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Preparing for an
Uncertain Future Climate
in the Inland Empire
Identifying Robust WaterManagement Strategies
David G. Groves, Robert J. Lempert,
Debra Knopman, Sandra H. Berry
Sponsored by the National Science Foundation
Environment, Energy, and Economic Development
A R AND I NFRASTRUCTURE , SAFE TY, AND E NVIR O N MENT PR O G R A M
The research described in this report was sponsored by the National Science Foundation
and was conducted under the auspices of the Environment, Energy, and Economic
Development Program (EEED) within RAND Infrastructure, Safety, and Environment
(ISE), in partnership with the RAND Frederick S. Pardee Center for Longer Range Global
Policy and the Future Human Condition.
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© Copyright 2008 RAND Corporation
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Preface
This documented briefing reports on the fourth in a series of workshops, which was held on
September 17, 2007, at the Chino, California, headquarters of the Inland Empire Utilities
Agency (IEUA). It presents the slides from the workshop, along with supporting information.
The primary purpose of this fourth workshop was to present follow-up analysis of water-management options for the IEUA service area to accommodate uncertain but potentially significant climate change and other management uncertainties.
The findings of the first three workshops, held in the fall of 2006, are described in a
RAND Corporation report, Presenting Uncertainty About Climate Change to Water-Resource
Managers: A Summary of Workshops with the Inland Empire Utilities Agency (Groves, Knopman,
et al., 2008).
The work reported here represents one part of a larger project, “Improving Decisions in a
Complex and Changing World,” a multiyear effort funded by the National Science Foundation
(NSF) as part of the climate-change decisionmaking under uncertainty (DMUU) component
of the agency’s human and social dynamics (HSD) priority area, that aims to improve methods
of supporting decisions under deep uncertainty. As part of this project, we are working with
water agencies in California to help them better understand how climate change might affect
their systems and what actions, if any, they need to take to address this challenge. For this
project, RAND partnered with IEUA to (1) evaluate different methods for evaluating and presenting water-management uncertainty, (2) examine how the IEUA region’s plan and enhancements would perform under different future conditions, and (3) suggest management strategies
that would be robust to uncertainties about the future.
The audience for this documented briefing includes the workshop participants from
IEUA, other water managers and civic leaders from the IEUA service area, California’s regional
and state water managers, and water managers and decisionmakers elsewhere with an interest in developing strategies for adapting to uncertain climate change and other uncertainties
affecting water supply, reliability, and quality.
The RAND Environment, Energy, and Economic Development Program
This research was conducted under the auspices of the Environment, Energy, and Economic
Development Program (EEED) within RAND Infrastructure, Safety, and Environment (ISE),
in partnership with the RAND Frederick S. Pardee Center for Longer Range Global Policy and
the Future Human Condition. The mission of ISE is to improve the development, operation,
use, and protection of society’s essential physical assets and natural resources and to enhance
iii
iv
Preparing for an Uncertain Future Climate in the Inland Empire
the related social assets of safety and security of individuals in transit and in their workplaces
and communities. The EEED research portfolio addresses environmental quality and regulation, energy resources and systems, water resources and systems, climate, natural hazards and
disasters, and economic development—both domestically and internationally. EEED research
is conducted for government, foundations, and the private sector. The mission of the Pardee
Center is to explore trends and potential developments in our world 35 to 200 years from
now, to develop and apply means of evaluating their effect on individuals and society, and to
enhance the quality of human life over that span by improving policies aimed at coping with
those trends and developments. Pardee Center projects address such areas as global warming,
genetic engineering, the Internet, nuclear-waste disposal, potable water, population growth,
and the sustainable use of natural resources.
Questions or comments about this briefing should be sent to the project leader, Robert
Lempert (Robert_Lempert@rand.org). Information about the Environment, Energy, and Economic Development Program is available online (http://www.rand.org/ise/environ), as is information about the Pardee Center (http://www.rand.org/international_programs/pardee/) and
the DMUU project (http://www.rand.org/ise/projects/improvingdecisions/). Inquiries about
EEED projects should be sent to the following address:
Michael Toman, Director
Environment, Energy, and Economic Development Program, ISE
RAND Corporation
1200 South Hayes Street
Arlington, VA 22202-5050
703-413-1100, x5189
Michael_Toman@rand.org
Inquiries about the Pardee Center and its research should be sent to this address:
Robert Lempert, Director
Frederick S. Pardee Center for Longer Range Global Policy and Future Human Condition
1776 Main Street
P.O. Box 2138
Santa Monica, CA 90407-2138
310-393-0411, x6217
Robert_Lempert@rand.org
Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
CHAPTER ONE
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
CHAPTER TWO
The Climate-Change Challenge. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
CHAPTER THREE
Evaluating Adaptive Management Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Supplies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Demands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Chino Basin Groundwater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Recycling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Shortages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Chino Basin Groundwater (Direct Use). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Desalted Groundwater. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Imported Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Groundwater Replenishment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Recycled Water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
Water Saved Through Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
CHAPTER FOUR
Comparison of Options. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Major Implications and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
CHAPTER FIVE
Survey Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
v
Summary
Water-resource managers have long strived to meet their goals of system reliability and environmental protection in the face of many uncertainties, including demographic and economic
forecasts, intrinsic weather variability, and short-term climate change induced by El Niño and
other naturally occurring cycles. Now water managers face a new uncertainty—the potential
for longer-term and more persistent climate change, which, in coming years, may significantly
affect the availability of supply and patterns of water demand. Information about the future
effects of climate change is deeply uncertain and likely to remain so for the foreseeable future.
Thus, the scientific community is debating how to most usefully characterize this important
yet uncertain information for decisionmakers.
The RAND Corporation is conducting a large, multiyear study under a grant from the
National Science Foundation (NSF) on climate-change decisionmaking under uncertainty
(see ISE, 2007). As part of that project, we are working with water agencies in California to
help them better understand how climate change might affect their systems and what actions,
if any, they need to take to address this challenge. As a key component of this effort, we have
conducted four workshops in cooperation with the Inland Empire Utilities Agency (IEUA),
whose service area overlies Southern California’s Chino Groundwater Basin. We chose to work
with IEUA because of its forward-leaning management team and articulation of strategies
intended to improve the long-term water outlook for its service area. The first three workshops
are described in detail in Groves, Knopman, et al. (2008). This document describes the analysis
developed for the fourth workshop, held in September 2007.
The workshop described here was developed to help water managers, technical staff,
elected officials, and other planners from the IEUA region consider the significance of potential
climate change relative to other key planning uncertainties and evaluate options for reducing
their vulnerability to supply shortfalls under a wide range of plausible future conditions. We
also administered surveys to the participants before and after the workshop to assess how the
participants’ views about the climate-change challenge and their possible responses changed, as
well as how well various aspects of our presentation informed them about these issues.
We used an integrated decision framework to evaluate the performance of IEUA plans
over a wide range of uncertain planning assumptions. The framework centers around a watermanagement model developed using the Water Evaluation and Planning (WEAP) modeling
environment (see SEI, undated). The WEAP model incorporates temperature and precipitation
time series reflective of historical weather and plausible ranges of climate change. Each set of
assumptions and specifications of IEUA plans is evaluated using a set of outcome measures,
including the cost of providing supply to IEUA’s retail customers and the cost of incurring
shortages.
vii
viii
Preparing for an Uncertain Future Climate in the Inland Empire
We considered nine adaptive management strategies. Each assumed that the management actions described in IEUA’s 2005 Regional Urban Water Management Plan (IEUA, 2005)
would be enacted. Some strategies included near-term commitment to implementing additional water-management strategies. Others required adaptation by implementing additional
management actions if conditions deteriorated over time. The specific augmenting actions were
chosen in consultation with IEUA staff members. They included actions that either are under
active consideration or have been identified as potential strategies for promoting water-supply
reliability and addressing climate change.
We evaluated these various plans under a wide range of planning assumptions and possible weather sequences. Following the scenario-discovery procedure outlined in Groves and
Lempert (2007) and Lempert, Groves, et al. (2006), we then use a cluster-finding algorithm
called the patient rule induction method (PRIM) (Friedman and Fisher, 1999) to find and
characterize clusters in the database of simulations that represent management conditions
under which the plans perform poorly.
In some climate-change scenarios, we found that the actions described in the 2005
Regional Urban Water Management Plan (IEUA, 2005) would lead to significant shortages and
high-cost outcomes. We identified the key risk factors leading to costs that are above a specific
cost-impact threshold—namely, declining precipitation, strong effects of climate change on
imports, and greater than anticipated declines in Chino basin percolation. When the 2005
Regional Urban Water Management Plan (the 2005 UWMP) is specified to adapt to changing conditions over time, there are fewer high-cost outcomes across the various futures, and
those futures that lead to high-cost outcomes are characterized by slightly different factors. We
evaluated other strategies as well. In general, strategies that increased the development of local
resources in the near term lead to lower overall costs, regardless of the scenario for which the
plan was evaluated. The key risk factors are different for the different plans.
We presented the ensembles of results using two types of visualizations—histograms of
performance and scatter plots that disaggregate supply-provisioning costs and shortage costs.
The scatter plots, which show the results of the individual simulations as single points on a
graph, provide more useful information but are more complex and difficult to understand.
These scatter plots revealed that not all high-cost cases can be explained by the key risk factors
identified and that some cases classified by the risk factors do not result in costs that exceed the
threshold. For the former case, one may also seek to develop an additional characterization of
results that exceeds the cost threshold but does not arise from the first set of key risk factors.
In summary, the findings suggest that the IEUA region can reduce its exposure to adverse
climate-change effects by taking advantage of the favorable economics of local resource development in the region. As long as the local resource-development activities (including increasing efficiency) are less costly than imports and precipitation trends under climate change are
flat to strongly decreasing, there is little risk in overinvestment. The results also indicate that,
if current IEUA regional leadership expects that future water managers and city planners will
respond to decreasing reliability, some actions may be deferred. However, if the region were to
implement only the 2005 UWMP now and wait before augmenting its plans, the region would
remain vulnerable to scenarios in which there are significant precipitation declines, reductions
in basin percolation, and strong reductions in imports due to climate change.
The results of the surveys that were administered before and after the workshop suggested
that the survey respondents slightly increased their support for additional near-term watermanagement actions. They reported that they felt that robust decisionmaking (RDM) was a
Summary
ix
useful methodology for presenting climate-related risks and presenting information in a useful
way that was helpful for planning. Most notably, the comparison of the before- and afterworkshop responses suggests that the RDM analysis provided information that increased the
participants’ concerns about the effect of climate change—both the likelihood of significant
effects and the severity of the effects. At the same time, water planners increased their belief
that they could mitigate or manage these effects. This is a noteworthy finding, as a primary
objective of an RDM analysis is to illustrate possible threats and then identify strategies that
can be taken to address these threats without having a clear understanding of exactly how the
future may evolve. In this case, the survey results suggest that this objective was met.
Acknowledgments
We would like to thank the National Science Foundation for the support it has provided for
this research under its grant SES-0345925. David Yates of the National Center for Atmospheric
Research continued to work with us to develop improved climate data for the IEUA region.
We are also indebted to IEUA General Manager and CEO Richard Atwater and Executive
Manager for Policy Development Martha Davis for their encouragement and substantive and
logistical support of the workshops. We would also like to thank Ryan Shaw and Andy Campbell of IEUA for their help in compiling data for the water-management model and Sarah
Olmstead, a fellow at the Frederick S. Pardee RAND Graduate School, for her assistance with
some of the modeling. This work would not have been possible without positive participation
of the 18 workshop attendees who provided us with their views on the methods and results
before, during, and after the workshop. Finally, as this work builds extensively on the work
documented in an earlier report (Groves, Knopman, et al., 2008), we extend our appreciation
once again to those recognized in the earlier report.
xi
Abbreviations
af
acre-feet
AOGCM
atmosphere-ocean general circulation model
CDF
cumulative distribution function
DMUU
decisionmaking under uncertainty
DYY
dry-year yield
EEED
Environment, Energy, and Economic Development Program
gpd
gallons per day
HSD
human and social dynamics
IEUA
Inland Empire Utilities Agency
IPCC
Intergovernmental Panel on Climate Change
ISE
RAND Infrastructure, Safety, and Environment
Metropolitan
Metropolitan Water District of Southern California
NCAR
National Center for Atmospheric Research
NSF
National Science Foundation
PRIM
patient rule induction method
PV
present value
RDM
robust decisionmaking
RUWMP
IEUA’s 2005 Regional Urban Water Management Plan
SWP
State Water Project
taf
thousand acre-feet
UWMP
urban water-management plan
WEAP
Water Evaluation and Planning
WMM
water-management model
xiii
CHAPTER ONE
Introduction
1
2
Preparing for an Uncertain Future Climate in the Inland Empire
This documented briefing reports on the fourth in a series of workshops conducted with the
Inland Empire Utilities Agency (IEUA), headquartered in Chino, California, about 40 miles
east of Los Angeles. In the previous three workshops, described in detail in Groves, Knopman,
et al. (2008), we developed a simulation model that evaluated the performance of IEUA’s plans
over a wide range of futures, including potential effects of climate change; used this simulation
to examine the vulnerabilities of IEUA’s current plans; and explored how different characterizations of uncertainty affect water managers’ understanding and willingness to act on this
information. In this fourth workshop, we built on the results of the previous three to examine a larger set of management options available to IEUA. In particular, this study compared
strategies that implement a wider range of actions now with strategies that defer some actions
to a later date, when more reliable information may become available on the effects of climate
change on the IEUA region.
We chose to work with IEUA because of its forward-leaning management team and
articulation of strategies intended to improve the long-term water outlook for its service area.
IEUA’s management team was interested in working with RAND because it wished to further
explore the adequacy of its existing plans under a wide range of possible climate conditions.
Note that this documented briefing, in some cases, presents slightly modified versions
of the slides shown to workshop participants. In particular, some slides were eliminated to
improve the flow of the briefing.
Introduction
3
For nearly all types of planning decisions related to future resource use, decisionmakers face
varying degrees of uncertainty about changes in the physical environment, land use, population dynamics, and governance. The prospect of climate change, from local and regional
to global scale, adds a further dimension of complexity to planning. Lempert, Popper, and
Bankes (2003) and Popper, Lempert, and Bankes (2005) described uncertainty as “deep” when
theory and past observations are insufficient to provide well-defined probability distributions
for important future events on which all participants in a decision can agree and that they can
accept as accurate. The effects of climate change certainly contribute such deep uncertainty to
IEUA’s planning.
RAND is conducting a large multiyear study, “Improving Decisions in a Complex and
Changing World,” under a grant from the National Science Foundation (NSF) as part of
the climate-change decisionmaking under uncertainty (DMUU) component of the agency’s
human and social dynamics (HSD) priority area. This larger project aims to conduct basic
research to improve computer-based tools that support decisionmaking under conditions of
deep uncertainty; examine the best means to represent uncertain scientific information to
individuals and groups so that they can act on it more effectively; and strengthen the scientific
foundations of robust decisionmaking (RDM), a new approach to decision support under deep
uncertainty. As part of this project, we are working with water agencies in California to help
them better understand how climate change might affect their systems and what actions, if
any, they need to take to address this challenge. For this project, RAND partnered with IEUA
to (1) evaluate different methods for evaluating and presenting water-management uncertainty,
(2) examine how the IEUA region’s plan and enhancements would perform under different
future conditions, and (3) suggest management strategies that would be robust against uncertainties about the future.
4
Preparing for an Uncertain Future Climate in the Inland Empire
This fourth workshop built on three previous workshops, held September 28, October 20, and
November 3, 2006, and described in detail in Groves, Knopman, et al. (2008). We helped
IEUA managers, technical staff, other water managers and planners from the IEUA region,
and other participants involved in California water planning to consider the significance of
potential climate change relative to a few other key uncertainties and how planners might
respond by reducing their vulnerability to supply shortfalls under various scenarios.
We prepared for the workshops by first developing a computer simulation model to estimate the performance of IEUA’s 2005 Regional Urban Water Management Plan (the 2005
UWMP) (IEUA, 2005) and potential modifications to the plan over a wide variety of scenarios. These scenarios included different future climates as well as different levels of achievement
of critical recycling and replenishment goals in the 2005 UWMP.
Future climate scenarios were developed from two approaches: extrapolations of past conditions in the IEUA service area and statistically generated temperature and precipitation time
series using results derived from a number of global-scale models that capture greenhouse
gas–driven climate change. The other uncertainties considered in the scenarios include two
key features of the 2005 UWMP: recycling and replenishment. Recycling refers to the collection, treatment, and reuse of water for outdoor landscaping and selected indoor uses (e.g., toilet
flushing). Replenishment refers to moving surface-water supplies from run-off or other sources
into the Chino Groundwater Basin, an aquifer underlying the IEUA service area that meets
more than a third of the IEUA’s current demand.
The RAND project team presented three characterizations of uncertainty and administered surveys to workshop participants before, during, and after each of the workshops to
record their views about the effectiveness and implications of the different presentations. The
first workshop characterized what is known about future climate change and then demon-
Introduction
5
strated differences in the performance of the 2005 UWMP and the plans in place prior to this,
based on assumptions that the current climate would continue into the future. In this first
workshop, the RAND team also presented climate and other uncertainties using a traditional
scenario approach, in which planners examine a small set of future conditions without assigning any likelihood or probability to their occurrence.
In the second workshop, we presented state-of-the-art probabilistic scenarios of climate
change and then used these probability distributions to estimate the expected performance of
the 2005 UWMP.
Finally, in the third workshop, we presented policy-relevant scenarios derived from one
key step in RDM, a quantitative decision-analysis approach for supporting decisions under
deep uncertainty. These scenarios, in contrast to the hand-crafted scenarios, are analytically
derived by assessing the 2005 UWMP over a very wide range of plausible future conditions,
noting those futures in which the 2005 UWMP fails to perform adequately and using statistical approaches to identify those few key factors most important in predicting whether a future
scenario might cause the 2005 UWMP to fail. Unlike the probabilistic scenarios, probabilities
are not assigned to these scenarios. We intended these policy-relevant scenarios to help IEUA
consider ways in which it might augment the RUWMP to make it more robust against potentially stressful future conditions.
The traditional scenario analysis demonstrated that current plans will perform well if
the future climate is benign—that is, wetter than historic conditions—even with incomplete
implementation of IEUA’s recycling and replenishment goals. If the future climate is adverse—
that is, drier and warmer than historic conditions—then one option to ensure sufficient supply
to meet demand would be for IEUA to fully meet its recycling and replenishment goals, as well
as invest in more efficiency, and possibly allow more groundwater replenishment with recycledwater supplies.
The probability-weighted scenarios suggest that, if one believed the best-available probabilistic information about both the future climate and the IEUA region’s ability to meet the
agency’s recycling and replenishment goals, then the current RUWMP would ensure that the
chance of a shortage over the next 25 years will not exceed 7 percent.
The policy-relevant scenarios derived from the RDM method identified two sets of
conditions most threatening to the success of IEUA region’s water-management plans—a
Dry, Flashy, Low-Recycling scenario and a Wet, Effective-Recycling scenario. Under the Dry,
Flashy, Low-Recycling scenario, the current plan fails to prevent frequent and significant shortages. These shortages would impose significant economic and social costs to water users. Under
the Wet, Effective-Recycling scenario, IEUA’s RUWMP generates significantly more available
water supply than the agency needs to meet demand, could indicate overinvestment in supply
enhancements, and could lead to higher costs than necessary to water users to pay for the
unneeded water investments. Note that these policy-relevant scenarios highlight two fundamentally different types of risks: the risk arising from physical shortage of supplies and the risk
arising from overinvestment when supplies are adequate.
In the specific case of IEUA, there are likely other benefits of supply enhancements (e.g.,
less dependency on imported supplies and the ability to sell additional supply to other regions)
that we did not include in this first phase of the analysis that would likely reduce or even eliminate the negative impact of this scenario. The analysis developed for the workshop presented
here reflects the benefit of displacing expensive imports with less expensive local resources or
through demand reductions.
6
Preparing for an Uncertain Future Climate in the Inland Empire
Additional efficiency and groundwater-management strategies improve performance
under the Dry, Flashy, Low-Recycling scenario but may also generate excess surpluses if this
adverse scenario does not come to pass. The analysis, described in Groves, Knopman, et al.
(2008), suggested that, if managers from the IEUA region believe that future conditions are
more than 25 percent likely to be consistent with the Dry, Flashy, Low-Recycling scenario,
then investments in greater efficiency or more use of recycled water for groundwater replenishment than what is specified by the RUWMP would be prudent.
Regarding the different presentations of uncertainty, the traditional scenarios provided a
simple description of a range of future conditions relevant to IEUA. But many such scenario
analyses fall short of decisionmakers’ needs, because the choice of scenarios can appear arbitrary and there is not a direct way to infer policy choices from the scenarios. Probabilistic scenarios can provide a concise ranking of the desirability of alternative IEUA plans but can lead
to errors of omission in planning by downplaying the potential importance of possible futures
that deviate from “most likely” conditions. Generating policy-relevant scenarios was found to
provide useful information but can also prove to be a nontrivial analytical exercise and one
more complicated to explain to decisionmakers than the other approaches are.
Introduction
7
Following the fall 2006 workshops, IEUA discussed with us ways to improve the representation of the management options that the IEUA service area faced and evaluate scenarios. As a
result, we decided to improve the model, develop a revised RDM analysis, and present findings
in a fourth workshop. In particular, we expanded the model to provide the capacity to develop
water-management plans that can adapt to changing conditions over time. We also worked
with IEUA to include monetary estimates of providing water supplies to the region’s end users
and estimates of costs of incurring shortages. These cost estimates were generated for each
model simulation. We could thus better compare performance of the various management
plans across specific future conditions. Finally, with researchers from the National Center for
Atmospheric Research (NCAR), we developed an improved set of monthly weather sequences
(temperature, precipitation, and wind speed) reflective of plausible climate change.
Using this improved model, the RAND team addressed uncertainty and identified promising water-management plans for the IEUA region. In contrast to the first three exercises, this
workshop used only RDM methods and did not compare alternative means of characterizing
the uncertainty. In response to the third workshop’s survey results, we attempted to improve
the presentation of the RDM-derived results.
CHAPTER TWO
The Climate-Change Challenge
This documented briefing is organized in six parts. The preceding chapter set the stage for the
fourth workshop by reviewing the design and findings of the first three workshops. This second
chapter describes the global and more local-scale challenge presented by changing climatic
conditions, serving as a review of a more extended discussion on climate change presented in
the earlier workshops. The third chapter describes the nature of the adaptation decision that
water managers face: Should they enhance the RUWMP now, or should they wait until some
point in the future when they may know more about climate trends? The fourth chapter demonstrates the implications of different strategic options under a wide range of possible futures.
In the fifth chapter, we summarize the results of the survey administered to participants before
and after the workshop, which was intended to help us better understand the influence of the
analytical approach on perceptions and preferences for changes in current plans. An appendix,
available online, presents the surveys administered to the participants before and after the presentation (Groves, Lempert, et al., 2008).
9
10
Preparing for an Uncertain Future Climate in the Inland Empire
An expanding body of scientific evidence suggests that the historic climate records that IEUA
currently uses to support its planning will no longer prove a reliable guide to the future (Solomon, 2007). Temperatures in the region will very likely increase, and precipitation may increase
or decrease. These climate trends could have significant effects on the IEUA region, increasing
demand for irrigation; generating more intense and, possibly, less frequent storms; diminishing
the Sierra snow pack from which the region draws much of its imported water; and decreasing
the local supplies available for recharging groundwater (California Climate Change Center and
California Energy Commission, 2006).
For some geophysical parameters, such as temperature, the general trends are clear. For
others, such as precipitation or storm frequency, they are not. For both, the details at the geographic scale generally required for IEUA planning remain deeply uncertain. Temperature and
precipitation forecasts derive from atmosphere-ocean general circulation models (AOGCMs).
More than 20 such models exist worldwide, and most give quantitatively different forecasts for
Southern California (Tebaldi, 2006). In addition, none of these models gives a satisfactory representation of the potential for abrupt climate changes. The possibility for such rapid change
has increasingly engaged the scientific community as it has increasingly observed changes in
the earth’s climate system occurring more quickly than expected (Hansen et al., 2007).
The Climate-Change Challenge
11
The Intergovernmental Panel on Climate Change (IPCC) fourth assessment report provided
estimates of the scientific community’s confidence in many different types of climate projections, largely derived from these AOGCMs (Solomon, 2007). For instance, the report indicated
that scientists give a probability of higher than 90 percent that the earth’s atmosphere will continue to warm during the 21st century. Scientists give a smaller but still significant probability
of 66 percent or greater that the areas affected by drought will increase in the future.
While the IPCC does not directly address the issue of uncertainty about the structure of
climate models or missing phenomenology that might significantly lessen or worsen the severity of its projections (Oppenheimer et al., 2007), these probability estimates provide a rough
gauge of scientists’ confidence that their models correctly project some of the factors that might
most affect IEUA.
12
Preparing for an Uncertain Future Climate in the Inland Empire
Assuming that the AOGCMs are valid representations of future climate dynamics, one can
look at the range of predicted temperature and precipitation changes over Southern California.
According to 21 AOGCMs, the likely range (± one standard deviation of the mean projected
increase) of average summertime temperature increase is projected to be between 0.1 degrees
Celsius and 2.1 degrees Celsius. The likely range of average wintertime precipitation trends is
between a 19 percent decrease and an 8 percent increase (Tebaldi, 2006).
The Climate-Change Challenge
13
Water planners in the IEUA service area also face other deep uncertainties that may affect
the future performance of their system. The reliability of imported supplies from the State
Water Project (SWP) via the Metropolitan Water District of Southern California (Metropolitan) depends on difficult-to-predict legal decisions and potentially catastrophic events. For
instance, in December 2007, a U.S. District Court decision restricted the amount of water that
can be pumped from the San Francisco Bay Delta in order to protect the delta smelt, a threatened species (NRDC v. Kempthorne, 2007). Because of this decision, pumping in 2008 will be
reduced by up to 30 percent (DWR, 2007). As another example, an earthquake could cause
catastrophic levee failures in the delta, resulting in the elimination or significant decrease in
water exports to Southern California for months to years (Lund et al., 2007).
IEUA also faces uncertainty about its future water needs. Projections of future water
demand can be developed by estimating changes in the number of water users or activities and
changes in the amount of water used by each user or activity. Any such estimates, however,
are very uncertain. Although it is widely expected that rapid urbanization of the IEUA service
area will continue through about 2030 and lead to increases in the number of households and
commercial businesses and thus the number of water users (Husing, 2006), economic factors
largely unrelated to water management—such as the recent mortgage crisis and rise in mortgage defaults—can occur unexpectedly and have a major effect on development patterns. Perhousehold water demands are also expected to decline, but by how much is difficult to predict.
Trends in new residential developments in the IEUA service area suggest significantly lower
water-use rates (180 gallons per day [gpd] versus 270 gpd) than are typically considered in
water-demand forecasts (Davis, 2007).
Acknowledging these uncertainties, the California Water Plan Update 2005 (DWR,
2005) developed three scenarios of future water demand in which the growth of the number
14
Preparing for an Uncertain Future Climate in the Inland Empire
of households and the increase in naturally occurring conservation (or declines in water-use
intensity due to the natural replacement and modernization of water-using devices) varied by
significant amounts. Wilkinson and Groves (2006) expanded on the water-plan analysis and
looked at different demand projections for Southern California.
The effectiveness of water-management programs and initiatives in the region is also
uncertain. In our first workshop, in 2006, we surveyed the 31 participants about their beliefs
about the region achieving its ambitious recycling goals. Only 67 percent believed that the
goals would be achieved by 2025 (Groves, Knopman, et al., 2008). A variety of reasons were
discussed in subsequent workshops and conversations with IEUA staff members about the reasons for this. Significant factors included the continued support of the cities to purchase and
distribute recycled water to large water users, the ability to raise the required state and federal
funding to partially fund the capital improvements necessary to distribute recycled-water supplies throughout the service area, and the sustained interest of the region’s cities and agencies
to continue to cooperate and plan effectively.
The Climate-Change Challenge
15
Decisionmakers often find it difficult to manage such uncertainties. Their training, experience,
and analytic tools derive from an analytic tradition that requires one to characterize uncertainties with a single set of well-defined probability-density functions to then rank the desirability
of alternative decision options. Such predict-then-act approaches can be extraordinarily useful
for many decisions but can prove inadequate under conditions of deep uncertainty. When
decisionmakers attempt to apply predict-then-act approaches under such conditions, they may
face pressures to underestimate the uncertainties, find it hard to make decisions because competing uncertainty estimates suggest very different conclusions, and leave themselves vulnerable to surprise by neglecting valuable information that is not useful for improving probabilistic
forecasts (Lempert, Nakicenovic, et al., 2004; Lempert, Popper, and Bankes, 2003).
CHAPTER THREE
Evaluating Adaptive Management Strategies
In this chapter, we first describe the nature of the adaptation decision that IEUA managers—
and water managers throughout the western United States and elsewhere—face as they consider their systems’ vulnerability to climate change and other uncertainties that may diminish system reliability or add to costs. Next, we describe the four components of the modeling
framework to evaluate both nonadaptive and adaptive management strategies in the IEUA
service area. The components of the modeling framework are
t
t
t
t
the simulation model used
the specific management strategies evaluated
the uncertainties considered as a basis of the scenarios
the metrics used to evaluate the performance of each management strategy.
17
18
Preparing for an Uncertain Future Climate in the Inland Empire
Faced with uncertainty, decisionmakers often must choose between early action and a waitand-see approach. For instance, the skipper of the trailing boat on this slide faces a choice: Tack
now and stay close behind the leaders, or hold course, diverge from the others, and perhaps
gain the lead with a more favorable wind. Each choice offers uncertain costs and benefits.
In this chapter, we describe an analytical approach to assist IEUA managers in assessing
the costs and benefits of their alternative early-action and wait-and-see options.
Evaluating Adaptive Management Strategies
19
As a base for our analysis, we considered the IEUA’s 2005 Regional Urban Water Management Plan (IEUA, 2005). As described in Groves, Knopman, et al. (2008), the plan’s primary approach to addressing new water-supply needs includes increasing the use of the Chino
Groundwater Basin by about 75 percent through increased surface-water replenishment (sometimes referred to as replenishment of the groundwater) and developing an extensive recycled
water system to deliver up to 69,000 acre-feet (af) of supply by 2025.
20
Preparing for an Uncertain Future Climate in the Inland Empire
In addition to implementation of the various water-management strategies described in the
RUWMP, the IEUA region is both pursuing and considering other options.
IEUA anticipates continued reductions in the intensity of water use in new construction
as the region’s cities develop new landscape ordinances by 2010 to comply with California
Assembly Bill 1881 (signed by the governor in September 2006). Landscape ordinances have
the potential to dramatically limit outdoor water use through the restriction of landscaped
area and mandates to use water-efficient irrigation techniques and practices. IEUA could also
achieve greater demand reductions through the expansion of programs designed to retrofit
existing homes and commercial buildings with water-saving devices, such as upgraded toilets
and urinals (Gleick et al., 2003). Finally, the region could follow the lead of such cities as Las
Vegas, which has begun to pay water users to remove highly water-using landscape (such as
turf).
IEUA is also considering a more aggressive roll-out of its recycled-water–use system. Specifically, in the summer of 2007, IEUA developed a business plan to increase the annual available supply to 49 taf by 2010, which represents a speed-up of the RUWMP expansion schedule
by five years.
Finally, there are several options for increasing use of the Chino Groundwater Basin
supply. First, IEUA is involved in negotiations with Metropolitan to increase the size of the
dry-year yield (DYY) program from 33 taf annual yield to 50 taf annual yield. The DYY program enables IEUA to forgo the use of groundwater during periods of increased availability of
imported supplies and then increase groundwater use during periods of low imported-supply
availability. Next, the Chino Basin Watermaster is working with the California Department of
Health and Safety to change the Chino Groundwater Basin replenishment-blending requirement to allow a higher percentage of recycled water to be percolated into the groundwater
Evaluating Adaptive Management Strategies
21
basin. Currently, only about one-third of the replenishment water may be recycled water; the
rest must be made up of local storm water or imported surface supplies. It may be possible to
increase this percentage from 33 percent to 50 percent. Another option for increasing the effective yield of the Chino Groundwater Basin is to increase the capture of storm water. Effective
yield is the amount of water that can be withdrawn annually from a groundwater basin without causing significant drawdown of overall volume in storage. Increased storm-water capture
would allow for more replenishment of groundwater, including increased capture of recycled
water used in outdoor landscaping.
22
Preparing for an Uncertain Future Climate in the Inland Empire
Long-term water management is inherently an adaptive process. Water planners typically
review their long-term plans periodically and adjust them in response to changing and unpredictable conditions. When evaluating different policy or management choices, planners commonly compare how fixed actions will perform in the future and thus determine which actions
to commit to implementing in the near term. This approach can work well when the future
is predictable. But under deep uncertainty, conditions are unlikely to play out as expected,
and, thus, planners need to make adjustments to their earlier strategies. An analysis that fails
to consider how decisionmakers will attempt to adjust to changing conditions can exaggerate
the poor performance of previously established policies or neglect opportunities for near-term
actions that can have significant and beneficial effects on future choices.
In the context of IEUA, we modeled adaptive strategies to evaluate which actions should
be undertaken now and which can be put off for possible later action. We describe the details
of the model’s implementation of these actions in the remainder of this chapter.
Evaluating Adaptive Management Strategies
23
The RAND team developed an integrated decisionmaking framework to evaluate the performance of IEUA plans over a range of uncertain planning assumptions. The framework centers
on a water-management model (WMM) developed using the Water Evaluation and Planning
(WEAP) modeling environment (see SEI, undated). Each set of assumptions and specifications of IEUA plans is evaluated using a set of outcome measures. Each of these components
is described next.
24
Preparing for an Uncertain Future Climate in the Inland Empire
The WEAP simulation model evaluates the performance of IEUA plans under specific scenarios,
each of which reflects plausible trends in climate change and other planning assumptions.
Evaluating Adaptive Management Strategies
25
The WEAP model simulates water supply and demand using a stylized representation of the
system’s major water flows on a monthly time scale from 2005 to 2040. Building on the version used in our previous workshops (Groves, Knopman, et al., 2008), the model represents
IEUA’s supply and demand relationships by using a set of nodes corresponding to discrete
water-management elements, such as catchments, indoor-demand sectors, surface supplies,
and groundwater basins. Rivers, conveyance facilities, and other pathways (such as percolation
flows) link these elements together. Time series of monthly weather parameters are used to
drive the system’s hydrology, using a soil-moisture model. The model specification was based
on IEUA’s RUWMP, Chino Basin Optimum Management Program (Wildermuth Environmental, Inc., 1999), and other documents provided by IEUA, such as Husing (2006), and the
model continues to be refined and developed as a part of this ongoing project. This slide shows
the basic model schematic.
The overall model was calibrated and validated by comparing (1) the results for the simulation that corresponds to historical temperature and precipitation trends and management
conditions and actions described in the RUWMP (e.g., the 2005 UWMP) with (2) the projections of average water demand and supply provided by the RUWMP. Results from the calibration, along with additional model details, are provided in Groves, Knopman, et al. (2008).
Key features of the WMM are described in the following sections.
Supplies
Major water sources to the region included the following:
26
Preparing for an Uncertain Future Climate in the Inland Empire
t precipitation over catchments: drives local supplies, Chino Groundwater Basin replenishment, and storm water for replenishment
t imports from Metropolitan: direct use (both “commitment” supplies based on existing
agreements and additional amounts as needed and available) and replenishment (both for
direct replenishment and in-lieu replenishment via the DYY program)
t non–Chino basin groundwater: fixed representation of non–Chino Groundwater Basin
use by IEUA members.
Demands
Major water demands include the following:
t Urban indoor: Household demand is based on projections of the number of households
and per-household water use. Note that new development is specified to use less water
than existing houses do. Indoor commercial and industrial demand is based on projections of the number of employees and per-employee water use.
t Urban outdoor: Outdoor demand is estimated by WEAP’s rainfall-runoff model, which
considers (1) the projected area of urban development, (2) the fraction of urban land that
is irrigated landscaping, (3) monthly temperature and precipitation, and (4) parameters
that define the irrigation needs of landscaping and infiltration of precipitation and irrigation out of the root zone (Groves, Knopman, et al., 2008; Yates, Purkey, et al., 2005;
Yates, Sieber, et al., 2005).
t Agricultural demand: Demand is assumed to come from irrigation based on similar
parameters to those used to model urban outdoor demand. The WMM assumes a significant decline in agricultural area and water demand consistent with the 2005 UWMP.
Chino Basin Groundwater
The WMM also simulates Chino Groundwater Basin inflow and outflow. The WMM shows
direct-use groundwater, desalted groundwater, the Chino Groundwater Basin replenishment
program (using imported Metropolitan, recycled, and storm water), and the DYY program
(modeled as a separate groundwater basin).
Recycling
The WMM reflects IEUA’s recycling program for both direct use and Chino Groundwater
Basin replenishment. Recycled supply comes from treated wastewater from direct indoor water
use. However, the amount of available recycled supply is specified exogenously in the model;
that is, it is not directly linked to treated wastewater from indoor use. This simplification is
immaterial, as the total amount of recycled supply made available is always less than the direct
indoor water use.
Evaluating Adaptive Management Strategies
27
The WEAP model incorporates temperature and precipitation time series reflective of historical weather and plausible ranges of climate change. Historical weather sequences were developed using historical daily observations of temperature, precipitation, and dew-point temperature from 1980 to 2003 and monthly climatological wind-speed data for the region. Data were
obtained for three locations representative of IEUA’s agricultural region, urban region, and
upper watershed from the Daymet U.S. Data Center (NTSG, undated). We supplemented this
information with monthly climatological wind-speed data for the region.
Claudia Tebaldi, a researcher at NCAR, provided us with probabilistic temperature and
precipitation forecasts for the region of Southern California that covered the IEUA service
area. These forecasts were based on 21 AOGCMs and a global carbon-emission scenario identified as A1B in the IPCC Special Report on Emissions Scenarios (Nakicenovic, 2000). Tebaldi’s
methodology (Tebaldi, Mearns, et al., 2004; Tebaldi, Smith, et al., 2005) uses a fully Bayesian
approach to combine the predictions of the individual AOGCM forecasts into a single probabilistic forecast using the criteria of minimizing bias and maximizing convergence (i.e., the reliability ensemble average criteria from Giorgi and Mearns, 2002). The plots in this slide show
the probability-density functions for summertime temperature and wintertime precipitation.
The numbers on the curves represent the values corresponding to nine deciles of the corresponding cumulative distribution function (see Groves, Knopman, et al., 2008). The triangles
indicate the actual trends that each AOGCM forecast reported that were used as the basis for
the probability-density function.
28
Preparing for an Uncertain Future Climate in the Inland Empire
AOGCMs generate forecasts at scales consistent with the 500 km 2 “cells” of their model grids,
which are considerably larger than the IEUA service area. Thus, the Tebaldi estimates were
at too coarse a scale to be useful in the modeling of IEUA’s hydrology. For this reason, we
needed to add another step in generating climate scenarios for IEUA, through a process known
as “down-scaling,” bringing regional-scale estimates down to the more local scale of IEUA.
Another collaborator, David Yates of NCAR, applied a climate-downscaling procedure called
K-nn (Yates, Gangopadhyay, et al., 2003), to project the regional-scale climate changes on the
local weather patterns as characterized by the historical data. The K-nn procedure resamples
historical daily weather data so that the resulting sequences retain the same basic statistical
character of the historical data but include a specified exogenous trend. For this analysis, the
K-nn method was used to create 25 realizations for each of the nine deciles of precipitation and
temperature change, producing a total of 450 time series.
The Bayesian climate-ensemble method does not provide information about the relationship between temperature and precipitation trends (known as covariance). A simple regression
of historical annual temperature on precipitation suggests a statistically insignificant negative
relationship. Looking forward, the evidence is mixed. Most climate models suggest that strong
warming will deepen persistent drought in the subtropical region—IEUA is at the northern
edge of this boundary. This effect suggests a strong negative relationship between temperature and precipitation. However, if El Niño conditions are disproportionately strengthened as
warming trends continue, then the region could experience more warm and tropical storms,
which would be consistent with a positive relationship. So we assumed that the driest (wettest)
precipitation decile corresponds to the warmest (coolest) temperature decile. This assumption
is a conservative assumption, in that it will lead to the most inclusive set of plausible climate
scenarios as a basis of testing the water-management plans of the IEUA region.
Evaluating Adaptive Management Strategies
29
The K-nn resampling method does not guarantee that sequences with the appropriate
precipitation trend will correspond to the desired temperature trend. We therefore adjusted the
monthly temperature trends (using a growing linear additive factor) to meet the 2030-appropriate trend specified by the cumulative distribution function (CDF).
The figures on this slide show three specific temperature (top) and precipitation (bottom)
sequences drawn from the ensemble of series. The red sequence reflects one that exhibits strong
warming and drying trends. The green reflects a moderate warming trend and no precipitation
trend. Finally, the blue line reflects only slight warming and a slight precipitation increase.
30
Preparing for an Uncertain Future Climate in the Inland Empire
The monthly temperature and precipitation time series affect estimates of outdoor demand, via
a soil-moisture model. As described in Groves, Knopman, et al. (2008), the soil-moisture model
estimates the irrigation requirements and the return flow for any precipitation and applied irrigation water (e.g., evapotranspiration, surface runoff, subsurface runoff, deep percolation). For
the urban catchment and agricultural catchment, the following parameters are specified: irrigated land area, crop coefficient, soil water capacity, leaf-area index (parameter that controls
the surface runoff response), root-zone conductivity, preferred flow direction (parameter that
specifies the portion of water that infiltrates past the root-zone flows horizontally to adjacent
rivers or vertically to the underlying aquifer), lower and upper irrigation threshold (parameters
that control how frequently irrigation is used), and the initial soil-moisture amount.
This slide shows the historical annual precipitation from 1980 to 2003 projected forward
(applying 1980 to 2005, 1981 to 2006, and so on) and corresponding urban outdoor and
agricultural water demand. Note that this precipitation sequence is derived from the same
historical sequence shown in the previous slide. The decline in agricultural water demand and
corresponding increase in urban outdoor water demand are due to land conversion from agricultural to urban uses. The interannual variability in demand is directly related to annual precipitation and temperature (not shown). During wet years, demand is low. During dry years,
demand is higher.
Evaluating Adaptive Management Strategies
31
The WMM simulates annual deliveries of the California SWP system as delivered by Metropolitan. The anticipated annual available supply is specified by the water-management strategy. For example, the 2005 UWMP projects a supply of 60.2 taf in 2005 to increase to 82.5
taf by 2025. The actual delivered supply in any simulation is affected by (1) the previous
October–March precipitation totals for the IUEA region (dry years lead to reductions in Metropolitan imports as specified in the 2005 UWMP, and wet years permit additional deliveries);
(2) the extent of the climate-change signal (as defined by the climate decile, explained below);
and (3) an uncertain model parameter that specifies how much the Metropolitan supplies are
reduced under climate change. Note that this scheme assumes a perfect correlation between
precipitation in the IEUA service area and that in Northern California—the source area of
the SWP. An improved representation would relax this assumption. The default sensitivity
of Metropolitan supplies to climate change ranges between a 10 percent and 50 percent reduction by 2030 (depending on the severity of the climate-change signal—treated as an exogenous
parameter in the WMM). The top line in the bottom graph shows how annual deliveries of
imports are affected under historical weather conditions. Note that two dry years (2024 and
2027) trigger dry-year import reductions (by an amount specified in the 2005 UWMP).
Local supplies, primarily surface runoff from the San Gabriel Mountains, comprise a
relatively small portion (about 5 percent) of the total IEUA supply. This supply responds to the
weather pattern specified for the Upper Watershed. The model is tuned so that, on average,
18.7 taf of local supply is available. During dry years, this amount decreases approximately
proportionally to the percentage decrease in precipitation during those years. The lower line in
the bottom graph shows the local supply response to a simulation using historical weather.
32
Preparing for an Uncertain Future Climate in the Inland Empire
The WMM adjusts the Chino basin “safe yield” to achieve a balance between the inflows and
outflows. Safe yield is the amount of water than can be withdrawn from a groundwater basin
over several years without exceeding its ability to be replenished naturally during that time
and is based on the Peace 1 Agreement described in Wildermuth Environmental (1999). The
inflows to the Chino basin are percolation from the urban outdoor, agriculture, and native
vegetation catchments and replenishment from local storm water, recycled water, and imports.
The outflows include extractions of low-quality water that is desalted prior to delivery to end
users in the region and direct-use pumping by IEUA members and a few outside agencies.
At 2010 and every five years thereafter, the WMM evaluates the amount of water in
storage in the Chino basin (at the beginning of the simulation, storage is 5 million af). If
the storage has dropped below this initial level, then the safe yield is reduced by one-half the
amount of the previous deficit for the next five years. The safe yield is then recalibrated to
reflect the new groundwater condition.
Evaluating Adaptive Management Strategies
33
For the fourth workshop, we used the WMM to evaluate nine specific management plans for
the IEUA region. The first five plans are nonadaptive, meaning that the plans do not change
over time (though actions may change as specified by the plan). The next four are adaptive,
meaning that they update as described in the slide.
The first plan, UWMP forever, is designed to represent implementation of the RUWMP
without any updates over time. This is also the base strategy evaluated for the first three workshops, as described in Groves, Knopman, et al. (2008).
The UWMP + DYY with recycling plan includes two additional management actions:1
(1) increase the size of the DYY program to 50 taf yield by 2010 and 75 taf yield by 2020, and
(2) expand the recycled-water system to deliver 49 taf per year of supply to end users by 2010.
This represents a speed-up of the expansion schedule in the 2005 UWMP by five years.
The UWMP + replenishment plan includes two additional management actions to the
UWMP forever plan: (1) increase the allowable recycled-water content of Chino Groundwater
Basin replenishment water from 33 percent to 50 percent, and (2) increase storm-water capture
from 12 taf to 35 taf (an increase of 23 taf) by 2020.
The UWMP + efficiency plan increases the efficiency targets of the UWMP forever plan
by 10 percent for indoor efficiency and 20 percent for outdoor efficiency by 2030.
The UWMP + all enhancements plan includes all the UWMP forever actions plus the
additional actions included in the other three nonadaptive management plans.
1
When referring to plans, a plus sign (+) indicates that the change is implemented now; with indicates that the change will
be implemented in the future.
34
Preparing for an Uncertain Future Climate in the Inland Empire
The next four plans (UWMP with updates, UWMP + DYY and recycling with updates,
UWMP + replenishment with updates, and UWMP + efficiency with updates) are similar to
the first four plans except that they are adaptive.
Referring back to slide 16, we can now explain how the WMM handles adaptive strategies. The first step in developing adaptive strategies is to determine whether any near-term decisions should be made to augment the RUWMP. If the choice is no, then only the RUWMP
actions are implemented (upper branch of diagram). In 2015 and every five years thereafter, the
WMM then evaluates whether supply has been sufficient to meet demand over the preceding
five years. If the average surplus is 10 taf lower than the anticipated surplus in the RUWMP,
then adaptivity is triggered within the model. If the average surplus is sufficient, then implementation of the RUWMP action continues as planned. Alternatively, the IEUA region may
choose to implement some additional action now and then evaluate it every five years as before
(lower branch of diagram in slide 16).
If adaptivity is triggered, then the model specifies that water-use efficiency will increase
and that facilities to capture storm water for groundwater replenishment will be developed.
The implementation rate is set to the rate it would be if the policy were enacted in the first
period and completed by the end of the simulation. Thus, if adaptivity is triggered late in the
simulation period, these actions will not be fully implemented by the end of the simulation.
The adaptive strategies remain in effect even if conditions improve. We make this assumption
because, in general, it is likely that it will be financially beneficial to continue these actions
once they have been initiated.
In many jurisdictions, conditions could change such that development of local resources
would lead to growing water surpluses. In these cases, adaptivity would trigger a scale-back
of actions. In the IEUA case, however, preliminary analysis suggested that the RUWMP
would unlikely be viewed as too aggressive because any local resource development would
enable the region to reduce the use of its highest-cost water source—imports supplied by
Metropolitan. More discussion of the costs of the various water-management actions can be
found on slide 29.
Evaluating Adaptive Management Strategies
35
The WMM evaluates each plan under specific assumptions. For this workshop, we considered the eight assumptions listed in this slide. The ranges for these assumptions were derived
from a variety of sources. The precipitation- and temperature-trend ranges reflect the ranges of
trends specified in the weather-sequence generation procedure described in slide 21. The recycling-delay and replenishment-achievement ranges were derived from the participant survey
results from the first workshop, as described in Groves, Knopman, et al. (2008). The range
of new-development water intensity is derived from information received from Davis (2007).
The effect of climate change on Metropolitan supplies derives from an internal review of several recent modeling studies that estimated the reliability of SWP deliveries under different
climate-change scenarios (DWR, 2006; Vicuña, 2006; Zhu, Jenkins, and Lund, 2006). The
range of basinwide percolation changes was specified by the authors and chosen to represent a
modest range of values for purposes of the scenario analysis. The range of projected increase in
the costs of imported supplies were specified by varying the assumed escalation rate (4.5 percent) used by Sunding (2007). Finally, the escalation in costs of improving efficiency is set to
range between one-half and double the nominal increase of 4.5 percent per year.
36
Preparing for an Uncertain Future Climate in the Inland Empire
The WMM produces a wide variety of outputs. In the first three workshops, we considered
the probability of a shortage in any particular year and the average annual surplus as the two
key metrics. We evaluated the performance of a plan played out in a particular future (set of
planning assumptions). Although these metrics can be informative—clearly, plans that lead
to few shortages are preferred over those that lead to large shortages—it is not clear how large
surpluses ought to be before they are viewed as excessive. Based on the workshops and subsequent discussions with IEUA planners, it was determined that a better metric would be the
discounted economic cost of providing water supplies and coping with any shortages under
each future, as simulated by the WMM.
For the fourth workshop, we evaluated each future by annual outcome measures related
to demand, supply, cost of provisioning supply, and financial effect of shortages from 2005 to
2040. We summarized the outputs by evaluating the present value (PV) of the costs of providing supply from the perspective of the region’s water agencies to the end users and of incurring
shortages.
Evaluating Adaptive Management Strategies
37
As shown in this slide, the total cost for water in each simulation is the sum of the PV of the
annual water-supply cost and the PV of the annual water-shortage cost. The water-supply cost
is the volume of water used multiplied by its average cost. The water-shortage cost is the volume
of unmet supply multiplied by the cost of shortages. For the analysis presented here, we use
a discount rate of 4.5 percent (the current risk-free long-term interest rate) to match that of a
recent study regarding the net benefits of alternative Chino basin management programs by
Sunding (2007).
38
Preparing for an Uncertain Future Climate in the Inland Empire
We worked with IEUA staff to estimate the cost of provisioning supply to end users. The
model considers levelized costs from the perspective of the region’s water agencies. Levelized
cost is the total cost to an agency of providing water divided by the total amount of water provided to end users. The use of levelized costs assumes constant marginal costs within the range
of use across the simulations. The costs of not having available supplies to provide are included
as costs of shortages. The costs of reducing water demand through new efficiency programs or
mandates are also specified. Each cost increases over time at a specific rate.
This slide presents the levelized cost in dollars per af for 2005 (dark bars) and 2015 (light
bars) of shortages (orange bar), of each supply (green bars), and of demand reduction (blue
bar) for base-case cost assumptions. Note that the cost increases for the different supplies are
not uniform. Costs of imported supplies, in particular, increase at a much faster rate than
the others. By 2015, the cost of tier 2 imported supply exceeds all others, including desalted
groundwater.
Next, we describe the basis for each estimate of current costs and an escalation rate. Note
that the WEAP model does not currently enable an analysis using marginal costs.
Shortages
The effective cost of incurring a supply shortage in the IEUA region is roughly equivalent to
the recently established rate set by Metropolitan for delivering supply to an agency beyond its
allocated amount during the current drought conditions. This rate is set to be twice the treated
Evaluating Adaptive Management Strategies
39
tier 2 water rate, or roughly $1,200 per af.2 This effective cost is projected to rise 4.5 percent
per year.
Chino Basin Groundwater (Direct Use)
We used an estimate of the cost of pumping Chino basin groundwater for direct use by municipalities and agriculture to be about $130 per af (Campbell, 2007). This cost also includes facility maintenance and escalates at 4.5 percent per year.
Desalted Groundwater
The cost of water supplied by the Chino basin desalters is $550 per af, which includes costs
of filtration of $50 per af, according to the Chino Basin Desalter Authority (Atwater, 2007).
These costs are expected to rise by about 4.5 percent per year.
Imported Supply
Costs of imported supply (provided by Metropolitan) are based on current 2008 importedwater rates ($341 per af for tier 1 and $437 per af for tier 2). The cost of these supplies is held
constant until 2008, at which point they rise about $100 per af per year, about the rate increase
expected in Metropolitan’s forthcoming updated long-range financial plan (Atwater, 2007):
t 2009: $450 per af (tier 1) and $560 per af (tier 2)
t 2010: $550 per af (tier 1) and $670 per af (tier 2)
t 2011: $650 per af (tier 1) and $785 per af (tier 2).
After 2011, costs rise between 2.5 percent and 8 percent per year, as specified by an uncertain parameter in the model.
Groundwater Replenishment
Costs of replenishment are disaggregated into costs for the replenishment facilities, the replenishment water, and the cost of spreading. Costs for the facilities are estimated to be about
$94 per af (Campbell, 2007). Costs for spreading range from $15 to $50 per af (depending
on hydrology); we used $30 per af as an average cost. Costs for replenishment supplies are as
follows:
t imported by Metropolitan: $238 per af plus $13 per af IEUA administrative fee
t recycled: $63 per af
t local storm water: $0 per af.
2
Metropolitan charges its customers two different rates for direct-use imported supply. The tier 1 rate applies to a specific
amount of water delivered (59.7 taf per year for IEUA). Deliveries above the tier 1 amount are charged a higher tier 2 rate.
40
Preparing for an Uncertain Future Climate in the Inland Empire
Recycled Water
The cost of recycled supply is specified to be the sales price of the water by IEUA to its member
agencies, which then distribute it to end users: $60 per af now, increasing to $76 per af (2012)
and $153 per af (2036) (Shaw, 2007). This relatively low cost for recycled water reflects significant state and federal cost sharing and grants for capital costs.
Water Saved Through Efficiency
Formal estimates for the cost of saving water through efficiency in the region were not available. We worked with IEUA staff members to develop estimates that were consistent with the
other cost estimates and also reflective of the costs that the region’s agencies faced. We did not
estimate a total social cost of implementing efficiency. Instead, we developed estimates of the
costs that the agencies within the region would bear to induce a unit of water savings. There
would be other, potentially significant, costs borne by the region’s developers and water users
to meet efficiency mandates or program requirements that are not included in the model.
Using program budget information and estimates of efficiency savings provided by IEUA, we
estimated a base-case cost of efficiency to be $43 per af. These costs increase over time as a
function of the amount of efficiency savings induced (having more aggressive saving targets
induces greater costs) and an uncertainty parameter. For example, efficiency costs in 2040 for
a 15 percent savings by 2040 range between $200 per af and $400 per af.
Evaluating Adaptive Management Strategies
41
The next several slides demonstrate the basic results from several specific model simulations. In
the upper left chart on each slide, we show the annual precipitation used for each simulation.
In the lower left, we show the computed supply mix for the simulation. The supply categories
are (from bottom to top): Chino groundwater, non-Chino groundwater, recycled water, local
supply, imports, DYY, unneeded supply, and shortage). The right graph shows the corresponding total PV of discounted costs for the simulation (including shortage costs). Note that this
measure reflects both the relative use of the different supplies as shown in the supply-mix graph
and the per-unit cost of the water as shown in the previous slide.
This slide shows the projected performance of the UWMP forever plan under historical
climate conditions and base-case planning assumptions. Note that there are no shortages or
costs associated with shortages and that a sizable surplus (unneeded supply) is projected during
most years (as suggested by the 2005 UWMP). The significant expansion of the recycled-supply
program limits the amount of imported supply required in this simulation. The total cost of
this strategy and the climate scenario as simulated is about $3 billion.
42
Preparing for an Uncertain Future Climate in the Inland Empire
This slide shows the projected performance of the UWMP forever plan under a set of climate
conditions in which precipitation is lower than average and declining (adverse conditions). All
other planning assumptions remain the same as in the previous slide. In this case, significant
shortages occur in 2030 and beyond. Also, the amount of Chino groundwater is adjusted
downward several times—first, very slightly in 2015, again more dramatically in 2020, and
again in 2030. Note that, during the early years, there are sizable surpluses, and the amount
of imported water use is low (as recycled supplies increase). Once groundwater use is curtailed
due to lower infiltration and lower replenishment, use of imported supplies rises to the maximum available amount. The DYY program is used around 2020 and again in 2030, although it
runs out of supply by 2034, as conditions continue to deteriorate. Finally, notice that the total
demand, the top of the surplus or shortage area, is greater under this simulation than in the
previous one; this is due to the hotter and drier conditions in this case. The cost of this strategy and the climate scenario as simulated exceeds $4 billion, largely due to the costs associated
with shortages.
Evaluating Adaptive Management Strategies
43
This slide shows exactly the same conditions as those in the previous slide but for the UWMP
with updates plan. In this case, adaptation dramatically improves the performance of the
UWMP. Specifically, because conditions are dry at the beginning of the simulation, adaptivity is triggered early (in 2015). This then initiates significant improvements in efficiency and
storm-water capture such that, by 2030 (when shortages were experienced in the previous simulation), demand is reduced considerably and groundwater use is less curtailed due to increased
replenishment. The total cost of this adaptive strategy and the climate scenario is much smaller
than in the previous case, because IEUA’s costs of efficiency and additional storm-water capture are estimated to be low.
CHAPTER FOUR
Comparison of Options
We now use the WMM to compare how different water-management options (or plans) perform across the wide range of possible future conditions, to better understand which actions
would be most desirable for the agencies in the IEUA region to take now.
45
46
Preparing for an Uncertain Future Climate in the Inland Empire
As discussed earlier, traditional analytic decisionmaking approaches would evaluate IEUA’s
options by first characterizing the uncertainty the agency faces as a prelude to suggesting its
best course of action. This slide shows the basic structure of such an analysis, common in water
planning. A standard decisionmaking analysis begins by structuring the problem, by developing a computer model that estimates how particular decisions (or strategies) will perform. If
there is uncertainty about how a strategy will perform, these uncertainties are next characterized with probability distributions over the inputs to the model. Each option is then evaluated
and ranked according to one or more decision criteria. The top-ranked option (assuming a
weighting for multiple-criteria problems) is often interpreted as optimum. Finally, a sensitivity
analysis is performed to assess how the optimum strategy would perform under different combinations of uncertain conditions. Such predict-then-act analyses are most useful when water
planners can characterize the uncertainty with sufficient reliability that the sensitivity analysis
does not significantly change the optimum strategy. Under conditions of deep uncertainty, the
uncertainty is not so reliably characterized, and it may thus be impossible to confidently choose
a single optimum strategy.
Comparison of Options
47
RDM is a new approach to supporting decisions under such conditions of deep uncertainty. It
seeks to identify strategies that perform reasonably well, compared with the alternatives, over a
wide range of plausible futures (Groves and Lempert, 2007; Lempert and Collins, 2007; Lempert, Popper, and Bankes, 2003). We have found in our previous work that RDM often characterizes uncertainty and options for managing it in ways that decisionmakers find credible,
because they often naturally seek robust strategies. RDM can also contribute to contentious
political debates, because parties to a decision can agree on near-term actions without having
to agree on expectations about the future.
48
Preparing for an Uncertain Future Climate in the Inland Empire
An RDM analysis begins, similarly to a standard probabilistic analysis, by structuring the problem. But instead of next characterizing the uncertainties as a prelude to ranking the decisionmaking strategies, an RDM analysis first proposes alternative strategies and then characterizes
the uncertainties according to their effect on the choice among these options. To accomplish
this, the RDM analysis begins with a set of alternative strategies and then assesses each over a
wide range of plausible futures. Each future is defined by a particular combination of values for
the uncertain input parameters to the model. The analysis then uses statistical procedures to
determine those combinations of uncertainty parameters most important to the choice among
the strategies. For instance, we might find that, if future precipitation levels drop below a certain threshold in the IEUA region, the agency might consider augmenting its current UWMP.
(As described later in this chapter, what we actually find is a bit more complicated.) Once the
RDM analysis has isolated the combinations of uncertainties most important to comparing
the policy options, it identifies the key trade-offs among the most promising strategies. At this
stage, RDM may employ probabilistic information to illuminate such trade-offs. For instance,
the analysis might suggest that decisionmakers choose one strategy over another as long as
future precipitation was sufficiently likely to remain above some threshold, helping the decisionmakers decide whether this is a risk they are willing to take.
Ideally, an RDM analysis helps identify a robust strategy, one that performs reasonably
well compared with the alternatives over a very wide range of uncertainties. If none of the
strategies initially considered emerges as robust, the RDM process shown in this slide can be
repeated, using the information about key uncertainties and trade-offs to suggest new and
potentially more robust strategies.
In many cases, this type of analysis can be very helpful, because it allows decisionmakers
to identify and agree on a robust strategy, even if the uncertainties are very large. However,
Comparison of Options
49
the success of an RDM analysis often depends on the ability to find strategies that have this
robustness property. If no such strategies exist,1 the results of an RDM analysis may not prove
particularly useful or satisfying to decisionmakers. But even when no robust strategy exists, the
RDM analysis may provide some guidance to decisionmakers on where they need to invest in
research to reduce key uncertainties or find ways to expand their options.
1
Lempert and Collins (2007) described some conditions under which robust strategies do not exist.
50
Preparing for an Uncertain Future Climate in the Inland Empire
We began this phase of our analysis by evaluating the performance of the UWMP forever plan
under the entire set of weather sequences derived from the AOGCM data (225 runs = 25 runs
times 9 deciles).
This slide shows the average annual unmet demand over the 35-year simulation period
for each climate-change decile; the leftmost bar is associated with strongly decreasing precipitation trends. As expected, the average annual unmet demand for the UWMP forever plan is
greatest for the weather sequences that exhibit the largest precipitation decline. There are no
shortages at all for the top third of the climate sequences (those with increasing precipitation
trends, on average).
These results suggest that subsequent analysis of vulnerabilities of the region’s plans is best
focused on those weather sequences that exhibit decreasing precipitation trends. As increasing
precipitation trends will only increase local and imported supplies while suppressing demand
for outdoor irrigation in the model used for the analysis, there would be no vulnerabilities to
probe for such scenarios.
Comparison of Options
51
We next evaluated the WMM and various plans under a wide range of planning assumptions
and possible weather sequences (with a focus on those futures with declining precipitation—
deciles 1–4). For the next several slides, we present histograms of the PV of total cost, in billions of dollars, for 200 individual runs of the WMM. We use a Latin hypercube experimental
design (i.e., a quasiuniform design) across the model parameters associated with the assumptions described in slide 26 (except that we restrict the range of weather sequences to only those
from deciles 1 to 4). Note that the PV measure includes both the cost of providing supply to
the end users and the cost of incurring any shortages.
This slide shows a histogram of PV total costs for the UWMP forever plan. For reference,
we also indicate the result for the UWMP forever plan under historical weather conditions and
nominal planning assumptions. The PV total costs for most of the 200 simulations are greater
than those under historical weather and nominal planning assumptions (to the right of the
arrow in the graph).
52
Preparing for an Uncertain Future Climate in the Inland Empire
We next compare alternative plans to the UWMP forever plan. This slide shows the UWMP
forever plan (in blue) as in the previous slide but also overlays a histogram representing the
results for the UWMP + DYY and recycling plan (in gold). Note that there are fewer simulations in which PV total costs is $4.5 billion or more for the UWMP + DYY and recycling plan.
These results indicate that adding these actions now reduces the effect of unfavorable climate
and planning assumptions on the UWMP forever plan.
Comparison of Options
53
This slide compares the UWMP forever (blue) plan with the UWMP + replenishment (gold)
plan for 500 futures. The UWMP + replenishment plan reduces even more high-cost outcomes
than the UWMP forever or the UWMP + DYY and recycling plans.
54
Preparing for an Uncertain Future Climate in the Inland Empire
This slide compares the UWMP forever (blue) plan with the UWMP + efficiency (gold) plan
for 200 futures. The UWMP + efficiency plan reduces even more high-cost outcomes than
have the other plans evaluated so far.
Comparison of Options
55
This graph compares the UWMP forever (blue) plan with the UWMP + all enhancements
(gold) plan for 200 futures. The UWMP + all enhancements plan reduces the most high-cost
outcomes than have the other nonadaptive plans evaluated so far.
56
Preparing for an Uncertain Future Climate in the Inland Empire
We showed that augmenting the UWMP forever plan with all enhancements reduces the
number of high-cost outcomes. Although the PV total cost metrics include what IEUA believes
to be the major financial costs of implementing these programs, there are other costs and barriers not captured by the model. For example, a significant amount of coordination across the
cities and agencies will be required to speed up the expansion of the recycling program and
increase the amount of storm water that can be captured and used for Chino basin replenishment. Planners in the IEUA region are thus keenly interested in what specific risks are reduced
by implementing additional management programs.
Following the RDM approach, we specify a threshold output value above which the PV
total cost shows poor performance. In this case, the value is set at $3.75 billion in PV total
costs (about 20 percent higher than would be incurred under the UWMP forever plan and
nominal planning assumptions and also the upper level of costs for the UWMP + all enhancements plan). We then ask what factors cause the UWMP forever plan to incur higher costs
than these.
Following the scenario-discovery procedure outlined in Groves and Lempert (2007) and
Lempert, Groves, et al. (2006), we use a cluster-finding algorithm called the patient rule induction method (PRIM) (Friedman and Fisher, 1999) to find and characterize clusters in the database of simulations that represent management conditions in which the UWMP forever plan
performs poorly.
PRIM is a data-mining algorithm designed to generate a set of low-dimensional “boxes”
of high-dimensional data containing regions in which the value of a particular function is
large (or small) compared with its value outside these boxes. PRIM is particularly useful for
identifying scenarios, because it aims to optimize both the classification accuracy of the boxes
(the percentage of large- or small-function values they contain) and the interpretability of the
Comparison of Options
57
boxes (the simplicity of the rules needed to define them). We implement PRIM using publicly
available software that inputs a data set (which can be the output of a model run over many
combinations of input values) and a criterion for cases of interest. The algorithm yields as outputs the descriptions of several alternative low-dimensional regions, or boxes, that contain a
high density of and span a high proportion of the interesting cases.
The PRIM algorithm yielded three key factors that lead the UWMP forever plan to perform poorly: (1) large declines in precipitation (deciles 1 and 2), (2) strong climate effect on
imports (greater than a 22 percent decline in average annual imports by 2040), and (3) strong
reductions in Chino basin percolation (greater than 3.8 percent decline). Simulations in which
these conditions are simultaneously achieved explain 53 of the 116 (46 percent) high-cost outcomes for the UWMP forever plan. Note that 95 percent of the outcomes that include these
three key factors are high cost.
58
Preparing for an Uncertain Future Climate in the Inland Empire
In summary, we found that enhancing the UWMP with all measures now reduces significant
risks due to declining precipitation, strong effects of climate change on imports, and greaterthan-anticipated declines in Chino basin percolation. Note that these are similar to the factors
found in the analysis in the third workshop (Groves, Knopman, et al., 2008)—strong precipitation declines, low achievement of recycling goals, and greater-than-anticipated declines in
Chino basin percolation.
These results suggest the following question: “Could the region wait until later to act?” To
address this question, we evaluate a series of adaptive plans in the same manner as we evaluated
the nonadaptive plans.
Comparison of Options
59
In this slide, we evaluate the risks of the UWMP with updates plan versus the UWMP + all
enhancements plan. When we add adaptivity to the UWMP forever plan, there are fewer
high-cost outcomes across the various futures, and those futures that lead to costs that are
above the $3.75 billion threshold are characterized by slightly different factors. The UWMP
with updates plan is still vulnerable to large declines in precipitation (decile 1 or 2) and strong
climate effects on imports (declines greater than 25 percent by 2040), but, instead of being vulnerable to declines in Chino basin percolation, it is more vulnerable to higher water demand
(water intensity in new developments being less than 25 percent lower than that of current
development). The UWMP with updates plan is less vulnerable to declines in groundwater
infiltration because of the increases in groundwater replenishment that occur as an adaptive
action in response to deteriorating conditions. High-cost outcomes, then, are more frequently
caused by futures in which demand is higher than expected. Note that these risk factors explain
23 of the 33 high-cost outcomes (67 percent); 35 percent of all outcomes described by these risk
factors are high-cost outcomes.
60
Preparing for an Uncertain Future Climate in the Inland Empire
In this slide, we evaluate the risks of the UWMP + DYY and recycling with updates plan
versus the UWMP + all enhancements plan. The results are very similar to the UWMP with
updates plan, though the previous vulnerability to low water demand is replaced by vulnerability to high costs of imports. Specifically, UWMP + DYY and recycling with updates plan
is vulnerable to large declines in precipitation (decile 1 or 2) and strong climate effects on
imports (declines greater than 33 percent by 2040), but, instead of being vulnerable to declines
in Chino basin percolation or water demand, it is more vulnerable to higher costs of imports
(via Metropolitan). The fact that a key factor is now related not to the occurrence of shortages
but simply to higher costs of delivering water suggests that vulnerabilities to this plan are now
related to situations in which investments in more local resources (as is done in the UWMP +
all enhancements plan) pay off because they allow the region to reduce expensive imported supplies. A key vulnerability of a less aggressive plan (e.g., the UWMP + DYY and recycling with
updates plan) is that costs of imports increase even faster than anticipated, leading to higher
total costs. Note that these risk factors explain eight of the 23 high-cost outcomes (35 percent)
and that 24 percent of all outcomes described by the risk factors are high-cost outcomes.
Comparison of Options
61
In this slide, we evaluate the risks of the UWMP + efficiency with updates plan versus the
UWMP + all enhancements plan. Both of these plans do well, suggesting that increasing efficiency now can avoid most of the high-shortage cases in later years.
62
Preparing for an Uncertain Future Climate in the Inland Empire
In summary, these results suggest that, if current IEUA regional leadership expects that future
water managers and city planners will respond to decreasing reliability, some actions may be
deferred. For example, if the region implements the RUWMP with increased efficiency now
and increases storm-water replenishment if surpluses decline too much (e.g., implements the
UWMP + efficiency with updates plan), it will face similar risks to those it would face if it
implemented all actions now. However, if the region were to implement the RUWMP and rely
on updates, it would still be vulnerable to significant precipitation decline, reductions in basin
percolation, and reduction in imports due to climate change.
Comparison of Options
63
The results shown so far have aggregated the 200 model runs. We now show comparisons of
different plans using scatter plots, which show the results of the individual simulations as single
points on a graph. Such scatter plots may provide more useful information to decisionmakers
but at a cost of increased complexity. The x-axis indicates the PV of the shortage costs, and the
y-axis indicates the PV of the supply costs. Results in the lower-left corner, for example, have
low shortage costs and low supply costs. Results in the upper-right corner have high shortage
and supply costs. The sum of the PV shortage costs and PV supply costs are the PV total costs
shown in the histograms in the earlier slides.
This graph shows the results of the UWMP forever plan in two scenarios. Scenario A
exhibits modest warming and minimal precipitation decrease, and scenario B exhibits significant warming and precipitation decrease. Note that the UWMP forever plan leads to no shortage costs in scenario A but PV shortage costs of about $2 billion in scenario B. Scenario B also
leads to higher supply costs.
64
Preparing for an Uncertain Future Climate in the Inland Empire
This graph is the same as the graph on the previous slide except that it includes the results for
the UWMP forever plan in 198 other scenarios. Note that the histogram on slide 38 summarizes these same results. For scenarios that experience no shortages (e.g., PV shortage costs are
0), the PV supply costs range from around $2.75 billion to $3.5 billion. Shortage costs, on the
other hand, range from $0 to more than $3 billion for a few extreme cases.
Comparison of Options
65
We now show comparisons of the UWMP forever and the UWMP + DYY and recycling
with updates plans using the scatter plots. We overlay a horizontal and vertical line to help
emphasize how the patterns of results differ for the two plans. For example, 63 percent of the
scenarios lead to more than $500 million in PV shortage costs for the UWMP forever plan,
whereas only 16 percent of the scenarios lead to more than $500 million in PV shortage costs.
About 67 percent of the scenarios lead the former plan to have PV supply costs greater than
$3 billion, compared to only 38 percent for the latter plan. Thus, including future updates and
implementing the DYY + recycling plan’s additional actions reduces both shortage and supply
costs.
66
Preparing for an Uncertain Future Climate in the Inland Empire
This slide shows the results from the previous slide (upper two graphs) as well as two more
plans: the UWMP + efficiency with updates plan and the UWMP + all enhancements plan.
These two new plans significantly reduce the risk of adverse climate and other planning conditions. It is interesting to note that there is still significant variability in supply costs (as seen by
the vertical spread of the points along the y-axis). This is expected as, during dry years, under
either plan, the region is likely to rely on expensive imported supplies. During less dry years,
the additional local resource development leads to lower supply costs as the region substitutes
away from imports toward local resources, such as recycled supply, storm water, and efficiency
savings.
Comparison of Options
67
The previous slide suggests that early action reduces costs due to shortages and supply-delivery
costs overall. A common concern with water-resource development is that, under some conditions, the additional development will be unneeded or go unused. These so-called stranded assets
then lead to higher costs than would have been experienced under plans with less-aggressive
infrastructure investment.
To evaluate this concern, we calculate the difference in PV total cost between the UWMP
forever plan and the best-performing strategy for one-fourth of the 200 runs evaluated previously. The graph shows these results plotted against the total shortage under the UWMP
forever plan. The symbol shape indicates which plan is the best performer. Note that the bestperforming plan is either the UWMP + efficiency with updates or the UWMP + all enhancements. The dots aligned along the y-axis of the graph correspond to simulations in which
there are no shortages in the UWMP forever plan. Even under these cases, an enhanced plan
would perform better. For these cases, the best-performing plan would reduce PV total costs
by between about $150 million and more than $400 million. In summary, overinvesting is
unlikely to be a significant concern to the IEUA region, provided that precipitation trends
decrease or stay the same over the next 35 years. More analysis is needed to ensure that overinvestment would not occur in scenarios in which precipitation trends increase.
68
Preparing for an Uncertain Future Climate in the Inland Empire
We now look at the remaining risk for a selection of the plans. The four plans presented in this
slide are the same as those presented in slide 53. The red diagonal line indicates the $3.75 billion threshold shown in slides 55 and 56. Recall that the sum of the x-axis and y-axis values
equals the PV total costs. Dots to the right of the threshold line indicate those simulations with
high costs.
The plot shows that, similarly to what we saw in the histograms, as adaptivity and additional near-term local resource-development activities are implemented, the number of cases
with high costs decreases significantly.
Comparison of Options
69
This slide presents the same key risk factors for each plan identified and described in earlier
slides. We indicate with red triangles those simulation results that are characterized by the key
risk factors. In this view, one can see that not all bad cases are explained by the key risk factors
and that some cases classified by the risk factors do not result in costs that exceed the threshold.
For the former case, one may also seek to develop an additional characterization of results that
exceed the cost threshold but do not arise from the key risk factors identified here.
70
Preparing for an Uncertain Future Climate in the Inland Empire
To summarize our results and frame a discussion of their implications, we graph the number
of outcomes that exceed the $3.75 billion cost threshold for each IEUA region plan. We also
include the text description of those factors that lead to many of the high-cost outcomes.
The key findings of this study can thus be summarized as follows:
t The IEUA region faces risk from decreasing precipitation trends and other adverse planning conditions.
t Under the UWMP forever plan (e.g., simply implementing the actions described in IEUA’s
RUWMP), there are numerous plausible future conditions in which both shortage and
supply costs are higher than would be the case with more-aggressive local resource development. These high-cost outcomes are characterized by cases in which there are large
declines in precipitation, strong effects of climate on imports, and moderate reductions in
Chino basin percolation over the simulation period (2005–2040).
t Out of eight alternative plans that increase local resource development in the near term
and in response to degrading conditions, the plans that do more lead to greater reductions
in high-cost outcomes (the sum of discounted delivery and shortage costs).
t The key factors generating the risks change modestly as the region implements more
local resources. For example, the region’s vulnerability to reductions in Chino basin percolation is reduced with updates and more wastewater replenishment. Vulnerabilities to
higher costs of imports and the underlying water demand in the region become more
important as the region increases its reliance on local resources.
• The UWMP + efficiency with updates and the UWMP + all enhancements plans perform similarly well in reducing high-cost outcomes.
Comparison of Options
71
Major Implications and Recommendations
These findings suggest that the IEUA region can reduce its exposure to adverse climate-change
effects by taking advantage of the favorable economics of local resource development in the
region. As long as the local resource-development activities (including increasing efficiency)
are less costly than imports and precipitation trends under climate change are flat to strongly
decreasing, there is little risk of overinvestment. We have demonstrated that preparing the
region to adapt in the future as climate-change effects and other planning uncertainties
become more apparent can be very effective and, in some cases, as effective as developing more
resources now. One promising well-hedged strategy would be to implement the actions within
the RUWMP while increasing the region’s commitment to indoor and outdoor water-use efficiency. Implementing these actions, as well as studying the options for increasing storm-water
capture for groundwater replenishment in coming decades, would represent a sensible and significant response to the threat of climate change.
CHAPTER FIVE
Survey Results
We administered surveys to the workshop participants at the beginning (before the presentation) and at the end (after the presentation) of the workshop. We compared the responses at
the two points in time to assess how participants’ views changed in response to the material
presented in the workshop.
Twelve of the participants in this workshop reported that their primary area of current professional activity was being managers or directors, four reported being planners, two
reported being public officials or consumer representatives, and the other six reported being
“other.” None was a professor or student.
Nine reported spending all or a lot of their time working on planning for water resources
in Southern California. Three spend half their time, eight spend some or a little of their time,
and three spend almost none of their time. One respondent declined to answer this question.
When asked how familiar they were with the IEUA RUWMP, four reported that they were
involved in developing it; two worked with it extensively as a planning tool or read it thor73
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Preparing for an Uncertain Future Climate in the Inland Empire
oughly; 10 were familiar with it, though not in detail; and eight were slightly or not at all
familiar with it. Finally, six of the participants in this workshop had attended all three of the
previous workshops, two had attended two of them, three had attended one workshop, and 13
had not attended any of the prior workshops.
The next set of slides presents some findings from the survey results.
Survey Results
75
Surveys before and after the presentation were administered to 24 workshop participants (six
of the respondents had attended at least one previous workshop). Because of the small number
of individuals sampled, results cannot be viewed as having statistical significance. Instead, we
report these data as notional findings, suggestive of hypotheses that we may choose to test
under more-rigorous and -controlled conditions at a later date.
Both the pre- and postworkshop surveys asked several questions about how serious climate change may be, how likely it was for the serious effects on the IEUA region, and how well
equipped IEUA-region planners were to manage the effects of climate change. Of the 24 participants, about half thought that their view of the consequences of bad climate change and the
likelihood of bad climate change were the same after the workshop as before, but 35 percent
thought that consequences of bad climate change were more serious than before and 40 percent thought that the likelihood of bad climate change was greater than before. However, 75
percent changed their views in the positive direction about the ability of water planners at the
IEUA to plan for and manage the effects of bad climate-change outcomes on the water supply.
This seems to indicate that the RDM-based workshop may have made most of the participants
more confident about managing the future effects of climate change in their region.
In summary, the comparison of the before- and after-workshop responses suggests that
the briefing provided information that increased the participants’ concerns about the effect of
climate change—both the likelihood of significant effects and the severity of the effects. At
the same time, water planners increased their belief that they could mitigate or manage these
effects. This is a noteworthy finding, as a primary objective of an RDM analysis is to illustrate
possible threats and then identify strategies that can be taken to address these threats without
having a clear understanding of exactly how the future may evolve. In this case, the survey
results suggest that this objective was met.
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Preparing for an Uncertain Future Climate in the Inland Empire
The surveys also asked the participants to rate the importance of implementing various watermanagement actions in the near term. Most participants believed that most of the actions
listed in the survey (see Groves, Lempert, et al., 2008) should be implemented now, including
significant proposals, such as retrofitting houses with more-efficient water-using devices and
gray-water or dual-use systems. For most proposed actions, participants reported only small
changes in their willingness to implement most proposed actions due to the workshop—nearly
every participant endorsed taking each action (that is, thought IEUA should be doing it now)
at the beginning of the session, and only one or two additional participants thought that was
the case by its end.
It is important to note that the workshop was presented at the end of one of the driest
years on record for the IEUA region. It is probable that support for implementing many of
these actions was due both to the general anxiety throughout the region that the drought
would continue and to the longer-term effects of climate change. Also, as mentioned earlier,
in the first workshop, in 2006, the surveys revealed significant concern that the region would
not meet all its recycling or groundwater-replenishment goals. The analysis suggests that doing
conservation now (for example) does hedge against some uncertainties, such as those surrounding the implementation of the recycling and replenishment program, and this may be behind
some of the support for additional near-term water-management actions.
Survey Results
77
The exception was the item “carry out outdoor landscape retrofits, including turf removal.”
While only 44 percent before the workshop said to do it now, 85 percent after the workshop
endorsed doing it now.
We also asked about how certain the participants were about their ratings of actions to
be taken. We asked, “How sure are you that your choice is correct?” and asked them to rate
their level of certainty on a 1 to 5 scale, where 1 = completely sure and 5 = not sure at all. The
preworkshop means varied from 1.95 to 2.43. The postworkshop means varied from 1.59 to
1.82. Because of small sample size, we cannot say whether this result is statistically significant,
but notionally, it seems to indicate greater levels of certainty after the workshop. This would be
consistent with the hypothesis that RDM can help groups converge on the actions to be taken
and be more able to undertake them.
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Preparing for an Uncertain Future Climate in the Inland Empire
We asked workshop participants to rate the usefulness of RDM on a variety of dimensions
using a 1–4 scale, where 1 = agree strongly and 4 = disagree strongly. More than 60 percent
of participants agreed strongly that RDM provided results that could be used in planning (75
percent), enabled comparisons of climate-related risks (60 percent), and presented information
in an objective way (61 percent). Fifty-five percent agreed strongly that RDM provided results
that support a choice among plans. Nearly everyone agreed strongly or somewhat that RDM
was useful for these purposes. Note that, unlike the design of the previous three workshops, in
this workshop, RDM was not being compared with another method.
Survey Results
79
However, we found that only 15 percent agreed strongly that RDM was easy to understand,
10 percent agreed strongly that it was easy to explain to stakeholders, and 35 percent agreed
strongly that it presented sufficient information about climate change for planning purposes.
Nonetheless, again, nearly all participants agreed strongly or agreed somewhat that RDM was
useful for these purposes.
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Preparing for an Uncertain Future Climate in the Inland Empire
We presented three types of graphical displays about the results from RDM. These were histograms and scatter plots that summarized results of a large number of scenarios and the characterization of key risk factors. We asked participants using the same 4-point “agree strongly” to
“disagree strongly” scale whether these were useful ways of presenting data. A majority agreed
strongly that all three approaches were useful, and the majority of the rest somewhat agreed
that they were useful.
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