Download Changes in Water Use Under Regional Climate Change Scenarios

Changes in Water Use Under Regional Climate Change Scenarios [Project
#4263]
ORDER NUMBER: 4263
DATE AVAILABLE: September 2013
PRINCIPAL INVESTIGATORS:
Jack C. Kiefer, John M. Clayton, Benedykt Dziegielewski, and James Henderson
OBJECTIVES
The primary purpose of this research study was to increase the adaptive capacity of water
utilities in planning for and responding to pressures that may result from climate change. Unlike
the majority of previous studies regarding the potential effects of climate change, this study
concentrates on the demand for water. The primary objectives of this study were to:





Review the importance of climate in shaping general demand patterns and
geographical differences in water use
Examine ways to model the effects of climate and weather on water use
Prepare downscaled climate projections and develop a process for selecting climate
scenarios for further investigation
Demonstrate the use of water demand modeling methods to simulate and quantify
potential demand impacts from selected climate scenarios
Evaluate the implications of potential demand-side impacts of alternative climate
change scenarios for water resources planning and management
Illustrations and examples of useful ideas and techniques play an important role in all
aspects of this study and take full advantage of water use data provided by several water utilities.
BACKGROUND
U.S. cities and municipalities regard a reliable supply of water as an essential service to
protect public health and safety and support economic growth and community well being. The
water utility industry accommodates this need through securing and treating ample water supply
resources for “on demand” delivery of high quality water in sufficient quantities and at suitable
pressure for consumption and fire protection.
Understanding the consequences of changes in climate is particularly important for the
water supply sector. Climate change has been identified as a key future trend and uncertainty
affecting water demand, supply, and resource competition in the United States (Dziegielewski
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and Kiefer, 2006). To date, studies of the effects of climate change on water resources have
generally remained supply-centric due to the hydrologically sensitive nature of water systems.
Several studies have identified potentially severe impacts of climate change on the ability to
capture, store, and divert water for human and ecological purposes [e.g., see Frederick and Major
(1997), Frederick and Gleick (1999), Cromwell et al (2008)]. Alterations may occur in processes
related to run-off, streamflow, available storage, and other hydrologic factors, which will affect
available supplies and supply variability.
Notwithstanding potential impacts on water supply, climate change can also be expected
to affect the demand for water. Water use depends both on long-term climate and seasonal
weather patterns, and is responsive to short-term fluctuations in actual weather conditions. Over
the long run, climate change may also influence long-term trends in regional population growth
and the location and scale of production processes, which drive the average level of water
demand in any particular locale. Because climate change can be expected to affect both the
demand and supply of water, climate change will influence the future reliability of water supply
systems (Kiefer, 2006).
There have been relatively few studies of the potential impacts of climate change on the
demand for water, and the topic has been identified as a gap in scientific knowledge related to
climate change adaptation (Intergovernmental Panel on Climate Change, 2008). Since the
demand for water is also influenced by climate and associated weather conditions, it is possible
that water demand and supply may diverge at an accelerating rate due to climate change
(California Urban Water Agencies, 2007). If climate change results in hotter and drier weather in
the future, it can be expected to increase demand for water and reduce supply, thereby
exacerbating water shortages or causing new ones. Because it is the mission of most if not all
water providers to meet the demands of their customers, it is necessary to anticipate the potential
implications of climate change on water consumption in order to more robustly understand the
risks and vulnerabilities associated with climate change, which may affect future water
management options (Figure ES.1).
APPROACH
The study began with a reconnaissance-level evaluation of regional trends in water use in
the United States, inclusive of demands associated with non-urban sectors. The purpose of the
regional analysis was to highlight broad-scale water use patterns and to identify water demand
pressures that may intensify under future climate. Using data on county- and state-level water
withdrawals collected by the U.S. Geological Survey and other secondary information, several
water use metrics were evaluated within the context of indicators of climate vulnerability
including regional trends in population, the presence and allocation of withdrawals among
potentially competing water uses (such as urban demands, agriculture, power production, and
ecological flows), rates and levels of water withdrawals for specific purposes, the degree of
reliance on surface water supply sources, and estimated time trends in metrics calculated for
these indicators of vulnerability.
The regional analysis served as an important backdrop for evaluating prospective climate
impacts on the demands of municipal (or urban) water systems, which was the primary focus of
the study. With regard to municipal water demands, the research approach set out with a
foundational assessment of the importance of climate in shaping water use patterns, which
utilizes a substantial amount of data provided by participating water utilities for the illustration of
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Figure ES.1 Water Demand, Supply, and Pathways of Influence from External
Factors Such as Climate Change
key points and concepts. A fundamental requirement for empirically estimating the potential
impacts of climate change on demand is the ability to construct statistical relationships that
correlate climate and associated weather patterns with water use. Therefore, the next key
component of the research approach involved an assessment of water demand modeling
techniques and their applicability to climate change analysis. Key modeling considerations are
discussed, including the measurement and choice of water use metrics and the selection of
appropriate climate and weather variables. Alternative methods are provided for differentiating
the effects of climate, which are embodied in repeating cyclical patterns in water demand, from
the effects of actual weather, which contribute to the variability of demand around these normal
repeating patterns. The evaluation of water use modeling techniques also makes use of data
provided by participating water utilities, as well as several useful concepts that have been
introduced in the literature over the last several decades.
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From these macro-regional and foundational underpinnings, the study shifts toward the
empirical estimation of potential water demand impacts for the following set of six case study
utilities:
1.
2.
3.
4.
5.
6.
Colorado Springs Utilities
Region of Durham (Ontario, Canada)
Massachusetts Water Resources Authority
Southern Nevada Water Authority
San Diego County Water Authority
Tampa Bay Water
A methodological framework for conducting the case studies was developed, which
includes processes for selecting and processing downscaled climate projection scenarios from
available General Circulation Models (GCMs), translating these projections into implied future
values of weather, and substituting these scenarios into water demand models to predict potential
demand-side impacts (Figure ES.2).
Figure ES.2 Generalized Process for Development of Case Studies
In order to meet the requirements of the water demand models, this study employed
downscaled model projections from the Bias-Corrected Constructed Analog (BCCA) section of
the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project
phase 3 (CMIP3) multimodel dataset (CMIP3 dataset) (Maurer et al., 2010). The BCCA dataset
contains results from a subset of 9 of the models in the CMIP3 archive. The BCCA dataset has
climate change projections for time slices surrounding the following years: 2055 and 2090. Each
time slice in this dataset is a 20-year time period with the identified year in the middle of the
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period ― for example the 2055 time slice includes the years 2046 to 2065. Multiple model runs
using different initial conditions are provided for some models, and there are a total of 53
model/runs for a given time period. Baseline projections (backcasts) for the period 1961 to 2000
are available for each model, however the period 1971 to 2000 is used for this study. The
projected change in climate compared to baseline, or the ‘delta’ (e.g., + 2 F or -5%
precipitation), is the most critical piece of information for translating projected changes in
climate into projected changes in demand.
Figure ES.3 Illustration of Quadrant Scenario Approach to Model Selection
The case studies use a scenario approach to incorporating climate change projections into
water demand modeling. The scenarios are designed to identify a wide range of model outputs in
terms of temperature and precipitation. The range of outputs is conceptualized based on four
quadrants of temperature and precipitation pairings, which within a scatterplot identify four
general projection conditions relative to the (conceptual) mean of all available projections for a
given time period (Figure ES.3). The scenarios are labeled “Hotter/Drier”, “Hotter/Wetter”,
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“Cooler/Drier”, and “Cooler/Wetter.” A “Middle/Moderate” scenario is also identified.1 Note
that the scenario approach does not attempt to assign probabilities or likelihoods to individual
scenarios, which is beyond the general ability of climate science as it exists currently. Use of a
scenario approach served two important purposes for the study. Namely, this approach defined a
range of climate model projections for a particular location, given the significant variability of
projections across GCMs and uncertainty associated with model run output. Furthermore, this
approach served as a useful data reduction technique and limiting the number scenarios to an
adequate range of extremes reduced data processing time significantly.
Finally, the range of five climate scenarios was uniquely selected for each case study
location for 2055 and 2090 climate projection periods. The implied changes in climate relative to
historical conditions were then fed into the water demand models either provide by or estimated
for the case study utilities to generate predicted changes in water use relative to levels of water
use that would be predicted under historical climate conditions. The results of the case studies
were then synthesized and used to evaluate implications for adaptation and water supply
planning and management.
RESULTS/CONCLUSIONS
The study resulted in several principal conclusions spanning across several topics that are
important to evaluating the potential effects of climate change on water demand. The main
conclusions can be summarized as follows:
1. Weather sensitive demands are prevalent and will be affected by climate change.
Weather-sensitive water demands exist in virtually all places in the country and account
for a substantial portion of total municipal water demands in most regions and a majority of total
demand in some areas and times of the year. Municipal water demands are sensitive to regional
differences in climate and are responsive to variability in actual weather conditions.
In hot and dry climates of the West average customer demands can be 50 to 80 percent
higher than in the humid East. Climate is responsible for explaining a considerable amount, if not
a majority, of intra-annual variability (i.e., average month-to-month changes) in demands in most
water utility service areas. After accounting for long-term trend, variability of weather conditions
within a given climate accounts for most of the inter-annual differences in demand (e.g.,
differences in annual demand between consecutive years). Fundamental differences in climate
across geographical regions explain large differences in average rates of water consumption, as
well as differences in the pattern of monthly and daily demands within the calendar year.
2. Evaluation of weather and climate impacts involves a host of technical modeling
requirements, choices, and tradeoffs.
With regard to water use modeling, an over-riding conclusion is that only certain types of
models, specifically those that contain and relate weather and climate indicators to water use, are
1
The Hotter/Drier, Cooler/Wetter, Cooler/Drier, and Hotter/Wetter scenarios are selected relative to the
Middle/Moderate scenario (and named accordingly), without reference to current or historical climate.
For example, in the context of this study, a “cooler” climate projection scenario may in fact be hotter than
the current climate.
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relevant for evaluating the potential effects of climate change. Water use models based on
relatively more frequent measurements of water use (e.g., monthly, weekly, and daily) are more
preferable for evaluating the effects of weather and climate effects than models based on coarser
time measurements. Aggregate measures of demand, such as water production, are typically
more readily available, have more frequent measurements, and are easier to match with weather
records than water billing data for customers and customer classes, which tend to reflect uneven
and less frequent time intervals due to customary meter reading and customer billing practices.
However, disaggregate data may be generally preferred for evaluating long-term structural trends
in demands and differences in climate sensitivity across various water using sectors.
Disaggregation of water use into sectors or user types can provide more information about the
effects of weather and climate and how these effects may vary over relatively homogeneous
classes of customers.
Demand models should be specified to include measures of warmth and moisture, both of
which are available or can be calculated from climate projection data. Historical observations on
air temperature and precipitation should in most cases be readily available. Furthermore, climate
projection data fundamentally contain projections of air temperature and precipitation, which
makes a direct connection to historical data and model variables, in terms of definition and
measurement. Other climatic variables, such as reference evapotranspiration (ETo), effective
precipitation, and others, have proven useful for modeling demand, but both historical and
projection data for those variables are relatively less available and require more assumptions to
derive than basic measures of temperature and precipitation.
Systematic seasonal patterns of demand associated with climate are typically highly
correlated with air temperatures and agronomic measures of moisture requirements that are
correlated with air temperature (such as ETo). Water demand models that account for systematic
seasonal patterns in historical water use by specification of repeating fixed or harmonic seasonal
effects may render these models less useful in cases where seasonal patterns associated with
future climate are expected to differ significantly. Because of its high correlation with the notion
of seasons, average high air temperatures may be used as an effective statistical instrument for
capturing the effects of historical seasonal fluctuations in demand and for projecting potential
future seasonal patterns under climate change scenarios. The separation of demand into base and
seasonal use (i.e., non-weather- and weather-sensitive) components is useful for identifying
particular thresholds of temperature to use as seasonal instruments, which do not necessarily
force future demands to follow the same seasonal patterns of demand associated with historical
climate.
Projected impacts of climate change scenarios differ across different water demand
models that diverge in underlying specification and functional form. The addition of non-weather
socioeconomic covariates in water demand models enhances the ability to evaluate factors that
may counteract or further exacerbate predicted demand effects from future climate scenarios.
Probabilistic methods for demand forecasting further enhance evaluation of climate scenarios by
providing a means of examining variability in climate relative to uncertainty about
socioeconomic conditions.
3. Derivation and processing of climate model projections is a data intensive process.
The identification and processing of suitable climate projections is the bridge between
modeling the response of water use to climate and weather and the use of water demand models
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in assessing potential impact. Projections for multiple climate model runs should be used to
evaluate a range of projected climate scenarios, since future climate projections are implicitly
considered to be equally likely to occur.
Daily-level climate projection data are required to derive values of certain weather
variables, such as average maximum daily temperature, the length of hot or dry spells, and
others. The need for multiple climate runs and requirements for daily scale data can create
voluminous data sets that can be hard to manage. Data reduction techniques are recommended to
make data processing and simulations more manageable. The selection of relatively extreme
scenarios is helpful, both as a data reduction technique and as a means of characterizing the
range of climate projections.
Finally, even if downscaled climate projections are considered to be bias-corrected,
ground-truthing of climate model backcasts of historical weather conditions relative to observed
historical averages is necessary to examine whether biases may still exist because of differences
in geographical scale. Additional bias corrections were necessary for the case studies evaluated
in this study.
4. Climate projections and estimated demand impacts vary geographically.
The reconnaissance-level evaluation of regional climate change vulnerabilities and
statistical estimation of demand impacts for six utilities suggest that future climate scenarios
could lead to additional complications for water resources management. With respect to broad
regional trends, many highly-populated areas rely on surface water as the primary source for
meeting demands. These sources are generally more hydrologically variable and vulnerable to
climate shifts than ground water sources, and this reliance is increasing in some places (Figure
ES.4). For regions with high and growing urban demands, high rates of agricultural withdrawals
and greater reliance on surface water sources, climate changes that result in warmer and drier
conditions or changes in seasonal supply conditions will likely exacerbate existing demand
pressures.
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Figure ES.4: Percentage Surface Water Withdrawals by County, Freshwater,
Thermoelectric Withdrawals Removed, 2005 (Source: U.S. Geological Survey, Estimated
Use of Water in the United States, County-Level Data for 2005)
With regard to case study locations, substantial warming is predicted for the case study
locations, with double-digit increases (in degrees Fahrenheit) under some scenarios by 2090.
Projected changes in precipitation show less agreement among climate models than projected
changes in temperature. However, climate projections for western case studies (Southern Nevada
Water Authority, San Diego County Water Authority, and Colorado Springs Utilities) more
consistently indicate less annual precipitation. Among the six regions, only MWRA is projected
to receive more precipitation annually than observed historically.
On an average annual basis, an increase in water demand is projected for all case study
utilities and across all climate projection scenarios evaluated for 2055 and 2090 climate
projection years (Table ES.1). Among the case studies, the estimated relative increases in
demand are far and away the greatest for Colorado Springs Utilities (CSU), where the predicted
climate-induced increases in demand range from a maximum of 23.2 percent under mean 2055
climate to a maximum of 45.0 percent under mean 2090 climate. The estimated degree of
potential increases in demand is also relatively high for San Diego County (SDCWA), where the
maximum relative projected increases in demand are 12.7 percent under mean 2055 climate and
23.7 percent under mean 2090 climate.
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Table ES.1
Range of Estimated Projected Changes in Mean Annual Demand by
Case Utility and Climate Projection Year
 Mean Estimated Demand
 Mean Estimated Demand
2055 Climate (%)
2090 Climate (%)
Utility Min
Max
Min Max
Colorado Springs Utilities
(CSU) 5.9%
23.2%
7.7% 45.0%
Regional Municipality of
Durham (Ontario, Canada)
(Durham Region) 1.6%
4.3%
2.0% 8.3%
Massachusetts Water
Resources Authority (MWRA) 1.7%
5.0%
2.5% 9.1%
Southern Nevada Water
Authority (SNWA) 3.9%
9.4%
5.2% 15.5%
San Diego County Water
Authority (SDCWA) 3.5%
12.7%
9.2% 23.7%
Tampa Bay Water
(TBW) 1.2%
5.3%
2.1% 9.9%
 = Relative (delta) change in mean water demand as compared to reference mean demand under
historical weather conditions.
There are similarities among the results for Durham Region (Ontario, Canada),
Massachusetts Water Resources Authority (MWRA), and Tampa Bay Water (TBW). Namely,
estimated increases in demand are relatively small on an annual basis when compared with the
results for the other western utilities, and the range of estimated changes in demand across
scenarios is considerably smaller, as well. Only moderate impacts ranging from a maximum
change of about +5% for 2055 climate and a maximum change of about +10% for 2090 climate
are estimated for these three water utilities which are located in the more humid East.
The range of projected impacts for Southern Nevada Water Authority (SNWA) is in the
middle of the six cases. Projected impacts for SNWA range from a maximum projected increase
in demand of 9.4 percent under mean 2055 climate to a maximum projected increase of 15.5
percent under mean 2090 climate.
In almost every case, the maximum estimated demand impacts for 2090 climate are
nearly double the maximum impacts estimated for 2055 climate. The range of impacts is also
wider for the 2090 projection year. Furthermore, estimated impacts vary seasonally and are most
pronounced for the 2090 Hotter/Drier scenario (see Figure ES.5). Seasonal estimates of demand
impacts generally point to a lengthening of the watering season (e.g., spring-like conditions
starting sooner and summer-like conditions lasting longer into the fall).
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Estimated Changes in Average Demand by Season, 2090 Hotter/Drier
Scenario
% change in demand
60%
50%
40%
30%
20%
10%
0%
-10%
CSU
Winter
Spring
Summer
Fall
25.6%
54.3%
52.4%
35.3%
Durham
Region
0.6%
9.5%
17.8%
3.5%
MWRA
SNWA
SDCWA
TBW
-0.3%
11.1%
16.4%
6.8%
27.2%
14.6%
11.2%
17.1%
23.7%
24.8%
24.6%
20.8%
8.0%
10.9%
15.3%
5.6%
Figure ES.5: Estimated Seasonal Demand Impacts by Case Study Region under 2090
Hotter/Drier Scenario
Estimated increases in demand among some case studies would be considered equivalent
to effects of significant growth in the number of accounts or population under historical normal
climate conditions. Implied weather variability within some climate projection scenarios
produces estimates of demand that would be unlikely to be experienced under historical weather.
This relates also to hot and dry weather spells and the potential for weather anomalies such as
drought. For some cases, the largest absolute average projected change (decrease) in
precipitation is paired with relatively large projected changes in seasonal demand For CSU,
TBW, and SDCWA, the greatest projected decreases in precipitation generally occur during the
seasons when these locations historically receive the most rainfall (i.e., summer in CSU and
TBW and winter in SDCWA). For TBW, the 2090 Hotter/Drier projection scenario reflects a
dramatic decrease in total precipitation, which would likely alter water use patterns to an extent
that cannot be adequately captured by current water demand models.
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5. A range of options could assist in adapting to demand impacts.
The case studies and regional assessments point to several possibilities for adapting to the
consequences of climate-induced changes in water demand. Should they continue, some recent
trends in patterns of water use, such as declining rates of per capita domestic use and shifts in
allocations of water among competing uses, may in some regions counteract some of the
additional pressures from warmer temperatures, less precipitation, and urban growth.
Denser urban land development could counteract projected increases in water use by
reducing irrigated landscape areas and lowering the response of water use to climatic conditions.
Furthermore, water pricing strategies could counteract projected increases in water use, either as
a result of more supply scarcity and higher costs of service, or through rate structures designed
exclusively for the purposes of providing incentives, or both.
Increases in water efficiency due to passive and active replacement of inefficient water
fixtures, stemming from current and potential future plumbing standards and an evolving market
for water-efficient products, generally provide a realistic alternative supply (or buffer) for
climate-induced increases in water use.
Conceptually, this represents a tradeoff between demands, where lower indoor or
domestic demands permit more flexibility for supplying higher weather-sensitive demands. For
some of the case study utilities, projected increases in annual average water use are within a
range that could be mitigated by increases in water efficiency. However, greater efficiency
cannot be considered a panacea for some case studies and scenarios, such as for Colorado
Springs, where the sheer magnitude of projected impacts of some scenarios is seemingly out of
reach of efficiency potential alone. Furthermore, the degree to which any given community can
rely on reductions in indoor (or weather-insensitive) uses to offset increases in weather-sensitive
demands may also depend on local and regional water management policies that differentiate and
account for consumptive and non-consumptive uses.
It is possible that impacts of a warmer climate (and possibly also a drier climate in some
regions) could translate into an increased awareness of society of the importance of water in
people’s daily lives, particularly if there is a greater likelihood of water shortages and water
curtailments. Changes in water-using behaviors can extend beyond hardware-driven changes in
the efficiency of water use, and there is evidence that such behavioral change or evolving norms
with respect to water use are already occurring in some areas that are naturally “water-short”
because of current climate and hydrologic conditions.
Finally, projected increases in demand relative to available water supplies may increase
the economic value of water, which may make investments in alternative supplies and system
rehabilitation more economically justified to both water consumers and water providers.
Accommodation of higher demands could also provide opportunities to increase the economic
benefits associated with water. Furthermore, in some places, climate induced increases in
demand could be met with greater regional supply yields. Ultimately, water utility management
of these and other potential effects of climate change, will involve a balance of local, as well as
perhaps more regional, considerations including the willingness of water customers to pay for
new or more reliable water supplies and the cost of accommodating new or altered water
demands.
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APPLICATIONS/RECOMMENDATIONS
Based on the results of the case studies, a major conclusion of this study is that changes
in climate are predicted to vary both in magnitude and seasonally across the regions of the
United States, and the impacts of these changes on water demand will vary because of different
geographical sensitivities of demand to climate and weather. The impacts on demand could be
relatively large for some locations and relatively moderate or even minor for others. The point is
that there is no way of discerning potential impacts without undertaking the types of analyses
demonstrated in the case studies. Therefore, a chief recommendation is that water utilities spend
more time resources studying and modeling climate- and weather-induced water demand
patterns. By applying some of the analytical techniques demonstrated in this study, it is hopeful
that water utilities will gain a more thorough understanding of the importance of climate in
shaping water demands relative to longer-term socioeconomic factors and the role that actual
weather plays in influencing shorter-term demand variability. The insights that are gained about
demand may reveal important lessons and implications for both water supply operations and
planning, and not just in the context of assessing climate change.
This study was intentionally designed to be “demand-centric” in order to help fill a
knowledge gap relative to the knowledge that has been accumulated about the potential effects of
climate change on water supplies. Ultimately, however, for the purposes of understanding the
possible consequences of climate change and related adaptation opportunities, neither water
demand nor supply can be evaluated in isolation. Additional research is needed to develop better
and more integrated analytical frameworks for addressing more directly water supply reliability,
which as a concept captures the notion of demand-supply balance. Integrated analytical
approaches that are capable of jointly simulating demand and supply should be developed or
extended to accommodate evaluation of climate change scenarios. Such methods would enhance
the understanding of risks relative to reference conditions without a change in climate.
In concert with more emphasis on water supply reliability and integrated demand and
supply modeling, it is recommended that more research be undertaken to evaluate climate
scenarios with respect to the possible duration and frequency of future droughts. The effects of
hot and dry spells on demand were only touched upon in this study, as opposed to accumulated
precipitation deficits over longer periods of time which define drought. The downscaled daily
climate data processed during this study suggested the possibility of protracted periods of
relatively high temperatures and low precipitation that far exceeded the length of hot and dry
spells identified in available historical weather record. The predicted impacts on demands would
be considered extreme relative to what would be predicted under historical spells. The
magnification of dry and hot spells could be indicative of the likelihood of more severe and
longer-lasting droughts occurring under future climate. There is currently not a great level of
comfort in using daily climate projection data to characterize the persistence of hot and dry
periods and even less confidence for discerning seasonal, annual or multi-year droughts. Once
there is, however, this will enhance the ability to estimate unrestricted, drought-like demands and
corresponding water supplies during potential future droughts, and thereby improve the quality
of assessments of water supply reliability under future climate.
Future research should also leverage ongoing research on residential and nonresidential
end uses of water, as well as the emerging wealth of information available from advanced
metering infrastructure (AMI) technology. Finer scale measurements of water use at an end use
level could support the analysis and illustration of specific behavioral and technological origins
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of observed levels and fluctuations of water use. Further development of end-use, agent-based
models of water demand could offer the means to simulate detailed responses to changing
climate patterns, as well as present a platform for assessing the effectiveness of specific policies
and coping mechanisms for adapting to climate change.
This study estimated possible climate-induced impacts on water demand for case study
locations by superimposing alternative projections of climate associated with the years 2055 and
2090 upon socioeconomic and other conditions that occurred in the recent past, or, in two cases,
are projected to occur by 2035. Furthermore, the climate scenarios that were addressed, while
considering relevant extremes, do not reflect any judgments regarding the likelihood or relative
probability that they will actually be realized. Together, these methodological constraints
increase uncertainty, but also point to future areas of improvement in demand forecasting and
climate scenario development, which could enhance the ability to create more suitable reference
conditions for evaluating water demand impacts.
Finally, this study has demonstrated that assessment of climate impacts is a complex and
multidimensional challenge, which entails a number of analytical steps, each involving the
collection and processing of substantial amounts of information and a host of uncertainties.
Water planning and management frameworks that are adaptive and anticipatory to changing
conditions offer the greatest promise for meeting these challenges and managing the effects of
uncertainty. Continual measurement and monitoring of water demand and climate trends should
become an established part of the water industry’s research and development portfolio.
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