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 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 19642007 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 19882002 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