U.S. Department of the Interior

U.S. Geological Survey

US Army Corps

of Engineers®

Climate Change and Water Resources Management: 

A Federal Perspective

Circular 1331
Climate Change and Water Resources 

Management: A Federal Perspective

By Levi D. Brekke, Julie E. Kiang, J. Rolf Olsen, Roger S. Pulwarty, David A. Raff, 

D. Phil Turnipseed, Robert S. Webb, and Kathleen D. White

Circular 1331

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2009

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Cover: Photograph showing Parker Dam in Arizona and California. Photograph courtesy Bureau of 

Reclamation.

Back cover (clockwise from top left corner): U.S. Geological Survey suspended sediment 

sampling at Little Colorado River in Arizona; Salt-Gila project in Arizona (courtesy Bureau of 

Reclamation); U.S. Geological Survey discharge measurement at Goose River in North Dakota; U.S. 

Army Corps of Engineers pump and levee at Davenport, Iowa (courtesy U.S. Army Corps of Engineers); 

sandbags and a temporary floodwall in Hannibal, Mo. (courtesy U.S. Army Corps of Engineers); and Mark 

Twain Lake and Clarence Cannon Dam in Missouri (courtesy U.S. Army Corps of Engineers).

Suggested citation:

Brekke, L.D., Kiang, J.E., Olsen, J.R., Pulwarty, R.S., Raff, D.A., Turnipseed, D.P., Webb, R.S., and White, K.D., 2009, 

Climate change and water resources management—A federal perspective: U.S. Geological Survey Circular 1331, 

65 p. (Also available online at http://pubs.usgs.gov/circ/1331/.)

ISBN 978–1–4113–2325–4
iii

Contents

Executive Summary ......................................................................................................................................1

Chapter 1—Introduction......................................................................................................................1

Chapter 2—Tracking Climate Change Impacts................................................................................1

Chapter 3—Anticipating Climate Change: Available Climate Information for 

Decisionmaking in Long-Range Planning ...........................................................................2

Chapter 4—Anticipating Climate Change: Approaches for Decisionmaking.............................2

Chapter 5—Responding to Climate Change: Adaptation Options ................................................2

Chapter 6—Opportunities for Advancing Planning Capabilities ..................................................3

1 Introduction ...............................................................................................................................................5

1.1 Is Climate Changing? ....................................................................................................................5

1.2 What Climate Changes are of Most Concern to Water Resources Management? ...........6

1.3 How is Climate Information Used in Water Resources Management?................................7

1.4 Other Changes Affecting Water Resources Management.....................................................8

1.5 Sector Impacts Due to Climate Change ....................................................................................9

2 Tracking Climate Change Impacts ........................................................................................................13

2.1 Tracking Hydrologic Change: Monitoring Networks .............................................................13

2.2 Tracking Hydrologic Change: Trend Analysis .........................................................................13

2.3 Improving Process Understanding and Modeling Capabilities ..........................................15

3 Anticipating Climate Change: Available Climate Information for Decisionmaking in 

Long-Range Planning ....................................................................................................................17

3.1 Use of Climate Information in General Long-Range Systems Evaluations ........................17

3.1.1 Establishing Assumptions and a Plausible Planning Future Through 

Traditional Use of Instrumental Records..................................................................17

3.1.2 Expanding the Set of Plausible Planning Futures Using Stochastic 

Modeling and Paleoclimate Information .................................................................18

3.1.3 Defining Plausible Planning Futures Based on Climate Projection 

Information ...................................................................................................................19

3.2 Use of Climate Information in Flood-Risk Evaluations...........................................................20

3.2.1 Flood-Risk Evaluation Methods.....................................................................................20

3.2.2 Incorporating Climate Projection Information Into Flood-Risk Evaluations ..........20

3.2.3 Incorporating Paleoflood Information Into Flood-Risk Evaluations ........................21

3.3 Recent Reclamation and USACE Planning Applications Involving the Use of 

Expanded Climate Information Sets...................................................................................21

3.4 Summary and Discussion ..........................................................................................................21

4 Anticipating Climate Change: Approaches for Decisionmaking .....................................................23

4.1 Decisions and Scales..................................................................................................................23

4.2 Describing Future Climate for Planning...................................................................................23

4.3 Incorporating Uncertainties in Planning .................................................................................25

4.4 Other Methods for Choosing Alternatives...............................................................................25

4.4.1 Robust Decision Criteria.................................................................................................25

4.4.2 Adaptive Management ...................................................................................................26

4.5 Summary .......................................................................................................................................26
iv

5 Responding to Climate Change: Adaptation Options.........................................................................29

5.1 Adaptation Options Involving Operational Changes..............................................................29

5.2 Adaptation Options Involving Water-Demand Management...............................................30

5.3 Adaptation Options Involving Infrastructure Modifications.................................................30

5.4 Challenges ....................................................................................................................................31

5.5 Summary .......................................................................................................................................31

6 Opportunities To Improve Planning Capabilities ...............................................................................33

6.1 Knowledge Gaps and Potential Research Priorities ............................................................33

6.2 Gaps in Existing Hydrologic and Meteorologic Data Networks .........................................35

6.3 Understanding and Incorporating Nonstationarity Concepts..............................................35

6.4 Opportunities To Improve Planning ..........................................................................................36

6.5 Opportunities for Further Collaboration...................................................................................36

6.6 Summary .......................................................................................................................................37

7 References Cited .....................................................................................................................................39

Appendix A. Paleoclimate Reconstruction of Past Droughts and Floods .........................................47

A1 Drought Reconstruction .............................................................................................................47

A2 Flood Reconstruction ..................................................................................................................48

A3 References Cited .........................................................................................................................48

Appendix B. Downscaling General Circulation Model Results...........................................................51

B1 Downscaling Methods................................................................................................................51

B2 Downscaled Climate Projections Archive...............................................................................52

B3 References Cited .........................................................................................................................53

Appendix C. Recent Reclamation and USACE Planning Applications Involving the Use of 

Expanded Climate Information Sets............................................................................................55

C1 Lake Ontario–St. Lawrence River Study ..................................................................................55

C1.1 Process and Purpose ......................................................................................................55

C1.2 Role of Climate Information............................................................................................56

C2 Colorado River Basin Study........................................................................................................57

C2.1 Process and Purpose ......................................................................................................57

C2.2 Role of Climate Information............................................................................................57

C3 California Central Valley Study ..................................................................................................59

C3.1 Process and Purpose ......................................................................................................59

C3.2 Role of Climate Information............................................................................................60

C4 References Cited..........................................................................................................................62

Appendix D. Glossary..................................................................................................................................65

Figures

1. Smoothed reconstructions of large-scale surface temperature variations.......................6

2. Trends in yearly dates of spring snowmelt onset and centers of volume of yearly 

streamflow hydrographs in western North America..............................................................7

3. Change in 30-year mean annual precipitation.........................................................................7

4. Global mean sea level observed since 1870 and projected for the future..........................7

5. Average frequency of western U.S. forest wildfires by elevation and early, mid-, 

and late snowmelt years from 1970 to 2002............................................................................10
6. Mean seasonal precipitation changes over North America...............................................10

7. Fractional area of the country affected by ice storms .........................................................11

8. Analytical framework for relating climate to water supplies, demands, and 

constraints. ..................................................................................................................................17

9. Bottom-up and top-down scenario definitions in climate change assessments ............24

10. Age map indicating the last published regional-regression analysis for rural 

peak flows....................................................................................................................................35

C–1. Geographic setting for International Joint Commission ......................................................55

C–2. Projected 2050 climate change conditions ............................................................................56

C–3. Locations of the Colorado River Basin hydrologic input sites in the Colorado 

River Simulation System............................................................................................................58

C–4. Probabilistic projection of Lake Mead end-of-December elevations................................59

C–5. Estimated natural flow of the Colorado River at the Lees Ferry gaging station, 

Arizona..........................................................................................................................................59

C–6. California Central Valley Project and State Water Project service areas. .......................60

C–7. “Above Folsom Lake” location .................................................................................................61

C–8. Evaluation of climate projections spread ...............................................................................61

C–9. Selected climate projections for framing the climate change sensitivity analysis.........62

Tables

1. Potential environmental and socioeconomic changes affecting water 

resources management decisionmaking .................................................................................9

2. Knowledge gaps discussed and prioritized at a geographically focused 

forum on climate change and western water management...............................................34

B–1. General advantages and disadvantages associated with statistical and 

dynamical classes of downscaling methods .........................................................................51

Conversion Factors

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

kilometer (km) 0.6214 mile (mi)

Volume

cubic meter (m3

) 0.0008107 acre-foot (acre-ft) 

Vertical Datums

Elevation, as used in this report, refers to distance above sea level. Because this report is based 

on a large number of previously published scientific investigations, “sea level” is not referenced 

to a single vertical datum. “Mean sea level” also is not used with reference to a single datum; 

where used, the phrase means the average surface of the ocean as determined by calibration 

of measurements at tidal stations.
vi

Acronyms

ACWI Advisory Committee on Water Information

BCSD Bias-Correction and Spatial Disaggregation

BSR Biennial Science Report [to the California Governor’s Office]

C–CAWWG Climate Change and Western Water Group

CA–DWR California Department of Water Resources

CCSP U.S. Climate Change Science Program

CMIP Coupled Model Intercomparison Project

COOP U.S. Cooperative Observer Network

CPC Climate Prediction Center

CRSS Colorado River Simulation System 

CVP Central Valley Project

DCP Downscaled Climate Projections

DP Direct Paleo

EPA U.S. Environmental Protection Agency

FAA Federal Aviation Administration

GCM General circulation model

GMSL Global mean sea level

HBN Hydrologic Benchmark Network

HCDN Hydroclimatic Data Network

IACWD Interagency Committee on Water Data

ICWP Interstate Council on Water Policy

IFRMC Intergovernmental Flood Risk Management Committee

IJC International Joint Commission

IPCC Intergovernmental Panel on Climate Change

ISM Index Sequential Method

NASQAN National Stream Quality Accounting Network

NCDC National Climatic Data Center

NCEP National Centers for Environmental Prediction

NEPA National Environmental Policy Act

NESDIS National Environmental Satellite Data and Information Service

NOAA National Oceanic and Atmospheric Administration

NOHRSC National Operational Hydrologic Remote Sensing Center

NOS National Oceanographic Service

NPC Nonparametric Paleo-Conditioned

NWS National Weather Service

OCAP BA Operational Criteria and Plan Biological Assessment

OCE Office of the Chief Economist

OMB Office of Management and Budget

P&G Economic and Environmental Principles and Guidelines for Water and Related 

Land Resources Implementation Studies

PMF Probable maximum flood

PMP Probable maximum precipitation

RCM Regional climate model

Reclamation U.S. Bureau of Reclamation

RISA [NOAA] Regional Integrated Sciences and Assessments

SWP [California] State Water Project

USACE U.S. Army Corps of Engineers

USCRN U.S. Climate Reference Network

USDA U.S. Department of Agriculture
vii

USFWS U.S. Fish and Wildlife Service

USGS U.S. Geological Survey

WAOB World Agricultural Outlook Board

WCRP World Climate Research Programme

West-FAST Western States Federal Agency Support Team

WRPS Water Resources Product Suite

WSWC Western States Water Coucil

Climate Change and Water Resources Management:

A Federal Perspective

By Levi D. Brekke,1 Julie E. Kiang,2 J. Rolf Olsen,3 Roger S. Pulwarty,4 David A. Raff,1 D. Phil Turnipseed,2

Robert S. Webb,4

 and Kathleen D. White3

Executive Summary 

Many challenges, including climate change, face the 

Nation’s water managers. The Intergovernmental Panel on 

Climate Change (IPCC) has provided estimates of how climate 

may change, but more understanding of the processes driving 

the changes, the sequences of the changes, and the manifestation of these global changes at different scales could be beneficial. Since the changes will likely affect fundamental drivers 

of the hydrological cycle, climate change may have a large 

impact on water resources and water resources managers. 

The purpose of this interagency report prepared by the 

U.S. Geological Survey (USGS), U.S. Army Corps of Engineers (USACE), Bureau of Reclamation (Reclamation), and 

National Oceanic and Atmospheric Administration (NOAA) is 

to explore strategies to improve water management by tracking, anticipating, and responding to climate change. The key 

points below briefly summarize the chapters in this report and 

represent underlying assumptions needed to address the many 

impacts of climate change.

Chapter 1—Introduction

Observational evidence shows that many natural systems 

are being affected by regional climate changes, particularly temperature increases. The Fourth Assessment Report by the IPCC 

(2007a, b, c), previous assessment reports, and related documents present evidence of global climate change, with particular 

attention to issues facing water resources managers. The findings presented in IPCC’s 2007 report represent improvements 

over previous iterations because of improved data from new 

sensors, increased sophistication of analyses, improved understanding of physical processes and process models, and better 

understanding of the uncertainty of model results.

Climate change is but one of many dynamic processes 

impacting water resources management. Other processes (for 

example, change in population size and location, economic 

1

U.S. Bureau of Reclamation. 2

U.S. Geological Survey. 3

U.S. Army Corps of Engineers. 4

National Oceanic and Atmospheric Administration.

development and land use, aging infrastructure, ground-water 

development, and changing social values) also have major 

influences on water resources and must be considered along 

with climate change in a holistic approach to water resources 

management. Climate change has the potential to affect many 

sectors in which water resource managers play an active role, 

including water availability, water quality, flood risk reduction, ecosystems, coastal areas, navigation, hydropower, and 

other energy sectors. These changes may have adverse or 

positive impacts on one or more sectors. Any or all of these 

changes could occur gradually or abruptly. 

Key Point 1: The best available scientific evidence based on 

observations from long-term monitoring networks indicates 

that climate change is occurring, although the effects differ 

regionally.

Key Point 2: Climate change could affect all sectors of water 

resources management, since it may require changed design 

and operational assumptions about resource supplies, system 

demands or performance requirements, and operational constraints. The assumption of temporal stationarity in hydroclimatic variables should be evaluated along with all other 

assumptions.

Key Point 3: Climate change is but one of many challenges 

facing water resource managers. A holistic approach to water 

resources management includes all significant drivers of change.

Chapter 2—Tracking Climate Change Impacts

Detecting hydrologic changes requires data from longterm monitoring networks to establish baseline conditions and 

then record any changes over time. Long-term monitoring networks are critical for detecting and quantifying actual impacts, 

providing a basis for understanding hydrologic processes and 

trends, allowing calibration and validation of models used to 

project future conditions, and supporting design and evaluation of adaptation strategies. Trend detection can be used 

to help water managers recognize if the data upon which the 

design and operation of water resource systems were based are 

no longer consistent with current conditions.

Key Point 4: Long-term monitoring networks are critical for 

detecting and quantifying climate change and its impacts. Con-
tinued improvement in the understanding of climate change, 

its impacts, and the effectiveness of adaptation or mitigation 

actions requires continued operation of existing long-term 

monitoring networks and improved sensors deployed in space, 

in the atmosphere, in the oceans, and on the Earth’s surface.

Key Point 5: Monitoring needs to focus on locations that 

describe the climate signal (for example, upstream and downstream from major water-management infrastructure or in 

vulnerable ecological reaches). 

Chapter 3—Anticipating Climate Change: 

Available Climate Information for 

Decisionmaking in Long-Range Planning

Water resources planning involves making assumptions 

about future plausible hydroclimatic conditions (for example, 

temperature, precipitation, and river flows). The choice of 

information supporting these assumptions is affected by a 

changing climate. While science is not capable of predicting 

the exact magnitude of the changes, there are methods to characterize the range of possible changes. This chapter focuses 

on two types of decision processes: planning for long-term 

system operations and evaluations of flood risk. 

The instrumental record has historically been vital in planning for both norms and extremes, as it provides information on 

the conditions under which water resource systems may operate. 

Given a changing climate, it may be appropriate to evaluate 

the system response for a range of hydroclimatic variability 

wider than in the historical record. This can be accomplished 

by including paleoclimate information and stochastic methods. 

Climate projection information can also be incorporated into 

planning assumptions. Although a single best method has yet 

to be determined, incorporating climate projections generally 

involves surveying available climate projection information, 

deciding what portion to relate to planning assumptions, and 

conducting the intervening impact analysis on natural and social 

systems. These results are then related to planning assumptions about supplies, demands, and operating constraints. In 

many planning studies, assumptions are developed relative to a 

stationary reference climate (referred to later as the Stationary 

System paradigm). Under this paradigm, planning assumptions 

can reflect climate from either the instrumental record or from a 

climate projection for a fixed period in the future. Alternatively, 

the System Projection paradigm frames long-range system 

evaluations using planning assumptions that change over time 

and that are consistent with climate projections.

Key Point 6: Paleoclimate information and stochastic modeling 

can be useful for developing climate scenarios that include a 

wide range of potential hydroclimatic conditions. The expanded 

variability may allow a more robust evaluation of planning alternatives, particularly when there is concern that study outcomes 

and decisions may be sensitive to climate assumptions.

Key Point 7: Current expectations about future climate may 

indicate a need to supplement historical climate information. 

Planning assumptions might instead be related to projections 

of future temperature and precipitation. This can be accomplished using a multitude of approaches; a best approach has 

yet to be determined. 

Key Point 8: A System Projection paradigm for adaptation 

planning, as opposed to a Stationary System paradigm, may 

offer a more appropriate context for characterizing planning 

assumptions, albeit at the potential cost of adding planning 

complexity.

Chapter 4—Anticipating Climate Change: 

Approaches for Decisionmaking

Water resource managers make decisions in the face of 

uncertainty associated with varying space and time scales, and 

they make assumptions about supplies, demands, weather, 

climate, and operational constraints at those scales. Water 

resources agencies are governed by multiple laws and regulations. Several studies have concluded that current water-management planning regulations are flexible enough to accommodate planning for climate change. However, current planning 

approaches have generally assumed that future climate conditions will be similar to the historical record—an assumption 

that may be suspect if climate is changing. A robust decision 

criterion supports selection of plans that will perform well over 

a wide range of possible future scenarios, although uncertainties will remain no matter how future scenarios are generated. A 

sequential decision process allows alternative courses of action, 

given different possible future conditions, and can be changed 

as new information becomes available. These approaches are 

not mutually incompatible and can be used in conjunction with 

current water-management planning methods that primarily 

employ cost-benefit analysis and sensitivity analysis. Incorporation of adaptive management can build in flexibility and 

reevaluation of decisions that evolve over time in response to 

new information. The use of multiple scenarios in the context of 

robust/adaptive planning will enhance decisionmaking, particularly if the scenarios span a wide range of possible outcomes.

Key Point 9: Adopting alternatives that perform well over a 

wide range of future scenarios could improve system flexibility. 

Water resources planning and management requires an appreciation of existing and potential future uses of water resources, 

particularly when public health and safety are involved. 

Key Point 10: Adaptive management is an approach where 

decisions are made sequentially over time and allows adjustments to be made as more information is known. This 

approach may be useful in dealing with the additional uncertainty introduced by potential climate change.

Chapter 5—Responding to Climate Change: 

Adaptation Options

Because climate has such a large effect on water resource 

system design and operations, it is apparent that climate 

   Climate Change and Water Resources Management: A Federal Perspective
change would translate into modified design and operational 

assumptions for determining resource supplies, system 

demands, system performance requirements, and operational 

constraints. Several water-management or system-development options might be considered to facilitate adaptation 

under climate change, including operational, demand management, and infrastructure changes. Options should be evaluated 

across appropriate spatial areas; specific options will vary 

from system to system, as will the preference among these 

options.

Key Point 11: Adaptation options include operational, demand 

management, and infrastructure changes. 

Chapter 6—Opportunities for Advancing 

Planning Capabilities

There are significant gaps in knowledge, monitoring, 

and practice that limit incorporation of climate change considerations into water resources planning and management. 

Climate change must be quantified with respect to the myriad 

of other natural and cultural issues that face the Nation’s water 

managers. Sound water management is built on long-term 

hydrological and meteorological monitoring networks that 

provide sound, accurate, timely, and consistent data that can 

be used readily to develop and assess decisionmaking tools 

needed to quantify uncertainty, forecast change, and create 

the multiphase, multilevel climate scenarios that will provide 

reasonable and relevant management. Changes to planning and 

analysis that better accommodate nonstationarity will improve 

water management. Collaboration in all of these activities may 

allow more rapid results and improved communication, both 

within the water resources community and to other stakeholders.

Key Point 12: Research and monitoring are both needed to fill 

knowledge gaps and set up advances in planning capabilities. 

Although neither will eliminate all uncertainties, they will 

provide significant improvements in understanding the effects 

of climate change on water resources, including quantity and 

quality, and in evaluating associated uncertainties and risks 

required for more informed decisionmaking.

Executive Summary    

1 Introduction 

Climate change and its potential impacts on water 

resources have become an increasingly common topic at scientific conferences and meetings among water managers. This 

is particularly true for the four Federal agencies that have collaboratively managed data and information for water resources 

since their founding. These are the USACE (formed in 1802), 

the USGS (formed in 1879), Reclamation (formed in 1902), 

and NOAA [formed in 1970 from a number of existing agencies, including the U.S. Coast and Geodetic Survey (1807) and 

the Weather Bureau (1870)]. 

The four agencies, two termed “operating agencies” 

(USACE and Reclamation) and two termed “science agencies” 

(USGS and NOAA),

 share a symbiotic relationship, where the 

operating capabilities required by one agency may drive the 

direction of science inquiries for another, which in turn may 

result in improved knowledge and processes for operations. 

Similarly, the data collected and compiled by one agency for a 

specific purpose can be used by another agency to supplement 

other data and information for an entirely different purpose. 

Given the rate at which observed climate variability impacts 

have affected water resources projects, particularly in the West, 

and the potential for significant future changes, the senior leaders 

of the four agencies expressed a need to collaborate on future climate-related efforts. In May 2007, representatives met to discuss 

recent findings from the research community, their relevance to 

water management, and approaches that were already being considered or piloted to incorporate climate-change considerations 

into water management. It was agreed that a comprehensive 

assessment of approaches for including climate variability and 

change in water resources management would be valuable. An 

interagency working group was formed to carry out this mission.

This report presents an exploration by the four agencies of strategies to improve water management by tracking, 

anticipating, and responding to climate change. The terms of 

reference for the report are to consider the responses and adaptations of a responsible Federal body in the monitoring, management, and future design of the Nation’s water resources. 

The report focuses on managed water resources. This report 

is a first step; the agencies will next address the knowledge, 

technology, and research gaps, and the monitoring strategies 

for improving understanding and aiding in decisionmaking. 

Although the report does not offer recommendations, it does 

lay a foundation for future climate change actions.

1.1 Is Climate Changing?

The 2007 Intergovernmental Panel on Climate Change 

Working Group 1 and Working Group 2 reports provide a 



There are complementary operations and science activities in these agencies (for example, the National Weather Service is an operational activity 

within NOAA, while USACE and Reclamation have research activities). 

Other Federal agencies have active programs in both water resources research 

and water resource management.

summary of ongoing research to assess whether or not climate 

change is actually happening and to provide an assessment of 

the impacts of climate change (Intergovernmental Panel on 

Climate Change, 2007a,b). According to the Working Group 2 

report’s Summary for Policymakers (Intergovernmental Panel 

on Climate Change, 2007d), “Observational evidence from all 

continents and most oceans shows that many natural systems 

are being affected by regional climate changes, particularly 

temperature increases.” Reconstructions of the Earth’s climate 

over the past 2,000 years have shown that while temperature 

has varied on multiple time scales (National Research Council, 

1998), there appears to have been a significant increase during 

the most recent 100 years (National Research Council, 2006) 

(fig. 1). The National Research Council (NRC) (2006) notes that 

each proxy record presents a different temperature history and 

is subject to a somewhat different set of uncertainties, which 

are understood to generally decrease as time nears the present. 

However, the NRC (2006) considers these reconstructions to be 

a “qualitatively consistent picture of temperature changes over 

the last 1,100 years and especially over the last 400.”

Special attention is given by the IPCC to climate and water 

(Bates and others, 2008). They conclude that: “Observational 

records and climate projections provide abundant evidence that 

freshwater resources are vulnerable and have the potential to 

be strongly impacted by climate change, with wide-ranging 

consequences for human societies and ecosystems.” They also 

suggest that “Current water management practices may not be 

robust enough to cope with the impacts of climate change on 

water supply reliability, flood risk, health, agriculture, energy 

and aquatic ecosystems.” Most importantly for water resources 

managers, the addition of climate change to existing variability 

can impact the fundamental assumption of stationarity (Bates 

and others, 2008; Milly and others, 2008). Assessment of this 

assumption will require monitoring and careful evaluation 

(Karner, 2002; Cohn and Lins, 2005). 

The changes to Earth’s climate are caused by changes in 

the global energy budget, including surface and atmospheric 

energy exchanges, internal variability, and external forcings 

outside the climate system (National Research Council, 2006). 

The dominant drivers of change over the past 2,000 years are 

changes in the concentrations of greenhouse gases (GHGs), 

aerosols, volcanic activity, and solar radiation (National 

Research Council, 2006). GHGs of particular concern are carbon dioxide (CO2

), methane (CH4), and nitrous oxide (N2O). 

GHGs derive from both natural (for example, volcanic emissions and wildfires) and anthropogenic (human-influenced) 

sources (for example, burning of fossil fuels and deforestation). According to IPCC (2007a), no driver other than GHGs 

provides a scientifically sound explanation of most of the 

warming observed both globally and nationally over the past 

few decades.

Key Point 1: The best available scientific evidence based 

on observations from long-term monitoring networks indicates 

that climate change is occurring, although the effects differ 

regionally. 

1 Introduction    
General circulation models (GCMs) are used to make 

projections of future climate change. The GCMs are validated 

through comparison to observations, generally of the past 100 

years, to assess the validity of the models. Increasing uncertainties going backward through time (fig. 1) limit the potential for 

older records to be used in validation. Recent results generally 

indicate improvements over previous generations of models, particularly the ability to represent weather systems, climate variability (for example, monsoons and El Niño), ocean processes 

(for example, the Gulf Stream), surface hydrology, and other 

Earth-system processes, components, and dynamics (Collins 

and others, 2006; Schmidt and others, 2006). One of the ways in 

which these models have advanced is through improvements in 

the representation of the processes responsible for key Earthsystem feedbacks, such as those associated with water vapor, 

clouds, sea ice, and the carbon cycle (Delworth and others, 2006; 

Gnanadesikan and others, 2006; Wittenberg and others, 2006). 

These improvements in GCMs have been possible in large 

part because of large amounts of new information derived from 

improved monitoring of space, atmospheric, ocean, and terrestrial 

processes, which have supplemented observations from long-term 

monitoring networks. The IPCC (2007a) also reports increased 

sophistication of analyses and improved understanding of physical 

processes, the resulting process models, and uncertainty related 

to model results. Yet, at the same time that our need for observational data to support adaptive management in response to climate 

change is increasing, the observational networks crucial to increasing our understanding are shrinking (Bates and others, 2008).

1.2 What Climate Changes are of Most Concern 

to Water Resources Management?

Climate change has the potential to affect many sectors in 

which water resource managers play an active role. The major 

drivers are changing temperature and precipitation regimes, 

and increasing global sea level and associated impacts.

Temperature increases are expected to change the mix of 

precipitation toward more rain and less snow. Such precipitation shifts would affect the origin and timing of runoff, leading to less runoff from spring snowmelt and more runoff from 

winter rainfall, particularly in high-latitude or mountainous 

areas. These shifts have already been reported in northern New 

England, the Great Lakes region, and the Western United States 

(fig. 2) (Stewart and others, 2005; Hodgkins and Dudley, 2006a; 

Knowles and others, 2006; Hodgkins and others, 2007). Increasing temperature may also increase potential evapotranspiration 

from vegetation and land surfaces and may thereby decrease the 

amount of water that then reaches streams, lakes, and reservoirs. 

Changing water temperatures and ocean circulation may change 

the intensity and frequency of coastal storms under future 

climate conditions, but there is still much uncertainty as to what 

those changes may be. (See Knutson and Tuleya, 2004; Emanuel and others, 2007; Shepherd and Knutson, 2007; Knutson 

and others, 2008.)

Precipitation changes are expected to differ across the 

country, with some areas receiving more and others receiving 

less, as suggested by the model simulations shown in figure 3. 

There may also be changes in seasonal patterns and extremes 

of precipitation. Depending on location, these possible 

changes have led to concerns that droughts and floods, defined 

relative to past experiences, will occur more frequently and 

(or) be more severe under future climate conditions (Intergovernmental Panel on Climate Change, 2007b).

Sea level varies over time, principally in response to 

global climate change (National Research Council, 1987; 

Intergovernmental Panel on Climate Change, 2007a). The 

IPCC (Bindoff and others, 2007) concluded that the global 

mean sea level rose at an average rate of about 1.7 ± 0.5

   Climate Change and Water Resources Management: A Federal Perspective

Figure 1. Smoothed 

reconstructions of large-scale 

surface temperature variations 

(Northern Hemisphere mean 

or global mean) plus the 

instrumental record of global 

mean surface temperature. 

Darker gray shading indicates 

greater generalized uncertainty 

(National Research Council, 

2006.) 
45°

40°

35°

140° 130° 120° 50°

45°

40°

35°

110°

140° 120°

B

A

>20 days earlier

15–20

10–15

5–10

<10

5–10 days later

10–15

15–10

>20

Figure 2. Trends in A, yearly dates of spring snowmelt onset; and 

B, centers of volume of yearly streamflow hydrographs in western 

North America, based on U.S. Geological Survey stream gages 

in the United States and an equivalent Canadian streamflow 

network. Large circles indicate sites with trends that differ 

significantly from zero at a 90-percent confidence level; small 

circles are not confidently identified. (From Dettinger, 2005a.)

mm/year during the twentieth century and that the rate has 

been slightly higher between 1961 and 2003. Recent climate 

research has documented global warming during the twentieth century and has predicted either continued or accelerated 

global warming for the twenty-first century and possibly 

beyond (Intergovernmental Panel on Climate Change, 2007a) 

(fig. 4). Changing sea level (mean and extreme high) will 

impact coastal and estuarine regions, with increased erosion 

of sandy beaches and saline intrusion in coastal and estuarine 

aquifers (National Research Council, 1987). 

Any or all of these changes could occur gradually or 

abruptly (National Research Council, 2002, 2006; Climate 

Change Science Program, 2008e). The temporal onset of such 

change is relevant to future actions.

1.3 How is Climate Information Used in Water 

Resources Management?

Climate information is used by decisionmakers throughout water resources management. The effective use of climate 

information can be impacted by the degree of collaboration 

between climatologists, hydrologists, and the decisionmakers. 

Figure 3. Change in 30-year mean annual precipitation, 

measured in centimeters per year (cm/year). The median 

difference between 1971–2000 and 2041–2070 is based on 

112 projections obtained from “Statistically Downscaled 

WCRP CMIP3 Climate Projections” (http://gdo-dcp.ucllnl.org/

downscaled_cmip3_projections). 

Figure 4. Global mean sea level (GMSL) observed since 1870 

and projected for the future (deviation from the 1980–1999 mean). 

[For illustrative purposes only, from U.S. Army Corps of Engineers 

(2008); Intergovernmental Panel on Climate Change (2007a, FAQ 

5.1, fig. 1).] 

The U.S. Climate Change Science Program (CCSP) (2008b) 

notes that “...mismatches between needs and information 

resources continue to occur at multiple levels and scales. Currently there is substantial tension between providing tools at 

the space and time scales useful for water resources decisions 

that are also scientifically accurate, reliable and timely.” 

Assumptions about future climate states have implicitly 

been represented in the planning, design, operation, and major 

rehabilitation of local and regional water resource systems. 

Traditionally, these systems have been designed to operate 

within an envelope of climate variability defined by observed 

(past) streamflow and weather variations on different time and 

space scales. By focusing on streamflow and weather variations 

1 Introduction 
in a retrospective period, there is an inherent assumption that the 

envelope of these variations will remain unchanged in the future; 

that is, they will be stationary during the operation of the system.

Once water resource systems are constructed, the 

continued operation of these systems is affected by retrospective, current, and near-term future climate information. 

Retrospective climate information comes into play when 

operating constraints and water-supply forecast models are 

updated to reflect recent trends in climate. For example, the 

redevelopment of water-supply forecast models would be 

based on an expanded or more recent retrospective record of 

streamflow and climate observations. Likewise, the redevelopment of flood control rules would conceivably be based on an 

expanded record of flood hydrology data. Current and nearterm future climate information (for example, seasonal to 1-

year forecasts) might be used to determine annual performance 

objectives. For example, annual water allocations to system 

water contractors (that is, the fraction of full-contract water 

entitlements that contractors can expect to receive during the 

coming year) are based on current water stocks and forecast 

water supplies, the latter being dependent on near-term climate 

forecast information. 

Because of the importance of climate in system design 

and operations, it is apparent that climate change could 

translate into changed design and operational assumptions 

about resource supplies, system demands or performance 

requirements, and operational constraints, impacting all sectors of water resources management. The significance of such 

changes depends on the increment of climate change over the 

project life cycle and the operational outcome of concern. If 

an increment is sufficiently large, the assumed hydroclimatic 

variability underlying system design may no longer be valid.

1.4 Other Changes Affecting Water Resources 

Management

Many dynamic processes have and will continue to 

impact water resources management in addition to climate 

change (Climate Change Science Program, 2008a). Important 

changes in land cover and land use, water consumption, and 

water resources infrastructure will also affect water resources 

management.

Land cover and land use changes over time can result 

in changes to basin runoff patterns and sedimentation rates, 

which could change flood peaks, impact geomorphology, and 

alter reservoir storage for water supply, flood storage, and 

other uses. Land cover and land use changes include residential and commercial development, deforestation, reforestation, and wildfires. These changes may also affect hydrologic 

stationarity and the uncertainty in flow-frequency estimates. 

Withdrawal and consumption of water change as a result 

of changing economic activity (for example, industry and 

irrigation), changes in population, and changes in values. 

These changes can have a tremendous impact on water availability (Lettenmaier and others, 1999; Vorosmarty and others, 

2000) and can result in altered base flow to streams, changing 

temperature and chemistry of streamflow, saline water intrusion in some coastal and inland settings, changes in groundwater levels, and land subsidence in certain hydrogeologic 

settings. Ground water is being depleted in many areas, with 

consequences for present and future ground-water availability 

and surface-water supplies. Fast population growth in the arid 

and semiarid regions of the United States is already stressing 

limited water supplies. 

Water resources infrastructure, such as dams, levees, 

and locks, must be maintained to provide safe and functional 

operations. Deferred maintenance accelerates deterioration 

(American Society of Civil Engineers, 2005), and natural 

processes, such as subsidence, sedimentation, changes in sea 

level, and seismic events, can also reduce infrastructure performance over time. 

These processes often occur concurrently and may have 

interactions. Climate change adds further complexity. In some 

cases, the combination of these many influences on water 

resources may exacerbate existing problems. In other cases, 

it is possible that the interactions between different processes 

will diminish impacts to water resources systems. For example, the aging and poorly maintained levee infrastructure, combined with the growth of residential, commercial, and industrial development in flood plains (with or without levees), 

has substantially increased flood risk on a national level. In 

some locations, climate impacts will exacerbate this problem 

due to increased precipitation intensity, higher peak runoff, 

or changes to the form of precipitation that increase runoff. 

However, in other locations, climate impacts may reduce this 

problem through decreases in precipitation.

Water managers have long recognized that these dynamic 

processes affect water resources. However, political and social 

institutions often implicitly assume that conditions are static 

or stationary. The engineering and economic approaches 

that underlie virtually all water planning in the United States 

assume that the underlying climate and hydrologic processes 

are stationary, even if their statistics are not perfectly known. 

Effective management of our existing water resources infrastructure depends on adaptation to current realities—realities 

of the physical infrastructure, the competing demands for 

water, public values, and climate. None of these are static and 

table 1 lists some potential changes to be included in water 

resources management decisions.

Key Point 2: Climate change could affect all sectors of 

water resources management, since it may require changed 

design and operational assumptions about resource supplies, system demands or performance requirements, 

and operational constraints. The assumption of temporal 

stationarity in hydroclimatic variables should be evaluated 

along with all other assumptions.

Key Point 3: Climate change is but one of many challenges 

facing water resource managers, and a holistic approach to water 

resources management includes all significant drivers of change.

 Climate Change and Water Resources Management: A Federal Perspective
Table 1. Potential environmental and socioeconomic changes 

affecting water resources management decisionmaking.

[After Nicholls and others, 2008]

Climate-induced Non-climate-induced

Changes in rain-snow partitioning Vertical land movement

Changes in precipitation intensity Population growth

Accelerated sea level rise Changes in land use

Changes in sea-surface temperature Changes in societal values

Changes in wind and wave patterns Changes in water use

Changes in sediment budgets Changes in sediment budgets

Altered wildland fire conditions Changes in economic conditions

Changes due to climate adaptation Infrastructure resourcing

measures

Changes due to mitigation measures

1.5 Sector Impacts Due to Climate Change 

Potential water resources management sector impacts 

are briefly summarized below, but a full discussion is beyond 

the scope of this report. The sector impacts discussed here 

are based largely on the IPCC Fourth Assessment Working 

Group II Report (Intergovernmental Panel on Climate Change, 

2007b) and the IPCC technical paper on climate and water 

(Intergovernmental Panel on Climate Change, 2008), to which 

the reader is directed for additional information. The Climate 

Change Science Program’s Synthesis and Assessment Product 

4.3 (Climate Change Science Program, 2008a) and the American Water Works Association Research Foundation’s primer 

(Miller and Yates, 2006) also provide useful summaries of 

potential climate change impacts on water resources. 

Water availability for municipal and industrial use, 

irrigation, navigation support, hydropower, and environmental 

flows is a significant concern in regions throughout the United 

States. Potential climate change impacts affecting water availability include changes in precipitation amount, intensity, 

timing, and form (rain or snow); changes in snowmelt timing; and changes to evapotranspiration (Intergovernmental 

Panel on Climate Change, 2007a, b). The results from several 

general circulation models agree that the southwestern United 

States is likely to experience precipitation and evapotranspiration changes that result in less runoff and water availability 

(Milly and others, 2005; Intergovernmental Panel on Climate 

Change, 2007a). The prudent use of reservoir storage, as well 

as conjunctive surface-water and ground-water management, 

are strategies that water managers employ to optimize water 

availability. The existing water infrastructure may or may not 

be able to accommodate different amounts or temporal patterns of streamflow and still serve their intended purposes. In 

areas that experience a decrease in water availability, competition for water among users will likely increase. Users with the 

lowest priority water rights are most likely to experience problems. In these areas, decreased water supplies could adversely 

affect economic development, recreational opportunities, or 

habitat. 

Water demand for irrigation may increase as transpiration increases in response to higher temperatures. However, 

more efficient water use by plants as a result of higher carbon 

dioxide concentrations may reduce this impact. Some areas 

may also experience an extended growing season, which could 

increase demand. The demand for water in thermal energy 

generation could either increase or decrease, depending on 

future trends in water use efficiency and the development of 

new power plants. Demand might decrease in areas receiving increased precipitation, depending on agricultural and 

municipal adaptation strategies. These changes in demand may 

require water managers to reevaluate the effectiveness of current demand management strategies. 

Water quality is impacted by changing precipitation 

and temperature resulting from climate change (Great Lakes 

Water Quality Board, 2003; Climate Change Science Program, 

2008a). The resulting local and short-term impacts on ecological thresholds are of greatest concern, rather than the annual 

medians that are commonly reported (Murdoch and others, 

2000). Increasing air temperatures may lead to increased 

water temperature, which can affect habitat suitability and the 

chemical properties of water. Altered water temperature in 

reservoirs and lakes influences the potential for algal blooms, 

which can further reduce oxygen levels (Poff and others, 2002; 

Intergovernmental Panel on Climate Change, 2007b). Changes 

in water availability may affect concentrations of suspended 

sediment, nutrients, and chemical contaminants in rivers and 

lakes. Changes to precipitation intensity and frequency influence non-point-source pollution (that is, pollutants washed 

from agriculture fields, roads, and other land surfaces by runoff). In areas with melting glacial ice and permafrost, previously frozen ground may become more susceptible to erosion, 

altering sediment transport.

Stormwater and wastewater infrastructure may need to 

include climate change effects in their design and evaluation 

to improve performance under changing water availability, 

water demand, and water-quality conditions. Likewise, the use 

of contemporary best management practices to control future 

non-point-source pollution situations may be most effective 

if system developments are planned in the context of possible 

future climate conditions. 

Flood risk reduction structures, water-system operational 

strategies, and resource management decisions may face more 

intense rainstorms, more events of rain on snow, and greater 

portions of watersheds participating in winter rainfall-runoff 

generation (Intergovernmental Panel on Climate Change, 

2007a, b). These changes may create more frequent and more 

severe flooding of some rivers and lakes. However, because 

of uncertainties in climate models and flood record analyses, 

the nature of changes in specific locations remains uncertain 

and will require detailed study. The design and evaluation of 

flood-risk-reduction infrastructure should use the most recent 

available data and consider possible future climate conditions, 

including shifts in the seasonal timing of typical high flows. 

Spring high flows in snow-dominated watersheds are already 

shifting earlier in the year because of earlier snowmelt associ1 Introduction 
ated with higher temperatures (fig. 2). Reservoir water control 

plans may need to be adjusted to reflect new flood regimes. 

Different melt and thaw patterns could alter the frequency and 

timing of ice-jam floods. Glacial outburst floods pose a threat 

in some western alpine mountain regions and in some areas of 

Alaska. 

Wildland fires may increase due to climate changes that 

result in hotter, drier conditions, and changes in plant and 

insect phenology that result in increased forest or species 

mortality. Fires play an important role in water resources 

management, with potential impacts to public safety, runoff 

characteristics, erosion, and sediment transport in fire-scarred 

areas. In a study of wildfire activity in the western United 

States between 1970 and 2003, Westerling and others (2006) 

noted a relation between wildfire frequency and snowmelt timing (fig. 5) that appeared to be due primarily to climate rather 

than other drivers. 

Ecosystem or species response in the face of climate 

change is highly complex (Davis and others, 1998; Poff and 

others, 2002); detailed studies may be required to assess and 

predict responses in environmentally sensitive areas. Potential 

aquatic ecosystem impacts include changes in water temperature and quality, alterations in seasonal streamflow and flood 

regimes, variations in rate and timing of flow from springs and 

seeps, and modifications to the extent and depth of wetlands. 

These impacts would also affect riparian and upland wildlife. 

Figure 5. Average frequency of western U.S. forest wildfires by 

elevation and early, mid-, and late snowmelt years from 1970 to 

2002 (after Westerling and others, 2006).

Figure 6. Mean seasonal precipitation 

changes over North America: DecemberJanuary-February (left) and June-JulyAugust (right) fractional change in 

precipitation from 1980–1999 to 2080–2099, 

averaged over 21 models (see fig. 11.12; 

Intergovernmental Panel on Climate 

Change, 2007c) superimposed over a map 

of navigation from DOT freight analysis 

(see red lines; Caldwell and others, 2002).

Risks to aquatic ecosystems and neighboring animal communities may be especially pronounced in snowmelt-dominated 

watersheds and watersheds in Alaska, the Rockies, and the 

Northwest where glacier meltwater is a significant contributor to summer streamflow. Accelerated glacier retreat will 

result in short-term increases in summer streamflow (Fountain and Tangborn, 198) but a longer term decrease in flow, 

potentially rendering some high-elevation streams intermittent. Ibanez and others (2006) suggest that identification of 

vulnerabilities and leading indicators of change, plus carefully designed monitoring, can provide the most insight into 

potential climate change impacts to ecosystems and responses. 

Hannah and others (2002) report that the use of protected areas 

to adapt for climate change impacts under a moderate climate 

change scenario can be an important conservation strategy. 

The management of water systems can both significantly 

affect aquatic and riparian ecosystems and be significantly 

affected by management objectives within those ecosystems.

Sea-level changes can cause a number of impacts in 

coastal and estuarine zones, including changes in shoreline 

erosion, inundation or exposure of low-lying coastal areas, 

changes in storm and flood damages, shifts in the extent and 

distribution of wetlands and other coastal habitats, and alterations to salinity intrusion into estuaries and ground-water 

systems (National Research Council, 1987; Poff and others 

2002; Climate Change Science Program, 2008c). The expected 

sea-level rise, combined with possibly heightened storm surge, 

would have a profound effect on coastal systems, with the 

most dramatic effects being wetland loss, loss in the productivity of estuaries, changes in barrier islands, and increased 

vulnerability to coastal erosion and flooding. The impacts 

would be especially pronounced if the frequency and intensity 

of hurricanes increase. Given that estimates of future rates of 

sea-level rise remain uncertain (Rahmstorf and others, 2007; 

Domingues and others, 2008), planning and design studies 

should consider designs that are most appropriate for a range 

of possible future rates of rise (National Research Council, 

1987; Cayan and others, 2008). Strategies that would be 

appropriate for a broad range of rise possibilities could receive 

preference over those that would be optimal for a particular 

rate of rise but unsuccessful for other possible outcomes. 

Navigation impacts have recently been examined by the 

International Navigation Association (PIANC) (Moser and 

others, 2008b). They identified drivers of climate change, 

including changes in temperature, precipitation, waves, sea 

10 Climate Change and Water Resources Management: A Federal Perspective
level, ice, geomorphological variables, and socioeconomic and 

political conditions (ACIA, 2004; Bindoff and others, 2007; 

Lemke and others, 2007; Meehl and others, 2007; Trenberth 

and others, 2007; Nicholls and others, 2008). Maritime 

impacts identified by PIANC include altered infrastructure 

vulnerability to sea level, waves, and wind; changed conditions affecting vessel maneuvering; variations in ice cover 

impacting polar access (ACIA, 2004, 2005); and changes in 

sea spray, affecting icing. Changes in water availability and 

the resulting changes in channel depth and velocity will affect 

inland navigation, trafficability, and infrastructure operations 

(fig. 6) (Moser and others, 2008a; Intergovernmental Panel on 

Climate Change, 2007c). Compared to the maritime sector, the 

inland navigation sector may have more capacity to respond to 

climate drivers because the water resources infrastructure can 

modify runoff. Increased use of commercial inland navigation 

over land transportation may mitigate GHG emissions. 

Energy production and demand are especially sensitive to 

climate change (Intergovernmental Panel on Climate Change, 

2007b). These effects are magnified in regions with both 

heating and cooling needs. Ice-storm frequency or intensity, 

as well as permafrost extent, affects the energy infrastructure, 

including transmission lines and gas and oil pipelines (fig. 7). 

Hydropower generation will be affected by changes in water 

availability, particularly in snowmelt-dominated basins, where 

impacts have already been reported (Hamlet and others, 2002; 

California Energy Commission, 2005; Northwest Power and 

Conservation Council, 2005). Hydropower production at facilities that are operated to meet multiple objectives (for example, 

flood-risk reduction, irrigation, municipal and industrial water 

supply, navigation, in-stream flow augmentation, and water 

quality) may be especially vulnerable to changes. Changes in 

water availability and water quality also affect thermal energy 

production. For example, power plants have had to limit generation in some areas because of limited water availability for cooling water, leading some public officials and citizens to express 

concerns about the potential water use of proposed new plants 

(U.S. Department of Energy, 2006). Linkages between water 

and energy also exist because of water use in energy production 

and energy use in water treatment and distribution.

1 Introduction 11

Figure 7. Fractional area of the country affected by ice storms. 

The plot shows the average 1947–2003 ice-storm trajectory (green 

line) and deviations (dashed gray lines) (Jones and others, 2004).

2 Tracking Climate Change Impacts

Monitoring data is essential for understanding and 

tracking the impacts of climate change. This chapter seeks to 

address the following questions:

How are monitoring data used to track climate 

impacts? 

How do data inform physical system understanding?

What monitoring networks currently exist?

2.1 Tracking Hydrologic Change: Monitoring 

Networks

Current projections of climate changes and their potential 

impacts harbor many uncertainties, and these uncertainties are 

unlikely to dissipate in the near term. Within these uncertainties 

are the possibility for surprises, which could be unpleasant and 

quick to appear. In this context, a strategy that balances detecting and adjusting to changes against extrapolating (including 

modeling) and anticipating changes will be most prudent. Thus, 

monitoring of climatic and hydrologic conditions plays an 

important role in addressing potential climate changes. 

To detect hydrologic changes due to climate change or 

other causes, data from long-term monitoring networks are 

essential for establishing baseline conditions and tracking any 

changes over time. Monitoring networks are also essential 

for fully understanding the hydrologic processes that lead to 

changes in water resources and for calibrating and validating 

models used to project future conditions. In turn, information 

about possible or likely future changes to climate improves the 

effectiveness of planning studies and allows the development 

and implementation of reasonable strategies for adapting to a 

changing climate. 

Key Point 4: Long-term monitoring networks are critical 

for detecting and quantifying climate change and its impacts. 

Continued improvement in the understanding of climate change, 

its impacts, and the effectiveness of adaptation or mitigation 

actions requires continued operation of existing long-term 

monitoring networks and improved sensors deployed in space, in 

the atmosphere, in the oceans, and on the Earth’s surface.

Monitoring networks include in situ methods as well as 

remote sensing technologies such as radar and satellites. Existing data allow us to look at data retrospectively. However, 

monitoring networks must continue to operate into the future 

if we are to detect future changes in hydrologic systems due 

to climate change (or the lack thereof) and to craft effective 

responses.

To be useful for climate change studies, monitoring 

networks need to be in place in locations relevant to water 

managers. For example, monitoring stations should be located 

in watersheds important for water supply or vulnerable to 

changes in water quality. In addition to monitoring of the 

natural system, data on human water use can be valuable in 

planning for climate change. The USGS periodically publishes 

estimates of water use in the United States by sector (for 

example, Hutson and others, 2004) compiled from data collected by State and local agencies. The periodic nature of these 

reports and the varying data-collection methods limit their 

utility for evaluating demand interactions with climate. 

Climate change is easier to detect on global to regional 

scales. Monitoring networks for detecting change are especially valuable when they are regional or involve local 

networks that are integrated to allow regional analyses. Also 

needed for planning and operational analysis is a comprehensive set of parameters that characterize current and future 

climate conditions. 

A number of Federal, State, and local agencies operate 

observation networks that are valuable for climate change 

analysis. The USGS operates the largest water-monitoring 

network in the United States, as well as biological-monitoring 

networks. These are briefly described in the inset box. NOAA 

operates the Nation’s largest meteorological network and 

provides data on oceans. The NOAA observational networks 

are also described in an inset box. Other Federal agencies 

also maintain important water-monitoring networks, such as 

the Natural Resources Conservation Service’s snow surveys 

and Snowtel network. State and local agencies are able to 

supplement these larger networks with needed local data. 

USACE and Reclamation also conduct project-specific water 

resources-monitoring activities. 

Key Point 5: Monitoring needs to focus on locations 

that describe the climate signal (for example, upstream and 

downstream from major water-management infrastructure or in 

vulnerable ecological reaches).

2.2 Tracking Hydrologic Change: Trend Analysis

As discussed in chapter 1, climate change is expected to 

cause changes to streamflow, precipitation, and other hydroclimatic variables. The continuous long-term streamflow and 

meteorological records described in the preceding section are 

critical for detecting trends or shifts in the statistics of historical streamflow or other hydroclimatic variables. Such nonstationarity in hydroclimatic conditions would represent a change 

from the assumptions that have been used to design and manage water resource systems. Consequently, it is important to 

know if and how trends manifest themselves. 

Trend detection must be carried out with care, as trends 

may also be caused by land use changes, changes in water 

infrastructure, or other factors. Furthermore, while the magnitude of a trend may be relatively easy to quantify, its statistical significance may be more ambiguous because of natural 

climate variability and long-term persistence, which can cause 

oscillatory patterns in long-term hydroclimatic records (Cohn 

and Lins, 2005). 

•

•

•

2 Tracking Climate Change Impacts 13
Box 2.1 Key USGS Monitoring Networks for 

Water Resources Management

Water

The USGS operates the National Water Information System 

to monitor the occurrence, quantity, quality, distribution, 

and movement of surface and underground waters. Specific 

streamflow, ground-water, and water-quality stations have 

been identified for use in studying long-term trends. The 

Hydroclimatic Data Network (HCDN) is a subset of the national 

network of streamgages that were screened against strictly 

defined criteria of measurement accuracy and natural conditions 

to provide a dataset for studying climate variations (Slack and 

Landwehr, 1992; Slack and others, 1993). Numerous watershed 

changes may have taken place since the HCDN sites were 

first identified, and the identification of a suitable network of 

streamgages is being revisited. Among the thousands of groundwater wells that the USGS monitors annually, about 500 wells 

have been identified for inclusion in the Ground-Water Climate 

Response Network (Cunningham and others, 2007). These wells 

are used to monitor the effects of droughts and other climate 

variability on ground-water levels. The USGS also collects and 

analyzes chemical, physical, and biological properties of water, 

sediment, and biological tissue samples from both surface- and 

ground-water sources. Some of these sites are included in two 

water-quality networks that were created to provide long-term 

measurements, the Hydrologic Benchmark Network (HBN) and 

the National Stream Quality Accounting Network (NASQAN) 

(Hooper and others, 1997; Murdoch and others, 2005). The 

USGS also operates a small program to monitor glaciers that 

includes the longest detailed observations of glacial change in 

North America. 

Ecology

Through the Natural Resources Monitoring Partnership, the 

USGS is consolidating metadata on current monitoring efforts 

(by Federal, State, local, and nongovernmental entities) to make 

common monitoring protocols available and to allow researchers 

to discover current monitoring efforts by location. In addition, 

the USGS coordinates a Breeding Bird Survey, the Amphibian 

Research and Monitoring Initiative, and the Western Mountain 

Initiative. Water is intrinsic to the function of all ecosystems, and 

a Climate Effects Network is in development that will build on 

existing programs. The USGS is also helping to coordinate the 

development of a new USA National Phenology Network that is 

being designed to monitor periodic plant and animal life-cycle 

events. Examples include the timing of leafing and flowering, 

agricultural crop stages, insect emergence, and animal migration. 

All of these monitoring efforts include data that can be used to 

track the effects of climate change on ecology.

Trend analysis should also be conducted over large areas 

affected by similar weather systems. However, the analysis must 

be done carefully to consider cross-correlation among the stations 

in a region. Douglas and others (2000) demonstrate that ignoring 

spatial correlation can lead to erroneous conclusions about the 

existence of regional trends in low flows and high flows. Vogel 

and others (2001) also note the importance of considering spatial 

correlation in an analysis of record-breaking floods.

It is important to try to understand the drivers behind 

the trends in order to understand whether the trend is likely 

to persist, plateau, or reverse. For example, a trend towards 

Box 2.2 Key NOAA Monitoring Networks for 

Water Resources Management

Three of NOAA’s line offices, the National Weather 

Service (NWS), the National Environmental Satellite Data and 

Information Service (NESDIS), and the National Oceanographic 

Service (NOS), monitor, quality control, and archive data from 

several key climate and hydrologic systems. The National 

Climatic Data Center (NCDC) is the national archive for climate 

data and products (http://www.ncdc.noaa.gov/oa/ncdc.html).

The U.S. Cooperative Observer Network (COOP) consists 

of weather stations operated by State universities and State or 

Federal agencies; it also includes privately owned stations that 

are managed and maintained by the NWS. The network includes 

regular NWS offices, airports with weather stations operated 

by the NWS or the Federal Aviation Administration (FAA), and 

U.S. military bases. There are typically about 8,000 stations 

operating in any one year. The earliest data are from 1886 and are 

organized by month.

The National Operational Hydrologic Remote Sensing Center 

(NOHRSC) archives the National Snow Observation Database 

and conducts airborne snow surveys for satellite snow-cover 

mapping, snow modeling and data assimilation, and development 

of visualization tools and integrated snow datasets for geospatial 

applications. Other variables being monitored by satellite include 

water vapor/atmospheric precipitable water and the vegetation 

health index (at 15 km). Through the NOS/National Estuarine 

Research Reserves, NOAA tracks nearshore water-quality and 

nutrient loads. NOAA scientists are combining this information 

with other weather and climate data to assess the effects of 

human activities on ecosystems and the impact of onshore 

pollutants and runoff into the marine environment. Data are 

collected on water temperature, salinity, pH, dissolved oxygen, 

and turbidity.

The U.S. Climate Reference Network (USCRN) is a 

network of climate stations now being developed as part of a 

NOAA initiative. The primary goal of the USCRN is to provide 

future long-term homogeneous observations of temperature 

and precipitation that can be coupled to long-term historical 

observations for the detection and attribution of present and 

future climate change. 

Several of these datasets are used to develop integrated 

products, indices, and outlooks (such as the U.S. Drought 

Monitor, crop moisture index, and so forth) with other agencies 

and partners. The U.S. Drought Monitor, which is produced on 

a weekly basis, is a collaborative effort between Federal and 

academic partners, including the National Drought Mitigation 

Center, the USDA/OCE/WAOB/Joint Agricultural Weather 

Facility, the NOAA/NWS/NCEP/CPC, and the NOAA/NESDIS/

National Climatic Data Center. The NWS River Forecast Centers 

provide streamflow forecasts for the United States. Their Water 

Resources Product Suite (WRPS) includes a comprehensive suite 

of high-resolution (1–10 km), gridded hydrologic state variable 

and flux datasets and derived variables. 

higher runoff peaks that is driven by an increase in impervious surfaces in an urbanizing area is likely to persist unless 

the driver changes (Dietz 2007). Understanding the cause of 

the trend can also allow modeling of future runoff peaks using 

future development plans as an input. Finally, as McCabe and 

Wolock (2002) point out, it can also be important to identify 

whether a trend occurs as a gradual change or as an abrupt 

shift. 

14 Climate Change and Water Resources Management: A Federal Perspective
Water managers are often interested in estimating the 

frequency at which droughts and floods of specified magnitude may occur. Changes in the probability of extreme events 

such as floods and droughts can be difficult to detect because 

the events are inherently infrequent. If changes are observed, 

then the frequency analysis may need to be adjusted accordingly. Although several researchers have proposed methods 

for incorporating trend-based changes into frequency analysis 

(Strupczewski and Kaczmarek, 2001; Strupczewski and others, 2001; Cunderlik and Burn, 2003; Cunderlik and Ouarda, 

2006; El Adlouni and others, 2007; Leclerc and Ouarda, 

2007), it remains to be determined which would serve as the 

most appropriate procedure (for example, deciding on trendevaluation period or handling low-frequency variability). The 

need to include nonstationarity in flood-frequency estimation 

is revisited in chapter 6. 

Despite its limitations, trend detection can help water 

managers recognize if the data upon which the design and 

operation of water resource systems were based are no longer 

consistent with current conditions. For example, trends toward 

less spring snowpack and earlier spring runoff have been 

observed in mountainous watersheds in the western United 

States as well as in parts of New England (Hodgkins and 

others, 2003; Mote 2003, 2006; Stewart and others, 2005; 

Hodgkins and Dudley 2006a, b; Knowles and others, 2006). 

These trends are consistent with general circulation model 

projections of climate change impacts. The studies document 

clear trends in the timing of high flows but do not demonstrate 

changes in the overall flood risk in the basins studied.

On the other hand, possible changes indicated by GCM 

projections have not always been observed. GCM projections 

have indicated a possibility of increased heavy rain events 

leading to more frequent and intense flood events (Intergovernmental Panel on Climate Change, 2007b). However, most 

studies of the historical streamflow record have not shown a 

consistent increase in flood events in the United States (Lins 

and Slack, 1999; Douglas and others, 2000; McCabe and 

Wolock, 2002; Kundzewicz and others, 2005). One study of 

very large rivers suggests an increase in the largest floods in 

some of the world’s largest river basins (Milly and others, 

2002). 

2.3 Improving Process Understanding and 

Modeling Capabilities 

Observational data have long been used in studies that 

seek to improve our understanding of hydrologic processes. 

In terms of climate change, IPCC (2007a) reports that observational data are part of what has allowed increased sophistication of analyses, improved understanding of physical 

processes, the resulting process models, and characterization 

of the uncertainty of model results. Climate change may result 

in complex interactions in natural systems. The effects on 

processes, such as ground-water and surface-water interaction, 

ecosystem change, or pollutant transport, will be difficult to 

assess without continued monitoring.

These data are also critical for calibrating and validating 

models and initializing model projections. Without monitoring networks, we would have no basis for evaluating the many 

models that are routinely used in water resources today, including, for example, the hydraulic models that are used to route 

flood flows or the watershed models that are used to estimate 

streamflow and water-quality conditions under current land 

use. The continued usefulness of models under a changed climate also requires continued collection of observational data.

2 Tracking Climate Change Impacts 15

3 Anticipating Climate Change: 

Available Climate Information for 

Decisionmaking in Long-Range 

Planning

This chapter focuses on several questions about how 

climate information can be related to long-term, long-range 

water management planning and decisions:

How has climate traditionally been represented in 

water management? 

What motivates the use of an expanded set of climate 

information? 

What are some issues and limitations in considering an 

expanded set of climate information?

To this end, two classes of long-range water-management decisions are discussed: general system evaluations and 

flood-risk evaluations. For the first class, a generalized planning 

framework is introduced (section 3.1) to describe how longrange evaluations are set up by assumptions for possible future 

supplies, demands, and operating constraints. The role of climate 

information in establishing these assumptions is then discussed, 

including the traditional use of instrumental records and the 

potential use of expanded climate information. Expanded climate 

information might include a mix of paleoclimatic evidence 

of hydroclimatic conditions, stochastic modeling to augment 

sequence possibilities, and (or) climate-projection information to define climate possibilities during the future planning 

horizon. For the second class, the probabilistic and deterministic 

approaches for flood-risk evaluation are discussed (section 3.2). 

The focus is placed on the underlying climate assumptions and 

the challenges introduced by a changing climate while conducting such evaluations. Thereafter, several recent Reclamation and 

USACE studies featuring the expanded use of climate information are summarized (section 3.3) to highlight common themes 

and implications for planning processes. Finally, a summary 

discussion is offered on how these traditional and potential applications of climate information call attention to system portrayal 

paradigms, particularly in adaptation planning, and research 

avenues to advance long-range decisionmaking capabilities.

3.1 Use of Climate Information in General LongRange Systems Evaluations

Long-range planning studies for water resources management typically focus on questions about proposed system 

changes (either physical or operational). Climate information 

is reflected in such studies through assumptions made about 

water supplies, demands, and operational constraints (fig. 8). 

Water-supply assumptions are developed to portray an 

appropriate envelope of supply possibilities suitable for the 

planning horizon (that is, surface water and ground water; 

•

•

•

Instrumental Records:

observed weather (T

and P) and runoff (Q)

Climate Projections:

modeled weather and

runoff

Enhanced Instrumental

Record: reconstructed

weather and/or runoff

statistical modeling watershed simulation

Q T, P, and Q T, P, and (or) Q

Supply Variability Demand Variability Operating Constraints

Operations and Uncertainties

Figure . Analytical framework for relating climate to water 

supplies, demands, and constraints.

3 Anticipating Climate Change: Available Climate Information for Decisionmaking in Long-Range Planning 17

statistical description of possibilities, including mean, variance, sequences, and so forth). Water-supply assumptions are 

a direct reflection of the expected climate during the study’s 

planning horizon. As discussed in section 3.1.1, water-supply 

assumptions have traditionally been based on available historical observations (for example, streamgages and ground-water 

well logs). These assumptions are based on the premise that 

the range of observed supply variability is a reasonable proxy 

for future supply possibilities. 

Demand assumptions are characterized for each of the 

agricultural, municipal, in-stream, and other uses featured 

in the study. The focus of demand assumptions is often on 

identifying demand “upper limits.” However, for some studies, 

the objective might be to identify demand limits relative to 

available supplies, constraints, and required system performance. Demands are often characterized at a district level 

(for example, irrigation district and municipality). Physical 

assessments are used to estimate water demands relative to 

climate and other drivers (for example, district-level irrigation 

demands, given a scenario mix of cropping choices, temperature, precipitation, and water-use efficiencies). 

The final category of assumptions involves the various operational constraints affected by an underlying climate 

assumption. For example, hydrologic event possibilities are 

predicated on an underlying climate regime (section 3.2) 

and affect the required flood-control rules at surface-water 

reservoirs. In turn, flood-control rules affect the constraints on 

water-supply storage. Further, aquatic ecosystems and riparian environments depend on air temperature and hydrologic 

regimes, which affect the assumed constraints on reservoir 

release patterns to support ecosystems. 

3.1.1 Establishing Assumptions and a Plausible 

Planning Future Through Traditional Use of 

Instrumental Records

Long-range planning assumptions for supplies, demands, 

and constraints have typically been based on information 

from the recent historical and observed record (labeled here 

as the “instrumental record”). In this practice, assumed water 

supplies are based on naturalized flows, which are computed 

from historical streamgage data, ground-water well logs, and 
impairment information. Water demands would be based on 

historical water use and land cover. 

Reliance on the instrumental record to establish these 

assumptions implies that the past is a reasonable proxy for the 

future. In other words, it is assumed that the range of observations from the instrumental record includes enough situations 

to represent a reasonable envelope of plausible future conditions appropriate for planning. It is possible, though, that 

the future may contain situations that have not already been 

observed (for example, more extreme months or seasons, and 

more severe and sustained droughts). However, this possibility 

has generally not been compelling enough to trigger planning 

assumptions other than those supported by the instrumental record. This situation appears to be changing, however 

(see section 3.3), particularly as stakeholders become more 

informed about the scientific community’s improved knowledge on climate of the preinstrumental record, recent trends 

in climate, and the projected future climate, and they expect 

such knowledge to be factored into planning. The following sections discuss opportunities to affect how supply and 

demand assumptions are developed in order to incorporate this 

improved knowledge.

3.1.2 Expanding the Set of Plausible Planning 

Futures Using Stochastic Modeling and 

Paleoclimate Information 

Variations and timing of extremes within a particular set 

of supply-and-demand assumptions may be very important in 

determining whether or not a system can perform satisfactorily. These variations reflect hydroclimatic variability (that is, 

variations in temperature, precipitation, and runoff over various time scales). To expand on the historical record basis for 

planning, one planning response is to preserve the statistics of 

the instrumental record, while allowing for possible changes 

in the sequencing of conditions. This gives rise to the plausibility of developing synthetic hydroclimatic time series using 

stochastic modeling. Doing so introduces an expanded set 

of planning assumptions about plausible droughts and other 

hydroclimatic extremes. 

Generally speaking, stochastic development of hydroclimatic scenarios involves the following steps: (1) choosing a 

reference period from which hydroclimatic statistics will be 

preserved; (2) collecting data from the reference period; (3) 

building a stochastic model, perhaps using parametric (Stedinger and Taylor, 1982a,b; Salas, 1993) or nonparametric 

techniques (Lall and Sharma, 1996); (4) verifying that the 

model preserves reference hydroclimate statistics and autocorrelation characteristics; and (5) applying the model to generate 

synthetic hydrologic sequences for planning purposes. For this 

discussion, the emphasis is on step (1). The reference period 

must portray a climate that is still relevant for the planning 

future. The instrumental record offers one reference period to 

support stochastic modeling. Other reference periods might 

be considered, including those from the paleoclimatic record 

(for example, evidence found in tree rings, sediment deposits, 

and sand dunes). Other uses for the paleoclimatic record are 

discussed below. 

A variety of techniques have been developed to translate paleoclimatic data into hydroclimatic reconstructions 

(appendix A). For example, tree ring records have been used 

to reconstruct annual streamflow in various western U.S. 

basins. In general, these reconstructions are less reliable as 

indicators of past hydroclimatic magnitudes in any specific 

year and are instead more reliable as relative state indicators 

(that is, whether a reconstructed year was wet or dry relative 

to the reconstructed period median). Such state information 

is particularly useful for planning when the affected decision 

is sensitive to system performance under drought or other 

sequence variation possibilities. This has motivated numerous 

water resource agencies to incorporate streamflow reconstructions based on tree rings into their planning assumptions about 

supply variability (Woodhouse and Lukas, 2006; Bureau of 

Reclamation, 2007). 

Paleoclimatic information may indicate a wider range of 

hydroclimatic variability prior to instrumental records. Determining the relevance of paleoclimatic information to support 

planning in today’s changing climate remains a matter of 

research. Such context also depends on recent climate trends 

and projected climate change that may exist outside of the 

climate envelope indicated by paleoclimatic information. 

Given a choice to incorporate paleoclimatic information 

into planning, there are several ways in which such information can be used. One approach is to directly use the information for both reference climate statistics and sequencing. 

This involves the assumption that the hydroclimatic statistics 

and sequence from the reconstructed record are valid for 

future planning. A second approach might build on the first 

to include stochastic modeling to expand the set of sequence 

possibilities. Each sequence would reflect the statistics of the 

reconstructed record but would offer different sequencing. A 

consequence of these approaches is that assumed runoff magnitudes (for example, monthly-to-annual volume possibilities) 

are a representation of the paleorecord. It may be preferred 

to have these magnitudes represent the instrumental record 

while retaining the sequence possibilities of the paleorecord. 

This gives rise to a third approach, where the stochastic model 

is first used to generate categorical sequences (for example, 

wet versus dry), and a second stage is used to associate runoff 

magnitudes from the instrumental record (Bureau of Reclamation, 2007).

Key Point 6: Paleoclimate information and stochastic 

modeling can be useful for developing climate scenarios that 

include a wide range of potential hydroclimatic conditions. The 

expanded variability may allow a more robust evaluation of 

planning alternatives, particularly when there is concern that study 

outcomes and decisions may be sensitive to climate assumptions.

18  Climate Change and Water Resources Management: A Federal Perspective
3.1.3 Defining Plausible Planning Futures Based 

on Climate Projection Information 

Given the evidence of recent climate trends and projected 

future climate conditions, there may be motivation to rely less 

on the instrumental record or paleoclimatic record and instead to 

relate planning assumptions to projections of future temperature 

and precipitation. These climate projections are based on global 

climate modeling that represents our current understanding of 

cause and effect in the climate system. The decision to use such 

climate projections depends on the following:

Whether the planning horizon is relevant in a climate 

change context [that is, it spans at least several decades 

into the future, given that climate is generally not 

characterized for periods less than multiple decades, and 

climate change must be measured over multiple decades 

(Intergovernmental Panel on Climate Change, 2007a)]; 

Whether such information has been “regionalized” to a 

spatial resolution that is fine enough to support the development of planning assumptions (for example, using 

downscaling techniques described in appendix B); and 

Whether such downscaled projections are viewed to 

contain information that is reliable enough for planning.

Given an affirmative determination on each of these 

factors, a general procedure might be used to connect climate 

information to planning assumptions: 

Survey contemporary climate projections that have 

been regionalized to the planning area and span the 

future planning horizon. 

Decide which projections, variables, and aspects to 

incorporate. 

Relate the retained information to natural conditions 

(for example, hydrology and ecosystems) and social 

conditions (for example, water demand drivers) that set 

up planning assumptions for supplies, demands, and 

constraints.

A survey of climate projections might start with 

the global dataset developed through the World Climate 

Research Programme (WCRP) Coupled Model Intercomparison Project (CMIP) [CMIP1 (Meehl and others, 2000), CMIP2 (Covey and others, 2003), and CMIP3 

(http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php)]. The WCRP 

CMIP3 efforts were fundamental to the completion of the 

IPCC Fourth Assessment Report (Intergovernmental Panel on 

Climate Change, 2007a). The CMIP3 dataset features simulation of future climates using multiple GCMs, considering 

multiple future pathways for greenhouse gas (GHG) emissions 

(Intergovernmental Panel on Climate Change, 2000). 

Regionalization of climate projections is primarily focused 

on translating spatially coarse GCMs into basin-scale information (downscaling techniques are discussed in appendix B). 

For example, many CMIP3 projections have been downscaled 

•

•

•

•

•

•

for the contiguous United States using a statistical technique 

(Wood and others, 2002) and have been made available at a 

public-access Web site. The downscaling technique underlying 

that archive development also features the subjective choice to 

compensate for climate model biases. Philosophically, it might 

be expected that a climate model’s simulation of the past should 

reflect chosen statistical aspects of the observed past. When this 

is not the case, a climate model “bias” is deemed to exist [that 

is, a tendency to simulate climates that are too wet or dry and 

(or) too warm or cool]. In that event, the regionalization procedure might be scoped to also address the issue of climate model 

bias. Whether and how this bias is accounted for in the use of 

climate projection information is a matter of subjective choice. 

Another issue with the use of climate projections is reconciling 

the time step of the projections with the temporal resolution 

required for the corresponding demand assumptions. Global climate modeling groups often report monthly values for temperature and precipitation. However, daily weather time series may 

be required to drive hydrologic simulations that reveal changes 

to runoff timing. Temporal disaggregation techniques are then 

required to provide the needed temporal resolution for temperature and precipitation projections.

After obtaining regionalized climate projection information, 

the next step is to decide which projections, variables, and aspects 

of these variable projections are relevant for the given planning 

study. Several questions might be addressed in this process: 

Should all projections be retained, or should the analyst 

apply some rationale to cull some projections from 

consideration?

Should retained projections be regarded equally or 

unequally (for example, based on perceived climate 

model skill)? 

Which aspects of the projections should be related to the 

planning study (for example, which variables and what 

statistical or sequential aspects of these variables)? 

These questions are currently a matter of research. Ultimately, answers to these questions reflect climate relevance to 

the planning study (for example, variables, statistics, and planning horizon) and regard for the relative credibility of different 

projection variables and aspects.

Given a set of chosen, relevant climate projections, the 

next step is to relate that information to the planning assumptions and ultimately to arrive at impacts. The multitude of 

approaches that accomplish this task have been summarized 

“Statistically Downscaled WCRP CMIP3 Climate Projections,” available 

at http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/.

•

•

•

Key Point 7: Current expectations about future climate 

may indicate a need to supplement historical climate information. 

Planning assumptions might instead be related to projections of 

future temperature and precipitation. This can be accomplished 

using a multitude of approaches; a best approach has yet to be 

determined. 

3 Anticipating Climate Change: Available Climate Information for Decisionmaking in Long-Range Planning 19
by Vicuna and Dracup (2007). There is not yet any clear 

“best” method to relate climate projection information through 

planning assumptions to arrive at impacts.

As there are opportunities to blend paleoclimatic and 

instrumental records while developing water-supply assumptions, there are also opportunities to blend paleoclimatic and 

projected climate information. For example, the third approach 

described in section 3.1.2 might be modified for this task. The 

paleoclimate could remain as the source of wet-dry sequences 

(that is, interannual to interdecadal variability). Then, rather 

than use instrumental records as the source for runoff magnitude 

possibilities, these magnitudes could come from runoff projections developed in association with climate projections (for 

example, change in runoff seasonality). Determining how to 

blend these sources of information remains a matter of research.

3.2 Use of Climate Information in Flood-Risk 

Evaluations

Evaluations of flood likelihood and consequences, and 

hence flood risk, can impact multiple decisions throughout 

water management. Infrastructure reliability is often evaluated 

relative to its ability to withstand unlikely flood events. Levee 

systems, canals, and dams are evaluated regularly with respect 

to their ability to endure events. Water-control plans for surfacewater reservoirs often feature “flood space” requirements linked 

to hydrologic event hazards, varying throughout the year, and 

expectations for downstream societal protection against floods. 

Climate assumptions are evident in flood-risk evaluations 

based on how hydrologic hazards are characterized. Fundamentally, the climate regime underlying the hydrologic possibilities directly determines the portfolio of hydrologic hazards 

that could occur. For this reason, it is reasonable to question 

the appropriateness of any underlying climate assumption for 

a given flood-risk evaluation.

3.2.1 Flood-Risk Evaluation Methods

Flood risk might be estimated using probabilistic or deterministic techniques. Probabilistic floods are estimated events 

associated with a probability of occurrence, typically derived 

from the observed record. The estimation procedure involves 

surveying historical hydrologic data, characterizing annual maximum floods, fitting a distribution to these annual maximums, and 

using that distribution to infer events of rare reoccurrence (for 

example, 1-in-100-year or 1-in-500-year floods). The most common framework for establishing probabilistic extremes within the 

United States is Bulletin 17–B, which presents “Guidelines for 

Determining Flood Flow Frequency” (IACWD, 1982).

Deterministic floods include design floods and Probable 

Maximum Floods (PMFs) and are estimated without assumptions about recurrence probability. For example, the PMF is 

the flood that may be expected from the most severe combination of critical meteorological and hydrologic conditions 

that are reasonably possible in a particular drainage area. The 

meteorological forcing for the PMF is the Probable Maximum 

Precipitation (PMP). The PMP is the greatest depth (amount) 

of precipitation for a given storm duration that is theoretically 

possible for a particular geographic location. To determine 

the PMP, the concepts of storm maximization and geographic 

storm translation are applied. 

3.2.2 Incorporating Climate Projection 

Information Into Flood-Risk Evaluations

Properly evaluating future flood risk within a changing 

climate remains a goal of water-management decisionmakers. 

Changes in temperature and precipitation would conceptually 

affect the characterization of flood-frequency distributions in 

a given region. The previous section discussed how instrumental records serve as the primary source of information to 

characterize flood risk. A key assumption underlying current 

probabilistic techniques is that the distribution of floods is 

regarded as stationary (chap. 1). A number of researchers have 

proposed alternative probabilistic techniques that allow for 

nonstationarity in flood event distributions. The most common 

adaptation approach is to allow the parameters of an assumed 

distribution to vary with time; nonparametric techniques have 

also been proposed. In general, additional research is required 

to establish the most suitable methods for treating nonstationarity in flood-risk evaluations for the United States.

An alternative is that flood risk be evaluated using a more 

limited set of recent observations, but extrapolating the probability of infrequent events from a short record is fraught with 

uncertainty. Furthermore, for long-term evaluations of flood 

risk, it might be questioned whether any of the instrumental 

record can be used to portray future flood risk. To that end, the 

climate projection information discussed earlier (sec. 3.1.3) 

might be surveyed for temperature and precipitation conditions relevant to flood-event estimation. However, if such 

an approach is pursued, careful examination of the relation 

between flood mechanisms and the reliability of the climate 

models to portray these mechanisms is warranted.

For probabilistic methods, the same hydrologic simulation 

techniques used to characterize water-supply assumptions under 

climate change (section 3.1.3) might be used to produce floodevent information. For example, simulated hydrologic projections consistent with climate projections might be surveyed for 

annual series of maximum flood events (or other hydrologic 

extremes of interests). Such information might be generated 

relative to an ensemble of climate projections to incorporate 

projection uncertainty into the estimation of projected floodfrequency distributions, evolving through time. There are many 

uncertainties associated with such an approach, particularly 

those introduced by the limited abilities of climate models to 

sufficiently portray hydrometeorological extremes within climate projections (Intergovernmental Panel on Climate Change, 

This framework is being explored through ongoing research supported 

jointly by Reclamation and USACE, with the focus on implications for hydrologic hazard assessments in dam safety evaluations.

20 Climate Change and Water Resources Management: A Federal Perspective
2007a). However, to the extent that monthly to seasonal climate 

conditions affect regional flood potential, this use of climate 

projection information might offer insight into the implications 

of climate change for trends in flood risk during the coming 

decades. For deterministic methods, climate projections might 

be used to guide meteorological assumptions feeding into PMP 

estimation. Questions remain about how climate projections 

can be utilized to guide the PMP procedures involving storm 

“maximization” and “translation.” 

3.2.3 Incorporating Paleoflood Information Into 

Flood-Risk Evaluations

The prospects of climate change might compel us to consider a range of potential flood events beyond those implied 

by the instrumental record. Paleofloods offer another way of 

characterizing such events. Paleoflood hydrology is the study 

of floods prior to the instrumental record or in ungaged basins 

(Costa, 1987; Baker, 2008). More information on paleoflood 

hydrology can be found in appendix A. The study of landforms, sediments, and botanical evidence can be used to infer 

information about previous flooding. Flood reconstructions 

can be used to improve flood-frequency estimates, as well as 

to provide information on the magnitude and age of the largest 

flood(s) for a particular basin and for hydrologically homogeneous geographical regions (Jarrett and England, 2002).

Paleoflood reconstructions can be used in a variety of 

ways. One use involves informal comparison of current floods 

to paleofloods, putting current floods into the context of events 

that appear to have occurred in the past. Also, paleoflood data 

might be referenced in flood-frequency analyses (see Baker 

and others, 2002; Baker, 2008). As with previously described 

uses of paleoclimate information, the use of paleoflood information requires an assumption that paleoflood magnitudes are 

relevant to the future. 

3.3 Recent Reclamation and USACE Planning 

Applications Involving the Use of Expanded 

Climate Information Sets

In recent years, Reclamation, USACE, and other Federal 

and State agencies have explored the use of expanded climate 

information sets to support various water resources planning 

efforts. Three examples are listed below, where the planning 

focus involves evaluating proposed or anticipated plans for 

long-term operation (or water control):

Lake Ontario-St. Lawrence River Study, which used 

climate projection information and stochastic modeling 

to guide hydrologic variability assumptions in water 

control planning for the Lake Ontario-St. Lawrence 

River System (IJC, 2006).

Colorado River Basin Study, which used nonparametric 

stochastic modeling with paleoclimate information to 

•

•

guide water-supply variability assumptions in operations planning for the Colorado River Storage System 

(Bureau of Reclamation, 2007).

California Central Valley Study, which used climate 

projection and sea-level rise information to guide 

water-supply assumptions in a biological assessment 

on multiple fish species in the California Central Valley (Bureau of Reclamation, 2008).

Each study’s use of different climate information types is 

described further in appendix C. It is not possible to precisely 

say whether and how decision outcomes were affected by the 

use of expanded climate information sets. However, it can be 

said that the stakeholders in all of these studies made it clear 

that they wanted the analyses of these systems to relate system 

impact and study outcomes to projected climate information and (or) broader climate-variability assumptions. These 

pressures from stakeholders resulted in the agencies making 

changes in their traditional methods of analysis. To that end, 

each study process was completed, technical and communication challenges were overcome, and each planning process 

ultimately benefited by addressing stakeholder expectations to 

incorporate a broader array of possible climate assumptions. 

3.4 Summary and Discussion 

The focus of this chapter was on how climate information has traditionally been used in two classes of long-range 

water-management decisions (general system evaluations and 

flood-risk evaluations). Motivations were discussed for using 

an expanded set of climate information to support both decision processes. Expanded climate information might involve 

the use of paleoclimatic evidence on hydroclimatic conditions, 

stochastic modeling to augment sequence possibilities, and 

(or) the incorporation of climate-projection information. 

Paleoclimatic evidence of supply variations and flood 

events may portray hydrologic possibilities that have not 

occurred in the instrumental record. This provides motivation to 

consider a range of hydrologic possibilities beyond those from 

the instrumental record. Evidence that we exist in a changing 

climate provides further motivation. Paleoclimatic evidence 

about hydrologic conditions offers an accessible source of 

information for planning. In addition, stochastic modeling techniques offer the opportunity to expand planning assumptions of 

hydrologic sequences with implications for supply variability 

(for example, drought possibilities). The use of such techniques 

requires the implicit belief that the reference period underlying 

the stochastic model is relevant to the planning future.

To date, more attention has been focused on the methods 

relating climate-projection information to water-supply and 

demand assumptions. Until uncertainty narrows considerably, 

or until enough time elapses to see which methods best characterize future conditions, there will continue to be an array of reasonable approaches. At this time, it seems safe to say that there 

•

3 Anticipating Climate Change: Available Climate Information for Decisionmaking in Long-Range Planning 21
is no single “best” procedure for considering projected climate 

information in either class of long-range decisionmaking. 

Questions to management agencies about adapting, 

physically or operationally, to climate change are likely to 

continue. In addressing questions on climate change adaptation through time, the establishment of planning assumptions 

becomes complicated within a context of climate nonstationarity. To review, using traditional planning approaches, planning 

assumptions are developed relative to a stationary reference 

climate (that is, the Stationary System paradigm) that typically 

reflects climate from the instrumental record. Now consider 

establishing planning assumptions to reflect future climate 

change while maintaining the Stationary System paradigm. 

The task involves adjusting planning assumptions based on the 

instrumental record to reflect the effects of incremental climate 

change [for example, approaches featured in International Joint 

Commission (IJC) (2006) and Bureau of Reclamation (2008)]. 

Detection and appropriate application of incremental climate 

change using climate projections (or instrumental records) may 

be challenging. For example, it may be clear that some regional 

hydroclimatic conditions are nonstationary and are evolving 

in a steady fashion (for example, air temperature), thereby 

making climate change detection and the selection of a stationary regime generally straightforward. For other variables, 

such detection may be much more difficult because of natural 

variability within the model projections (or in instrumental 

records). For example, detecting changes in precipitation climatology is difficult given the large amount of variability that 

exists at both interannual and multidecadal time scales. 

To avoid such detection uncertainties, it may be clearer 

and more appropriate (albeit at the cost of complexity) to 

frame long-range system evaluations relative to projected 

planning assumptions consistent with climate projections (that 

is, the System Projection paradigm). In doing so, planning 

assumptions for water supplies, demands, and constraints 

would be projected through time, consistent with the transient characteristics of climate projections. The development 

of such system projections would require the view that the 

transient aspects in climate projections are credible enough 

for planning purposes. It would also require the view that 

hydrologic sequences consistent with climate projections are 

suitable substitutes for those that might be taken from the 

instrumental record. If such views are held, then use of this 

paradigm could allow the questions of adaptation to management agencies to be more easily addressed. 

For long-range planning practices to advance in incorporating climate projection information, it is clear that further 

research is necessary to improve our understanding in many 

areas (chap. 6). Two areas are highlighted here: (1) establishing valid climate planning assumptions and assessing impacts 

in response to global climate change, and (2) determining the 

potential for precipitation extremes to change and adapting 

planning for extreme precipitation. The first area is crucial for 

improving our ability to characterize water-supply assumptions under climate change. The latter is crucial for evaluating 

flood risk in relation to structural safety and operational flood 

protection.

Key Point 8. A System Projection paradigm for adaptation 

planning, as opposed to a Stationary System paradigm, may 

offer a more appropriate context for characterizing planning 

assumptions, albeit at the potential cost of adding planning 

complexity.

22 Climate Change and Water Resources Management: A Federal Perspective
4 Anticipating Climate Change: 

Approaches for Decisionmaking

This chapter reviews whether the existing planning 

frameworks used by water-management agencies are flexible enough to incorporate the uncertainties related to climate 

change. The chapter reviews how climate plays a role in 

system planning and operations, and introduces issues with 

incorporating climate information into planning approaches. 

The uncertainty of projections of future climate and of 

approaches to assigning probabilities to future conditions are 

discussed. Robust decisionmaking and adaptive management 

are presented as options to make decisions more flexible given 

uncertainty.

4.1 Decisions and Scales

Contemporary water-management decisions are made 

at a variety of space and time scales and are informed by 

assumptions about supplies, demands, weather, climate, and 

operational constraints at those scales. Generally, decisions 

apply spatially from stream corridors to multistate regions and 

temporally from days to decades. There are several analytical 

approaches that might be considered for incorporating climate 

change information into a planning process, ranging from no 

discussion to qualitative or quantitative analyses. Whether the 

information is used in any analysis may depend on the availability of regional climate projections, their suitability (that is, 

whether projected variables and scales match those required 

in the planning analysis to drive management decisions), and 

whether such projections suggest significant changes in future 

climate relative to past climate. 

Because climate changes are traditionally detected over 

a period that spans multiple decades (Intergovernmental 

Panel on Climate Change, 2007a), decisions with application 

horizons of greater than roughly 20 years might reasonably be 

informed by climate change information. A variety of decisions and planning analyses may involve looking ahead more 

than 20 years, including: 

General planning studies exploring feasibility, economic benefits and costs, and estimation of risks (such 

as flood damage or water-supply shortages) to help 

decisionmakers decide among alternative proposed 

actions, including proposed infrastructure and (or) 

establishment of long-term operations criteria.

Proposal documentation on expected benefits and 

impacts of alternative proposed actions (for example, 

the National Environmental Policy Act). 

Consultation with fish and wildlife agencies on how 

proposals may affect environmental conditions and 

species listed as threatened or endangered (for example, section 7 consultations under the Endangered 

Species Act). 

•

•

•

Many decisions involve application horizons that range 

from days to years, such as daily release scheduling, monthly 

operations scheduling to determine annual water allocations, 

and hydropower marketing strategies. These decisions occur 

at time scales that are shorter than those required for detecting 

climate change (Intergovernmental Panel on Climate Change, 

2007a). However, climate still plays a role in these decisions. 

Instead of being informed by future climate projections, they 

are informed by climate information from the past. This past 

information is used to calibrate water-supply forecast models 

and to provide a basis for assumed demands and operating 

constraints during upcoming months and seasons. If historical 

climate change has been observed, this can be incorporated 

into the decision to the extent that it affects supply, demand, 

or constraint assumptions (for example, updating water-supply 

forecast models to reflect more recent weather-runoff relations 

rather than those from the earlier period of record). 

In many planning studies, it is necessary to conduct a 

multiobjective analysis that compares the economic costs with 

the benefits of alternative plans. The Economic and Environmental Principles and Guidelines (P&G) for Water and Related 

Land Resources Implementation Studies (U.S. Water Resources 

Council, 1983) are guidelines for water-management agencies 

to use for planning. The planning process is supposed to explicitly consider future conditions during the planning horizon. 

While there is no discussion of stationarity in P&G, Frederick 

and others (1997) state that this step could include a forecast of 

climate-change impacts. Under the P&G, planners identify areas 

of risk and uncertainty and describe them clearly “so that decisions can be made with knowledge of the degree of reliability of 

the estimated benefits and costs” (U.S. Water Resources Council, 1983). P&G recommends the use of sensitivity analysis, 

which is described as varying assumptions and examining the 

effects on outcomes of benefits and costs. Frederick and others 

(1997) state that the P&G is flexible enough to accommodate 

planning for climate change. They note that sensitivity analysis 

and scenario planning are tools for understanding uncertainty 

that can be employed with the P&G. 

4.2 Describing Future Climate for Planning

When defining potential future climate change, planners 

would primarily be informed by projections generated using 

atmosphere-ocean GCMs for the reasons discussed in section 

3.1.3. These models simulate the climate-system response to 

an assumed scenario of future greenhouse gas emissions, or 

“climate forcings,” from an estimated “initial system condition.” The models are complex deterministic models of nonlinear systems. Although their purpose is to project future climate 

conditions, there are many sources of uncertainties in the models, including forcing uncertainty, initial condition uncertainty, 

and climate modeling uncertainties (Stainforth and others, 

2007). Forcing uncertainty deals with future greenhouse gas 

emissions (that is, human behavior) and other natural factors (for example, the occurrence and magnitude of future 

4 Anticipating Climate Change: Approaches for Decisionmaking 23
volcanic events) (Rayner, 2000). Initial condition uncertainty 

is associated with an incomplete description of earth system 

conditions at the beginning of climate simulations. Climate 

modeling uncertainties are the knowledge limitations about the 

climate-system physics (for example, clouds formation, ocean 

processes, ice-sheet melt processes, and many others) and the 

limited ability to approximate the physics at space and time 

scales that are computationally feasible. Despite these uncertainties, each generation of climate models has gotten better at 

simulating past climate (Reichler and Kim, 2008), and we can 

expect that, with continued investment in the science, they will 

continue to improve in the coming years and decades.

Scenario analysis is one method to deal with complex, 

uncertain systems. Traditional scenario analysis uses a small 

number of scenarios (Schwartz, 1991). These scenarios could be 

defined relative to climate projections, demographic outlooks, 

and other planning drivers. Such scenarios might be cast as “top 

down” (Colorado Water Conservation Board, 2008) (fig. 9). 

These contrast with “bottom up” scenarios (Colorado Water 

Conservation Board, 2008) defined within a sensitivity analysis 

where thresholds of operations flexibility are revealed by incrementally adjusting planning drivers. These approaches are not 

necessarily exclusive (Miller and Yates, 2006).

One example of the traditional scenario approach is the 

Millennium Ecosystem Assessment framework to account for 

the future of ecosystem services (World Resources Institute, 

2003). Because of the complexity of ecosystems, the assessment used four internally consistent scenarios to describe the 

range of plausible futures for Earth’s ecosystems. Likewise, 

the IPCC has been using the scenario paradigm (Intergovernmental Panel on Climate Change, 2000) to describe future 

greenhouse gas emission possibilities associated with future 

human activity (that is, population growth, economic development, technological change, and ultimately energy use). 

One question associated with the scenario approach is: 

What is an appropriate number of scenarios to use? In traditional scenario analysis (Schwartz, 1991), there are often only 

two or three major future drivers that are uncertain and two 

or three possible states for each of the two or three drivers. 

A small number of scenarios may be insufficient to model a 

range of values for important input parameters. An alternative 

approach is to use a large number of scenarios to describe a 

wide range of possible futures (Groves and Lempert, 2007). 

The set of scenarios should contain as diverse a set of plausible futures as possible and represent a wide range of different types of information about the future (Lempert and others, 

2003). The aim is to test alternative policies against a variety 

of possible conditions. 

Groves and others (2008) conducted workshops with the 

California Inland Empire Utilities Agency to describe climate 

change uncertainty for water management. They used three 

methods: a traditional scenario analysis with a small number 

of scenarios, a scenario-rich approach where relative probabilities were not assigned, and another scenario-rich approach 

where such probabilities were assigned. The stakeholders 

who reviewed the three approaches found that the traditional 

scenario approach was the easiest to understand and explain to 

decisionmakers, but they felt that it provided much less information than the other approaches (Groves and others, 2008). 

Scenarios have been used in many studies to evaluate 

potential climate change impacts (Parson and others, 2007). 

These studies have employed different numbers of scenarios 

and different ways to handle scenario probabilities. One 

example is the New York City Department of Environmental 

Protection assessment of climate change impacts on New York 

City’s water supply and coastal vulnerability (Rosenzweig and 

others, 2007). The study task force selected five GCMs and 

three emission scenarios and developed model-based probability distributions for temperature increases and changes in precipitation. Another example is an examination of the impact of 

sea-level rise on coastal flooding in the metropolitan Boston 

area (Kirshen and others, 2008). The study used two scenarios 

Key Point 9: Adopting alternatives that perform well 

over a wide range of future scenarios could improve system 

flexibility. Water resources planning and management requires 

an appreciation of existing and potential future uses of water 

resources [Mr. Steven L. Stockton, PE, Director of Civil Works, 

USACE, in testimony before the Subcommittee on Water Resources and 

Environment, 24 June 2008 (http://www.usace.army.mil/cw/cecw-cp/

news/stockton_testimony.pdf)], particularly when public health and 

safety are involved.

Impact and 

Adaptation

Options

1. Climate and socioeconomic 

scenarios

2. Global circularion model 

output

3. Regional downscaling

4. Projected responses

5. Identify vulnerabilities

6. Develop adaptation options

7. Alternatives assessment

6. Assess alternatives

5. Projected responses

4. Regional downscaling

3. Develop adaptation 

options

2. Identify drivers

1. Identify vulnerabilities

Figure . Bottom-up and 

top-down scenario definitions 

in climate change assessments 

(after Colorado Water 

Conservation Board, 2008).

24 Climate Change and Water Resources Management: A Federal Perspective
of sea-level rise and four possible adaptation scenarios. A 

simulation was then done to calculate future damages for each 

scenario. A third example is the Lake Ontario-St. Lawrence 

River study, described in section 3.3 and appendix C (International Joint Commission, 2006). Four climate projections 

were chosen that bracketed the “spread” of temperature and 

precipitation changes: dry-warm, wet-warm, dry-hot, and wethot. The scenarios were used to evaluate how robust the plans 

were to climate change conditions without considering their 

likelihood of occurring.

4.3 Incorporating Uncertainties in Planning

There are two viewpoints on whether it is necessary to 

estimate probabilities for future scenarios, such as those describing future climate conditions. In one sense, it is reasonable to 

expect decisionmakers to want to know the relative likelihoods 

of posed scenarios before making planning decisions. However, such probability assignments can be misleading, and it is 

difficult to define the boundaries of the scenario and the range 

of future uncertainty (Groves and Lempert, 2007). Lempert 

and others (2003) state that probabilities should be used with 

scenarios only if they contain solid information. Estimating 

probabilities of future conditions is discussed in this section.

Water resources agencies have generally employed statistical models to estimate the likelihood of future hydrologic 

events. Hydrologists recognize that there are multiple sources 

of uncertainty in these estimates, such as measurement error 

due to imperfections in how flow was measured and sample 

error from using a finite dataset for the statistical model. However, there are other sources of uncertainty that are much more 

difficult to quantify, such as model uncertainty. The underlying assumption behind using a statistical model may be wrong, 

with one such assumption being that the past data are stationary and representative of the future. 

In the absence of empirical data and statistical models, 

another approach is to estimate probabilities based on subjective judgment. The IPCC uses a subjective characterization of 

probability to assess the likelihood of future climate change. 

In guidance written for the IPCC, Moss and Schneider (2000) 

make the case for subjective judgment:

“It is certainly true that ‘science’ itself strives for objective empirical information to test theory and models. But at the same time 

‘science for policy’ must be recognized as a different enterprise than 

‘science’ itself, since science for policy involves being responsive to 

policymakers’ needs for expert judgment at a particular time, given 

the information currently available, even if those judgments involve 

a considerable degree of subjectivity” (Moss and Schneider, 2000).

Various methods are available to elicit probability distributions from experts (Morgan and Henrion, 1992). Research by 

Tversky and Kahnemann (1974) has shown that experts use the 

same heuristics and have the same cognitive biases as laymen. 

Experts, like others, tend to be overconfident in their predictions 

and their ability to assess the likelihood of events. The Guidance 

Notes for Lead Authors of the IPCC Fourth Assessment Report 

on Addressing Uncertainties (Intergovernmental Panel on 

Climate Change, 2005) warns against the tendency of a group to 

converge to an expressed value and to become overconfident. 

The P&G allows the use of subjective probability distributions to characterize uncertainty in the absence of empirical data that can be used to represent future random events. 

However, when subjective probabilities are used, the P&G 

recommends that the study report should state clearly that 

the numerical estimates are subjective and there should be a 

description of the impact of other subjective distributions on 

design (U.S. Water Resources Council, 1983). 

Several studies have recently attempted to derive future 

climate probability distributions from climate projection information (Murphy and others, 2004; Tebaldi and others, 2004; 

Dettinger, 2005b), sometimes involving the preconditioning or 

weighting of climate projection information based on the relative skill among the climate models used to generate projections 

(Tebaldi and others, 2005; Brekke and others, 2008). However, 

there are several difficulties with these approaches. Tebaldi and 

Knuuti (2007) point out that climate models are not independent, since models have similar resolution and must parameterize the same processes. Stainforth and others (2007) state that 

the effort to weight models is futile: “relative to the real world, 

all models have effectively zero weight.” They argue “there is 

no reason to expect these distributions to relate to the probability of real-world behavior” (Stainforth and others, 2007). 

4.4 Other Methods for Choosing Alternatives

4.4.1 Robust Decision Criteria

Water-management agency planning is often based on 

maximizing the expected net economic benefits to the Nation. 

The expected net economic benefits are calculated based on a 

probability distribution for future conditions. Because of the 

uncertainty of future climate, several authors have proposed 

alternative decision criteria. Rather than trying to choose the 

right design for a likely future, “robustness” is an alternative criterion for planning (Matalas, 1997). A robust decision criterion 

tries to choose plans that perform well over a wide range of possible future scenarios. Fiering and Kindler (1987) maintain that 

“optimality alone is not a sufficient characteristic of acceptable 

system design.” Water resources managers can be expected to be 

“surprised” in the future because of the increasing complexity of 

water resources management. Surprises are counterexpected or 

unexpected events, and water resources planners should minimize the likelihood of surprise (Fiering and Kindler, 1987). 

A related concept is the decision criterion of minimizing the maximum regret. Regret is the difference between the 

performance of some future alternative and the alternative that 

would have performed best for that particular future. The criterion can be used when the probabilities of future conditions 

are unknown or very uncertain. A robust strategy then can be 

defined as having little regret over a wide range of plausible 

futures (Lempert and others, 2003).

Lempert and others (2003) proposed an approach that 

features robust decision criteria that they call Robust Decision 

4 Anticipating Climate Change: Approaches for Decisionmaking 25
Making (RDM); it has four elements (Lempert and others, 

2003; Dewar and Wachs, 2006):

Consider a large number of scenarios that contain a 

range of plausible futures that are as diverse as possible.

Seek robust, rather than optimal, strategies that do well 

across a broad range of plausible futures.

Employ adaptive strategies to achieve robustness; 

adaptive strategies evolve over time in response to new 

information.

Use computer tools for interactive exploration of the 

multiplicity of plausible futures.

Dewar and Wachs (2006) argue that robustness methods 

are superior to sensitivity analysis. Robustness methods consider a wider range of possible situations, while a few sensitivity studies may not include some important system responses 

for situations not included in the few cases considered. The 

primary difference of the approach of Lempert and others 

(2003) is the use of a large number of plausible future scenarios that can be generated by computer models. The scenarios 

that seem most closely associated with system vulnerabilities 

are first identified. An optimal policy does best for a fixed set 

of assumptions about the future. The robust policy performs 

well across a wide range of plausible futures. Robust decision 

criteria are compatible with other decision criteria and could 

be an additional piece in a multicriteria decision problem. 

4.4.2 Adaptive Management

Many planning situations require an emphasis on adaptability and flexibility. Anticipatory management builds in the 

flexibility to anticipate future conditions. “Faced with a multiplicity of plausible futures, a decisionmaker may settle on 

near-term actions but plan to adjust them in specific ways as 

new information renders some futures implausible and others 

more likely” (Lempert and others, 2003). The Second Assessment Report of the IPCC proposed using a sequential decision 

process for dealing with climate change (Intergovernmental 

Panel on Climate Change, 1996). Future decisions should “be 

able to respond to new information with mid course corrections” that allows time to learn and change course.

Adaptive management is one decision process that “promotes flexible decisionmaking that can be adjusted in the face 

of uncertainties as outcomes from management actions and 

other events become better understood” (National Research 

Council, 2004). Adaptive management offers a framework 

where robust decision criteria may be considered. Adaptive 

management is an iterative process of six steps: (1) assess the 

problem, (2) design, (3) implement, (4) monitor, (5) evaluate, 

and (6) adjust (Williams and others, 2007). 

Water-management agencies have primarily associated adaptive management with environmental management 

and ecosystem restoration. Adaptive management has been 

•

•

•

•

used for evaluating alternative reservoir releases in order 

to improve downstream aquatic habitat (National Research 

Council, 2004). Adaptive management can actually be used 

for any dynamic system where there is uncertainty about the 

future. DeNeufville (2000) describes a similar process called 

dynamic strategic planning for planning various types of technological projects. 

Adaptive management is more suited to guiding operational or institutional changes rather than construction of new 

water facilities. Structural solutions may be hard to reverse 

unless they are designed to anticipate alternative future 

conditions with planned upgrades. Adaptive management can 

be either “active” or “passive” (National Research Council, 

2004). Active approaches include management actions that test 

hypotheses about how the system will respond to a particular 

course of action. Passive approaches focus on monitoring and 

evaluating conditions. The adaptive management approach 

toward climate uncertainty would follow a course of monitoring conditions and adjusting policies as changes are observed 

or scientific uncertainty is reduced. The monitoring need of 

adaptive management may require a change in authorities for 

Federal water-management agencies. ,

4.5 Summary

Several studies have concluded that current water-management planning regulations such as the P&G are flexible 

Since the Water Resources Development Act (WRDA) of 1986, the 

USACE must turn over post-construction, project-related responsibilities to a 

non-Federal sponsor for civil works projects with the exception of navigation. These responsibilities include operations, maintenance, repair, and 

rehabilitation. If later modifications are needed for projects, a cost-shared 

feasibility study and authorization of project modification by Congress may 

be required. Exceptions to this rule include Section 1135 authority from the 

1986 WRDA, Section 216 authority from the 1970 Flood Control Act, and 

the Comprehensive Everglades Restoration Project authorized by the 2000 

WRDA. Section 216 of the River and Harbor Act and Flood Control Act of 

1970 gives the USACE authority to reevaluate projects that the USACE has 

constructed. These authorities allow modifications in response to significantly 

changed conditions without seeking additional congressional authorization 

(NRC, 2004). The USACE has limited funding for inspections of completed 

Flood Damage Reduction projects. The current USACE policy restricts costshared monitoring of ecosystem restoration projects to 5 years and 1% of the 

total project costs for most projects. This is being reconsidered in response 

to Section 2039, Monitoring Ecosystem Restoration, WRDA 2007 (PL 110-

114). The current policy on cost-shared monitoring of ecosystem restoration 

projects is limited to 3% of the total project costs, excluding monitoring costs; 

however, variations can be requested.

The Department of the Interior has developed guidance to its bureaus 

regarding adaptive management located in their Department Manual at 552 

DM 1 entitled “Adaptive Management Implementation Guidance,” dated 

January 1, 2008.

Key Point 10: Adaptive management is an approach that 

makes decisions sequentially over time and allows adjustments 

to be made as more information is known. This approach may be 

useful in dealing with the additional uncertainty introduced by 

potential climate change.

26 Climate Change and Water Resources Management: A Federal Perspective
enough to accommodate planning for climate change. However, current planning approaches have generally assumed that 

past climate conditions will be similar to the recent past, an 

assumption that may be suspect given that climate is changing. 

In the absence of the stationarity assumption, other methods 

can be used to estimate the likelihood of future hydrologic 

conditions, including subjective probability methods and 

approaches that use climate models to derive a range of possible future conditions. However, probability estimates using 

these approaches could give misleading results that do not 

consider the full range of uncertainty. 

Other decisionmaking approaches can be used for dealing 

with uncertainty. A robust decision criterion tries to choose 

plans that perform well over a wide range of possible future 

scenarios. A sequential decision process plans for alternative 

courses of action, given different possible future conditions, 

and can be changed as new information is gained. Decisionmaking that aims for flexibility could be enhanced by using 

a framework that employs a wide range of plausible future 

conditions, seeks robust solutions that do well across a broad 

range of plausible futures, and employs adaptive strategies that 

evolve over time in response to new information. Maximizing flexibility across these scenarios, however, may come at a 

prohibitive cost. Evaluating this trade-off between flexibility 

and cost is part of the planning process. 

These approaches are not mutually incompatible and 

can be used in conjunction with current water-management planning methods that primarily employ cost-benefit 

analysis and sensitivity analysis. All of these approaches 

present options and then try to assess their performance 

under a range of conditions. Approaches such as the method 

proposed by Lempert and others (2003) may do a better 

job of representing multiple plausible futures, but these 

approaches are more computationally intensive and are often 

difficult to explain to stakeholders. There is nothing about 

these approaches that guarantees they will discover and 

incorporate a greater range of options or futures than other 

approaches. The value of every approach lies in its application to a specific problem. Each approach can be helpful, but 

each approach can also lead us to think that we know more 

about the future than we do.

4 Anticipating Climate Change: Approaches for Decisionmaking 27

5 Responding to Climate Change: 

Adaptation Options

There are several water-management options that might 

be considered to facilitate adaptation to climate change, 

including operational changes, demand management, and 

infrastructure changes. Climate change may translate into 

changed design and operational assumptions for determining resource supplies, system demands, system performance 

requirements, and operational constraints. The strategy options 

available for consideration will vary from system to system, 

as will the preference among these options. The following section outlines some potential strategies that might be considered 

and also discusses some of the challenges in evaluating and 

implementing the adaptation options.

Adaptation options designed to ensure water supply 

during average and drought conditions require integrating 

demand-side and supply-side strategies and depend on the 

existence of an operational framework for adaptive management and planning to cope with uncertainty. Evaluation of 

such strategies would likely require a partnership between 

Federal, State, and local interests. This chapter does not go 

into the specific planning authorities; instead available options 

are presented for adapting to climate change as it occurs across 

various temporal and spatial scales. These options would 

include the incorporation of lessons from responses to climate 

variability into longer term vulnerability-reduction efforts and 

within governance mechanisms from communities and watersheds to international agreements. 

Integrated watershed management provides an important 

governing framework for anticipating and achieving successful adaptation measures across socioeconomic, environmental, and administrative systems. To be effective, integrated 

approaches must occur at the appropriate scale or scales 

needed to facilitate effective actions for specific outcomes, 

and they must be based on strong linkages among monitoring, 

research, and management as climate varies and changes. A 

more comprehensive mode of operation that includes watershed management (given interbasin transfers and so forth) 

is integrated water resources management. Integrated watermanagement strategies include capturing social and individual 

risk perception, reshaping planning processes, coordinating 

land and water resources management, recognizing waterquantity and water-quality linkages, increasing conjunctive use 

of surface water and ground water, improving techniques to 

manage demand and conserve water, protecting and restoring 

natural systems, and learning through adaptive management 

experiments, including consideration of climate change. In 

addition, integrated strategies explicitly address impediments 

to the flow of information across the nodes of action (agencies, States, tribes, communities, and the private sector) and 

focus on decision quality as well as acceptability (Pulwarty, 

2003). Institutional efforts to reduce conflict can also help 

to achieve desired goals. A fully integrated approach is not 

always needed, but rather the appropriate scale for integration 

will depend on the extent to which it facilitates effective action 

in response to specific needs (Moench and others, 2003). 

In particular, an integrated approach to water management that is robust—that can produce socially acceptable 

options and inform decisionmaking as resource characteristics (quality, quantity, and reliability) change—could help to 

resolve conflicts among competing water users. In several 

places in the western United States, water managers and various interest groups have been experimenting with methods to 

promote consensus-based decisionmaking as new information 

arises. These efforts include local watershed initiatives and 

State-led or Federal-sponsored efforts to incorporate stakeholder involvement in planning processes (U.S. Department of 

the Interior, 2005). Such initiatives can facilitate negotiations 

between competing interest groups to achieve mutually satisfactory problem-solving that considers a wide range of factors.

Key Point 11: Adaptation options include operational, 

demand management, and infrastructure changes. 

5.1 Adaptation Options Involving Operational 

Changes

One adaptation to climate change is to make better use of 

existing water resources by building more flexibility into operating plans. Existing operating plans are based on the historical 

climate. For example, flood-control rules are based on evaluations of historical flood risk, which have a climate context as 

described in section 3.2. There may be benefits from revising 

reservoir storage rules and authorized purposes as climate 

changes. Changes in climate or other aspects of basin hydrology, as well as changes in social values, may result in new uses 

for reservoir storage that have a greater economic or social 

value than the current uses. Flood storage space could be evaluated based on updated hydrologic records and future projections. Some projects may be operated more efficiently as part of 

an integrated system rather than as independent projects. 

Updates may be rapid or time consuming and expensive, 

depending on the river system and the nature and extent of 

the proposed changes. Locations for which observed climate 

change to date have resulted in a call for operational changes 

(for example, snowpack-dominated watersheds) may benefit 

from a systematic revision of reservoir operating plans and 

drought contingency plans. Other locations for which climate 

change is not a major driver may not require an extensive 

review or revision. When contemplating the value of incorporating climate projections into reservoir and river operations, 

managers must weigh potential benefits, given uncertainties in 

climate information, against the known and immediate costs of 

revision to operations. 

On the short term, water managers could increase the 

adaptive capacity to climate change through increased operational flexibility. One way could be through the use of intraseasonal to interannual climate forecasts. Much of the seasonal 

5 Responding to Climate Change: Adaptation Options 29
forecast skill is due to predictions of El Niño or La Niña and 

correlated impacts in North America (Climate Change Science 

Program, 2008d). Reservoir operators could reduce flood storage during years that are forecast to be dry. In some areas of 

the country, such as California, there is also some limited skill 

at forecasting major rain events up to 2 weeks in advance. A 

forecast of such an event could allow for evacuation of reservoirs in anticipation of a flood. Further research needs to be 

conducted on both developing better forecasts and incorporating the forecasts into reservoir operations. 

Reservoir operations that employ an adaptive management process can have the flexibility to adapt to observed climate conditions on an annual basis. An annual operating plan 

(AOP) is developed based on current hydrologic conditions, 

the forecast, and likely runoff scenarios (U.S. Army Corps of 

Engineers, 2004). The draft AOP forecasts the regulation of 

the system for various runoff scenarios and includes public 

involvement in developing the plan.

Adaptations to climate change include making better use 

of existing water resources through integrated surface-water 

and ground-water management. Conjunctive use refers to the 

coordinated use of ground water and surface water to optimize 

the use of both sources (Galloway and others, 2003). The 

2005 update of the California Water Plan estimates that annual 

water deliveries could be increased by 0.5–2 million acre-feet 

statewide if conjunctive management were more fully utilized 

(California Department of Water Resources, 2005). 

5.2 Adaptation Options Involving WaterDemand Management

Reducing the demand for water has been advocated as 

a way to reduce the vulnerability of managed water systems 

to climate change (Bates and others, 2008). Water-demand 

management is a strategy to make better use of water, reducing 

waste and increasing economic efficiency. However, waterdemand management is largely a State and local responsibility; the Federal role is constrained by Congressional authorization. Demand-side management balances water demands with 

limited available supplies by having a more efficient allocation 

of existing supplies. Water that is saved reduces the need for 

costly infrastructure. 

One adaptation strategy is to enhance mechanisms for 

market-based transfers of water among uses. Climate change 

and shifting patterns of demand may increase market pressures that today are moving water from one use to another. 

Increased use of voluntary water leasing, water banks, and 

water markets can increase the opportunity for water rights 

holders to shift water among users. Transfers can either be 

permanent by purchasing water rights or temporary by having 

contracts to purchase water during dry years. Markets and 

higher prices provide an incentive to adopt water conservation, 

particularly during periods of limited supply and drought. 

Another strategy is to reduce overall water consumption 

through conservation and efficiency improvements. Municipal 

water utilities can encourage water conservation by individual 

metering and pricing. The agricultural sector can reduce water 

consumption by changing the selection of crops and irrigation 

methods and by adopting technological innovations such as 

drought-resistant plant varieties. 

Most measures to reduce demand are implemented at the 

local level or by individual producers and households. The 

water-management agencies can continue to promote wateruse efficiency in several sectors, as well in their own operations and water delivery systems. The Federal Government 

can encourage water markets and water transfers by removing 

regulatory restrictions or by providing incentives. More efficient intergovernmental collaboration and coordination among 

Federal, State, regional, and local agencies will facilitate the 

flow of data and information and improve water resources 

planning. The Federal Government also has a lead role in 

research that produces technological advances that can reduce 

water use per capita. 

As noted earlier, population growth in semiarid regions 

of the country has increased the demand for limited water supplies and has heightened vulnerability to drought. More population in flood plains and coastal areas has increased flood 

risk and has increased public demand for flood-risk-reduction 

measures. Land-use planning and zoning regulations can be 

used by State and local governments to limit development in 

vulnerable regions. The Federal Government can influence 

flood-plain requirements through the National Flood Insurance 

Program, but it generally has limited authority over land-use 

planning decisions.

5.3 Adaptation Options Involving Infrastructure 

Modifications

Management of existing, long-lived infrastructure 

includes up-to-date maintenance, rehabilitation, and upgrades 

to ensure flexibility to a wide range of potential climate 

variability. Much of the water resources infrastructure in the 

United States is aging and needs maintenance, rehabilitation, 

and repair (American Society of Civil Engineers, 2005). The 

infrastructure may not meet its design level of performance 

under the current climate and could be more vulnerable to 

failure under future climate scenarios. One important adaptation to a changing climate is to evaluate the potential risk to 

existing, long-lived infrastructure, such as dams and levees, 

caused by possible increases in the magnitude, frequency, 

and duration of large floods. Alternative strategies for meeting project goals may need to be evaluated and may result in 

modification to infrastructure. 

One strategy to reduce the risk of an individual water 

supply is to create more diverse portfolios of water supply. This approach could include new surface-water storage 

and (or) ground-water storage. Conjunctive management of 

surface and ground waters could help replenish ground-water 

supplies. Another source of freshwater supply is desalination. 

Desalination plants require both a large capital investment and 

30 Climate Change and Water Resources Management: A Federal Perspective
large amounts of energy, but costs per unit of freshwater have 

been declining (National Research Council, 2008). Desalination is an option for both seawater and brackish ground water. 

Other approaches to enhance water supplies include reusing 

high-quality water and treating sources of degraded water for 

use, and protecting the integrity of existing water supplies.

5.4 Challenges

There are several challenges in evaluating and implementing adaptation options. There is uncertainty about the 

hydrologic impacts of climate change. Resources are limited and there are many competing requests for funding. For 

example, changes in reservoir operations and allocation can be 

time consuming and expensive. The process often requires an 

environmental impact statement (EIS), with public participation by stakeholders who have different objectives. 

There are also legislative and regulatory requirements 

that could limit adaptation options. For some Congressionally 

authorized projects, it may be necessary for Congress to pass 

legislation allowing changes in a project’s structure, authority, 

or purpose, including updates to operating plans. The Federal 

planning process requires that future benefits be discounted. 

Measures to adapt to climate change may provide benefits 

only in the distant future, so these future benefits may be considered negligble in the current Federal planning process. 

Agencies may also need to adopt a decisionmaking 

framework that encourages robust solutions that can be 

updated over time. The NRC (2004) made the following recommendations that are relevant to Federal water agencies for 

adopting an adaptive management framework: 

Post-construction evaluations should be a standard for 

the adaptive management of projects and systems.

Congress should provide a new study authority and 

direction that will increase the ability to monitor 

and evaluate post-construction changes and periodically adjust operations of existing projects in order to 

increase overall project benefits.

Congress should allocate funding and personnel 

resources to help support and sustain an adaptive management program within the water agencies.

•

•

•

The administration and Congress should consider 

revising cost-sharing formulas to promote the application of adaptive management principles.

Addressing these adaptation challenges is the focus of the 

next chapter.

5.5 Summary

Several water-management or system-development 

options might be considered to facilitate adaptive management in response to a changing climate, including operational 

changes, demand management, and infrastructure changes. 

Climate change may translate into changed design and operational assumptions for determining resource supplies, system 

demands, system performance requirements, and operational 

constraints. Adaptations to climate change would make better use of existing water resources through integrated water 

resources management. Integrated water-management strategies include capturing social and individual risk perception, 

reshaping planning processes, coordinating land and water 

resources management, recognizing water-quantity and waterquality linkages, increasing conjunctive use of surface water 

and ground water, improving techniques to manage demand 

and conserve water, protecting and restoring natural systems, 

and learning through adaptive management experiments, 

including consideration of climate change.

Operating plans could build in flexibility to adapt to 

potential climate conditions. Management of existing, longlived infrastructure includes up-to-date maintenance, rehabilitation, and upgrades to ensure flexibility to a wide range of 

potential climate variability. Strategies for adaptation involve 

both water-supply and water-demand management. Most 

measures to reduce water demand are implemented at the local 

level or by individual producers and households. Local and 

State governments make decisions on land use that affect their 

community’s susceptibility to drought and floods. Therefore, 

effective adaptation to climate change will require collaboration and coordination among Federal, State, regional, and local 

agencies. The strategy options available for consideration will 

vary from system to system, as will the preference among 

these options.

•

5 Responding to Climate Change: Adaptation Options 31

6 Opportunities To Improve Planning 

Capabilities 

This chapter addresses the following questions that 

agencies might consider as they strategize efforts to build 

adaptive capacity relative to the possibilities of future climate change: 

How might knowledge gaps be addressed in the near 

term through monitoring and research? 

What can be done to improve planning and address 

state-of-practice gaps? 

Where are there opportunities for interagency collaboration and how can these interagency activities be 

leveraged to address knowledge gaps? 

As discussed throughout this report, many uncertainties remain with respect to climate change and its potential 

impacts on water resources. This chapter identifies the major 

gaps that must be bridged to achieve success in addressing 

the effects of climate change. Additional research may narrow 

uncertainties, provide information in more useable forms, or 

develop more robust strategies for incorporating uncertainty 

into decisionmaking. However, additional research will not 

eliminate uncertainty entirely, and robust and flexible operations and planning approaches can be used to help manage 

water resources effectively despite this uncertainty. 

This chapter begins with a discussion of knowledge gaps 

and potential research priorities (section 6.1). The need for 

continued (and possibly expanded) monitoring is discussed in 

section 6.2. Section 6.3 recaps the need to develop methods 

to incorporate nonstationarity into planning and technical 

analyses. Section 6.4 describes other opportunities to advance 

planning, including possible changes to current methods for 

evaluating projects. Finally, section 6.5 presents some advantages to increased collaboration and some examples of such 

ongoing activities. 

6.1 Knowledge Gaps and Potential Research 

Priorities 

Knowledge gaps and needs for additional research are 

identified throughout this report. Research needs and priorities will vary for different places and for different water-management activities. For example, the research priorities and 

knowledge gaps recognized by coastal-resource managers 

in Florida will not likely match those recognized by surfacewater managers in Washington State. For example, highresolution digital elevation data such as Light Detection and 

Ranging (LiDAR) data exist for much of the coastline, but not 

for riverine floodplains. To this end, geographically focused 

discussions on research needs and priorities might be useful 

to help agencies steer and target efforts that would address 

regionally relevant knowledge gaps. 

•

•

•

An example process involving a regionally focused 

gap assessment and scoping for interagency research coordination is the Climate Change and Western Water Group 

(C–CAWWG). This collaboration was formed during 2007–

2008 by Reclamation’s Research and Development Office, 

NOAA’s Earth System Research Laboratory Physical Science Division (ESRL PSD) Climate Analysis Branch, and the 

USGS Central Region; the vision includes inviting involvement from other interested Federal and State agencies. On the 

matter of addressing regional knowledge gaps, C–CAWWG 

agencies convened a workshop in February 20–21, 200810 to 

discuss current capabilities for incorporating climate change 

into western U.S. water resources management and to discuss potential research strategies and efforts to improve these 

capabilities. The workshop was attended by management and 

technical staff from the three convening C–CAWWG agencies 

and from other invited Federal agencies (USACE, U.S. Forest 

Service, U.S. Fish and Wildlife Service, and so forth). 

The C–CAWWG workshop provides an example of 

a regionally focused discussion that generated insights on 

climate change planning issues, illuminated knowledge gaps, 

and revealed management input on which of these gaps might 

be prioritized. The gap topics and surveyed research priorities 

from the C–CAWWG workshop are listed in table 2. Such 

information is useful for senior management faced with decisions on how to allocate limited resources in order to improve 

their agency’s ability to plan for a changing climate.

Many of the gap topics listed in table 2 overlap with 

research questions raised in this report. For example, section 3.4 

highlighted our need to be able to assess how regional precipitation extremes might respond to global climate change, which is 

similar to the C–CAWWG gaps 3.3 and 4.3 (table 2). Chapter 4 

of this report discussed various issues associated with making 

decisions under uncertainty, which relates to gap 7.1. 

In summary, table 2 offers a mix of prioritized gaps 

focused on one region (western United States) and generally 

one resource sector (mostly surface-water management). However, many of the prioritized gaps address themes common to 

multiple-resource management issues, and they were broadly 

identified by a mix of interagency workshop attendees, suggesting that some of these gaps might be granted priority 

attention at the broader national level, including: 

Developing region- and sector-specific literature summaries on the state of regional climate change science, 

observed trends, and projected impacts to the sector 

resources (for example, coastal resources in the Gulf 

10See http://www.esrl.noaa.gov/psd/workshops/mwwcc/index.html.

•

6 Opportunities To Improve Planning Capabilities 33

Key Point 12: Research and monitoring are both needed to 

fill knowledge gaps and set up advances in planning capabilities. 

Although neither will eliminate all uncertainties, they will 

provide significant improvements in understanding the effects 

of climate change on water resources, including quantity and 

quality, and in evaluating associated uncertainties and risks 

required for more informed decisionmaking.
Table 2. Knowledge gaps discussed and prioritized at a geographically focused forum on Climate Change and Western Water 

Management1

.

Knowledge gaps discussed, C-CAWWG, February 200 Location in this report2

1. Access to Literature Syntheses

1.1 Clearinghouse on scientific literature relating climate change to water resources planning

1.2 Region-specific literature summaries

2. Access to Climate Projection Data

2.1 Downscaled data at finer spatial resolutions, for different variables Sec. 3.1.3; appendix B

2.2 Downscaled data that isn’t based on “stationarity” Sec. 3.1.3 and 3.4

3. Ability to Translate Climate Projection Data into Planning Scenarios

3.1 Basis for weighting climate projections Sec. 4.2 and 4.3

3.2 Ability to jointly consider paleoclimate, near-term climate variability, and projected climate information

3.3 Assess extreme meteorological possibilities under climate change Sec. 3.2 and 3.4

4. Ability to Assess Natural Systems Response to Climate Change

4.1 Assess impact on groundwater and its interaction with surface water Sec. 2.1 and 2.3

4.2 Assess impact on land cover and ecosystems Sec. 2.1 and 2.3

4.3 Assess extreme hydrologic possibilities relate to flood risk associated with structural safety, flood control rule 

requirements at reservoirs, and so on

Sec. 2.2, 3.2, 3.4

4.4 Understand implications of hydrologic model choice for runoff impacts assessments

5. Ability to Assess Social Systems Response to Climate Change

5.1 Anticipate social responses that constrain reservoir management (for example, surface water demands at the 

district level, flood protection values and expected service, environmental protection values and expected service)

5.2 Assess water use requirements for different crops under joint climate and atmospheric carbon dioxide changes

6. Practices for Assessing Operations and Dependent Resources Response

6.1 Conduct policy search studies (optimization, perfect foresight)

6.2 Ability to assess operations impacts based on realistic operator learning under climate change (for example, 

by striking a balance between the reactive operator depiction featured in traditional scenario analyses and the 

perfect foresight aspects of the “policy search” analyses)

6.3 Assess operations impacts on climate

7. Ability to Assess, Characterize and Communicate Uncertainties

7.1 Assess and characterize uncertaintes for each analytical stage (for example, climate projections, downscaling 

methods, natural and social system response analyses, operations analysis)

Sec. 4.3

7.2 Assess interrelation of uncertainties across analytical stages

7.3 Ability to effectively communicate uncertainties and their relation to Reclamation planning processes 1

Darker shading indicates greater priority, as assessed by a survey of the water managers at the forum.

2

If discussed in report.

Note: Workshop information is available at http://www.esrl.noaa.gov/psd/workshops/mwwcc/index.html.

Coast region and ground-water resources in the Great 

Plains).

Developing downscaled climate-projection information at finer spatial-temporal resolutions than what is 

already available (for example, submonthly and less 

than 1/8 degree resolution), for more variables (for 

example, diurnal temperature range, cloudiness, and 

solar radiation), and using methods that do not rely on 

“stationarity” between the relation of large-scale atmospheric circulation and local land-surface climate.

Improving our ability to assess the potential response 

of regional precipitation and hydrologic extremes to 

global climate change.

Improving our ability to assess and anticipate region-specific impacts of climate change on land cover and ecosystems and potentially land-cover feedbacks on climate.

Improving our understanding of how social systems 

mediate climate change impacts and establish expectations for water resource system performance and reliability, which would presumably need to be preserved 

under a changing climate.

Improving our ability to assess, characterize, and communicate uncertainties as they are introduced at each 

analytical stage during the process of relating climate 

change information to water resources management 

implications.

•

•

•

•

•

34 Climate Change and Water Resources Management: A Federal Perspective
6.2 Gaps in Existing Hydrologic and 

Meteorologic Data Networks 

Successful water-supply planning and water resources 

management require an accurate understanding of how much 

water is available under different hydrologic conditions, what 

the quality of that water is, and how both availability and 

quality are likely to change over time. Long-term earth science 

(hydrological, biological, geological, and so forth) monitoring networks are a fundamental tool for any water resources 

planning and management and are paramount in addressing 

climate change impacts. It is essential that data on components of the natural hydrologic system, such as precipitation, 

snowpack, streamflow, ground water, and water quality, be 

collected and developed through sustained long-term networks 

to understand long-term trends. It is also essential that rational 

standards for data collection be employed so that datasets 

maintain consistency and relevancy.

The USGS and other Department of the Interior agencies have suggested a framework for monitoring based on 

the Framework for Environmental Monitoring and Related 

Research strategy (Committee on Environmental and Natural 

Resources, 1997). This framework suggests a tiered approach 

to monitoring, starting with general inventories using remote 

sensing and progressing through several levels to intensive 

studies at select locations. Whether or not such an approach is 

employed, it will be important to determine if current networks are sufficient for monitoring relevant changes at the 

range of scales needed or if gaps need to be filled with new 

monitoring efforts.

Currently, most long-term continuous earth-science 

data-collection networks are largely maintained and operated 

by Federal agencies such as the USGS, the NOAA National 

Weather Service, Reclamation, and the USACE. In recent 

decades, maintenance of these networks has declined because 

of lack of funding. The USGS alone has deactivated or discontinued almost 1,700 surface-water streamgages in the U.S. 

Many other stream and river sites have never been monitored 

but could help increase our understanding of the myriad of 

issues facing the Nation’s water resources managers because 

of changes to the environment and to climate. To adequately 

address the effects of water-resources planning, design, and 

operation, a comprehensive network for earth-science datacollection is needed that is timely, accurate, consistent, and 

relevant.

6.3 Understanding and Incorporating 

Nonstationarity Concepts

Nonstationarity presents many challenges to the Nation’s 

water resource managers. The assumption of stationarity has 

been used throughout the development of infrastructure for 

managing water resources. 

Under the Stationary System paradigm, which has traditionally been employed in long-range planning (introduced 

in section 3.4), planning scenarios are based on stationary 

climate conditions. The System Projection paradigm (introduced in section 3.4), which allows conditions to evolve over 

time, is a potentially more useful and appropriate option for 

long-range planning for a changing climate. However, for 

water-planning entities that currently use a Stationary System paradigm to portray system possibilities, a transition to 

a System Projection paradigm may introduce technical and 

educational challenges. 

Many other types of analyses are also integrally linked 

to stationary concepts (for example, hydrologic statistics such 

as flood frequency, low-flow frequency, and flow duration, 

and design criteria). Widely accepted methods for incorporating nonstationarity do not yet exist. While research proceeds, 

efforts can be made to bring analyses up to date, so that they 

use the most recently available data. 

Hydrologic frequency analysis is used to estimate the 

frequency and severity of floods and droughts and is used here 

as an example of a traditional analysis in need of updating. 

Research aimed at properly incorporating the likely effects of 

climate change on floods and low flows is crucial to prudent 

water-management decisions. This research might also address 

questions about the risks of assuming stationarity in water 

resources planning and management. The hydrologic community continues to have substantial uncertainty about the 

magnitude of these future changes, and only limited research 

has been published that addresses incorporating nonstationarity into frequency analyses.

The consideration of climate change may make it more 

important that frequency analyses be updated to represent the 

most applicable data and methods. The USGS slowly continues to improve and update flood-frequency and regionalregression analyses that expand frequency estimates to 

ungaged areas (fig. 10). 

Figure 10 indicates there are 10 States whose floodfrequency regional-regression analysis is close to or greater 

than 15 years old. For example, although work is underway 

1974-1985

1991-1995

1996-2000

1986-1990

2001-2007

Years Equations Published

Regional-regression equations

may not be representative of

the entire State.

WA

ID

MT MN ND OR

WI NY

MI

SD WY

CA

IA PA

UT

NE OH IL IN CO WV VA MD KS MO KY

AZ

NC

NM

TN OK

TX

AR SC

MS AL GA

LA

FL

AK

* NV

HI-AS

VTNH

ME

MA

CT RI

NJ

DE

PR-VI

Figure 10. Age map indicating when the last regional-regression 

analysis for rural peak flows was published by the U.S. Geological 

Survey.

6 Opportunities To Improve Planning Capabilities 35
to update the analysis, the most recently published analysis 

of flood frequency for California is greater than 20 years old. 

Flood insurance rate maps use these estimates to delineate 

Special Flood Hazard Areas for the National Flood Insurance 

Program. It is important that flood-frequency estimates be up 

to date so the public and planners have as accurate an assessment of their flood risk as possible. Active analysis of existing 

flood records, and critical evaluation of climate research, will 

require increased investment by the hydrologic science and 

engineering community (Federal, State, and local government; 

academia; and the private sector). 

6.4 Opportunities To Improve Planning

Planning analysis involves economic as well as technical 

evaluation of potential projects. The discount rate used in the 

economic analysis of projects affects the valuation of benefits 

and costs that will be accrued in the future. As such, the choice 

of discount rate can affect decisionmaking. As discussed in 

chapter 4, the development of robust plans and adaptive management are means of coping with increased uncertainty about 

the future.

Federal guidelines have generally favored plans based 

on economic optimization for expected conditions rather than 

plans that are robust for a range of uncertain conditions. An 

adaptive management approach may require changes in how 

projects are funded, since funding would need to be provided 

for monitoring conditions and updating plans over time.

Changes in the discount rate and guidelines for making 

economic decisions would require broad agreement among 

the entities of the executive branch. The Office of Management and Budget (OMB), the Office of Science and Technology Policy (OSTP), the Office of Information and Regulatory 

Affairs (OIRA), the Council on Environmental Quality (CEQ), 

and the Council of Economics Advisors (CEA) are groups 

that may have an interest in these changes and would need to 

concur on new approaches. An adaptive management approach 

that requires funding for monitoring conditions and making 

changes over time may be viewed favorably by OMB if it 

means less investment in the initial years of a project. 

6.5 Opportunities for Further Collaboration

Gaps in climate change research abound. Collaborative 

interagency research that pools common resources is needed 

to further develop existing models that address climate change 

and spur new thought to create new methods and models. 

Increased climate monitoring is needed to track changes and 

to help develop and calibrate the models. Collaboration in 

these monitoring efforts can help to ensure that data-collection procedures are consistent and that quality assurance is 

uniformly applied. Collaborative efforts can also improve the 

communication of climate change science to water managers 

and the public if a more consistent message is framed. Several 

examples of collaborative efforts follow. 

The USACE has formed an interagency group on coastal 

climate change issues. This group consists of the USACE, 

USGS, NOAA, and the Federal Emergency Management 

Agency (FEMA). An initial task is to update the USACE guidance on sea-level change. 

A Federal Climate Change/Water Work Group was 

formed that is composed of the Department of the Interior 

(USGS and Reclamation), Department of Agriculture (Forest 

Service and Natural Resources Conservation Service), NOAA, 

U.S. Environmental Protection Agency (EPA), and USACE. A 

memorandum was signed by principals of these departments 

that authorizes senior staff from the agencies to cooperate in 

work to adapt water program management to reflect changing 

climatic conditions.

As already mentioned in section 6.1, Reclamation’s 

Research and Development Office, NOAA’s ESRL PSD 

Climate Analysis Branch, and the USGS Central Region have 

convened the Climate Change and Western Water Group 

(C–CAWWG). This workgroup recognizes that western U.S. 

water supply and use is at the nexus of many Federal, State, 

and local agencies. Understanding climate variability and 

climate change trends, determining their current and potential 

future influence on water supply and water use, and identifying potential adaptation strategies are common emerging 

priorities across these entities. Collaboration between these 

entities is essential to ensure efficiency and full utilization of 

interdisciplinary expertise and to avoid duplication. To that 

end, C–CAWWG serves as an interagency workgroup meant 

to ensure efficient research and development (R&D) collaborations and information sharing across the Federal agencies, 

and to promote improved understanding of climate change 

impacts on western water supplies and water use. The vision 

of C–CAWWG is to eventually benefit Federal, State, and 

local water managers and, through time, incorporate their 

feedback to guide future research planning. 

A Western States Federal Agency Support Team (WestFAST) has been created to facilitate collaboration with the 

Western States Water Council (WSWC). The initial participating Federal agencies in the WestFAST include USGS, EPA, 

U.S. Forest Service, Reclamation, NRCS, USFWS, Bureau 

of Land Management, NOAA, Reclamation, and USACE. In 

addition, a WSWC Federal Liaison Officer position has been 

created, with the salary and expenses being funded by several 

Federal agencies. 

Besides these examples, there are other intergovernmental entities that could serve as vehicles to address these 

collaboration needs. Examples include the Interstate Council 

on Water Policy (ICWP), the Advisory Committee on Water 

Information (ACWI), and the Intergovernmental Flood Risk 

Management Committee (IFRMC). 

There are also government programs that are designed 

to incorporate stakeholder input. For example, the NOAA 

Regional Integrated Sciences and Assessments (RISA) program supports research that addresses complex climate-sensitive issues of concern to decisionmakers and policy planners 

at a regional level. RISA teams comprise researchers from the 

36 Climate Change and Water Resources Management: A Federal Perspective
physical, natural, engineering, and social sciences who work 

with stakeholders in a region to determine how climate impacts 

key resources and how climate information can best be communicated to decisionmakers. These research-stakeholder efforts 

are critical in addressing a range of issues sensitive to climate 

and in need of socioeconomic impacts and public policy analysis. RISAs are focusing on issues of particular importance to the 

regions they cover, including agriculture and ranching, coastal 

impacts, drought, fisheries, forestry, human health, snowpack, 

transportation, water resource management, and wildfire. 

6.6 Summary

There are significant gaps in knowledge, monitoring, and 

practice that limit incorporation of climate change considerations into water resources planning and management. Climate 

change must be quantified with respect to the myriad of other 

natural and cultural issues that face the Nation’s water managers. Sound water management is built on sound, accurate, 

timely, and long-term hydrological and meteorological monitoring networks that are consistent and that can be used readily 

to assess and provide decisionmaking tools needed to quantify uncertainty, forecast change, and create the multiphase, 

multilevel climate scenarios that will provide reasonable and 

relevant management. Changes to planning and analysis that 

better accommodate nonstationarity will improve water management. Collaboration in all these activities may allow more 

rapid results and improved communication both within the 

water resources community and to other stakeholders.

6 Opportunities To Improve Planning Capabilities 37

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Appendix A. Paleoclimate Reconstruction of Past Droughts and Floods

To establish exact dates, a living tree is cored, and the 

known years are matched with tree-ring records obtained from 

nonliving trees (Stahle and Cleaveland, 1992). Overlapping 

chronologies from different sets of trees can sometimes be 

used to extend the record back in time. In this way, tree rings 

can provide hundreds, and in some cases more than a thousand, years of tree-ring chronologies. 

A statistical model describing the correlation between 

the instrumental record climate or streamflow record and the 

tree-ring chronologies can be developed using overlapping 

periods. For example, a regression model can be developed to 

estimate annual streamflow from tree-ring widths. This model 

is then applied to the preinstrumental record to estimate annual 

streamflow over the length of the tree-ring records. Ideally, 

tree-ring chronologies should be developed for sites in all of 

the major runoff-producing areas of a river basin, because this 

is likely to maximize the fit of the regression model (Meko 

and others, 1995). Principal components analysis and canonical correlation analysis are sometimes used, particularly when 

multiple tree-ring sites and (or) multiple hydroclimatic records 

are used (Loaiciga and others, 1993).

The uncertainty in the reconstructed record can be 

estimated by the standard error of prediction. However, if the 

tree-ring chronology for the extended period includes values 

that were not observed in the calibration period, extrapolation 

of the regression model into this range of values will introduce additional uncertainty into the reconstructed time series. 

Another source of uncertainty that may affect the time series 

is the number of trees available to create different periods of 

the tree chronology. The number of trees typically decreases 

toward the beginning of a chronology, increasing the uncertainty in that part of the reconstructed record (Meko and others, 1995).

Cook and others (2007) and Stahle and others (2007) 

describe the use of tree-ring chronologies to reconstruct 

approximately 1,000 years of drought history over most of 

North America. They used tree rings to reconstruct the Palmer 

Drought Severity Index (PDSI), an index calculated from 

instrumental records of precipitation and temperature as a 

measure of available soil moisture. Their analysis shows that 

past “megadroughts” eclipse those in much of the instrumental record in terms of duration and severity. This is consistent 

with Woodhouse and Overpeck’s (1998) analysis, which used 

historical documents, archaeological remains, lake sediments, 

and geomorphic data in addition to tree rings, to reconstruct 

2,000 years of drought history in the central United States. 

Eolian sediments (dunes), lake sediments, riverine cave 

sediments, and ocean sediments can also be used as proxies to reconstruct hydroclimatic information. While they do 

not allow the accuracy and resolution that is possible with 

tree-ring reconstructions, different inferences may be drawn 

from different proxies, giving a more complete picture of past 

drought events (Woodhouse, 2004).

Climate information for periods prior to the instrumental 

record can be reconstructed using historical information and 

proxy data from tree rings, sediment, and other sources. These 

reconstructed time series are generally less precise than the 

instrumental record, with varying uncertainties and time resolution, depending on the technique used; however, they can 

provide useful information on the range of variability that has 

been seen at a particular location. Paleorecords can provide 

a much better record of variability than is typically available 

from the instrumental record.

For some variables, paleoclimate reconstructions have 

been estimated millions of years into the past. Generally, the 

further back in time reconstructions are attempted, the less 

accurate they are. Water managers have varying planning 

horizons, but they are generally less than 30–40 years, and the 

large variations that may have occurred over the past millions 

of years have limited relevance. Water managers are primarily 

interested in scenarios that are consistent with current climate 

and natural variability. Holocene records (from approximately 

the last 10,000 years) provide a greater range of variability 

than observed in the instrumental record, as well as different 

sequencing of events, and they allow for reasonable estimates 

of uncertainty that can be incorporated into subsequent sensitivity analysis.

Historical documents, such as newspaper articles, diaries, 

and letters, sometimes contain useful information about notable 

climate events such as floods or prolonged droughts. In some 

cases, regular records of meteorological conditions can be 

found. For example, both Thomas Jefferson and James Madison kept meteorological diaries in the late eighteenth century 

(Druckenbrod and others, 2003). These historical records can be 

used to supplement the other techniques described below. 

A1 Drought Reconstruction

Common proxies for drought reconstruction are annual 

tree rings, analyzed using dendrochronology techniques. 

Annual variations in a tree’s growth are recorded in the width 

of its annual growth rings. Under some conditions, the variation in the growth of trees is primarily a response to climatic 

conditions, rather than factors such as competition or disease. 

For example, in the western United States, trees growing in 

arid and semiarid areas on open, dry, and rocky, south-facing slopes are most suitable for use in climate reconstructions 

because their growth is most often limited by moisture stress 

(Woodhouse, 2004). The low precipitation and high evapotranspiration rates that lead to moisture stress are the same 

conditions that lead to low streamflow or drought conditions. 

When the tree-ring patterns are similar in a number of trees 

(typically 10 or more), year-to-year differences can be attributed to climatic differences rather than to stresses experienced 

by an individual tree. These tree-ring chronologies can then be 

used as a proxy for climatic conditions. 

Appendix A 47
A2 Flood Reconstruction

Paleoflood hydrology is the study of floods prior to 

the instrumental record or in ungaged basins (Costa, 1987; 

Baker, 2008). The study of landforms, sediments, and botanical evidence can be used to infer information about previous flooding. Flood reconstructions can be used to improve 

flood-frequency estimates, but more importantly, to provide 

information on the magnitude and age of the largest flood(s) 

in a particular basin and for hydrologically homogeneous 

geographical regions (Jarrett and England, 2002).

For reconstructing individual flood events, paleostage 

indicators (PSIs) are used to estimate the maximum flood 

stage that has occurred on a river. Paleoflood hydrologists then 

translate the stage estimate to a flow estimate using standard 

hydraulic methods that are also used for recent floods (Webb 

and Jarrett, 2002) and date the event. 

The most commonly used PSIs are slackwater deposits of 

coarse-grained sediments, deposited in areas of flood inundation where velocities are minimal (Baker, 2008; Jarrett and 

England, 2002). Flood bars, eroded geologic features, and 

modifications of terraces and flood plains are also used as 

PSIs. Some of these PSIs can be preserved for tens of thousands of years, although most paleoflood reconstructions are 

made for the Holocene. Radiocarbon dating is commonly 

used to estimate the age of PSIs (for example, to within 50 to 

100 years for a flood that occurred during the Holocene). A 

minimum age of the sediment deposit can also be estimated by 

the age of any trees growing on them. In some situations, the 

thickness of sediment layers and the particle size contained in 

them can also provide clues to previous flood magnitudes. The 

layering itself may provide information about the frequency of 

flood events. 

The maximum flood stage estimated from PSIs is used 

to estimate the maximum flow using indirect-flow estimation 

techniques. These techniques are sometimes used to estimate 

flood flows in the systematic record, except that instead of 

PSIs, high water marks are taken from indicators such as 

disturbed grass, mud, silt, seed lines, and other flood-carried 

debris. Hydraulic principles are used to estimate flow rates 

based on the high water indicated by physical evidence and on 

estimated channel properties. To estimate channel properties 

for paleofloods, the river channel at the time of the paleoflood 

must be essentially the same as the modern river channel. 

Consequently, paleoflood reconstruction is most appropriate for bedrock channels that remain stable over time. These 

techniques are not suitable for unstable channels.

Using modern floods, Jarrett and England (2002) 

compared the maximum stage estimated from flood bars and 

slack water deposits to high water marks traditionally used by 

hydrologists to estimate flood stage. While there were some 

differences between the PSIs and the high water marks, Jarrett 

and England concluded that flood bars and slack water deposits generally provide a reliable and accurate indication of the 

maximum height of the flood. As pointed out by Hirschboeck 

(2003), paleoflood indicators based on flood deposits provide 

direct physical evidence of the occurrence of past floods. The 

evidence is not filtered through a biological response, such as 

tree-ring growth. Nevertheless, tree-growth responses to flood 

events can also be used to document flood stages. Common 

responses include the formation of scars, sprouting from tilted 

stems, and eccentric ring growth (Yanosky and Jarrett, 2002). 

The average maximum height of scars can provide an indicator of maximum flood stage. This evidence can be combined 

with dendrochronology techniques to date the flood events to 

a specific year. Interpretations of individual annual rings can 

sometimes identify the time of year a flood occurred to within 

a few months (Yanosky and Jarrett, 2002). However, requirements for flood-scarred, living trees in the flood plain can 

limit the length of the paleoflood reconstruction using dendrochronology (Yanosky and Jarrett, 2002). 

A3 References Cited

Baker, V., 2008, Paleoflood hydrology—Origin, progress, 

prospects: Geomorphology, v. 101, no. 1–2, p. 1–13.

Cook, E.R., Seager, R., Cane, M.A., and Stahle, D.W., 2007, 

North American drought: Reconstructions, causes, and consequences: Earth-Science Reviews, v. 81, p. 93–134.

Costa, J.E., 1987, A history of paleoflood hydrology in the 

United States, 1800–1970, in Landa, E.R., and Ince, S., eds., 

History of hydrology: History of Geophysics, v. 3, p. 49–54.

Druckenbrod, D.L., Mann, M.E., Stahle, D.W., Cleaveland, 

M.K., Therrell, M.D., and Shugart, H.H., 2003, Late-eighteenth-century precipitation reconstructions from James 

Madison’s Montepelier Plantation: Bulletin of the American 

Meteorological Society, v. 84, no. 1, p. 57–71.

Hirschboeck, K.K., 2003, Floods, paleofloods, and drought—

Insights from the Upper Tails: CLIVAR/PAGES/IPCC 

Drought Workshop, November 18–21, Tucson, AZ. 

Jarrett, R.D., and England, J.F., Jr., 2002, Reliability of paleostage indicators for paleoflood studies, Modern hazards, in

House, P.K., Webb, R.H., Baker, V.R., and Levish, D.R., 

eds., Principles and applications of paleoflood hydrology: 

Water Science and Application, American Geophysical 

Union, v. 3, p. 91–109.

Loaiciga, H.A., Haston, L., and Michaelsen, J., 1993, Dendrohydrology and long-term hydrologic phenomena: Reviews 

of Geophysics, v. 31, no. 2, p. 151–171.

Meko, D.M., Stockton, C.W., and Boggers, W.R., 1995, 

The tree-ring record of severe sustained drought: Water 

Resources Bulletin, v. 31, no. 5, p. 789–801.

Meko, D.M, Woodhouse, C.A., Baisan, C.A., Knight, T., 

Lukas, J.J., Hughes, M.K., and Salzer, M.W., 2007, Medieval drought in the Upper Colorado River Basin: Geophysical Research Letters, v. 34, p. L10705.

48  Climate Change and Water Resources Management: A Federal Perspective
Stahle, D.W., and Cleaveland, M.K., 1992, Reconstruction and 

analysis of spring rainfall over the southeastern U.S. for the 

past 1000 years: Bulletin of the American Meteorological 

Society, v. 73, p. 1947–1961.

Stahle, D.W., Fye, F.K., Cook, E.R., and Griffin, R.D., 2007, 

Tree-ring reconstructed megadroughts over North America 

since A.D. 1300: Climatic Change, v. 83, p. 133–149.

Webb, R.H., and Jarrett, R.D., 2002, One-dimensional estimation techniques for discharges of paleofloods and historical 

floods, in Ancient floods, modern hazards: Principles and 

applications of paleoflood hydrology, American Geophysical Union Water Science and Application Series, v. 5, 

p. 111–125.

Woodhouse, C.A., 2004, A paleo perspective on hydroclimatic 

variability in the western United States: Aquatic Sciences, v. 

66, p. 346–356.

Woodhouse, C.A., and Overpeck, J.T., 1998, 2000 years of 

drought variability in the central United States: Bulletin 

of the American Meteorological Society, v. 79, no. 12, p. 

2693–2714.

Yanosky, T.M., and Jarrett, R.D., 2002, Dendrochronologic 

evidence for the frequency and magnitude of paleofloods, 

in House, P.K., Webb, R.H., Baker, V.R., and Levish, 

D.R., eds., Ancient floods, modern hazards: Principles and 

applications of paleoflood hydrology: Water Science and 

Application, American Geophysical Union, v. 5, p. 77–89.

Appendix A 49

Appendix B. Downscaling General Circulation Model Results

The spatial scale of climate model output is too coarse for 

regional studies on water resources response (Maurer and others, 2007). By definition, climate projection downscaling is the 

process of transferring general circulation model (GCM) output 

to a finer spatial scale that is more meaningful for analyzing 

local and regional climate conditions. Downscaling is justified, at least in principle. Anthropogenic global climate change 

would lead to changes in large-scale atmospheric features, such 

as the tropical “Hadley Cell” atmospheric circulation and the 

wintertime climatological storm tracks in the middle latitudes. 

However, the effect of large-scale feature changes on local 

surface climate cannot be resolved in the current generation of 

GCMs, which introduces the need for downscaling.

B1 Downscaling Methods

Many downscaling methods have been developed, all of 

which have strengths and weaknesses. Several reports offer 

discussions on the various methodologies, notably the IPCC 

Fourth Assessment (Intergovernmental Panel on Climate 

Change, 2007, ch. 11) and Wigley (2004). Fowler and others 

(2007) offer an extensive review of downscaling methods that 

have been developed since the 1990s, method intercomparison 

studies, and discussion of the appropriate application of these 

methodologies for hydrologic impacts studies.

The various methodologies might be classified by two fundamentally different approaches: dynamical, where a regional 

climate model (RCM) with finer spatial resolution is embedded 

within a GCM; and, statistical, where large-scale climate features are statistically related to fine-scale climate for the region. 

The RCMs used for dynamical downscaling are typically 

resolved at the ~0.5° latitude and longitude scale and feature 

parameterized physical atmospheric processes (Fowler and others, 2007). They are able to simulate regional climate features 

such as orographic precipitation, rain shadows in mountainous 

regions, extreme climate events, and regional-scale anomalies.

There are advantages and disadvantages associated with 

the available downscaling techniques (table B–1). In both 

approaches, downscaling skill depends strongly on biases 

inherited from the driving GCM. It has been shown that 

application of either method using historical GCM-simulated 

climate produces more realistic hydrologic simulation if the 

GCM-simulated climate conditions are first bias-corrected 

relative to observations (Fowler and others, 2007).

Based on their review of available methods and method 

intercomparison studies, Fowler and others (2007) conclude 

that, generally speaking, temperature can be downscaled with 

more skill than precipitation, winter climate can be downscaled 

with more skill than summer because of stronger relations with 

large-scale circulation, and wetter climates can be downscaled 

with more skill than drier climates. However, it remains difficult 

to directly compare the skill of different methods because of 

the range of climate statistics that have been assessed in the 

literature, the large range of predictors used, and the different 

proposed methods for assessing model performance.

Although theoretical strengths and weaknesses of each 

downscaling method are generally established (for example, 

those listed in table B–1), no single best downscaling method 

is obviously identifiable (Fowler and others, 2007). Simple 

statistical downscaling methods seem to perform well and at 

low computational cost when the goal is to reproduce mean 

climate characteristics. If the goal is to reproduce extreme 

characteristics, a more sophisticated method may be warranted. Salathé and others (2007) note that in mountainous 

regions there may be important orographic controls on precipitation, such as rain shadows affecting lee-side precipitation 

relative to mean storm patterns, or there may be important 

land-surface feedbacks potentially affecting local climate as 

regional temperatures increase (for example, warming leading 

to reduced snow-cover area, reduced land-surface albedo, 

increased land-surface absorption of solar radiation and emission of long-wave radiation, and thus a positive reinforcement on local warming). In these geographic situations and 

for the purpose of capturing different climate qualities, it may 

be preferable to apply RCM-based, dynamical, downscaling 

techniques rather than statistical techniques.

Appendix B 51

Table B–1. General advantages and disadvantages associated with statistical and dynamical classes of downscaling methods.

Statistical Dynamical

Advantages • Comparatively cheap and computationally efficient

• Can provide point-scale climatic variables from GCMscale output

• Able to directly incorporate observations into method

• Produces responses based on physically consistent processes

• Produces finer-resolution information from GCM-scale 

output that can resolve atmospheric processes on a smaller 

scale (for example, orographic and rain shadow effects in 

mountainous areas)

Disadvantages • Does not account for non-stationarity in the predictorpredictand relationship

• Climate system feedbacks not included

• Dependent on GCM boundary forcing; affected by 

biases in underlying GCM

• Dependent on statistical or empirical model structure 

and associated parameters; different models will give 

different results

• Computationally intensive

• Limited number of scenario ensembles available

• Dependent on GCM boundary forcing; affected by biases in 

underlying GCM

• Dependent on RCM parameterizations; different RCMs will 

give different results
B2 Downscaled Climate Projections Archive

As noted, downscaling skill depends strongly on biases 

inherited from the driving GCM. Thus, it would seem 

appropriate to scope studies on prospective climate impacts 

on hydrology and water resource sectors so that they sufficiently represent the breadth and distribution of contemporary climate projections, independent of the method selected 

for downscaling. Fowler and others (2007) support this 

notion, suggesting that probabilistic methods for developing scenarios of future climate and associated hydrology 

may offer a robust way of assessing climate change impacts. 

Furthermore, they assert that the inclusion of uncertainty 

estimates using a multi-GCM approach may offer the most 

potential for advancement within both the “downscaling for 

hydrological impacts” science community and for practitioners. Addressing this issue, a downscaled climate projections (DCP) archive has been made available (“Statistically 

Downscaled WCRP CMIP3 Climate Projections” available at 

http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/), 

featuring spatially downscaled translations of 112 CMIP3 

projections collectively produced by 16 CMIP3 models 

simulating 3 emissions paths [B1 (low), A1b (middle), A2 

(high)] from different end-of-the-twentieth-century climate 

conditions. The DCP archive permits survey of climate 

projection information over locations or areas within the 

contiguous United States, southern Canada, and northern 

Mexico. The following considerations drove selection of 

the statistical approach supporting DCP archive development [Bias-Correction and Spatial Disaggregation (BCSD) 

described in Wood and others (2002, 2004), as reported at 

http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/

#Limitations]:

Well tested and documented, especially in applications 

in the United States.

Automated and efficient enough to feasibly permit 

downscaling of many twenty-first century climate 

projections, thereby permitting more comprehensive 

assessments of downscaled climate projection uncertainty.

Able to produce output that statistically matches observations for a historical period.

Capable of producing spatially continuous, fine-scale 

gridded output of precipitation and temperature suitable for water resources and other watershed-scale 

impacts analysis.

While there are many statistical techniques available 

(Wigley, 2004; Intergovernmental Panel on Climate Change, 

2007; Fowler and others, 2007), only the BCSD met all of 

these criteria at the time of DCP archive development. 

To date, there has not been a demonstration of using 

dynamical downscaling to produce a dataset as comprehensive 

as the DCP archive (in terms of geography, variables, projec-

•

•

•

•

tions, and projected years represented). The computational 

expense associated with RCM application to the DCP projections scope was the primary reason why RCM application 

was viewed to be infeasible in DCP-archive development. 

While there are new efforts to downscale multiple climate 

projections using multiple RCMs, such as the North American 

Regional Climate Change Assessment Program (NARCCAP, 

http://www.narccap.ucar.edu/), the computational requirements 

of applying RCM-based downscaling for a few decades and a 

few GCM projections remain large compared to the DCP scope 

of downscaling 150 years from more than 100 GCM simulations. 

Compared to dynamical downscaling approaches, the 

BCSD method has been shown to provide downscaling capabilities comparable to those of other statistical and dynamical methods in the context of hydrologic impacts (Wood and 

others, 2004). However, as already noted, dynamical downscaling has also been shown to identify some local climate 

effects and land-surface feedbacks that BCSD cannot readily 

identify (Salathé and others, 2007). Another potential limitation of BCSD, like any statistical downscaling method, is the 

assumption of some stationarity, where it is assumed that the 

relation between large-scale precipitation and temperature 

and fine-scale precipitation and temperature in the future will 

be the same as in the past. For example, the processes determining how precipitation and temperature anomalies for any 

2°-grid box are distributed within that grid box are assumed 

to govern in the future as well. A second assumption included 

in the bias-correction step of the BCSD method is that any 

biases exhibited by a GCM for the historical period will also 

be exhibited in future simulations. Tests of these assumptions, 

using historic data, show that they appear to be reasonable, 

inasmuch as the BCSD method compares favorably to other 

downscaling methods (Wood and others, 2004). 

BCSD has been frequently used to support climate 

change impacts assessments on western U.S. hydrology in 

recent years, such as the Columbia-Snake Basin (Payne and 

others, 2004), the California Central Valley (Van Rheenan 

and others, 2004; Maurer and Duffy, 2005; Anderson and 

others, 2008; Maurer, 2007), and the Colorado River Basin 

(Christensen and others, 2004; Christensen and Lettenmaier, 

2007). The California Governor’s office receives a collection 

of studies every 2 years in a Biennial Science Report (BSR). 

In the 2008 BSR update, two techniques will be featured 

(http://meteora.ucsd.edu/cap/scen08_data.html): BCSD and 

“Constructed Analogues” (CA) (Hidalgo and others, 2008). 

Both methodologies satisfy the DCP-archive development 

criteria outlined above. A recent comparison of the methods 

(Maurer and Hidalgo, 2008) shows that the results are not 

significantly different when the methods are used to develop 

monthly time-series temperature and precipitation projections. 

However, for the goal of developing daily projected time 

series of temperature and precipitation information, the CA 

methodology was found to be preferable in some locations and 

during some times of the year. For both methods, however, the 

skill of the methodology was found to be significantly limited 

by the uncertainties of the input GCM information.

52 Climate Change and Water Resources Management: A Federal Perspective
B3 References Cited

Anderson, J., Chung, F., Anderson, M., Brekke, L., Easton, 

D., Ejeta, M., Peterson, R., and Snyder, R., 2008, Progress 

on Incorporating Climate Change into Management of 

California’s Water Resources, Climatic Change, v. 87, no.1, 

p. S91–S108.

Christensen, N., and Lettenmaier, D.P., 2007, A multimodel 

ensemble approach to assessment of climate change impacts 

on the hydrology and water resources of the Colorado River 

basin: Hydrology and Earth System Sciences, v. 3, p.1–44.

Christensen, N.S., Wood, A.W., Voisin, N., and Lettenmaier, 

D., 2004, The effects of climate change on the hydrology 

and water resources of the Colorado River basin: Climatic 

Change, v. 62, p. 337–363.

Fowler, H.J., Blenkinsop, S., and Tebaldi, C., 2007, Review: 

Linking climate change modeling to impacts studies—

Recent advances in downscaling techniques for hydrological modelling: International Journal of Climatology, v. 27, 

p. 1547–1578.

Hidalgo, H.G., Dettinger, M.D., and Cayan, D.R., 2008, 

Downscaling with constructed analogues—Daily precipitation and temperature fields over the United States: 

Sacramento, CA, California Energy Commission, Report 

No. CEC–500–2007–123.

Intergovernment Panel on Climate Change, Climate change 

2007—The physical science basis. Contribution of Working Group I to Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon, S., Qin, 

D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., 

Tignor, M., and Miller, H.L., eds.: Cambridge, United 

Kingdom, Cambridge University Press. Available at 

http://www.ipcc.ch/ipccreports/ar4-wg1.htm.

Maurer, E.P., 2007, Uncertainty in hydrologic impacts of 

climate change in the Sierra Nevada, California under two 

emissions scenarios: Climatic Change, v. 82, p. 309–325.

Maurer, E.P., Brekke, L., Pruitt, T., and Duffy, P.B., 2007, 

Fine-resolution climate projections enhance regional 

climate change impact studies: Eos, Transactions of the 

American Geophysical Union, v. 88, no. 47, p. 504.

Maurer, E.P., and Duffy, P.B., 2005, Uncertainty in projections 

of streamflow changes due to climate change in California: 

Geophysical Research Letters, v. 32, no. 3, p. L03704.

Maurer, E.P., and Hidalgo, H.G., 2008, Utility of daily vs. 

monthly large-scale climate data—An intercomparison of 

two statistical downscaling methods: Hydrology and Earth 

System Sciences, v. 12, p. 551–563.

Payne, J.T., Wood, A.W., Hamlet, A.F., Palmer, R.N., and 

Lettenmaier, D.P., 2004, Mitigating the effects of climate 

change on the water resources of the Columbia River basin. 

Climatic Change: v. 62, no. 1–3, p. 233–256.

Salathé, E.P., Mote, P.W., and Wiley, M.W., 2007, Review of 

scenario selection and downscaling methods for the assessment of climate change impacts on hydrology in the United 

States Pacific Northwest: International Journal of Climatology, v. 27, p. 1611–1621.

Van Rheenen, N.T., Wood, A.W., Palmer, R.N., and Lettenmaier, D.P., 2004, Potential implications of PCM climate 

change scenarios for Sacramento-San Joaquin River Basin 

hydrology and water resources: Climatic Change, v. 62, 

p. 257–281.

Wigley, T.M.L., 2004, Input needs for downscaling of climate 

data: Discussion paper prepared for California Energy Commission Public Interest Energy Research Program Report 

500–04–027.

Wood, A.W., Maurer, E.P., Kumar, A., and Lettenmaier, D.P., 

2002, Long-range experimental hydrologic forecasting for 

the eastern United States: Journal of Geophysical ResearchAtmospheres, v. 107, no. D20, p. 4429.

Wood, A.W., Leung, L.R., Sridhar, V., and Lettenmaier, D.P., 

2004, Hydrologic implications of dynamical and statistical 

approaches to downscaling climate model outputs: Climatic 

Change, v. 15, p. 189–216.

Appendix B 53

Appendix C. Recent Reclamation and USACE Planning Applications Involving 

the Use of Expanded Climate Information Sets

As discussed in chapter 3, there have been several 

recent examples of Reclamation, USACE, and other Federal 

and State agencies exploring the use of expanded climate 

information sets to support various water resources planning 

efforts. In this context, an expanded set is defined to include 

instrumental record information plus any mix of the following: (1) synthetic hydrologic sequences developed through 

stochastic modeling, (2) additional reference climate and 

sequence indicated by paleoclimate evidence, and (3) projected climate information consistent with future scenarios 

of greenhouse gas emissions (Intergovernmental Panel on 

Climate Change, 2007). 

Three examples were mentioned in chapter 3, where the 

focus was on evaluating proposed or expected long-term plans 

of operation:

Lake Ontario–St Lawrence River Study, which used 

climate projection information and stochastic modeling 

to guide hydrologic variability assumptions in water 

control planning for the Lake Ontario–St. Lawrence 

River System (International Joint Commission, 2006).

Colorado River Basin Study, which used nonparametric 

stochastic modeling with paleoclimate information to 

guide water supply variability assumptions in operations planning for the Colorado River Storage System 

(Bureau of Reclamation, 2007).

California Central Valley Study, which used climate 

projection and sea-level rise information to guide water 

supply assumptions in a biological assessment on 

multiple fish species in the California Central Valley 

(Bureau of Reclamation, 2008).

This appendix discusses the process and purposes of each 

study and how climate information was related to planning 

assumptions. 

C1 Lake Ontario–St. Lawrence River Study

C1.1 Process and Purpose

The International Joint Commission (IJC) oversees 

operation of the St. Lawrence River Hydropower Project. Current operations of this water resources system are conducted 

according to Plan D–1958, which consists of rules for making 

weekly releases from Lake Ontario that vary based on lake 

inflows and levels, time of year, ice conditions, Ottawa River 

flows, and other factors. Plan D–1958 was developed relative 

to hydroclimate observations collected during 1860–1954. 

In response to interest in understanding whether the water 

control plan should be modernized (for example, to better 

accommodate changing social objectives related to environmental management or recreational boating), the IJC called for 

the development of plan information on criteria and options 

for regulating Lake Ontario water levels and outflow to the 

St. Lawrence River (fig. C–1). The objective was to explore 

options that would benefit affected interests reliant on collective system resources and would conform to the requirements of the Boundary Waters Treaty. The optional control 

plans were evaluated relative to three criteria: (1) support the 

ecological integrity of the system, (2) maximize net benefits 

including both economic and environmental benefits, and 3) 

minimize disproportionate losses.11

Within this decision framework, climate assumptions 

were one of the factors affecting plan viability. Specifically, 

there was the study guideline that regulation “of the Lake 

Ontario-St. Lawrence River system will be adaptable” and to 

the extent possible be designed to accommodate “potential 

for changes in water supply as a result of climate change and 

stochastic variability” (International Joint Commission, 2006). 

Figure C–1. Geographic setting for International Joint 

Commission (2006) regarding the use of projected regional climate 

information and stochastic data enrichment to guide water control 

planning in the Lake Ontario-St. Lawrence River system. 

11This last criterion has not generally been used in USACE planning studies. 

“Disproportionate loss” was a qualitative determination that included several 

factors including the duration and frequency of the impacts, an assessment of 

which plan minimizes the maximum losses, and an assessment of the robustness of the plans under extreme water supply conditions.

•

•

•

Appendix C 55
C1.2 Role of Climate Information

The economic and environmental performance evaluations conducted for the plan options were based on a host of 

modeling activities for various affected resources areas. Each 

evaluation required various planning assumptions related 

to system supplies, demands, and water control constraints 

(ch. 3).

Initial assessment of plan performances was based on 

planning water supply assumptions consistent with the climate 

of the instrumental record (1900–2000, or 101 years), both in 

terms of statistics and sequence. Relative to this initial assessment, two sensitivity analyses were then conducted to explore 

how plan evaluations might be sensitive to: (1) alternative 

hydroclimatic sequencing still consistent with the climate 

statistics of the instrumental record, and (2) climate regime 

changes inferred by the surveyed climate projections. 

For the first sensitivity analysis, a stochastic model 

was developed (ch. 3) to reflect the climate statistics of the 

instrumental record. The model was then applied to produce 

multiple synthetic 101-year sequences of supplies to the 

Great Lakes, the Ottawa River, and other downstream tributary flows. The stochastic model reflected the probabilistic 

relations between instrumental record supplies from one 

year to the next, the seasonal patterns of supplies, and their 

quarter-month to quarter-month correlations. The model also 

preserved other important statistical properties of the system, 

such as the varying lengths of drought and surplus periods and 

the spatial relation of supplies among basins. Lastly, the model 

included a random component to generate natural variations 

(constrained by observations) for each of the modeled hydrologic component. 

For the second sensitivity analysis, the intent was to 

consider a range of potential water supplies associated with 

shifts in climate statistics from those of the late twentieth 

century to those of the mid-twenty-first century. Interest was 

focused on how such a climate change might impact seasonal 

runoff and evaporation. To that end, 28 global climate projections were surveyed, including those developed for or shortly 

after the release of the IPCC Third Assessment (Intergovernmental Panel on Climate Change, 2001). These projections were then evaluated to assess mean annual temperature 

and precipitation changes over the study region between the 

periods of 1961–1990 and 2041–2069 (Mortsch and others, 

2005). Climate projection selection was driven by an interest 

to choose projections that collectively bracketed the “spread” 

of temperature and precipitation changes (fig. C–2). For each 

selected projection, period mean changes were assessed, again 

from 1961–1990 to 2041–2069, for variables necessary for 

hydrologic response modeling [that is precipitation (ratio), 

minimum daily air temperature at 2 meters (oC), average 

daily air temperature at 2 meters (oC), maximum daily air 

temperature at 2 meters (oC), wind speed increase at 2 meters 

(ratio), specific humidity increase (ratio), and cloud cover 

increase (ratio)]. These changes in variable period means were 

then used to adjust historical meteorology data for the Great 

Figure C–2. Projected 2050 

climate change conditions 

sampled from 28 climate 

projections averaged over the 

Great Lakes region (Mortsch 

and others, 2005). Circled 

projections indicate those used 

for the sensitivity analysis in 

International Joint Commission 

(2006).

56 Climate Change and Water Resources Management: A Federal Perspective
Lakes and Ottawa River basins, relative to which hydrologic 

modeling was conducted to develop planning water supply 

sequences associated with the given climate change regime. 

In summary, the economic and environmental evaluations 

of plan options in IJC (2006) were based on multiple modeling analyses considering multiple unique “stationary climates” 

(instrumental record and projected climate) and using stochastic modeling to augment the sense of plausible climate variability associated with the instrumental record climate. 

C2 Colorado River Basin Study

C2.1 Process and Purpose

The Secretary of the Interior, acting through Reclamation, 

proposed adopting interim guidelines for allocating water in 

the Colorado River Lower Basin (Lower Basin) and coordinated operations for Lake Powell and Lake Mead, particularly 

under drought and low reservoir conditions (referred to as 

“shortage criteria”). Reclamation served as the lead Federal agency for the purposes of compliance pursuant to the 

National Environmental Policy Act of 1969 and development 

of the final EIS on the proposed action (Bureau of Reclamation, 2007). Five Federal agencies assisted with environmental 

analysis and the preparation of the EIS: the Bureau of Indian 

Affairs (BIA), U.S. Fish and Wildlife Service (USFWS), 

National Park Service (NPS), Western Area Power Administration (Western), and the United States Section of the International Boundary and Water Commission (USIBWC).

Prior to this effort, the Department of the Interior did not 

have specific operational guidelines in place to address the 

operations of Lake Powell and Lake Mead during drought and 

low reservoir conditions (Bureau of Reclamation, 2007). The 

purpose of the proposed action was to 

Improve Reclamation’s management of the Colorado 

River by considering trade-offs between the frequency 

and magnitude of reductions of water deliveries, and 

considering the effects on water storage in Lake Powell 

and Lake Mead, and on water supply, power production, recreation, and other environmental resources; 

Provide mainstream United States users of Colorado 

River water, particularly those in the Lower Division 

States, a greater degree of predictability with respect to 

the amount of annual water deliveries in future years, 

particularly under drought and low reservoir conditions; and 

Provide additional mechanisms for the storage and 

delivery of water supplies in Lake Mead to increase 

the flexibility of meeting water use needs from Lake 

Mead, particularly under drought and low reservoir 

conditions (Bureau of Reclamation, 2007). 

The adopted guidelines would remain in effect through 

2026.

•

•

•

C2.2 Role of Climate Information

The environmental effects analyses conducted for the 

various proposed action alternatives (and no-action alternative) were driven by assumptions of system water supplies, 

demands, and operational constraints feature in the Colorado 

River Simulation System (CRSS) (fig. C–3). CRSS was used 

to look at a range of future Colorado River system conditions 

under each action alternative. Initial planning assumptions 

were characterized on a monthly time step based on instrumental records and served as “scenario” assumptions for a 

future period of 2008 through 2060 (admittedly extending 

beyond the proposed action’s application horizon of 2008 

through 2026). The traditional use of CRSS involves blockresampling of instrumental records [that is, Index Sequential 

Method (ISM)] (Bureau of Reclamation, 2007), resulting in 

multiple input hydrologic sequences consistent with the instrumental record, and setting up an ensemble of system simulations that are evaluated collectively (see fig. C–4). 

In this study, no projected climate information was 

considered in the modeling analyses, in part because of the 

relatively short lookahead period associated with the study 

(that is, 19 years). However, there was interest in understanding the potential effects of future inflow sequences outside 

the range of historical flow sequences (for example, a future 

with different hydrologic variability and associated severity, 

frequency, and duration of droughts). As a result, a sensitivity 

analysis (Bureau of Reclamation, 2007, Appendix N) was conducted on the sensitivity of system conditions to an expanded 

range of hydrologic variability viewed to be plausible during 

the planning horizon. 

In developing assumptions about hydrologic variability, 

two climate regimes were referenced in the study: (1) the 

climate of instrumental record (that is, natural runoff estimates based on Colorado River basin observations during 

1906–200) (fig. C–); and (2) the climate from the reconstructed period of annual streamflow at Lees Ferry based on 

tree-ring records (Meko and others, 2007). Stochastic modeling was used to develop synthetic hydrologic and water supply 

sequences consistent with either reference climate (Bureau of 

Reclamation, 2007, appendix N).

Paleoclimate-based reconstructions of Lees Ferry streamflow were used in two ways for this study:

• Direct Paleo (DP), which involved basing supply 

sequences on both the state and magnitudes information from the reconstructed streamflows, and 

• Nonparametric Paleo-Conditioned (NPC), which 

involved harvesting only the state information from the 

reconstructed flows and blending that information with 

magnitudes information from the instrumental record.

The DP technique involved developing hydrologic input 

sequences from a 1,244-year annual reconstruction of Colorado River streamflow at Lees Ferry (Meko and others, 2007). 

This sequence was of particular interest because it encapsulated the Medieval Climate Anomaly (900 to 1300), a period 

Appendix C 57
MEXICO

Figure C–3. Locations 

of the Colorado River 

Basin hydrologic input 

sites in the Colorado River 

Simulation System (Bureau of 

Reclamation, 2007).

flow reconstruction at one location (Lees Ferry) to monthly 

streamflows at the 29 CRSS inflow locations (fig. C–3) 

(Prairie and others, 2007). ISM was then applied to this latter hydrologic dataset to generate 1,244 traces of 3-year 

hydrologic input sets, reflecting the runoff magnitudes and 

sequences associated with the paleoclimate period.

The NPC technique was developed because reported 

magnitudes of reconstructed streamflow at Lees Ferry vary 

considerably depending on reconstruction (Bureau of Reclamation, 2007). Thus the role of paleoclimate in the NPC technique was limited to providing information on hydrologic state 

when various paleoclimate data indicate hydrologic droughts 

in the western United States were abnormally widespread 

(Meko and others, 2007). A strength of this dataset was that 

the reconstructed streamflow sequences were different from 

sequences from the natural flow record. A weakness of the 

dataset was the uncertainty of the reconstructed streamflow 

magnitudes. It is understood that reconstructed flow magnitudes are sensitive to the sampling and statistical method 

employed (Hidalgo et al., 2000). After this annual Lees Ferry 

streamflow sequence was selected, nonparametric techniques 

were used to spatially and temporally relate the annual stream58  Climate Change and Water Resources Management: A Federal Perspective
Figure C–4. Probabilistic 

projection of Lake Mead 

end-of-December elevations 

under the no-action alternative 

based on the default use 

of natural flow records [fig. 

4.2–2 in chapter 4 of Bureau 

of Reclamation (2007)]. The 

colored lines correspond to 

individual CRSS simulations 

corresponding to specific 

hydrologic input traces 

generated in application of 

the Index Sequential Method 

sampling from the historical 

natural flow record (that is, 

Traces 1, 21, and 48, arbitrarily 

selected for illustration). 

The black lines correspond 

to sampled 10, 50, and 90 

percentile elevations from 

year-specific distributions 

across the ensemble of CRSS 

simulations completed (and 

hydrologic traces analyzed).

Figure C–5. Estimated natural flow of the Colorado River at 

the Lees Ferry gaging station, Arizona, 1906–2005 (Bureau of 

Reclamation, 2007, fig. 3.3–1).

possibilities, as evident in the reconstructed streamflow data 

(that is, relatively wet versus dry, and year-to-year sequences 

of these states), which was found to more synchronous among 

the various published streamflow reconstructions at Lees 

Ferry. The purpose of this technique was to use state information from the paleoclimate information to guide modeling of 

annual hydrologic sequences defining whether the river state is 

relatively dry or wet in any given year of the sequence, but to 

then combine this sequence information with the magnitudes 

information (assumed possibilities) from the instrumental 

record (Prairie and others, 2007). A strength of this technique 

is that it combines the strengths of using the streamgage record 

adjusted to natural flow (relatively more certain estimates of 

annual and monthly streamflow magnitude possibilities) and 

the strength of the DP method (sequences of relative dry and 

wet conditions not witnessed in the natural flow record). A 

weakness of this technique is that it only portrayed magnitudes 

observed in the natural flow record and involves relatively 

more complex hydrologic modeling techniques that are more 

challenging to explain to stakeholders. Proceeding with this 

approach, the NPC technique was applied to generate 125

traces of 53-year hydrologic input sets for CRSS.

C3 California Central Valley Study

C3.1 Process and Purpose

Reclamation and the California Department of Water 

Resources (CA–DWR) operate the Central Valley Project 

(CVP) and State Water Project (SWP) systems, respectively, 

located in California’s Central Valley (fig. C–6). In 2004, Reclamation initiated formal and early section 7 consultation of 

the Federal Endangered Species Act with the National Marine 

Fisheries Service and the U.S. Fish and Wildlife Service. The 

consultation considered how CVP and SWP system operations 

currently and are projected to affect multiple listed fish species 

through 2030. In preparation for this consultation, Reclamation and CA–DWR developed a biological assessment on the 

coordinated CVP/SWP operations, as well as the Operational 

Criteria and Plan (OCAP BA). The 2004 OCAP BA, which 

was prepared to provide a baseline description of the CVP/

Appendix C 59
SWP facilities and operating environment, identified the many 

factors influencing the physical and institutional conditions 

and decisionmaking process under which the projects then 

currently operated.

Subsequent to their release, the 2004 OCAP BA and associated biological opinions were challenged on several fronts, 

one of which was failure to consider the potential effects of 

climate change on the operating environment during the consultation horizon. A 2008 OCAP BA has been developed, with 

both instrumental record and projected climate information 

factored into the BA development. The report addressed how 

climate change might affect tributary streamflows and water 

temperatures, sea-level rise effects on the delta environment, 

and dependent operations during the consultation horizon.

Several levels of climate analysis were considered: 

Qualitative discussion of implications of climate 

change for future CVP and SWP operations.

Quantitative sensitivity analysis of implications for 

future CVP and SWP operations under a range of 

potential climates circa 2030 in order to illustrate the 

how the OCAP future operational baseline is sensitive 

to the future climate assumption.

Quantitative depiction of the OCAP future operational 

baseline with a more resolved probability distribution 

estimated for future climate circa 2030 and translated 

into associated changes in water supply, demand, and 

operational constraint assumptions.

The first approach was ruled out in favor of one of the 

quantitative approaches, given that regional climate projection 

•

•

•

information was available and that a consultation horizon of 

2030 (that is, greater than 20 years) would span a period where 

climate change and hydrologic impacts could be detected and 

assessed (Intergovernmental Panel on Climate Change, 2007; 

see climate and climate change period descriptions in section 

1). Given the uncertainties associated with estimating climate 

change probability distributions, the second approach was chosen (“sensitivity analysis”) with the objective of illustrating 

how the OCAP BA’s future depiction of CVP/SWP operation 

is sensitive to a range of regional climate and sea level possibilities by the consultation horizon (that is, 2030) as indicated 

by projections available for each condition

C3.2 Role of Climate Information

The future baseline depiction of CVP/SWP operations 

depends on several climate-related assumptions, including 

water supplies, water demands, and operational constraints. In 

the default analysis, these assumptions are based on hydroclimate observations from the instrumental record, reflected 

by hydrologic observations and impairment information from 

1922 to 2003. System water demands are evaluated relative to 

scenario climate and land cover conditions. These supply and 

demand assumptions are compatible if the view is held that 

climate of the instrumental record (underlying supply assumptions) is still applicable to the future planning horizon and 

that the scenario definition underlying demand assumptions is 

applicable to the future planning horizon. 

In this study the hydroclimatic sequencing and relative 

variability aspects of the instrumental record were preserved 

(for example, relative severity and timing of droughts). 

However, this full-period sequence was adjusted in the mean 

to reflect mean monthly natural runoff responses to regional 

climate change possibilities by the early twenty-first century 

relative to the late twentieth century.12 Further, the effects of 

coincidental sea-level rise on delta conditions were related to 

operations analyses (for example, they were allowed to affect 

the modeled delta salinity conditions constraining upstream 

release objectives to satisfy delta water quality or cross-delta 

water conveyance objectives).

To bracket ranges of temperature and precipitation 

change possibilities, four regional climate change scenarios 

were defined to represent a change range by roughly 2030, 

similar to the bracketing approach used in IJC (2006) but 

12On the matter of relating regional climate change possibilities to watersupply assumptions, the study considered climate projection information 

developed for the IPCC Fourth Assessment (Intergovernmental Panel on Climate Change, 2007) that had been statistically downscaled to basin-relevant 

resolution (that is, the Web archive “Statistically Downscaled WCRP CMIP3 

Climate Projections” at http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections). The 112 climate projections included in this archive were considered 

to be equally plausible projections of the future, given available literature 

suggesting difficulty in culling projections based on model skill (Reichler and 

Kim, 2008; Brekke and others, 2008; Gleckler and others, 2008) and given 

studies showing that regional climate projection uncertainty may not be significantly reduced even if projection sets are restricted to only include those 

from skill-based “better models” (Brekke and others, 2008).

Figure C–6. California Central Valley Project and State Water 

Project service areas.

60 Climate Change and Water Resources Management: A Federal Perspective
surveying a larger collection of downscaled contemporary 

projections from the web archive mentioned above. The four 

climate projections were selected for how their paired precipitation–temperature changes spanned projected climate 

possibilities, given four selection factors: 

Choice of historical and future periods for assessing 

climate changes, 

Metric of climate change, 

Location of climate change, and

Change-range of interest in both projected conditions 

(dependent on periods, metric, and location). 

In this study, the choices for the four selection factors 

were: 

1971–2000 and 2011–2040,

Mean-annual temperature and mean-annual precipitation during each period given the interest in meanannual water supply assumptions framing the study,

A central location relative to the combined origins of 

CVP/SWP surface-water supplies, ultimately selected 

as upstream from Folsom Lake (fig. C–7), and 

The 10th and 90th rank-percentile changes in both projected conditions among the 112 projections surveyed.

•

•

•

•

•

•

•

•

The spread and change range of interest among surveyed 

climate projections are shown on figure C–8, first independently for temperature and precipitation changes (upper left 

and lower right panels) and then for joint changes in both 

variables (upper right panel). The resultant projection selections are shown on figure C–9. They were chosen because 

they most closely span the change range of interest (that is, 

the yellow region on fig. C–9). Qualitatively speaking, the 

selected projections were viewed to generally encapsulate 

available regional climate projection information describing 

2030 climate possibilities for this study region and to suggest 

climate changes spanning “less warm” to “more warm” conditions and drier to wetter conditions.

On the matter of defining sea-level rise (SLR) possibilities for the delta by year 2030, ideally a range of scenarios 

would have been defined and combined with each operations 

study specific to the four regional climate change scenarios. 

However, due to limitations with delta simulation tool availability, only one SLR scenario was selected. The scenario 

was defined to be consistent with SLR projection information provided in IPCC (2007) and also by the SLR implied 

Figure C–7. “Above Folsom Lake” location (that is, Selection 

Factor #3) for assessing the spread of mean climate changes 

among surveyed climate projections in Bureau of Reclamation 

(2008).Projections data were obtained from the Web archive of 

“Statistically Downscaled WCRP CMIP3 Climate Projections” 

(http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections).

Figure C–8. Evaluation of climate projections spread, given the 

selection factors from Bureau of Reclamation (2008). The upper 

left and lower right panels, respectively, show distributions of 

projected changes in mean annual temperature and precipitation 

across the 112 climate projections surveyed (black “x” symbols 

are used to show rank projection-specific changes). Change 

ranges spanning the 10 and 90 percentile changes are indicated 

on both plots using green lines. The upper right panel shows 

paired changes in both variables by projection (black circles). It 

also shows the change region spanned by the intersected 10-to90 percentile change ranges assessed for each variable (yellow 

region).

Appendix C 61
using a projection methodology published subsequent to the 

finalization of IPCC (2007) (Rahmstorf, 2007a, b). The latter 

approach uses the observed linear relation between rates of 

change of global surface air temperature and sea level, along 

with projected changes in global surface air temperature, 

to predict the future SLR. To some degree, this approach 

accounts for the effects of ice melt in potential SLR, which 

was understood to not be fully or well represented in the 

climate simulations referenced in IPCC (2007). Further, it was 

understood that sea level data associated with direct CMIP3 

output on SLR are potentially unreliable due to datum issues 

with sea-surface elevations.

Given scenarios for both regional climate change and 

sea-level rise, scenario-impacts assessment followed. Regional 

climate changes were translated into natural hydrologic 

response (that is, changes in surface-water runoff), which were 

subsequently related to CVP/SWP reservoir inflows. Next, the 

operations analysis was conducted based on hydrology representing the four regional climate scenarios and was matched 

with the scenario-adjusted delta representation corresponding 

to the SLR scenario. Results from these analyses were used 

to indicate the sensitivity of CVP/SWP operations to climate 

(for example, mean annual water deliveries, carryover storage 

volumes) and also the sensitivity of dependent conditions to 

climate (that is, delta flows and velocities, reservoir and river 

water temperatures).

Note that CVP/SWP water demands were not modified 

with respect to regional climate change. This approach was 

based on the assumption that district-level demand-management flexibility existed for both CVP and SWP water contractors (for example, shifts in cropping choices, irrigation technology), enough so that district-level water demands would 

not necessarily have to change even though crop-specific 

water needs might be predictable relative to climate change.

C4 References Cited

Brekke, L.D., Dettinger, M.D., Maurer, E.P., and Anderson, 

M., 2008, Significance of model credibility in estimating 

climate projection distributions for regional hydroclimatological risk assessments: Climatic Change, v. 89, no. 3–4, p. 

371–394. Available at http://www.springerlink.com/content/

1586u015g87v8754/.

Bureau of Reclamation, 2007, Analysis of hydrologic variability sensitivity, Appendix N in Final EIS—Colorado River 

interim guidelines for lower basin shortages and coordinated operations for Lake Powell and Lake Mead: Bureau 

of Reclamation, U.S. Department of the Interior.

Bureau of Reclamation, 2008, Sensitivity of future CVP/SWP 

operations to potential climate change and associated sea 

level rise, Appendix R in CVP/SWP OCAP Biological 

Assessment: Bureau of Reclamation, U.S. Department of 

the Interior.

Gleckler, P.J., Taylor, K.E., and Doutriaux, C., 2008, Performance metrics for climate models, Journal of Geophysical 

Research, v. 113, D06104, doi:10.1029/2007JD008972.

Hidalgo, H.G., Piechota, T.C., and Dracup, J.A., 2000, Alternative principal components regression procedures for dendrohydrologic reconstructions, Water Resources Research, 

v. 36, no. 11, p. 3241–3249.

International Joint Commission, 2006, Options for managing Lake Ontario and St. Lawrence River water levels 

and flows: Report to the International Joint Commission, 

prepared by the International Lake Ontario—St. Lawrence 

River Study Board.

Intergovernmental Panel on Climate Change, 2001, Climate 

change 2001: The Scientific Basis, Cambridge University 

Press, 881 p.

Intergovernmental Panel on Climate Change, 2007, Climate 

change 2007—The physical science basis. Contribution of 

Working Group I to the Fourth Assessment Report of the 

Intergovernmental Panel on Climate Change, Solomon, 

S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, 

K.B., Tignor, M., and Miller, H.L., eds.: Cambridge, 

United Kingdom, Cambridge University Press. Available at 

http://www.ipcc.ch/ipccreports/ar4-wg1.htm.

Figure C–9. Selected climate projections (green diamonds) 

for framing the climate change sensitivity analysis in Bureau of 

Reclamation (2008). The selected projections were selected for 

how they encapsulate the spread of potential climate changes 

from 112 climate projections (fig.C–8) assessed relative to the four 

selection factor choices made for this study

62 Climate Change and Water Resources Management: A Federal Perspective
Meko, D.M, Woodhouse, C.A., Baisan, C.A., Knight, T., 

Lukas, J.J., Hughes, M.K., and Salzer, M.W., 2007, Medieval drought in the Upper Colorado River Basin: Geophysical Research Letters, v. 34, p. L10705.

Mortsch, L.D., Alden, M., Klaassen, J., 2005, Development of 

Climate Change Scenarios for Impact and Adaptation Studies in the Great Lakes – St. Lawrence Basin, report prepared 

for the International Joint Commission—International Lake 

Ontario St. Lawrence River Study Board, 29 p.

Prairie, J., Rajagopalan, B., Lall, U., and Fulp, T., 2007, A 

stochastic nonparametric technique for space-time disaggregation of streamflows: Water Resources Research, v. 43, 

p. W03432.

Rahmstorf, S., 2007a, A semi-empirical approach to projecting 

future sea-level rise: Science, v. 315, p. 368–370.

Rahmstorf, S., 2007b, Response to comments on “A SemiEmpirical Approach to Projecting Future Sea-Level Rise”: 

Science, v. 317, p. 1866d.

Reichler, T., and Kim, J., 2008, How Well Do Coupled Models Simulate Today’s Climate?, Bulletin of the American 

Meteorological Society, v. 89, no. 3, p. 303–311.

Appendix C 63

Appendix D. Glossary

[This glossary provides definitions for terms specific to climate change or 

water resources management, as they are used in this report.]

Abrupt climate change, sometimes called rapid climate 

change, results from the nonlinearity of the climate system, 

which may lead to abrupt events. The term “abrupt” often 

refers to time scales faster than the typical time scale of the 

responsible forcing (Intergovernmental Panel on Climate 

Change, 2007a).

Climate in a narrow sense is usually defined as the average 

weather, or more rigorously, as the statistical description in 

terms of the mean and variability of relevant quantities over a 

period of time ranging from months to thousands or millions 

of years (Intergovernmental Panel on Climate Change, 2007a).

Climate change refers to a change in the state of the climate 

that can be identified (for example, by using statistical tests) 

by changes in the mean and (or) the variability of its properties 

and that persists for an extended period, typically decades 

or longer. Climate change may be due to natural internal 

processes or external forcings or to persistent anthropogenic 

changes in the composition of the atmosphere or in land use 

(Intergovernmental Panel on Climate Change, 2007a).

Climate variability refers to variations in the mean state and 

other statistics (such as standard deviations, the occurrence 

of extremes, and so forth) of the climate on all spatial and 

temporal scales beyond that of individual weather events 

(Intergovernmental Panel on Climate Change, 2007a).

Operations is used in this report to refer generally to water 

resources operations. The term “reservoir regulation” is used 

to clarify operations related to dams and reservoirs. The term 

“gate operations” is used specifically to reference the opening 

and closing of dam or reservoir gates.

Sea-level change is an increase or decrease in the mean 

level of the ocean. Sea level can change globally because 

of changes in the shape of the ocean basins, changes in the 

total mass of water, and changes in water density. Sea-level 

changes induced by changes in water density are called 

“steric.” Density changes induced by temperature changes 

only are called “thermosteric,” while density changes induced 

by salinity changes are called “halosteric” (Intergovernmental 

Panel on Climate Change, 2007b). Eustatic sea-level change 

is a change in the global average sea level brought about by an 

increase in the volume of the world ocean. Relative sea-level 

rise occurs where there is a local increase in the level of the 

ocean relative to the land, which might be due to ocean rise 

and (or) land subsidence. In areas subject to rapid land uplift, 

the relative sea level can fall (Intergovernmental Panel on 

Climate Change, 2007b).

Stationarity is the idea that while climate may exhibit 

variability, the underlying statistics that describe the climate 

(such as its mean and variance) do not change over time. 

Rather, these characteristics are stationary. This leads to an 

assumption that the past represents a reasonable proxy for 

the future. Water resource managers have traditionally relied 

on this assumption by using historical records of streamflow 

and weather variation to design and operate water resource 

systems. However, the assumption of stationarity is challenged 

by climate change, as well as by other changes to hydrologic 

systems, such as alterations of land use.

Appendix D 65
Manuscript approved for publication December 17, 2008.

Prepared by the Reston Publishing Service Center.

Edited by Marilyn A. Billone.

Photocomposition by Anna N. Glover.

For more information concerning this report, please contact

 Julie E. Kiang, U.S. Geological Survey, 415 National Center,

 Reston, VA 20192, jkiang@usgs.gov.
Brekke and others—Climate Change and Water Resources Management: A Federal Perspective—Circular 1331