FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Chapter 3.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 Editors Pavel Kabat (Netherlands), Zbigniew Kundzewicz (Poland) Volunteer Chapter Scientist Asako Nishijima (Japan) Contents Executive Summary 3.1. Introduction 3.2. Observed Hydrological Changes due to Climate Change 3.2.1. Detection and Attribution 3.2.2. Precipitation, Evapotranspiration, Soil Moisture, Permafrost, and Glaciers 3.2.3. Streamflow 3.2.4. Groundwater 3.2.5. Water Quality 3.2.6. Soil Erosion and Sediment Load 3.2.7. Extreme Hydrological Events and Their Impacts 3.3. Drivers of Change for Freshwater Resources 3.3.1. Climatic Drivers 3.3.2. Non-Climatic Drivers 3.4. Projected Hydrological Changes 3.4.1. Methodological Developments in Hydrological Impact Assessment 3.4.2. Evapotranspiration, Soil Moisture and Permafrost 3.4.3. Glaciers 3.4.4. Runoff and Streamflow 3.4.5. Groundwater 3.4.6. Water Quality 3.4.7. Soil Erosion and Sediment Load 3.4.8. Extreme Hydrological Events (Floods and Droughts) 3.5. Projected Impacts, Vulnerabilities, and Risks 3.5.1. Availability of Water Resources 3.5.2. Water Uses 3.5.2.1. Agriculture Subject to Final Copyedit 1 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 3.5.2.2. Energy Production 3.5.2.3. Municipal Services 3.5.2.4. Freshwater Ecosystems 3.5.2.5. Other Uses 3.6. Adaptation and Managing Risks 3.6.1. Options 3.6.2. Dealing with Uncertainty in Future Climate Change 3.6.3. Costs of Adaptation to Climate Change 3.6.4. Adaptation in Practice in the Water Sector 3.7. Linkages with Other Sectors and Services 3.7.1. Impacts of Adaptation in Other Sectors on Freshwater Systems 3.7.2. Climate Change Mitigation and Freshwater Systems 3.7.2.1. Impact of Climate Change Mitigation on Freshwater Systems 3.7.2.2. Impact of Water Management on Climate Change Mitigation 3.8. Research and Data Gaps References Chapter Box 3-1. Case Study: Himalayan Glaciers Frequently Asked Questions 3.1: How will climate change affect the frequency and severity of floods and droughts? 3.2: How will the availability of water resources be affected by climate change? 3.3: How should water management be modified in the face of climate change? 3.4: Does climate change imply only bad news about water resources? Executive Summary Key risks at the global scale Freshwater-related risks of climate change increase significantly with increasing greenhouse gas emissions (high agreement, robust evidence) [3.4; 3.5]. Modelling 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]. Each degree of warming is projected to decrease renewable water resources by at least 20% for an additional 7% of the global population. By the end of the 21st century, 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) [Table 3-2; 3.4.8]. Climate change is projected to reduce renewable surface water and groundwater resources significantly in most dry subtropical regions (high agreement, robust evidence) [3.4; 3.5]. This will exacerbate competition for water among agriculture, ecosystems, settlements, industry and energy production, affecting regional water, energy and food security [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 greenhouse-gas 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 (medium agreement, Subject to Final Copyedit 2 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 limited evidence). Flood hazards are projected to increase in parts of south, southeast and northeast Asia, tropical Africa, and South America (medium agreement, limited evidence). Since the mid-20th century, socio-economic 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 (medium agreement, limited evidence) [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 this century under the RCP8.5 scenario (medium confidence) [WGI Ch12]. This is likely to increase the frequency of short hydrological droughts (less surface water and groundwater) in these regions (medium agreement, medium evidence) [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 (high agreement, medium evidence). 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 due 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 (high agreement, medium evidence). 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 (high agreement, robust evidence) [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]. 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 (high agreement, robust evidence). 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 (medium agreement, limited evidence). 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 (high agreement, medium evidence). 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 (high agreement, limited evidence). Adaptive techniques include scenario planning, experimental approaches that involve learning Subject to Final Copyedit 3 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 (high agreement, limited evidence). 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 greenhouse gas emissions imply risks for freshwater systems (high agreement, medium evidence). 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]. 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 non-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. [INSERT FIGURE 3-1 HERE 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).] 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 mainly due to increases in temperature and sea level, local changes of precipitation, and changes in the variability of those quantities. • Semi-arid 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, mainly based 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 Chapter 4 for freshwater in cold regions and WGI Chapter 10 for detection and attribution, Chapter 11 for near-term Subject to Final Copyedit 4 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 projections, and Chapter 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 21-30. Sections 3.2.7, 3.4.8 and 3.6.3 discuss impact costs 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 of the documented change is not due to natural variability of the water cycle (Chapter 18; WGI 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 integrated, it is necessary to rely heavily on multi-step attribution, in which hydrological changes are shown to result from climatic changes that may in turn result partly from human activities. [INSERT TABLE 3-1 HERE 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 drivers, not all of which are necessarily anthropogenic; in the diagram, symbols with borders represent end-to-end attribution of the impact on resources to anthropogenic climate change. 1: Gerten et al. (2008), Piao et al. (2010), Alkama et al. (2011); 2: Piao et al. (2010); 3: Shiklomanov et al. (2007); 4: Hidalgo et al. (2009); 5: Collins (2008); 6: Baraer et al. (2012); 7: Rosenzweig et al. (2007); 8: Min et al. (2011); 9: Pall et al. (2011); 10: Aguilera and Murillo (2009); 11: Jeelani (2008); 12: Evans et al. (2005); 13: Marcé et al. (2010); 14: Pednekar et al. (2005); 15: Paerl et al. (2006); 16: Tibby and Tiller (2007).] 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 rctrl in the simulated actual climate and rexpt in the simulated climate in which there is no anthropogenic forcing, and suppose there are many paired instances of rctrl and rexpt, with the ratio of risks in each pair given by F = rexpt/rctrl. 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 was 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 three-fold, and at most a few percent of the simulation pairs suggested that anthropogenic forcing actually decreased the risk. This summary is worded carefully: the Subject to Final Copyedit 5 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 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 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, in diurnal temperature range, aerosol concentration, (net) solar radiation, vapour 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 (Fischer et al., 2013; Gemmer et al., 2011), 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 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 GHGs (greenhouse gases) due to permafrost degradation can have unprecedented impacts on the climate, but these processes are not well represented in global climate models yet (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 US 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 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 stream flow 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 Subject to Final Copyedit 6 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 observed streamflow changes due to decreased stomatal opening of many plant species at higher CO2 concentration remains disputed (Box CC-VW). In regions with seasonal snow storage, warming since the 1970s has led to earlier spring discharge maxima (high agreement, robust evidence) 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 due 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, due 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 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 (high agreement, medium to robust evidence). Greater runoff results in greater loads of salts, faecal coliforms, pathogens and heavy metals (Boxall et al., 2009; Paerl et al., 2006; Pednekar et al., 2005; Tibby and Tiller, 2007) (medium to high agreement, robust evidence, 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 hurricanes (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 (medium to high agreement, robust evidence) (Benítez-Gilabert et al., 2010; Boxall et al., 2009; Gascuel-Odoux et al., 2010; Howden et al., 2010; Loos et al., 2009; Macleod et al., 2012; Saarinen et al., 2010; Tetzlaff et al., 2010). 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 (Benítez- Gilabert et al., 2010; Chang, 2004; Ozaki et al., 2003) (medium agreement, limited evidence). Studies of impacts on groundwater quality are limited and mostly report elevated concentrations of faecal coliforms during the rainy season or after extreme rain events (high agreement, medium evidence), with varying response times (Auld et al., 2004; Curriero et al., 2001; Jean et al., 2006; Seidu et al., 2013; Tumwine et al., 2002; 2003). 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 (medium agreement, limited evidence). 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 Subject to Final Copyedit 7 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 regime and the many other possible sources of pollution (high confidence, Benítez-Gilabert et al., 2010; Howden et al., 2010; Kundzewicz and Krysanova, 2010; Senhorst and Zwolsman, 2005; Ventela et al., 2011; Whitehead et al., 2009a). [INSERT FIGURE 3-2 HERE Figure 3-2: Observations of the impacts of climate on water quality.] 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 (Bussi et al., 2013; Nyman et al., 2011). 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 (Miao et al., 2011; Wang et al., 2007). 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. Potential 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 have 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 predominantly triggered by monsoon and tropical cyclone activity, are largely attributed to population growth leading to increased exposure (Petley, 2012). In summary, there is low agreement and limited evidence 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). Subject to Final Copyedit 8 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 There is no strong evidence for trends in observed flooding in the USA (Hirsch and Ryberg, 2012), Europe (Benito and Machado, 2012; Hannaford and Hall, 2012; Mudelsee et al., 2003; Stahl et al., 2010), 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 (Giuntoli et al., 2012; Hattermann et al., 2012; Petrow and Merz, 2009), 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 towards earlier seasonal flood peaks, but flood magnitudes show contrasting trends, driven by temperature and precipitation, in basins with and without glaciers: increasing peaks in the former and decreasing peaks in the latter (Dahlke et al., 2012; Wilson et al., 2010). 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 favourable 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). Socio-economic 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 7 billion US$ per year in the 1980s to about 24 billion US$ per year in 2011 (Munich Re, 2012; 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 1980, the annual number of flood-related deaths has been in the thousands, with over 95% in developing countries and 75% in southern, southeastern and eastern Asia (Handmer et al., 2012). There is high confidence (high agreement, medium evidence) 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; Benito and Machado, 2012; Hilker et al., 2009), although there are exceptions (Chang et al., 2009; Jiang et al., 2005). 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, Standardised Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Standardised 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 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 towards lower summer minimum flows for 1962–2004 in small catchments in southern and eastern Europe were found, 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 ENSO (El Niño-Southern Oscillation) 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). Subject to Final Copyedit 9 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 Chapter 2). Among other climatic drivers are atmospheric carbon dioxide, 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 modelling of the atmospheric response to external forcing, and the external forcing itself as described by the Representative Concentration Pathways (RCPs; Section 1.1.3 in Chapter 1). Internal variability and variation between models account for all of the uncertainty in precipitation in the first few decades of the 21st century in CMIP (Coupled Model Intercomparison Project) Phase 3 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 Chapter 11) is due mostly to divergent scenarios. CMIP5 simulations of the water cycle during the 21st century (WGI 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, but by about 1.5 times more over land than over ocean (very high confidence). • 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 latitudes, 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 Chapter 12, 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 (Figure 12-25 in WGI Chapter 12). 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; Figure 12-23 and Section 12.4.5.3 in WGI Chapter 12). 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 (Berg et al., 2013; Utsumi et al., 2011). 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 1.5-2.5% K–1, the 20-year return amount of daily precipitation typically increases at 4-10% K–1. Agreement between model-simulated extremes and reanalysis extremes is good in the extra-tropics but poor in the tropics, where there is robust evidence of greater Subject to Final Copyedit 10 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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, socio-economic and technological changes, including lifestyle changes. These change both exposure to hazard and requirements for water resources. A wide range of socio-economic 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 socio-economic 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). Due 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 due 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. Arnell, 2011; Arnell and Gosling, 2013; Bae et al., 2011; Chiew et al., 2009; Gosling et al., 2010; Jackson et al., 2011; Kling et al., 2012; Olsson et al., 2011). 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; Christierson et al., 2012; Liu et al., 2013; Manning et al., 2009). 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 only used 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 (Chen J. et al., 2011; Quintana Segui et al., 2010). 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 (Piani et al., 2010; van Pelt et al., 2009; 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 Subject to Final Copyedit 11 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 largely depends on simulated precipitation and is better for large basins, but the limited evidence suggests 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 (Arnell, 2011; Cloke et al., 2010; Lawrence and Haddeland, 2011; Steele-Dunne et al., 2008; Vaze et al., 2010). 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), due 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 which would be critical for a system and then uses a hydrological model to determine the meteorological conditions which 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; 2008b). 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 characterise 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 show 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 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 CO2 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 risk of extreme hot days (Hirschi et al., 2011; Seneviratne et al., 2006) and heat waves. For a range of scenarios, soil-moisture droughts lasting 4–6 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 current climate. Changes consistent with warming are also evident in the freshwater systems and permafrost of northern regions. The area of permafrost is projected to continue to decline over the first half of the 21st century in all emissions scenarios (Figure 4-18 in WGI Chapter 4). Under RCP2.6, permafrost area is projected to stabilize at near 20% less than the 20th century area, and then begin to increase slightly. Subject to Final Copyedit 12 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 3.4.3. Glaciers All projections for the 21st century (WGI 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 towards 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 ~105 km2 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 only be dated 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. _____ START BOX 3-1 HERE _____ 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 five 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. [INSERT FIGURE 3-3 HERE 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 multi-annual measurements). Region-wide measurement (Kääb et al., 2012) was by satellite laser altimetry. Global average (WGI Chapter 4) is shown as a 1- sigma confidence region.] 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 15-78% 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 over-compensates for the loss of ice. Subject to Final Copyedit 13 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 70-200 mm/year 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 afterwards (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. _____ END BOX 3-1 HERE _____ 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 largely 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. Arnell and Gosling, 2013; Döll and Zhang, 2010; Fung et al., 2011; Hirabayashi et al., 2008; Murray et al., 2012; Nakaegawa et al., 2013; Okazaki et al., 2012; Schewe et al., 2013; Tang and Lettenmaier, 2012; Weiland et al., 2012a). 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 largely driven 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 2oC 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 Chapter 12 (Figure 12-24), largely because it is based on fewer climate models. [INSERT FIGURE 3-4 HERE 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 4 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).] 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 2oC 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 4oC rise in temperature. In the Mitano catchment in Uganda, for example, there is a non-linear relationship between amount of Subject to Final Copyedit 14 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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. [INSERT FIGURE 3-5 HERE Figure 3-5: Change in mean monthly runoff across seven climate models in seven catchments, with a 2oC increase in global mean temperature above 1961-1990 (Arnell, 2011; Hughes et al., 2011; Kingston and Taylor, 2010; 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 2oC increase (dotted line) and a 4oC increase (solid line).] 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 areas 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 which currently experience considerable snowfall, where the marginal effect on snowfall and snowmelt of higher temperatures 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 (Green et al., 2011; Taylor R. et al., 2013a) has increased significantly since then. Ensemble studies, relying on between four and twenty 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 semi-arid High Plains aquifer of the USA (Crosbie et al., 2013b; Ng et al., 2010). 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 CO2 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 due to exceedance of the infiltration capacity (typically in humid areas), or may increase it due to faster percolation through the root zone and thus reduced evapotranspiration (typically in semi-arid 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 (Crosbie et al., 2013b; van Roosmalen et al., 2007). The sensitivity of groundwater recharge change to precipitation change was found to be highest for low groundwater recharge and lowest for high groundwater recharge, the ratio of recharge change to precipitation change ranging from 1.5 to 6.0 in the semi-arid 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- 70% of groundwater recharge, although only 25-50% 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 Subject to Final Copyedit 15 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 interface. While 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 meter, the thickness of the unconfined freshwater layer decreases by roughly 40 meter (Ghyben-Herzberg relation). Deltas are also affected by storm surges that drive salt water 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). Salt water 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 semi-arid areas where the groundwater table is within 2-10 meter of the surface (Ferguson and Maxwell, 2010; Jiang et al., 2009). 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 (Andersen et al., 2006; Arheimer et al., 2005; Bonte and Zwolsman, 2010; Ducharne, 2008; Marshall and Randhir, 2008; Rehana and Mujumdar, 2012; Towler et al., 2010; Trolle et al., 2011; Wilby et al., 2006). 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 (a) local conditions; (b) climatic and environmental assumptions; and (c) the current or reference pollution state (Bonte and Zwolsman, 2010; Chang, 2004; Kundzewicz and Krysanova, 2010; Sahoo et al., 2010; Trolle et al., 2011; Whitehead et al., 2009a; 2009b). 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 (Bonte and Zwolsman, 2010; Brikowski, 2008; Ducharne, 2008; Loos et al., 2009; Marshall and Randhir, 2008; Qin et al., 2010; Sahoo et al., 2010; Trolle et al., 2011), rivers (Andersen et al., 2006; Bowes et al., 2012; Whitehead et al., 2009a; 2009b) 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 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 CO2 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 40-50% in Australia and Africa (Yang et al., 2003). The largest increases are expected in semiarid areas, where a single event may contribute 40% of total annual erosion (Bussi et al., 2013). In agricultural lands in temperate regions, soil erosion may respond to more intense erosion in complex non-linear ways; for instance in the UK a 10% increase in winter rainfall (i.e. during early growing season) could increase annual erosion Subject to Final Copyedit 16 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 of arable land by up to 150% (Favis-Mortlock and Boardman, 1995), while in Austria a simulation for 2010–2099 projected a decrease of rainfall by 10-14% in erosion-sensitive months and thus a decline in soil erosion by 11-24% (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 5-195% during 2010-2039 under conventional tillage, for three emission scenarios (A2, B2 and GGa), whereas under conservation tillage they show decreases of 26-77% (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 11-14% in two Danish rivers under the SRES A2 emission scenario was projected to increase the annual suspended sediment load by 9–16% 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 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 2-11% 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 due to the non-linear 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 SREX report (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 due to variation between climate models and their coupling to hydrological models. [INSERT FIGURE 3-6 HERE 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 CMIP5 GCMs under 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. 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 (coloured thick lines) for each scenario. Shading denotes ±1 standard deviation. Right: maximum and minimum (whiskers), mean (horizontal thick lines within each bar), ±1 standarddeviation (box) and projections of each GCM (coloured symbols) 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 4-14 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 0.4-1.2% 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 7-25, depending on the RCP, with strong increases in Asia and Africa due to high population growth.] 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 Chapter 12; Orlowsky and Seneviratne, 2013; Vidal et al., Subject to Final Copyedit 17 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 2012), 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 characterise ‘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, 18-30% of the land surface (excluding cold areas) experienced a significant increase in the frequency of 3-month hydrological droughts, whilst approximately 15-45% 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), short hydrological droughts are projected to increase in frequency whilst 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, due 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. Projections from 21 GCMs under SRES A1B of the population exposed by 2050 to a doubling of flood frequency range from 31 to 449 million people, and the change in risk varies between -9 and +376% (Arnell and Gosling, 2013). Studies of projected flood damages are mainly focussed in Europe, the USA and Australia (Bouwer, 2013; Handmer et al., 2012). 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 pre-industrial 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). [INSERT TABLE 3-2 HERE Table 3-2: Effects of different GHG emissions scenarios on hydrological changes and freshwater-related impacts of climate change on humans and ecosystems. Among the SRES scenarios, GHG emissions are highest in A1f and A2, lower in A1 and B2, and lowest in B1. 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, quantified as the CMIP5 model Subject to Final Copyedit 18 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 mean) over different reference periods, typically since pre-industrial. GW is projected to be, for RCP8.5, approximately 2°C in the 2040s and 4°C in the 2080s. For RCP6.0, GW is 2°C in the 2060s and 2.5°C in the 2080s, while in RCP2.6, GW stays below 1.8°C throughout the 21st century (Figure 1-4 in Chapter 1). Population scenario SSP2 assumes a medium population increase.] 3.5.1. Availability of Water Resources Approximately 80% of the world’s population already suffers serious threats to its water security, as measured by indicators including water availability, water demand and pollution (Vörösmarty et al., 2010). Climate change can alter the availability of water and therefore threaten water security. 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 (Arnell et al., 2011; Arnell et al., 2013; Fung et al., 2011; Gerten et al., 2013; Gosling and Arnell, 2013; Hayashi et al., 2010; Murray et al., 2012; 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 which 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 2oC above pre-industrial, 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 approximately 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 1oC rise in global mean temperature (compared to the 1990s), rising to 14% at 2oC and 17% at 3oC; the spread across climate and hydrological models was, however, large. [INSERT FIGURE 3-7 HERE Figure 3-7: Human vulnerability to climate-change induced decreases of renewable groundwater resources by the 2050s. Lower (B2) and higher (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 the vulnerability. The index is only defined for areas where groundwater recharge is projected to decrease by at least 10% relative to 1961-1990 (Döll, 2009)] Under climate change, reliable surface water supply is expected to decrease due to increased variability of river flow that is due in turn to 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 only sustainable 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 11-39%) for RCP2.6 to 38% (range 27-50%) for RCP8.5 (Portmann et al., 2013; Table 3-2). The land area affected by decreases of groundwater resources increases linearly Subject to Final Copyedit 19 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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, the 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 7–21% 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 partly be explained 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 CO2 concentration (CO2 fertilization) might partly cancel out the adverse effects of climate change, potentially reducing global irrigation water demand (Konzmann et al., 2013; 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 CO2 effects, i.e. decreases in per-calorie water demand. The CO2 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 CO2 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 modelling study (Rost et al., 2009). In some 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 Subject to Final Copyedit 20 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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; 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 3.2.5) 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 (Golombek et al., 2012; Renofalt et al., 2010). 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 due 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 in Europe and the USA, due to increases in stream temperatures and the incidence of low flows (Flörke et al., 2012; van Vliet et al., 2012; Table 3-2). Warmer cooling water was computed to lower thermal power plant efficiency and thus electricity production by 1.5-3% in European countries by the 2080s under emissions scenario 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; Black and King, 2009; Bonte and Zwolsman, 2010; Brooks et al., 2009; Chakraborti et al., 2011; Christierson et al., 2012; Hall and Murphy, 2010; Jiménez, 2008; Major et al., 2011; Mukhopadhyay and Dutta, 2010; Qin et al., 2010; Thorne and Fenner, 2011; van Vliet and Zwolsman, 2008; Whitehead et al., 2009a): • 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). Subject to Final Copyedit 21 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 • 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 (Arnell et al., 2011; Zwolsman et al., 2010). 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 designs, 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; 2009b; 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 faecal 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 comprised 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 Chapter 4.3.3.3) but also 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; Section 3.7.2). Subject to Final Copyedit 22 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 (Badjeck et al., 2010; Beniston, 2012; Koetse and Rietveld, 2009; Pinter et al., 2006; Rabassa, 2009). 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; Buhaug et al., 2010; Burke et al. 2009; 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). While 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. 3.6.1. Options There is growing agreement that an adaptive approach to water management 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 programme of adaptation typically mixes “hard” infrastructural and “soft” institutional measures (Bates et al., 2008; Cooley, 2008; Mertz et al., 2009; Olhoff and Schaer, 2010; Sadoff and Muller, 2009; UNECE, 2009). [INSERT TABLE 3-3 HERE Table 3-3: Categories of climate change adaptation options for the management of freshwater resources. A+M: may assist both adaptation and mitigation (1) This includes water reuse, rain water harvesting, and desalination, among others. With information from: Arkell (2011a; 2011b); Andrews (2009); Bahri (2009); Bowes et al. (2012); de Graaf and der Brugge (2010); Dembo (2010); Dillon and Jiménez (2008); Elliott et al. (2011); Emelko et al. (2011); Godfrey et al. (2010); Howard et al. (2010); Jiménez and Asano (2008); Jiménez (2011); Keller (2008); Kingsford (2011); Mackay and Last (2010); Major et al. (2011); Marsalek et al. (2006); McCafferty (2008); McGuckin (2008); Mogaka et al. (2006); Mukhopadhyay and Dutta (2010); Munasinghe (2009); NACWA (2009); OECD (2010); OFWAT (2009); Reiter (2009); Renofalt et al. (2010); Seah (2008); Sprenger et al. (2011); Thöle (2008); UNESCO (2011); UNHABITAT (2008); Vörösmarty et al. (2000); Wang X. et al. (2011); Whitehead et al. (2009b); Zwolsman et al. (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). Subject to Final Copyedit 23 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 16.5 in Chapter 16. 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 (Bergsma et al., 2012; Engle and Lemos, 2010; Goulden et al., 2009; Huntjens et al., 2010; Stuart-Hill and Schulze, 2010; Wilby and Vaughan, 2011; Ziervogel et al., 2010); 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 abundant. Changes in operating practices and infrastructure improvements could help California’s water managers respond to changes in the volume and timing of supply (Connell-Buck et al., 2011; Medellin-Azuara et al., 2008). 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 characterise the potential range of impacts on water resources and flooding. Others (e.g. Brekke et al., 2008; Christierson et al., 2012; Hall et al., 2012; Lopez et al., 2009) use very large numbers of scenarios to generate likelihood distributions of indicators of impact for use in risk assessment. However, it has been argued (Dessai et al., 2009; Hall, 2007; Stainforth et al., 2007) that attempts to construct probability distributions of impacts are misguided because of “deep” uncertainty, which arises because analysts do not know, or cannot agree upon, 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 (Anagnostopoulos et al., 2010; Blöschl and Montanari, 2010; Koutsoyiannis et al., 2008; 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 (Huard, 2011; Koutsoyiannis et al., 2009; 2011); the critique also assumes that adaptation assessment procedures would only use 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 towards adaptive water management (Gersonius et al., 2013; Huntjens et al., 2012; Matthews and Wickel, 2009; Mysiak et al., 2009; Pahl-Wostl, 2007; Pahl-Wostl et al., 2008; Short et al., 2012) and the adoption of resilient or “no-regrets” approaches (Henriques and Spraggs, 2011; WWAP, 2009). 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, whilst climate change is frequently cited as a key motive, there is very little published guidance on how to implement the adaptive water Subject to Final Copyedit 24 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 management approach. Some examples are given in Ludwig et al. (2009). The most comprehensive overview of adaptive water management which explicitly incorporates climate change and its uncertainty is the three-step framework of the US 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). 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, with US$451 billion (85%) required in developing countries, mainly in Asia and Africa (Kirshen, 2007). Including two further costs, for reservoir construction since 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 (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$14.0 billion for a dry GCM projection of the SRES A2 scenario and US$19.7 billion for a wet GCM projection (World Bank, 2010; Ward et al., 2010). Annual urban infrastructure costs, primarily for wastewater treatment and urban drainage, were US$13.7 billion (dry) and US$27.5 billion (wet). Under both GCM projections for the A2 scenario, the water sector accounted for approximately 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$1.1–2.7 billion for current urban water infrastructure, plus US$1.0–2.5 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 $0.15-0.5 billion for existing facilities and $0.55-1.5 billion for new developments. For wastewater treatment, the equivalent estimates are $0.1-0.2 billion and $0.075-0.2 billion. For the coterminous United States under “business as usual”, over 45% of economic costs are due to water quality and environmental flow impacts, suggesting significant costs for wastewater treatment infrastructure (Henderson et al., 2013). 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). Subject to Final Copyedit 25 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 [INSERT TABLE 3-4 HERE 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.] 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 km2) 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- 100% were computed, mostly in semi-arid 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 (Trabucco et al., 2008; van Dijk and Keenan, 2007; 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 meter 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 semi-arid 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. Subject to Final Copyedit 26 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 management 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/km2 (Gunkel, 2009). CO2 leakage to freshwater aquifers from saline aquifers used for carbon capture and storage (CCS) can lower pH by 1-2 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 approximately 9,000-30,000 m3 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 17-20% 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 1.3-3.1% of current global CO2 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 CO2 storage in soils by reducing water stress and so enhancing biomass production. Irrigation in semi-arid California did not significantly increase soil organic carbon (Wu et al., 2008). Water management in rice paddies can reduce CH4 emissions. If rice paddies are drained at least once during the growing season, with resulting increased water withdrawals, global CH4 emissions from rice fields could be decreased by 4.1 Tg/year (16% around the year 2000), and N2O 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 socio-economic data, such as rates of surface water and groundwater withdrawal by each sector, and information on already-implemented Subject to Final Copyedit 27 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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. 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. Morover, the establishment of a proper baseline to isolate the effects derived from climate change from those antropogenic caused 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 on 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. Frequently Asked Questions FAQ 3.1: How will climate change affect the frequency and severity of floods and droughts? [to be placed in Section 3.4.9] 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 south-east 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 Subject to Final Copyedit 28 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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. FAQ 3.2: How will the availability of water resources be affected by climate change? [to be placed in Section 3.5.1] 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. FAQ 3.3: How should water management be modified in the face of climate change? [to be placed in Section 3.6.1] 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 re-use, 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. FAQ 3.4: Does climate change imply only bad news about water resources? [to be placed after Section 3.6] 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. Subject to Final Copyedit 29 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Box CC-RF. Impact of Climate Change on Freshwater Ecosystems due to Altered River Flow Regimes [Petra Döll (Germany), Stuart E. Bunn (Australia)] It is widely acknowledged that the flow regime is a primary determinant of the structure and function of rivers and their associated floodplain wetlands, and flow alteration is considered to be a serious and continuing threat to freshwater ecosystems (Bunn and Arthington, 2002; Poff and Zimmerman, 2010; Poff et al., 2010). Most species distribution models do not consider the effect of changing flow regimes (i.e. changes to the frequency, magnitude, duration and/or timing of key flow parameters) or they use precipitation as proxy for river flow (Heino et al., 2009). There is growing evidence that climate change will significantly alter ecologically important attributes of hydrologic regimes in rivers and wetlands, and exacerbate impacts from human water use in developed river basins (medium confidence) (Aldous et al., 2011; Xenopoulos et al., 2005). By the 2050s, climate change is projected to impact river flow characteristics like long-term average discharge, seasonality and statistical high flows (but not statistical low flows) more strongly than dam construction and water withdrawals have done up to around the year 2000 (Figure RF-1; Döll and Zhang, 2010). For one climate scenario (SRES A2 emissions, HadCM3 climate model), 15% of the global land area may be negatively affected, by the 2050s, by a decrease of fish species in the upstream basin of more than 10%, as compared to only 10% of the land area that has already suffered from such decreases due to water withdrawals and dams (Döll and Zhang, 2010). Climate change may exacerbate the negative impacts of dams for freshwater ecosystems but may also provide opportunities for operating dams and power stations to the benefit of riverine ecosystems. This is the case if total runoff increases and, as occurs in Sweden, the annual hydrograph becomes more similar to variation in electricity demand, i.e. with a lower spring flood and increased runoff during winter months (Renofalt et al., 2010). Because biota are often adapted to a certain level of river flow variability, the projected larger variability of river flows that is due to increased climate variability is likely to select for generalist or invasive species (Ficke et al., 2007). The relatively stable habitats of groundwater-fed streams in snow-dominated or glacierized basins may be altered by reduced recharge by meltwater and as a result experience more variable (possibly intermittent) flows (Hannah et al., 2007). A high-impact change of flow variability is a flow regime shift from intermittent to perennial or vice versa. It is projected that until the 2050s, river flow regime shifts may occur on 5-7% of the global land area, mainly in semi-arid areas (Döll and Müller Schmied, 2012; see Table 3-2 in Chapter 3). In Africa, one third of fish species and one fifth of the endemic fish species occur in eco-regions that may experience a change in discharge or runoff of more than 40% by the 2050s (Thieme et al., 2010). Eco-regions containing over 80% of Africa’s freshwater fish species and several outstanding ecological and evolutionary phenomena are likely to experience hydrologic conditions substantially different from the present, with alterations in long-term average annual river discharge or runoff of more than 10% due to climate change and water use (Thieme et al., 2010). Due to increased winter temperatures, freshwater ecosystems in basins with significant snow storage are affected by higher river flows in winter, earlier spring peak flows and possibly reduced summer low flows (Section 3.2.3 in Chapter 3). Strongly increased winter peak flows may lead to a decline in salmonid populations in the Pacific Northwest of the USA of 20-40% by the 2050s (depending on the climate model) due to scouring of the streambed during egg incubation, the relatively pristine high-elevation areas being affected most (Battin et al., 2007). Reductions in summer low flows will increase the competition for water between ecosystems and irrigation water users (Stewart et al., 2005). Ensuring environmental flows through purchasing or leasing water rights and altering reservoir release patterns will be an important adaptation strategy (Palmer et al., 2009). [INSERT FIGURE RF-1 HERE Figure RF-1: Impact of climate change relative to the impact of water withdrawals and dams on natural flows for two ecologically relevant river flow characteristics (mean annual river flow and monthly low flow Q90), computed by a global water model (Döll and Zhang, 2010). Monthly Q90 was defined as the flow that is exceeded in 9 out 10 months. Impact of climate change is the percent change of flow between 1961-1990 and 2041-2070 according to the emissions scenario A2 as implemented by the global climate model HadCM3. Impact of water withdrawals and Subject to Final Copyedit 30 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 reservoirs is computed by running the model with and without water withdrawals and dams that existed in 2002. Please note that the figure does not reflect spatial differences in the magnitude of change.] Observations and models suggest that global warming impacts on glacier and snow-fed streams and rivers will pass through two contrasting phases (Burkett et al., 2005; Vuille et al., 2008; Jacobsen et al., 2012). In the first phase, when river discharge is increased due to intensified melting, the overall diversity and abundance of species may increase. However, changes in water temperature and stream-flow may have negative impacts on narrow range endemics (Jacobsen et al., 2012). In the second phase, when snowfields melt early and glaciers have shrunken to the point that late-summer stream flow is reduced, broad negative impacts are foreseen, with species diversity rapidly declining once a critical threshold of roughly 50% glacial cover is crossed (Figure RF-2). River discharge also influences the response of river temperatures to increases of air temperature. Globally averaged, air temperature increases of 2°C, 4°C and 6°C are estimated to lead to increases of annual mean river temperatures of 1.3°C, 2.6°C and 3.8°C, respectively (van Vliet et al., 2011). Discharge decreases of 20% and 40% are computed to result in additional increases of river water temperature of 0.3° C and 0.8°C on average (van Vliet et al., 2011). Therefore, where rivers will experience drought more frequently in the future, freshwater-dependent biota will suffer not only directly by changed flow conditions but also by drought-induced river temperature increases, as well as by related decreased oxygen and increased pollutant concentrations. [INSERT FIGURE RF-2 HERE Figure RF-2: Accumulated loss of regional species richness (gamma diversity) of macroinvertebrates as a function of glacial cover in catchment. Obligate glacial river macroinvertebrates begin to disappear from assemblages when glacial cover in the catchment drops below approximately 50%, and 9-14 species are predicted to be lost with the complete disappearance of glaciers in each region, corresponding to 11, 16 and 38% of the total species richness in the three study regions in Ecuador, Europe and Alaska. Data are derived from multiple river sites from the Ecuadorian Andes and Swiss and Italian Alps, and a temporal study of a river in the Coastal Range Mountains of southeast Alaska over nearly three decades of glacial shrinkage. Each data point represents a river site or date (Alaska), and lines are Lowess fits. Adapted by permission from Macmillan Publishers Ltd: Nature Climate Change, Jacobsen et al., 2012, © 2012.] Box CC-RF References Aldous, A., J. Fitzsimons, B. Richter, and L. Bach, 2011: Droughts, floods and freshwater ecosystems: evaluating climate change impacts and developing adaptation strategies. Marine and Freshwater Research, 62(3), 223-231. Battin, J., M.W. Wiley, M.H. Ruckelshaus, R.N. Palmer, E. Korb, K.K. Bartz, and H. Imaki, 2007: Projected impacts of climate change on salmon habitat restoration. Proceedings of the National Academy of Science, 104(16), 6720-6725. Bunn, S. and A. Arthington, 2002: Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environmental Management, 30(4), 492-507. Burkett, V., D. Wilcox, R. Stottlemyer, W. Barrow, D. Fagre, J. Baron, J. Price, J. Nielsen, C. Allen, D. Peterson, G. Ruggerone, and T. Doyle, 2005: Nonlinear dynamics in ecosystem response to climatic change: Case studies and policy implications. Ecological Complexity, 2(4), 357-394. Döll, P. and H. Müller Schmied, 2012: How is the impact of climate change on river flow regimes related to the impact on mean annual runoff? A global-scale analysis. Environmental Research Letters, 7(1), 014037. Döll, P. and J. Zhang, 2010: Impact of climate change on freshwater ecosystems: a global-scale analysis of ecologically relevant river flow alterations. Hydrology and Earth System Sciences, 14(5), 783-799. Ficke, A.D., C.A. Myrick, and L.J. Hansen, 2007: Potential impacts of global climate change on freshwater fisheries. Reviews in Fish Biology and Fisheries, 17(4), 581-613. Hannah, D.M., L.E. Brown, A.M. Milner, A.M. Gurnell, G.R. McGregord, G.E. Petts, B.P.G. Smith, and D.L. Snook, 2007: Integrating climate- hydrology-ecology for alpine river systems. Aquatic Conservation-Marine and Freshwater Ecosystems, 17(6), 636-656. Heino, J., R. Virkalla, and H. Toivonen, 2009: Climate Change and freshwater biodiversity: detected patterns, future trends and adaptations in northern regions. Biological Reviews, 84(1), 39-54. Jacobsen, D., A.M. Milner, L.E. Brown, and O. Dangles, 2012: Biodiversity under threat in glacier-fed river systems. Nature Climate Change, 2(5), 361-364. Subject to Final Copyedit 31 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Palmer, M.A., D.P. Lettenmaier, N.L. Poff, S.L. Postel, B. Richter, and R. Warner, 2009: Climate change and river ecosystems: protection and adaptation options. Environmental Management, 44(6), 1053-1068. Poff, N.L., B.D. Richter, A.H. Arthington, S.E. Bunn, R.J. Naiman, E. Kendy, M. Acreman, C. Apse, B.P. Bledsoe, M.C. Freeman, J. Henriksen, R.B. Jacobson, J.G. Kennen, D.M. Merritt, J.H. O'Keeffe, J.D. Olden, K. Rogers, R.E. Tharme, and A. Warner, 2010: The ecological limits of hydrologic alteration (ELOHA): a new framework for developing regional environmental flow standards. Freshwater Biology, 55(1), 147-170. Poff, N.L. and J.K.H. Zimmerman, 2010: Ecological responses to altered flow regimes: a literature review to inform the science and management of environmental flows. Freshwater Biology, 55(1), 194-205. Renofalt, B.M., R. Jansson, and C. Nilsson, 2010: Effects of hydropower generation and opportunities for environmental flow management in Swedish riverine ecosystems. Freshwater Biology, 55(1), 49-67. Stewart, I., D. Cayan, and M. Dettinger, 2005: Changes toward earlier streamflow timing across western North America. Journal of Climate, 18(8), 1136-1155. Thieme, M.L., B. Lehner, R. Abell, and J. Matthews, 2010: Exposure of Africa's freshwater biodiversity to a changing climate. Conservation Letters, 3(5), 324-331. van Vliet, M.T.H., F. Ludwig, J.J.G. Zwolsman, G.P. Weedon, and P. Kabat, 2011: Global river temperatures and sensitivity to atmospheric warming and changes in river flow. Water Resources Research, 47(2), W02544. Vuille, M., B. Francou, P. Wagnon, I. Juen, G. Kaser, B.G. Mark, and R.S. Bradley, 2008: Climate change and tropical Andean glaciers: past, present and future. Earth-Science Reviews, 89(3-4), 79-96. Xenopoulos, M., D. Lodge, J. Alcamo, M. Marker, K. Schulze, and D. Van Vuuren, 2005: Scenarios of freshwater fish extinctions from climate change and water withdrawal. Global Change Biology, 11(10), 1557-1564. Box CC-VW. Active Role of Vegetation in Altering Water Flows under Climate Change [Dieter Gerten (Germany), Richard Betts (UK), Petra Döll (Germany)] Climate, vegetation and carbon and water cycles are intimately coupled, in particular via the simultaneous transpiration and CO2 uptake through plant stomata in the process of photosynthesis. Hence, water flows such as runoff and evapotranspiration are affected not only directly by anthropogenic climate change as such (i.e. by changes in climate variables such as temperature and precipitation), but also indirectly by plant responses to increased atmospheric CO2 concentrations. In addition, effects of climate change (e.g. higher temperature or altered precipitation) on vegetation structure, biomass production and plant distribution have an indirect influence on water flows. Rising CO2 concentration affects vegetation and associated water flows in two contrasting ways, as suggested by ample evidence from Free Air CO2 Enrichment (FACE), laboratory and modelling experiments (e.g. Leakey et al., 2009; de Boer et al., 2011; Reddy et al., 2010). On the one hand, a physiological effect leads to reduced opening of stomatal apertures, which is associated with lower water flow through the stomata, i.e. lower leaf-level transpiration. On the other hand, a structural effect (“fertilization effect”) stimulates photosynthesis and biomass production of C3 plants including all tree species, which eventually leads to higher transpiration at regional scales. A key question is to what extent the climate- and CO2-induced changes in vegetation and transpiration translate into changes in regional and global runoff. The physiological effect of CO2 is associated with an increased intrinsic water use efficiency (WUE) of plants, which means that less water is transpired per unit of carbon assimilated. Records of stable carbon isotopes in woody plants (Peñuelas et al., 2011) verify this finding, suggesting an increase in WUE of mature trees by 20.5% between the early 1960s and the early 2000s. Increases since pre-industrial times have also been found for several forest sites (Andreu-Hayles et al., 2011; Gagen et al., 2011; Loader et al., 2011; Nock et al., 2011) and in a temperate semi- natural grassland (Koehler et al., 2010), although in one boreal tree species WUE ceased to increase after 1970 (Gagen et al., 2011). Analysis of long-term whole-ecosystem carbon and water flux measurements from 21 sites in North American temperate and boreal forests corroborates a notable increase in WUE over the two past decades (Keenan et al., 2013). An increase in global WUE over the past century is supported by ecosystem model results (Ito and Inatomi, 2012). A key influence on the significance of increased WUE for large-scale transpiration is whether vegetation structure and production has remained approximately constant (as assumed in the global modelling study by Gedney et al., 2006) or has increased in some regions due to the structural CO2 effect (as assumed in models by Piao et al., 2007; Subject to Final Copyedit 32 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Gerten et al., 2008). While field-based results vary considerably among sites, tree ring studies suggest that tree growth did not increase globally since the 1970s in response to climate and CO2 change (Peñuelas et al., 2011; Andreu-Hayles et al., 2011). However, basal area measurements at over 150 plots across the tropics suggest that biomass and growth rates in intact tropical forests have increased in recent decades (Lewis et al., 2009). This is also confirmed for 55 temperate forest plots, with a suspected contribution of CO2 effects (McMahon et al., 2010). Satellite observations analysed in Donohue et al. (2013) suggest that an increase in vegetation cover by 11% in warm drylands (1982–2010 period) is attributable to CO2 fertilization. Owing to the interplay of physiological and structural effects, the net impact of CO2 increase on global-scale transpiration and runoff remains rather poorly constrained. This is also true because nutrient limitation, often omitted in modelling studies, can suppress the CO2 fertilization effect (see Rosenthal and Tomeo, 2013). Therefore, there are conflicting views on whether the direct CO2 effects on plants already have a significant influence on evapotranspiration and runoff at global scale. AR4 reported work by Gedney et al. (2006) which suggested that the physiological CO2 effect (lower transpiration) contributed to a supposed increase in global runoff seen in reconstructions by Labat et al. (2004). However, a more recent analysis based on a more complete dataset (Dai et al., 2009) suggested that river basins with decreasing runoff outnumber basins with increasing runoff, such that a small decline in global runoff is likely for the period 1948–2004. Hence, detection of vegetation contributions to changes in water flows critically depends on the availability and quality of hydrometeorological observations (Haddeland et al., 2011; Lorenz and Kunstmann, 2012). Overall, the evidence since AR4 suggests that climatic variations and trends have been the main driver of global runoff change in the past decades; both CO2 increase and land use change have contributed less (Piao et al., 2007; Gerten et al., 2008; Alkama et al., 2011; Sterling et al., 2013). Oliveira et al. (2011) furthermore pointed to the importance of changes in incident solar radiation and the mediating role of vegetation; according to their global simulations, a higher diffuse radiation fraction during 1960– 1990 may have increased evapotranspiration in the tropics by 3% due to higher photosynthesis from shaded leaves. It is uncertain how vegetation responses to future increases in CO2 and to climate change will modulate the impacts of climate change on freshwater flows. 21st century continental- and basin-scale runoff is projected by some models to either increase more or decrease less when the physiological CO2 effect is included in addition to climate change effects (Betts et al., 2007; Murray et al., 2012). This could somewhat ease the increase in water scarcity anticipated in response to future climate change and population growth (Gerten et al., 2011; Wiltshire et al., in press). In absolute terms, the isolated effect of CO2 has been modelled to increase future global runoff by 4–5% (Gerten et al., 2008) up to 13% (Nugent and Matthews, 2012) compared to the present, depending on the assumed CO2 trajectory and whether feedbacks of changes in vegetation structure and distribution to the atmosphere are accounted for (they were not in Nugent and Matthews, 2012). In a global model intercomparison study (Davie et al., in press), two out of four models projected stronger increases and, respectively, weaker decreases in runoff when considering CO2 effects compared to simulations with constant CO2 concentration (consistent with above findings, though magnitudes differed between the models), but two other models showed the reverse. Thus, the choice of models and the way they represent the coupling between CO2, stomatal closure and plant growth is a source of uncertainty, as also suggested by Cao et al. (2009). Lower transpiration due to rising CO2 concentration may also affect future regional climate change itself (Boucher et al., 2009) and enhance the contrast between land and ocean surface warming (Joshi et al., 2008). Overall, although physiological and structural effects will influence water flows in many regions, precipitation and temperature effects are likely to remain the prime influence on global runoff (Alkama et al., 2010). An application of a soil-vegetation-atmosphere-transfer model indicates complex responses of groundwater recharge to vegetation-mediated changes in climate, with computed groundwater recharge being always larger than would be expected from just accounting for changes in rainfall (McCallum et al., 2010). Another study found that even if precipitation slightly decreased, groundwater recharge might increase as a net effect of vegetation responses to climate change and CO2 rise, i.e. increasing WUE and either increasing or decreasing leaf area (Crosbie et al., 2010). Depending on the type of grass in Australia, the same change in climate is suggested to lead to either increasing or decreasing groundwater recharge in this location (Green et al., 2007). For a site in the Netherlands, a biomass decrease was computed for each of eight climate scenarios indicating drier summers and wetter winters (A2 emissions scenario), using a fully coupled vegetation and variably saturated hydrological model. The resulting Subject to Final Copyedit 33 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 increase in groundwater recharge up-slope was simulated to lead to higher water tables and an extended habitat for down-slope moisture-adapted vegetation (Brolsma et al., 2010). Using a large ensemble of climate change projections, Konzmann et al. (2013) put hydrological changes into an agricultural perspective and suggested that the net result of physiological and structural CO2 effects on crop irrigation requirements would be a global reduction (Figure VW-1). Thus, adverse climate change impacts on irrigation requirements and crop yields might be partly buffered as WUE and crop production improve (Fader et al., 2010). However, substantial CO2-driven improvements will only be realized if proper management abates limitation of plant growth by nutrient availability or other factors. [INSERT FIGURE VW-1 HERE Figure VW-1: Percentage change in net irrigation requirements of 11 major crops from 1971–2000 to 2070–2099 on areas currently equipped for irrigation, assuming current management practices. Top: impact of climate change including physiological and structural crop responses to increased atmospheric CO2 concentration (maximum effect in the absence of co-limitation by nutrients). Bottom: impact of climate change only. Shown is the median change derived from climate change projections by 19 GCMs (based on the SRES A2 emissions scenario) used to force a vegetation and hydrology model. Modified after Konzmann et al. (2013).] Changes in vegetation coverage and structure due to long-term climate change or shorter-term extreme events such as droughts (Anderegg et al., 2013) also affect the partitioning of precipitation into evapotranspiration and runoff, sometimes involving complex feedbacks with the atmosphere such as in the Amazon region (Port et al., 2012; Saatchi et al., 2013). One model in the study by Davie et al. (in press) showed regionally diverse climate change effects on vegetation distribution and structure, which had a much weaker effect on global runoff than the structural and physiological CO2 effects. As water, carbon and vegetation dynamics evolve synchronously and interactively under climate change (Heyder et al., 2011; Gerten et al., in press), it remains a challenge to disentangle the individual effects of climate, CO2 and land cover change on the water cycle. Box CC-VW References Alkama, R., M. Kageyama, and G. Ramstein, 2010: Relative contributions of climate change, stomatal closure, and leaf area index changes to 20th and 21st century runoff change: A modelling approach using the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model. Journal of Geophysical Research-Atmospheres, 115, D17112. Alkama, R., B. Decharme, H. Douville, and A. Ribes, 2011: Trends in global and basin-scale runoff over the late twentieth century: methodological issues and sources of uncertainty. Journal of Climate, 24(12), 3000-3014. Anderegg, W.R.L., J.M. Kane, and L.D.L. Anderegg, 2013: Consequences of widespread tree mortality triggered by drought and temperature stress. Nature Climate Change, 3, 30-36. Andreu-Hayles, L., O. Planells, E. Gutierrez, E. Muntan, G. Helle, K.J. Anchukaitis, and G.H. Schleser, 2011: Long tree-ring chronologies reveal 20th century increases in water-use efficiency but no enhancement of tree growth at five Iberian pine forests. Global Change Biology, 17(6), 2095-2112. Betts, R.A., O. Boucher, M. Collins, P.M. Cox, P.D. Falloon, N. Gedney, D.L. Hemming, C. Huntingford, C.D. Jones, D.M.H. Sexton, and M.J. Webb, 2007: Projected increase in continental runoff due to plant responses to increasing carbon dioxide. Nature, 448(7157), 1037-1041. Boucher, O., A. Jones, and R.A. Betts, 2009: Climate response to the physiological impact of carbon dioxide on plants in the Met Office Unified Model HadCM3. Climate Dynamics, 32(2-3), 237-249. Brolsma, R.J., M.T.H. van Vliet, and M.F.P. Bierkens, 2010: Climate change impact on a groundwater-influenced hillslope ecosystem. Water Resources Research, 46, W11503. Cao, L., G. Bala, K. Caldeira, R. Nemani, and G. Ban-Weiss, 2009: Climate response to physiological forcing of carbon dioxide simulated by the coupled Community Atmosphere Model (CAM3.1) and Community Land Model (CLM3.0). Geophysical Research Letters, 36, L10402. Crosbie, R.S., J.L. McCallum, G.R. Walker, and F.H.S. Chiew, 2010: Modelling climate-change impacts on groundwater recharge in the Murray-Darling Basin, Australia. Hydrogeology Journal, 18(7), 1639-1656. Dai, A., T. Qian, K.E. Trenberth, and J.D. Milliman, 2009: Changes in continental freshwater discharge from 1948 to 2004. Journal of Climate, 22(10), 2773-2792. Subject to Final Copyedit 34 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Davie, J.C.S., P.D. Falloon, R. Kahana, R.Dankers, R. Betts, F.T. Portmann, D.B. Clark, A.Itoh, Y. Masaki, K. Nishina, B.Fekete, Z. Tessler, X. Liu, Q. Tang, S. Hagemann, T.Stacke, R.Pavlick, S. Schaphoff, S.N. Gosling, W.Franssen, and N. Arnell: Comparing projections of future changes in runoff and water resources from hydrological and ecosystem models in ISI-MIP, Earth System Dynamics, in press. de Boer, H.J., E.I. Lammertsma, F. Wagner-Cremer, D.L. Dilcher, M.J. Wassen, and S.C. Dekker, 2011: Climate forcing due to optimization of maximal leaf conductance in subtropical vegetation under rising CO2. Proceedings of the National Academy of Sciences of the United States of America, 108(10), 4041-4046. Donohue, R.J., M.L. Roderick, T.R. McVicar, and G.D. Farquhar, 2013: Impact of CO2 fertilization on maximum foliage cover across the globe’s warm, arid environments. Geophysical Research Letters, 40(12), 3031-3035. Fader, M., S. Rost, C. Müller, A. Bondeau, and D. Gerten, 2010: Virtual water content of temperate cereals and maize: present and potential future patterns. Journal of Hydrology, 384(3-4), 218-231. Gagen, M., W. Finsinger, F. Wagner-Cremer, D. McCarroll, N.J. Loader, I. Robertson, R. Jalkanen, G. Young, and A. Kirchhefer, 2011: Evidence of changing intrinsic water-use efficiency under rising atmospheric CO2 concentrations in Boreal Fennoscandia from subfossil leaves and tree ring delta 13C ratios. Global Change Biology, 17(2), 1064-1072. Gedney, N., P.M. Cox, R.A. Betts, O. Boucher, C. Huntingford, and P.A. Stott, 2006: Detection of a direct carbon dioxide effect in continental river runoff records. Nature, 439(7078), 835-838. Gerten, D., S. Rost, W. von Bloh, and W. Lucht, 2008: Causes of change in 20th century global river discharge. Geophysical Research Letters, 35(20), L20405. Gerten, D., J. Heinke, H. Hoff, H. Biemans, M. Fader, and K. Waha, 2011: Global water availability and requirements for future food production. Journal of Hydrometeorology 12(5), 885-899. Gerten, D., W. Lucht, S. Ostberg, J. Heinke, M. Kowarsch, H. Kreft, Z.W. Kundzewicz, J. Rastgooy, R. Warren, and H.J. Schellnhuber: Asynchronous exposure to global warming: freshwater resources and terrestrial ecosystems. Environmental Research Letters, in press. Green, T.R., B.C. Bates, S.P. Charles, and P.M. Fleming, 2007: Physically based simulation of potential effects of carbon dioxide - altered climates on groundwater recharge. Vadose Zone Journal, 6(3), 597-609. Haddeland, I., D.B. Clark, W. Franssen, F. Ludwig, F. Voss, N.W. Arnell, N. Bertrand, M. Best, S. Folwell, D. Gerten, S. Gomes, S.N. Gosling, S. Hagemann, N. Hanasaki, R. Harding, J. Heinke, P. Kabat, S. Koirala, T. Oki, J. Polcher, T. Stacke, P. Viterbo, G.P. Weedon, and P. Yeh, 2011: Multimodel estimate of the global terrestrial water balance: setup and first results. Journal of Hydrometeorology, 12(5), 869-884. Heyder, U., S. Schaphoff, D. Gerten, and W. Lucht, 2011: Risk of severe climate change impact on the terrestrial biosphere. Environmental Research Letters, 6(3), 034036. Ito, A., and M. Inatomi, 2012: Water-use efficiency of the terrestrial biosphere: a model analysis focusing on interactions between the global carbon and water cycles. Journal of Hydrometeorology, 13(2), 681-694. Joshi, M.M., J.M. Gregory, M.J. Webb, D.M.H. Sexton, and T.C. Johns, 2008: Mechanisms for the land/sea warming contrast exhibited by simulations of climate change. Climate Dynamics, 30(5), 455-465. Keenan, T.F., D.Y. Hollinger, G. Bohrer, D. Dragoni, J.W. Munger, H.P. Schmid, and A.D. Richardson, 2013: Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise. Nature, 499(7458), 324-327. Koehler, I.H., P.R. Poulton, K. Auerswald, and H. Schnyder, 2010: Intrinsic water-use efficiency of temperate seminatural grassland has increased since 1857: an analysis of carbon isotope discrimination of herbage from the Park Grass Experiment. Global Change Biology, 16(5), 1531-1541. Konzmann, M., D. Gerten, and J. Heinke, 2013: Climate impacts on global irrigation requirements under 19 GCMs, simulated with a vegetation and hydrology model. Hydrological Sciences Journal, 58(1), 88-105. Labat, D., Y. Godderis, J. Probst, and J. Guyot, 2004: Evidence for global runoff increase related to climate warming. Advances in Water Resources, 27(6), 631-642. Leakey, A.D.B., E.A. Ainsworth, C.J. Bernacchi, A. Rogers, S.P. Long, and D.R. Ort, 2009: Elevated CO2 effects on plant carbon, nitrogen, and water relations: six important lessons from FACE. Journal of Experimental Botany, 60(10), 2859-2876. Lewis, S.L., J. Lloyd, S. Sitch, E.T.A. Mitchard, and W.F. Laurance, 2009: Changing ecology of tropical forests: evidence and drivers. Annual Review of Ecology Evolution and Systematics, 40, 529-549. Loader, N.J., R.P.D. Walsh, I. Robertson, K. Bidin, R.C. Ong, G. Reynolds, D. McCarroll, M. Gagen, and G.H.F. Young, 2011: Recent trends in the intrinsic water-use efficiency of ringless rainforest trees in Borneo. Philosophical Transactions of the Royal Society B-Biological Sciences, 366(1582), 3330-3339. Lorenz, C. and H. Kunstmann, 2012: The hydrological cycle in three state-of-the-art reanalyses: intercomparison and performance analysis. Journal of Hydrometeorology, 13(5), 1397-1420. McCallum, J.L., R.S. Crosbie, G.R. Walker, and W.R. Dawes, 2010: Impacts of climate change on groundwater in Australia: a sensitivity analysis of recharge. Hydrogeology Journal, 18(7), 1625-1638. McMahon, S.M., G.G. Parker, and D.R. Miller, 2010: Evidence for a recent increase in forest growth. Proceedings of the National Academy of Sciences of the United States of America, 107(8), 3611-3615. Subject to Final Copyedit 35 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Murray, S.J., P.N. Foster, and I.C. Prentice, 2012: Future global water resources with respect to climate change and water withdrawals as estimated by a dynamic global vegetation model. Journal of Hydrology, 448-449, 14-29. Nock, C.A., P.J. Baker, W. Wanek, A. Leis, M. Grabner, S. Bunyavejchewin, and P. Hietz, 2011: Long-term increases in intrinsic water-use efficiency do not lead to increased stem growth in a tropical monsoon forest in western Thailand. Global Change Biology, 17(2), 1049- 1063. Nugent, K.A. and H.D. Matthews, 2012: Drivers of future northern latitude runoff change. Atmosphere-Ocean, 50(2), 197-206. Oliveira, P.J.C., E.L. Davin, S. Levis, and S.I. Seneviratne, 2011: Vegetation-mediated impacts of trends in global radiation on land hydrology: a global sensitivity study. Global Change Biology, 17(11), 3453-3467. Peñuelas, J., J.G. Canadell, and R. Ogaya, 2011: Increased water-use efficiency during the 20th century did not translate into enhanced tree growth. Global Ecology and Biogeography, 20(4), 597-608. Piao, S., P. Friedlingstein, P. Ciais, N. de Noblet-Ducoudre, D. Labat, and S. Zaehle, 2007: Changes in climate and land use have a larger direct impact than rising CO2 on global river runoff trends. Proceedings of the National Academy of Sciences of the United States of America, 104(39), 15242-15247. Port, U., V. Brovkin, and M. Claussen, 2012: The influence of vegetation dynamics on anthropogenic climate change. Earth System Dynamics, 3, 233-243. Reddy, A.R., G.K. Rasineni, and A.S. Raghavendra, 2010: The impact of global elevated CO2 concentration on photosynthesis and plant productivity. Current Science, 99(1), 46-57. Rosenthal, D.M., and N.J. Tomeo, 2013: Climate, crops and lacking data underlie regional disparities in the CO2 fertilization effect. Environmental Research Letters, 8(3), 031001. Saatchi, S., S. Asefi-Najafabady, Y. Malhi, L.E.O.C. Aragão, L.O. Anderson, R.B. Myneni, and R. Nemani, 2013: Persistent effects of a severe drought on Amazonian forest canopy. Proceedings of the National Academy of Sciences of the United States of America, 110(2), 565-570. Sterling, S.M., A. Ducharne, and J. Polcher, 2013: The impact of global land-cover change on the terrestrial water cycle. Nature Climate Change, 3, 385-390. Wiltshire, A., J. Gornall, B. Booth, E. Dennis, P. Falloon, G. Kay, D. McNeall, C. McSweeney, and R. Betts, : The importance of population, climate change and CO2 plant physiological forcing in determining future global water stress. Global Environmental Change, in press. Box CC-WE: The Water-Energy-Food/Feed/Fiber Nexus as Linked to Climate Change [Douglas J. Arent (USA), Petra Döll (Germany), Kenneth M. Strzepek (UNU / USA), Blanca Elena Jimenez Cisneros (Mexico), Andy Reisinger (New Zealand), FerencToth (IAEA / Hungary), Taikan Oki (Japan)] Water, energy, and food/feed/fiber are linked through numerous interactive pathways and subject to a changing climate, as depicted in Figure WE-1. The depth and intensity of those linkages vary enormously between countries, regions and production systems. Energy technologies (e.g. biofuels, hydropower, thermal power plants), transportation fuels and modes, and food products (from irrigated crops, in particular animal protein produced by feeding irrigated crops and forages) may require significant amounts of water (Sections 3.7.2, 7.3.2, 10.2, 10.3.4, 22.3.3, 25.7.2; Allan, 2003; King and Weber 2008; McMahon and Price, 2011; Macknick et al., 2012a). In irrigated agriculture, climate, irrigating procedure, crop choice and yields determine water requirements per unit of produced crop. In areas where water (and wastewater) must be pumped and/or treated, energy must be provided (Asano et al., 2006; Khan and Hanjra, 2009; USEPA, 2010; Gerten et al., 2011). While food production, refrigeration, transport and processing require large amounts of energy (Pelletier et al., 2011), a major link between food and energy as related to climate change is the competition of bioenergy and food production for land and water (Section 7.3.2, Box 25-10; Diffenbaugh et al., 2012; Skaggs et al., 2012) (robust evidence, high agreement). Food and crop wastes, and wastewater, may be used as sources of energy, saving not only the consumption of conventional non-renewable fuels used in their traditional processes, but also the consumption of the water and energy employed for processing or treatment and disposal (Schievano et al., 2009; Sung et al., 2010; Olson, 2012). Examples of this can be found in several countries across all income ranges. For example, sugar cane by-products are increasingly used to produce electricity or for cogeneration (McKendry, 2002; Kim and Dale 2004) for economic benefits, and increasingly as an option for greenhouse gas mitigation. [INSERT FIGURE WE-1 HERE Figure WE-1: The water-energy-food nexus as related to climate change. The interlinkages of supply/demand, quality and quantity of water, energy and food/feed/fiber with changing climatic conditions have implications for both adaptation and mitigation strategies.] Subject to Final Copyedit 36 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Most energy production methods require significant amounts of water, either directly (e.g., crop-based energy sources and hydropower) or indirectly (e.g., cooling for thermal energy sources or other operations) (Sections 10.2.2 10.3.4, 25.7.4; van Vliet et al., 2012; Davies et al., 2013) (robust evidence, high agreement). Water for biofuels, for example, under the IEA Alternative Policy Scenario, which has biofuels production increasing to 71 EJ in 2030, has been reported by Gerbens-Leenes et al. (2012) to drive global consumptive irrigation water use from 0.5% of global renewable water resources in 2005 to 5.5% in 2030, resulting in increased pressure on freshwater resources, with potential negative impacts on freshwater ecosystems. Water is also required for mining (Section 25.7.3), processing, and residue disposal of fossil and nuclear fuels or their byproducts. Water for energy currently ranges from a few percent in most developing countries to more than 50% of freshwater withdrawals in some developed countries, depending on the country (Kenny et al., 2009; WEC, 2010). Future water requirements will depend on electricity demand growth, the portfolio of generation technologies and water management options employed (WEC, 2010; Sattler et al., 2012) (medium evidence, high agreement). Future water availability for energy production will change due to climate change (Sections 3.4, 3.5.1, 3.5.2.2) (robust evidence, high agreement). Water may require significant amounts of energy for lifting, transport and distribution and for its treatment either to use it or to depollute it. Wastewater and even excess rainfall in cities requires energy to be treated or disposed. Some non-conventional water sources (wastewater or seawater) are often highly energy intensive. Energy intensities per m3 of water vary by about a factor of 10 between different sources, e.g. locally produced potable water from ground/surface water sources vs. desalinated seawater (Box 25-2, Tables 25-6 and 25-7; Macknick et al., 2012b; Plappally and Lienhard, 2012). Groundwater (35% of total global water withdrawals, with irrigated food production being the largest user; Döll et al., 2012) is generally more energy intensive than surface water. In India, for example, 19% of total electricity use in 2012 was for agricultural purposes (Central Statistics Office, 2013), with a large share for groundwater pumping. Pumping from greater depth increases energy demand significantly– electricity use (kWhr/m3 of water) increases by a factor of 3 when going from 35 to 120 m depth (Plappally and Lienhard, 2012). The reuse of appropriate wastewater for irrigation (reclaiming both water and energy-intense nutrients) may increase agricultural yields, save energy, and prevent soil erosion (Smit and Nasr, 1992; Jimenez, 1996; Wichelns et al., 2007; Raschid-Sally and Jayakody, 2008) (medium confidence). More energy efficient treatment methods enable poor quality (“black”) wastewater to be treated to quality levels suitable for discharge into water courses, avoiding additional fresh water and associated energy demands (Keraita et al, 2008). If properly treated to retain nutrients, such treated water may increase soil productivity, contributing to increased crop yields/food security in regions unable to afford high power bills or expensive fertilizer (Oron, 1996; Lazarova and Bahri, 2005; Redwood and Huibers, 2008; Jimenez, 2009) (high confidence). Linkages among water, energy, food/feed/fiber and climate are also strongly related to land use and management (Section 4.4.4, Box 25-10) (robust evidence, high agreement). Land degradation often reduces efficiency of water and energy use (e.g. resulting in higher fertilizer demand and surface runoff), and compromises food security (Sections 3.7.2, 4.4.4). On the other hand, afforestation activities to sequester carbon have important co-benefits of reducing soil erosion and providing additional (even if only temporary) habitat (see Box 25-10) but may reduce renewable water resources. Water abstraction for energy, food or biofuel production or carbon sequestration can also compete with minimal environmental flows needed to maintain riverine habitats and wetlands, implying a potential conflict between economic and other valuations and uses of water (Sections 25.4.3 and 25.6.2, Box 25-10) (medium evidence, high agreement). Only a few reports have begun to evaluate the multiple interactions among energy, food, land, and water and climate (McCornick et al., 2008; Bazilian et al., 2011; Bierbaum and Matson, 2013), addressing the issues from a security standpoint and describing early integrated modeling approaches. The interaction among each of these factors is influenced by the changing climate, which in turn impacts energy and water demand, bioproductivity and other factors (see Figure WE-1 and Wise et al., 2009), and has implications for security of supplies of energy, food and water, adaptation and mitigation pathways, air pollution reduction as well as the implications for health and economic impacts as described throughout this report. The interconnectivity of food/fiber, water, land use, energy and climate change, including the perhaps not yet well understood cross-sector impacts, are increasingly important in assessing the implications for adaptation/mitigation policy decisions. Fuel-food-land use-water-GHG mitigation strategy interactions, particularly related to bioresources for food/feed, power, or fuel, suggest that combined assessment of water, land type and use requirements, energy Subject to Final Copyedit 37 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 requirements and potential uses and GHG impacts often epitomize the interlinkages. For example, mitigation scenarios described in the IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation (IPCC, 2011) indicate up to 300EJ of biomass primary energy by 2050 under increasingly stringent mitigation scenarios. Such high levels of biomass production, in the absence of technology and process/management/operations change, would have significant implications for land use, water and energy, as well as food production and pricing. 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Lovell, D. Nolasco, O. Thorne, R. de Sutter, B. Fülöp, P. Staufer, and Å. Johannessen, 2010: Climate Change and the Water Industry - Practical Responses and Actions. Perspectives on water and climate change adaptation, International Water Association, Den Haag, The Netherlands, 16 pp. Subject to Final Copyedit 60 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 drivers, not all of which are necessarily anthropogenic; in the diagram, symbols with borders represent end-to-end attribution of the impact on resources to anthropogenic climate change. 1: Gerten et al. (2008), Piao et al. (2007), Alkama et al. (2011); 2: Piao et al. (2010); 3: Shiklomanov et al. (2007); 4: Hidalgo et al. (2009); 5: Collins (2008); 6: Baraer et al. (2012); 7: Rosenzweig et al. (2007); 8: Min et al. (2011); 9: Pall et al. (2011); 10: Aguilera and Murillo (2009); 11: Jeelani (2008); 12: Evans et al. (2005); 13: Marcé et al. (2010); 14: Pednekar et al. (2005); 15: Paerl et al. (2006); 16: Tibby and Tiller (2007). Observed change Attributed to Ref Changed runoff (global, 1960-1994) Mainly climatic change, and to a lesser degree CO2 1 increase and land-use change Reduced runoff (Yellow River, China) Increased temperature; only 35% of reduction 2 attributable to human withdrawals Earlier annual peak discharge (Russian Arctic, Increased temperature and earlier spring thaw 3 1960-2001) Earlier annual peak discharge (Columbia River, Anthropogenic warming 4 western USA, 1950-1999) Glacier meltwater yield greater in 1910-1940 Glacier shrinkage forced by comparable warming 5 than in 1980-2000 (European Alps) rates in the two periods Decreased dry-season discharge (Peru, 1950s- Decreased glacier extent in the absence of a clear 6 1990s) trend in precipitation Disappearance of Chacaltaya Glacier, Bolivia Ascent of freezing isotherm at 50 meters per 7 (2009) decade, 1980s to 2000s More intense extremes of precipitation (northern Anthropogenic greenhouse-gas emissions 8 tropics and mid-latitudes, 1951-1999) Fraction of risk of flooding (England and Wales, Extreme precipitation attributable to anthropogenic 9 autumn 2000) greenhouse radiation Decreased recharge of karst aquifers (Spain, 20th Decreased precipitation, and possibly increased 10 century) temperature; multiple confounding factors Decreased groundwater recharge (Kashmir, Decreased winter precipitation 11 1985-2005) Increased dissolved organic carbon in upland Increased temperature and precipitation; multiple 12 lakes (UK, 1988-2004) confounding factors Increased anoxia in a reservoir, moderated during Decreased runoff due to decreased precipitation and 13 ENSO (El Niño-Southern Oscillation) episodes increased evaporative demand (Spain, 1954-2007) Variable faecal pollution in a saltwater wetland Variable storm runoff; 70% of coliform variability 14 (California, 1969-2000) attributable to variable precipitation Nutrient flushing from swamps, reservoirs (North Hurricanes 15 Carolina, 1970s-2002) Increased lake nutrient content (Victoria, Increased air and water temperature 16 Australia, 1984-2000) Subject to Final Copyedit 61 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Table 3-2: Effects of different GHG emissions scenarios on hydrological changes and freshwater-related impacts of climate change on humans and ecosystems. Among the SRES scenarios, GHG emissions are highest in A1f and A2, lower in A1 and B2, and lowest in B1. 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, quantified as the CMIP5 model mean) over different reference periods, typically since pre-industrial. GW is projected to be, for RCP8.5, approximately 2°C in the 2040s and 4°C in the 2080s. For RCP6.0, GW is 2°C in the 2060s and 2.5°C in the 2080s, while in RCP2.6, GW stays below 1.8°C throughout the 21st century (Figure 1-4 in Chapter 1). Population scenario SSP2 assumes a medium population increase. Type of hydrological Description of indicator Hydrological change or impact Reference change or impact in different emissions scenarios or for different degrees of global warming (GW) Decrease of renewable Percent of global population affected Up to 2°C above the 1990s (GW Schewe et water resources, by a water resource decrease of more 2.7°C) each degree of GW al. (2013) global scale than 20% as compared to the 1990s affects an additional 7% (mean of 5 GCMs and 11 global hydrological models, population scenario SSP2) Decrease of renewable Percent of global population affected RCP2.6: 24% (11-39%) Portmann groundwater resources, by a groundwater resource decrease RCP4.5: 26% (23-32%) et al. global scale of more than 10% by the 2080s as RCP6.0: 32% (18-45%) (2013) compared to the 1980s (mean and RCP8.5: 38% (27-50%) range of 5 GCMs, population scenario SSP2) Exposure to floods, Percent of global population annually RCP2.6: 0.4% (0.2-0.5%) Hirabayas global scale exposed, in the 2080s, to a flood RCP4.5: 0.6% (0.4-1.0%) hi et al. corresponding to the 100-year flood RCP6.0: 0.7% (0.3-1.1%) (2013) discharge for the 1980s (mean and RCP8.5: 1.2% (0.6-1.7%) range of 5-11 GCMs, population GW 2°C: 0.5% (0.3-0.6%) constant at 2005 values) GW 4°C: 1.2% (0.8-2.2%) 1980s: 0.1% (0.04-0.16%) Change in irrigation Change of required irrigation water RCP2.6: -0.2-1.6% Hanasaki water demand, withdrawals by the 2080s (on area RCP4.5: 1.9-2.8% et al. global scale irrigated around 2000) as compared RCP8.5: 6.7-10.0% (2013) to the 1980s (range of 3 GCMs) River flow regime shifts Percent of global land area (except SRES B2: 5.4-6.7% Döll and from perennial to Greenland and Antarctica) affected SRES A2: 6.3-7.0% Müller intermittent and vice by regime shifts between the 1970s Schmied versa, global scale and the 2050s (range of 2 GCMs) (2012) Water scarcity Percent of global population living in No significant differences Gerten et countries with less than 1300 m3/year between SRES B1 and A2 al. (2011) of per-capita in the 2080s (mean of 17 GCMs, population constant at 2000 values) New or aggravated water Percent of global population living in GW 2°C: 8% Gerten et scarcity river basins with new or aggravated GW 3.5°C: 11% al. (2013) water scarcity around 2100 as GW 5°C: 13% compared to 2000 (less than 1000 m3/year of per-capita blue water resources) (median of 19 GCMs, population constant at 2000 values) Exposure to water Population in water-stressed For emissions scenarios with Arnell et scarcity watersheds (less than 1000 m3/year of 2oC target, compared to SRES al. (2013) Subject to Final Copyedit 62 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 per-capita blue water resources) A1: exposed to an increase in stress (1 5-8% impact reduction in 2050 GCM) 10-20% reduction in 2100 Change of groundwater Probability that groundwater recharge GW 1.4°C: close to 0 almost Crosbie et recharge in the whole of decreases to less than 50% of the everywhere al. (2013a) Australia 1990s value by 2050 (16 GCMs) GW 2.8°C: in western Australia 0.2-0.6, in central Australia 0.2- 0.3, elsewhere close to 1 Change in groundwater Percent change between baseline and SRES B1: -22% Holman et recharge in East Anglia, future groundwater recharge, in %, SRES A1f: -26% al. (2009) UK by the 2050s (1 GCM) Change of river Changes between the 1970s and the Differences between SRES B2 van discharge, groundwater 2080s (1 regional climate model) and A2 are very small compared Roosmale recharge and hydraulic to the changes between the n et al. head in groundwater in 1970s and the 2080s in each (2007) two regions of Denmark scenario River flow regime shift Shift from bimodal to unimodal (1 Occurs in scenarios with GW of Kingston for river in Uganda GCM) at least 4.3°C but not for smaller and Taylor GW (2010) Agricultural (soil Mean duration, affected area and Smaller increases over time for Vidal et al. moisture) droughts in magnitude of short and long drought SRES B1 than for A2 and A1B (2012) France events throughout the 21st century (1 GCM) Salinization of artificial (1) Daily probability of exceedance Reference period 1997-2007 Bonte and coastal freshwater lake of maximum allowable (GW 0.8°C): (1) 2.5%, (2) 103 Zwolsman IJsselmeer in the concentration (MAC) of chloride days (2010) Netherlands (a drinking (150 mg/liter), GW 1.8°C, no change in water source) due to (2) Maximum duration of MAC atmospheric circulation: (1) seawater intrusion exceedance (2050, 1 GCM) 3.1%, (2) 124 days GW 2.8°C and change in atmospheric circulation: (1) 14.3%, (2) 178 days Decrease of hydropower Reduction of mean annual SRES B1: 8% Beyene et production at Lake hydropower production by the 2080s SRES A2: 7% al. (2010) Nasser, Egypt compared to hydropower production 1950-99 (11 GCMs) Reduction of usable Number of days per year with a Without climate change: 16 van Vliet capacity of thermal capacity reduction of more than 50% SRES B1: 22 et al. power plants in Europe (for existing power plants) (2031- SRES A2: 24 (2012) and USA due to low 2060, 3 GCMs) river flow and excessive water temperature Flood damages in (1) Expected annual damages, in SRES B2: (1) 14-15 billion Feyen et Europe (EU27) 2006- €, €/year, (2) 440,000-470,000 al. (2012) (2) Expected annual population people exposed (2080s, 2 GCMs) SRES A2: (1) 18-21 billion €/year, (2) 510,000-590,000 people Reference period: (1) 6.4 billion €/year, (2) 200,000 people Subject to Final Copyedit 63 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Table 3-3: Categories of climate change adaptation options for the management of freshwater resources. OPTION A+M Institutional Support integrated water resources management, including the integrated management of land considering X specifically negative and positive impacts of climate change Promote synergy of water and energy savings and efficient use X Identify “low-regret policies” and build a portfolio of relevant solutions for adaptation X Increase resilience by forming water utility network working teams Build adaptive capacity Improve and share information X Adapt the legal framework to make it instrumental for addressing climate change impacts X Develop financial tools (credit, subsidies and public investment) for the sustainable management of water, and for considering poverty eradication and equity Design and operation Design and apply decision-making tools that consider uncertainty and fulfill multiple objectives Revise design criteria of water infrastructure to optimize flexibility, redundancy and robustness Ensure plans and services are robust, adaptable or modular, give good value, are maintainable, and have X long-term benefits, especially in low-income countries Operate water infrastructure so as to increase resilience to climate change for all users and sectors When and where water resources increase, alter dam operations to allow freshwater ecosystems to benefit Take advantage of hard and soft adaptation measures X Carry out programs to protect water resources in quantity and quality Increase resilience to climate change by diversifying water sources(1) 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 influent 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 floods Design cities and rural settlements to be resilient to floods 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 efficient use of water by all users Improve irrigation efficiency and reduce demand for irrigation water X Promote switching to more appropriate crops (drought-resistant, salt-resistant; low water demand) X Plant flood- or drought-resistant crop varieties Agricultural irrigation 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 efficiency certifications X A+M: may assist both adaptation and mitigation (1) This includes water reuse, rain water harvesting, and desalination, among others. Subject to Final Copyedit 64 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 With information from: Arkell (2011a; 2011b); Andrews (2009); Bahri (2009); Bowes et al. (2012); de Graaf and der Brugge (2010); Dembo (2010); Dillon and Jiménez (2008); Elliott et al. (2011); Emelko et al. (2011); Godfrey et al. (2010); Howard et al. (2010); Jiménez and Asano (2008); Jiménez (2011); Keller (2008); Kingsford (2011); Mackay and Last (2010); Major et al. (2011); Marsalek et al. (2006); McCafferty (2008); McGuckin (2008); Mogaka et al. (2006); Mukhopadhyay and Dutta (2010); Munasinghe (2009); NACWA (2009); OECD (2010); OFWAT (2009); Reiter (2009); Renofalt et al. (2010); Seah (2008); Sprenger et al. (2011); Thöle (2008); UNESCO (2011); UNHABITAT (2008); Vörösmarty et al. (2000); Wang X. et al. (2011); Whitehead et al. (2009b); Zwolsman et al. (2010) 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. Subject to Final Copyedit 65 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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). Subject to Final Copyedit 66 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure 3-2: Observations of the impacts of climate on water quality. Subject to Final Copyedit 67 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 multi-annual measurements). Region-wide measurement (Kääb et al., 2012) was by satellite laser altimetry. Global average (WGI Chapter 4) is shown as a 1- sigma confidence region. [Illustration to be redrawn to conform to IPCC publication specifications.] Subject to Final Copyedit 68 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 4 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). [Illustration to be redrawn to conform to IPCC publication specifications.] Subject to Final Copyedit 69 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure 3-5: Change in mean monthly runoff across seven climate models in seven catchments, with a 2oC increase in global mean temperature above 1961-1990 (Arnell, 2011; Hughes et al., 2011; Kingston and Taylor, 2010; 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 2oC increase (dotted line) and a 4oC increase (solid line). [Illustration to be redrawn to conform to IPCC publication specifications.] Subject to Final Copyedit 70 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 a) b) 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 CMIP5 GCMs under 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. 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 (whiskers), mean (horizontal thick lines within each bar), ±1 standard deviation (box) and projections of each GCM (colored symbols) averaged over the 21st century. The Subject to Final Copyedit 71 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 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 4-14 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 0.4-1.2% 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 7-25, depending on the RCP, with strong increases in Asia and Africa due to high population growth. [Illustration to be redrawn to conform to IPCC publication specifications.] Figure 3-7: Human vulnerability to climate-change induced decreases of renewable groundwater resources by the 2050s. Lower (B2) and higher (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 the vulnerability. The index is only defined for areas where groundwater recharge is projected to decrease by at least 10% relative to 1961-1990 (Döll, 2009). Subject to Final Copyedit 72 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure RF-1: Impact of climate change relative to the impact of water withdrawals and dams on natural flows for two ecologically relevant river flow characteristics (mean annual river flow and monthly low flow Q90), computed by a global water model (Döll and Zhang, 2010). Monthly Q90 was defined as the flow that is exceeded in 9 out 10 months. Impact of climate change is the percent change of flow between 1961-1990 and 2041-2070 according to the emissions scenario A2 as implemented by the global climate model HadCM3. Impact of water withdrawals and reservoirs is computed by running the model with and without water withdrawals and dams that existed in 2002. Please note that the figure does not reflect spatial differences in the magnitude of change. [Illustration to be redrawn to conform to IPCC publication specifications.] Subject to Final Copyedit 73 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure RF-2: Accumulated loss of regional species richness (gamma diversity) of macroinvertebrates as a function of glacial cover in catchment. Obligate glacial river macroinvertebrates begin to disappear from assemblages when glacial cover in the catchment drops below approximately 50%, and 9-14 species are predicted to be lost with the complete disappearance of glaciers in each region, corresponding to 11, 16 and 38% of the total species richness in the three study regions in Ecuador, Europe and Alaska. Data are derived from multiple river sites from the Ecuadorian Andes and Swiss and Italian Alps, and a temporal study of a river in the Coastal Range Mountains of southeast Alaska over nearly three decades of glacial shrinkage. Each data point represents a river site or date (Alaska), and lines are Lowess fits. Adapted by permission from Macmillan Publishers Ltd: Nature Climate Change, Jacobsen et al., 2012, © 2012. [Illustration to be redrawn to conform to IPCC publication specifications.] Subject to Final Copyedit 74 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure VW-1: Percentage change in net irrigation requirements of 11 major crops from 1971–2000 to 2070–2099 on areas currently equipped for irrigation, assuming current management practices. Top: impact of climate change including physiological and structural crop responses to increased atmospheric CO2 concentration (maximum effect in the absence of co-limitation by nutrients). Bottom: impact of climate change only. Shown is the median change derived from climate change projections by 19 GCMs (based on the SRES A2 emissions scenario) used to force a vegetation and hydrology model. Modified after Konzmann et al. (2013). [Illustration to be redrawn to conform to IPCC publication specifications.] Subject to Final Copyedit 75 28 October 2013 FINAL DRAFT IPCC WGII AR5 Chapter 3 Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014 Figure WE-1: The water-energy-food nexus as related to climate change. The interlinkages of supply/demand, quality and quantity of water, energy and food/feed/fiber with changing climatic conditions have implications for both adaptation and mitigation strategies. Subject to Final Copyedit 76 28 October 2013