229
3
Freshwater Resources
Coordinating Lead Authors:
Blanca E. Jiménez Cisneros (Mexico), Taikan Oki (Japan)
Lead Authors:
Nigel W. Arnell (UK), Gerardo Benito (Spain), J. Graham Cogley (Canada), Petra Döll
(Germany), Tong Jiang (China), Shadrack S. Mwakalila (Tanzania)
Contributing Authors:
Thomas Fischer (Germany), Dieter Gerten (Germany), Regine Hock (Canada), Shinjiro Kanae
(Japan), Xixi Lu (Singapore), Luis José Mata (Venezuela), Claudia Pahl-Wostl (Germany),
Kenneth M. Strzepek (USA), Buda Su (China), B. van den Hurk (Netherlands)
Review Editor:
Zbigniew Kundzewicz (Poland)
Volunteer Chapter Scientist:
Asako Nishijima (Japan)
This chapter should be cited as:
Jiménez Cisneros
, B.E., T. Oki, N.W. Arnell, G. Benito, J.G. Cogley, P. Döll, T. Jiang, and S.S. Mwakalila, 2014:
Freshwater resources. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and
Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir,
M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken,
P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom
and New York, NY, USA, pp. 229-269.
3
230
Executive Summary............................................................................................................................................................ 232
3.1. Introduction ............................................................................................................................................................ 234
3.2. Observed Hydrological Changes Due to Climate Change ........................................................................................ 234
3.2.1. Detection and Attribution ................................................................................................................................................................. 234
3.2.2. Precipitation, Evapotranspiration, Soil Moisture, Permafrost, and Glaciers ....................................................................................... 236
3.2.3. Streamflow ....................................................................................................................................................................................... 236
3.2.4. Groundwater .................................................................................................................................................................................... 237
3.2.5. Water Quality ................................................................................................................................................................................... 237
3.2.6. Soil Erosion and Sediment Load ....................................................................................................................................................... 237
3.2.7. Extreme Hydrological Events and their Impacts ................................................................................................................................ 239
3.3. Drivers of Change for Freshwater Resources ......................................................................................................... 240
3.3.1. Climatic Drivers ................................................................................................................................................................................ 240
3.3.2. Non-Climatic Drivers ......................................................................................................................................................................... 240
3.4. Projected Hydrological Changes ............................................................................................................................. 241
3.4.1. Methodological Developments in Hydrological Impact Assessment ................................................................................................. 241
3.4.2. Evapotranspiration, Soil Moisture, and Permafrost ........................................................................................................................... 241
Box 3-1. Case Study: Himalayan Glaciers .................................................................................................................................... 242
3.4.3. Glaciers ............................................................................................................................................................................................. 243
3.4.4. Runoff and Streamflow ..................................................................................................................................................................... 243
3.4.5. Groundwater ..................................................................................................................................................................................... 243
3.4.6. Water Quality ................................................................................................................................................................................... 246
3.4.7. Soil Erosion and Sediment Load ....................................................................................................................................................... 246
3.4.8. Extreme Hydrological Events (Floods and Droughts) ........................................................................................................................ 247
3.5. Projected Impacts, Vulnerabilities, and Risks .......................................................................................................... 248
3.5.1. Availability of Water Resources ........................................................................................................................................................ 248
3.5.2. Water Uses ....................................................................................................................................................................................... 251
3.5.2.1.Agriculture ........................................................................................................................................................................... 251
3.5.2.2.Energy Production ................................................................................................................................................................ 252
3.5.2.3.Municipal Services ............................................................................................................................................................... 252
3.5.2.4.Freshwater Ecosystems ........................................................................................................................................................ 253
3.5.2.5.Other Uses ........................................................................................................................................................................... 253
Table of Contents
231
Freshwater Resources Chapter 3
3
3.6. Adaptation and Managing Risks ............................................................................................................................. 253
3.6.1. Options ............................................................................................................................................................................................. 254
3.6.2. Dealing with Uncertainty in Future Climate Change ......................................................................................................................... 254
3.6.3. Costs of Adaptation to Climate Change ............................................................................................................................................ 256
3.6.4. Adaptation in Practice in the Water Sector ....................................................................................................................................... 256
3.7. Linkages with Other Sectors and Services .............................................................................................................. 257
3.7.1. Impacts of Adaptation in Other Sectors on Freshwater Systems ....................................................................................................... 257
3.7.2. Climate Change Mitigation and Freshwater Systems ........................................................................................................................ 257
3.7.2.1.Impact of Climate Change Mitigation on Freshwater Systems ............................................................................................. 257
3.7.2.2.Impact of Water Management on Climate Change Mitigation ............................................................................................. 258
3.8. Research and Data Gaps ......................................................................................................................................... 258
References ......................................................................................................................................................................... 259
Frequently Asked Questions
3.1: How will climate change affect the frequency and severity of floods and droughts? ....................................................................... 247
3.2: How will the availability of water resources be affected by climate change? ................................................................................... 251
3.3: How should water management be modified in the face of climate change? .................................................................................. 253
3.4: Does climate change imply only bad news about water resources? ................................................................................................. 257
232
Chapter 3 Freshwater Resources
3
Executive Summary
K
ey Risks at the Global Scale
Freshwater-related risks of climate change increase significantly with increasing greenhouse gas (GHG) concentrations (robust
evidence, high agreement). {3.4, 3.5} Modeling studies since AR4, with large but better quantified uncertainties, have demonstrated clear
differences between global futures with higher emissions, which have stronger adverse impacts, and those with lower emissions, which cause
less damage and cost less to adapt to. {Table 3-2} For each degree of global warming, approximately 7% of the global population is projected
to be exposed to a decrease of renewable water resources of at least 20% (multi-model mean). By the end of the 21st century, the number of
people exposed annually to the equivalent of a 20th-century 100-year river flood is projected to be three times greater for very high emissions
(Representative Concentration Pathway 8.5 (RCP8.5)) than for very low emissions (RCP2.6) (multi-model mean) for the fixed population distri-
bution at the level in the year 2005. {Table 3-2, 3.4.8}
Climate change is projected to reduce renewable surface water and groundwater resources significantly in most dry subtropical
regions (robust evidence, high agreement). {3.4, 3.5} This will intensify competition for water among agriculture, ecosystems,
settlements, industry, and energy production, affecting regional water, energy, and food security (limited evidence, medium to
high agreement). {3.5.1, 3.5.2, Box CC-WE}
In contrast, water resources are projected to increase at high latitudes. Proportional changes
are typically one to three times greater for runoff than for precipitation. The effects on water resources and irrigation requirements of changes
in vegetation due to increasing GHG concentrations and climate change remain uncertain. {Box CC-VW}
So far there are no widespread observations of changes in flood magnitude and frequency due to anthropogenic climate change,
but projections imply variations in the frequency of floods (limited evidence, medium agreement).
Flood hazards are projected to
increase in parts of South, Southeast, and Northeast Asia; tropical Africa; and South America (limited evidence, medium agreement). Since the
mid-20th century, socioeconomic losses from flooding have increased mainly due to greater exposure and vulnerability (high confidence).
Global flood risk will increase in the future partly due to climate change (limited evidence, medium agreement). {3.2.7, 3.4.8}
Climate change is likely to increase the frequency of meteorological droughts (less rainfall) and agricultural droughts (less soil
moisture) in presently dry regions by the end of the 21st century under the RCP8.5 scenario (medium confidence). {WGI AR5
Chapter 12} This is likely to increase the frequency of short hydrological droughts (less surface water and groundwater) in these
regions (medium evidence, medium agreement). {3.4.8}
Projected changes in the frequency of droughts longer than 12 months are more
uncertain, because these depend on accumulated precipitation over long periods. There is no evidence that surface water and groundwater
drought frequency has changed over the last few decades, although impacts of drought have increased mostly due to increased water demand.
{3.5.1}
Climate change negatively impacts freshwater ecosystems by changing streamflow and water quality (medium evidence, high
agreement).
Quantitative responses are known in only a few cases. Except in areas with intensive irrigation, the streamflow-mediated
ecological impacts of climate change are expected to be stronger than historical impacts owing to anthropogenic alteration of flow regimes by
water withdrawals and the construction of reservoirs. {Box CC-RF, 3.5.2.4}
Climate change is projected to reduce raw water quality, posing risks to drinking water quality even with conventional treatment
(medium evidence, high agreement).
The sources of the risks are increased temperature, increases in sediment, nutrient and pollutant
loadings due to heavy rainfall, reduced dilution of pollutants during droughts, and disruption of treatment facilities during floods.
{3.2.5, Figure 3-2, 3.4.6, 3.5.2.3}
In regions with snowfall, climate change has altered observed streamflow seasonality, and increasing alterations due to climate
change are projected (robust evidence, high agreement). {Table 3-1, 3.2.3, 3.2.7, 3.4.5, 3.4.6, 26.2.2}
Except in very cold regions,
warming in the last decades has reduced the spring maximum snow depth and brought forward the spring maximum of snowmelt discharge;
smaller snowmelt floods, increased winter flows, and reduced summer low flows have all been observed. River ice in Arctic rivers has been
observed to break up earlier. {3.2.3, 28.2.1.1}
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Freshwater Resources Chapter 3
Because nearly all glaciers are too large for equilibrium with the present climate, there is a committed water resources change
during much of the 21st century, and changes beyond the committed change are expected due to continued warming; in glacier-
fed rivers, total meltwater yields from stored glacier ice will increase in many regions during the next decades but decrease
thereafter (robust evidence, high agreement).
Continued loss of glacier ice implies a shift of peak discharge from summer to spring, except
in monsoonal catchments, and possibly a reduction of summer flows in the downstream parts of glacierized catchments. {3.4.3}
There is little or no observational evidence yet that soil erosion and sediment loads have been altered significantly due to
changing climate (limited evidence, medium agreement). However, increases in heavy rainfall and temperature are projected to change
soil erosion and sediment yield, although the extent of these changes is highly uncertain and depends on rainfall seasonality, land cover, and
soil management practices. {3.2.6, 3.4.7}
Adaptation, Mitigation, and Sustainable Development
Of the global cost of water sector adaptation, most is necessary in developing countries where there are many opportunities
for anticipatory adaptation (medium evidence, high agreement). There is limited published information on the water sector costs of
adaptation at the local level. {3.6.1, 3.6.3}
An adaptive approach to water management can address uncertainty due to climate change (limited evidence, high agreement).
Adaptive techniques include scenario planning, experimental approaches that involve learning from experience, and the development of flexible
and low-regret solutions that are resilient to uncertainty. Barriers to progress include lack of human and institutional capacity, financial
resources, awareness, and communication. {3.6.1, 3.6.2, 3.6.4}
Reliability of water supply, which is expected to suffer from increased variability of surface water availability, may be enhanced
by increased groundwater abstractions (limited evidence, high agreement). This adaptation to climate change is limited in regions
where renewable groundwater resources decrease due to climate change. {3.4.5, 3.4.8, 3.5.1}
Some measures to reduce GHG emissions imply risks for freshwater systems (medium evidence, high agreement). If irrigated,
bioenergy crops make water demands that other mitigation measures do not. Hydropower has negative impacts on freshwater ecosystems,
which can be reduced by appropriate management. Carbon capture and storage can decrease groundwater quality. In some regions,
afforestation can reduce renewable water resources but also flood risk and soil erosion. {3.7.2.1, Box CC-WE}
234
Chapter 3 Freshwater Resources
3
3.1. Introduction
Changes in the hydrological cycle due to climate change can lead to
diverse impacts and risks, and they are conditioned by and interact with
n
on-climatic drivers of change and water management responses
(Figure 3-1). Water is the agent that delivers many of the impacts of
climate change to society, for example, to the energy, agriculture, and
transport sectors. Even though water moves through the hydrological
cycle, it is a locally variable resource, and vulnerabilities to water-related
hazards such as floods and droughts differ between regions. Anthropogenic
climate change is one of many stressors of water resources. Non-
climatic drivers such as population increase, economic development,
urbanization, and land use or natural geomorphic changes also challenge
the sustainability of resources by decreasing water supply or increasing
demand. In this context, adaptation to climate change in the water
sector can contribute to improving the availability of water.
The key messages with high or very high confidence from the Working
Group II Fourth Assessment Report (AR4; IPCC, 2007) in respect to
freshwater resources were:
• The observed and projected impacts of climate change on freshwater
systems and their management are due mainly to increases in
temperature and sea level, local changes of precipitation, and
changes in the variability of those quantities.
• Semiarid and arid areas are particularly exposed.
• Warmer water, more intense precipitation, and longer periods of
low flow reduce water quality, with impacts on ecosystems, human
health, and reliability and operating costs of water services.
• Climate change affects water management infrastructure and
practice.
•
Adaptation and risk management practices have been developed
for the water sector in some countries and regions.
• The negative impacts of climate change on freshwater systems
outweigh its benefits.
This chapter assesses hydrological changes due to climate change,
based mainly on research published since AR4. Current gaps in research
and data are summarized in Section 3.8. For further information on
observed trends in the water cycle, please see Chapter 2 of the Working
Group I (WGI) contribution to this assessment. See WGI AR5 Chapter 4
for freshwater in cold regions and WGI AR5 Chapters 10 for detection
and attribution, 11 for near-term projections, and 12 for long-term
projections of climate change. In this Working Group II contribution,
impacts on aquatic ecosystems are discussed in Chapter 4 (see also
Section 3.5.2.4). Chapter 7 describes the impacts of climate change on
food production (see also Section 3.5.2.1 for the impact of hydrological
changes on the agricultural sector). The health effects of changes in
water quality and quantity are covered in Chapter 11, and regional
vulnerabilities related to freshwater in Chapters 21 to 30. Sections 3.2.7,
3.4.8, and 3.6.3 discuss impact and adaptation costs related to water
resources; these costs are assessed more broadly in Chapter 10.
3.2. Observed Hydrological Changes
Due to Climate Change
3.2.1. Detection and Attribution
A documented hydrological change is not necessarily due to anthropogenic
climate change. Detection entails showing, usually statistically, that part
Impacts and risks
Hydrological changes
Climate changes
Non-climatic changes
Exposure and
vulnerability
DRIVERS RESPONSES
Water demand
changes
Land use,
land cover
changes
Socioeconomic development
GDP, population, …
Adaptation of water
management to climate change
urbanization,
forest, …
municipal,
industrial,
energy,
agricultural
Interactions of freshwater
systems and
climate change mitigation
for humans
for freshwater ecosystems
(Section 3.5)
(Section 3.3.1)
(Sections 3.3 and 3.4)
(Section 3.6)
(Section 3.7.2)(Section 3.3.2)
surface water and groundwater
quantity and quality
timing and extreme events
precipitation, temperature, sea level,
CO
2
concentration, …
Figure 3-1 | Framework (boxes) and linkages (arrows) for considering impacts of climatic and social changes on freshwater systems, and consequent impacts on and risks for humans and freshwater
ecosystems. Both climatic (Section 3.3.1) and non-climatic (Section 3.3.2) drivers have changed natural freshwater systems (Section 3.2) and are expected to continue to do so (Section 3.4). They also
stimulate adaptive measures (Section 3.6). Hydrological and water management changes interact with each other and with measures to mitigate climate change (Section 3.7.2). Adaptive measures
influence the exposure and vulnerability of human beings and ecosystems to water-related risks (Section 3.5).
235
3
Freshwater Resources Chapter 3
of the documented change is not due to natural variability of the water
cycle (Chapter 18; WGI AR5 Chapter 10). For robust attribution to climatic
change, all the drivers of the hydrological change must be identified, with
confidence levels assigned to their contributions. Human contributions
such as water withdrawals, land use change, and pollution mean that
this is usually difficult. Nevertheless, many hydrological impacts can be
attributed confidently to their climatic drivers (Table 3-1). End-to-end
attribution, from human climate-altering activities to impacts on
freshwater resources, is not attempted in most studies, because it requires
experiments with climate models in which the external natural and
anthropogenic forcing is “switched off.” However, climate models do
not currently simulate the water cycle at fine enough resolution for
attribution of most catchment-scale hydrological impacts to anthropogenic
climate change. Until climate models and impact models become better
Observed change Attributed to Reference
1 Changed runoff (global, 1960–1994) Mainly climatic change, and to a lesser degree CO
2
increase and land use
change
Gerten et al. (2008); Piao et al.
(2007); Alkama et al. (2011)
2 Reduced runoff (Yellow River, China) Increased temperature; only 35% of reduction attributable to human
withdrawals
Piao et al. (2010)
3 Earlier annual peak discharge (Russian Arctic, 1960–2001) Increased temperature and earlier spring thaw Shiklomanov et al. (2007)
4 Earlier annual peak discharge (Columbia River, western USA, 1950–1999) Anthropogenic warming Hidalgo et al. (2009)
5 Glacier meltwater yield greater in 1910–1940 than in 1980–2000
(European Alps)
Glacier shrinkage forced by comparable warming rates in the two periods Collins (2008)
6 Decreased dry-season discharge (Peru, 1950s–1990s) Decreased glacier extent in the absence of a clear trend in precipitation Baraer et al. (2012)
7 Disappearance of Chacaltaya Glacier, Bolivia (2009) Ascent of freezing isotherm at 50 meters per decade, 1980s–2000s Rosenzweig et al. (2007)
8 More intense extremes of precipitation (northern tropics and mid-latitudes,
1951–1999)
Anthropogenic greenhouse gas emissions Min et al. (2011)
9 Fraction of risk of fl ooding (England and Wales, autumn 2000) Extreme precipitation attributable to anthropogenic greenhouse radiation Pall et al. (2011)
10 Decreased recharge of karst aquifers (Spain, 20th century) Decreased precipitation, and possibly increased temperature; multiple
confounding factors
Aguilera and Murillo (2009)
11 Decreased groundwater recharge (Kashmir, 1985–2005) Decreased winter precipitation Jeelani (2008)
12 Increased dissolved organic carbon in upland lakes (UK, 1988–2003) Increased temperature and precipitation; multiple confounding factors Evans et al. (2005)
13 Increased anoxia in a reservoir, moderated during ENSO (El Niño-Southern
Oscillation) episodes (Spain, 1964–1991 and 1994–2007)
Decreased runoff due to decreased precipitation and increased evaporative
demand
Marcé et al. (2010)
14 Variable fecal pollution in a saltwater wetland (California, 1969–2000) Variable storm runoff; 70% of coliform variability attributable to variable
precipitation
Pednekar et al. (2005)
15 Nutrient fl ushing from swamps, reservoirs (North Carolina, 1978–2003) Hurricanes Paerl et al. (2006)
16 Increased lake nutrient content (Victoria, Australia, 1984–2000) Increased air and water temperature Tibby and Tiller (2007)
Table 3-1 | Selected examples, mainly from Section 3.2, of the observation, detection, and attribution of impacts of climate change on freshwater resources. Observed
hydrological changes are attributed here to their climatic d rivers, not all of which are necessarily anthropogenic.
Very low Low Medium
Degree of confidence in attribution
High Very high
Very low
Streamflow
Cryosphere
Extremes
Groundwater
Symbols 1-16: see table below
W
ater quality
Low Medium
Degree of confidence in detection
High Very high
Unfilled symbols: attributed to
anthropogenic climate change
(end-to-end attribution)
Filled symbols: attributed to
observed climate change
1
4
8
9
2
10
11
13
12
14
15
16
56
7
3
236
Chapter 3 Freshwater Resources
3
i
ntegrated, it is necessary to rely heavily on multistep attribution, in
which hydrological changes are shown to result from climatic changes
that may in turn result partly from human activities.
Extreme hydrological events, such as floods, prompt speculation about
whether they are “caused” by climate change. Climate change can indeed
alter the probability of a particular event. However, to estimate the
alteration reliably it is necessary to quantify uncertainties due to natural
variability in the changed and the unchanged climates, and also—
because of the need for model simulations—uncertainties due to
limited ability to simulate the climate.
The probability or risk of the extreme event can be measured by recording
the fraction of events beyond some threshold magnitude. Call this
fraction r
c
trl
in the simulated actual climate and r
e
xpt
in the simulated
climate in which there is no anthropogenic forcing, and suppose there
are many paired instances of r
ctrl
and r
expt
, with the ratio of risks in each
pair given by F = r
expt
/r
ctrl
. The distribution of risk ratios F describes the
likelihood that the climate change has altered the risk. Several thousand
pairs of such simulations were run to estimate the risk ratio for the
floods in England and Wales in autumn 2000 (Pall et al., 2011). Each pair
started from a unique initial state that differed slightly from a common
reference state, and was obtained with a seasonal forecast model driven
by patterns of attributable warming found beforehand from four climate-
model simulations of the 20th century. The forecast model was coupled
to a model of basin-scale runoff and channel-scale hydraulics. It is not
probable that such exercises will become routine for assessing single-
event risks in, for example, the insurance industry, because the necessary
amount of computation is so formidable. Nevertheless, the result was
compelling: in each of the four sets of simulation pairs, the risk increased
greatly on average in the runs forced by anthropogenic greenhouse
radiation. In aggregate, the most probable amount of increase was two-
to threefold, and at most a few percent of the simulation pairs suggested
that anthropogenic forcing actually decreased the risk. This summary is
worded carefully: the thousands of simulation pairs were needed for
quantifying the uncertainties, which led unavoidably to a spread of
likelihoods and thus to statements about uncertainty about risk that
are themselves uncertain.
3.2.2. Precipitation, Evapotranspiration, Soil Moisture,
Permafrost, and Glaciers
Global trends in precipitation from several different datasets during
1901–2005 are statistically insignificant (Bates et al., 2008; WGI AR5
Chapter 2). According to regional observations, most droughts and
extreme rainfall events of the 1990s and 2000s have been the worst
since the 1950s (Arndt et al., 2010), and certain trends in total and
extreme precipitation amounts are observed (WGI AR5 Chapter 2).
Most regional changes in precipitation are attributed either to internal
variability of the atmospheric circulation or to global warming (Lambert
et al., 2004; Stott et al., 2010). It was estimated that the 20th century
anthropogenic forcing contributed significantly to observed changes in
global and regional precipitation (Zhang et al., 2007). Changes in snowfall
amounts are indeterminate, as for precipitation; however, consistent
with observed warming, shorter snowfall seasons are observed over most
of the Northern Hemisphere, with snowmelt seasons starting earlier
(
Takala et al., 2009). In Norway, increased temperature at lower
altitudes has reduced the snow water equivalent (Skaugen et al., 2012).
Steady decreases since the 1960s of global and regional actual
evapotranspiration and pan evaporation have been attributed to changes
in precipitation, diurnal temperature range, aerosol concentration, (net)
solar radiation, vapor pressure deficit, and wind speed (Fu et al., 2009;
McVicar et al., 2010; Miralles et al., 2011; Wang A. et al., 2011). Regional
downward and upward trends in soil moisture content have been
calculated for China from 1950 to 2006, where longer, more severe, and
more frequent soil moisture droughts have been experienced over 37%
of the land area (Wang A. et al., 2011). This is supported by detected
increases since the 1960s in dry days and a prolongation of dry periods
(Gemmer et al., 2011; Fischer et al., 2013), and can be attributed to
increases in warm days and warm periods (Fischer et al., 2011).
Decreases in the extent of permafrost and increases in its average
temperature are widely observed, for example, in some regions of the
Arctic and Eurasia (WGI AR5 Chapter 4) and the Andes (Rabassa, 2009).
Active layer depth and permafrost degradation are closely dependent
on soil ice content. In steep terrain, slope stability is highly affected by
changes in permafrost (Harris et al., 2009). The release of greenhouse
gases (GHGs) due to permafrost degradation can have unprecedented
impacts on the climate, but these processes are not yet well represented
in global climate models (Grosse et al., 2011). In most parts of the world
glaciers are losing mass (Gardner et al., 2013). For example, almost all
glaciers in the tropical Andes have been shrinking rapidly since the
1980s (Rabassa, 2009; Rabatel et al., 2013); similarly, Himalayan
glaciers are losing mass at present (Bolch et al., 2012).
3.2.3. Streamflow
Detected trends in streamflow are generally consistent with observed
regional changes in precipitation and temperature since the 1950s. In
Europe, streamflow (1962–2004) decreased in the south and east and
generally increased elsewhere (Stahl et al., 2010, 2012), particularly in
northern latitudes (Wilson et al., 2010). In North America (1951–2002),
increases were observed in the Mississippi basin and decreases in the
U.S. Pacific Northwest and southern Atlantic–Gulf regions (Kalra et al.,
2008). In China, a decrease in streamflow in the Yellow River (1960–
2000) is consistent with a reduction of 12% in summer and autumn
precipitation, whereas the Yangtze River shows a small increase in
annual streamflow driven by an increase in monsoon rains (Piao et al.,
2010; see Table 3-1). These and other streamflow trends must be
interpreted with caution (Jones, 2011) because of confounding factors
such as land use changes (Zhang and Schilling, 2006), irrigation (Kustu
et al., 2010), and urbanization (Wang and Cai, 2010).
In a global analysis of simulated streamflows (1948–2004), about one-
third of the top 200 rivers (including the Congo, Mississippi, Yenisei,
Paraná, Ganges, Columbia, Uruguay, and Niger) showed significant
trends in discharge; 45 recorded decreases and only 19 recorded
increases (Dai et al., 2009). Decreasing trends in low and mid-latitudes
are consistent with recent drying and warming in West Africa, southern
Europe, south and east Asia, eastern Australia, western Canada and the
USA, and northern South America (Dai, 2013). The contribution to
237
3
Freshwater Resources Chapter 3
o
bserved streamflow changes due to decreased stomatal opening of
many plant species at higher carbon dioxide (CO
2
) concentration
remains disputed (Box CC-VW).
In regions with seasonal snow storage, warming since the 1970s has led
to earlier spring discharge maxima (robust evidence, high agreement)
and has increased winter flows because more winter precipitation falls
as rain instead of snow (Clow, 2010; Korhonen and Kuusisto, 2010; Tan
et al., 2011). There is robust evidence of earlier breakup of river ice in
Arctic rivers (de Rham et al., 2008; Smith, 2000). Where streamflow is
lower in summer, decrease in snow storage has exacerbated summer
dryness (Cayan et al., 2001; Knowles et al., 2006).
3.2.4. Groundwater
Attribution of observed changes in groundwater level, storage, or
discharge to climatic changes is difficult owing to additional influences
of land use changes and groundwater abstractions (Stoll et al., 2011).
Observed trends are largely attributable to these additional influences.
The extent to which groundwater abstractions have already been
affected by climate change is not known. Both detection of changes in
groundwater systems and attribution of those changes to climatic
changes are rare owing to a lack of appropriate observation wells and
a small number of studies. Observed decreases of the discharge of
groundwater-fed springs in Kashmir (India) since the 1980s were
attributed to observed precipitation decreases (Jeelani, 2008; Table 3-1).
A model-based assessment of observed decreases of groundwater levels
in four overexploited karst aquifers in Spain led to the conclusion that
groundwater recharge not only decreased strongly during the 20th
century due to the decreasing precipitation but also that groundwater
recharge as a fraction of observed precipitation declined progressively,
possibly indicating an increase in evapotranspiration (Aguilera and
Murillo, 2009; Table 3-1).
3.2.5. Water Quality
Most observed changes of water quality due to climate change (Table
3-1; Figure 3-2) are known from isolated studies, mostly of rivers or
lakes in high-income countries, of a small number of variables. In
addition, even though some studies extend over as many as 80 years,
most are short term. For lakes and reservoirs, the most frequently
reported change is more intense eutrophication and algal blooms at
higher temperatures, or shorter hydraulic retention times and higher
nutrient loads resulting from increased storm runoff (medium to robust
evidence, high agreement). Increased runoff results in greater loads of
salts, fecal coliforms, pathogens, and heavy metals (Pednekar et al.,
2005; Paerl et al., 2006; Tibby and Tiller, 2007; Boxall et al., 2009) (robust
evidence, medium to high agreement, depending on the pollutant). In
some cases there are associated impacts on health. For instance,
hospital admissions for gastrointestinal illness in elderly people
increased by 10% when turbidity increased in the raw water of a
drinking water plant even when treated using conventional procedures
(Schwartz et al., 2000). However, positive impacts were also reported.
For example, the risk of eutrophication was reduced when nutrients
were flushed from lakes and estuaries by more frequent storms and
h
urricanes (Paerl and Huisman, 2008). For rivers, all reported impacts
on water quality were negative. Greater runoff, instead of diluting
pollution, swept more pollutants from the soil into watercourses (robust
evidence, medium to high agreement) (Boxall et al., 2009; Loos et al.,
2009; Benítez-Gilabert et al., 2010; Gascuel-Odoux et al., 2010; Howden
et al., 2010; Saarinen et al., 2010; Tetzlaff et al., 2010; Macleod et al.,
2012). Increased organic matter content impaired the quality of
conventionally treated drinking water (Weatherhead and Howden,
2009). In streams in semiarid and arid areas, temperature changes had
a stronger influence on the increase of organic matter, nitrates, and
phosphorus than precipitation changes (Ozaki et al., 2003; Chang, 2004;
Benítez-Gilabert et al., 2010) (limited evidence, medium agreement).
Studies of impacts on groundwater quality are limited and mostly report
elevated concentrations of fecal coliforms during the rainy season or
after extreme rain events (medium evidence, high agreement), with
varying response times (Curriero et al., 2001; Tumwine et al., 2002, 2003;
Auld et al., 2004; Jean et al., 2006; Seidu et al., 2013). Given the
widespread use of groundwater for municipal supply and minimal or
lacking treatment of drinking water in poor regions, increased pollution
is a source of concern (Jean et al., 2006; Seidu et al., 2013). Another
concern is the nonlinearity (except for temperature) of relationships
between water quality and climatic variables (limited evidence, medium
agreement). In general, the linkages between observed effects on water
quality and climate should be interpreted cautiously and at the local
level, considering the type of water body, the pollutant of concern, the
hydrological regime, and the many other possible sources of pollution
(high confidence; Senhorst and Zwolsman, 2005; Whitehead et al.,
2009a; Benítez-Gilabert et al., 2010; Howden et al., 2010; Kundzewicz
and Krysanova, 2010; Ventela et al., 2011).
3.2.6. Soil Erosion and Sediment Load
Precipitation extremes in many regions have increased since 1950
(Seneviratne et al., 2012), which suggests an increase in rainfall erosivity
that would enhance soil erosion and stream sediment loads. A warmer
climate may affect soil moisture, litter cover, and biomass production
and can bring about a shift in winter precipitation from snow to more
erosive rainfall (Kundzewicz et al., 2007) or, in semiarid regions, an
increase in wildfires with subsequent rainfall leading to intense
erosive events (Nyman et al., 2011; Bussi et al., 2013). The effects of
climate change on soil erosion and sediment load are frequently
obscured by human agricultural and management activities (Walling,
2009).
Only few studies have isolated the contribution of climate change to
observed trends in soil erosion and sediment load. In the Yellow River
basin, where soil erosion results mostly from heavy rainfall, reduced
precipitation (~10%) contributed about 30% to a total reduction in
stream sediment loads reaching the sea during 2000–2005, compared
to 1950–1968, with the remaining 70% attributable to sediment
trapping in reservoirs and soil conservation measures (Wang et al., 2007;
Miao et al., 2011). Dai et al. (2008), analyzing the decrease in sediment
load of the Yangtze River over 1956–2002, found that climate change
was responsible for an increase of about 3 ± 2%; most of the decline
in its lower reaches was due to dam construction (Three Gorges Dam)
and soil conservation measures.
238
Chapter 3 Freshwater Resources
3
Total renewable freshwater resources in mm year
–1
(1961–1990)
Study
locations
0
10 50 100 200 300 500 1000 7670
2
7
10
13
17
6
9
1
16
3
4
14
15
8
19
5
18
12
1
1
Figure 3-2 | Observations of the impacts of climate on water quality.
Location Study period Observation on water quality Reference
1 Danube River, Bratislava,
Slovakia
1926–2005 The water temperature is rising but the trend of the weighted long-term average temperature values
resulted close to zero because of the interannual distribution of the mean monthly discharge.
Pekarova et al. (2008)
2 Purrumbete, Colac and Bullen
Merri Lakes, Victoria, Australia
1984–2000 The increases in salinity and nutrient content were associated with the air temperature increase;
salinity in addition was associated with variations in the effective precipitation.
Tibby and Tiller (2007)
3 Lake Tahoe, California and
Nevada States, USA
1970–2007 Thermal stability resulting from a higher ambient temperature decreased the dissolved oxygen content. Sahoo et al. (2010)
4 Neuse River Estuary, North
Carolina, USA
1979–2003 Intense storms and hurricanes fl ushed nutrients from the estuary, reducing eutrophic conditions and
the risk of algal blooms.
Paerl et al., (2006); Paerl
and Huisman (2008)
5 River Meuse, western Europe 1976–2003 Increase of water temperature and the content of major elements and some heavy metals were
associated with droughts. Algal blooms resulted from a higher nutrient content due to higher water
temperature and longer residence time.
van Vliet and Zwolsman
(2008)
6 Lake Taihu, Wuxi, Jiangsu,
China
2007 The lake, already suffering from periodic cyanobacterial blooms, was affected by a very intensive bloom
in May 2007 attributed to an unusually warm spring and leading to the presence of Microcystis toxins
in the water. This forced two million people to drink bottled water for at least one week.
Qin et al. (2010)
7 Sau Reservoir, Spain 1964–2007 Stream fl ow variations were of greater signifi cance than temperature increases in the depletion of
dissolved oxygen.
Marcé et al. (2010)
8 22 upland waters in UK 1988–2002 Dissolved organic matter increased due to temperature increase but also due to rainfall variations, acid
deposition, land use, and CO
2
enrichment.
Evans et al. (2005)
9 Coastal rivers from western
Finland
1913–2007 Low pH values are associated with higher rainfall and river discharge in an acid sulfate soil basin.
Saarinen et al. (2010)
1961–2007 Critical values of dissolved organic carbon is associated with higher rainfall and river discharge.
10 15 pristine mountain rivers,
northern Spain
1973–2005 For a semiarid area, there is a clear relationship between increases in air temperature and a higher
nutrient and dissolved organic carbon content.
Benítez-Gilabert et al.
(2010)
11 30 coastal rivers and
groundwater of western
France
1973–2007
(2–6 years)
Interannual variations in the nutrient content associated with air temperature, rainfall, and
management practices changes. These effects were not observed in groundwater because of the delay
in response time and the depuration of soil on water.
Gascuel-Odoux et al.
(2010)
12 Girnock, Scotland 14 months Higher risks of fecal pollution are clearly related to rainfall during the wet period. Tetzlaff et al. (2010)
13 27 rivers in Japan 1987–1995 Increases in organic matter and sediment and decreases in the dissolved oxygen content are associated
with increases in ambient temperature. Precipitation increases and variations are associated with an
increase in the organic matter, sediments, and chemical oxygen demand content in water.
Ozaki et al. (2003)
14 Conestoga River Basin,
Pennsylvania, USA
1977–1997 There is a close association between annual loads of total nitrogen and annual precipitation increases.Chang (2004)
15 USA 1948–1994 Increased rainfall and runoff are associated with site-specifi c outbreaks of waterborne disease.Curriero et al. (2001)
16 Northern and eastern Uganda 1999–2001,
2004, 2007
Elevated concentrations of fecal coliforms are observed in groundwater-fed water supplies during the
rainy season.
Tumwine et al. (2002,
2003); Taylor et al. (2009)
17 Taiwan, China 1998 The probability of detecting cases of enterovirus infection was greater than 50%, with rainfall rates
>31 mm h
–1
. The higher the rainfall rate, the higher the probability of an enterovirus epidemic.
Jean et al. (2006)
18 Rhine Basin 1980–2001 Nutrient content in rivers followed seasonal variations in precipitation which were also linked to
erosion within the basin.
Loos et al. (2009)
19 River Thames, England 1868–2008 Higher nutrient contents were associated to changes in river runoff and land use. Howden et al. (2010)
239
3
Freshwater Resources Chapter 3
P
otential impacts of climate change on soil erosion and sediment
production are of concern in regions with pronounced glacier retreat
(Walling, 2009). Glacial rivers are expected to discharge more meltwater,
which may increase sediment loads. However, the limited evidence is
inconclusive for a global diagnosis of sediment load changes; there are
both decreasing (e.g., Iceland; Lawler et al., 2003) and increasing trends
(Patagonia; Fernandez et al., 2011). So far, there is no clear evidence
that the frequency or magnitude of shallow landslides has changed over
past decades (Huggel et al., 2012), even in regions with relatively complete
event records (e.g., Switzerland; Hilker et al., 2009). Increased landslide
impacts (measured by casualties or losses) in south and Southeast Asia,
where landslides are triggered predominantly by monsoon and tropical
cyclone activity, are largely attributed to population growth leading to
increased exposure (Petley, 2012).
In summary, there is limited evidence and low agreement that
anthropogenic climate change has made a significant contribution to
soil erosion, sediment loads, and landslides. The available records are
limited in space and time, and evidence suggests that, in most cases,
the impacts of land use and land cover changes are more significant
than those of climate change.
3.2.7. Extreme Hydrological Events and their Impacts
There is low confidence, due to limited evidence, that anthropogenic
climate change has affected the frequency and magnitude of floods
at global scale (Kundzewicz et al., 2013). The strength of the evidence
is limited mainly by lack of long-term records from unmanaged
catchments. Moreover, in the attribution of detected changes it is
difficult to distinguish the roles of climate and human activities (Section
3.2.1). However, recent detection of trends in extreme precipitation
and discharge in some catchments implies greater risks of flooding at
regional scale (medium confidence). More locations show increases in
heavy precipitation than decreases (Seneviratne et al., 2012). Flood
damage costs worldwide have been increasing since the 1970s,
although this is partly due to increasing exposure of people and assets
(Handmer et al., 2012).
There is no strong evidence for trends in observed flooding in the USA
(Hirsch and Ryberg, 2012), Europe (Mudelsee et al., 2003; Stahl et al.,
2010; Benito and Machado, 2012; Hannaford and Hall, 2012), South
America, and Africa (Conway et al., 2009). However, at smaller spatial
scales, an increase in annual maximum discharge has been detected in
parts of northwestern Europe (Petrow and Merz, 2009; Giuntoli et al.,
2012; Hattermann et al., 2012), while a decrease was observed in
southern France (Giuntoli et al., 2012). Flood discharges in the lower
Yangtze basin increased over the last 40 years (Jiang et al., 2008; Zhang
et al., 2009), and both upward and downward trends were identified in
four basins in the northwestern Himalaya (Bhutiyani et al., 2008). In
Australia, only 30% of 491 gauge stations showed trends at the 10%
significance level, with decreasing magnitudes in southern regions and
increasing magnitudes in the northern regions (Ishak et al., 2010). In
Arctic rivers dominated by a snowmelt regime, there is no general trend
in flood magnitude and frequency (Shiklomanov et al., 2007). In Nordic
countries, significant changes since the mid-20th century are mostly
toward earlier seasonal flood peaks, but flood magnitudes show
c
ontrasting trends, driven by temperature and precipitation, in basins
with and without glaciers increasing peaks in the former and decreasing
peaks in the latter (Wilson et al., 2010; Dahlke et al., 2012). Significant
trends at almost one-fifth of 160 stations in Canada were reported,
most of them decreases in snowmelt-flood magnitudes (Cunderlik and
Ouarda, 2009). Similar decreases were found for spring and annual
maximum flows (Burn et al., 2010).
Attribution has been addressed by Hattermann et al. (2012), who
identified parallel trends in precipitation extremes and flooding in
Germany, which for the increasing winter floods are explainable in
terms of increasing frequency and persistence of circulation patterns
favorable to flooding (Petrow et al., 2009). It is very likely that the
observed intensification of heavy precipitation is largely anthropogenic
(Min et al., 2011; see also Section 3.2.1).
Socioeconomic losses from flooding are increasing (high confidence),
although attribution to anthropogenic climate change is established
only seldom (Pall et al., 2011). Reported flood damages (adjusted for
inflation) have increased from an average of US$7 billion per year in
the 1980s to about US$24 billion per year in 2011 (Kundzewicz et al.,
2013). Economic, including insured, flood disaster losses are higher in
developed countries, while fatality rates and economic losses expressed
as a proportion of gross domestic product are higher in developing
countries. Since 1970, the annual number of flood-related deaths has
been in the thousands, with more than 95% in developing countries
(Handmer et al., 2012). There is high confidence (medium evidence, high
agreement) that greater exposure of people and assets, and societal
factors related to population and economic growth, contributed to the
increased losses (Handmer et al., 2012; Kundzewicz et al., 2013). When
damage records are normalized for changes in exposure and vulnerability
(Bouwer, 2011), most studies find no contribution of flooding trends to
the trend in losses (Barredo, 2009; Hilker et al., 2009; Benito and
Machado, 2012), although there are exceptions (Jiang et al., 2005;
Chang et al., 2009).
Assessments of observed changes in “drought” depend on the definition
of drought (meteorological, agricultural, or hydrological) and the chosen
drought index (e.g., consecutive dry days, Standardized Precipitation
Index (SPI), Palmer Drought Severity Index (PDSI), Standardized Runoff
Index (SRI); see Seneviratne et al., 2012). Meteorological (rainfall) and
agricultural (soil moisture) droughts have become more frequent since
1950 (Seneviratne et al., 2012) in some regions, including southern
Europe and western Africa, but in others (including the southern USA;
Chen et al., 2012) there is no evidence of change in frequency (WGI
AR5 Chapter 2).
Very few studies have considered variations over time in hydrological
(streamflow) drought, largely because there are few long records from
catchments without direct human interventions. A trend was found
toward lower summer minimum flows for 1962–2004 in small catchments
in southern and Eastern Europe, but there was no clear trend in northern
or Western Europe (Stahl et al., 2010). Models can reproduce observed
patterns of drought occurrence (e.g., Prudhomme et al., 2011), but as
with climate models their outputs can be very divergent. In simulations
of drought at the global scale in 1963–2000 with an ensemble of
hydrological models, strong correlations were noted between El Niño-
240
Chapter 3 Freshwater Resources
3
S
outhern Oscillation (ENSO) events and hydrological droughts, and—
particularly in dry regions—low correlations between meteorological
and hydrological droughts, which suggests that hydrological droughts
cannot necessarily be inferred from rainfall deficits (van Huijgevoort et
al., 2013).
3.3. Drivers of Change
for Freshwater Resources
3.3.1. Climatic Drivers
Precipitation and potential evaporation are the main climatic drivers
controlling freshwater resources. Precipitation is strongly related to
atmospheric water vapor content, because saturation specific humidity
depends on temperature: warmer air can hold much more water vapor.
Temperature has increased in recent decades while surface and
tropospheric relative humidity have changed little (WGI AR5 Chapter 2).
Among other climatic drivers are atmospheric CO
2
, which affects plant
transpiration (Box CC-VW), and deposited black carbon and dust, both
of which, even in very small concentrations, enhance melting of snow
and ice by reducing the surface albedo.
Uncertainty in the climatic drivers is due mainly to internal variability
of the atmospheric system, inaccurate modeling of the atmospheric
response to external forcing, and the external forcing itself as described
by the Representative Concentration Pathways (RCPs; Section 1.1.3).
Internal variability and variation between models account for all of the
uncertainty in precipitation in the first few decades of the 21st century
in Coupled Model Intercomparison Project Phase 3 (CMIP3) projections
(Hawkins and Sutton, 2011). The contribution of internal variability
diminishes progressively. By no later than mid-century, most of the
uncertainty in precipitation is due to discrepancies between models,
and divergent scenarios never contribute more than one-third of the
uncertainty. In contrast, the uncertainty in temperature (WGI AR5
Chapter 11) is due mostly to divergent scenarios.
CMIP5 simulations of the water cycle during the 21st century (WGI AR5
Chapter 12), with further constraints added here from 20th century
observations, can be summarized as follows:
• Surface temperature, which affects the vapor-carrying capacity of
the atmosphere and the ratio of snowfall to precipitation, increases
non-uniformly (very high confidence), probably by about 1.5 times
more over land than over ocean.
• Warming is greatest over the Arctic (very high confidence), implying
latitudinally variable changes in snowmelt and glacier mass budgets.
• Less precipitation falls as snow and snow cover decreases in extent
and duration (high confidence). In the coldest regions, however,
increased winter snowfall outweighs increased summer snowmelt.
• Wet regions and seasons become wetter and dry regions and seasons
become drier (high confidence), although one observational analysis
(Sun et al., 2012) is discordant; moreover the models tend to
underestimate observed trends in precipitation (Noake et al., 2012)
and its observed sensitivity to temperature (Liu et al., 2012).
• Global mean precipitation increases in a warmer world (virtually
certain), but with substantial variations, including some decreases,
from region to region. Precipitation tends to decrease in subtropical
l
atitudes, particularly in the Mediterranean, Mexico and Central
America, and parts of Australia, and to increase elsewhere, notably
at high northern latitudes and in India and parts of central Asia
(likely to very likely; WGI AR5 Figure 12-41). However, precipitation
changes generally become statistically significant only when
temperature rises by at least 1.4°C, and in many regions projected
21st century changes lie within the range of late 20th century
natural variability (Mahlstein et al., 2012).
• Changes in evaporation have patterns similar to those of changes in
precipitation, with moderate increases almost everywhere, especially
at higher northern latitudes (WGI AR5 Figure 12-25). Scenario-
dependent decreases of soil moisture are widespread, particularly
in central and southern Europe, southwestern North America,
Amazonia, and southern Africa (medium to high confidence; WGI
AR5 Figure 12-23; WGI AR5 Section 12.4.5.3).
More intense extreme precipitation events are expected (IPCC, 2012).
One proposed reason is the projected increase in specific humidity:
intense convective precipitation in short periods (less than 1 hour) tends
to “empty” the water vapor from the atmospheric column (Utsumi et
al., 2011; Berg et al., 2013). Annual maxima of daily precipitation that
are observed to have 20-year return periods in 1986–2005 are projected
to have shorter return periods in 2081–2100: about 14 years for RCP2.6,
11 years for RCP4.5, and 6 years for RCP8.5 (Kharin et al., 2013). Unlike
annual mean precipitation, for which the simulated sensitivity to
warming is typically 1.5 to 2.5% K
–1
, the 20-year return amount of daily
precipitation typically increases at 4 to 10% K
–1
. Agreement between
model-simulated extremes and reanalysis extremes is good in the
extratropics but poor in the tropics, where there is robust evidence of
greater sensitivity (10 ± 4% K
–1
, O’Gorman, 2012). In spite of the
intrinsic uncertainty of sampling infrequent events, variation between
models is the dominant contributor to uncertainty. Model-simulated
changes in the incidence of meteorological (rainfall) droughts vary
widely, so that there is at best medium confidence in projections
(Seneviratne et al., 2012). Regions where droughts are projected to
become longer and more frequent include the Mediterranean, central
Europe, central North America, and southern Africa.
3.3.2. Non-Climatic Drivers
In addition to impacts of climate change, the future of freshwater
systems will be impacted strongly by demographic, socioeconomic, and
technological changes, including lifestyle changes. These change both
exposure to hazard and requirements for water resources. A wide range
of socioeconomic futures can produce similar climate changes (van Vuuren
et al., 2012), meaning that certain projected hydrological changes (Section
3.4) can occur under a wide range of future demographic, social, economic,
and ecological conditions. Similarly, the same future socioeconomic
conditions can be associated with a range of different climate futures.
Changing land use is expected to affect freshwater systems strongly in
the future. For example, increasing urbanization may increase flood
hazards and decrease groundwater recharge. Of particular importance
for freshwater systems is future agricultural land use, especially irrigation,
which accounts for about 90% of global water consumption and severely
impacts freshwater availability for humans and ecosystems (Döll, 2009).
241
3
Freshwater Resources Chapter 3
O
wing mainly to population and economic growth but also to climate
change, irrigation may significantly increase in the future. The share of
irrigation from groundwater is expected to increase owing to increased
variability of surface water supply caused by climate change (Taylor R.
et al., 2013a).
3.4. Projected Hydrological Changes
3.4.1. Methodological Developments in
Hydrological Impact Assessment
Most recent studies of the potential impact of climate change on
hydrological characteristics have used a small number of climate
scenarios. An increasing number has used larger ensembles of regional
or global models (e.g., Chiew et al., 2009; Gosling et al., 2010; Arnell,
2011; Bae et al., 2011; Jackson et al., 2011; Olsson et al., 2011; Kling et
al., 2012; Arnell and Gosling, 2013 ). Some studies have developed
“probability distributions” of future impacts by combining results from
multiple climate projections and, sometimes, different emissions scenarios,
making different assumptions about the relative weight to give to each
scenario (Brekke et al., 2009b; Manning et al., 2009; Christierson et al.,
2012; Liu et al., 2013). These studies conclude that the relative weightings
given are typically less important in determining the distribution of future
impacts than the initial selection of climate models considered. Very
few impact studies (Dankers et al., 2013; Hanasaki et al., 2013; Portmann
et al., 2013; Schewe et al., 2013) have so far used scenarios based on
CMIP5 climate models, and these have used only a small subset.
Most assessments have used a hydrological model with the “delta
method” to create scenarios, which applies projected changes in climate
derived from a climate model either to an observed baseline or with a
stochastic weather generator. Several approaches to the construction
of scenarios at the catchment scale have been developed (Fowler et al.,
2007), including dynamical downscaling using regional climate models
and a variety of statistical approaches (e.g., Fu et al., 2013). Systematic
evaluations of different methods have demonstrated that estimated
impacts can be very dependent on the approach used to downscale
climate model data, and the range in projected change between
downscaling approaches can be as large as the range between different
climate models (Quintana Segui et al., 2010; Chen J. et al., 2011). An
increasing number of studies (e.g., Fowler and Kilsby, 2007; Hagemann
et al., 2011; Kling et al., 2012; Teutschbein and Seibert, 2012; Veijalainen
et al., 2012; Weiland et al., 2012a) have run hydrological models with
bias-corrected input from regional or global climate model output (van
Pelt et al., 2009; Piani et al., 2010; Yang et al., 2010), rather than by
applying changes to an observed baseline. The range between different
bias correction methods can be as large as the range between climate
models (Hagemann et al., 2011), although this is not always the case
(Chen C. et al., 2011; Muerth et al., 2013). Some studies (e.g., Falloon
and Betts, 2006, 2010; Hirabayashi et al., 2008; Nakaegawa et al., 2013)
have examined changes in global-scale river runoff as simulated directly
by a high-resolution climate model, rather than by an “off-line”
hydrological model. Assessments of the ability of climate models directly
to simulate current river flow regimes (Falloon et al., 2011; Weiland et
al., 2012b) show that performance depends largely on simulated
precipitation and is better for large basins, but the limited evidence
s
uggests that direct estimates of change are smaller than off-line
estimates (Hagemann et al., 2013).
The effects of hydrological model parameter uncertainty on simulated
runoff changes are typically small when compared with the range from
a large number of climate scenarios (Steele-Dunne et al., 2008; Cloke
et al., 2010; Vaze et al., 2010; Arnell, 2011; Lawrence and Haddeland,
2011). However, the effects of hydrological model structural uncertainty
on projected changes can be substantial (Dankers et al., 2013;
Hagemann et al., 2013; Schewe et al., 2013), owing to differences in
the representation of evaporation and snowmelt processes. In some
regions (e.g., high latitudes; Hagemann et al., 2013) with reductions in
precipitation (Schewe et al., 2013), hydrological model uncertainty can be
greater than climate model uncertainty—although this is based on small
numbers of climate models. Much of the difference in projected changes
in evaporation is due to the use of different empirical formulations
(Milly and Dunne, 2011). In a study in southeast Australia, the effects
of hydrological model uncertainty were small compared with climate
model uncertainty, but all the hydrological models used the same
potential evaporation data (Teng et al., 2012).
Among other approaches to impact assessment, an inverse technique
(Cunderlik and Simonovic, 2007) starts by identifying the hydrological
changes that would be critical for a system and then uses a hydrological
model to determine the meteorological conditions that trigger those
changes; the future likelihood of these conditions is estimated by
inspecting climate model output, as in a catchment study in Turkey
(Fujihara et al., 2008a,b). Another approach constructs response surfaces
relating sensitivity of a hydrological indicator to changes in climate.
Several studies have used a water-energy balance framework (based
on Budyko’s hypothesis and formula) to characterize the sensitivity of
average annual runoff to changes in precipitation and evaporation
(Donohue et al., 2011; Renner and Bernhofer, 2012; Renner et al., 2012).
A response surface showing change in flood magnitudes was constructed
by running a hydrological model with systematically varying changes in
climate (Prudhomme et al., 2010). This approach shows the sensitivity of
a system to change, and also allows rapid assessment of impacts under
specific climate scenarios which can be plotted on the response surface.
3.4.2. Evapotranspiration, Soil Moisture, and Permafrost
Based on global and regional climate models as well as physical
principles, potential evapotranspiration over most land areas is
very likely to increase in a warmer climate, thereby accelerating the
hydrologic cycle (WGI AR5 Chapter 12). Long-term projections of actual
evapotranspiration are uncertain in both magnitude and sign. They are
affected not only by rising temperatures but also by changing net
radiation and soil moisture, decreases in bulk canopy conductance
associated with rising CO
2
concentrations, and vegetation changes related
to climate change (Box CC-VW; Katul and Novick, 2009). Projections of
the response of potential evapotranspiration to a warming climate are
also uncertain. Based on six different methodologies, an increase in
potential evapotranspiration was associated with global warming
(Kingston et al., 2009). Regionally, increases are projected in southern
Europe, Central America, southern Africa, and Siberia (Seneviratne et
al., 2010). The accompanying decrease in soil moisture increases the
242
Chapter 3 Freshwater Resources
3
Box 3-1 | Case Study: Himalayan Glaciers
The total freshwater resource in the Himalayan glaciers of Bhutan, China, India, Nepal, and Pakistan is known only roughly; estimates
range from 2100 to 5800 Gt (Bolch et al., 2012). Their mass budgets have been negative on average for the past 5 decades. The loss
rate may have become greater after about 1995, but it has not been greater in the Himalaya than elsewhere. A recent large-scale
measurement, highlighted in Figure 3-3, is the first well-resolved, region-wide measurement of any component of the Himalayan
water balance. It suggests strongly that the conventional
measurements, mostly on small, accessible glaciers, are
not regionally representative.
Glacier mass changes for 2006–2100 were projected by
simulating the response of a glacier model to CMIP5
projections from 14 General Circulation Models (GCMs)
(Radić et al., 2013). Results for the Himalaya range
between 2% gain and 29% loss to 2035; to 2100, the
range of losses is 15 to 78% under RCP4.5. The model-
mean loss to 2100 is 45% under RCP4.5 and 68% under
RCP8.5 (medium confidence). It is virtually certain that
these projections are more reliable than an earlier
erroneous assessment (Cruz et al., 2007) of complete
disappearance by 2035.
At the catchment scale, projections do not yet present a
detailed region-wide picture. However the GCM-forced
simulations of Immerzeel et al. (2013) in Kashmir and
eastern Nepal show runoff increasing throughout the
century. Peak ice meltwater is reached in mid- to late-
century, but increased precipitation overcompensates for
the loss of ice.
The growing atmospheric burden of anthropogenic black carbon implies reduced glacier albedo, and measurements in eastern Nepal
by Yasunari et al. (2010) suggest that this could yield 70 to 200 mm yr
–1
of additional meltwater. Deposited soot may outweigh the
greenhouse effect as a radiative forcing agent for snowmelt (Qian et al., 2011).
The hazard due to moraine-dammed ice-marginal lakes continues to increase. In the western Himalaya, they are small and stable in
size, while in Nepal and Bhutan they are more numerous and larger, and most are growing (Gardelle et al., 2011). There has been
little progress on the predictability of dam failure but, of five dams that have failed since 1980, all had frontal slopes steeper than
10° before failure and much gentler slopes afterward (Fujita et al., 2013). This is a promising tool for evaluating the hazard in
detail.
The relative importance of Himalayan glacier meltwater decreases downstream, being greatest where the runoff enters dry regions in
the west and becoming negligible in the monsoon-dominated east (Kaser et al., 2010). In the mountains, however, dependence on
and vulnerability to glacier meltwater are of serious concern when measured per head of population.
0
Global average (excluding
Greenland, Antarctica)
Average of local measurements
Himalaya-wide measurement
1960 1970 1980 1990 2000 2010
−20
−16
–12
−8
−4
4
Glacier mass-budget rate (water-equivalent meters per decade)
Figure 3-3 | All published glacier mass balance measurements from the Himalaya
(based on Bolch et al., 2012). To emphasize the variability of the raw information, each
measurement is shown as a box of height ±1 standard deviation centred on the
average balance (±1 standard error for multiannual measurements). Region-wide
measurement (Kääb et al., 2012) was by satellite laser altimetry. Global average (WGI
AR5 Chapter 4) is shown as a 1-sigma confidence region.
Himalaya local measurements
243
3
Freshwater Resources Chapter 3
risk of extreme hot days (Seneviratne et al., 2006; Hirschi et al., 2011)
and heat waves. For a range of scenarios, soil moisture droughts lasting
4 to 6 months double in extent and frequency, and droughts longer than
12 months become three times more common, between the mid-20th
century and the end of the 21st century (Sheffield and Wood, 2008).
Because of strong natural variability, the generally monotonic projected
increases are statistically indistinguishable from the current climate.
Changes consistent with warming are also evident in the freshwater
systems and permafrost of northern regions. The area of permafrost is
p
rojected to continue to decline over the first half of the 21st century
in all emissions scenarios (WGI AR5 Figure 4-18). Under RCP2.6, the
permafrost area is projected to stabilize at near 37% less than the 20th
century area.
3.4.3. Glaciers
All projections for the 21st century (WGI AR5 Chapter 13) show continued
mass loss from glaciers. In glacierized catchments, runoff reaches an
annual maximum in summer. As the glaciers shrink, their relative
contribution decreases and the annual runoff peak shifts toward spring
(e.g., Huss, 2011). This shift is expected with very high confidence in
most regions, although not, for example, in the eastern Himalaya, where
the monsoon and the melt season coincide. The relative importance of
high-summer glacier meltwater can be substantial, for example
contributing 25% of August discharge in basins draining the European
Alps, with area about 105 km
2
and only 1% glacier cover (Huss, 2011).
Glacier meltwater also increases in importance during droughts and
heat waves (Koboltschnig et al., 2007).
If the warming rate is constant, and if, as expected, ice melting per unit
area increases and total ice-covered area decreases, the total annual yield
passes through a broad maximum: “peak meltwater.” Peak-meltwater
dates have been projected between 2010 and 2050 (parts of China, Xie
et al., 2006); 2010–2040 (European Alps, Huss, 2011); and mid- to late-
century (glaciers in Norway and Iceland, Jóhannesson et al., 2012). Note
that the peak can be dated only relative to a specified reference date.
Declining yields relative to various dates in the past have been detected
in some observational studies (Table 3-1); that is, a peak has been passed
already. There is medium confidence that the peak response to 20th-
and 21st-century warming will fall within the 21st century in many
inhabited glacierized basins, where at present society is benefitting from
a transitory “meltwater dividend.” Variable forcing leads to complex
variations of both the melting rate and the extent of ice, which depend
on each other.
If they are in equilibrium, glaciers reduce the interannual variability of
water resources by storing water during cold or wet years and releasing
it during warm years (Viviroli et al., 2011). As glaciers shrink, however,
their diminishing influence may make the water supply less dependable.
3.4.4. Runoff and Streamflow
Many of the spatial gaps identified in AR4 have been filled to a very large
extent by catchment-scale studies of the potential impacts of climate
change on streamflow. The projected impacts in a catchment depend on
the sensitivity of the catchment to change in climatic characteristics and
on the projected change in the magnitude and seasonal distribution of
precipitation, temperature, and evaporation. Catchment sensitivity is
l
argely a function of the ratio of runoff to precipitation: the smaller the
ratio, the greater the sensitivity. Proportional changes in average annual
runoff are typically between one and three times as large as proportional
changes in average annual precipitation (Tang and Lettenmaier, 2012).
Projected scenario-dependent changes in runoff at the global scale,
mostly from CMIP3 simulations, exhibit a number of consistent patterns
(e.g., Hirabayashi et al., 2008; Döll and Zhang, 2010; Fung et al., 2011;
Murray et al., 2012; Okazaki et al., 2012; Tang and Lettenmaier, 2012;
Weiland et al., 2012a; Arnell and Gosling, 2013; Nakaegawa et al., 2013;
Schewe et al., 2013). Average annual runoff is projected to increase at
high latitudes and in the wet tropics, and to decrease in most dry
tropical regions. However, for some regions there is very considerable
uncertainty in the magnitude and direction of change, specifically in
China, south Asia, and large parts of South America. Both the patterns
of change and the uncertainty are driven largely by projected changes
in precipitation, particularly across south Asia. Figure 3-4 shows the
average percentage change in average annual runoff for an increase
in global average temperature of 2°C above the 1980–2010 mean,
averaged across five CMIP5 climate models and 11 hydrological models.
The pattern of change in Figure 3-4 is different in some regions from
the pattern shown in WGI AR5 Figure 12-24, largely because it is based
on fewer climate models.
The seasonal distribution of change in streamflow varies primarily with
the seasonal distribution of change in precipitation, which in turn varies
between scenarios. Figure 3-5 illustrates this variability, showing the
percentage change in monthly average runoff in a set of catchments
from different regions using scenarios from seven climate models, all
scaled to represent a 2°C increase in global mean temperature above the
1961–1990 mean. One of the climate models is separately highlighted,
and for that model the figure also shows changes with a 4°C rise in
temperature. In the Mitano catchment in Uganda, for example, there
is a nonlinear relationship between amount of climate change and
hydrological response. Incorporating uncertainty in hydrological model
structure (Section 3.4.1) would increase further the range in projected
impacts at the catchment scale.
There is a much more consistent pattern of future seasonal change in
areas currently influenced by snowfall and snowmelt. A global analysis
(Adam et al., 2009) with multiple climate scenarios shows a consistent
shift to earlier peak flows, except in some regions where increases in
precipitation are sufficient to result in increased, rather than decreased,
snow accumulation during winter. The greatest changes are found near
the boundaries of regions that currently experience considerable
snowfall, where the marginal effect of higher temperatures on snowfall
and snowmelt is greatest.
3.4.5. Groundwater
While the relation between groundwater and climate change was rarely
investigated before 2007, the number of studies and review papers
244
Chapter 3 Freshwater Resources
3
(Green et al., 2011; Taylor R. et al., 2013a) has increased significantly
since then. Ensemble studies, relying on between 4 and 20 climate models,
of the impact of climate change on groundwater recharge and partially
also on groundwater levels were done for the globe (Portmann et al.,
2013), all of Australia (Crosbie et al., 2013a), the German Danube basin
(Barthel et al., 2010), aquifers in Belgium and England (Goderniaux et
al., 2011; Jackson et al., 2011), the Pacific coast of the USA and Canada
(Allen et al., 2010), and the semiarid High Plains aquifer of the USA
(Ng et al., 2010; Crosbie et al., 2013b). With three exceptions, simulations
were run under only one GHG emissions scenario. The range over the
climate models of projected groundwater changes was large, from
significant decreases to significant increases for the individual study
areas, and the range of percentage changes of projected groundwater
recharge mostly exceeded the range of projected precipitation changes.
The uncertainties in projected groundwater recharge that originate in
the hydrological models have not yet been explored. There are only a
few studies of the impacts on groundwater of vegetation changes in
response to climate change and CO
2
increase (Box CC-VW). Nor are
there any studies on the impact of climate-driven changes of land use on
groundwater recharge, even though projected increases in precipitation
and streamflow variability due to climate change are expected to lead
to increased groundwater abstraction (Taylor R. et al., 2013a), lowering
groundwater levels and storage.
Under any particular climate scenario, the areas where total runoff (sum
of surface runoff and groundwater recharge) is projected to increase (or
decrease) roughly coincide with the areas where groundwater recharge
and thus renewable groundwater resources are projected to increase
(or decrease) (Kundzewicz and Döll, 2009). Changes in precipitation
intensity affect the fraction of total runoff that recharges groundwater.
Increased precipitation intensity may decrease groundwater recharge
owing to exceedance of the infiltration capacity (typically in humid
areas), or may increase it owing to faster percolation through the root
zone and thus reduced evapotranspiration (typically in semiarid areas)
(Liu, 2011; Taylor R. et al., 2013b). The sensitivity of groundwater recharge
and levels to climate change is diminished by perennial vegetation, fine-
grained soils, and aquitards and is enhanced by annual cropping, sandy
soils, and unconfined (water table) aquifers (van Roosmalen et al., 2007;
Crosbie et al., 2013b). The sensitivity of groundwater recharge change
to precipitation change was found to be highest for low groundwater
<–50 –30 –10
50<3010
60
70
80
Relative change (%)
Agreement (%)
Figure 3-4 | Percentage change of mean annual streamflow for a global mean temperature rise of 2°C above 1980–2010 (2.7°C above pre-industrial). Color hues show the
multi-model mean change across 5 General Circulation Models (GCMs) and 11 Global Hydrological Models (GHMs), and saturation shows the agreement on the sign of change
across all 55 GHM–GCM combinations (percentage of model runs agreeing on the sign of change) (Schewe et al., 2013).
245
3
Freshwater Resources Chapter 3
HadCM3(4˚C)
HadGEM1
NCAR CCSM3
ECHAM5/MPI-OM
IPSL-CM4
HadCM3(2˚C)
CSIRO-Mk3.0
CCCma-CGCM3.1(T47)
Harper’s Brook: UK
% Change
Months
Liard: Canada
Rio Grande: Brazil
Mekong: Vietnam
Xiangxi: China
Okavango: Botswana
Mitano: Uganda
–80
–40
0
40
80
120
160
DNOSAJJMAMFJ
–
80
–
40
0
4
0
8
0
1
20
1
60
D
NOSAJJMAMFJ
–80
–
40
0
40
8
0
1
20
160
D
NOSAJJMAMFJ
–80
–40
0
40
80
120
160
DNOSAJJMAMFJ
–80
–40
0
40
80
120
160
DNOSAJJMAMFJ
–80
–40
0
40
8
0
1
20
1
60
DNOSAJJMAMFJ
–80
–40
0
40
80
120
160
DNOSAJJMAMFJ
Figure 3-5 | Change in mean monthly runoff across seven climate models in seven catchments, with a 2°C increase in global mean temperature above 1961–1990 (Kingston
and Taylor, 2010; Arnell, 2011; Hughes et al., 2011; Kingston et al., 2011; Nobrega et al., 2011; Thorne, 2011; Xu et al., 2011). One of the seven climate models (HadCM3) is
highlighted separately, showing changes with both a 2°C increase (dotted line) and a 4°C increase (solid line).
246
Chapter 3 Freshwater Resources
3
r
echarge and lowest for high groundwater recharge, the ratio of
recharge change to precipitation change ranging from 1.5 to 6.0 in the
semiarid High Plains aquifer (Crosbie et al., 2013b). Decreasing snowfall
may lead to lower groundwater recharge even if precipitation remains
constant; at sites in the southwestern USA, snowmelt provides at least
40 to 70% of groundwater recharge, although only 25 to 50% of average
annual precipitation falls as snow (Earman et al., 2006).
Climate change affects coastal groundwater not only through changes
in groundwater recharge but also through sea level rise which, together
with the rate of groundwater pumping, determines the location of the
saltwater/freshwater interface. Although most confined aquifers are
expected to be unaffected by sea level rise, unconfined aquifers are
expected to suffer from saltwater intrusion (Werner et al., 2012). The
volume available for freshwater storage is reduced if the water table
cannot rise freely as the sea level rises (Masterson and Garabedian,
2007; Werner et al., 2012). This happens where land surfaces are low
lying, for example, on many coral islands and in deltas, but also where
groundwater discharges to streams. If the difference between the
groundwater table and sea level is decreased by 1 m, the thickness of
the unconfined freshwater layer decreases by roughly 40 m (Ghyben-
Herzberg relation). Deltas are also affected by storm surges that drive
saltwater into stream channels, contaminating the underlying fresh
groundwater from above (Masterson and Garabedian, 2007). In three
modeling studies, the impact of sea level rise on groundwater levels
was found to be restricted to areas within 10 km from the coast
(Carneiro et al., 2010; Oude Essink et al., 2010; Yechieli et al., 2010).
Saltwater intrusion due to sea level rise is mostly a very slow process
that may take several centuries to reach equilibrium (Webb and Howard,
2011). Even small rates of groundwater pumping from coastal aquifers
are expected to lead to stronger salinization of the groundwater than
sea level rise during the 21st century (Ferguson and Gleeson, 2012;
Loaiciga et al., 2012).
Changes in groundwater recharge also affect streamflow. In the Mitano
basin in Uganda, mean global temperature increases of 4°C or more
with respect to 1961–1990 are projected to decrease groundwater
outflow to the river so much that the spring discharge peak disappears
and the river flow regime changes from bimodal to unimodal (one
seasonal peak only) (Kingston and Taylor, 2010; Figure 3-5). Changing
groundwater tables affect land surface energy fluxes, including
evaporation, and thus feed back on the climate system, in particular in
semiarid areas where the groundwater table is within 2 to 10 m of the
surface (Jiang et al., 2009; Ferguson and Maxwell, 2010).
3.4.6. Water Quality
Climate change affects the quality of water through a complex set of
natural and anthropogenic mechanisms working concurrently in parallel
and in series. Projections under climate change scenarios are difficult,
both to perform and interpret, because they require not only integration
of the climate models with those used to analyze the transportation
and transformation of pollutants in water, soil, and air but also the
establishment of a proper baseline (Arheimer et al., 2005; Andersen et
al., 2006; Wilby et al., 2006; Ducharne, 2008; Marshall and Randhir,
2008; Bonte and Zwolsman, 2010; Towler et al., 2010; Trolle et al., 2011;
R
ehana and Mujumdar, 2012). The models have different spatial scales
and have to be adapted and calibrated to local conditions for which
adequate and appropriate information is needed. In consequence, there
are few projections of the impacts of climate change on water quality;
where available, their uncertainty is high. It is evident, however, that
water quality projections depend strongly on (1) local conditions;
(2) climatic and environmental assumptions; and (3) the current or
reference pollution state (Chang, 2004; Whitehead et al., 2009a,b; Bonte
and Zwolsman, 2010; Kundzewicz and Krysanova, 2010; Sahoo et al.,
2010; Trolle et al., 2011). Most projections suggest that future negative
impacts will be similar in kind to those already observed in response to
change and variability in air and water temperature, precipitation, and
storm runoff, and to many confounding anthropogenic factors (Chang,
2004; Whitehead et al., 2009a). This holds for natural and artificial
reservoirs (Brikowski, 2008; Ducharne, 2008; Marshall and Randhir,
2008; Loos et al., 2009; Bonte and Zwolsman, 2010; Qin et al., 2010;
Sahoo et al., 2010; Trolle et al., 2011), rivers (Andersen et al., 2006;
Whitehead et al., 2009a,b; Bowes et al., 2012) and groundwater
(Butscher and Huggenberger, 2009; Rozemeijer et al., 2009).
3.4.7. Soil Erosion and Sediment Load
Heavy rainfalls are likely to become more intense and frequent during
the 21st century in many parts of the world (Seneviratne et al., 2012;
WGI AR5 Chapter 11), which may lead to more intense soil erosion even
if the total rainfall does not increase. At the global scale, soil erosion
simulated assuming doubled CO
2
is projected to increase about 14%
by the 2090s, compared to the 1980s (9% attributed to climate change
and 5% to land use change), with increases by as much as 40 to 50%
in Australia and Africa (Yang et al., 2003). The largest increases are
expected in semiarid areas, where extreme events may contribute
about half of total erosion; for instance, in Mediterranean Spain 43% of
sediment yield over the time period 1990–2009 was produced by a single
event (Bussi et al., 2013). In agricultural lands in temperate regions, soil
erosion may respond to more intense erosion in complex nonlinear
ways; for instance in the UK a 10% increase in winter rainfall (i.e., during
early growing season) could increase annual erosion of arable land by
up to 150% (Favis-Mortlock and Boardman, 1995), while in Austria a
simulation for 2070–2099 projected a decrease of rainfall by 10 to 14%
in erosion-sensitive months and thus a decline in soil erosion by 11 to
24% (Scholz et al., 2008). Land management practices are critical for
mitigating soil erosion under projected climate change. In China’s
Loess Plateau, four GCMs coupled to an erosion model show soil
erosion increasing by –5 to 195% of soil loss during 2010–2039 under
conventional tillage, for three emission scenarios (Special Report
on Emission Scenarios (SRES) A2 and B2, and IS92a), whereas under
conservation tillage they show decreases of 26 to 77% (Li et al., 2011).
Climate change will also affect the sediment load in rivers by altering
water discharge and land cover. For example, an increase in water
discharge of 11 to 14% in two Danish rivers under the SRES A2 emission
scenario was projected to increase the annual suspended sediment load
by 9 to 36% during 2071–2100 (Thodsen et al., 2008). Increases in total
precipitation, increased runoff from glaciers, permafrost degradation,
and the shift of precipitation from snow to rain will further increase soil
erosion and sediment loads in colder regions (Lu et al., 2010). In a major
247
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Freshwater Resources Chapter 3
headwater basin of the Ganges River, increased precipitation and glacier
runoff are projected to increase sediment yield by 26% by 2050
(Neupane and White, 2010). In the tropics, the intensity of cyclones is
projected to increase 2 to 11% by 2100, which may increase soil erosion
and landslides (Knutson et al., 2010).
In summary, projected increases in heavy rainfall and temperature will
lead to changes in soil erosion and sediment load, but owing to the
nonlinear dependence of soil erosion on rainfall rate and its strong
dependence on land cover there is low confidence in projected changes
in erosion rates. At the end of the 21st century, the impact of climate
change on soil erosion is expected to be twice the impact of land use
change (Yang et al., 2003), although management practices may mitigate
the problem at catchment scale.
3.4.8. Extreme Hydrological Events (Floods and Droughts)
The Special Report on Managing the Risks of Extreme Events and
Disasters to Advance Climate Change Adaptation (SREX; Seneviratne
et al., 2012) recognized that projected increases in temperature and
heavy precipitation imply regional-scale changes in flood frequency
and intensity, but with low confidence because these projections were
obtained from a single GCM. Global flood projections based on multiple
CMIP5 GCM simulations coupled with global hydrology and land surface
models (Dankers et al., 2013; Hirabayashi et al., 2013) show flood hazards
increasing over about half of the globe, but with great variability at the
catchment scale. Projections of increased flood hazard are consistent
for parts of south and Southeast Asia, tropical Africa, northeast Eurasia,
and South America (Figure 3-6), while decreases are projected in parts
of northern and Eastern Europe, Anatolia, central Asia, central North
America, and southern South America. This spatial pattern resembles
closely that described by Seneviratne et al. (2012), but the latest
projections justify medium confidence despite new appreciation of the
large uncertainty owing to variation between climate models and their
coupling to hydrological models.
There have been several assessments of the potential effect of climate
change on meteorological droughts (less rainfall) and agricultural
droughts (drier soil) (e.g., WGI AR5 Chapter 12; Vidal et al., 2012;
Orlowsky and Seneviratne, 2013), but few on hydrological droughts,
either in terms of river runoff or groundwater levels. Many catchment-
scale studies (Section 3.4.4) consider changes in indicators of low river
flow (such as the flow exceeded 95% of the time), but these indicators
do not necessarily characterize “drought” as they define neither duration
nor spatial extent, and are not necessarily particularly extreme or rare.
In an ensemble comparison under SRES A1B of the proportion of the
land surface exhibiting significant projected changes in hydrological
drought frequency to the proportions exhibiting significant changes in
meteorological and agricultural drought frequency, 18 to 30% of the
land surface (excluding cold areas) experienced a significant increase
in the frequency of 3-month hydrological droughts, while about 15 to
45% saw a decrease (Taylor I. et al., 2013). This is a smaller area with
increased frequency, and a larger area with decreased frequency, than
for meteorological and agricultural droughts, and is understandable
because river flows reflect the accumulation of rainfall over time. Flows
during dry periods may be sustained by earlier rainfall. For example, at
the catchment scale in the Pacific Northwest (Jung and Chang, 2012),
Frequently Asked Questions
FAQ 3.1 | How will climate change affect the frequency and severity
of floods and droughts?
Climate change is projected to alter the frequency and magnitude of both floods and droughts. The impact is expected
to vary from region to region. The few available studies suggest that flood hazards will increase over more than
half of the globe, in particular in central and eastern Siberia, parts of Southeast Asia including India, tropical Africa,
and northern South America, but decreases are projected in parts of northern and Eastern Europe, Anatolia, central
and East Asia, central North America, and southern South America (limited evidence, high agreement).The frequency
of floods in small river basins is very likely to increase, but that may not be true of larger watersheds because
intense rain is usually confined to more limited areas. Spring snowmelt floods are likely to become smaller, both
because less winter precipitation will fall as snow and because more snow will melt during thaws over the course
of the entire winter. Worldwide, the damage from floods will increase because more people and more assets will
be in harm’s way.
By the end of the 21st century meteorological droughts (less rainfall) and agricultural droughts (drier soil) are projected
to become longer, or more frequent, or both, in some regions and some seasons, because of reduced rainfall or
increased evaporation or both. But it is still uncertain what these rainfall and soil moisture deficits might mean for
prolonged reductions of streamflow and lake and groundwater levels. Droughts are projected to intensify in southern
Europe and the Mediterranean region, central Europe, central and southern North America, Central America,
northeast Brazil, and southern Africa. In dry regions, more intense droughts will stress water supply systems. In
wetter regions, more intense seasonal droughts can be managed by current water supply systems and by adaptation;
for example, demand can be reduced by using water more efficiently, or supply can be increased by increasing the
storage capacity in reservoirs.
248
Chapter 3 Freshwater Resources
3
s
hort hydrological droughts are projected to increase in frequency while
longer droughts remain unchanged because, although dry spells last
longer, winter rainfall increases.
The impacts of floods and droughts are projected to increase even
when the hazard remains constant, owing to increased exposure and
vulnerability (Kundzewicz et al., 2013). Projected flood damages vary
greatly between models and from region to region, with the largest
losses in Asia. Studies of projected flood damages are mainly focused
in Europe, the USA, and Australia (Handmer et al., 2012; Bouwer, 2013).
In Europe, the annual damage (€6.4 billion) and number of people
exposed (200,000) in 1961–1990 are expected to increase about
twofold by the 2080s under scenario B2 and about three times under
scenario A2 (Feyen et al., 2012). Drought impacts at continental and
smaller scales are difficult to assess because they will vary greatly
with the local hydrological setting and water management practices
(Handmer et al., 2012). More frequent droughts due to climate change
may challenge existing water management systems (Kim et al., 2009);
together with an increase of population, this may place at risk even the
domestic supply in parts of Africa (MacDonald et al., 2009).
3.5. Projected Impacts, Vulnerabilities, and Risks
In general, projections of freshwater-related impacts, vulnerabilities,
and risks caused by climate change are evaluated by comparison to
historical conditions. Such projections are helpful for understanding
human impact on nature and for supporting adaptation to climate
change. However, for supporting decisions on climate mitigation, it is
more helpful to compare the different hydrological changes that are
projected under different future GHG emissions scenarios, or different
amounts of global mean temperature rise. One objective of such
projections is to quantify what may happen under current water
resources management practice, and another is to indicate what actions
may be needed to avoid undesirable outcomes (Oki and Kanae, 2006).
The studies compiled in Table 3-2 illustrate the benefits of reducing GHG
emissions for the Earth’s freshwater systems. Emissions scenarios are
rather similar until the 2050s. Their impacts, and thus the benefits of
mitigation, tend to become more clearly marked by the end of the 21st
century. For example, the fraction of the world population exposed to
a 20th century 100-year flood is projected to be, at the end of the 21st
century, three times higher per year for RCP8.5 than for RCP2.6
(Hirabayashi et al., 2013). Each degree of global warming (up to 2.7°C
above preindustrial levels; Schewe et al., 2013) is projected to decrease
renewable water resources by at least 20% for an additional 7% of the
world population. The number of people with significantly decreased
access to renewable groundwater resources is projected to be roughly
50% higher under RCP8.5 than under RCP2.6 (Portmann et al., 2013).
The percentage of global population living in river basins with new or
aggravated water scarcity is projected to increase with global warming,
from 8% at 2°C to 13% at 5°C (Gerten et al., 2013).
3.5.1. Availability of Water Resources
About 80% of the world’s population already suffers serious threats to
its water security, as measured by indicators including water availability,
BCC-CSM1.1
CCCma-CanESM2
CMCC-CM
CNRM-CM5
CSIRO-Mk3.6.0 GFDL-ESM2G
INM-CM4
MIROC5
MPI-ESM-LR
MRI-CGCM3 NCC-NorESM1-M
Return period (years)
DecreaseIncrease
Flood frequency
2525 50 75 95 105 125 250 500 1000
(a)
M
aximum
+1 Std Dev
Mean
−1 Std Dev
Minimum
150
Mean
±1 Std Dev
100
50
Historical
RCP8.5
RCP6.0
RCP4.5
RCP2.6
(
b)
Projected
1980 2000 2020 2040
Historical
RCP8.5
RCP6.0
R
CP4.5
RCP2.6
2060 2080 2100
0
Number of people exposed to flood
(return period ≥100 years) (millions of people)
Figure 3-6 | (a) Multi-model median return period (years) in the 2080s for the 20th
century 100-year flood (Hirabayashi et al., 2013), based on one hydrological model
driven by 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) General
Circulation Models (GCMs) under Representative Concentration Pathway 8.5 (RCP8.5).
At each location the magnitude of the 100-year flood was estimated by fitting a
Gumbel distribution function to time series of simulated annual maximum daily
discharge in 1971–2000, and the return period of that flood in 2071–2100 was
estimated by fitting the same distribution to discharges simulated for that period.
Regions with mean runoff less than 0.01 mm day
–1
, Antarctica, Greenland, and Small
Islands are excluded from the analysis and indicated in white. (b) Global exposure to
the 20th-century 100-year flood (or greater) in millions of people (Hirabayashi et al.,
2013). Left: Ensemble means of historical (black thick line) and future simulations
(colored thick lines) for each scenario. Shading denotes ±1 standard deviation. Right:
Maximum and minimum (extent of white), mean (thick colored lines), ±1 standard
deviation (extent of shading), and projections of each GCM (thin colored lines)
averaged over the 21st century. The impact of 21st century climate change is
emphasized by fixing the population to that of 2005. Annual global flood exposure
increases over the century by 4 to 14 times as compared to the 20th century (4 ± 3
(RCP2.6), 7 ± 5 (RCP4.5), 7 ± 6 (RCP6.0), and 14 ± 10 (RCP8.5) times, or 0.1% to
0.4 to 1.2% of the global population in 2005). Under a scenario of moderate
population growth (UN, 2011), the global number of exposed people is projected to
increase by a factor of 7 to 25, depending on the RCP, with strong increases in Asia
and Africa due to high population growth.
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Freshwater Resources Chapter 3
Table 3-2 | Effects of different greenhouse gas (GHG) emissions scenarios on hydrological changes and freshwater-related impacts of climate change on humans and
ecosystems. Among the Special Report on Emission Scenarios (SRES) scenarios, GHG emissions are highest in A1f and A2, lower in A1 and B2, and lowest in B1. Representative
Concentration Pathway 8.5 (RCP8.5) is similar to A2, while the lower emissions scenarios RCP6.0 and RCP4.5 are similar to B1. RCP2.6 is a very low emissions scenario (Figure
1-4 and Section 1.1.3.1 in Chapter 1). The studies in the table give global warming (GW: global mean temperature rise, quantifi ed as the Coupled Model Intercomparison Project
Phase 5 (CMIP5) model mean) over different reference periods, typically since pre-industrial. GW since pre-industrial is projected to be, for RCP8.5, approximately 2°C in the
2040s and 4°C in the 2090s. For RCP6.0, GW is 2°C in the 2060s and 2.5°C in the 2090s, while in RCP2.6, GW stays below 1.5°C throughout the 21st century (Figure 1-4 in
Chapter 1). Population scenario SSP2 assumes a medium population increase. The number of GCMs that were used in the studies is provided.
Type of hydrological
change or impact
Description of indicator
Hydrological change or impact in different emissions
scenarios or for different degrees of global warming
(GW)
Reference
Decrease of renewable water
r
esources, global scale
Percent of global population affected by a water resource decrease
o
f more than 20% as compared to the 1990s (mean of 5 General
Circulation Models (GCMs) and 11 global hydrological models,
p
opulation scenario SSP2)
Up to 2°C above the 1990s (GW 2.7°C), each degree of GW affects
a
n additional 7%
Schewe et al.
(
2013)
Decrease of renewable
groundwater resources, global
s
cale
Percent of global population affected by a groundwater resource
decrease of more than 10% by the 2080s as compared to the
1
980s (mean and range of 5 GCMs, population scenario SSP2)
• RCP2.6: 24% (11–39%)
• RCP4.5: 26% (23–32%)
•
R
CP6.0: 32% (18–45%)
• RCP8.5: 38% (27–50%)
Portmann et
al. (2013)
E
xposure to fl oods, global scale Percent of global population annually exposed, in the 2080s, to a
fl ood corresponding to the 100-year fl ood discharge for the 1980s
(
mean and range of 5–11 GCMs, population constant at 2005
values)
•
R
CP2.6: 0.4% (0.2–0.5%)
• RCP4.5: 0.6% (0.4–1.0%)
•
R
CP6.0: 0.7% (0.3–1.1%)
• RCP8.5: 1.2% (0.6–1.7%)
• GW 2°C: 0.5% (0.3–0.6%)
•
G
W 4°C: 1.2% (0.8–2.2%)
• 1980s: 0.1% (0.04–0.16%)
H
irabayashi
et al. (2013)
Change in irrigation water
d
emand, global scale
Change of required irrigation water withdrawals by the 2080s (on
a
rea irrigated around 2000) as compared to the 1980s (range of
3 GCMs)
• RCP2.6: –0.2 to 1.6%
•
R
CP4.5: 1.9–2.8%
• RCP8.5: 6.7–10.0%
Hanasaki et
a
l. (2013)
R
iver fl ow regime shifts from
perennial to intermittent and vice
versa, global scale
P
ercent of global land area (except Greenland and Antarctica)
affected by regime shifts between the 1970s and the 2050s (range
of 2 GCMs)
•
S
RES B2: 5.4–6.7%
• SRES A2: 6.3–7.0%
D
öll and
Müller
Schmied
(2012)
Water scarcity Percent of global population living in countries with less than 1300
m
3
yr
–
1
of per capita blue water resources in the 2080s (mean of 17
GCMs, population constant at 2000 values)
No signifi cant differences between SRES B1 and A2 Gerten et al.
(2011)
New or aggravated water
scarcity
Percent of global population living in river basins with new or
aggravated water scarcity around 2100 as compared to 2000 (less
than 1000 m
3
yr
–1
of per capita blue water resources) (median of 19
GCMs, population constant at 2000 values)
• GW 2°C: 8%
• GW 3.5°C: 11%
• GW 5°C: 13%
Gerten et al.
(2013)
Exposure to water scarcity Population in water-stressed watersheds (less than 1000 m
3
yr
–1
of
per capita blue water resources) exposed to an increase in stress
(1 GCM)
For emissions scenarios with 2°C target, compared to SRES A1:
• 5–8% impact reduction in 2050
• 10–20% reduction in 2100
Arnell et al.
(2013)
Change of groundwater recharge
in the whole of Australia
Probability that groundwater recharge decreases to less than 50%
of the 1990s value by 2050 (16 GCMs)
• GW 1.4°C: close to 0 almost everywhere
• GW 2.8°C: in western Australia 0.2–0.6, in central Australia
0.2–0.3, elsewhere close to 1
Crosbie et al.
(2013a)
Change in groundwater recharge
in East Anglia, UK
Percent change between baseline and future groundwater
recharge, in %, by the 2050s (1 GCM)
• SRES B1: –22%
• SRES A1f: –26%
Holman et al.
(2009)
Change of river discharge,
groundwater recharge, and
hydraulic head in groundwater in
two regions of Denmark
Changes between the 1970s and the 2080s (1 regional climate
model)
Differences between SRES B2 and A2 are very small compared to
the changes between the 1970s and the 2080s in each scenario.
van
Roosmalen et
al. (2007)
River fl ow regime shift for river
in Uganda
Shift from bimodal to unimodal (1 GCM) Occurs in scenarios with GW of at least 4.3°C but not for smaller
GW.
Kingston and
Taylor (2010)
Agricultural (soil moisture)
droughts in France
Mean duration, affected area, and magnitude of short and long
drought events throughout the 21st century (1 GCM)
Smaller increases over time for SRES B1 than for A2 and A1B. Vidal et al.
(2012)
Salinization of artifi cial coastal
freshwater lake IJsselmeer in the
Netherlands (a drinking water
source) due to seawater intrusion
(1) Daily probability of exceedance of maximum allowable
concentration (MAC) of chloride (150 mg L
–1
)
(2) Maximum duration of MAC exceedance (2050, 1 GCM)
• Reference period 1997–2007 (GW 0.8°C): (1) 2.5%, (2) 103 days
• GW 1.8°C, no change in atmospheric circulation: (1) 3.1%, (2)
124 days
• GW 2.8°C and change in atmospheric circulation: (1) 14.3%, (2)
178 days
Bonte and
Zwolsman
(2010)
Decrease of hydropower
production at Lake Nasser, Egypt
Reduction of mean annual hydropower production by the 2080s
compared to hydropower production 1950–99 (11 GCMs)
• SRES B1: 8%
• SRES A2: 7%
Beyene et al.
(2010)
Reduction of usable capacity of
thermal power plants in Europe
and USA due to low river fl ow
and excessive water temperature
Number of days per year with a capacity reduction of more than
50% (for existing power plants) (2031–2060, 3 GCMs)
• Without climate change: 16
• SRES B1: 22
• SRES A2: 24
van Vliet et al.
(2012)
Flood damages in Europe (EU27) (1) Expected annual damages, in 2006
(2) Expected annual population exposed (2080s, 2 GCMs)
• SRES B2: (1) 14–15 billion € yr
–1
, (2) 440,000–470,000 people
• SRES A2: (1) 18–21 billion € yr
–1
, (2) 510,000–590,000 people
• Reference period: (1) 6.4 billion € yr
–1
, (2) 200,000 people
Feyen et al.
(2012)
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Chapter 3 Freshwater Resources
3
water demand, and pollution (Vörösmarty et al., 2010). Climate change
can alter the availability of water and therefore threaten water security
as defined by UNESCO (2011).
Global-scale analyses so far have concentrated on measures of resource
availability rather than the multi-dimensional indices used in Vörösmarty
et al. (2010). All have simulated future river flows or groundwater
recharge using global-scale hydrological models. Some have assessed
future availability based on runoff per capita (Hayashi et al., 2010; Arnell
et al., 2011, 2013; Fung et al., 2011; Murray et al., 2012; Gerten et al.,
2013; Gosling and Arnell, 2013; Schewe et al., 2013), whilst others have
projected future human withdrawals and characterized availability
by the ratio of withdrawals to availability from runoff or recharge
(Arnell et al., 2011; Gosling and Arnell, 2013; Hanasaki et al., 2013). A
groundwater vulnerability index was constructed that combined future
reductions of renewable groundwater resources with water scarcity,
dependence on groundwater, and the Human Development Index
(Figure 3-7) (Döll, 2009). There are several key conclusions from this set
of studies. First, the spatial distribution of the impacts of climate change
on resource availability varies considerably between climate models,
and strongly with the pattern of projected rainfall change. There is
strong consistency in projections of reduced availability around the
Mediterranean and parts of southern Africa, but much greater variation
in projections for south and East Asia. Second, some water-stressed
areas see increased runoff in the future (Section 3.4.4), and therefore
less exposure to water resources stress. Third, over the next few decades
and for increases in global mean temperature of less than around 2°C
above preindustrial, changes in population will generally have a greater
effect on changes in resource availability than will climate change. Climate
change would, however, regionally exacerbate or offset the effects of
population pressures. Fourth, estimates of future water availability are
sensitive not only to climate and population projections and population
assumptions, but also to the choice of hydrological impact model
(Schewe et al., 2013) and to the adopted measure of stress or scarcity.
As an indication of the potential magnitude of the impact of climate
change, Schewe et al. (2013) estimated that about 8% of the global
population would see a severe reduction in water resources (a reduction
in runoff either greater than 20% or more than the standard deviation
of current annual runoff) with a 1°C rise in global mean temperature
(compared to the 1990s), rising to 14% at 2°C and 17% at 3°C; the
spread across climate and hydrological models was, however, large.
Under climate change, reliable surface water supply is expected to
decrease due to increased variability of river flow that is due in turn to
Vulnerability index
Low High
< 10% decrease
No decrease
Small to no decrease
Projected change in groundwater recharge
> 10 % decrease
B2 - ECHAM4
A2 - ECHAM4
B2 - HadCM3
A2 - HadCM3
Figure 3-7 | Human vulnerability to climate change–induced decreases of renewable groundwater resources by the 2050s. Lower (Special Report on Emission Scenarios (SRES) B2) and
higher (SRES A2) emissions pathways are interpreted by two global climate models. The higher the vulnerability index (computed by multiplying percentage decrease of groundwater recharge
by a sensitivity index), the higher is the vulnerability. The index is defined only for areas where groundwater recharge is projected to decrease by at least 10% relative to 1961–1990 (Döll,
2009).
251
3
Freshwater Resources Chapter 3
increased precipitation variability and decreased snow and ice storage.
Under these circumstances, it might be beneficial to take advantage
of the storage capacity of groundwater and to increase groundwater
withdrawals (Kundzewicz and Döll, 2009). However, this option is
sustainable only where, over the long term, withdrawals remain well
below recharge, while care must also be taken to avoid excessive
reduction of groundwater outflow to rivers. Therefore, groundwater
cannot be expected to ease freshwater stress where climate change is
projected to decrease groundwater recharge and thus renewable
groundwater resources (Kundzewicz and Döll, 2009). The percentage of
projected global population (SSP2 population scenario) that will suffer
from a decrease of renewable groundwater resources of more than 10%
between the 1980s and the 2080s was computed to range from 24%
(mean based on five GCMs, range 11 to 39%) for RCP2.6 to 38% (range
27 to 50%) for RCP8.5 (Portmann et al., 2013; see also Table 3-2). The
land area affected by decreases of groundwater resources increases
linearly with global mean temperature rise between 0°C and 3°C. For
each degree of global mean temperature rise, an additional 4% of the
global land area is projected to suffer a groundwater resources decrease
of more than 30%, and an additional 1% to suffer a decrease of more
than 70% (Portmann et al., 2013).
3.5.2. Water Uses
3.5.2.1. Agriculture
Water demand and use for food and livestock feed production is governed
not only by crop management and its efficiency, but also by the balance
between atmospheric moisture deficit and soil water supply. Thus,
changes in climate (precipitation, temperature, radiation) will affect the
water demand of crops grown in both irrigated and rainfed systems.
Using projections from 19 CMIP3 GCMs forced by SRES A2 emissions
to drive a global vegetation and hydrology model, climate change by
the 2080s would hardly alter the global irrigation water demand of
major crops in areas currently equipped for irrigation (Konzmann et al.,
2013). However, there is high confidence that irrigation demand will
increase significantly in many areas (by more than 40% across Europe,
USA, and parts of Asia). Other regions—including major irrigated areas
in India, Pakistan, and southeastern China—might experience a slight
decrease in irrigation demand, due for example to higher precipitation,
but only under some climate change scenarios (also see Biemans et al.,
2013). Using seven global hydrological models but a limited set of
CMIP5 projections, Wada et al. (2013) suggested a global increase in
irrigation demand by the 2080s (ensemble average 7 to 21% depending
on emissions scenario), with a pronounced regional pattern, a large
inter-model spread, and possible seasonal shifts in crop water demand
and consumption. By contrast, based on projections from two GCMs
and two emissions scenarios, a slight global decrease in crop water
deficits was suggested in both irrigated and rainfed areas by the 2080s,
which can be explained partly by a smaller difference between daily
maximum and minimum temperatures (Zhang and Cai, 2013). As in
other studies, region-to-region variations were very heterogeneous.
Where poor soil is not a limiting factor, physiological and structural crop
responses to elevated atmospheric CO
2
concentration (CO
2
fertilization)
might partly cancel out the adverse effects of climate change, potentially
reducing global irrigation water demand (Konzmann et al., 2013; see
also Box CC-VW). However, even in this optimistic case, increases in
irrigation water demand by >20% are still projected under most
scenarios for some regions, such as southern Europe. In general, future
irrigation demand is projected to exceed local water availability in many
places (Wada et al., 2013). The water demand to produce a given
amount of food on either irrigated or rainfed cropland will increase in
many regions due to climate change alone (Gerten et al., 2011, projections
from 17 CMIP3 GCMs, SRES A2 emissions), but this increase might be
moderated by concurrent increases in crop water productivity due to
CO
2
effects, that is, decreases in per-calorie water demand. The CO
2
effects may thus lessen the global number of people suffering water
scarcity; nonetheless, the effect of anticipated population growth is
likely to exceed those of climate and CO
2
change on agricultural water
demand, use, and scarcity (Gerten et al., 2011).
Rainfed agriculture is vulnerable to increasing precipitation variability.
Differences in yield and yield variability between rainfed and irrigated
land may increase with changes in climate and its variability (e.g., Finger
et al., 2011). Less irrigation water might be required for paddy rice
cultivation in monsoon regions where rainfall is projected to increase
and the crop growth period to become shorter (Yoo et al., 2013). Water
demand for rainfed crops could be reduced by better management
(Brauman et al., 2013), but unmitigated climate change may counteract
such efforts, as shown in a global modeling study (Rost et al., 2009). In
Frequently Asked Questions
FAQ 3.2 | How will the availability of water resources be affected by climate change?
Climate models project decreases of renewable water resources in some regions and increases in others, albeit with
large uncertainty in many places. Broadly, water resources are projected to decrease in many mid-latitude and dry
subtropical regions, and to increase at high latitudes and in many humid mid-latitude regions (high agreement,
robust evidence). Even where increases are projected, there can be short-term shortages due to more variable
streamflow (because of greater variability of precipitation) and seasonal reductions of water supply due to reduced
snow and ice storage. Availability of clean water can also be reduced by negative impacts of climate change on
water quality; for instance, the quality of lakes used for water supply could be impaired by the presence of algae-
producing toxins.
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Chapter 3 Freshwater Resources
3
s
ome regions, expansion of irrigated areas or increases of irrigation
efficiencies may overcome climate change impacts on agricultural water
demand and use (McDonald and Girvetz, 2013).
3.5.2.2. Energy Production
Hydroelectric and thermal power plants, and the irrigation of bioenergy
crops (Box CC-WE), require large amounts of water. This section assesses
the impact of hydrological changes (as described in Section 3.4) on
hydroelectric and thermal power production. The impacts of changes in
energy production due to climate change mitigation efforts are discussed
in Section 3.7.2.1, while the economic implications of the impact of
climate change on thermal power and hydropower production as well
as adaptation options are assessed in Chapter 10.
Climate change affects hydropower generation through changes in the
mean annual streamflow, shifts of seasonal flows, and increases of
streamflow variability (including floods and droughts), as well as by
increased evaporation from reservoirs and changes in sediment fluxes.
Therefore, the impact of climate change on a specific hydropower plant
will depend on the local change of these hydrological characteristics,
as well as on the type of hydropower plant and on the (seasonal) energy
demand, which will itself be affected by climate change (Golombek et
al., 2012). Run-of-river power plants are more susceptible to increased
flow variability than plants at dams. Projections of future hydropower
generation are subject to the uncertainty of projected precipitation and
streamflow. For example, projections to the 2080s of hydropower
generation in the Pacific Northwest of the USA range from a decrease
of 25% to an increase of 10% depending on the climate model (Markoff
and Cullen, 2008). Based on an ensemble of 11 GCMs, hydropower
generation at the Aswan High Dam (Egypt) was computed to remain
constant until the 2050s but to decrease, following the downward trend
of mean annual river discharge, to 90% (ensemble mean) of current
mean annual production under both SRES B1 and A2 (Beyene et al., 2010;
see also Table 3-2). In snow-dominated basins, increased discharge in
winter, smaller and earlier spring floods, and reduced discharge in
summer have already been observed (Section 3.2.6) and there is
high confidence that these trends will continue. In regions with high
electricity demands for heating, this makes the annual hydrograph more
similar to seasonal variations in electricity demand, reducing required
reservoir capacities and providing opportunities for operating dams and
power stations to the benefit of riverine ecosystems (Renofalt et al.,
2010; Golombek et al., 2012). In regions with high electricity demand
for summertime cooling, however, this seasonal streamflow shift is
detrimental. In general, climate change requires adaptation of operating
rules (Minville et al., 2009; Raje and Mujumdar, 2010) which may,
however, be constrained by reservoir capacity. In California, for example,
high-elevation hydropower systems with little storage, which rely on
storage in the snowpack, are projected to yield less hydropower owing
to the increased occurrence of spills, unless precipitation increases
significantly (Madani and Lund, 2010). Storage capacity expansion
would help increase hydropower generation but might not be cost
effective (Madani and Lund, 2010).
Regarding water availability for cooling of thermal power plants, the
number of days with a reduced useable capacity is projected to increase
i
n Europe and the USA, owing to increases in stream temperatures and
the incidence of low flows (Flörke et al., 2012; van Vliet et al., 2012; see
also Table 3-2). Warmer cooling water was computed to lower thermal
power plant efficiency and thus electricity production by 1.5 to 3% in
European countries by the 2080s under emissions scenario SRES A1B
(Golombek et al., 2012).
3.5.2.3. Municipal Services
Under climate change, water utilities are confronted by the following
(Bates et al., 2008; Jiménez, 2008; van Vliet and Zwolsman, 2008; Black
and King, 2009; Brooks et al., 2009; Whitehead et al., 2009a; Bonte and
Zwolsman, 2010; Hall and Murphy, 2010; Mukhopadhyay and Dutta,
2010; Qin et al., 2010; Chakraborti et al., 2011; Major et al., 2011;
Thorne and Fenner, 2011; Christierson et al., 2012):
• Higher ambient temperatures, which reduce snow and ice volumes
and increase the evaporation rate from lakes, reservoirs, and aquifers.
These changes decrease natural storage of water, and hence, unless
precipitation increases, its availability. Moreover, higher ambient
temperatures increase water demand, and with it the competition
for the resource (medium to high agreement, limited evidence).
• Shifts in timing of river flows and possible more frequent or intense
droughts, which increase the need for artificial water storage.
• Higher water temperatures, which encourage algal blooms and
increase risks from cyanotoxins and natural organic matter in water
sources, requiring additional or new treatment of drinking water
(high agreement, medium evidence). On the positive side, biological
water and wastewater treatment is more efficient when the water
is warmer (Tchobanoglous et al., 2003).
• Possibly drier conditions, which increase pollutant concentrations.
This is a concern especially for groundwater sources that are already
of low quality, even when pollution is natural as in India and
Bangladesh, North and Latin America and Africa; here arsenic, iron,
manganese, and fluorides are often a problem (Black and King, 2009).
• Increased storm runoff, which increases loads of pathogens, nutrients,
and suspended sediment.
• Sea level rise, which increases the salinity of coastal aquifers, in
particular where groundwater recharge is also expected to decrease.
Climate change also impacts water quality indirectly. For instance, at
present many cities rely on water from forested catchments that requires
very little treatment. More frequent and severe forest wildfires could
seriously degrade water quality (Emelko et al., 2011; Smith et al., 2011).
Many drinking water treatment plants—especially small ones—are not
designed to handle the more extreme influent variations that are to be
expected under climate change. These demand additional or even
different infrastructure capable of operating for up to several months
per year, which renders wastewater treatment very costly, notably in
rural areas (Zwolsman et al., 2010; Arnell et al., 2011).
Sanitation technologies vary in their resilience to climate impacts
(Howard et al., 2010). For sewage, three climatic conditions are of
interest (NACWA, 2009; Zwolsman et al., 2010):
• Wet weather: heavier rainstorms mean increased amounts of water
and wastewater in combined systems for short periods. Current
253
3
Freshwater Resources Chapter 3
d
esigns, based on critical “design storms” defined through analysis
of historical precipitation data, therefore need to be modified. New
strategies to adapt to and mitigate urban floods need to be developed,
considering not only climate change but also urban design, land
use, the “heat island effect,” and topography (Changnon, 1969).
• Dry weather: soil shrinks as it dries, causing water mains and sewers
to crack and making them vulnerable to infiltration and exfiltration of
water and wastewater. The combined effects of higher temperatures,
increased pollutant concentrations, longer retention times, and
sedimentation of solids may lead to increasing corrosion of sewers,
shorter asset lifetimes, more drinking water pollution, and higher
maintenance costs.
• Sea level rise: intrusion of brackish or salty water into sewers
necessitates processes that can handle saltier wastewater.
Increased storm runoff implies the need to treat additional wastewater
when combined sewers are used, as storm runoff adds to sewage; in
addition, the resulting mixture has a higher content of pathogens and
pollutants. Under drier conditions higher concentrations of pollutants
in wastewater, of any type, are to be expected and must be dealt with
(Whitehead et al., 2009a,b; Zwolsman et al., 2010). The cost may rule
this out in low-income regions (Chakraborti et al., 2011; Jiménez, 2011).
The disposal of wastewater or fecal sludge is a concern that is just
beginning to be addressed in the literature (Seidu et al., 2013).
3.5.2.4. Freshwater Ecosystems
Freshwater ecosystems are composed of biota (animals, plants, and
other organisms) and their abiotic environment in slow-flowing surface
waters such as lakes, man-made reservoirs, or wetlands; in fast-flowing
surface waters such as rivers and creeks; and in the groundwater. They
have suffered more strongly from human activities than have marine
and terrestrial ecosystems. Between 1970 and 2000, populations of
freshwater species included in the Living Planet Index declined on
average by 50%, compared to 30% for marine and also for terrestrial
species (Millennium Ecosystem Assessment, 2005). Climate change is
an additional stressor of freshwater ecosystems, which it affects not only
through increased water temperatures (discussed in Section 4.3.3.3) but
a
lso by altered streamflow regimes, river water levels, and extent and
timing of inundation (Box CC-RF). Wetlands in dry environments are
hotspots of biological diversity and productivity, and their biotas are at
risk of extinction if runoff decreases and the wetland dries out (as
described for Mediterranean-type temporary ponds by Zacharias and
Zamparas, 2010). Freshwater ecosystems are also affected by water
quality changes induced by climate change (Section 3.2.5), and by
human adaptations to climate change-induced increases of streamflow
variability and flood risk, such as the construction of dykes and dams
(Ficke et al., 2007; see also Section 3.7.2).
3.5.2.5. Other Uses
In addition to direct impacts, vulnerabilities, and risks in water-related
sectors, indirect impacts of hydrological changes are expected for
navigation, transportation, tourism, and urban planning (Pinter et al.,
2006; Koetse and Rietveld, 2009; Rabassa, 2009; Badjeck et al., 2010;
Beniston, 2012). Social and political problems can result from hydrological
changes. For example, water scarcity and water overexploitation may
increase the risks of violent conflicts and nation-state instability (Barnett
and Adger, 2007; Burke et al. 2009; Buhaug et al., 2010; Hsiang et al.,
2011). Snowline rise and glacier shrinkage are very likely to impact
environmental, hydrological, geomorphological, heritage, and tourism
resources in cold regions (Rabassa, 2009), as already observed for
tourism in the European Alps (Beniston, 2012). Although most impacts
will be adverse, some might be beneficial.
3.6. Adaptation and Managing Risks
In the face of hydrological changes and freshwater-related impacts,
vulnerability, and risks due to climate change, there is need for adaptation
and for increasing resilience. Managing the changing risks due to the
impacts of climate change is the key to adaptation in the water sector
(IPCC, 2012), and risk management should be part of decision making
and the treatment of uncertainty (ISO, 2009). Even to exploit the positive
impacts of climate change on freshwater systems, adaptation is generally
required.
Frequently Asked Questions
FAQ 3.3 | How should water management be modified in the face of climate change?
Managers of water utilities and water resources have considerable experience in adapting their policies and practices
to the weather. But in the face of climate change, long-term planning (over several decades) is needed for a future
that is highly uncertain. A flexible portfolio of solutions that produces benefits regardless of the impacts of climate
change (“low-regret” solutions) and that can be implemented adaptively, step by step, is valuable because it allows
policies to evolve progressively, thus building on—rather than losing the value of—previous investments. Adaptive
measures that may prove particularly effective include rainwater harvesting, conservation tillage, maintaining
vegetation cover, planting trees in steeply sloping fields, mini-terracing for soil and moisture conservation, improved
pasture management, water reuse, desalination, and more efficient soil and irrigation water management. Restoring
and protecting freshwater habitats, and managing natural floodplains, are additional adaptive measures that are
not usually part of conventional management practice.
254
Chapter 3 Freshwater Resources
3
3.6.1. Options
There is growing agreement that an adaptive approach to water
m
anagement can successfully address uncertainty due to climate
change. Although there is limited evidence of the effectiveness of such
an approach, the evidence is growing (Section 3.6.2). Many practices
identified as adaptive were originally reactions to climate variability.
Climate change provides many opportunities for “low-regret” solutions,
capable of yielding social and/or economic benefits and adaptive both
to variability and to change (Table 3-3). Adaptive techniques include
scenario planning, experimental approaches that involve learning from
experience, and the development of flexible solutions that are resilient
to uncertainty. A program of adaptation typically mixes “hard”
infrastructural and “soft” institutional measures (Bates et al., 2008;
Cooley, 2008; Mertz et al., 2009; Sadoff and Muller, 2009; UNECE, 2009;
Olhoff and Schaer, 2010).
To avoid adaptation that goes wrong—“maladaptation”—scientific
research results should be analyzed during planning. Low-regret solutions,
such as those for which moderate investment clearly increases the
capacity to cope with projected risks or for which the investment is
justifiable under all or almost all plausible scenarios, should be considered
explicitly. Involving all stakeholders, reshaping planning processes,
coordinating the management of land and water resources, recognizing
linkages between water quantity and quality, using surface water and
groundwater conjunctively, and protecting and restoring natural systems
are examples of principles that can beneficially inform planning for
adaptation (World Bank, 2007).
Integrated Water Resource Management continues to be a promising
instrument for exploring adaptation to climate change. It can be
joined with a Strategic Environmental Assessment to address broader
considerations. Attention is currently increasing to “robust measures”
(European Communities, 2009), which are measures that perform well
under different future conditions and clearly optimize prevailing strategies
(Sigel et al., 2010). Barriers to adaptation are discussed in detail in
Section 16.4. Barriers to adaptation in the freshwater sector include
lack of human and institutional capacity, lack of financial resources,
lack of awareness, and lack of communication (Browning-Aiken et al.,
2007; Burton, 2008; Butscher and Huggenberger, 2009; Zwolsman et
al., 2010). Institutional structures can be major barriers to adaptation
(Goulden et al., 2009; Engle and Lemos, 2010; Huntjens et al., 2010;
Stuart-Hill and Schulze, 2010; Ziervogel et al., 2010; Wilby and Vaughan,
2011; Bergsma et al., 2012); structures that promote participation of
and collaboration between stakeholders tend to encourage adaptation.
Some adaptation measures may not pass the test of workability in an
uncertain future (Campbell et al., 2008), and uncertainty (Section 3.6.2)
can be another significant barrier.
Case studies of the potential effectiveness of adaptation measures are
increasing. Changes in operating practices and infrastructure improvements
could help California’s water managers respond to changes in the
volume and timing of supply (Medellin-Azuara et al., 2008; Connell-
Buck et al., 2011). Other studies include evaluations of the effectiveness
of different adaptation options in Washington state, USA (Miles et al.,
2010) and the Murray-Darling basin, Australia (Pittock and Finlayson,
2011), and of two dike-heightening strategies in the Netherlands
(
Hoekstra and de Kok, 2008). Such studies have demonstrated that it is
technically feasible in general to adapt to projected climate changes,
but not all have considered how adaptation would be implemented.
3.6.2. Dealing with Uncertainty
in Future Climate Change
One of the key challenges in factoring climate change into water
resources management lies in the uncertainty. Some approaches (e.g.,
in England and Wales; Arnell, 2011) use a small set of climate scenarios
to characterize the potential range of impacts on water resources and
flooding. Others (e.g., Brekke et al., 2008; Lopez et al., 2009; Christierson
et al., 2012; Hall et al., 2012) use very large numbers of scenarios to
generate likelihood distributions of indicators of impact for use in
risk assessment. However, it has been argued (Hall, 2007; Stainforth
et al., 2007; Dessai et al., 2009) that attempts to construct probability
distributions of impacts are misguided because of “deep” uncertainty,
which arises because analysts do not know, or cannot agree on, how
the climate system and water management systems may change, how
models represent possible changes, or how to value the desirability of
different outcomes. Stainforth et al. (2007) therefore argue that it is
impossible in practice to construct robust quantitative probability
distributions of climate change impacts, and that climate change
uncertainty needs to be represented differently, for example by using
fewer plausible scenarios and interpreting the outcomes of scenarios
less quantitatively.
Some go further, arguing that climate models are not sufficiently robust
or reliable to provide the basis for adaptation (Koutsoyiannis et al.,
2008; Anagnostopoulos et al., 2010; Blöschl and Montanari, 2010;
Wilby, 2010), because they are frequently biased and do not reproduce
the temporal characteristics (specifically the persistence or “memory”)
often found in hydrological records. It has been argued (Lins and Cohn,
2011; Stakhiv, 2011) that existing water resources planning methods
are sufficiently robust to address the effects of climate change. This
view of climate model performance has been challenged and is the
subject of some debate (Koutsoyiannis et al., 2009, 2011; Huard,
2011); the critique also assumes that adaptation assessment procedures
would use only climate scenarios derived directly from climate model
simulations.
Addressing uncertainty in practice by quantifying it through some form
of risk assessment, however, is only one way of dealing with uncertainty.
A large and increasing literature recommends that water managers
should move from the traditional “predict and provide” approach
toward adaptive water management (Pahl-Wostl, 2007; Pahl-Wostl et
al., 2008; Matthews and Wickel, 2009; Mysiak et al., 2009; Huntjens et
al., 2012; Short et al., 2012; Gersonius et al., 2013) and the adoption of
resilient or “no-regrets” approaches (WWAP, 2009; Henriques and
Spraggs, 2011). Approaches that are resilient to uncertainty are not
entirely technical (or supply-side), and participation and collaboration
amongst all stakeholders are central to adaptive water management.
However, although climate change is frequently cited as a key motive,
there is very little published guidance on how to implement the adaptive
water management approach. Some examples are given in Ludwig
et al. (2009). The most comprehensive overview of adaptive water
255
3
Freshwater Resources Chapter 3
management that explicitly incorporates climate change and its
uncertainty is the three-step framework of the U.S. Water Utilities
Climate Alliance (WUCA, 2010): system vulnerability assessment, utility
planning using decision-support methods, and decision making and
implementation. Planning methods for decision support include classic
decision analysis, traditional scenario planning, and robust decision
making (Lempert et al., 1996, 2006; Nassopoulos et al., 2012). The latter
was applied by the Inland Empire Utilities Agency, supplying water to
a region in Southern California (Lempert and Groves, 2010). This led
to the refinement of the company’s water resource management plan,
making it more robust to three particularly challenging aspects of
climate change that were identified by the scenario analysis.
Another framework, based on risk assessment, is the threshold-scenario
framework of Freas et al. (2008).
Category Option
May assist both
adaptation and
mitigation
Institutional
S
upport integrated water resources management, including the integrated management of land considering specifi cally negative and positive impacts
of climate change
X
P
romote synergy of water and energy savings and effi cient use X
Identify “low-regret policies” and build a portfolio of relevant solutions for adaptation X
I
ncrease resilience by forming water utility network working teams
Build adaptive capacity
I
mprove and share information X
Adapt the legal framework to make it instrumental for addressing climate change impacts X
Develop fi nancial tools (credit, subsidies, and public investment) for the sustainable management of water, and for considering poverty eradication
a
nd equity
Design and
operation
Design and apply decision-making tools that consider uncertainty and fulfi ll multiple objectives
R
evise design criteria of water infrastructure to optimize fl exibility, redundancy, and robustness
Ensure plans and services are robust, adaptable, or modular; give good value; are maintainable; and have long-term benefi ts, especially in low-
i
ncome countries
X
Operate water infrastructure so as to increase resilience to climate change for all users and sectors
W
hen and where water resources increase, alter dam operations to allow freshwater ecosystems to benefi t
Take advantage of hard and soft adaptation measures X
C
arry out programs to protect water resources in quantity and quality
Increase resilience to climate change by diversifying water sources
a
and improving reservoir management X
Reduce demand by controlling leaks, implementing water-saving programs, cascading and reusing water X
Improve design and operation of sewers, sanitation, and wastewater treatment infrastructure to cope with variations in infl uent quantity and
quality
Provide universal sanitation with technology locally adapted, and provide for proper disposal and reintegration of used water into the environment
or for its reuse
Reduce impact
of natural
disasters
Implement monitoring and early warning systems
Develop contingency plans
Improve defenses and site selection for key infrastructure that is at risk of fl oods
Design cities and rural settlements to be resilient to fl oods
Seek and secure water from a diversity (spatially and source-type) of sources to reduce impacts of droughts and variability in water availability
Promote both the reduction of water demand and the effi cient use of water by all users
Promote switching to more appropriate crops (drought-resistant, salt-resistant; low water demand) X
Plant fl ood- or drought-resistant crop varieties
Agricultural
irrigation
Improve irrigation effi ciency and reduce demand for irrigation water X
Reuse wastewater to irrigate crops and use soil for carbon sequestration X
Industrial use
When selecting alternative sources of energy, assess the need for water X
Relocate water-thirsty industries and crops to water-rich areas
Implement industrial water effi ciency certifi cations X
a
This includes water reuse, rain water harvesting, and desalination, among others.
Sources: Vörösmarty et al. (2000); Marsalek et al. (2006); Mogaka et al. (2006); Dillon and Jiménez (2008); Jiménez and Asano (2008); Keller (2008); McCafferty (2008);
McGuckin (2008); Seah (2008); UN-HABITAT (2008); Thöle (2008); Andrews (2009); Bahri (2009); Munasinghe (2009); NACWA (2009); OFWAT (2009); Reiter (2009); Whitehead
et al. (2009b); de Graaf and der Brugge (2010); Dembo (2010); Godfrey et al. (2010); Howard et al. (2010); Mackay and Last (2010); Mukhopadhyay and Dutta (2010); OECD
(2010); Renofalt et al. (2010); Zwolsman et al. (2010); Arkell (2011a, 2011b); Elliott et al. (2011); Emelko et al. (2011); Jiménez (2011); Kingsford (2011); Major et al. (2011);
Sprenger et al. (2011); UNESCO (2011); Wang X. et al. (2011); Bowes et al. (2012).
Table 3-3 | Categories of climate change adaptation options for the management of freshwater resources.
256
Chapter 3 Freshwater Resources
3
3.6.3. Costs of Adaptation to Climate Change
Calculating the global cost of adaptation in the water sector is a difficult
task and results are highly uncertain. Globally, to maintain water services
at non-climate change levels to the year 2030 in more than 200 countries,
total adaptation costs for additional infrastructure were estimated as
US$531 billion for the SRES A1B scenario (Kirshen, 2007). Including two
further costs, for reservoir construction because the best locations have
already been taken, and for unmet irrigation demands, total water sector
adaptation costs were estimated as US$225 billion, or US$11 billion per
year for the SRES A1B scenario (UNFCCC, 2007).
Average annual water supply and flood protection costs to 2050 for
restoring service to non-climate change levels were estimated to be
US$19.7 billion for a dry GCM projection of the SRES A2 scenario and
US$14.4 billion for a wet GCM projection (Ward et al., 2010; World
Bank, 2010). Annual urban infrastructure costs, primarily for wastewater
treatment and urban drainage, were US$13.0 billion (dry) and US$27.5
billion (wet). Under both GCM projections for the A2 scenario, the water
sector accounted for about 50% of total global adaptation cost, which
was distributed regionally in the proportions: East Asia/Pacific, 20%;
Europe/Central Asia, 10%; Latin America/Caribbean, 20%; Middle East/
North Africa, 5%; South Asia, 20%; sub-Saharan Africa, 20%.
Annual costs for adaptation to climate change in sub-Saharan Africa are
estimated as US$1.1 to 2.7 billion for current urban water infrastructure,
p
lus US$1.0 to 2.5 billion for new infrastructure to meet the 2015
Millennium Development Goals (Muller, 2007). These estimates assume
a 30% reduction in stream flow and an increase of at least 40% in the
unit cost of water. Annual estimates of adaptation costs for urban water
storage are US$0.05 to 0.15 billion for existing facilities and US$0.015
to 0.05 billion for new developments. For wastewater treatment, the
equivalent estimates are US$0.1 to 0.2 billion and US$0.075 to 0.2 billion.
3.6.4. Adaptation in Practice in the Water Sector
A number of water management agencies are beginning to factor climate
change into processes and decisions (Kranz et al., 2010; Krysanova et al.,
2010), with the amount of progress strongly influenced by institutional
characteristics. Most of the work has involved developing methodologies
to be used by water resources and flood managers (e.g., Rudberg et al.,
2012), and therefore represents attempts to improve adaptive capacity.
In England and Wales, for example, methodologies to gauge the effects
of climate change on reliability of water supplies have evolved since
the late 1990s (Arnell, 2011), and the strategic plans of water supply
companies now generally allow for climate change. Brekke et al. (2009a)
describe proposed changes to practices in the USA. Several studies report
community-level activities to reduce exposure to current hydrological
variability, regarded explicitly as a means of adapting to future climate
change (e.g., Barrios et al., 2009; Gujja et al., 2009; Kashaigili et al.,
2009; Yu et al., 2009).
Key risk Adaptation issues & prospects
Risk & potential for
adaptation
Timeframe
Climatic
drivers
Near term
(2030–2040)
Present
Long term
(2080–2100)
2°C
4°C
Very
low
Very
high
Medium
Near term
(2030–2040)
Present
Long term
(2080–2100)
2°C
4°C
Very
low
Very
high
Medium
Near term
(2030–2040)
Present
Long term
(2080–2100)
2°C
4°C
Very
low
Very
high
Medium
Flood risks associated with climate change increase with increasing
greenhouse gas emissions. (robust evidence, high agreement)
[3.4.8]
By 2100, the number of people exposed annually to a
20th-century 100-year flood is projected to be three
times greater for very high emissions (RCP8.5) than
for very low emissions (RCP2.6).
Climate change is projected to reduce renewable water resources
significantly in most dry subtropical regions.
(robust evidence, high agreement)
[3.5.1]
This will exacerbate competition for water among
agriculture, ecosystems, settlements, industry and
energy production, affecting regional water, energy,
and food security.
Because nearly all glaciers are too large for equilibrium with the present
climate, there is a committed water-resources change during much of the
21st century, and changes beyond the committed change are expected due
to continued warming; in glacier-fed rivers, total meltwater yields from
stored glacier ice will increase in many regions during the next decades but
decrease thereafter. (robust evidence, high agreement)
[3.4.3]
Continued loss of glacier ice implies a shift of peak
discharge from summer to spring, except in
monsoonal catchments, and possibly a reduction of
summer flows in the downstream parts of glacierized
catchments.
Table 3-4 | Key risks from climate change and the potential for reducing risk through mitigation and adaptation. Key risks are identified based on assessment of the literature
and expert judgments by chapter authors, with evaluation of evidence and agreement in supporting chapter sections. Each key risk is characterized as very low to very high. Risk
levels are presented in three time frames: the present, near term (here assessed over 2030–2040), and longer term (here assessed over 2080–2100). Sources: Xie et al., 2006;
Döll, 2009; Kaser et al., 2010; Arnell et al., 2011; Huss, 2011; Jóhannesson et al., 2012; Seneviratne et al., 2012; Arnell and Gosling, 2013; Dankers et al., 2013; Gosling and
Arnell, 2013; Hanasaki et al., 2013; Hirabayashi et al., 2013; Kundzewicz et al., 2013; Portmann et al., 2013; Radić et al., 2013; Schewe et al., 2013; WGI AR5 Chapter 13.
Climate-related drivers of impacts
Warming trend Extreme precipitation
Level of risk & potential for adaptation
Potential for additional adaptation
to reduce risk
Risk level with
current adaptation
Risk level with
high adaptation
Drying trend
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Freshwater Resources Chapter 3
3.7. Linkages with Other Sectors and Services
3.7.1. Impacts of Adaptation in Other Sectors
on Freshwater Systems
Adaptation in other sectors such as agriculture, forestry, and industry
might have impacts on the freshwater system, and therefore needs to
be considered while planning adaptation in the water sector (Jiang et
al., 2013). For example, better agricultural land management practices
can also reduce erosion and sedimentation in river channels (Lu et al.,
2010), while controlled flooding of agricultural land can alleviate the
impacts of urban flooding. Increased irrigation upstream may limit
water availability downstream (World Bank, 2007). A project designed
for other purposes may also deliver increased resilience to climate
change as a co-benefit, even without a specifically identified adaptive
component (World Bank, 2007; Falloon and Betts, 2010).
3.7.2. Climate Change Mitigation and Freshwater Systems
3.7.2.1. Impact of Climate Change Mitigation
on Freshwater Systems
Many measures for climate change mitigation affect freshwater systems.
Afforestation generally increases evapotranspiration and decreases total
runoff (van Dijk and Keenan, 2007). Afforestation of areas deemed
suitable according to the Clean Development Mechanism–Afforestation/
Reforestation provisions of the Kyoto Protocol (7.5 million km
2
) would
lead to large and spatially extensive decreases of long-term average
runoff (Trabucco et al., 2008). On 80% of the area, runoff is computed
to decline by more than 40%, while on 27% runoff decreases of 80 to
100% were computed, mostly in semiarid areas (Trabucco et al., 2008).
For example, economic incentives for carbon sequestration may
encourage the expansion of Pinus radiata timber plantations in the
Fynbos biome of South Africa, with negative consequences for water
supply and biodiversity; afforestation is viable to the forestry industry
only because it pays less than 1% of the actual cost of streamflow
reduction caused by replacing Fynbos by the plantations (Chisholm, 2010).
In general, afforestation has beneficial impacts on soil erosion, local
flood risk, water quality (nitrogen, phosphorus, suspended sediments),
and stream habitat quality (van Dijk and Keenan, 2007; Trabucco et al.,
2008; Wilcock et al., 2008).
Irrigated bioenergy crops and hydropower can have negative impacts on
freshwater systems (Jacobson, 2009). In the USA, water use for irrigating
biofuel crops could increase from 2% of total water consumption in
2005 to 9% in 2030 (King et al., 2010). Irrigating some bioenergy crops
may cost more than the energy thus gained. In dry parts of India, pumping
from a depth of 60 m for irrigating jatropha is estimated to consume
more energy than that gained from the resulting higher crop yields
(Gupta et al., 2010). For a biofuel scenario of the International Energy
Agency, global consumptive irrigation water use for biofuel production
is projected to increase from 0.5% of global renewable water resources
in 2005 to 5.5% in 2030; biofuel production is projected to increase
water consumption significantly in some countries (e.g., Germany, Italy,
and South Africa), and to exacerbate the already serious water scarcity
in others (e.g., Spain and China) (Gerbens-Leenes et al., 2012). Conversion
of native Caatinga forest into rainfed fields for biofuels in semiarid
northwestern Brazil may lead to a significant increase of groundwater
recharge (Montenegro and Ragab, 2010), but there is a risk of soil
salinization due to rising groundwater tables.
Hydropower generation leads to alteration of river flow regimes that
negatively affect freshwater ecosystems, in particular biodiversity and
abundance of riverine organisms (Döll and Zhang, 2010; Poff and
Zimmerman, 2010), and to fragmentation of river channels by dams,
with negative impacts on migratory species (Bourne et al., 2011).
Hydropower operations often lead to discharge changes on hourly
timescales that are detrimental to the downstream river ecosystem
(Bruno et al., 2009; Zimmerman et al., 2010). However, release
Frequently Asked Questions
FAQ 3.4 | Does climate change imply only bad news about water resources?
There is good news as well as bad about water resources, but the good news is very often ambiguous. Water may
become less scarce in regions that get more precipitation, but more precipitation will probably also increase flood
risk; it may also raise the groundwater table, which could lead to damage to buildings and other infrastructure or
to reduced agricultural productivity due to wet soils or soil salinization. More frequent storms reduce the risk of
eutrophication and algal blooms in lakes and estuaries by flushing away nutrients, but increased storm runoff will
carry more of those nutrients to the sea, exacerbating eutrophication in marine ecosystems, with possible adverse
impacts as discussed in Chapter 30. Water and wastewater treatment yields better results under warmer conditions,
as chemical and biological reactions needed for treatment perform in general better at higher temperatures. In
many rivers fed by glaciers, there will be a “meltwater dividend” during some part of the 21st century, due to
increasing rates of loss of glacier ice, but the continued shrinkage of the glaciers means that after several decades
the total amount of meltwater that they yield will begin to decrease (medium confidence). An important point is
that often impacts do not become “good news” unless investments are made to exploit them. For instance, where
additional water is expected to become available, the infrastructure to capture that resource would need to be
developed if it is not already in place.
258
Chapter 3 Freshwater Resources
3
m
anagement and structural measures like fish ladders can mitigate
these negative impacts somewhat (Williams, 2008). In tropical regions,
the global warming potential of hydropower, due to methane emissions
from man-made reservoirs, may exceed that of thermal power; based
on observed emissions of a tropical reservoir, this might be the case
where the ratio of hydropower generated to the surface area of the
reservoir is less than 1 MW km
–2
(Gunkel, 2009).
CO
2
leakage to freshwater aquifers from saline aquifers used for carbon
capture and storage (CCS) can lower pH by 1 to 2 units and increase
concentrations of metals, uranium, and barium (Little and Jackson, 2010).
Pressure exerted by gas injection can push brines or brackish water into
freshwater parts of the aquifer (Nicot, 2008). Displacement of brine into
potable water was not considered in a screening methodology for CCS
sites in the Netherlands (Ramírez et al., 2010). Another emergent
freshwater-related risk of climate mitigation is increased natural gas
extraction from low-permeability rocks. The required hydraulic fracturing
process (“fracking”) uses large amounts of water (a total of about 9000
to 30,000 m
3
per well, mixed with a number of chemicals), of which a
part returns to the surface (Rozell and Reaven, 2012). Fracking is
suspected to lead to pollution of the overlying freshwater aquifer or
surface waters, but appropriate observations and peer-reviewed studies
are still lacking (Jackson et al., 2013). Densification of urban areas to
reduce traffic emissions is in conflict with providing additional open
space for inundation in case of floods (Hamin and Gurran, 2009).
3.7.2.2. Impact of Water Management
on Climate Change Mitigation
A number of water management decisions affect GHG emissions. Water
demand management has a significant impact on energy consumption
because energy is required to pump and treat water, to heat it, and to
treat wastewater. For example, water supply and water treatment were
responsible for 1.4% of total electricity consumption in Japan in 2008
(MLIT, 2011). In the USA, total water-related energy consumption was
equivalent to 13% of total electricity production in 2005, with 70% for
water heating, 14% for wastewater treatment, and only 5% for pumping
of irrigation water (Griffiths-Sattenspiel and Wilson, 2009). In China,
where agriculture accounts for 62% of water withdrawals, groundwater
pumping for irrigation accounted for only 0.6% of China’s GHG emissions
in 2006, a small fraction of the 17 to 20% share of agriculture as a whole
(Wang et al., 2012). Where climate change reduces water resources in
dry regions, desalination of seawater as an adaptation option is
expected to increase GHG emissions if carbon-based fuels are used as
energy source (McEvoy and Wilder, 2012).
In Southeast Asia, emissions due to peatland drainage contribute 1.3
to 3.1% of current global CO
2
emissions from the combustion of fossil
fuels (Hooijer et al., 2010), and peatland rewetting could substantially
reduce net GHG emissions (Couwenberg et al., 2010). Climate change
mitigation by conservation of wetlands will also benefit water quality
and biodiversity (House et al., 2010). Irrigation can increase CO
2
storage
in soils by reducing water stress and so enhancing biomass production.
Irrigation in semiarid California did not significantly increase soil organic
carbon (Wu et al., 2008). Water management in rice paddies can reduce
methane (CH
4
) emissions. If rice paddies are drained at least once during
t
he growing season, with resulting increased water withdrawals, global
CH
4
emissions from rice fields could be decreased by 4.1 Tg yr
–
1
(16%
around the year 2000), and nitrous oxide (N
2
O) emissions would not
increase significantly (Yan et al., 2009).
3.8. Research and Data Gaps
Precipitation and river discharge are systematically observed, but data
records are unevenly available and unevenly distributed geographically.
Information on many other relevant variables, such as soil moisture, snow
depth, groundwater depth, and water quality, is particularly limited in
developing countries. Relevant socioeconomic data, such as rates of
surface water and groundwater withdrawal by each sector, and
information on already implemented adaptations for stabilizing water
supply, such as long-range diversions, are limited even in developed
countries. In consequence, assessment capability is limited in general,
and especially so in developing countries.
Modeling studies have shown that the adaptation of vegetation to
changing climate may have large impacts on the partitioning of
precipitation into evapotranspiration and runoff. This feedback should
be investigated more thoroughly (see Box CC-VW).
Relatively little is known about the economic aspects of climate change
impacts and adaptation options related to water resources. For example,
regional damage curves need to be developed, relating the magnitudes
of major water related disasters (such as intense precipitation and
surface soil dryness) to the expected costs.
There is a continuing, although narrowing, mismatch between the large
scales resolved by climate models and the catchment scale at which
water is managed and adaptations must be implemented. Improving the
spatial resolution of regional and global climate models, and the accuracy
of methods for downscaling their outputs, can produce information more
relevant to water management, although the robustness of regional
climate projections is still constrained by the realism of GCM simulations
of large-scale drivers. More computing capacity is needed to address these
problems with more ensemble simulations at high spatial resolution.
More research is also needed into novel ways of combining different
approaches to projection of plausible changes in relevant climate
variables so as to provide robust information to water managers. Robust
attribution to anthropogenic climate change of hydrological changes,
particularly changes in the frequency of extreme events, is similarly
demanding, and further study is required to develop rigorous attribution
tools that require less computation. In addition, there is a difficulty to
model and interpret results obtained from applying models at different
scales and with different logics to follow the future changes on water
quality. Moreover, the establishment of a proper baseline to isolate the
effects derived from climate change from the anthropogenic cause is a
major challenge.
Interactions among socio-ecological systems are not yet well considered
in most impact assessments. Particularly, there are few studies on the
impacts of mitigation and adaptation in other sectors on the water sector,
and conversely. A valuable advance would be to couple hydrological
models, or even the land surface components of climate models, to data
259
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Freshwater Resources Chapter 3
o
n water management activities such as reservoir operations, irrigation,
and urban withdrawals from surface water or groundwater.
To support adaptation by increasing reliance on groundwater and on
the coordinated and combined use of groundwater and surface water,
ground-based data are needed in the form of a long-term program to
monitor groundwater dynamics and stored groundwater volumes.
Understanding of groundwater recharge and groundwater surface water
interactions, particularly by the assessment of experiences of conjunctive
use of groundwater and surface water, needs to be better developed.
More studies are needed, especially in developing countries, on the
impacts of climate change on water quality, and of vulnerability to and
ways of adapting to those impacts.
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