation in 

the river or the creek flowing offsite 

• Channel diversions 

– Flood caused by the river diverting towards the site. 

Note that tsunami-induced hazards are not described in more detail in this report. For details 

related to tsunami analysis and review see the technical memorandum by González et al. 
5-3 

(2007) and the report by Prasad (2009). The remaining scenarios listed above should be 

described in sufficient detail and should include a review of historical flood occurrences and 

other pertinent site-specific data. These descriptions should be used to establish the relative 

importance of each of the flooding mechanisms at the site. For example, if the winters in the 

vicinity of the site are mild such that extensive ice formations for sustained periods do not occur 

and historical ice dam or ice jam formations have not been observed, flooding by ice-induced 

events could be ruled out. The remaining flooding mechanisms and respective plausible flood 

scenarios for each of these mechanisms constitute the set of alternative conceptual models for 

flooding at the site. These alternative conceptual models should then be analyzed further using 

the HHA approach described in Chapter 2. As described in Section 5.3 below, the selection of 

numerical flood-simulation models also depends on the set of plausible, site-specific, alternative 

conceptual models. 

5.2 Quality Assurance Criteria for Simulation Models 

After the selection of alternative conceptual models that may result in the design bases, the 

estimation of hazards is carried out. Frequently, simulation models are needed to estimate the 

flood hazards caused by hypothetical events such as the PMP, PMH, or dam breaches. 

Appendix B of 10 CFR Part 50 requires that the safety-related SSCs of nuclear power plants 

prevent or mitigate the consequences of postulated accidents that could cause undue risk to 

public health and safety. The appendix also describes quality assurance requirements for 

design, manufacture, construction, and operations of these SSCs. Therefore, any floodsimulation models that are used to establish the design bases of safety-related SSCs must 

comply with the requirements of this appendix. 

5.3 Selecting Simulation Models to Use 

Under most circumstances, flood-simulation models developed by Federal agencies such as the 

USACE or academic and research institutions that are currently being used in standard 

engineering practice are adequate for estimation of hazards to safety-related SSCs at a nuclear 

power plant site. These models are used in engineering practice and have a history of 

validation and verification (e.g., USACE 2010). 

However, there could be circumstances under which a customized flood-simulation model may 

be developed to account for site-specific conditions. A complete documentation of the technical 

bases of the customized model should be carried out. The documentation should include the 

following: 

• a description of all components of the model 

• a description of the governing equations 

• a description of the model implementation details including, where appropriate, 

simplifying assumptions, spatial and temporal discretization schemes, interpolation 

methods, solution procedures, timesteps used, and convergence criteria 

• a description of all model parameters 

• input data requirements 

• output details. 
5-4 

The numerical simulation models should be selected to ensure that the hydrodynamic 

conditions that are expected to occur at and near the site are adequately characterized by the 

model. The paragraphs below describe a few plausible scenarios where the site-specific 

hydrodynamic conditions may greatly influence the selection of appropriate simulation models. 

Notice that the plausible scenarios described below should already have been identified during 

the development of alternative conceptual models. 

For example, for a cascading dam-breach event upstream of the site depicted in Figure 5-1 in 

which the river near the site is constrained by levees that are not designed to withstand the 

flood expected during the dam-breach event, it may be postulated that the levees would be 

overtopped by the dam-failure flood and water would flow through a breach in the levee toward 

the site. Under this scenario, a two-dimensional hydrodynamic model may need to be used 

because the flow is not constrained within the river channel anymore. At the same time, the 

flood may carry significant amounts of sediments from the levee material along with the flow. 

The sediment-laden water would have an increased density and therefore would cause 

increased drag forces on structures in its path. A sediment erosion and deposition model may 

need to be used to estimate the sediment concentrations near structures of interest. 

Large floods generated by PMP events or multiple dam failures are also expected to overflow 

the banks of rivers and streams and occupy adjoining overbank and floodplain areas. Typically, 

overbank and floodplain areas contain vegetation and may also contain buildings and other 

structures. Because of the presence of these obstacles to flow, the overbank and floodplain 

areas have greater roughness than the main river channel. Therefore, an appropriate hydraulic 

model should be selected that allows roughness coefficients to vary along a channel crosssection. 

Large floods are expected to generate a significantly greater flow velocity than a normal bankfull 

discharge. Therefore, it is plausible that these floods would result in significantly greater erosion 

of the banks and the channel bottom. The eroded material would be carried along with the flow. 

It is also plausible that the faster velocities of flow in the overbank or floodplain areas would 

result in debris being carried along with the flow. When the flow carrying the sediment and 

debris enters a downstream reservoir impounded by a dam, flow velocities would reduce and 

the sediment and debris may settle in the reservoir. Depending on the size of the downstream 

reservoir, the sedimentation may result in changes in the reservoir’s storage capacity and its 

stage-discharge characteristics. The model should account for these changes to simulate the 

flood dynamics downstream of the reservoir accurately. 

In several regions of the United States, snowfall occurs during the winter and results in a 

snowpack at the beginning of spring. Rain-on-snow events have resulted in large floods in the 

past (Kattelmann et al. 1991; Kroczynski 2004; McCabe et al. 2007). Even a moderately severe 

rainfall event on an existing snowpack that is ready to start melting may cause severe flooding. 

The ANS (1992) recommends investigation of combined events consisting of a 100-year snowseason rainfall event on a probable maximum snowpack and a snow-season PMP on a 

100-year snowpack as alternative scenarios for precipitation-caused flooding. A snowmelt 

model may be necessary to simulate the runoff. The USACE HEC-HMS contains snowmelt 

functionality and should be used to simulate rain-on-snow floods. The soils may be frozen 

during a rain-on-snow event, and therefore should be assumed to allow no infiltration. 
5-5 

5.4 Accounting for Uncertainty in Input and Model Parameters for 

Estimation of Design-Basis Flood Hazards 

To estimate hazards caused by precipitation-generated floods at a site, usually two simulation 

models are needed. The first model is usually called a hydrologic model that requires 

hydrometeorological input and specification of a set of hydrologic model parameters that control 

the rainfall-runoff processes. The hydrologic model predicts the time history of discharges, 

called hydrographs, at several points of interest within the drainage basin upstream of the site. 

The second model, usually called a hydraulic model, requires a set of hydraulic model 

parameters and the hydrographs simulated by the hydrologic model as input. The hydraulic 

model predicts dynamic properties of the flood discharge such as velocity and depth. 

Generally, the values of inputs to and parameters of flood simulation models contain 

uncertainty. The uncertainty in hydrometeorological inputs exists because they can only be 

measured with some degree of inherent error. Identification of model parameters is uncertain 

because it is based on imperfectly measured input and predicted variables. The model 

parameters also contain uncertainty because of simplification of the true, complete, and 

frequently unknown, governing equations, which results in the model being only an 

approximation of reality. Therefore, predictions from flood-simulation models also contain 

uncertainty. 

Rainfall loss rates and rainfall-to-runoff transformation functions are the other two commonly 

used components in the hydrologic model. Loss rates specify the infiltration into soil. Because 

generally the hydrologic models used in standard engineering practice do not implement 

detailed characterization of groundwater flow into streams, the infiltrated water does not 

contribute to runoff generation. Therefore, specification of a non-zero loss rate reduces runoff 

generated from the PMP. 

Rainfall-to-runoff transformation functions have been represented by unit hydrographs 

(Sherman 1932) in surface-water hydrology for quite some time. Unit hydrographs can be 

derived from observed rainfall and corresponding measured streamflow (Chow et al. 1988). 

The main characteristics of a unit hydrograph are as follows: 

• a runoff volume equivalent to a unit depth over the drainage area 

• a duration over which the rainfall excess occurs 

• a constant time-to-peak and a constant time base. 

The unit hydrograph approach assumes that the rainfall-runoff response of a drainage area is 

linear; i.e., the direct runoff hydrograph form a rainfall excess of a given amount can simply be 

obtained by multiplying the unit hydrograph ordinates by the rainfall excess. However, recent 

research indicates that the characteristics of unit hydrographs, including time-to-peak and the 

time base, may depend on rainfall intensity. Some of these issues are discussed in Appendix I. 

To estimate unit hydrographs in ungauged drainage basins, several approaches have been 

developed (Chow et al. 1988). These approaches are based on observed data and 

generalizations that are assumed to be valid in other drainage basins. Therefore, the rainfallrunoff transformation function itself behaves as a model parameter that contains some 

uncertainty. In practice, unit hydrographs should be derived from rainfall and runoff measured 

in the drainage basin where the site is located. Also, because the characteristics of unit 

hydrographs depend on rainfall intensity, only large storms that generate extreme floods should 

be used in derivation of a unit hydrograph that would be used to estimate the PMF. Past 

studies (Pilgrim and Cordery, 1993; USACE 1994) have indicated that unit hydrographs 
5-6 

estimated for smaller storms should be adjusted to account for conditions that would be 

expected to occur during a PMP. These adjustments are also described in Appendix I. 

The estimate of dynamic properties of the flood discharge using a hydraulic model (e.g., USACE 

HEC-RAS) depends on several model parameters, principally the roughness coefficient. For a 

given discharge, increased roughness of the channel impedes the flow and therefore results in 

slower flow velocity compared to a smoother channel of otherwise identical properties 

(e.g., slope and cross-section). Therefore, the flow of some discharge is conveyed at a larger 

depth and slower velocity in a rougher channel compared to that in a smoother channel. The 

hydrostatic and hydrodynamic loadings on SSCs depend on the depth of flow and the velocity of 

flow, respectively. It follows then, that the hydrostatic loading is maximized by increasing 

depths of flow, which may result from increased roughness of the channel, and the 

hydrodynamic loading is maximized by reducing the roughness. Also, the duration of inundation 

may be greater for slower flow and therefore would result in a longer time of exposure to the 

flood hazards. Therefore, in estimation of design-basis loadings from floods, the roughness 

coefficient should be selected carefully to account for the tradeoffs described above. 

Design-basis flood analysis should carefully describe and quantify the sources of uncertainty by 

appropriately selected sensitivity analyses. The design-basis flood hazards should then be 

selected carefully from the predicted range of values of these hazard metrics (e.g., depth of 

flow, density of flow, velocity of flow, and duration of inundation) to ensure that the most adverse 

conditions are accounted for. 

5.5 Validation 

The accuracy of the model should be validated using site-specific data. Because the floods 

used to estimate the design bases are usually hypothetical and extreme, care should be 

exercised to ensure that the validation process accounts for the extreme severity of the 

recommended hydrometeorological events and conditions. The validation details should include 

the following: 

• a description of the validation approach 

• all validation datasets used including site-specific data 

• a demonstration that the validation of the simulation model includes floods approaching 

the severity of those resulting from recommended hydrometeorological events and 

conditions. 

It is extremely important that the validation of the simulation models and associated parameters 

use the largest reported historical floods near the site. The ability of the models to reproduce 

historical floods provides some assurance that the estimated design-basis floods near the site 

would not be underestimated. 

5.6 Reconciling Deterministic and Probabilistic Notions in the 

Context of Design-Basis Flood Estimation 

The primary focus of this report is to describe deterministic approaches for the estimation of 

design-basis flood events. The cause of the flood is assumed to be a worst-case event that 

cannot be exceeded in terms of severity; however, at the same time, the PMF is defined to be 

the most severe, reasonably possible flood at a site and the PMH is defined as the most severe 

hurricane that can reasonably occur in a region. There is some ambiguity in these definitions 

that introduces subjectivity in the selection of these events. Additional subjectivity is also 
5-7 

introduced in the estimation of design-basis floods during selection of model parameters and 

antecedent conditions. Several studies have criticized the “probable maximum” concept, 

especially that of the PMP (Benson 1973; Kite 1988; Dingman 1994). 

The SSCs exposed to flood hazards should be designed to prevent plant flooding risk beyond 

the Commission safety goals. The estimation of a deterministic design-basis flood does not 

specify its probability-of-exceedance. In general terms, “probable maximum” events are thought 

to have “virtually no risk of exceedance” (ANS 1992) and combining the effects of coincident 

events provides an additional margin of safety. Some efforts have focused on the estimation of 

the probability-of-exceedance of “probable maximum” events (Hershfield 1961, 1965; 

Newton 1983; Nobilis et al. 1991; Koutsoyiannis 1999; Papalexiou and Koutsoyiannis 2006). 

The Hershfield (1961, 1965) method is a statistical approach and is adopted by the World 

Meteorological Organization (WMO 1986). The ANS (1992) recommended that an average 

annual probability-of-exceedance less than 10-6 is an acceptable goal for selection of flood 

design bases. 

Chery and Wescott (1985) summarized the studies of Hershfield (1961) and Newton (1983) in a 

report to the Advisory Committee on Reactor Safeguards (ACRS) subcommittees on Reactor 

Radiological Effects and Extreme External Phenomena. They concluded that the mean 

probability of occurrence of a PMF is less than 10-5. They were not able to determine the 

confidence limits on the mean probability of occurrence of the PMF. 

Nobilis et al. (1991) used annual maximum daily precipitation from 504 stations in Austria to 

estimate the PMP using the method of Hershfield (1961, 1965), but obtained estimates of PMP 

that were smaller than observed extreme precipitation. Nobilis et al. (1991) concluded that the 

estimated PMP values were based on the Hershfield frequency factor estimated from average 

of mean extreme precipitation values and therefore did not adequately represent “outliers.” 

Koutsoyiannis (1999) presented a reanalysis of Hershfield’s data. He determined that there was 

no upper limit to Hershfield’s frequency factor, which is the basis for estimating the PMP (WMO 

1986). Therefore, Koutsoyiannis (1999) concluded that there is no upper limit to the amount of 

precipitation. He proposed to use a statistical analysis of all frequency factors representing 

annual maximum rainfalls at different stations rather than the analysis of only the frequency 

factor corresponding to the maximum observed rainfall at a station. Based on this modified 

analysis that used the generalized extreme value distribution, Koutsoyiannis (1999) was able to 

estimate that the Hershfield frequency factor of 15, used for estimating the PMP, corresponds to 

a return period of approximately 60,000 years. He recommended that the concept of PMP 

should be substituted with the determination of a design rainfall estimated for a selected 

probability-of-exceedance. 

Papalexiou and Koutsoyiannis (2006) concluded that an upper bound to dew point, an 

assumption also used in the deterministic storm maximization and transposition approaches to 

the estimation of the PMP, does not exist. 

Fontaine and Potter (1989) described stochastic storm transposition, a generalization to the 

transposition method used to estimate PMP. The generalization was based on the assumption 

that a storm of a given magnitude occurring at a given location within a meteorologically 

homogeneous region could occur anywhere else within the region with the same probability with 

appropriate adjustments to its characteristics. The assumption effectively provides a regional 

and larger set of extreme storms from which frequency distribution of extreme storms for a 

location of interest could be estimated. Wilson and Foufoula-Georgiou (1990) applied a similar 

method to the midwestern United States, but noted a need for further research. 
5-8 

Douglas and Barros (2003) used a multifractal approach to estimate fractal maximum 

precipitation in the eastern United States. They describe the behavior of rainfall as a 

multiscaling cascade in which progressively higher intensity cells are embedded as the spatial 

scale decreases from synoptic to mesoscale to local. They estimated the 3-day fractal 

maximum and the 3-day 10-6 exceedance-probability design PMP using 327 daily and 

1400 monthly time series data spanning from 1950 to 1997. Their estimates of the 3-day fractal 

maximum precipitation were consistently lower at 5 of the 7 locations, typically 50 to 70 percent 

of the 3-day PMP estimated using HMR 51 and 52. On the other hand, their estimates of the 

3-day 10-6 exceedance-probability design PMP were consistently higher at 5 of the 7 locations, 

ranging from 122 to 200 percent of the 3-day PMP estimated using HMR 51 and 52. Douglas 

and Barros (2003) concluded that because the 3-day 10-6 exceedance-probability design PMP 

generally exceeds the HMR 51 and 52 estimates, it can be viewed as an upper bound of known 

risk. 

The National Research Council (1988) study on estimation of probabilities of extreme floods 

also recommended the use of probabilistic methods for estimation of a range of floods and their 

associated probabilities rather than to focus on a single, large flood that was construed to 

represent an upper bound. The study mentioned two probabilistic approaches for determination 

of extreme floods at the site of interest: a statistical analysis of streamflow data and a statistical 

analysis of meteorological data coupled to a numerical model to simulate the physical 

processes involved in runoff generation. The study also recognized that the estimation of 

probability-of-exceedance of extreme floods would require extrapolation beyond the range of 

available observation. The study recommended three principles for improving extreme flood 

estimates: substituting space for time (regionalization), using structured models (spatial and 

inter-parametric dependences), and focusing on extreme value analysis (tails of distributions). 

The National Research Council (1988) recommended several parametric statistical distributions 

including log-Pearson Type III, the generalized extreme value distribution, and Wakeby 

distribution. The study also mentions that nonparametric methods may also be suitable for 

analysis of extreme values. 

The National Research Council (1988) recommended use of runoff simulation models in 

conjunction with the estimated magnitude and frequency of extreme meteorological events 

(such as those described above) to derive the probability-of-exceedance of extremely rare 

floods. The study noted that these models are capable of estimating complete hydrographs that 

can be very useful in design. It also noted that an appropriately chosen runoff model should be 

capable of simulating physical processes that are expected to occur during the very large 

events. The study mentioned that a study of extreme value events requires an explicit 

consideration of uncertainty that arises from sampling uncertainty, measurement errors, and 

modeling assumptions. 

A comprehensive Probabilistic Flood Hazard Assessment (PFHA) methodology has not yet 

been developed. However, discrete components of the PFHA are now available, although the 

overall framework still needs to be developed. This report is not a suitable place to describe 

and develop these concepts. Only a brief mention of the overall approach is made. The 

following discussion is based on a hybrid approach similar to that recommended by the National 

Research Council (1988) where a numerical runoff simulation model is used in conjunction with 

the probabilistic representation of the statistical distribution of extreme meteorological events. 

The PFHA consists of two discrete components: 

1. probability distributions of meteorological input variables (such as precipitation, air 

temperature, relative humidity) of extreme events 
5-9 

2. derivation of probability distribution of flood hazards (such as discharge, flow depth and 

velocity, duration of inundation) using a numerical runoff simulation model or 

combination of models. 

The probabilistic approaches for estimation of extreme value distributions have been in 

existence for some time. Both parametric and nonparametric approaches are now sufficiently 

well understood that they can be applied in practice. Data for estimation of extreme value 

distributions of meteorological variables often approach and exceed 100 years in the 

United States. Based on the recommendations of the National Research Council (1988), it 

should be relatively straightforward to accomplish component 1 above. 

The derivation of probability distribution of flood hazards would require simulation of a large 

number of scenarios consisting of input datasets sampled from the joint probability distribution 

of the meteorological variables. One complicating factor in component 2 above is the need to 

account for uncertainty in model parameters that can also be represented as a joint probability 

distribution. Adaptive techniques for sampling have been developed (Freer et al. 1996; Kuczera 

and Parent 1998; Bates and Campbell 2001; Hossain and Anagnostou 2005) that can be used 

to minimize the number of simulated scenarios while providing adequate sampling of the 

parameter hyperspace. Schaefer and Barker (2002), Swain et al. (2004), and the USACE 

(2005) provide examples of some such implementations. 

An integrated framework that establishes guidelines for bringing together already existing tools 

is needed to fully develop the PFHA approach. Further development of the PFHA approach is 

recommended for future study. 

5.7 Effects of Climate Variability on Design-Basis Flood Estimation 

Future changes in the hydrometeorological characteristics of the drainage basin upstream of a 

site can change precipitation-generated extreme floods at the site. Future changes in land use, 

increasing sedimentation of existing reservoirs, development of additional water and floodcontrol structures, and operational characteristics of existing controls can change the floods 

generated by dam breaches upstream of the site. Future changes in atmospheric, climatic, and 

oceanic conditions can change the characteristics of hurricanes and storm surges near a site. 

Most of the debate related to long-term climate change is based on the argument that the global 

surface temperature is increasing at an accelerated rate over the last few decades (IPCC 

2007a). The Intergovernmental Panel on Climate Change (IPCC) defines climate change as a 

change in the state of the climate that can be identified by detecting changes in the mean and/or 

the variability of its properties that persists for an extended period, typically decades or longer. 

The IPCC’s definition of climate change includes changes because of both natural variability 

and human activity. 

The IPCC (2007a) reported that the linear warming trend in air temperature over 1956 to 2005 is 

1.3 oC—nearly twice that for 1906 to 2005, 0.74 oC. The temperature increase is reported to be 

greater for the higher northern latitudes, average arctic temperatures are reported to have 

increased almost twice of the global average rate, and land surfaces are reported to have 

warmed faster than oceans. 

The IPCC (2007a) reported that global average sea level rose at an average rate of 

approximately 1.8 mm per year from 1961 to 2003, while the rate was approximately 3.1 mm 

per year from 1993 to 2003. The study was not able to clearly conclude whether the increased 

rate of sea level rise over the latter period was because of decadal variability or because of an 
5-10 

increase in long-term trend. The IPCC (2007a) reported that 57 percent of the sea-level rise 

since 1993 is attributable to thermal expansion, 28 percent is attributable to decreases in 

glaciers and ice caps, and the remainder is attributable to losses from polar ice sheets. 

The IPCC (2007a) reported that mountain glaciers and snow cover have declined all over the 

globe; the maximum area of seasonally frozen ground has decreased by approximately 

7 percent in the Northern Hemisphere since 1900. The decrease of seasonally frozen ground is 

greater in spring, approximately 15 percent. The IPCC (2007a) also reported that since 1980, 

the surface temperature of the top of the permafrost has increased by approximately 3 oC. 

The IPCC (2007a) reported that precipitation has significantly increased in eastern 

North America. The study also reported that changes in the frequency of extreme weather 

events over the last five decades indicate that it is very likely that cold days, cold nights, and 

frosts have become less frequent over land areas; it is likely that heat waves have become 

more frequent over land areas; it is likely that the frequency of heavy precipitation events has 

increased; and it is likely that occurrences of extreme high sea levels have increased. The 

IPCC (2007a) also reported that since 1970, intense tropical cyclone activity in the 

North Atlantic has increased. During 1995 to 2004, 13.6 tropical storms, 7.8 hurricanes, and 

3.8 major hurricanes occurred on an average compared to the 1970 to 1994 period, when the 

corresponding numbers were 8.6, 5, and 1.5, respectively (IPCC 2007b). 

The IPCC (2007a) concluded with high confidence that changes in the hydrological systems 

include increased runoff and earlier spring peak discharge in glacier and snow-fed rivers and 

warming of lakes and rivers with associated effects on their thermal structure and water quality. 

With respect to estimation of design-basis floods at nuclear power plant sites, the following 

changes reported by IPCC (2007a) are of importance: 

• increases in surface temperature and precipitation 

• decrease in snow cover and earlier spring peak runoff 

• increase in intense cyclone activity 

• increase in sea level. 

It is not clear how extreme precipitation, such as the PMP, would change under an altered 

climate that is characterized by increased temperature and precipitation. Generally, however, 

increased temperatures may lead to an increase in precipitable water and therefore may 

increase the PMP amount. The changes in temperature and snow cover may also affect the 

way storm systems develop, change the time of year when they occur, and the paths they follow 

to the site. We are not aware of any studies that investigate these factors. Therefore, a 

sensitivity analysis that incorporates temperature and precipitation trends projected by the IPCC 

reports should be carried out to determine whether the site has adequate margins available to 

accommodate anticipated changes in the design-basis flood over the operational life of the 

plant. 

Similarly, long-term increase in cyclonic activity has not been investigated to determine whether 

the PMH characteristics such as central pressure difference, size of the storm, track speed, and 

direction of approach may be affected in the altered climate scenarios. The estimates of PMH 

parameters may be subjected to a sensitivity analysis along with the accounting of projected 

sea-level rise during the operational life of the plant to determine whether the site has adequate 

margins available to accommodate anticipated changes in the design-basis flood. These 

sensitivity studies should be used for informed decision-making regarding selection of design 

bases and the need for protective structures and emergency procedures. 
6-1 

6 FUTURE DIRECTIONS 

The estimation of design-basis floods at nuclear power plant sites is currently based on a set of 

deterministic approaches that specify the “probable maximum” flood precursor event. 

Hydrologic, hydraulic, thermal, and hydrodynamic models are currently used to predict a set of 

extreme candidate floods at the site from which the most severe design-basis flood hazards are 

selected. The guidance for estimation of some of the “probable maximum” flood precursor 

events was developed several decades ago and therefore is based on old and outdated 

datasets. For example, various HMRs were prepared in the 1970s and 1980s (Schreiner and 

Riedel 1978; Hansen et al. 1982) and therefore have not used extreme precipitation data 

recorded since their publication. The current guidance for estimation of PMH was published in 

1979 and has not been updated to include more recent data. 

Future efforts to improve the reliability of the design-basis flood estimate should include the 

following: 

1. Incorporation of more recent site-specific hydrometeorological datasets in the estimation 

of design-basis floods. It should be noted here that an applicant can most reasonably 

use these datasets at its site for validation that the estimated design-basis flood is 

appropriately conservative, identification of site-specific model parameters, and 

demonstration of existence of sufficient margin in site characteristics and selected 

design bases. 

2. Development of probabilistic approaches for estimation of design-basis flood. An outline 

of the PFHA is described in Chapter 5. A probabilistic approach has the inherent 

advantage of clearly articulating the level of risk that a selected design basis would likely 

encounter during the operational life of the plant. A hybrid approach that uses simulation 

models and explicitly accounts for various uncertainties in estimation of extreme floods, 

augmented by probabilistic assessment of the level of risk to which safety-related SSCs 

would be exposed should be developed. 

3. Development of high-resolution hydrometeorological datasets. The recent availability of 

high-resolution data such as terrain and bathymetry data, subbasin delineations, channel 

network and its connectivity, more reliable and dense meteorological data, remotely 

sensed imagery, and spatial datasets representing soil and vegetation has greatly 

improved parameterization of numerical models. Future advances in data collection, 

verification, archiving, and dissemination would increase the reliability of model 

formulation and also increase the opportunities to validate model predictions. Future 

guidance for estimation of design-basis floods should take advantage of these 

improvements in data availability and reliability to demonstrate that public health and 

safety criteria of the NRC’s regulations are clearly met at all sites. 

4. Guidance related to climate variability and global climate change. Recent developments 

in global climate change research has shown that significant effects at global and 

national scales are expected (IPCC 2007a, b). However, the effects of these changes at 

the drainage basin- and site-scale need site-specific analysis. It is also unclear how 

changing climate affects the “probable maximum” events that are used for design-basis 

flood estimation at nuclear power plant sites. The characteristic scales of “probable 

maximum” events vary significantly (local intense precipitation is a site-scale 

phenomenon, PMP and PMF are drainage basin- to regional-scale phenomena, and 

PMH could be affected by changes at intercontinental scales). 

7-1 

7 REFERENCES 

10 CFR Part 50. Code of Federal Regulations, Title 10, Energy, Part 50, “Domestic Licensing of 

Production and Utilization Facilities.” 

10 CFR Part 52. Code of Federal Regulations, Title 10, Energy, Part 52, “Licenses, 

Certifications, and Approvals for Nuclear Power Plants.” 

Adamowski K. 1985. “Nonparametric Kernel Estimation of Flood Frequencies.” Water 

Resources Research 21(11):1585-1590. 

American Nuclear Society (ANS). 1992. American National Standard for Determining Design 

Basis Flooding at Power Reactor Sites. Prepared by the American Nuclear Society Standards 

Committee Working Group ANS-2.8, La Grange Park, Illinois. 

American Society of Mechanical Engineers (ASME). 2009. “Addenda to ASME/ANS RA-S–

2008.” Standard for Level 1/Large Early Release Frequency Probabilistic Risk Assessment for 

Nuclear Power Plant Applications. ASME/ANS RA-Sa–2009, New York. 

Benson M.A. 1973. “Thoughts on the design of design floods.” In the Proceedings of the 

2nd International Symposium in Hydrology, at Fort Collins, Colorado. Water Resources 

Publications, Fort Collins, Colorado. Pp.27-33. 

BOSS International. 1988. “BOSS HMR52 Users Manual.” BOSS International, Inc., 

Madison, Wisconsin. 

Brunner G. and M. Gee. 2009. “Extreme Flood Risk Methods.” In the Proceedings of the 

Association of State Dam Safety Officials Annual Conference. Lexington, Kentucky. 

Bunya S, J. Westerink, J.C. Dietrich, H.J. Westerink, L.G. Westerink, J. Atkinson, B. Ebersole, 

J.M. Smith, D. Resio, D., R. Jensen, M.A. Cialone, R. Luettich, C. Dawson, H.J. Roberts, and 

J. Ratcliff. 2010. “A High Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave and 

Storm Surge Model for Southern Louisiana and Mississippi: Part I–Model Development and 

Validation.” Monthly Weather Review 138:345-377. 

Chow V.T. 1959. Open-Channel Hydraulics. McGraw-Hill Book Company, New York. 

Chow V.T., D.R. Maidment, and L.W. Mays. 1988. Applied Hydrology. McGraw-Hill Book 

Company, New York. 

Clark C.O. 1945. “Storage and the Unit Hydrograph.” Transactions of the American Society of 

Civil Engineers 110:1419-1488. 

Cudworth A.G. Jr. 1989. “Flood Hydrology Manual.” A Water Resources Technical 

Publication, U.S. Department of Interior, Bureau of Reclamation, Denver, Colorado. 

Dingman S. L. 1994. “Physical Hydrology.” 1st edition. Prentice Hall, Inc., Upper Saddle 

River, New Jersey. 

Doten C.O., L.C. Bowling, E.P. Maurer, J.S. Lanini, and D.P. Lettenmaier. 2006. “A spatially 

distributed model for the dynamic prediction of sediment erosion and transport in mountainous 

forested watersheds.” Water Resources Research 42(4) doi: 

W0441710.1029/2004WR003829. 
7-2 

Douglas E.M. and A.P. Barros. 2003. “Probable maximum precipitation estimation using 

multifractals: Application in the eastern United States.” Journal of Hydrometerology 4: 1012-

1024. 

England J.F. Jr., R.D. Jarrett, and J.D. Salas. 2003. “Data-based comparisons of moments 

estimators that use historical and paleoflood data.” Journal of Hydrology 278(1-4):170-194. 

Federal Emergency Management Agency. 2010. “Numerical Models Meeting the Minimum 

Requirement of National Flood Insurance Program.” Available at 

http://www.fema.gov/plan/prevent/fhm/en_coast.shtm. Accessed December 20, 2010. 

Federal Energy Regulatory Commission. 2001. Engineering Guidelines for the Evaluation of 

Hydropower Projects. Chapter 8 – “Determination of the Probable Maximum Flood.” 

Washington, D.C. 

Flynn K.M., W.H. Kirby, and P.R. Hummel. 2006. “Users Manual for Program PeakFQ, Annual 

Flood-Frequency Analysis Using Bulletin 17B Guidelines.” In Chapter 4, Section B of the 

U.S. Geological Survey Techniques and Methods Report Book 4, U.S. Geological Survey, 

Reston, Virginia. 

Fontaine T.A. and K.W. Potter. 1989. “Estimating probabilities of extreme rainfalls.” Journal of 

Hydraulic Engineering 115(11):1562-1575. 

González F.I., E. Bernard, P. Dunbar, E. Geist, B. Jaffe, U. Kânŏglu, J. Locat, H. Mofjeld, A. 

Moore, C. Synolakis, V. Titov, and R. Weiss (Science Review Working Group). 2007. 

“Scientific and technical issues in tsunami hazard assessment of nuclear power plant sites.” 

NOAA Technical Memorandum OAR PMEL-136, Pacific Marine Environmental Laboratory, 

Seattle, Washington. 

Griffis V.W. and J.R. Stedinger. 2007. “Evolution of Flood Frequency Analysis with Bulletin 17.” 

Journal of Hydrologic Engineering 12(3):283-297. 

Gupta V.K., E. Waymire, and C.T. Wang. 1980. “A representation of an instantaneous unit 

hydrograph from geomorphology.” Water Resources Research 16(5):855-862. 

Haan C.T. 1977. Statistical Methods in Hydrology. The Iowa State Press, Ames, Iowa. 

Hansen E.M., L.C. Schreiner, and J.F. Miller. 1982. Application of Probable Maximum 

Precipitation Estimates – United States East of the 105th Meridian. NOAA Hydrometeorological 

Report 52, National Weather Service, Washington, D.C. 

Hershfield D.M. 1961. “Rainfall Frequency Atlas of the United States for Durations from 

30 Minutes to 24 Hours and Return Periods from 1 to 100 Years.” Technical Paper No. 40, 

U.S. Weather Bureau, U.S. Department of Commerce, Washington, D.C. 

Hershfield D.M. 1965. “Method for Estimating Maximum Probable Precipitation.” Journal of 

American Waterworks Association 57:965-972. 

Holland G.J. 1980. “An analytic model of the wind and pressure profiles in hurricanes.” 

Monthly Weather Review108:1212-1218. 
7-3 

Interagency Advisory Committee on Water Data (IACWD). 1982. “Guidelines for determining 

flood flow frequency.” Bulletin 17B of the Hydrology Subcommittee, Office of Water Data 

Coordination, U.S. Geological Survey, Reston, Virginia. 

International Atomic Energy Agency (IAEA). 2003. Flood Hazard for Nuclear Power Plants on 

Coastal and River Sites. IAEA Safety Guide No. NS-G-3.5, Vienna, Austria. 

Intergovernmental Panel on Climate Change (IPCC). 2007a. Climate Change 2007: Synthesis 

Report. Core Writing Team, RK Pachauri and A. Reisinger (eds.), Geneva, Switzerland. 

Intergovernmental Panel on Climate Change (IPCC). 2007b. Climate Change 2007: The 

Physical Science Basis. S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, 

M. Tignor, and H.L. Miller (eds.). Cambridge University Press, Cambridge, United Kingdom and 

New York.. 

Irish J.L., D.T. Resio, and J.J. Ratcliff. 2008. “The influence of storm size on hurricane Surge.” 

Journal of Physical Oceanography 38(11):2003-2013. 

Irish J.L., D.T. Resio, and M.A. Cialone. 2009. “A surge response function approach to coastal 

hazard assessment. Part 2: Quantification of spatial attributes of response functions.” Natural 

Hazards 51(1):183-205. 

Jelesnianski C.P., J. Chen, and W.A. Shaffer. 1992. SLOSH: Sea, Lake, and Overland Surges 

from Hurricanes. NOAA Technical Report NWS 48, National Oceanic and Atmospheric 

Administration National Weather Service, Silver Spring, Maryland. 

Kattelmann R., N. Berg, and B. McGurk. 1991. “A history of rain-on-snow floods in the Sierra 

Nevada.” Proceedings of the Western Snow Conference 59:138-141. 

Kite G.W. 1988. “Frequency and Risk Analysis in Hydrology.” Water Resources Publications, 

Littleton, Colorado. 

Koutsoyiannis D. 1999. “A probabilistic view of Hershfield’s method for estimating probable 

maximum precipitation.” Water Resources Research 35(4):1313-1322. 

Kroczynski S. 2004. “A Comparison of Two Rain-on-Snow events and the Subsequent 

Hydrologic Response in Three Small River Basins in Central Pennsylvania.” Eastern Region 

Technical Attachment 2004-04, National Oceanic and Atmospheric Administration National 

Weather Service Eastern Region Publications, Bohemia, New York. 

Lall U., Y. Moon, and K. Bosworth. 1993. “Kernel Flood Frequency Estimators: Bandwidth 

Selection and Kernel Choice.” Water Resources Research 29(4):1003-1015. 

McCabe, G.J., M.P. Clark, and L.E. Hay. 2007. “Rain-on-snow events in the Western 

United States.” Bulletin of the American Meteorological Society 88(3):319-328. 

Mukai A.Y., J.J. Westerink, R.A. Luettich, Jr., and D. Mark. 2002. Eastcoast 2001, A Tidal 

Constituent Database for Western North Atlantic, Gulf of Mexico, and Caribbean Sea. Coastal 

and Hydraulics Laboratory, U.S. Army Corps of Engineers, Vicksburg, Mississippi. 

Nash J.E. 1960. “A Unit Hydrograph Study with Particular Reference to British Catchments.” 

Proceedings of the Institute of Civil Engineers 17:249-282. 
7-4 

National Research Council. 1988. Estimating Probabilities of Extreme Floods, Methods and 

Recommended Research. Committee on Techniques for Estimating Probabilities of Extreme 

Floods, National Academy Press, Washington, D.C. 

Natural Resources Conservation Service (previously the U.S. Soil Conservation Service). 1985. 

“Hydrology.” Section 4 in National Engineering Handbook.” U.S. Department of Agriculture, 

Washington, D.C. 

Newton, D. 1983. “Realistic Assessment of Maximum Flood Potential.” Proceedings of the 

American Society of Civil Engineers, Journal of the Hydraulics Division 109:905-918. 

Nobilis, F., T. Haiden, and M. Kerschbaum. 1991. “Statistical Considerations Concerning 

Probable Maximum Precipitation (PMP) in the Alpine Country of Austria.” Theoretical and 

Applied Climatology 44:89-94. 

O’Connell D.R.H., D.A. Ostenaa, D.R. Levish, and R.E. Klinger. 2002. “Bayesian flood 

frequency analysis with paleohydrologic bound data.” Water Resources Research 38(5), 1058, 

doi: 10.1029/2000WR000028. 

Papalexiou S.M. and D. Koutsoyiannis. 2006. “A probabilistic approach to the concept of 

Probable Maximum Precipitation.” Advances in Geosciences 7:51-54. 

Pilgrim D.H. and I. Cordery. 1993. “Flood Runoff.” Chapter 9 in Handbook of Hydrology, 

D.R. Maidment (ed.), McGraw-Hill Book Company, New York. 

Powell M.D., P.J. Vickery, and T.A. Reinhold. 2003. “Reduced drag coefficient for high wind 

speeds in tropical cyclones.” Nature 203:279-283. 

Prasad R. 2009. Tsunami Hazard Assessment at Nuclear Power Plant Sites in the 

United States of America. NUREG/CR-6966, Office of New Reactors, U.S. Nuclear Regulatory 

Commission, Washington, D.C. 

Resio D.T., J.L. Irish, and M.A. Cialone. 2009. “A surge response function approach to coastal 

hazard assessment: Part 1, Basic Concepts.” Natural Hazards 51(1):163-182. 

Rodriguez-Iturbe I. and J.B. Valdes. 1979. “The geomorphologic structure of hydrologic 

response.” Water Resources Research 15(6):1409-1420. 

Rodriguez-Iturbe I. and A. Rinaldo. 1997. Fractal River Basins: Chance and Self-Organization. 

Cambridge University Press, New York. 

Schaefer M.G. and B.L. Barker. 2002. “Stochastic Event Flood Model.” Chapter 20 in 

Mathematical Models of Small Watershed Hydrology and Applications, V.P. Singh and 

D. Frevert (eds.), Water Resources Publications, Littleton, Colorado, p. 707-748. 

Scheffner N.W. 2008. “Water Levels and Long Waves.” In: Demirbilek, Z., Coastal 

Engineering Manual, Part II, Coastal Hydrodynamics Chapter 5-6 , Engineer Manual 1110-2-

1100, U.S. Army Corps of Engineers, Washington, D.C.. 

Schreiner L.C. and J.T. Riedel. 1978. Probable Maximum Precipitation Estimates, 

United States East of the 105th Meridian. Hydrometeorological Report No. 51, U.S. Department 

of Commerce, National Oceanic and Atmospheric Administration, and U.S. Department of Army 

Corps of Engineers, Washington, D.C. 
7-5 

Schwerdt R.W., F.P. Ho, and R.R. Watkins. 1979. Meteorological Criteria for Standard Project 

Hurricane and Probable Maximum Hurricane Windfields, Gulf and East Coasts of the United 

States. NOAA Technical Report NWS 23, National Oceanic and Atmospheric Administration, 

National Weather Service, Silver Spring, Maryland. 

Sherman L.K. 1932. “Streamflow from Rainfall by the Unit-graph Method.” Engineering News 

Record 108:501–505. 

Simpson R.H. and H.Riehl. 1981. The Hurricane and Its Impact. Louisiana State University 

Press, Baton Rouge. 

Snyder F.F. 1938. “Synthetic Unit-Graphs.” Transactions of the American Geophysical Union

19(1938):447-454,. 

Stedinger J.R., R.M. Vogel, and E. Foufoula-Georgiou. 1993. “Frequency Analysis of Extreme 

Events.” Chapter 18 in Handbook of Hydrology, D.R. Maidment (ed.), McGraw-Hill Book 

Company, New York. 

Stevens C.L. and G.A. Lawrence. 1997. “Estimation of wind-forced internal seiche amplitudes 

in lakes and reservoirs, with data from British Columbia, Canada.” Aquatic Sciences 59(2):115-

134. 

Swain R.E., J.F. England, Jr., K.L. Bullard, and D.A. Raff. 2006. “Guidelines for Evaluating 

Hydrologic Hazards.” U.S. Department of Interior, Bureau of Reclamation, Denver, Colorado. 

Swain R.E., J.F. England, Jr., K.L. Bullard, and D.A. Raff. 2004. Hydrologic Hazard Curve 

Estimating Procedures. Dam Safety Research Program Research Report DSO-04-08, 

U.S. Department of Interior, Bureau of Reclamation, Denver, Colorado. 

U.S. Army Corps of Engineers (USACE). 2010. “Hydrologic Modeling System (HEC-HMS) 

Validation Guide, Version 3.5.” Available at http://www.hec.usace.army.mil/software/hec-hms/. 

Accessed December 20, 2010, 2010. 

U.S. Army Corps of Engineers (USACE). 2009a. “Engineer Regulations and Manuals.” 

Publications of the U.S. Army Corps of Engineers. Washington, D.C. 

U.S. Army Corps of Engineers (USACE). 2009b. “Hydrologic Modeling System (HEC-HMS).” 

Available at http://www.hec.usace.army.mil/software/hec-hms/. Accessed June 9, 2009, 2009c. 

U.S. Army Corps of Engineers (USACE). 2009c “River Analysis System (HEC-RAS).” 

Available at http://www.hec.usace.army.mil/software/hec-ras/. Accessed June 10, 2009, 2009d. 

U.S. Army Corps of Engineers (USACE). 2008a. HEC-RAS River Analysis System User’s 

Manual. Version 4.0. U.S. Army Corps of Engineers Hydrologic Engineering Center, Davis, 

California. Available at http://www.hec.usace.army.mil/software/hec-ras/documents/HECRAS_4.0_Users_Manual.pdf. Accessed June 10, 2009. 

U.S. Army Corps of Engineers (USACE). 2008b. “Hydrologic Modeling System HEC-HMS 

User’s Manual. Version 3.3.” U.S. Army Corps of Engineers Hydrologic Engineering Center, 

Davis, California. Available at http://www.hec.usace.army.mil/software/hechms/documentation/HEC-HMS_Users_Manual_3.3.pdf. Accessed June 9, 2009. 
7-6 

U.S. Army Corps of Engineers (USACE). 2008c. Inflow Flood Hydrographs. USACE Dam 

Safety Program Portfolio Risk Assessment Draft Report, Washington D.C. 

U.S. Army Corps of Engineers (USACE). 2005. Stochastic Modeling of Extreme Floods on the 

American River at Folsom Dam. Flood-Frequency Curve Extension. Research Document 48, 

Institute for Water Resources, Hydrologic Engineering Center, Davis, California. 

U.S. Army Corps of Engineers (USACE). 1997. Hydrologic Engineering Requirements for 

Reservoirs. Engineer Manual 1110-2-1420, Washington, D.C. 

U.S. Army Corps of Engineers (USACE). 1994. Flood-Runoff Analysis. Engineer Manual 

1110-2-1417, Washington, D.C.. 

U.S. Army Corps of Engineers (USACE). 1991. “Inflow design floods for dams and reservoirs.” 

Engineer Regulation 1110-8-2(FR), Washington, D.C. 

U.S. Department of Interior, Bureau of Reclamation (Reclamation). 2010. Best Practices in 

Dam Safety Risk Analysis, Version 2.1. Denver, Colorado. 

U.S. Department of Interior, Bureau of Reclamation (Reclamation). 2003. Guidelines for 

Achieving Public Protection in Dam Safety Decision-Making. Denver, Colorado. 

U.S. Department of Interior, Bureau of Reclamation (Reclamation). 2002. “Interim Guidelines 

for Addressing the Risk of Extreme Hydrologic Events.” Denver, Colorado. 

U.S. Department of Interior, Bureau of Reclamation (Reclamation). 1987. Design of Small 

Dams. Third Edition. A Water Resources Technical Publication, Washington, D.C. 

U.S. Department of Interior, Bureau of Reclamation (Reclamation). 1977. Design of Arch 

Dams. A Water Resources Technical Publication, Denver, Colorado. 

U.S. Department of Interior, Bureau of Reclamation (Reclamation). 1976. Design of Gravity 

Dams. A Water Resources Technical Publication, Denver, Colorado. 

U.S. Department of Energy (DOE). 2002. Natural Phenomena Hazards Design and Evaluation 

Criteria for Department of Energy Facilities. DOE Standard STD-1020-2002, Washington, D.C. 

U.S. Department of Energy (DOE). 1995 Natural Phenomena Hazards Assessment Criteria. 

DOE Standard STD-1023-95, Washington, D.C.. 

U.S. Nuclear Regulatory Commission (NRC). 2007a. A Performance-Based Approach to 

Define the Site-Specific Earthquake Ground Motion. Regulatory Guide 1.208, Washington, D.C. 

U.S. Nuclear Regulatory Commission (NRC). 2007b. Seismic Design Classification. 

Regulatory Guide 1.29, Rev. 4, Washington, D.C. 

U.S. Nuclear Regulatory Commission (NRC). 1977. Design Basis Flood for Nuclear Power 

Plants. Regulatory Guide 1.59, Rev. 2, Washington, D.C. 

U.S. Nuclear Regulatory Commission (NRC). 1976. Flood Protection for Nuclear Power Plants. 

Regulatory Guide 1.102, Rev. 1, Washington, D.C. 
7-7 

Westerink J.J., R.A. Luettich, J.C. Feyen, J.H. Atkinson, C. Dawson, H.J. Roberts, M.D. Powell, 

J.D. Dunion, E,J, Kubatko, H. and Pourtaheri. 2008. “A basin to channel scale unstructured 

grid hurricane storm surge model applied to southern Louisiana.” Monthly Weather 

Review136(3):833–864. 

Wigmosta M.S., B. Nijssen, P. Storck, and D.P. Lettenmaier. 2002. “The Distributed Hydrology 

Soil Vegetation Model.” In Mathematical Models of Small Watershed Hydrology and 

Applications, V.P. Singh, D.K. Frevert (eds.), p. 7-42, Water Resource Publications, 

Littleton, Colorado. . 

Wigmosta M.S., L. Vail, and D.P. Lettenmaier. 1994. “A distributed hydrology-vegetation model 

for complex terrain.” Water Resources Research30:1665-1679. 

Wilson L.L. and E. Foufoula-Georgiou. 1990. “Regional Rainfall Frequency Analysis via 

Stochastic Storm Transposition.” Journal of Hydraulic Engineering 116(7):859-880. 

World Meteorological Organization (WMO). 1986. “Manual for Estimation of Probable 

Maximum Precipitation.” Second edition, WMO No. 332, Operational Hydrology Report No. 1, 

Geneva, Switzerland. 

Wüest A. and D.M. Farmer. 2003. “Seiche.” In McGraw-Hill Encyclopedia of Science and 

Technology, 9th Edition, McGraw-Hill Companies, New York. 

8-1 

8 GLOSSARY 

alternative conceptual models the set of conceptualizations that describes how 

plausible hydrometeorological phenomena may 

result in flood events that can cause hazards at 

a site; the set should account for uncertainty in 

geohydrologic, hydraulic, geoseismic, 

meteorologic, and structural characteristics that 

are relevant for the plausible phenomena. 

antecedent precipitation a precipitation event that precedes the main and 

usually larger storm 

causative Mechanism hydrometeorological phenomenon that may 

cause a flood 

Code of Federal Regulations (CFR) a collection of general and permanent rules 

published by executive departments and 

agencies of the Federal Government that are 

published in the Federal Register 

design-basis flood a flood caused by one or an appropriate 

combination of several hydrometeorological, 

geoseimic, or structural-failure phenomena, 

which results in the most severe hazards and 

therefore is used for design of critical facilities 

Early Site Permit (ESP) a permit issued by the NRC under 10 CFR 

Part 52, Subpart A, through which one or more 

sites are approved as suitable for locating a 

nuclear power facility, independent of a specific 

plant design 

Final Safety Analysis Report (FSAR) a report prepared by an applicant for licensing of 

nuclear facilities that documents safety-related 

analyses and is submitted to the NRC as part of 

the licensing application 

flood hazards conditions that facilities of a nuclear power plant 

may be exposed to during a flood event such as 

hydrostatic and hydrodynamic forces, debris 

accumulation, and impact forces that should be 

considered in the design to prevent loss of 

functionality 

General Design Criteria (GDC) general criteria listed in 10 CFR Part 50, 

Appendix A, that establish minimum 

requirements for design of facilities of a nuclear 

power plant 

grade elevation topographical elevation of the site near facilities 

of the nuclear power plant 
8-2 

hierarchical hazard assessment (HHA) HHA is a progressively refined, stepwise 

estimation of site-specific hazards that evaluates 

the safety of structures, systems, and 

components with the most conservative 

plausible assumptions consistent with available 

data 

Hydrometeorological Report (HMR) a report prepared and published by the National 

Oceanic and Atmospheric Administration 

National Weather Service to provide guidance 

for estimation of PMP for a specific area of the 

United States 

local intense precipitation the 1-hr, 2.56-km2

 (1-mi2) PMP at the location of 

the site 

precipitation loss the portion of total precipitation that is lost to 

processes such as interception, depression 

storage, and evapotranspiration and therefore 

does not appear as runoff 

probable maximum event a general concept used in hydrometeorological 

design that is thought to specify the physical limit 

of a natural event such as precipitation, flood, 

hurricanes, tsunami, and others 

probable maximum flood (PMF) the American Nuclear Society defines the PMF 

as “The hypothetical flood (peak discharge, 

volume, and hydrograph shape) that is 

considered to be the most severe reasonably 

possible, based on comprehensive 

hydrometeorological application of probable 

maximum precipitation and other hydrologic 

factors favorable for maximum flood runoff such 

as sequential storms and snowmelt.” (ANS 

1992) 

probable maximum hurricane (PMH) the American Nuclear Society defines the PMH 

as “A hypothetical hurricane having that 

combination of characteristics that makes it the 

most severe that can reasonably occur in the 

particular region involved. The hurricane 

approaches the point under study along a critical 

path and at an optimum rate of movement, which 

results in the most adverse flooding.” (ANS 

1992) 

probable maximum precipitation (PMP) the World Meteorological Organization defines 

the PMP as “The greatest depth of precipitation 

for a given duration meteorologically possible 

over a given size storm area at a particular 

location and at a particular time of the year, with 
8-3 

no allowance made for [future] long term climatic 

trends.” (WMO 1986) 

probable maximum storm surge (PMSS) a storm surge resulting from a PMH or PMWS 

probable maximum tsunami (PMT) the PMT is defined as “that tsunami for which the 

impact at the site is derived from the use of best 

available scientific information to arrive at a set 

of scenarios reasonably expected to affect the 

nuclear power plant site, taking into account 

(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.” (Prasad 2009) 

probable maximum windstorm (PMWS) the American Nuclear Society defines the 

PMWS as “A hypothetical extratropical cyclone 

that might result from the most severe 

combination of meteorological storm parameters 

that is considered reasonably possible in the 

region involved. The windstorm approaches the 

point under study along a critical path and at an 

optimum rate of movement, which will result in 

the most adverse flooding.” (ANS 1992) 

Regulatory Guide a publication by the NRC that provides guidance 

to licensees and applicants on implementing 

specific parts of the NRC's regulations, 

techniques used by the NRC staff in evaluating 

specific problems or postulated accidents, and 

data needed by the NRC staff in its review of 

applications for permits or licenses 

Seiche an oscillation of the water surface in an enclosed 

or semi-enclosed body of water initiated by an 

external cause 

structures, systems, and components (SSCs) facilities of a nuclear power plant, some of which 

may be essential for safe operation, shutdown, 

and maintaining safe shutdown conditions 

unit hydrograph the direct runoff hydrograph for a given drainage 

basin from unit depth of precipitation excess 

occurring uniformly over the basin during a 

specified duration 

Appendix A 

HYDROLOGICAL DATA SOURCES 

A-1 

APPENDIX A 

HYDROLOGICAL DATA SOURCES 

A.1 Introduction 

The Geographic Information System (GIS) is a vital tool used in the areas of integrated and 

hybrid hydrological modeling and/or data preparation. GIS is an effective framework for 

performing numerical and deterministic modeling of dynamic phenomena in both spatial and 

temporal contexts primarily because of the tight integration between spatial objects and tabular 

data (Kelmelis 1998). Hydrological modeling exhibits spatial and temporal variability, thereby 

making the constructs and philosophies of GIS well suited for this purpose. 

The fundamentals of GIS involve placing elements of the real world into a format that inherently 

provides some degree of generalization, thus resulting in a model of reality. Distinct elements in 

the real world can be captured as individual objects with some given set of characteristics or 

behaviors. For a given object, the characteristics are captured in a defined spatial and temporal 

domain. By capturing and integrating multiple objects to interpret reality, the framework for a 

model paradigm begins to emerge. It is clear that by observing reality; nearly everything 

exhibits cause-and-effect functions that provide variations in time, space, and scale. 

There are several key components that allow a GIS to function as an effective modeling system, 

providing capabilities beyond the core functions of a typical stand-alone model. Over the past 

15 years, there has been an increasing number of simulation models that are entirely contained 

within a GIS or are integrated with a GIS in some manner. In addition, the availability and 

variety of spatial data have increased significantly in the past decade as GIS has evolved into 

being a necessary tool for a large variety of disciplines. For the purpose of designing a flood 

regulatory guide, a combination of spatial data collection and pre-processing is conducted in 

preparation for various modeling efforts, both within and external to a GIS. In addition, the GIS 

environment is well suited for use as a data storage and visualization tool for modeling output. 

This appendix documents source data typically collected and processed for integrating the GIS 

into the hydrological modeling environment. 

A.2 Base Data Collections and Processing 

Depending on the specific modeling task and the level of detail required, the data and data 

sources identified and discussed below should be considered for collection. Special emphasis 

is placed on using nationally available datasets, thus allowing for a consistent base for modeling 

inputs. If a higher level of detail is required for a given area, state-run GIS clearinghouses will 

often have additional data; however, the primary national scale data should be suitable for most 

applications. 

A.2.1 Hydrologic Unit Code Boundaries 

The Hydrologic Unit Code (HUC) Boundaries system is a consistent hierarchical method of 

dividing major drainage basins throughout the nation. Smaller drainages are nested inside 

larger basins and have a coding sequence (i.e., the HUC) to define the hierarchy. There are 

four primary levels to the HUC system, starting with 21 regions throughout the nation. Within 

these 21 regions, there are 221 sub-regions, 378 accounting units, and finally 2,264 cataloguing 

units (USGS 2008). There are finer-detailed HUC levels; however, they are not yet consistent 
A-2 

throughout the nation. At the cataloguing unit level, these finer levels often are referred to as 

8-digit HUCs, signifying the number of digits used to define the drainage basin code. Figure A-1 

is an illustration of the nationwide 8-digit HUC. The inset shows a 12-digit HUC to show how 

the basins are nested into one another as well as to illustrate a future level of basin delineation. 

Figure A-1. Watershed Delineation at the HUC-8 Scale for the Conterminous United 

States, with Inset Showing a HUC-12 Scale 

Nationwide HUC data are readily available for the GIS environment from the National 

Hydrography Dataset (NHD). The NHD project, initiated in 1996, is a multi-agency cooperative 

(Federal, State, and local) effort led by the U.S. Geological Survey (USGS) and the 

U.S. Environmental Protection Agency (EPA). Its purpose is to develop and distribute a 

consistent nationwide surface hydrography dataset. Nationwide HUC information and data (in 

multiple formats) are available at: 

• Information URL: http://nationalatlas.gov/mld/hucs00m.html

• Data Access: http://nationalatlas.gov/atlasftp.html#hucs00m. 

Additional background information on specific watersheds can be found on the USGS and EPA 

websites identified below: 

• USGS Science in Your Watershed: http://water.usgs.gov/wsc/

• EPA Surf Your Watershed: http://cfpub.epa.gov/surf/locate/index.cfm. 
A-3 

A.2.2 Stream Networks/Waterbodies 

Routed and attributed stream networks and waterbodies are available under the NHD program 

at three primary scales: (1) Medium Resolution (1:100,000 scale), (2) High Resolution 

(1:24,000 scale), and (3) Local Resolution (<1:24,000, scale varies). While the local resolution 

data are not available throughout the conterminous United States, the High Resolution and 

Medium Resolution datasets are available. The NHD website (URL provided below) offers an 

interactive viewer to assess the availability of data for a given area. The website viewer also 

allows for interactive downloading of data. Alternatively, the NHD allows users to retrieve data 

for an entire 4-digit HUC; these data, called “pre-staged” data, are maintained as current as 

data available in the interactive viewer. Data can be accessed via file transfer protocol (FTP) 

links (uniform resource locators [URLs] provided below) and are available in several formats 

including Environmental Systems Research Institute (ESRI) coverage format, shapefile format, 

and personal geodatabase. The shapefile format is a de facto standard in geospatial data; thus, 

it should be usable by most GIS software products, in addition to ESRI products such as ArcGIS 

and Arc/INFO. The geodatabase format represents a new advanced geospatial file format 

containing multiple spatial data elements that can be linked and interact with one another 

through developed rule sets. The disadvantage to using the geodatabase file format is that it is 

limited to certain commercial software products such as ArcGIS and ERDAS Imagine. More 

information about the personal geodatabase can be found on the ESRI website at 

http://www.esri.com/software/arcgis/geodatabase/index.html. 

• Information URL: http://nhd.usgs.gov/

• Data Access: 

– Pre-Staged Data: ftp://nhdftp.usgs.gov/SubRegions/

– Interactive Viewer: http://nhd.usgs.gov/data.html

A.2.3 Digital Elevation Models 

Digital Elevation Models (DEMs) provide the basis for most hydrologic modeling and represent 

the earth’s surface at the ground level, often referred to as “bare earth.” This approach provides 

a representation of the terrain surface without obstruction from trees or buildings, and in the 

case of large waterbodies, an average water-surface elevation is used. A DEM is composed of 

a regular grid of points that represents a sample elevation with the specified resolution of the 

dataset. DEMs for the United States are available for most places at 10-m resolution, and full 

coverage is available at 30- and 90-m resolutions. 

DEMs are available from many sources and are available at several different resolutions. 

• Information URL: 

– National Elevation Dataset (NED): http://ned.usgs.gov/

– Shuttle Radar Topographic Mission (SRTM): http://www2.jpl.nasa.gov/srtm/

– The National Digital Elevation Program: http://www.ndep.gov/. 

• Data Access: 

– USGS Seamless Server: http://seamless.usgs.gov. 

The USGS Seamless Server provides access to several different sources and resolutions of 

DEM data, including the NED in 1-arc-second (~30-m), 1/3-arc-second (~10-m), and in limited 

areas 1/9-arc-second resolutions (~3-m). The SRTM data are available at 3-arc-second and 
A-4 

1-arc-second resolutions. The USGS Seamless Server offers an interactive viewer that is used 

to select and download DEM data of interest. DEM data downloaded from the USGS Seamless 

Server will be in the ESRI ArcGrid format. Figures A-2, A-3, and A-4 provide basic guidance on 

downloading data from the USGS Seamless Server. 

Figure A-2. Screen Shot of the Opening Page of the USGS Seamless Server Website. 

The tools on the left panel can be used to zoom and pan to an area of 

interest. Alternatively, X,Y coordinate pairs can be entered to zoom to the 

area of interest. 
A-5 

Figure A-3. Seamless Server Layers Can Be Turned On and Off on the Right Panel, 

Which Helps to Navigate and Identify the Area of Interest. When the area of 

interest has been identified, change the tab on the right panel to 

“Download,” and select the layers of interest (note: it is possible to 

download more than just DEM data here), then use the Download tools on 

the left-panel to select an area for downloading. 
A-6 

Figure A-4. As the Final Step in the Seamless Server Download Process, a New 

Window Showing the Files Available for Downloading Will Appear 

– EPA: http://www.epa.gov/waterscience/ftp/basins/gis_data/huc/. 

The EPA offers pre-staged data that are clipped and organized at the 8-digit HUC level, 

including NED 1-arc-second (~30-m) data. 

Figures A-5 and A-6 show the types of data available from the EPA website. 
A-7 

Figure A-5. EPA Data Access Organized by 8-digit HUCs. The folders are named after 

the 8-digit HUCs. 
A-8 

Figure A-6. Example of Data, Including NED DEM Data (available from EPA pre-staged 

data website) 

A.2.4 Land Cover 

Land-cover data, also referred to as Land Use/Land Cover (LULC) data, provide an important 

attribute for hydrologic modeling. There are several sources of LULC data; however, the most 

current and nationally available dataset is the 2001 National Land Cover Database (NLCD) from 

the Multi-Resolution Land Characteristics Consortium (MRLC). The MRLC, which was formed 

in 1993, consists of Federal agencies that combined resources to compile a consistent national 

land-cover database. The 2001 NLCD dataset is composed of classified 30-m Landsat-7 multispectral imagery. It also offers two additional datasets to complement the land-cover data: 

(1) percent urban imperviousness and (2) percent tree canopy. All data exist in the ERDAS 

Imagine raster file format (*.img), and both an interactive download tool and pre-staged data are 

available. 

• Information URLs: 

– MRLC Information Page: http://www.mrlc.gov/

– NLCD Background and Information: http://www.mrlc.gov/nlcd.php

– NLCD 2001 Land Class Definitions: http://www.mrlc.gov/nlcd_definitions.php. 

• Data Access: 

– MRLC Interactive Download Tool: http://gisdata.usgs.net/website/MRLC/viewer.htm. 

This tool operates the same as the USGS Seamless Server in that an area of interest is 

selected. To use the tool, the appropriate themes for downloading are selected under the 

“Download” tab on the right panel (Figure A-7), an area of interest is selected using the 

“Download” tools on the left panel, and links are made available to download the data. 
A-9 

Figure A-7. The Interactive MRLC Data Download Tool is Identical in Operation to the 

USGS Seamless Server 

– Pre-staged NLCD Data: http://www.mrlc.gov/nlcd_multizone_map.php. 

From this website, one can download pre-staged NLCD data for 15 zones throughout the 

conterminous United States and Alaska simply by clicking on the zone of interest (Figure A-8). 

Figure A-8. NLCD Pre-Staged Data Are Available for the Zones Indicated in the Figure. 

Data are available as ERDAS Imagine raster files bundled into 

downloadable zip files. 
A-10 

A.2.5 Soils 

Soils data are fundamental for evaluating subsurface and overland flow as well as groundwater 

recharge. The STATSGO dataset offers consistent coverage across the United States and is 

mapped at a source scale of 1:250,000, where the minimum mapping unit is 625 hectares. 

STATSGO data are produced by the National Cooperative Soil Survey 

(http://soils.usda.gov/partnerships/ncss/) and are distributed by the Natural Resources 

Conservation Service (NRCS). SSURGO, also distributed by the NRCS, is a larger-scale soils 

dataset based on 1:12,000 to 1:63,360 mapping scales. The SSURGO dataset was not entirely 

complete for the United States as of December 20, 2010 (see Figure A-9 for the completion 

status). 

Figure A-9. Completion Status for the SSURGO Soils Database 

• Information URL: 

– STATSGO Soils: http://soils.usda.gov/survey/geography/statsgo/

– SSURGO Soils: http://soils.usda.gov/survey/geography/ssurgo/. 

• Data Access: 

– NRCS Soil Data Mart Download Tool: http://soildatamart.nrcs.usda.gov/. 

The NRCS Soil Data Mart allows users to download NRCS soils data that are built on the fly 

according to the user’s needs. These data are generally available for download by county 

boundary and are available in ESRI’s Shapefile or Coverage format. The soils data are 

accompanied by a tabular database of detailed soils information. 

– Pennsylvania State University (Penn State) Soil Information for Environmental 

Modeling and Ecosystem Management: 

http://www.soilinfo.psu.edu/index.cgi?soil_data&conus&data_cov. 
A-11 

The Penn State CONUS-Soils product offers STATSGO data in a 1-km raster format (ESRI’s 

ArcGRID format) or vector format (ESRI’s coverage format) for the conterminous United States. 

As shown in Figure A-10, soils data offered include soil texture class, depth to bedrock, 

sand/silt/clay fraction, rock fragment class, rock fragment volume, bulk density, porosity, 

permeability, available water capacity, pH, plasticity, hydraulic conductivity, hydrologic soil 

group, and curve number. Standard STATSGO soils data are also available by state from the 

Penn State website. 

Figure A-10. The Penn State Soil Information for Environmental Modeling and 

Ecosystem Management Website Offers Easy-to-Access STATSGO Data for 

the Conterminous United States. A wide variety of soil property data, 

already in GIS data format, is available. 
A-12 

– EPA: http://www.epa.gov/waterscience/ftp/basins/statsgo/. 

Similar to the DEM offerings from the EPA, STATSGO data also are available in a pre-staged 

format that is clipped and organized at the state level (Figure A-11). 

Figure A-11. Pre-Staged STATSGO Data Available at the EPA Website 

A.2.6 Dam Locations 

The location and statistics of dams within a watershed may be of interest. The U.S. Army Corps 

of Engineers maintains the National Inventory of Dams, which is available from the National 

Atlas website referenced below. 

• National Inventory of Dams: http://crunch.tec.army.mil/nidpublic/webpages/nid.cfm

• Data Access: http://nationalatlas.gov/mld/dams00x.html. 
A-13 

A.2.7 Other Miscellaneous Geospatial Data of Interest 

• USGS Geospatial Hydrologic Data: http://water.usgs.gov/lookup/getgislist

• The National Map: http://nmviewogc.cr.usgs.gov/viewer.htm

• The National Atlas: http://nationalatlas.gov/atlasftp.html. 

A.3 References 

Kelmelis, J.A. 1998. “Process Dynamics, Temporal Extent, and Causal Propagation as the 

Basis for Linking Space and Time.” In: Spatial and Temporal Reasoning in Geographic 

Information Systems, Oxford University Press, Oxford, England. 

U.S. Geological Survey (USGS). 2008. Hydrologic Unit Maps. Available at 

http://water.usgs.gov/GIS/huc.html. Accessed May 30, 2008. 

Appendix B 

FLOODING FROM LOCAL INTENSE PRECIPITATION: 

A CASE STUDY 

B-1 

APPENDIX B 

FLOODING FROM LOCAL INTENSE PRECIPITATION: A CASE STUDY 

The flooding hazards from a local intense precipitation event occur at the immediate plant site, 

irrespective of the plant grade elevation. Safety-related structures, systems, and components 

(SSCs) should be protected from ponded (hydrostatic effects) waters during a local intense 

precipitation event and also from the drag and impact forces (hydrodynamic effects) of flowing 

water. 

Usually, a network of passive drainage channels is used around the immediate plant site where 

safety-related SSCs are placed. The site itself also may be graded so runoff generated by a 

local intense precipitation event drains away from the safety-related SSCs via a passive 

drainage network designed to route water from the site to a natural or artificial drainage or water 

body. However, the magnitude of flooding (i.e., ponded depth and drag and impact forces) 

depends on two factors: (1) the adequacy of the site grading with respect to its ability to drain 

water away from safety-related SSCs and (2) the conveyance capacity of the passive drainage 

network. 

In this study, three cases with respect to the site grading and the conveyance capacity of the 

passive drainage channels are considered. 

• Case 1 assumes that the site is well-graded and therefore effectively drains runoff 

generated during a local intense precipitation event to the passive drainage channels. It 

is further assumed that the drainage channels themselves remain fully functional without 

any blockage during the entire period of the flooding. 

• Case 2 relaxes the ideal assumptions made in Case 1 by assuming that the site grading 

remains effective and therefore drains the runoff to the passive drainage channels. 

However, in this case, the drainage channels themselves are postulated to experience 

partial, although severe, blockage, that significantly reduces the conveyance capacity of 

the channels. 

• Case 3 further assumes that the design of the site grade and the passive drainage 

channels are incapable of routing any flow from the immediate plant site, and therefore, 

overland flow occurs over the whole plant site during the local intense precipitation 

event. 

For each of these three cases, the U.S. Army Corps of Engineers (USACE) Hydrologic 

Engineering Center Hydrologic Modeling System (HEC-HMS) computer model was used to 

estimate runoff discharge during the local intense precipitation event. Then, the channel 

hydraulic conditions for the estimated discharges were modeled using the USACE Hydrologic 

Engineering Center River Analysis System (HEC-RAS) computer model. Results from these 

hypothetical simulations are described below. 

B.1 Case 1: Fully Functional Site Grading and Drainage Channels 

B.1.1 Drainage Characteristics 

Figures B-1 through B-3 show the site layout, the adjacent drainage areas, the plant facility 

locations, and the passive drainage channel network. As shown in Figure B-1, the hypothetical 
B-2 

plant site is located on the lower, southwestern portion of a small drainage. The undisturbed, 

northwestern portion of the adjacent drainage, labeled Contributing Area N and Contributing 

Area E, drains to the north and east channels of the hypothetical passive drainage network 

installed at the perimeter of the powerblock area. The powerblock area is graded so runoff 

generated on the area drains outward from the center of the area towards the passive drainage 

channels located on its perimeter (Figures B-2 and B-3). The passive drainage network slopes 

from its highest topographic elevation at the eastern part of the site to the site’s southwest 

corner via the north and the south channel segments. The passive drainage network joins a 

natural creek that originally drained the site. 

Figure B-1. Hypothetical Layout of a Site Including Adjacent Natural Drainage Areas, 

the powerblock area, and the Passive Drainage Channels and Their 

Relationship to a Natural Creek Flowing Offsite. The powerblock area is 

approximately 1.1 mi2

 (30.7 million ft2). The total drainage area contributing 

runoff to the creek flowing offsite is therefore, approximately 2.6 mi2

(72.5 million ft2

). 

N

Contributing Area N

1.0 mi2

Contributing Area E

0.5 mi

2

Power Block Area

Creek Flowing Offsite

N

Contributing Area N

1.0 mi2

Contributing Area E

0.5 mi

2

Power Block Area

Creek Flowing Offsite
B-3 

Figure B-2. Hypothetical Layout of Plant Buildings in the Powerblock Area 

Figure B-3. Hypothetical Local Drainage Areas and Reaches of the Passive Drainage 

Channels 

B.1.2 HEC-HMS Setup 

Figure B-4 shows the HEC-HMS schematic used to set up the local drainage areas in the 

powerblock area, the natural drainage areas, and their relationship to the passive drainage 

400 ft

720 ft

1120 ft

6400 ft

4800 ft

2400 ft

240 ft

128 ft

N

400 ft

720 ft

1120 ft

6400 ft

4800 ft

2400 ft

240 ft

128 ft

N

6400 ft

2400 ft

4800 ft

Conduits A and B

N

Subbasin NE1

Subbasin NW1 Subbasin NE2

Subbasin NW2

Subbasin SW1

Subbasin SW2 Subbasin SE1

Subbasin SE2

Reach NE1

Reach NW1 Reach NE2

Reach SW2

Reach NW2 Reach SW1

Reach SE2

Reach SE1

6400 ft

2400 ft

4800 ft

Conduits A and B

N

Subbasin NE1

Subbasin NW1 Subbasin NE2

Subbasin NW2

Subbasin SW1

Subbasin SW2 Subbasin SE1

Subbasin SE2

Reach NE1

Reach NW1 Reach NE2

Reach SW2

Reach NW2 Reach SW1

Reach SE2

Reach SE1
B-4 

channels surrounding the hypothetical powerblock area. This schematic was used in the HECHMS model to (1) estimate runoff generated from the powerblock area and from the adjacent 

natural drainage areas and (2) to then aggregate the runoff within the passive drainage 

channels with the outflow into the natural creek that drains offsite. 

Figure B-4. HEC-HMS Schematic Used to Estimate Runoff from the Powerblock Area 

into the Hypothetical Passive Drainage Channels 

It was conservatively assumed that no infiltration losses would occur during the local intense 

precipitation event. This assumption maximizes runoff and, therefore, maximizes the watersurface elevation in the passive drainage channels. If the conveyance capacity of the passive 

channels is adequate to route all of the runoff generated during a local intense precipitation 

event without the water-surface elevation in the channels rising to the grade elevation of the 

powerblock area, the plant’s safety-related SSCs would be safe. 

B.1.3 Estimation of the Local Intense Precipitation 

The local intense precipitation event is defined as the point probable maximum precipitation 

(PMP). Hydrometeorlogical Report 52 (HMR 52) recommends that the 1-hr, 1-mi2

 PMP be 

considered equivalent to a point PMP. The 1-hr, 1-mi2

 PMP for the hypothetical location of the 

nuclear power plant was estimated from Figure 24 in HMR 52. As recommended by HMR 52, 

the sub-1-hr duration PMP depths were obtained by applying multiplication factors to the 1-hr, 

1-mi2

 PMP depth obtained from HMR 52 Figures 36 (ratio of 5-min, 1-mi2 to 1-hr, 1-mi2 PMP 

depths), 37 (ratio of 15-min, 1-mi2

 to 1-hr, 1-mi2 PMP depths), and 38 (ratio of 30-min, 1-mi2 to 

1-hr, 1-mi2

 PMP depths). The 6-hr, 10-mi2 PMP depth can be obtained either directly from 
B-5 

HMR 51, or by using the ratio of 1-hr, 1-mi2

 to 6-hr, 10-mi2 PMP depths given in Figure 23 of 

HMR 52). Table B-1 below lists the estimated local intense precipitation for the hypothetical 

location of the nuclear power plant. 

Table B-1. Local Intense Precipitation for the Hypothetical Nuclear Power Plant 

Duration 

Area 

(mi2) Multiplier Applied to 

Local Intense 

Precipitation (in.) 

6 hr 10 1.0/0.621 

(HMR 52 Figure 23) 1-hr, 1-mi2

 PMP 31.0 

1 hr 1 NA NA 19.3 

(HMR 52 Figure 24) 

30 min 1 0.738 

(HMR 52 Figure 38) 1-hr, 1-mi2

 PMP 14.2 

15 min 1 0.509 

(HMR 52 Figure 37) 1-hr, 1-mi2

 PMP 9.8 

5 min 1 0.323 

(HMR 52 Figure 36) 1-hr, 1-mi2

 PMP 6.2 

 

B.1.4 Estimation of Runoff Hydrographs 

The local intense precipitation shown in Table B-1 was input into the HEC-HMS modeling 

system with a 5-minute time step. The first time step was set to the highest local intense 

precipitation depth, which is 6.2 in. The next two 5-minute time steps were set to an 

incremental precipitation depth of 1.8 in. ([9.8 - 6.2]/2 in.). Incremental precipitation depths for 

the subsequent time steps were determined from the cumulative local intense precipitation 

depths shown in Table B-1. The hyetograph of the local intense precipitation event on the 

hypothetical nuclear power plant site is shown in Figure B-5. 

It was conservatively assumed that the 1-hr, 1-mi2

 PMP would occur uniformly over the 2.6-mi2

local drainage. It was also conservatively assumed that the antecedent moisture conditions in 

the local drainage would be such that no rainfall losses would occur over the duration of the 

PMP event and the subsequent runoff events (i.e., the loss rate in the HEC-HMS basin model 

for each of the powerblock area subbasins and Contributing Areas N and E were set to “None”). 

HEC-HMS also requires that a Transform Method be specified for each subbasin. The 

Transform Method determines the temporal distribution of the runoff generated from the subbasin. A unit hydrograph (UH) approach was adopted. The UH used for the subbasins in the 

powerblock area and Contributing Areas N and E were based on the Soil Conservation Service 

(i.e., SCS; now the Natural Resources Conservation Service [NRCS]) synthetic graph applicable 

to drainage areas 2000 ac or smaller (SCS 1972). The UH approach to estimating runoff from 

rainfall excess is based on an assumption of linearity. This assumption postulates that the 

direct runoff hydrograph from a unit depth of rainfall excess is the UH and the direct runoff 

hydrograph for any other amount of rainfall excess can be estimated by scaling the ordinates of 

the UH by the corresponding rainfall excess (e.g., the ordinates of the direct runoff hydrograph 

corresponding to two units of rainfall excess are simply the ordinates of the UH multiplied by 

two). Traditionally, UH is derived from observed rainfall-runoff events. Where adequate 

observations of rainfall-runoff are not available, regionalized, synthetic UHs based on rainfall-
B-6 

runoff from similar drainage catchments have been developed (e.g., the SCS UH [SCS 1972] 

and the Snyder UH [Snyder 1938]). The recommendation for the applicability of these methods 

includes the size of the drainage catchment. The SCS UH is recommended for areas of 

2000 ac (3.1 mi2

) or less, and the Snyder UH is recommended for areas of 10 to 10,000 mi2. 

Figure B-5. Hyetograph of the Local Intense Precipitation Event on the Hypothetical 

Nuclear Power Plant Site 

The UH linearity assumption starts to break down as the rainfall intensity and volume increase 

to the magnitudes of the PMP event. During the PMP event, the large amount of rainfall excess 

causes the runoff mechanism to be dominated by highly non-linear hydraulic effects in the 

overland flow process. Surface roughness resulting from small irregularities may be subsumed 

by the greater depth of the overland flow, thereby increasing the likelihood of quicker delivery of 

overland flow to the channel network. When possible, unit hydrographs based on severe 

storms approaching the magnitude of a PMP event in the drainage basin of concern should be 

used. Therefore, USACE suggests that an adjustment to the traditional UH derived from 

observations of storms of smaller magnitudes is required to account for the more rapid overland 

flow response during storm events that approach the PMP (USACE 1994; see page 7-1). 

USACE also recommends that for large storms, the time to peak for the UH estimated from 

smaller storms be reduced (USACE 1994; see page 13-8). Other authors (Pilgrim and Cordery 

1993) have suggested that the peak discharge be increased by 20 to 50 percent and time-topeak be reduced by 33 percent. In the absence of specific guidance, the following 

UH adjustment method was adopted as reasonably conservative for this study: 

1. Reduce time-to-peak by 33 percent. 

2. Increase peak discharge by 20 percent. 

3. Ensure that the area under the UH, representing the volume of excess runoff, is 

equivalent to unit rainfall excess over the drainage basin. 

The 6-hr Local Intense Precipitation Hyetograph

Time (min)

Precipitation Depth (in)

0 30 60 90 120 150 180 210 240 270 300 330 360

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

6.200

1.800

1.467

0.850

0.195
B-7 

Where possible, a different adjustment method, supported by data in the drainage basin of 

concern, may be used. In these instances, a complete description of the method, the 

supporting data, and a justification should be presented. 

The modified SCS UH for the sub-basins in the powerblock area and Contributing Areas N and 

E were input into the HEC-HMS modeling system, which was set to use “User-Specified Unit 

Hydrograph” as the Transform Method for all sub-areas of the local drainage. Runoff from the 

drainage sub-areas would collect in the hypothetical passive drainage channels and be carried 

offsite. Kinematic wave routing was used for the drainage channels labeled NE1, NE2, NW1, 

NW2, SW1, SW2, SE1, and SE2 (see Figure B-4 above). The Manning’s roughness coefficient 

for all these drainage channels was set to 0.024 (Chow 1959). All channels were assumed to 

have a bottom width of 15 ft and side slope of 3:1 (H:V). Lag routing with a lag time of 

5 minutes was used for channels RDE and RDW. 

The HEC-HMS model was used to simulate the direct runoff hydrograph for the drainage 

channels. Figure B-6 shows the HEC-HMS simulated runoff discharge hydrograph at the outlet 

(the southwestern corner of the hypothetical passive drainage channel network). The peak 

discharges in all reaches were determined from the HEC-HMS simulations. 

Figure B-6. Direct Runoff Hydrograph at the Outlet of the Hypothetical Passive 

Drainage Network 

B.1.5 Estimation of Water-Surface Elevations 

The site grade elevation in the powerblock area is assumed to be 200 ft. The bottom elevations 

of channel reaches at specific points are shown in Table B-2. A conservative approach for 

estimating the bounding water-surface elevation in the hypothetical passive drainage channel 

network is to assume (1) that the peak discharges in all channel reaches occur simultaneously 

and (2) that these peak discharges represent steady-state conditions. These assumptions are 

conservative and would lead to estimates of a higher water-surface elevation in individual 

reaches than what would be expected during transient conditions that would actually occur 

Discharge Hydrograph at the Outlet

Time

Discharge (cfs)

0:001:002:003:004:005:006:007:008:009:00

10:0011:0012:0013:0014:0015:0016:0017:0018:00

0

2000

4000

6000

8000

10000
B-8 

during the local intense precipitation event. Therefore, the estimated water-surface elevations 

would be a bounding estimate. 

Table B-2 shows the HEC-HMS estimated peak discharges for all reaches of the hypothetical 

passive drainage network. The peak discharge at the outlet occurred 2 hr and 1 minute after 

the start of the local intense precipitation event. The peak discharges and the corresponding 

times for each of the reaches are shown in column 2. Column 3 shows the estimated discharge 

in each reach at the time corresponding to the peak discharge at the outlet. 

Table B-2. Comparison of Peak Discharges and Corresponding Times for Each Reach 

and the Discharges in Each Reach Corresponding to the Time of Peak 

Discharge at the Outlet 

Reach 

Upstream Bottom 

Elevation (ft) 

Peak Discharge and Time§ (cfs) 

[Time (hr:min)] 

Discharge at 2:01 

(cfs) 

NE1 180.0 1520.5 [1:58] 1518.0 

NE2 175.2 5699.6 [2:15] 5632.7 

NW1 168.8 6339.4 [2:05] 6318.4 

NW2 162.4 6900.2 [2:05] 6878.2 

SW1 157.6 7544.6 [2:04] 7526.2 

SW2 164.0 3146.2 [1:29] 2888.5 

SE1 175.2 2241.0 [1:32] 2153.8 

SE2 180.0 1430.5 [1:59] 1429.9 

RDE - 1619.2 [0:10] 50.9 

RDW - 1619.2 [0:10] 50.9 

Outlet 152.4 10414.7 [2:01] 10414.7 

§

 The discharges used in the steady-state, water-surface-profile simulations are indicated in 

boldface. 

Apart from reaches SW2, SE1, RDE, and RDW, the times of peak discharge in all reaches are 

within a few minutes of the time of peak discharge at the outlet point (i.e., 2 hr and 1 min). 

Therefore, in the HEC-RAS steady-state, water-surface profile simulations, the discharge in 

each reach except for the four reaches mentioned above were set to their own peak discharge 

rates. Because the times of the peak discharges in the four reaches are significantly earlier 

than those at the outlet, these peak discharges would pass through the outlet before the outlet 

discharge reaches its peak and, therefore, would not significantly affect the peak outlet 

discharge. The discharges for the four reaches whose peak-discharge times were significantly 

different from the outlet peak discharge time were set to their respective estimated discharge at 

2 hr and 1 min, which corresponds to the time of outlet peak discharge. 

The HEC-RAS model was set up for the hypothetical passive drainage channel network as 

shown in Figure B-7. A steady-state simulation was performed using the estimated discharges 

obtained from the HEC-HMS simulation as explained above. Uniform, trapezoidal cross 

sections for all channels with bottom widths of 40 ft and side slopes of 3:1 (H:V) were assumed. 

Intermediate cross sections required by the HEC-RAS computations were interpolated within 

the software package. Figures B-8 through B-11 show simulated cross sections with watersurface elevations at key points in the hypothetical passive drainage channel network. 
B-9 

Figure B-7. HEC-RAS Model Setup for the Hypothetical Passive Drainage Channel 

Network 
B-10 

Figure B-8. Simulated Steady-State, Water-Surface Elevations at the Top of the North 

Segment and at the Northeast Bend in the Hypothetical Passive Drainage 

Network 
B-11 

Figure B-9. Simulated Steady-State, Water-Surface Elevations at the South Bend and 

Above the Outlet in the North Segment of the Hypothetical Passive 

Drainage Network 
B-12 

Figure B-10. Simulated Water-Surface Elevations at the Top of the South Segment and 

at the West Bend in the Hypothetical Passive Drainage Network 
B-13 

Figure B-11. Simulated Steady-State, Water-Surface Elevations in the South Segment 

Above the Outlet and at the Outlet of the Hypothetical Passive Drainage 

Network 
B-14 

Figure B-12. Simulated Seady-State, Water-Surface Profile in the North Segment of the 

Hypothetical Passive Drainage Network 

Figure B-13. Simulated Steady-State, Water-Surface Profile in the South Segment of the 

Hypothetical Passive Drainage Network 
B-15 

For the local PMP event, conservatively estimated water-surface elevations in the hypothetical 

passive drainage network are shown in Table B-3. With the site grade elevation assumed to be 

200 ft, the maximum water-surface elevation, 186.3 ft, was simulated at the top of reach NE1. 

The maximum depth of flow, 13.7 ft, was simulated at the downstream end of reach SW2. 

However, the water-surface elevation associated with this location was only 166.5 ft. 

Table B-3. Simulated Profile Parameters at Steady State in the Hypothetical Passive 

Drainage Network 

Reach (Location) 

Bottom Elevation 

(ft) 

Water Surface Elevation 

(ft) 

Depth of Flow 

(ft) 

NE1 (Upstream) 180.0 186.3 6.3 

NE2 (Upstream) 175.2 184.5 9.3 

NW1 (Upstream) 168.8 178.4 9.4 

NW2 (Upstream) 162.4 172.7 10.3 

SW1 (Upstream) 157.6 168.5 10.9 

SW1 (Downstream) 152.8 165.7 12.9 

SW2 (Upstream) 164.0 169.5 5.5 

SW2 (Downstream) 152.8 166.5 13.7 

SE1 (Upstream) 175.2 180.2 5.0 

SE2 (Upstream) 180.0 184.4 4.4 

Outlet 152.4 164.7 12.3 

Bold text indicates maximum simulated water-surface elevation in the passive drainage network.

B.2 Case 2: Fully Functional Site Grading and Partially Blocked 

Drainage Channels 

It is common during a large flood for streams to carry a large amount of debris along with the 

flood waters. This debris has the potential to reduce the conveyance capacity in the channel by 

blocking part of the channel’s cross section. 

In Case 2, a partial blockage of the channel cross section by debris was assumed. The 

blockage was modeled as a continuous block of impervious material in the center of the 

channel, occupying the full bottom width of the channel and rising 10 ft from the bottom of the 

channel. All reaches were assumed to be blocked similarly. The immediate site drainage area 

was assumed to be functional in that it delivered the runoff to the channel reaches. All other 

conditions, including the discharges at various locations within the hypothetical passive 

drainage network, were identical to those in Case 1. 

Figures B-14 through B-17 show simulated water-surface elevations in the passive drainage 

network for Case 2. As expected, the reduction in conveyance resulted in increased watersurface elevations at all locations within the hypothetical passive drainage network. The watersurface elevations remained below the site grade of 200 ft (Figures B-18 and B-19). The 

maximum water-surface elevation, 192.6 ft, was simulated at the top of reach NE1 (see 

Table B-4 below). The maximum depth of flow, 19.4 ft, occurred at the downstream end of 

reach SW2; however, the water-surface elevation at this location was only 172.2 ft. 

It is worth noting, however, that a nearly complete or complete blockage would result in a 

completely compromised passive drainage network. 
B-16 

Figure B-14. Simulated Steady-State, Water-Surface Elevations at the Top of the North 

Segment and at the Northeast Bend in the Hypothetical Passive Drainage 

Network (partial blockage scenario) 
B-17 

Figure B-15. Simulated Steady-State, Water-Surface Elevations at the South Bend and 

Above the Outlet in the North Segment of the Hypothetical Passive 

Drainage Network (partial blockage scenario) 
B-18 

Figure B-16. Simulated Water-Surface Elevations at the Top of the South Segment and 

at the West Bend in the Hypothetical Passive Drainage Network (partial 

blockage scenario) 
B-19 

Figure B-17. Simulated Steady-State, Water-Surface Elevations in the South Segment 

Above the Outlet and at the Outlet of the Hypothetical Passive Drainage 

Network (partial blockage scenario) 
B-20 

Figure B-18. Simulated Steady-State, Water-Surface Profile in the North Segment of the 

Hypothetical Passive Drainage Network (partial blockage scenario) 

Figure B-19. Simulated Steady-State, Water-Surface Profile in the South Segment of the 

Hypothetical Passive Drainage Network (partial blockage scenario) 
B-21 

Table B-4. Simulated Profile Parameters at Steady State in the Hypothetical Passive 

Drainage Network (partial blockage scenario) 

Reach (Location) 

Bottom Elevation 

(ft) 

Water Surface Elevation 

(ft) 

Depth of Flow 

(ft) 

NE1 (Upstream) 180.0 192.6 12.6 

NE2 (Upstream) 175.2 190.8 15.6 

NW1 (Upstream) 168.8 184.6 15.8 

NW2 (Upstream) 162.4 178.8 16.4 

SW1 (Upstream) 157.6 174.5 16.9 

SW1 (Downstream) 152.8 171.7 18.9 

SW2 (Upstream) 164.0 176.4 12.4 

SW2 (Downstream) 152.8 172.2 19.4 

SE1 (Upstream) 175.2 187.2 12.0 

SE2 (Upstream) 180.0 191.5 11.5 

Outlet 152.4 170.9 18.5 

 

B.3 Case 3: Totally Compromised Drainage 

Assuming that the hypothetical passive drainage is completely compromised, the only way 

runoff can be conveyed from the immediate powerblock area is by overland sheet flow. The 

powerblock area was assumed to slope gently from east to west toward the outlet of the 

hypothetical passive drainage network (see Figures B-1 and B-20). 

Figure B-20. Oblique View of the Powerblock Area with Estimated Water Levels 2 Hours 

after Start of PMP. Axis labels distances from the western edge of 

powerblock. Flow is from right (east) to left (west). 
B-22 

The topography of the powerblock Area was constructed using bi-linear interpolation between 

the corners, mid-points of the edges, and the center-point of the area. The point elevations 

used to define the topography of the powerblock area are listed in Table B-5. 

Table B-5. Point Elevations Within and Around the Edge of the Powerblock Area 

Location Elevation (ft) 

Center 210.0 

East 200.0 

Northeast 195.2 

North 188.8 

Northwest 182.4 

West 177.6 

Southwest 172.8 

South 195.2 

Southeast 184.0 

Top elevation of obstructions 220.0 

The topography within the powerblock area was interpolated at a 40-ft resolution in both the 

south-north and west-east directions. The elevations where buildings are located within the 

powerblock area were set to an arbitrary elevation of 220 ft to create impediments to flow. The 

overall powerblock area is 6400 ft long in the west-to-east direction and 4800 ft wide in the 

south-to-north direction. No obvious single flow path would guide the orientation of the HECRAS layout. Because the highest elevation occurs at the middle point of the eastern edge and 

the lowest elevation occurs at western edge (southwest corner), the HEC-RAS layout was 

designed for flow from east to west. Therefore, to cover the total length of the powerblock area, 

a total of 161 cross-sections, spaced 40 ft apart, were established to span laterally from south to 

north. The cross-section designation used in this discussion is of the form Xnnnn where nnnn

indicates the distance in feet from the western edge of the powerblock area. The elevations 

across each section were prescribed with 121 points to span the 4800 ft width of the powerblock 

area. This configuration does not allow for flow across the north or south boundaries. The 

configuration of the powerblock area is shown in Figure B-20. The axis labeling in the figure is 

consistent with the cross-section naming convention described above. 

Two runoff scenarios were investigated. In Scenario 1, the combined runoff from upslope 

Contributing Areas N and E and the powerblock area, which was estimated previously using 

HEC-HMS, was used as a time-varying boundary condition on the eastern edge (X6400) of the 

powerblock area. The water-surface profile was then simulated in the HEC-RAS setup using 

unsteady flow. The combined runoff discharge during the PMP event is initially zero, increases 

to a peak of 6500 cfs 120 minutes after initiation of the PMP event, and then returns to zero 

after about 12 hours. The hydrograph used as the boundary condition for cross-section X6400 

during this simulation is shown in Figure B-21. Water flows to the west and discharges from the 

western boundary (cross-section X0000). The input discharge (X6400) and resulting estimated 

downstream hydrograph (X0000) for both of these cross sections are shown in Figure B-21. 

The downstream discharge peak lags the input discharge peak by about 30 minutes, with the 

peak only slightly attenuated. 
B-23 

Given these peak times, the most critical period to evaluate is between 120 and 150 minutes 

after initiation of the PMP event. Estimated levels of inundation at 120 minutes are shown in 

Figures B-22 through B-26 for cross-sections X5000, X4000, X3000, X2000, and X1000, where 

the cross-section number refers to the west-to-east distance from the western boundary. 

Figures B-22 to B-26 are ordered starting from upstream to downstream within the powerblock 

Area. 

Figure B-21. Simulated Discharges for Scenario 1 at the Boundaries of the Powerblock 

Area. Cross-section X6400 is the eastern boundary where the combined 

powerblock area and upslope contributing area discharge was applied as 

the time-varying boundary condition. Cross-section X0000 is the western 

(downslope) boundary of the powerblock area near the outlet of the 

hypothetical passive drainage network. 

In Scenario 2, peak runoff during the PMP event was applied to the powerblock area as a timeinvariant steady discharge. This scenario would result in a conservatively high estimate of the 

water-surface elevation during the PMP event. The simulated water-surface elevations at 

cross-sections X5000, X4000, X3000, X2000, and X1000 are shown in Figures B-22 through 

B-26. The water-surface elevations simulated in Scenario 2 (solid lines in Figures B-22 through 

B-26) are always higher than those simulated in Scenario 1 (dashed lines in Figures B-22 

through B-26). 

In both scenarios, the maximum water-surface elevation in and around the powerblock area did 

not exceed 197 ft. During Scenario 1, the water-surface elevation did not approach the 

structures located within the powerblock area (Figure B-20) and would not approach the 

structures in Scenario 2 because the water-surface elevations never exceeded 197 ft and the 

minimum grade elevation of the structures within the powerblock is 200 ft. 
B-24 

Figure B-22. Estimated Water-Surface Elevations at X5000 Resulting from Runoff 

Simulations During the PMP Event 

Figure B-23. Estimated Water-Surface Elevations at X4000 Resulting from Runoff 

Simulations During the PMP Event 
B-25 

Figure B-24. Estimated Water-Surface Elevations at X3000 Resulting from Runoff 

Simulations During the PMP Event 

Figure B-25. Estimated Water-Surface Elevations at X2000 Resulting from Runoff 

Simulations During the PMP Event 
B-26 

Figure B-26. Estimated Water-Surface Elevations at X1000 Resulting from Runoff 

Simulations During the PMP Event 

B.4 References 

Chow, V.T. 1959. Open-Channel Hydraulics. McGraw-Hill, New York. 

Pilgrim, D.H. and I. Cordery. 1993. “Flood Runoff.” Handbook of Hydrology. Chapter 9, 

Maidment, D.R., Editor in Chief, McGraw-Hill, New York. 

Snyder, F.F. 1938. Synthetic Unit-Graphs. Trans. Am. Geophys. Union 19(1938):447-454. 

Soil Conservation Service (SCS). 1972. “Travel Time, Time of Concentration, and Lag.” 

National Engineering Handbook, Section 4: Hydrology. Chapter 15, U.S. Department of 

Agriculture, Washington, D.C. 

U.S. Army Corps of Engineers (USACE). 1994. Flood-Runoff Analysis. Engineer Manual 

1110-2-1417, Department of the Army, Washington D.C. 
Appendix C 

DATA PREPARATION AND WATERSHED MODELING SETUP 

C-1 

APPENDIX C 

DATA PREPARATION AND WATERSHED MODELING SETUP 

This appendix describes the procedures used to prepare hydrological data and set up a 

watershed model to estimate design basis flood events that then can be used for design criteria 

at a proposed nuclear power plant site. The software used in this case study includes the 

Environmental Systems Research Institute’s (ESRI’s) ArcGIS v. 9.2, Environmental Modeling 

Systems, Inc.’s Watershed Modeling System (WMS) Volume 8.0, and U.S. Army Corps of 

Engineers’s Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) 3.2. 

In the following subsections, we describe hydrologic data preparation, delineation and setup of 

the watershed in WMS, and estimation of the probable maximum precipitation (PMP), probable 

maximum flood (PMF), and PMF water-surface elevations. 

C.1 Digital Elevation Model Data Preparation 

C.1.1 Compiling the Digital Elevation Models 

The first step in the data-preparation process involved compiling the 8-digit level Hydrologic Unit 

Code (HUC) boundaries for the drainage area of interest and subsequently identifying and 

collecting source Digital Elevation Models (DEMs) (described elsewhere in this document). For 

this case study, National Elevation Dataset (NED) DEM data at a 30-m resolution were collected 

for the study site. Normally, 10-m DEM data are desired as a starting point for data assembly 

because they provide the highest-level of resolution and accuracy, can be re-sampled to a 

desired and manageable resolution for large watersheds, and can still be available for finerscale modeling work if necessary. The disadvantage of using 10-m DEM data is that their size 

can be burdensome for larger watersheds; however, frequently the effort is worthwhile because 

it allows subsequent work to be based on the same underlying terrain model. For this study 

site, 30-m DEM data were selected because 10-m data were not available for all areas within 

the domain. 

A DEM resolution of 180 m was deemed suitable for demonstrating the methodology. The 

approximately 3000-mi2

 watershed was modeled using approximately 670,000 computational 

grid cells. The individual DEM tiles downloaded from the U.S. Geological Survey (USGS) 

(http://seamless.usgs.gov/) were mosaicked, cleaned, and re-sampled using ArcGIS v.9.2. 

While WMS provides the capability to do this preparatory work, it has been found to be more 

effective to assemble DEM data in ArcGIS and then to present a model-ready DEM to WMS. It 

also should be noted that a beta-version of USACE’s HEC-GeoHMS for ArcGIS software was 

evaluated for this study and was determined to be not yet suitable for production work. 

However, it is expected that in the future, GeoHMS for ArcGIS may become the accepted 

standard for preparing spatial data for HEC-HMS modeling. 

Within ArcGIS, individual DEM tiles were loaded, and the ‘Mosaic to New Raster’ toolbox utility, 

which requires an ArcGIS Spatial Analyst license, was used to bring the terrain model into a 

single dataset. To prepare the DEM data for hydrologic modeling, the Center for Research in 

Water Resources, University of Texas at Austin’s free ArcHydro v. 1.3 ArcGIS toolbox was 

used. 
C-2 

C.1.2 Filling Sinks 

The “Terrain Pre-Processing” tools within ArcHydro (see Figure C-1) offer a number of tools to 

prepare a DEM for best use in a hydrologic model. For example, it is necessary to fill the 

elevation sinks in the DEM to allow for unobstructed flow through the basin. This process also 

is called creating a “depressionless DEM.” Small irregularities, often created artificially during 

preparation of a DEM, may occur because of numerical inconsistencies and, therefore, may not 

represent real depressions. Filling a DEM smoothes out small irregularities and, therefore, 

results in a more realistic flow pattern. To coincide with DEM filling, special considerations can 

be made for natural depression areas. For example, lakes can be uniquely filled to a specified 

elevation before spilling, other natural depression areas can be evaluated for inclusion into or 

exclusion from the terrain-filling process, and known stream locations from another spatial 

dataset such as the National Hydrography Dataset (NHD) can be used to enforce drainage 

patterns into the DEM. It also is possible to incorporate features such as dikes that may not be 

captured in the source DEM. 

For this case study, the 30-m DEM data were re-sampled to 180-m resolution using the ArcGIS 

toolbox utility “Resample,” and conditioned with NHD stream data to enforce stream locations 

using the ArcHydro “DEM Reconditioning” tool. From this point forward, 180-m DEM data were 

used. The DEM was filled using the ArcHydro “Fill Sinks” tool. 

Figure C-1. The ArcHydro v. 1.3 Toolbar Showing the DEM Pre-Processing Tool 
C-3 

C.1.3 Delineation of the Watershed 

A goal in the terrain processing stage is to develop a DEM that has a specific watershed 

boundary that generally matches the HUC boundaries. There is some replication of data being 

produced to meet this goal; however, this was found to be the most effective approach. The 

filled DEM produced by ArcHydro was used to create a flow direction dataset, and then a flow 

accumulation dataset. The processing functions are available under the ArcHydro Terrain 

Preprocessing menu under “Flow Direction” and “Flow Accumulation.” These two datasets 

allow the determination of terrain connectivity, which describes how water flowing over the 

terrain accumulated through overland flow into channels and how the channels themselves are 

connected to others in the drainage system. These datasets also form the basis for determining 

the drainage boundaries. 

The next step is to determine a drainage outlet point in the basin and calculate the upstream 

drainage boundary corresponding to this outlet. The resulting drainage boundary then is used 

to clip the DEM data to the effective study area that can then be used within WMS. The 

resulting DEM-derived drainage boundary should generally resemble the HUC boundaries and 

should be compared and evaluated for their consistency. 

The DEM-generated drainage boundary is used as the final clipping dataset because it is used 

to run the remaining calculations. Using the HUC boundary will likely show some differences 

between flow directions generated because of the differences in the two delineation 

methodologies. There are two approaches that can be used to complete a drainage boundary. 

In one approach, the following sequence of functions from ArcHydro tools needs to be run from 

the Terrain Preprocessing menu: (1) Stream Definition, (2) Stream Segmentation, 

(3) Catchment Grid Delineation, (4) Catchment Polygon Processing, (5) Drainage Line 

Processing, and (6) Adjoint Catchment Processing. After this sequence has been run, the 

interactive selection tool, , can be used to identify the drainage outlet. Alternatively, an ESRIprovided toolbar called “Hydrologic Modeling” (see Figure C-2), which is typically 

accessible by enabling the toolbar under the Tools  Customize menu, can be 

used. The toolbar is available from the following website: 

http://edndoc.esri.com//arcobjects/9.2/CPP_VB6_VBA_VCPP_Doc/COM_Samples_Docs/Spati

alAnalyst/HydrologicModeling/63d45073-3ecb-4b98-afa3-6028fd9ade93.htm. The 

second method was used this case study. 

The “Hydrologic Modeling” toolbar requires specification of the Flow Direction and Flow 

Accumulation datasets under Hydrology  Interactive Properties. Before proceeding with 

watershed delineation, the outlet must be specified. The outlet can be identified interactively by 

displaying the Flow Accumulation dataset and other relevant datasets as shown in Figure C-3 

below. The drainage point, as indicated by other spatial datasets (e.g., USGS blue lines, river 

reach files, or NHD stream lines) that is the closest high-value flow accumulation grid cell should 

be selected as the outlet to ensure agreement with the DEM-derived flow direction and flow 

accumulation datasets. 
C-4 

Figure C-2. Toolbar for the Hydrologic Modeling Drop-Down Menu that Allows Simple 

Interactive Watershed Delineation 

Figure C-3. High-Value Flow Accumulation Values Need to Be Used for Determining a 

DEM-Agreed Drainage Outlet Point. A small area overview (left) of a 

classified flow accumulation grid isolates the high values and a detailed 

grid cell view (right) shows the level of detail required before interactively 

placing a drainage point, ensuring that the selected point agrees with flow 

accumulation data. 

The resulting drainage basin is evaluated and re-created if necessary to ensure consistency 

with the HUCs, and finally is saved to a shapefile. After the watershed delineation is done, the 

watershed boundary dataset is used to clip the filled DEM using the ArcToolbox tool “Extract by 

Mask,” which requires the boundary shapefile and the filled DEM as input. The resulting clipped 

DEM is exported to an ASCIIGRID format file using the “Raster to ASCII” tool available in the 

ArcToolbox. The resulting clipped DEM obtained during this case study is shown in Figure C-4. 
C-5 

Figure C-4. Depressionless DEM Clipped to DEM-Defined Drainage Area 

C.2 Watershed Setup in WMS 

The ASCIIGRID file generated as the last step in the ArcGIS process is opened and loaded into 

WMS via standard File  Open operation. Upon importing, a dialogue may present options for 

(1) smoothing the DEM data (this should be turned off because DEM processing has already 

been done in ArcGIS) and (2) thinning the DEM data (this should be set to 1). 

After loading the DEM data, the first processing step is to produce the flow-direction and flowaccumulation data using the TOPAZ algorithms available in WMS. This step is accomplished 

by setting the module to “Drainage” ( ) and running the TOPAZ modeling routing via the menu 

item DEM  Compute TOPAZ Flow Data (see Figure C-5). The TOPAZ modeling process 

produces flow accumulation results such as those shown in Figure C-6. 
C-6 

Figure C-5. The Flow Direction and Flow Accumulation Data Used for the HEC-HMS 

Data Preparation Are Generated Using the TOPAZ Model in WMS 

Figure C-6. Example Output from the TOPAZ Model Showing DEM-Generated Contour 

Lines and Flow Accumulation Data 
C-7 

As was demonstrated in the ArcGIS processing, once the flow-direction and flow-accumulation 

data are generated, a watershed boundary can be delineated. This process is accomplished in 

two steps. First the overall drainage area is delineated, and then the sub-basins are defined 

within the overall drainage area. The farthest downstream point in the watershed will define the 

extent of the watershed boundary. In WMS, this point is indicated by zooming into the grid-cell 

level, using the “Create Outlet Point” button ( ), and ensuring this location falls upon one of 

the flow accumulation cell points, similar to the operation conducted in ArcGIS. Once the 

drainage outlet is defined, the following commands are executed from the WMS menu: 

DEM  Stream Arcs 

DEM  Define Basins 

DEM  Basins  Polygons 

DEM  Compute Basin Data. 

For a large watershed, these processes may be computationally intensive. 

The case-study watershed was broken into 13 subbasin areas and was created by additional 

outlet points in WMS. Within the “Drainage” module, the “Select Feature Vertex” tool ( ) is 

used to identify the sub-basin outlets. The feature vertex is selected as shown in Figure C-7, 

and is converted to an outlet using the DEM  Node  Vertex menu option. The process is 

repeated for all 13 subbasins. When completed, the subbasins are defined, and statistics may 

be computed by executing the following sequence: 

DEM  Define Basins 

DEM  Basins  Polygons 

DEM  Compute Basin Data. 

The WMS sub-basin delineations for the case-study basin are presented in Figure C-8 and 

Figure C-9. 
C-8 

Figure C-7. Feature Vertex Is Selected and Converted to a Subbasin Drainage Outlet 

Figure C-8. Subbasin Delineation and Associated Labels Within the Primary Drainage 

Area 
C-9 

Figure C-9. The HEC-HMS Schematic View of the Case Study Watershed Within WMS 

The remaining steps for pre-processing spatial data for inclusion into HEC-HMS include 

incorporating land cover and soils data for the purpose of calculating a composite curve 

number, time of concentration, and lag time for each of the 13 subbasins. The soils data used 

in the case study were STATSGO data retrieved from the Penn State Soil Information for 

Environmental Modeling and Ecosystem Management project (see Appendix A). The landover 

data, the 2001 National Land Cover Database (NLCD), were retrieved from the Multi-Resolution 

Land Characteristics Consortium (MRLC) (see Appendix A). Both of these datasets had their 

unique attribute data exported and evaluated against the 1986 Soil Conservation Service (SCS; 

now Natural Resources Conservation Service or NRCS) Table of Runoff Curve Numbers. This 

comparison was made to fit the land cover classifications found in the 2001 NLCD data into the 

SCS curve number framework. The available STATSGO data already were classified into 

one of four hydrologic soil groups. As a requirement for WMS, a table defining specific curve 

numbers for each land cover and hydrologic soil group was constructed and imported to WMS 

(see Table C-1). Both the STATSGO and NLCD data were converted from raster formats to an 

Arc/INFO coverage format and were dissolved so adjacent polygons sharing similar attributes 

could be merged. The resulting data were exported to a shapefile, which then was imported to 

WMS. 

 
C-10 

Table C-1. Integration of SCS Curve Number Values for Specific Hydrologic Soil Groups 

and Land-Cover Types. WMS uses this table to calculate a composite curve 

number for each of the 13 case study subbasins. 

LANDCOVER_CODE DESCRIPTION SOIL_A SOIL_B SOIL_C SOIL_D

11 Open Water 100 100 100 100 

21 Developed, Open Space 39 61 74 80 

22 Developed, Low Intensity 48 66 78 83 

23 Developed, Medium 

Intensity 57 72 81 86 

24 Developed, High Intensity 77 85 90 92 

31 Barren Land 76 85 89 91 

41 Deciduous Forest 43 65 76 82 

42 Evergreen Forest 30 55 70 77 

43 Mixed Forest 30 55 70 77 

52 Shrub/Scrub 30 58 71 78 

71 Herbaceous 30 58 71 78 

81 Hay/Pasture 39 61 74 80 

82 Cultivated Crops 67 77 83 87 

90 Woody Wetlands 100 100 100 100 

95 Emergent Herbaceous 

Wetlands 100 100 100 100 

 

The composite curve numbers for each subbasin were calculated within the WMS Hydrologic 

Modeling Module, Calculators  Compute GIS Attributes. The composite curve number 

calculations were exported to an ASCII text file report for each subbasin. An example of these 

data follows: 
C-11 

========================================================== 

 Runoff Curve Number Report 

 (Generated by WMS) 

========================================================== 

Wed May 21 13:39:14 2008 

Runoff Curve Number Report for Basin 11B 

HSG Land Use Description CN Area Product 

 km^2 CN x A 

D Cultivated Crops 87 48.510 4220.383 

D Deciduous Forest 82 92.978 7624.178 

D Hay/Pasture 80 28.298 2263.807 

D Herbaceuous 78 76.808 5991.003 

D Evergreen Forest 77 218.296 16808.766 

D Mixed Forest 77 20.213 1556.367 

D Developed, Open Space 80 4.043 323.401 

D Woody Wetlands 100 117.233 11723.286 

D Emergent Herbaceuous Wetlands 100 8.085 808.502 

D Shrub/Scrub 78 4.043 315.316 

D Open Water 100 8.085 808.502 

CN (Weighted) = Total Product \ Total Area 

========================================== 

 83.6968 

The Lag Time and Time of Concentration calculations were completed within WMS using the 

SCS method and the Kirpich method for overland flow on bare earth, respectively. Calculators 

 Compute Travel Time  Compute Lag Time/Compute Time of Concentration. A sample of 

output for one of the case-study subbasins follows: 

********************************************************************* 

 Lag Time / Time of Concentration Data Computed in WMS 

 Wed May 21 15:08:08 2008 

********************************************************************* 

BASIN 24B AREA 1535.73 km^2 

Equations: 

Time of Concentration m * 0.00013 * (L^0.77/S^0.385) 22.191 hrs 

Variables: 

m Earth type coefficient 1.000 

L Length of overland flow 253791.070 ft 

S average overland slope 0.002 

********************************************************************* 

 Lag Time / Time of Concentration Data Computed in WMS 

 Wed May 21 15:08:22 2008 

********************************************************************* 

BASIN 24B AREA 1535.73 km^2 

Equations: 

Lag Time L^0.8 * ((((1000/CN)-10) + 1)^0.7)/(1900*sqrt(Y)) 8.418 hrs 

Variables: 

L Watershed length 253791.070 ft 

CN SCS curve number 83.285 

Y Watershed slope in percent 2.917 % 

The resulting subbasin data and the calculated characteristics described above, as well as 

basin area, basin length, shape factor, sinuosity, perimeter, various elevation statistics, basin 

slope, channel slope, and channel aspect, were exported as a GIS attribute table. In addition, 

all the required HEC-HMS model files were generated using “HEC-HMS  Save HMS File” for 

the purpose of operating HEC-HMS independently of the WMS interface. 
C-12 

C.3 Estimation of the Probable Maximum Precipitation using the 

BOSS HMR52 Program 

The PMP is defined as “... theoretically the greatest depth of precipitation for a given duration 

that is physically possible over a given size storm area at a particular geographical location at a 

certain time of year” (Hansen et al. 1982). It is considered to be an upper limit to the amount of 

rainfall that could fall over a specified area and time period. The larger the area, the smaller the 

PMP, because intense rainstorms are limited in size. Another definition of PMP that is more 

operational and relevant to projects such as this one, is “... the steps followed by 

hydrometeorologists in arriving at the answers supplied to engineers for hydrological design 

purposes” (WMO 1973). Schreiner and Riedel (1978) set forth a procedure and results for 

Probable Maximum Precipitation Estimates, United States East of the 105th Meridian in 

Hydrometeorological Report (HMR) 51. Their all-season estimates, for the most rainfall at any 

time of year, were developed for drainage areas from 10 to 20,000 mi2

 and for durations from 

6 to 72 hours. The basic data for the study were developed by a standardized depth-areaduration (D-A-D) analysis of point-precipitation amounts. The data were analyzed and 

processed to create isohyet (i.e., contour) maps of precipitation depths for different size 

drainage areas and time periods. 

The PMP procedure was further developed by Hansen et al. (1982) in Application of Probable 

Maximum Precipitation Estimates – United States East of the 105th Meridian, in HMR 52. HMR 

52 describes a stepwise approach for estimating the temporal and spatial distribution of PMP 

estimates from HMR 51 for an actual drainage basin. This approach takes into account the size 

of the basin and size and orientation of the PMP storm, which is assumed to have an elliptical 

shape. The rainfall depths, estimated from HMR 51, are regarded as the storm-centered, areaaveraged PMP. The PMP pattern encloses the area of the basin as well as an area of residual 

precipitation outside the PMP pattern. After applying the methods described in HMR 52, 

one obtains the drainage-averaged PMP, or the mean precipitation across subbasins and the 

entire basin, including any areas of residual precipitation. The elliptical-shaped storm is 

assumed to be fixed in location over the drainage basin so any potential impact of a moving 

storm on river flow at the outlet is not considered. The use of elliptical patterns for equal rainfall 

areas simplifies the generalization of depth-area relations and helps maintain consistency in 

results among different drainage areas and storm durations. 

For this case study, the watershed described above in Section C.1 was used. The MS-DOS 

software program BOSS HMR52 (BOSS International. 1988) was used to apply the HMR 52 

methodology to the study watershed. First, coordinates for the subbasin boundaries were input 

into the program. The BOSS HMR52 program allows only 100 coordinate points to be entered 

for a basin or subbasin boundary, the coordinates must be given in miles in a user-selected 

coordinate system, and they must be entered manually. The subbasin boundaries shown in 

Figure C-8 above were thinned within ArcGIS while keeping the new subbasin areas resulting 

from the thinned boundaries approximately the same as the original areas. The resulting basin 

and subbasin boundaries are shown in Figure C-10. 
C-13 

Figure C-10. Original and Thinned Boundaries of the Subbasins of the Study Watershed. 

Gray boundaries are from GIS processing and the blue boundaries are the 

simplified ones suitable for input to the BOSS HMR52 program. 

The BOSS HMR52 program provides default values for many of the input parameters, which are 

optimized internally to maximize the PMP for the input basin. The following input values were 

left blank so that the program would find the optimal values: PMP area (mi2

), storm orientation 

(degrees), and storm-center coordinates, which default to the centroid of the study basin. The 

preferred PMP orientation was set at 204 degrees for the study case; these values can be 

obtained from Figure 8 in HMR 52 (Hansen et al. 1982). The initial orientation was 

subsequently modified in the program to maximize rainfall. The number of computation storm 

periods was set to 12 so that the storm duration would be 72 hours, and the temporal 

distribution time interval was set to 120 minutes for 2-hour rainfall increments. The ratio of 

1-hour to 6-hour rainfall for isohyet A of a 20,000 mi2

 storm was set to 0.275; this value can be 

obtained from Figure 39 in HMR 52 (Hansen et al. 1982). The position of the maximum 6-hour 

increment was left blank, resulting in the default position of 7. A multiplier of 1.0 was applied to 

the PMP rainfall, resulting in no change to the baseline values. The PMP values from Table C-2 

were input into the program, and the default temporal order of the 6-hour increments of 

precipitation was used. The corresponding D-A-D curves are shown in Figure C-11. 

Table C-2. PMP Depths for Various Drainage Areas and Durations near the Study 

Watershed (from Schreiner and Riedel 1978) 

Area (mi2) 

Duration 

6 Hours 12 Hours 24 Hours 48 Hours 72 Hours 

10 31.0 37.0 43.8 48.2 51.0 

200 23.0 27.9 35.0 38.0 42.0 

1000 16.9 22.5 28.5 33.5 35.2 

5000 9.7 14.0 19.3 23.8 27.5 

10,000 7.4 11.1 15.8 20.0 23.3 

20,000 5.4 8.8 12.5 16.2 19.2 
C-14 

Figure C-11. The D-A-D Curves for the PMP Values near the Study Watershed. Notice 

that the plot uses a semi-logarithmic scale. 

The study basin PMP estimated by BOSS HMR52 program had a final storm orientation of 

160 degrees, an area of 6500 mi2

, and the isohyetal pattern shown in Figure C-12. The basinaverage rainfall for the 72-hour PMP is shown in Figure C-13. The PMP total rainfall over the 

basin was estimated to be 21.4 in. 

Figure C-12. Isohyet Plot of the PMP over the Study Basin Estimated by the BOSS 

HMR52 Program. The storm center is at the basin centroid, and the storm 

is oriented to maximize precipitation over the basin. 
C-15 

Figure C-13. The Hyetograph of Basin Aggregate PMP Rainfall Depths in 2-Hour 

Increments 

C.4 Estimation of the Probable Maximum Flood Using HEC-HMS 

The PMF is defined as “... [t]he hypothetical flood (peak discharge, volume, and hydrograph 

shape) that is considered to be the most severe reasonably possible, based on comprehensive 

hydrometeorological application of probable maximum precipitation and other hydrologic factors 

favorable for maximum flood runoff such as sequential storms and snowmelt” (ANS 1992). 

For the study basin, the input files created at the end of watershed setup in WMS 

(see Section C.2 above) were opened in HEC-HMS. Additional input for subbasin precipitation 

corresponding to the optimized PMP event and parameters related to rainfall-runoff generation 

and routing also are needed. The PMP hyetographs were input into HEC-HMS as a separate 

“gauge” for each subbasin. Each PMP hyetograph was constructed using 40 percent of the 

PMP depths during the first 72 hours, followed by a dry 72-hour period, and finally followed by 

the full 72-hour PMP storm (ANS 1992). 

The rest of the HEC-HMS parameters control how much runoff is generated (via loss rates), 

how runoff generated at any point in a subbasin gets translated to the outlet of the subbasin (via 

the rainfall-to-runoff transformation function), and how the runoff entering the channel or stream 

network is routed to the site (via channel routing). These parameters or hydrologic factors, 

which are favorable for maximum flood runoff, correspond to minimal loss (such that most or all 

of the PMP rainfall is converted to runoff), a quick transformation function (such that even runoff 

generated farther away from the outlet of a subbasin arrives quickly at the outlet), and quick 

channel routing (such as very small lag time or instantaneous routing in streams). These 

favorable assumptions lead to a conservative estimation of the PMF. The most conservative 

PMF scenario, therefore, results from assumption of no loss, no transformation, and 

instantaneous routing. It should be obvious that in any watershed of appreciable size, these 

three assumptions result in a PMF that is as conservative as it can be made. These 

assumptions can be modified and made more site-specific when hydrologic information and 
C-16 

data are available to support estimation of the loss rates, rainfall to runoff transformation 

functions, and channel routing parameters. For further discussion of how a more site-specific 

PMF may be estimated, see Sections 1.4 and 2.2.2 of this report. 

For this case study, four scenarios of hydrologic factors that control the characteristics of the 

estimated PMF (in terms of peak discharge, volume, and hydrograph shape) were used in HECHMS. The four scenarios are described below: 

1. No loss, no rainfall-to-runoff transformation, and instantaneous routing in channels 

2. No loss, SCS unit-hydrograph rainfall-to-runoff transformation, and instantaneous routing 

in channels 

3. No loss, SCS unit-hydrograph rainfall-to-runoff transformation with adjustments made to 

account for dominant nonlinearity effects during a PMP event, and instantaneous routing 

in channels 

4. Loss rates based on the SCS curve number method, SCS unit-hydrograph rainfall-torunoff transformation with adjustments made to account for dominant nonlinearity effects 

during a PMP event, and instantaneous routing in channels. 

Notice that the most conservative PMF would be generated by scenario 1. The next most 

conservative PMF would result from scenario 3. There are two mutually compensating factors 

in scenarios 2 and 4—no loss in scenario 2 increases the volume of runoff when compared to 

the curve number loss rate method in scenario 4 that results in a reduction of the volume of 

runoff; the SCS unit hydrograph adjusted for nonlinear effects results in a quicker and more 

peaked PMF hydrograph compared to the traditional SCS unit hydrograph. Therefore, the 

relative severity of the PMF resulting from scenarios 2 and 4 cannot be predicted a priori; 

however, the PMF for these two scenarios should be less conservative that that from scenario 

3. 

Figure C-14 shows the HEC-HMS-simulated PMF hydrographs at the outlet of the study basin. 
C-17 

Figure C-14. Estimated PMF Hydrographs for the Four Scenarios Used in the HEC-HMS 

Note that scenario 1 is the most conservative, and therefore bounding, PMF for the study basin. 

The next most conservative PMF corresponds to scenario 3. The effect of using loss rates is 

evident in the early part of the PMF hydrograph (scenario 4), where the volume of runoff is 

significantly less than that for scenario 3, which used no loss. Notice however, that the effect of 

the loss rate is not very significant during the full PMP storm (PMFs for scenarios 3 and 4 are 

almost identical). Scenario 3 used the traditional SCS unit hydrograph, which is less peaked 

and has a longer lag time compared to the SCS unit hydrograph modified for nonlinear effects, 

and the difference is significant in terms of the early arrival of the flood and a larger peak 

discharge for the modified SCS unit hydrographs. 

C.5 Estimation of the PMF Water-Surface Elevation using HEC-RAS 

The next step in determining the flood hazard from PMF involves estimating the water-surface 

elevation near the site. Although an approximate PMF water-surface elevation may be 

estimated if a stage-discharge relationship for the stream near the site is available, the preferred 

approach is to use the HEC-HMS-estimated flood discharges as input to the USACE Hydrologic 

Engineering Center River Analysis System (HEC-RAS) model. The HEC-RAS model is a 

one-dimensional hydraulic model that needs channel geometry descriptions and hydraulic 

properties (e.g., the Manning’s roughness coefficient) as input. An example application, 

although for a dam breach-generated flood, is described in Appendix D. 
C-18 

The HEC-RAS model is capable of simulating both steady- and unsteady-flow scenarios. In 

unsteady-flow simulations, complete flood discharge hydrographs input at multiple locations on 

the stream network can be used to estimate a transient water-surface elevation at each cross 

section used to define the stream network. An alternate approach is to use a steady-flow 

simulation with discharges at known points within the stream network set to the peak PMF 

discharge estimated previously by HEC-HMS. The water-surface elevations computed for the 

steady-state scenario described above are conservative estimates of the maximum watersurface elevations because the water-surface elevations from the corresponding unsteady-flow 

simulation, which uses the complete hydrographs, asymptotically approach those for the steadyflow scenario. Therefore, a steady-state simulation may be performed to arrive at a 

conservative estimate of the PMF water-surface elevations near the site. 

C.6 Combined-Events Flooding 

The American Nuclear Society (ANS 1992) recommends that a combination of events should be 

used to estimate design-basis floods at proposed power reactor sites. These combinations are 

described in more detail in Section 2.9 of this report. 

C.7 References 

American Nuclear Society (ANS). 1992. Determining Design Basis Flooding at Power Reactor 

Sites, ANSI/ANS-2.8-1992. ANS Standards Committee Working Group ANS-2.8, American 

Nuclear Society, La Grange Park, Illinois. 

BOSS International. 1988. BOSS HMR52 Users Manual. BOSS International, Inc. 

Madison, Wisconsin. 

Hansen E.M., L.C. Schreiner, and J.F. Miller. 1982. Application of Probable Maximum 

Precipitation Estimates – United States East of the 105th Meridian. Hydrometeorological Report 

No. 52 (HMR 52), National Weather Service, Washington D.C. 

Schreiner L.C. and J.T. Riedel. 1978. Probable Maximum Precipitation Estimates – 

United States East of the 105th Meridian. Hydrometeorological Report No. 51 (HMR51), 

National Weather Service, Washington D.C. 

World Meteorological Organization (WMO). 1973. Manual for Estimation of Probable Maximum 

Precipitation. WMO No. 3332, Operational Hydrology Report No. 1, Geneva, Switzerland. 
Appendix D 

FLOODING FROM DAM BREACHES AND FAILURES: 

A CASE STUDY 

D-1 

APPENDIX D 

FLOODING FROM DAM BREACHES AND FAILURES: A CASE STUDY 

Upstream dam breaches or failures are flooding mechanisms that should be considered when 

estimating the design-basis flood at a proposed nuclear power plant site. Dam breach usually 

refers to a structural failure of the embankment that may be caused by a hydrologic event 

(e.g., overtopping of the dam during a flood, leading to erosion of the dam face or piping and 

resulting in erosion of the embankment) or a seismic event. Because a seismic event usually is 

not expected to occur coincident with a large flood event, it is justified to assume that inflow into 

the reservoir impounded by the dam would be greater during a hydrologic failure than those 

during seismic failures. Therefore, assuming that the two causes of dam failure (i.e., hydrologic 

and seismic) would result in breaches that generate similar floods from release of stored water 

only, the flood from a hydrologic dam failure—caused by release of stored water augmented by 

the waters of a large flood, usually the probable maximum flood (PMF)—would bound those 

from the seismic failure. Consequently, in this study, we only describe a flood generated by a 

hydrologic dam failure accompanied by a PMF. The general approach for estimation of floods 

caused by non-hydrologic dam failures remains the same except that an appropriately selected 

concurrent flood discharge would be considered in place of the PMF (see Appendix H for 

recommendations). Non-hydrologic or sunny-day dam failures are briefly described in 

Chapter 3. 

In this study, the U.S. Army Corps of Engineers’ (USACE’s) Hydrologic Engineering Center 

River Analysis System (HEC-RAS) computer software was used to estimate the water-surface 

elevation in the modeled river reach. As stated in Chapters 3 and 5 of this report, the selection 

of methods, data, and models should be carried out using a careful considerations of sitespecific circumstances. The location of the site with respect to the dam breach would be an 

important consideration because the characteristics of the flow field may be different depending 

on the relative location of the site. For example, if the site is located on one of the banks of a 

river, a one-dimensional hydraulic model such as HEC-RAS may be appropriate because the 

estimation of flood water-surface elevation in the river would be the primary consideration. On 

the other hand, if the site were located downstream of a dam or embankment at a lower 

elevation such that breach of the embankment would result in water spreading out to inundate 

the site and its facilities, a two-dimensional hydraulic model may be more appropriate. The 

following discussion considers the first of the two examples described in this paragraph. 

D.1 Dam Failure Scenarios 

Two scenarios of dam failure should be considered: (1) failure of individual dams upstream of 

the site and (2) cascading or domino-like failures of dams upstream of the site. In the first 

scenario, one or more dams may be located upstream of the site but on different tributaries so 

the flood generated from the failure of an individual dam would not flow into the reservoir 

impounded by another dam. These individual dam failures should be analyzed together 

because it is likely that a large flood on one tributary would coincide with similar large floods in 

adjoining tributaries. In the second scenario, failure of an upstream dam may generate a flood 

that would become an inflow into the reservoir impounded by a downstream dam and may result 

in failure by overtopping of the downstream dam. If several such dams exist in a river basin, 

each sequence of dams within the river basin could fail in a cascade. Each of these cascading 

failure sequences should be investigated to determine one or more sequences of dam failures 

that may generate the most severe flood at the site. Simplified estimates of the total volume of 
D-2 

storage in each of the potential cascades should provide a good indication of the most severe 

combination. In multiple cascades that cannot be separated by simple hydrologic reasoning, all 

of the candidate cascades that are comparable in terms of their potential to generate the most 

severe flood at the site should be simulated using the methods described in this appendix. The 

most severe flood at the site resulting from these cascades should be used to determine the 

design-basis flood. 

For the example shown in Figure D-1, there are five dams upstream of the plant site. Because 

Dams 1, 2, and 4 are on different tributaries, they should be analyzed for individual failure. 

Dam 5 also could fail individually. On the other hand, the following cascading failures are 

possible: (1) C1: Dams 1, 3, and 5, (2) C2: Dams 2, 3, and 5, (3) C3: Dams 1 and 2 

individually followed by Dams 3 and 5, and (4) C4: Dams 4 and 5. 

Figure D-1. An Example of Dam Locations Upstream of a Plant Site 

It can be reasoned that the individual failures of Dams 1, 2, and 4 should be bounded by 

cascading failures C1, C2, and C4, respectively. Individual failure of Dam 5 should be bounded 

by all four cascading failure scenarios. Therefore, only the relative severity of the four 

cascading failure scenarios needs to be considered further. 

Depending on the storage capacities of the reservoirs impounded by dams in a given cascading 

scenario, it may be reasoned that the scenario that would release the largest volume of stored 

water may likely lead to the most severe flooding scenario. However, the distance a flood has 

to travel to reach a plant site also may affect the severity of the flood at the site. If a definite 

conclusion cannot be reached, all possible cascading scenarios should be simulated to 

determine the most severe scenario. 
D-3 

D.2 HEC-RAS Model Setup 

The purpose of this simulation is to illustrate the process used to estimate the peak watersurface elevation near a site. The causative event is a dam breach scenario resulting from 

overtopping during a PMF in the river basin upstream of the site. To accomplish this, at a 

minimum, the river network from a point just downstream of the most upstream dam postulated 

to fail to a point just downstream from the site needs to be modeled. The modeled river reach 

or reaches should be divided into a series of cross sections whose shape and elevation may be 

derived from either a Digital Elevation Model (DEM) and/or survey data (see Appendix A for 

some of these data sources). The dam-breach flood most likely would overflow the normal 

stream banks into the floodplains. The cross sections, therefore, should extend far enough on 

either side of the modeled river reach to ensure that the expected top width of flood discharge is 

contained within the cross section represented in the model. The HEC-RAS model also 

requires Manning’s roughness values for the stream; the roughness values may be varied along 

the cross section to represent heterogeneity between the normal channel and the floodplain. 

Stage-volume relationships for the impounded reservoir may be estimated if a DEM or 

topographic map predating the dam construction is available. In the absence of such data, 

surveys may need to be performed. 

An initial water-surface elevation, usually assumed to be the normal or full-pool elevation, for all 

dams and their respective impoundments should be determined. The downstream boundary 

condition is typically held at some reasonable value, such as the normal depth (i.e., the depth of 

flow when the water-surface slope is equal to the bed slope). Lateral and base flows also 

should be specified for all tributaries that flow into the modeled river reach; however, for the 

modeled reach, there were no tributaries. 

For this study, a different watershed layout than the one shown in Figure D-1 above, there are 

two dams located in the river reach being simulated; the upstream dam is Dam 1, and the 

downstream dam is Dam 2. Although there were two more dams located farther upstream, the 

storage capacities of their reservoirs were minor compared to those of the two dams being 

simulated. It was conservatively assumed that (1) the flood resulting from individual breaches of 

these dams would become the inflow for the reservoir impounded by Dam 1 and (2) the peak 

discharge of the inflow would coincide with the peak discharge of the outflow following the 

breach of Dam 1. The geometry of the modeled river reach including locations of the cross 

sections is shown in Figure D-2. Table D-1 lists the characteristics of the reservoirs impounded 

by the two dams. 

D.3 Breach Geometry 

Wahl (1998) compiled a list of methods to predict dam breach geometries based on case 

studies. These methods require several inputs related to the hydraulic and structural properties 

of the dam that are listed in the report. Wahl’s methods produce estimates of breach geometry 

parameters that vary significantly. Therefore, several of these methods should be used to 

estimate the range of breach parameters. In his report, Wahl mentions several additional 

studies that should be consulted to select an appropriate method for an individual dam based on 

the dam’s design characteristics. 

Breach geometry and development parameters (e.g., center station, final bottom width and 

elevation, left- and right-side slopes, and the duration for full development of the breach) were 

specified for the two dams, and both were set to breach in HEC-RAS. 
D-4 

Figure D-2. The HEC-RAS Geometry of the Study Reaches for Illustration of Flooding 

from a Postulated Cascading Dam Breach. The hypothetical site is located 

near the downstream end of Reach 1. 

Table D-1. Characteristics of Reservoirs Impounded by Dams 1 and 2 

Characteristic Dam 1 Dam 2 Total 

River Mile 260.1 258.1 to 222.0 NA 

Base Lateral Flow (cfs) 10,000 560,000 570,000 

Base Flow (ac-ft) 89,256 4,998,347 5,087,603 

Initial Elevation (ft) 495.0 342.1 NA 

Initial Storage (ac-ft) 8,022,500 3,450,000 11,472,500 

 

D.4 Simulation Results 

The shapes of the reservoir cross sections upstream of their respective dams at the start of the 

simulation are shown in Figures D-3 and D-4. The initial flow depth profile downstream of 

Dam 2 is shown in Figure D-5. Discharge from Dam 1 following its breach is the upper 

boundary condition. This discharge is characterized as a T.S. Gate Opening, which 

approximates a breach. The downstream condition is set to a normal flow conditions (i.e., the 

bed slope and friction slope are in equilibrium at the downstream end). The simulation was 

carried out for 108 hours to capture the peak discharge in the river near the plant site. The 
D-5 

stage and flow hydrographs for the upper and lower end of the modeled reach are shown in 

Figures D-6 and D-7. 

Figure D-3. Cross Section of the Reservoir Impounded by Dam 1 Upstream of the Dam 

at the Start of the Simulation 
D-6 

Figure D-4. Cross Section of the Reservoir Impounded by Dam 2 Upstream of the Dam 

at the Start of the Simulation 

Figure D-5. Water-Surface Profile in the Reach Downstream of Dam 2 at the Start of the 

Simulation. The hypothetical site is located near the downstream end of 

Reach 1. 
D-7 

Figure D-6. Stage and Discharge Hydrographs at the Top of the Reach Downstream of 

Dam 2 

Figure D-7. Stage and Discharge Hydrographs at the Location of the Hypothetical Site 
D-8 

Using the cross section at River Mile 99.406 as the location of the proposed site, the following 

flood information is derived from the analysis: (1) a peak discharge of 1.9 million cfs occurring 

59.5 hours after the start of the simulation and (2) a corresponding still water-surface elevation 

of 87.3 ft. 

D.5 References 

Wahl T.L. 1998. Prediction of Embankment Dam Breach Parameters: A Literature Review and 

Needs Assessment. DSO-98-004, Dam Safety Research Report, Water Resources Research 

Laboratory, U.S. Department of the Interior, Bureau of Reclamation Dam Safety Office, 

Washington, D.C. 
Appendix E 

FLOODING FROM STORM SURGES: A CASE STUDY 

 E-1

APPENDIX E 

FLOODING FROM STORM SURGES: A CASE STUDY 

A storm surge is the rise in water-surface elevation along shorelines produced by the shear 

force of the storm winds. Areas of the Atlantic and Gulf coasts experience several hurricanes 

every year. In other locations, including inland locations, storm surges can be caused by severe 

wind storms or moving squall lines. 

This appendix describes a method for estimating the probable maximum storm surge (PMSS). 

A PMSS is the surge that results from a combination of meteorological parameters of a probable 

maximum hurricane (PMH), a probable maximum wind storm, or a moving squall line and has 

virtually no probability of being exceeded in the region involved (NRC 2007). The PMH is a 

hypothetical, steady-state hurricane having a combination of values of meteorological 

parameters that will give the highest sustained wind speed that can probably occur at a 

specified coastal location (Schwerdt et al. 1979). Schwerdt et al. (1979) describe procedures to 

estimate the PMH wind field at any desired location along the Atlantic and Gulf Coasts of the 

United States. 

E.1 Estimation of the PMH 

The parameters that describe the PMH wind field are the difference between the peripheral 

pressure and the central pressure (Δp = pw - p0), the radius of maximum winds (R), the forward 

speed (T), and the track direction (θ). The peripheral pressure is fixed at 30.12 in. Hg or 

1020 mb. In Table 3.2 of their report, Schwerdt et al. (1979) describe a step-by-step method for 

determining the PMH wind field using a set of calculation sheets. The procedure is semigraphical in that a set of values from graphs and maps must be read and used in the calculation 

sheets. In this study, the method developed by Schwerdt et al. (1979) was implemented in 

spread-sheet software to facilitate the calculations. 

E.2 Estimation of the PMSS from the PMH Windfield 

The National Oceanic and Atmospheric Administration National Weather Service has developed 

a model named Sea, Lake, and Overland Surges from Hurricanes (SLOSH). Details of the 

SLOSH model are described by Jelesnianski et al. (1992). The model was developed as a realtime surge forecasting capability for emergency planning. It is a numerical model that 

approximately solves vertically averaged flow equations and yields an estimate of the elevation 

of the water surface. The water surface responds to changes in atmospheric pressure, wind 

and bottom stresses, bathymetry, and Coriolis effects. Advection terms are removed from the 

governing equations under the assumption that atmospheric pressure gradients and barotropic 

and boundary stresses are the dominant factors affecting surge elevations. The model uses a 

finite difference numerical scheme to estimate time-varying surge levels at discrete locations. In 

their publication, Jelesnianski et al. (1992) describe the computational mesh as being based on 

polar coordinates; however, the model has evolved and now allows parabolic and hyperbolic 

configurations. The meshes allow for variable spatial resolution where the mesh becomes finer 

in the shoreward direction and is coarser away from the shore in open waters. 

A set of SLOSH simulations based on variation in hurricane parameters allows development of 

a maximum envelope of water (MEOW), which is defined as the maximum water-surface 

elevation at any given location during the simulation of storm surge from a hypothetical 
 E-2

hurricane. Therefore, a MEOW map can be thought of as a map of peak water-surface 

elevations for a simulated hurricane specified by a set of parameters that include storm 

category, storm direction, forward speed, and initial tide level. 

MEOWs can be generated for several hypothetical hurricanes of a given Saffir-Simpson 

category. A map that shows the maximum water-surface elevations over the grid chosen from 

all these simulations for a given category of hurricanes is called the maximum of the MEOWs 

(MOM). Therefore, for any given area of interest, there will be five MOMs, one for each 

category of hurricanes. 

The MEOW and MOM concepts were adapted for use with the PMH to estimate maximum 

water-surface elevations. Because PMH does not have an associated Saffir-Simpson category, 

combinations of storm direction and forward speed were used in this study. As estimated from 

the procedure described by Schwerdt et al. (1979), a PMH also has an associated range of 

radius of maximum winds. Therefore, a set of SLOSH runs was made by varying the storm 

direction, its forward speed, and the radius of its maximum winds. The maximum water-surface 

elevation at each grid cell during the simulation was selected to create a map analogous to a 

MOM map. 

E.3 Details of SLOSH Simulations 

For the hypothetical drainage basin used for case studies described in the preceding 

appendices of this report, the characteristics shown in Table E.1 were determined from 

Schwerdt et al. (1979). 

A series of SLOSH simulation were performed with a combination of the following T, θ, and R 

values: 

• T = 9, 13, 17, 21, and 25 knots 

• θ = 80, 107.5, 135, 162.5 and 190 degrees 

• R = 7, 11, 15, 19 and 23 nautical miles. 

A SLOSH basin corresponding to the location of the hypothetical drainage basin was used. A 

set of MATLAB scripts was developed for pre-processing of data for input into the SLOSH 

model. Using the T, θ, and R values listed above, 125 SLOSH storm track files were prepared. 

These files were uniquely named pmhNNNN.trk, where NNNN was a four digit run identifier in 

the range of 1001 to 1125. The SLOSH runs were carried out in a batch process. 

Each SLOSH simulation took 7 to 8 minutes of central processing unit time to complete. The 

SLOSH binary output was stored in a pair of files named pmhNNNN.rex and pmhNNNN.env. 

The outputs were examined using SLOSH Display. The envelope of high water (EHW) was 

exported to a shapefile for post-processing with ArcGIS. Figure E-1 shows the PMH MOM 

water-surface elevations. 
 E-3

Table E-1. Characteristics of the Hypothetical Drainage Basin Used for Case Studies in 

Preceding Appendices of this Report (determined from Schwerdt et al. 1979) 

Characteristic Symbol Study Basin Reference/source: Schwerdt et al. (1979) 

Coriolis Parameter 

(sec-1) 

f 7.94 × 10-5 f = 2 Ω sin(ψ) where 

Ω = 7.29 × 10-5 rad/s 

Peripheral Pressure 

(in. Hg) 

Pw 30.25 Section 2.2.2 

Central Pressure 

(in. Hg) 

Po 26.25 Figure 2.2 

Radius Max Winds 

(nm) 

R 7.5-23 Figure 2.5 

Forward Speed (kt) T 7-24 Figure 2.7 

Track Direction 

(degrees clockwise 

from north) 

θ 70-205 Figure 2.8 

Density Coefficient K 69 Figure 2.11 when Pw and Po are expressed in 

in. Hg and R in nm. 

Maximum Gradient 

Winds (knots) 

Vgx 138.24 Equation 2.2: 

Vgx = K (Pw - Po)

1/2 – R f/2 

 

Figure E-1. The PMH MOM Water-Surface Elevations for the Study Watershed 
 E-4

E.4 References 

Jelesnianski C.P., J. Chen, and W.A. Shaffer. 1992. SLOSH: Sea, Lake, and Overland Surges 

from Hurricanes. NOAA Technical Report NWS 48, National Oceanic and Atmospheric 

Administration National Weather Service, Silver Spring, Maryland. 

Schwerdt R.W., F.P. Ho, and R.R. Watkins. 1979. Meteorological Criteria for Standard Project 

Hurricane and Probable Maximum Hurricane Windfields, Gulf and East Coasts of the 

United States. NOAA Technical Report NWS 23, National Oceanic and Atmospheric 

Administration, National Weather Service, Silver Spring, Maryland. 

U.S. Nuclear Regulatory Commission (NRC). 2007. Standard Review Plan for the Review of 

Safety Analysis Reports for Nuclear Power Plants. NUREG-0800, LWR Edition, Section 2.4.5, 

“Probable Maximum Surge and Seiche Flooding,” Washington, D.C. 
Appendix F 

FLOODING FROM A SEICHE: A CASE STUDY 

F-1 

APPENDIX F 

FLOODING FROM A SEICHE: A CASE STUDY 

Generally, a seiche is defined as an oscillation of the water surface in an enclosed or semienclosed body of water initiated by an external cause (Wüest and Farmer 2003; Scheffner 

2008). Once started, the oscillation may continue for several cycles; however, over time it 

gradually decays because of friction. 

External initiators or forcings that can cause a seiche include barometric fluctuations, rapid 

changes in wind direction, storm surges, and tsunamis. An external, local seismic event also 

could result in “sloshing” of the water in a reservoir or basin that could lead to a seiche (USGS 

2009). While the amplitude of a seiche is usually small, resonance may lead to large 

oscillations if the frequency of the forcing matches one of the natural periods of oscillation of the 

waterbody. 

Because the depth of a waterbody typically is small in comparison to the wave length, seiches 

are generally characterized by shallow water waves. The velocity of the wave is given by the 

term (gh)1/2, where g is the acceleration due to gravity and h is the water depth. The natural 

oscillation period of an enclosed, rectangular basin can be estimated from Merian’s formula 

(Scheffner 2008): 

T୬ ൌ ଶL

୬ ඥ୥୦ (F-1) 

In this formula, L is the length of the basin, and n is number of nodes in the standing wave. The 

simplest mode of oscillation of a waterbody is at the fundamental oscillation period, in which the 

standing wave has one node (n=1 in Merian’s formula). To estimate the oscillation period for an 

open rectangular basin, Scheffner (2008) modified Merian’s formula as follows: 

Tnൌ ଶL

ሺଵାଶ୬ሻඥ୥୦ (F-2) 

In this modified formula, the fundamental period corresponds to n=0. 

F.1 Estimating the Effects of Seiche in a Waterbody 

An estimate of the natural oscillation period of a reservoir, lake, or bay may be obtained by 

applying Merian’s formula. This period may then be compared to the periods of external 

forcings expected in the vicinity of the waterbody. If the two periods are close in magnitude, a 

partial to complete resonance may occur, thus amplifying the seiche. 

Merian’s formula and its modified form provide approximations only, and both formulas are 

based on the assumptions that the waterbody is rectangular in shape and has a uniform water 

depth. The natural oscillation periods of a waterbody strongly depend on its geometry and 

bathymetry; therefore, Merian’s formula and its modified form should be applied carefully. For 

more complex basin geometries and bathymetries, numerical modeling of water waves may be 

needed (Scheffner 2008). Rao and Schwab (1976) presented such a solution for Lake Ontario. 

Scheffner (2008) describes more recent hydrodynamic models that may be applied to estimate 

lake and coastal seiche water levels. These models require detailed bathymetry data, and 
F-2 

should be applied at sites where the approximate methods provided by Merian’s formula and its 

modified form do not conclusively rule out flooding hazards from seiche. 

Figure F-1 shows a lake that is used to demonstrate the method described above. The lake is 

approximately 1.82 mi long, has a surface area of approximately 297 ac, and a volume of 

approximately 7067 ac-ft. The pool elevation is 265 ft above mean sea level (MSL). 

Figure F-1. A Hypothetical Reservoir Used to Demonstrate the Estimation of a Potential 

Seiche Period 

The dimensions of an equivalent rectangular lake of uniform depth may be obtained by 

assuming the length, volume, and surface area of the equivalent lake to be equal to the 

corresponding characteristics of the reservoir shown in Figure F-1. The width and the depth of 

the equivalent rectangular lake are found by dividing the surface area by the length and by 

dividing the volume by the surface area. The obtained dimensions of the equivalent rectangular 

lake follow: the length is 1.82 mi, the width is 0.26 mi, and the average depth is 23.8 ft. 
F-3 

Using Merian’s formula for enclosed waterbodies as stated above, the fundamental oscillation 

period with one node (n=1) for the equivalent rectangular lake is estimated to be approximately 

11.5 min. The natural oscillation periods of expected external forcings, such as synoptic storm 

patterns, change in wind directions, and seismic activity expected in the vicinity of the lake, also 

should be determined. If the period of an external forcing is approximately equal to that of the 

lake, amplified seiche activity caused by resonance may occur in the lake. 

More detailed investigations for seiche activity in the lake may be required if resonance is 

expected and if there is relatively little margin between the lake pool level and the site grade. 

F.2 References 

Rao D.B. and D.J. Schwab. 1976. “Two Dimensional Normal Modes in Arbitrary Enclosed 

Basins on a Rotating Earth: Application to Lakes Ontario and Superior.” Philosophical 

Transactions of the Royal Society of London, A: Mathematical and Physical Sciences 281:63-

96. 

Scheffner N.W. 2008. “Water Levels and Long Waves.” In: Demirbilek, Z., Coastal 

Engineering Manual, Part II, Coastal Hydrodynamics Chapter 5-6 , Engineer Manual 1110-2-

1100, U.S. Army Corps of Engineers, Washington, D.C.. 

United States Geological Survey (USGS). 2009. Seismic Seiches. Available at 

http://earthquake.usgs.gov/learning/topics/seiche.php. Accessed May 26, 2009. 

Wüest A. and D.M. Farmer. 2002. “Seiche.” McGraw-Hill Encyclopedia of Science and 

Technology, 9th Edition, McGraw-Hill Companies, New York. 

Appendix G 

FLOODING FROM ICE-INDUCED EVENTS: A CASE STUDY 

G-1 

APPENDIX G 

FLOODING FROM ICE-INDUCED EVENTS: A CASE STUDY 

Ice events can lead to two scenarios involving ice jams or dams that may result in flooding. In 

one scenario, ice jams or dams that form upstream of a site may collapse, thereby causing a 

flood that may affect a proposed nuclear power plant site. In the other scenario, ice jams or 

dams may form downstream of a site, causing a blockage and a backwater effect that may 

reach the site. Both of these scenarios may be simulated using the U.S. Army Corps of 

Engineers’ (USACE’s) Hydrologic Engineering Center River Analysis System (HEC-RAS) 

software. 

G.1 Historical Ice Events 

The Ice Jam Database (USACE 2009a) contains information on historical ice jams and dams, 

and can be queried to obtain information regarding historical ice events. For example, a query 

for ice events in the state of Virginia returned 22 historical events from water years 1917 to 1990 

(USACE 2009b). The description field of the query results describes the events and frequently 

includes flood stage information. The information returned for the 1990 ice event in Virginia is 

shown in Figure G-1. 

When assessing the potential for flooding at a proposed nuclear power plant site, information 

obtained from the Ice Jam Database should be used to determine the most severe historical icejam or ice-dam conditions, including the dam height and flood stages. These properties should 

be used then to postulate a hypothetical ice jam or ice dam near the proposed site. 

G.2 Frazil Ice 

Frazil ice forms in supercooled, turbulent water that is free of ice and snow cover (USACE 

2002). Frazil ice crystals appear as elongated disks throughout the depth of the stream; these 

disks gradually stick together to form large ice floes and jams. For supercooling to occur, the air 

temperature usually must be 18oF or lower. 

Frazil ice is not related directly to flooding; however, it can be an important precursor to the 

formation of ice jams or dams. Therefore, the vicinity of a proposed site should be analyzed for 

the existence of conditions that may support the formation of frazil ice. The presence of freeflowing water, such as a stream, and low temperatures (i.e., 18oF or lower) are two of the most 

important conditions that could lead to the formation of frazil ice. 

Air temperature data for meteorological stations located near the site should be collected. The 

National Oceanic and Atmospheric Administration National Climatic Data Center (NCDC) 

archives daily air temperature data that can be searched and obtained interactively at the NCDC 

website (NCDC 2009). 
G-2 

Figure G-1. Details of the December 30, 1989, Ice Jam in Virginia Returned from the Ice 

Jam Database 

For all NCDC stations, the following air temperature data characteristics should be determined: 

minimum daily mean air temperature, number of days the temperature was below freezing, 

maximum duration of freezing spells, and maximum duration of spells during which daily mean 

air temperature was at or below 18oF. These characteristics may be used to determine whether 

the water temperature near the proposed site can fall to near freezing levels and if sustained 

cold spells are possible that may be suitable for formation of frazil ice. 
G-3 

G.3 Bounding Analysis 

Combined with the historical data from the Ice Jam Database, air temperature characteristics 

(see Section G.2) can be used to determine that the site does not experience conditions 

suitable for formation of frazil ice and ice jams or dams, specifically if there are no records of ice 

jams or dams in the vicinity, if the minimum air temperatures remain substantially above 

freezing, and if there are no periods when the air temperature is 18oF or lower. However, if the 

data do not conclusively demonstrate the absence of conditions that could lead to the formation 

of frazil ice, the potential for ice jam and dam formation in the vicinity of a proposed site should 

be investigated further. 

More detailed analysis for flooding from ice events would need to consider whether the most 

severe ice-event-induced flooding is bounded by another flooding mechanism that is relevant to 

the proposed site. In appreciably sized watersheds that have water-storage or flood-control 

impoundments, ice jams and dams may be expected to be smaller in size and, therefore, may 

cause floods that are smaller than those caused by breaches of impounding dams. In these 

situations, an analysis of the size of the flood that could be caused by breaches of impounding 

dams upstream of the site should be undertaken (see Appendix D). Results indicating that a 

flood resulting from breach of impounding dams would be larger than that from an ice event 

could be justification for not analyzing ice-jam or ice-dam floods in greater detail. However, if 

such a bounding flood is not found, the potential for ice-event-induced floods should be 

analyzed as described below. 

G.4 Upstream Breach of an Ice Dam 

The most severe historical conditions reported in the Ice Jam Database should be used to 

determine whether the resulting flood is bounded by floods from other upstream causal events 

such as the probable maximum flood and floods generated by upstream dam breaches. 

If the floods from other causal events are unambiguously larger than that caused by the most 

severe ice jam or dam, the analysis should be documented, and no further analysis of the ice 

event would be needed. Otherwise, the data should be used to specify a hypothetical ice jam or 

dam upstream of the site. The breach of the jam or dam should be postulated conservatively so 

the release of impounded water would maximize the flood. The water-surface elevation in the 

stream reach adjacent to the proposed site should be simulated using the methods described in 

Appendix D. 

G.5 Downstream Ice Jam and Resulting Backwater 

The most severe ice jam or dam, estimated as discussed above and then placed downstream of 

the site on the adjoining stream, should be used to postulate conditions that may result in the 

most severe backwater profile adjacent to the proposed site. The most severe backwater 

conditions at the site would occur during an upstream flood just prior to the breach of the ice jam 

or dam with its height and, therefore, its ability to block the channel conveyance maximized. 

The HEC-RAS software should be used to estimate the water-surface elevation in the stream 

reach under these conditions. The methods described in Appendix D are applicable except that 

the downstream ice jam or dam is not breached; however, it may be allowed to release a small 

discharge over and around the ice itself. 
G-4 

G.6 References 

National Climatic Data Center. 2009. “Surface Data, Daily U.S.” Available at 

http://gis.ncdc.noaa.gov/website/ims-cdo/sod/viewer.htm?Box=-180:-90:180:90. 

Accessed May 26, 2009. 

U.S. Army Corps of Engineers (USACE). 2002. Engineering and Design: Ice Engineering. 

Engineer Manual 1110-2-1612, U.S. Army Corps of Engineers, Washington, D.CU.S. Army 

Corps of Engineers (USACE). 2009a. “The Ice Jam Database.” Available at 

https://rsgis.crrel.usace.army.mil/icejam/. Accessed May 26, 2009. 

U.S. Army Corps of Engineers (USACE). 2009b. “Historical Ice Jams in Virginia.” Available at 

https://rsgis.crrel.usace.army.mil/apex/f?p=273:12:1304769456164015::::P12_GETREPORT,P1

2_SHOWITEMS:9,0. Accessed May 26, 2009. 
Appendix H 

COMBINED-EFFECT FLOODS 

H-1 

APPENDIX H 

COMBINED-EFFECT FLOODS 

The American Nuclear Society (ANS) states that a single flood-causing event is inadequate as a 

design basis for power reactors (ANS 1992). Flood-causing mechanisms are described in 

Chapter 2 of this report. Many flood-causing mechanisms can occur concurrently because they 

are not truly independent mechanisms. For example, floods from precipitation events may 

occur concurrently with an antecedent snowpack and wind-induced waves. In coastal regions, 

the precipitation event may be a result of hurricanes and, therefore, could coincide with a storm 

surge. High tides may combine with storm surges from hurricanes and with tsunamis. 

ANS has identified combinations of flooding mechanisms that are acceptable for use in 

determining design bases from flood hazards (ANS 1992). Because extreme events, such as a 

probable maximum flood, probable maximum storm surge, and probable maximum tsunami 

(PMT, are very rare events, combining two or more of these events is not advised when 

determining flood hazards. Instead, only one of the flood-causing events in the combination 

should be a probable maximum event, while the others are should be more commonly occurring 

events. The combinations identified by ANS are thought to have an probability-of-exceedance 

of less than 1 x 10-6 (ANS 1992). Supporting information related to the probability-ofexceedance of combined events is provided by ANS (1992); however, rigorous statistical 

analyses have not been completed for these estimates. 

H.1 Floods Caused by Precipitation Events 

ANS (1992) recommends that the following alternative combinations should be evaluated to 

determine the highest flood water elevation at the site. 

• Alternative 1 – Combination of: 

– Mean monthly base flow 

– Median soil moisture 

– Antecedent or subsequent rain: the lesser of (1) rainfall equal to 40 percent of 

probable maximum precipitation (PMP) and (2) a 500-year rainfall 

– The PMP 

– Waves induced by 2-year wind speed applied along the critical direction. 

• Alternative 2 – Combination of: 

– Mean monthly base flow 

– Probable maximum snowpack 

– A 100-year, snow-season rainfall 

– Waves induced by 2-year wind speed applied along the critical direction. 

• Alternative 3 – Combination of: 

– Mean monthly base flow 

– A 100-year snowpack 
H-2 

– Snow-season PMP 

– Waves induced by 2-year wind speed applied along the critical direction. 

H.2 Floods Caused by Seismic Dam Failures 

ANS (1992) recommends that the following alternative combinations be evaluated to determine 

the highest flood water elevation at the site. 

• Alternative 1 – Combination of: 

– A 25-year flood 

– A flood caused by dam failure resulting from a safe shutdown earthquake (SSE), and 

coincident with the peak of the 25-year flood 

– Waves induced by 2-year wind speed applied along the critical direction. 

• Alternative 2 – Combination of: 

– The lesser of one-half of the PMF or the 500-year flood 

– A flood caused by dam failure resulting from an operating basis earthquake (OBE), 

and coincident with the peak of the flood in item 1 above 

– Waves induced by 2-year wind speed applied along the critical direction. 

H.3 Floods along the Shores of Open and Semi-Enclosed Bodies of 

Water 

ANS (1992) recommends two scenarios for sites located along the shores of open or semienclosed bodies of water: (1) shore location and (2) streamside location. 

H.3.1 Shore Location 

• Combination of: 

– Probable maximum surge and seiche with wind-wave activity 

– Antecedent 10 percent exceedance high tide. 

H.3.2 Streamside Location 

• Alternative 1 – Combination of: 

– The lesser of one-half of the PMF or the 500-year flood 

– Surge and seiche from the worst regional hurricane or windstorm with wind-wave 

activity 

– Antecedent 10 percent exceedance high tide. 

• Alternative 2 – Combination of: 

– PMF in the stream 

– A 25-year surge and seiche with wind-wave activity 

– Antecedent 10 percent exceedance high tide. 
H-3 

• Alternative 3 – Combination of: 

– A 25-year flood in the stream 

– Probable maximum surge and seiche with wind-wave activity 

– Antecedent 10 percent exceedance high tide. 

• Alternative 4 – For drainage areas less than 300 mi2

 in hurricane-prone areas, a 

combination of: 

– PMF in the stream 

– PMH in the open or semi-enclosed waterbody 

– Antecedent 10 percent exceedance high tide. 

H.4 Floods along the Shores of Enclosed Bodies of Water 

ANS (1992) recommends two scenarios for sites located along the shores of enclosed bodies of 

water: (1) shore location and (2) streamside location. 

H.4.1 Shore Location 

• Combination of: 

– Probable maximum surge and seiche with wind-wave activity 

– The lesser of the 100-year or the maximum controlled water level in the enclosed 

body of water. 

H.4.2 Streamside location 

• Alternative 1 – Combination of: 

– The lesser of one-half of the PMF or the 500-year flood 

– Surge and seiche from the worst regional hurricane or windstorm with wind-wave 

activity 

– The lesser of the 100-year or the maximum controlled water level in the enclosed 

body of water. 

• Alternative 2 – Combination of: 

– PMF in the stream 

– A 25-year surge and seiche with wind-wave activity 

– The lesser of the 100-year or the maximum controlled water level in the enclosed 

body of water 

• Alternative 3 – Combination of: 

– A 25-year flood in the stream 

– Probable maximum surge and seiche with wind-wave activity 

– The lesser of the 100-year or the maximum controlled water level in the enclosed 

body of water. 
H-4 

H.5 Floods Caused by Tsunamis 

Although tsunami-induced flooding is not covered in this report, we describe combined events 

that include tsunamis. A more detailed discussion of tsunami hazards at nuclear power plant 

sites is presented by Prasad (2009). Two scenarios of site location are possible: (1) a shore 

location and (2) a streamside location. 

H.5.1 Shore Location 

• Combination of: 

– PMT runup 

– Antecedent 10 percent exceedance high tide. 

H.5.2 Streamside Location 

• Alternative 1 – Combination of: 

– A 25-year flood in the stream 

– Waves induced by 2-year wind speed applied along the critical direction 

– Run-up from a PMT-induced bore. 

• Alternative 2 – Combination of: 

– PMF in the stream 

– Waves induced by 2-year wind speed applied along the critical direction 

– Run-up from the worst observed tsunami-induced bore. 

• Alternative 3 – Combination of: 

– Mean monthly base flow 

– A flood caused by dam failure resulting from an SSE 

– Waves induced by 2-year wind speed applied along the critical direction 

– Run-up from a bore caused by a near-field tsunami consistent with the SSE. 

• Alternative 4 – Combination of: 

– A 25-year flood in the stream 

– A flood caused by dam failure resulting from an OBE 

– Waves induced by 2-year wind speed applied along the critical direction 

– Run-up from a bore caused by a near-field tsunami consistent with an OBE. 

H.6 References 

American Nuclear Society (ANS). 1992. Determining Design Basis Flooding at Power Reactor 

Sites. ANSI/ANS-2.8-1992, ANS Standards Committee Working Group ANS-2.8, American 

Nuclear Society, La Grange Park, Illinois. 
H-5 

Prasad, R. 2009. Tsunami Hazard Assessment at Nuclear Power Plant Sites in the 

United States of America. NUREG/CR-6966, U.S. Nuclear Regulatory Commission, Office of 

New Reactors, Washington, D.C. 

Appendix I 

UNIT HYDROGRAPHS AND NONLINEAR HYDROLOGIC 

RESPONSE 

I-1 

APPENDIX I 

UNIT HYDROGRAPHS AND NONLINEAR HYDROLOGIC RESPONSE 

In precipitation-runoff analysis, the unit hydrograph (Sherman 1932) is a useful and simple to 

implement concept. Unit hydrographs can be estimated from observed precipitation and 

corresponding runoff or streamflow measurements. Unit hydrographs for ungauged drainage 

basins, for which observations do not exist or are insufficient, have also been estimated 

synthetically. The approach has, however, been controversial in terms of its technical 

consistency and adequacy. Some of these issues are described in this appendix. 

I.1 Unit Hydrographs 

A unit hydrograph is generally defined as the direct runoff hydrograph resulting from a uniform, 

unit depth of precipitation or rainfall excess on a drainage area. The unit hydrograph theory of 

runoff generation is linear, in that the direct runoff hydrograph from a rainfall excess of a given 

amount can simply be obtained by multiplying the unit hydrograph ordinates by that amount. It 

follows, then that the runoff time-base in invariant and does not depend on rainfall intensity. 

The main characteristics of a unit hydrograph are: 

1. A runoff volume equivalent to a unit depth over the drainage area 

2. A duration over which the rainfall excess occurs, and 

3. A constant time-to-peak and a constant time base. 

The estimation of a direct runoff hydrograph from a sequence of varying rainfall excesses is 

simply obtained by convolution (Chow et al. 1988): 

ܳ௡ ൌ ∑ ሺܲ௠ܷ௡ି௠ାଵሻ ௡ஸெ

௠ୀଵ (I-1) 

where Qn is the ordinate of the direct runoff hydrograph at time n (1 ≤ n ≤ N), Pm is the mth of M

rainfall excesses, and U represents the unit hydrograph ordinates. The estimation of the 

ordinates of a unit hydrograph (U) from observed sequences of rainfall excess (P) and direct 

runoff hydrograph (Q) is accomplished by the reverse process, called deconvolution (Chow 

et al. 1988). The same set of linear equations given above is used. However, notice that there 

are N equations and only (N-M+1) unknowns, the ordinates of the unit hydrograph. Therefore, 

the system of linear equations is overdetermined. The system of linear equations can be solved 

to estimate the unit hydrograph with added constraints that all ordinates should be non-negative 

and the area under the unit hydrograph should represent unit depth of runoff from the drainage 

area. 

The uncertainty in the estimation of the unit hydrograph arises from the uncertainty in the 

determination of rainfall excess, for which an estimate of rainfall loss must be made and also 

from the determination of the direct runoff hydrograph from the observed streamflow sequence 

by removing baseflow, which may vary during the runoff event and is not known with a high 

degree of accuracy. For these reasons, unit hydrographs estimated from observed rainfallrunoff data may exhibit oscillations, negative ordinate values, and vary in shapes for different 

storms. Usually an “average” unit hydrograph from several observed rainfall-runoff sequences 

is estimated as a compromise. 
I-2 

For drainage areas where little or no observed data exist, synthetic unit hydrographs have been 

developed (for example, Snyder 1938; Natural Resources Conservation Service, previously Soil 

Conservation Service (SCS) 1985; Clark 1945). These synthetic unit hydrographs relate 

characteristics such as time-to-peak and peak discharge to the characteristics of the drainage 

area (Snyder’s unit hydrographs), or are dimensionless (SCS unit hydrographs), or are based 

on storage effects of the drainage basin (Clark’s unit hydrographs). These approaches are wellknown (Chow 1988; USACE 1994) and already implemented in standard rainfall-runoff models 

such as the U.S. Army Corps of Engineers’ (USACE’s) Hydrologic Engineering Center 

Hydrologic Modeling System (HEC-HMS) computer program. 

I.2 Nonlinear Runoff Response in Drainage Basins 

The rainfall-runoff process is highly nonlinear. Several sub-processes, such as interception of 

rainfall, throughfall, infiltration, evapotranspiration, rainfall-excess surface runoff generation, 

saturation-excess surface runoff generation, interflow, baseflow, and dynamic effects of open 

channel flow in the stream network (Dingman 2002; Chow 1959), determine the shape of the 

streamflow hydrograph at the outlet of a drainage area. Physically based process models, such 

as the Distributed Hydrology Soil-Vegetation Model (DHSVM) (Wigmosta et al. 1994, 2002) 

explicitly account for each of these processes to model the runoff response from a drainage 

area. 

The unit hydrograph has been recognized to ignore the nonlinearity of the runoff generation 

processes (Robinson et al. 1995), particularly the invariance to rainfall intensity. Minshall (1960) 

estimated unit hydrographs in a small watershed in Illinois and found that they were different for 

different storm intensities. Pilgrim and Cordery (1993) and USACE (1991, 1994) have 

recommended that for simulation of the runoff response from extreme precipitation events, an 

adjustment of unit hydrographs derived from observed rainfall-runoff sequences is needed, 

particularly if the rainfall events used in the derivation of the unit hydrograph are relatively small 

compared to the extreme precipitation events. 

The USACE (1994) cautions that the unit hydrograph used for a particular storm should be 

appropriate for a storm of that magnitude. The USACE (1994) recommends that unit 

hydrographs intended for use with large hypothetical storms should be derived from observed 

data of large historical events. It notes that under some conditions, it is appropriate to adjust a 

unit hydrograph to account for the shorter travel time of floods generated by large storm events. 

USACE (1991) recommended a “peaking” of 25 to 50 percent of unit hydrographs derived from 

smaller events in order for them to be used in the derivation of inflow design flood. Inflow 

design floods for dams that are capable of placing human life at risk are estimated from a 

probable maximum precipitation (PMP) event (USACE 1991). Pilgrim and Cordery (1993) cited 

studies in the United Kingdom and Australia where unit hydrograph adjustments of one-fifth 

increase in peak flow and a one-third reduction in time-to-peak were recommended. It is well 

known by kinematic wave theory that the time to equilibrium (the time to reach peak flow when 

the response from the whole drainage area has reached the outlet) is dependent on intensity of 

rainfall (Wong 1996). 

Saghafian (2006) has recently demonstrated, also based on the application of kinematic wave 

theory, that a nonlinear transformation of the ordinates on the rising limb of a unit hydrograph 

derived for one rainfall intensity can be used to perfectly predict the ordinates on the rising limb 

of another unit hydrograph corresponding to a different rainfall intensity. These results were 

obtained for a constant width plane, a converging plane, and a diverging plane. However, the 

results of the adjustment approach for a natural drainage basin previously used by Minshall 

(1960) showed slight errors when several unit hydrographs estimated from different storm 
I-3 

events were subjected to the same transformation and compared with one of the estimated unit 

hydrographs (Saghafian 2006). Saghafian (2006) attributed the disagreements to possible 

errors in estimation of effective rainfall intensities of the relatively small storm events used by 

Minshall (1960). 

The research for an appropriate adjustment for unit hydrographs derived from storms of 

intensities smaller than that of extreme design events is still ongoing. The Pacific Northwest 

National Laboratory is currently performing studies using DHSVM to estimate unit hydrographs 

from PMP events. The results of this study will be reported in the near future. 

In the interim, we recommend that the unit hydrograph intended to be used for estimation of the 

probable maximum flood be derived from the largest historical storm events. In addition, the 

estimated unit hydrograph should be validated against other comparably large historical storms 

not used in its derivation. When the historical storms used for estimation of the unit hydrograph 

is significantly smaller in magnitude than the PMP, the unit hydrograph peak discharge should 

adjusted using the following two methods and the more conservative of the two adjusted unit 

hydrographs should be used further: 

1. Increase the peak discharge of the unit hydrograph by one-fifth and decrease the timeto-peak by one-third. 

2. Adjust the rising limb of the unit hydrograph using the approach described by Saghafian 

(2006) and adjust the falling limb of the unit hydrograph to preserve the runoff volume to 

a unit depth over the drainage area. 

I.3 References 

Chow V.T., “Open-Channel Hydraulics.” McGraw-Hill Book Company, New York, 680 pp., 1959. 

Chow V.T., D.R. Maidment, and L.W. Mays. 1988. “Applied Hydrology.” McGraw-Hill Book 

Company, New York. 

Clark C.O. 1945. “Storage and the unit hydrograph.” Transactions of American Society of Civil 

Engineers 110:1419-1488. 

Dingman L.S. 2002. “Physical Hydrology.” Prentice Hall, 2nd Edition, Englewood Cliffs, 

New Jersey. 

Minshall N.E. 1960. “Predicting storm runoff on small experimental watersheds.” Journal of 

Hydraulics Division, American Society of Civil Engineers 86(HY8:17–38. 

Natural Resources Conservation Service (previously the U.S. Soil Conservation Service or 

SCS). 1985. National Engineering Handbook, Section 4, Hydrology. U.S. Department of 

Agriculture, Washington, D.C. 

Pilgrim D.H. and I. Cordery. 1993. “Flood Runoff.” Chapter 9 in Handbook of Hydrology, 

D.R. Maidment (ed.), McGraw-Hill Book Company, New York. 

Robinson J.S., M. Sivapalan, and J.D. Snell. 1995. “On the relative roles of hillslope 

processes, channel routing, and network geomorphology in the hydrologic response of natural 

catchments.” Water Resources Research 31(12):3089–3101. 
I-4 

Sherman L.K. 1932. “Streamflow from Rainfall by the Unit-graph Method.” Engineering News 

Record 108(1932):501–505. 

Snyder F.F. 1938. “Synthetic Unit-Graphs.” , 19(1938):447-454. 

U.S. Army Corps of Engineers (USACE). 1991. Inflow Design Floods for Dams and 

Reservoirs. Engineer Regulation 1110-8-2(FR), Washington, D.C. 

U.S. Army Corps of Engineers (USACE). 1994. Flood-Runoff Analysis. Engineer Manual 

1110-2-1417, Washington, D.C. 

Wigmosta M.S., L. Vail, and D.P. Lettenmaier. 1994. “A distributed hydrology-vegetation model 

for complex terrain.” Water Resources Research 30:1665-1679. 

Wigmosta M.S., B. Nijssen, P. Storck, and D.P. Lettenmaier. 2002. “The Distributed Hydrology 

Soil Vegetation Model,” In: Mathematical Models of Small Watershed Hydrology and 

Applications, V.P. Singh, D.K. Frevert (eds.), Water Resource Publications, Littleton, Colorado. 

Wong T.S.W. 1996. “Influence of upstream inflow on wave celerity and time to equilibrium on 

an overland plane.” Hydrological Sciences 41(2):195-205. 
BIBLIOGRAPHIC DATA SHEET

(See instructions on the reverse)

NRC FORM 335

(9-2004)

NRCMD 3.7

U.S. NUCLEAR REGULATORY COMMISSION 1. REPORT NUMBER

(Assigned by NRC, Add Vol., Supp., Rev.,

 and Addendum Numbers, if any.)

3. DATE REPORT PUBLISHED

MONTH YEAR

4. FIN OR GRANT NUMBER

2. TITLE AND SUBTITLE

5. AUTHOR(S) 6. TYPE OF REPORT

7. PERIOD COVERED (Inclusive Dates)

8. PERFORMING ORGANIZATION - NAME AND ADDRESS (If NRC, provide Division, Office or Region, U.S. Nuclear Regulatory Commission, and mailing address; if contractor,

9. SPONSORING ORGANIZATION - NAME AND ADDRESS (If NRC, type "Same as above"; if contractor, provide NRC Division, Office or Region, U.S. Nuclear Regulatory Commission, 

provide name and mailing address.)

and mailing address.)

10. SUPPLEMENTARY NOTES

11. ABSTRACT (200 words or less)

12. KEY WORDS/DESCRIPTORS (List words or phrases that will assist researchers in locating the report.)

14. SECURITY CLASSIFICATION

13. AVAILABILITY STATEMENT

unlimited

(This Page)

unclassified

(This Report)

unclassified

15. NUMBER OF PAGES

16. PRICE

NRC FORM 335 (9-2004) PRINTED ON RECYCLED PAPER

NUREG/CR-7046

PNNL-20091

Design-basis Flood Estimation for Site Characterization at Nuclear Power Plants in the

United States of America November 2011

N6575

Rajiv Prasad, Lyle F. Hibler, Andre M. Coleman, and Duane L. Ward, Pacific Northwest

National Laboratory

Technical

Not Applicable

Pacific Northwest National Laboratory

P.O. Box 999

Richland, WA 99352

Office of Nuclear Regulatory Research

Division of Fuel, Engineering, and Radiological Research

U.S. Nuclear Regulatory Commission

Washington, DC 20555

John Randall, NRC Project Manager; Thomas Nicholson, NRC Technical Monitor

The purpose of this document is to describe approaches and methods for estimation of the design-basis flood at nuclear power

plant sites. We define the design-basis flood and list the relevant U.S. Nuclear Regulatory Commission’s (NRC) regulations.

The concepts of hierarchical hazard assessment (HHA) and alternative conceptual models are introduced. The individual

flood-causing mechanisms and their effects are described. A description of the HHA method as applied to several of these

flooding mechanisms is provided. A brief discussion of combined events is also included. Two analytical approaches, the

deterministic and the probabilistic, used in standard engineering practice for estimation of design-basis floods are described.

The NRC’s quality assurance criteria for simulation models are described. A description of criteria used in selection of

simulation models is included. Uncertainty in input data and model parameters is discussed. A brief discussion of verification of

model-derived estimates is also included. We present an outline of the components of a formal Probabilistic Flood Hazard

Assessment approach. We briefly describe the findings of the fourth assessment report on climate change prepared by the

Intergovernmental Panel on Climate Change. We briefly describe incorporation of the effects of climate change in estimation of

the design-basis floods. We provide a few specific recommendations for further research. Incorporation of more recent

site-specific datasets to demonstrate the validity of estimated design-basis floods would provide additional assurance regarding

available margins. Development of a comprehensive probabilistic flood hazard assessment methodology that leverages existing

techniques and accounts for uncertainty in model inputs and parameters can provide an extremely useful tool for risk-informed

design-basis flood estimation at nuclear power plant sites.

design-basis flood, hierarchical hazard assessment, flood-causing mechanisms, alternative

conceptual models, probable maximum flood, probable maximum storm surge, paleo-flood, local

intense precipitation, dam failure, dam breach


UNITED STATES 

NUCLEAR REGULATORY COMMISSION

WASHINGTON, DC 20555-0001

--------------------

OFFICIAL BUSINESS
NUREG/CR

-7046 Design-Basis Flood Estimation for Site Characterization at 

Nuclear Power Plants in the United States of America