## FINAL REPORT

1 October 2004



# European Outlook on Water Use

Martina Flörke and Joseph Alcamo
Center for Environmental Systems Research University of KasselEuropean Outlook on Water Use Final Report



## ACKNOWLEDGEMENTS

This project was supported by EEA Contract 3241/B2003.EEA.51592, Stéphane Isoard was the responsible Project Manager at the EEA. Data were provided by the RIVM (climate scenarios), Stéphane Isoard (data on water quantity), EUROSTAT (data on water quantity), and all national Statistical Offices who gave their contribu tion by sending national data on water uses. The authors wish to thank their colleagues at th e Center for Environmental Systems Research, University of Kassel, for assistance of the WaterGAP calculations and preparation of results; in particular, Ellen Teichert and Kerstin Schulze. We are al so thankful to Barbara Lübkert for her editorial assistance.European Outlook on Water Use Final Report



## CONTENTS

1. INTRODUCTION................................................................................................................... ...1
1.1 O BJECTIVES ...........................................................................................................................1 1.2 S COPE

............................................................................................................................... .....1
2. DRIVING FORCES AND OTHER FA CTORS OF WATER USE ......................................4
2.1 D OMESTIC S ECTOR ................................................................................................................4 2.2 E LECTRICITY P RODUCTION S ECTOR ......................................................................................5 2.3 M ANUFACTURING S ECTOR ....................................................................................................5 2.4 A GRICULTURE S ECTOR ..........................................................................................................6 2.5 D RIVING F ORCES I NCLUDED IN THIS S TUDY ..........................................................................7
3. METHODOLOGY.................................................................................................................... .9
3.1 T HE S CENARIO A PPROACH ....................................................................................................9 3.2 M ODELING A PPROACH ..........................................................................................................9 3.2.1 Introduction..................................................................................................................9 3.2.2 WaterGAP: Water Availability...................................................................................10 3.2.3 WaterGAP: Domestic Water Use...............................................................................11 3.2.4 WaterGAP: Water Use for Electricity Production.....................................................16 3.2.5 WaterGAP: Water Use in the Manufacturing Industry..............................................18 3.2.6 WaterGAP: Irrigation Water Use ..............................................................................19 3.2.7 WaterGAP: Livestock Water Use...............................................................................21 3.3 I MPROVED E STIMATES A CHIEVED IN THIS S TUDY ...............................................................22
4. ASSUMPTIONS OF THE BASELINE SCENARIO (LREM-E) .........................................23
4.1 T HE W ORLD OF THE B ASELINE S CENARIO – A Q UALITATIVE D ESCRIPTION .......................23 4.2 D RIVING F ORCE A SSUMPTIONS ...........................................................................................24 4.2.1 Population ..................................................................................................................24 4.2.2 Economic growth (GDP/cap

⋅ year).............................................................................25 4.2.3 Structural change in the domestic sector ...................................................................26 4.2.4 Thermal electricity production...................................................................................26 4.2.5 Structural change in the el ectricity production sector...............................................26 4.2.6 Manufacturing output (gross value added)................................................................27 4.2.7 Irrigated area .............................................................................................................28 4.2.8 Livestock density.........................................................................................................30 4.2.9 Technological change – Improvements in water use efficiency.................................31 4.2.10 Climate change...........................................................................................................31
5. ASSUMPTIONS OF THE CLIMATE POLICY SCENARIO ( SEP) .................................34
5.1 T HE W ORLD OF THE C LIMATE P OLICY S CENARIO – A Q UALITATIVE D ESCRIPTION ............34 5.2 D RIVING F ORCE A SSUMPTIONS ...........................................................................................34
6. SCENARIO RESULTS............................................................................................................39
6.1 W ATER U SE .........................................................................................................................39 6.2 W ATER A VAILABILITY AND W ATER S TRESS .......................................................................48 6.2.1 Water Availability.......................................................................................................48 6.2.2 Water Stress................................................................................................................49 6.3 C ONTRIBUTION TO THE W ATER F RAMEWORK D IRECTIVE ...................................................51
7. UNCERTAINTY AND SENSIT IVITY OF RESULTS........................................................53European Outlook on Water Use Final Report

7.1 U NCERTAINTY OF D OMESTIC W ATER U SE T RENDS .............................................................53 7.2 S ENSITIVITY TO L OWER PER C APITA I NCOME ......................................................................54 7.3 S ENSITIVITY TO U NCERTAIN F UTURE I RRIGATED A REA ......................................................56
8. RECOMMENDATIONS FOR IMPROVING WATER OUTLOOKS FOR EUROPE ...58
9. CONCLUSIONS.................................................................................................................... ...60
10. REFERENCES ..................................................................................................................... 62
APPENDIX A: DOMESTIC WATER USE MODEL – CONCEPT OF STRUCTURAL CHANGE ......................................................................................................................... .................67
APPENDIX B: CALCULATION OF TECHNOLOGICAL CHANGES...................................74
H ISTORICAL TECHNOLOGICAL CHANGES OF WATER INTENSITY : E LECTRICITY PRODUCTION SECTOR

............................................................................................................................... .............74 H ISTORICAL TECHNOLOGICAL CHANGES OF WATER INTENSITY : M ANUFACTURING SECTOR ...........75
APPENDIX C: GROSS VALUE ADDED FOR THE BASELINE (LREM-E) AND CLIMATE POLICY (SEP) SCENARIOS.....................................................................................79
APPENDIX D: OVERVIEW OF MODEL OUTPUTS................................................................81
APPENDIX E: DRIVING FORCE ASSUMPTIONS FOR THE LOW ECONOMIC GROWTH VARIANT ................................................................................................................. ....83European Outlook on Water Use Final Report



## FIGURES

Figure 1. ‘Europe-30’ region c overed in this report............................................................................ .2 Figure 2. Percentage share of sectoral-specific water use in the Europe-30 region for the year 2000. Sources: EUROSTAT and national Statistical Offices......................................................4 Figure 3. Household water use and water prices in OECD countries. Source: OECD (1999). ...........5 Figure 4. Extent of irrigated land in Turkey between 1961 and 2001. These data depict the surface area equipped for irrigation but not n ecessarily irrigated ev ery year. Source: FAO (2004). ........................................................................................................................ ..................6 Figure 5. Area equipped for irriga tion versus total arable land by country as used in the WaterGAP model. Source: Dö ll and Siebert (2000). ...................................................................7 Figure 6. Conceptual model of structural change in the dom estic sector...........................................12 Figure 7. Structural change in water intensity in the domestic sector in Germany. Source: DESTATIS. ...................................................................................................................... ..........13 Figure 8. Temporal trend of per capita water use in the domestic sector in the Czech Republic. Source: EUROSTAT............................................................................................................... ...14 Figure 9. Technological improvements leading to hi gher water use efficiency in the domestic use sector. Source: V-ZUG AG (2004)......................................................................................15 Figure 10. Impact of technological ch ange on water use intensity. ...................................................15 Figure 11. Location of European power plants taken into account in this study. Sources: UDI (2000) and NIMA (2000). ........................................................................................................ ..17 Figure 12. Comparison of simulated and published wa ter use in the electricity production sector and model efficiency. 25 European c ountries are taken into account........................................18 Figure 13. Validation of the irri gation model: calculated irrigati on water withdrawals versus published data................................................................................................................. ............21 Figure 14. Atmospheric GHG concentration (CO 2 equivalents) for the baseline (LREM-E, upper line) and the climate policy (SEP, lowe r line) scenarios. Source: EEA (2004)...............32 Figure 15. Differences in long-term average annual temperature (top) and percentage change in long-term average precipitation (bottom) as calculated for the baseline (LREM-E) scenario; 2030 projections compared to today’s level. ..............................................................33 Figure 16. Differences in long-term average annual temperature (top) and percentage change in long-term average precipitation (bottom) as calculated for the climate policy (SEP) scenarios; 2030 projections co mpared to today’s level..............................................................37 Figure 17. Difference between the baseline (LRE M-E) and climate policy (SEP) scenarios. Differences in long-term average annual temp erature (top) and preci pitation (bottom). ..........38 Figure 18. Profile of sector-specific water wi thdrawals in the Northern Europe in 2000. Sources: EUROSTAT and nationa l Statistical Offices. .............................................................39 Figure 19. Computed water with drawals for the baseline (LREM-E) scenario for Northern Europe. ........................................................................................................................ ...............40 Figure 20. Profile of sector-specific water wit hdrawals in Southern Europe in 2000. Sources: EUROSTAT and national Statistical Offices.............................................................................41European Outlook on Water Use Final Report

Figure 21. Computed water with drawals for the baseline (LREM-E) scenario for Southern Europe. ........................................................................................................................ ...............41 Figure 22. Profile of sector-specific water withdr awals in the New EU Member States in 2000. Sources: EUROSTAT and nationa l Statistical Offices. .............................................................42 Figure 23. Computed water with drawals for the baseline (LREM-E) scenario for the New EU Member States.................................................................................................................. ..........42 Figure 24. Profile of sectoral-specific water wi thdrawals in the EU Candidate States in 2000. Sources: EUROSTAT and nationa l Statistical Offices. .............................................................43 Figure 25. Computed water withdrawals for th e baseline (LREM-E) scenario for the EU Candidate Countries. ........................................................................................................... .......44 Figure 26. Computed water withdrawals for irriga tion in the base year 2000 and in 2030 for the baseline (LREM-E) and climat e policy (SEP) scenarios. ..........................................................45 Figure 27. Computed water withdrawals for the el ectricity production in the base year 2000 and in 2030 for the baseline (LREM-E) a nd climate policy (SEP) scenarios...................................46 Figure 28. Comparison of water use scenarios. (See text for explanation of numbers).....................47 Figure 29. Change in average annu al water availability for Eu ropean river basins under the baseline (LREM-E) scenario co mpared to today’s level............................................................48 Figure 30. Comparison of the baseline (LREM- E) and climate policy (SEP) scenarios. Differences in changes in average annual water availability for European river basins............49 Figure 31. Water stress under current conditions and under the baseline s cenario. Top: Current conditions. Bottom: Baseline scenario, 2030. ............................................................................50 Figure 32. Sensitivity analysis of the domestic sector, New EU Member States. .............................54 Figure 33. Sensitivity analysis of the electricity production sector , New EU Member States. .........56 Figure 34. Sensitivity analysis of the manufacturing sector, New EU Member States. ....................56 Figure 35. Sensitivity analysis of the agricu ltural sector, New EU Member States. .........................57 Figure 36. Domestic structural water use intensity (baseline curve) for Austria. Source: EUROSTAT and national Statistical Office. .............................................................................68 Figure 37. Domestic structural water use intens ity (baseline curve) for Belgium. Source: EUROSTAT and national Statistical Office. .............................................................................68 Figure 38. Domestic structural water use inte nsity (baseline curve) for Denmark. Source: EUROSTAT and national Statistical Office. .............................................................................68 Figure 39. Domestic structural water use inte nsity (baseline curve) for Finland. Source: EUROSTAT and national Statistical Office. .............................................................................68 Figure 40. Domestic structural water use intens ity (baseline curve) for Germany. Source: EUROSTAT and national Statistical Office. .............................................................................68 Figure 41. Domestic structural water use inte nsity (baseline curve) for Ireland. Source: EUROSTAT and national Statistical Office. .............................................................................68 Figure 42. Domestic structural water use intensity (baseline curve) for Luxembourg. Source: EUROSTAT and national Statistical Office. .............................................................................69 Figure 43. Domestic structural water use inte nsity (baseline curve) for The Netherlands. Source: EUROSTAT and nati onal Statistical Office. ................................................................69European Outlook on Water Use Final Report

Figure 44. Domestic structural water use inte nsity (baseline curve) for Sweden. Source: EUROSTAT and national Statistical Office. .............................................................................69 Figure 45. Domestic structural water use inte nsity (baseline curve) for United Kingdom. Source: EUROSTAT and nati onal Statistical Office. ................................................................69 Figure 46. Domestic structural water use inte nsity (baseline curve) for Norway. Source: EUROSTAT and national Statistical Office. .............................................................................69 Figure 47. Domestic structural wa ter use intensity (baseline cu rve) for Switzerland. Source: EUROSTAT and national Statistical Office. .............................................................................69 Figure 48. Domestic structural water use inte nsity (baseline curve) for France. Source: EUROSTAT and national Statistical Office. .............................................................................70 Figure 49. Domestic structural water use inte nsity (baseline curve) for Greece. Source: EUROSTAT and national Statistical Office. .............................................................................70 Figure 50. Domestic structural water use inte nsity (baseline curve) for Italy. Source: EUROSTAT and national Statistical Office. .............................................................................70 Figure 51. Domestic structural water use intens ity (baseline curve) for Portugal. Source: EUROSTAT and national Statistical Office. .............................................................................70 Figure 52. Domestic structural water use inte nsity (baseline curve) for Spain. Source: EUROSTAT and national Statistical Office. .............................................................................70 Figure 53. Domestic structural water use inte nsity (baseline curve) for Cyprus. Source: EUROSTAT and national Statistical Office. .............................................................................71 Figure 54. Domestic water use intensity (baseline curve) fo r the Czech Republic. Source: EUROSTAT and national Statistical Office. .............................................................................71 Figure 55. Domestic water use in tensity (baseline curve) for Estonia. Source: EUROSTAT and national Statistical Office. ................................................................................................... .......71 Figure 56. Domestic water use intensity (base line curve) for Hungar y. Source: EUROSTAT and national Statistical Office. ............................................................................................... ....71 Figure 57. Domestic water use in tensity (baseline curve) for Latvia. Source: EUROSTAT and national Statistical Office. ................................................................................................... .......71 Figure 58. Domestic water use in tensity (baseline curve) for Lithuania. Source: EUROSTAT and national Statistical Office. ............................................................................................... ....71 Figure 59. Domestic structural water use inte nsity (baseline curve) for Malta. Source: EUROSTAT and national Statistical Office. .............................................................................72 Figure 60. Domestic water use intensity (base line curve) for Poland. Source: EUROSTAT and national Statistical Office. ................................................................................................... .......72 Figure 61. Domestic water use intensity (base line curve) for the Slovak Republic. Source: EUROSTAT and national Statistical Office. .............................................................................72 Figure 62. Domestic structural water use intens ity (baseline curve) for Slovenia. Source: EUROSTAT and national Statistical Office. .............................................................................72 Figure 63. Domestic structural water use intens ity (baseline curve) for Bulgaria. Source: EUROSTAT and national Statistical Office. .............................................................................73 Figure 64. Domestic structural water use intens ity (baseline curve) for Romania. Source: EUROSTAT and national Statistical Office. .............................................................................73European Outlook on Water Use Final Report

Figure 65. Domestic water use intensity (baselin e curve) for Turkey. Source: EUROSTAT and national Statistical Office. ................................................................................................... .......73 Figure 66. Historical te chnological change of water intensit y of tower cooling systems, (time period 1989-2002). Source: Vattenfall (2002). ..........................................................................75 Figure 67. Historical technological change of water intensity of tower cooling systems, considering two time periods (1989-1997 a nd 1997-2002). Source: Vattenfall (2002). ...........75 Figure 68. Determination of the historical tec hnological change in water intensity of the manufacturing of food products , beverages, and tobacco, c onsidering two time periods (1953-1983 and 1983-1998). Source: DESTATIS.....................................................................76 Figure 69. Determination of the historical tec hnological change of water intensity of the manufacturing of textiles , considering two time pe riods (1957-1979 and 1979-1998). Source: DESTATIS............................................................................................................... .....76 Figure 70. Determination of the historical tec hnological change of water intensity of the manufacturing of pulp, paper, publishing and printing, considering two time periods (1957-1983 and 1983-1998). Source: DESTATIS.....................................................................77 Figure 71. Determination of the historical technological change of water intensity for the manufacturing of, non-metallic, mineral products considering one time period (1979- 2001). Source: DESTATIS. ....................................................................................................... 77 Figure 72. Determination of the historical technological change of water intensity for the manufacturing of chemicals and man-made fibres, considering two time periods (1957- 1979 and 1979-1998). Source: DESTATIS. ..............................................................................78 Figure 73. Determination of historical tech nological change of water intensity for the manufacturing of basic metals and fabrica tion of metal products, considering one time period (1952-1991). Source: DESTATIS...................................................................................78European Outlook on Water Use Final Report



## TABLES

Table 1. European countries and reporti ng regions included in this report. ........................................2 Table 2. Index of agreement for structural ch ange model of domestic water intensity. ....................13 Table 3. Population trends in the Europe-30 region, 1990 to 2030. Source: EUROSTAT, Global Urban Observatory and Statistics Unit of UN-HABITAT, PRIMES. Regions are defined in Table 1..................................................................................................................... ...............24 Table 4. Per capita GDP in the Europe- 30 region, 1990 to 2030. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES . Regions are defined in Table 1. .....................25 Table 5. Projected thermal electricity production for the baseline (LREM-E) scenario. Source: EUROSTAT, PRIMES. Regions ar e defined in Table 1. ..........................................................26 Table 6. Gross value added separated by sector s in the Northern Europe economy. Source: EUROSTAT, Economic and Financial Affair s DG, PRIMES. Regions are defined in Table 1........................................................................................................................ ................27 Table 7. ‘Area equipped for irri gation’ and the ‘percentage of equipped area exploited for irrigation’ (base year 2000). .................................................................................................. .....29 Table 8. Baseline (LREM-E) scenario assumptions for the change in exte nt of irrigated land and change in irrigation water use efficiency.............................................................................30 Table 9. Projected thermal electricity production for the climate policy (SEP) scenario. Source: EUROSTAT, PRIMES. Regions ar e defined in Table 1. ..........................................................35 Table 10. Difference in thermal electricity produ ction for the baseline (LREM-E) and climate policy (SEP) scenarios. Source: EUROSTAT, PR IMES. Regions are defined in Table 1........35 Table 11. Per capita GDP in the Europe-3 0 region under the low economic growth assumptions, 1990 to 2030. Source: EUROSTAT , Economic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1......................................................55 Table 12. Gross value added separated by sector s in the Southern Europe economy. Source: EUROSTAT, Economic and Financial Affair s DG, PRIMES. Regions are defined in Table 1........................................................................................................................ ................79
Table 13. Gross value added se parated by sectors in the Ne w EU Member States economy. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in Table 1..................................................................................................................... ...............79 Table 14. Gross value added separated by sector s in the EU Candidate Countries economy. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in Table 1..................................................................................................................... ...............80 Table 15. Water use in 2030 (in million m3). Ov erview of the model outputs (domestic and agricultural sector)........................................................................................................... ...........81 Table 16. Water use in 2030 (in million m3). Over view of the model outputs (manufacturing and electricity sector). ....................................................................................................... .........82 Table 17. Gross value added separated by sector s in the Northern Eu rope economy (low economic growth variant). Source: EUROST AT, Economic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1......................................................83European Outlook on Water Use Final Report

Table 18. Gross value added separated by sector s in the Southern Europe economy (low economic growth variant). Source: EUROST AT, Economic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1......................................................84 Table 19. Gross value added separated by sectors in the New EU Member States economy (low economic growth). Source: EUROSTAT, Econo mic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1......................................................................84 Table 20. Gross value added separated by sectors in the EU Candidate Countries economy (low economic growth). Source: EUROSTAT, Econo mic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1......................................................................85 Table 21. Projected thermal electricity production for the low economic growth variant. Source: EUROSTAT, PRIMES. Regions ar e defined in Table 1. ..........................................................85 Table 22. Difference in thermal electricity pr oduction for the baseline scenario and low economic growth variant. Source: EUROSTAT, PRIMES. Regions are defined in Table 1. ...86European Outlook on Water Use Final Report



## EXECUTIVE SUMMARY This report presents quantitative scenarios of fu ture water use up to 2030 in 30 European countries (the EU plus 5 EEA member countries). Estimates are also presented for future water availability and water stress. Two scenarios we re developed – a baseline scenar io reflecting a continuation of current trends and a climate policy scenario assuming drasti c policies to limit greenhouse gas emissions. The scenarios account for a wide range of driving forces of water use including changing population, economic growth, technological changes, changes in electricity production, transition to new types of power station coo ling, structural changes in dom estic water use, extent and exploitation of irrigated areas, and climate change.
The WaterGAP model was the t ool used to compute the scen arios. After calibration, model estimates compared well to historical trends or base year data on the count ry level. Nevertheless, scenario estimates have major uncertainties such as the trend in per capita water use in some of the countries undergoing a major econom ic transition, the emergence of new water-intensive industries, the useful lifetime of different pow er stations requiring wa ter withdrawals, and th e future extent of irrigated areas. Future water outlooks should try to reduce these a nd other uncertainties. In a number of ways this study a dvanced the state-of-the -art of European wate r use outlooks. First, it used newly available historical data to improve calculations of domestic water use. Second, it employed a new data base on the cooling systems of power stations to improve calculations of water use in the electric ity production sector. Third, for the first time detailed calculations of water use in several manufacturing sectors were perfor med. Finally, calculati ons of water use in agriculture were tested against independent national estimates. Some of the study’s major findings are:

• The trend of total European water withdrawals is downward . Under the two scenarios, total water withdrawals in the Europe-30 countries decrease by approximately 11% between 2000 and 2030. 18 of 30 European countries have a d ecreasing trend. These results are intermediate compared to previously published estimates.

• The profile of water us e in Europe is changing. In Northern Europe the most important waterusing sector is now the electricity production sector but in the fu ture it will be the manufacturing and domestic sectors (with low to medium certainty) 1 . In the New EU Member States, the most important sector is the electricity production se ctor but this will be replaced by the domestic sector (with low certainty). Water withdrawals in Southern Europe and in the EU Candidate States are currently dominated by agricultural water use and this will remain so (with medium to high certainty).

• A multi-sector approach is needed . Since no single sector will dominate water use in Europe, it is not advisable to focus wate r conservation efforts in Eur ope on any individual sector. Therefore, the European Water Framework Directive offers a good instrument by setting environmental quality goals and requiring countries to implement integrated water management strategies to attain these goals. These strategies allow different countrie s to address different water use sectors that are dominant in these countries.

• A river basin approach is also needed . For administrative and techni cal reasons it makes sense to carry out water conservation programs on th e country-scale. However, the river basin approach required by the Water Framework Direc tive makes it also necessary to address water use issues (including the reductio n of water use and treatment of runoff from water use) on the river basin scale.

1 This and other certainty statements pres ented in the text are expert judgments.European Outlook on Water Use Final Report

• A major unknown is future domestic water use in new EU Member States . Since per capita water use is now relatively low in many of these st ates, an intervention now to encourage water conservation could avoid large increases in the do mestic water use in these countries (low to medium certainty), and thereby help countries to meet the goals set forth in the Water Framework Directive.

• Water use in the electricity production sector is expected (with medium certainty) to significantly decrease during the scenario period. It is apparent (with medium certainty) that requiring the use of tower cooling in all new power stations is an effective strategy for reducing overall water withdrawals.

• Technological development lowers water use . We expect (with medium certainty) that technological improvements in water use sect ors will continue to lead to significant improvements in the efficiency of water use.

• Irrigation water withdrawals may increase in the South. A combination of drier/warmer climate and expanding irrigated area may increase water wit hdrawals for agriculture in the South (low to medium uncertainty). However, this increa sing tendency will be dampened somewhat by continuing improvements in the water use efficiency of irrigation.

• Increase in irrigated areas and/ or irrigation water withdrawals may deteriorate the ecological and chemical status of freshwater bodies. The increase of irrigation withdrawals in the South may lead (with medium certainty) to an increase of contaminated agricultural r unoff to surface and groundwater. Countries will have to take this into acc ount when implementing the Water Framework Directive.

• Climate policies will lead to lower water use in the electricity production sector (medium to high certainty). The emission reductions assumed in the climate policy scenario do not dampen climate change very much in the coming decades (because of inertia in the climate system). However, climate policies could have a more noticeable effect on the future magnitude and profile of energy production a nd thereby on the volume of wate r used in the electricity production sector. Since more non- thermal renewable energy will be used, the capacity of thermal power plants will decline and less cooling water will be needed in the electricity sector.European Outlook on Water Use Final Report 1



## 1. INTRODUCTION

A key responsibility of the European Environmen t Agency (EEA) is to periodically assess the current and future state of the environment in Europe. This assessment is contained in a comprehensive ‘State of the Environment and Ou tlook’ report published every five years. It is obvious that such a comprehensive assessment of Eu rope’s environment shoul d also assess the state of Europe’s freshwater resources . Of particular concern to soci ety is the use of these water resources. Besides satisfying basic needs for dr inking water and sanitati on, water in the household also supports other needs such as housecleaning, dishwashing, cl othes washing, an d landscaping, Water plays a vital role in Europe’s economy. It is needed to produce steam a nd to cool turbines in thermal power stations, and is a necessary input fo r the manufacturing industry where it is used to produce power, as input to various industrial pro cesses, or as a basic raw material. Much of Europe’s agricultural production co mes from irrigated fields, a nd irrigation requires extensive withdrawals of freshwater. Not only is water use cr itical from the standpoint of society, but the use of water is also an important determinant of wate r availability and quality in Europe’s freshwater system. For that reason the future of water use will have an important influence of the future state of the continent’s inland fisheries and freshwater ecosystems. Because of the importance of water use in Europe, the EEA plans to include an ‘outlook’ of future water use in Europe in their ne xt State of the Environment and Outlook report to be published in 2005.


### 1.1 Objectives This report is prepared on behalf of the EEA as a contribution to the next State of the Environment and Outlook Report 2005 (SoEOR2005). In addition, it can also provide valuable information when implementing the European Water Framework Dire ctive. In particular this report provides background information for the outlook on water use in Europe up to 2030. The objectives of the study are to: (a) Produce quantitative estimates of water use in Europe up to 2030. In this study, we use the WaterGAP model (Water – G lobal A ssessment and P rognosis) for modeling European water use and water availability. This model provides a framework for taking into account the impact of major driving forces on future wa ter use and availability in Europe. (b) Explain the effects of changes in driving forces on future water use. In this report, we analyse and explain the impact of key economic, demographic, technological and other driving forces on the future of water use in Europe. This includes the impact of climate change on irrigated agriculture. (c) Assess the impact of climate change and ch anging water use on future water availability and water stress. Although the emphasis of this study is on future water use, we also analyse the possible effects of climate change and futu re water use on water availability and water stress. (d) Contribute to the development of a medi um-term systematic approach to water use outlooks. The methodology presented in this study can be a major component of a systematic approach for periodically assessing Europe’s water use.


### 1.2 Scope Scenarios in this report cove r a ‘medium’ time horizon, from 2000 (base year) to 2030. Year 2000 is used as a base year because of the availability of data from that year. Most scenario assumptions and results are given in 5-year intervals.European Outlook on Water Use Final Report 2

Data are produced for 30 European countries which we refer to in this report as the ‘Europe-30’. These countries are listed in Table 1 and shown in Figure 1. For reporting purposes we sometimes summarize scenar io results into four regions (Table 1). These regions are based on a pragmatic combination of geographic and poli tical factors. Due to lack of data Iceland and Liechtenstein are not included in the study.
Table 1. European countries and reporti ng regions included in this report.

Reporting region Countries

Northern Europe Austria, Belgium, Denmark, Finland, Germany, Ireland, Luxembourg, The Netherlands, Sweden, United Kingdom, Norway, Switzerland Southern Europe France, Greece, Italy, Portugal, Spain

New EU Member States Cyprus, Czech Republic, Estonia, Hungary , Latvia, Lithuania, Malta, Poland, Slovak Republic, Slovenia EU Candidate States Bulgaria, Romania, Turkey Europe-30 all countries listed above

Figure 1. ‘Europe-30’ region covered in this report.

Estimates of future water use are presented on both th e regional, country and sectoral level. In this report we use the following conventions for water sectors:

• Domestic – Water use of households and small businesses.

• Manufacturing – Water use in all facilitie s producing industrial products.

• Electricity power production – Water use in all facilities producing electrical power except for the power producing facilities of the manufacturing water sector.

• Agriculture – Water consumed by irriga tion and used by livestock.European Outlook on Water Use Final Report 3

As noted above, we analyse not only changes in water use but also changes in water availability and water stress. ‘Water availability’ is used here to mean the total rive r discharge in a river basin which is made up of surface runoff and groundwater recharge.
Water stress is taken here as a measure of the am ount of pressure put on wa ter resources and aquatic ecosystems by the users of these resources, includi ng municipalities, industries, power plants and agricultural users (see, for exam ple, Alcamo et al., 2000; Vörösmarty et al., 2000; Cosgrove and Rijsberman, 2000). Here we use a conventional measure of water stre ss, the withdrawal-toavailability ratio. This is the ratio of total an nual water withdrawals devided by the total water availability. Because water availability and water stress vary so strongly spatially, it is not meaningful to compute them on the country or sectoral level as we do for water use. Inst ead we compute them on the grid and river basin level.European Outlook on Water Use Final Report 4



## 2. DRIVING FORCES AND OTHER FACTORS OF WATER USE

Water use in Europe is divided between four important sectors: domestic, electricity, manufacturing, and agriculture (Figure 2). A wide range of factors influe nce water use in these sectors as we describe in the following paragraphs.

Water withdrawal per sector in Europe-30 in 2000

32%

24% 13% 31%

Agriculture Domestic Manufacturing Electricity

Figure 2. Percentage share of sect oral-specific water use in the Eu rope-30 region for the year 2000. Sources: EUROSTAT 2 and national Statistical Offices.



### 2.1 Domestic Sector
The domestic sector accounts for ab out 24 percent of total water wi thdrawn in the Europe-30 in 2000 (Figure 2). This sector usually includes hous eholds and businesses but not manufacturing or electrical produc tion facilities. The intensity of water use in households [m 3 /(cap

⋅ year)] depends on many factors including the amount of household income which is related to the amount of water-usi ng appliances in a household (Höglund, 1999; Dalhuisen et al., 2003). Anothe r factor is the size of the household since it is usually observed that ther e are economies of scale in wate r usage per person in larger households (Björnsen, 1993; Höglund, 1999). Othe r demographic factors such as the age distribution of the population also apparently affect the amount of water use since some age groups tend to have higher per capita water usage than othe rs. There is also an observed difference between water consumption patterns in urban versus rural areas. Higher water prices are also know n to dampen the demand for wate r in households and businesses (Hansen, 1994; Dalhuisen et al., 2003). Hence changing water prices are a driving force of water use in this sector. On the other hand the relatio nship between prices and demand are highly variable because household and business outlays for water ar e normally only a very small fraction of their total income, and because prices and price stru ctures vary tremendously across Europe. Figure 3 vividly illustrates the wide vari ability between average domestic wa ter prices and wa ter use across Europe. Currently countries with roughly the same per capita wa ter use have a factor of six difference in water prices.

2 EUROSTAT. Statistical Office of the European Communities.European Outlook on Water Use Final Report 5

Figure 3. Household water use and water prices in OECD countries. Source: OECD (1999).
Moreover the paucity of data makes it impossible to generalize about the re lationship of price and demand for all of Europe. Of course a decisive fact or in the domestic sector is not only how much water is used per capita but the size of the popul ation using water. The amount of water withdrawn for domestic water supply will also depend on the am ount of losses in the wa ter distribution system. These losses vary considerably between European countries; they range from less than 5% in Germany to 50% in Bulgaria in 1999 (EEA, 2003). Such high percentages of water lost can be effectively reduced with new piping systems.


### 2.2 Electricity Production Sector This sector accounts for about 31 percent of total water withdrawn in the Europe-30 in 2000 (Figure 2). Within the electricity production sector therma l power plants account for most of the water withdrawn while the amount of water required by wind, solar, a nd hydroelectric pow er stations is relatively small. (Sometimes the water evaporated in reservoirs of hydroelectric power stations are reckoned as water requirements of electricity produc tion, but we do not take this into account in our study). In this context, a therma l power plant is a pow er-generating plant wh ich uses heat to produce energy. Such plants may burn fossil fuels, biomass or use nuclear energy to produce the necessary thermal energy (GEMET, 2000). The rate of water withdrawals per unit electricity generated is much higher in power stations using traditional once-through flow cooling than in th e more contemporary tower cooled plants. Hence one of the principal driving forces of water use in the electricity production is the rate at which plants with once-through flow cooling are be ing replaced by tower cooled plants. Obviously, another crucial driving force is the magnitude of electri city produced at ther mal power plants and how this will change in the future.


### 2.3 Manufacturing Sector Manufacturing activity acc ounts for about 13 percent of the tota l water withdrawn in the Europe-30 in 2000 (Figure 2). The intensity of water use [m 3 /(1000 € gross value added) ] varies tremendously from industry to industry. Fo r example it is around 138 m 3 /(1000 € gross value added) in the paper industry and only 1 m 3 /(1000 € gross value added) in the textil e industry (values with respect to Turkey Sweden

Belgium Germany Switzerland

Austria Hungary Spain Australia

Denmark

Finland France

Netherlands UK Luxemburg

Greece Czech Rep US

Italy Canada

0 20 40 60 80 100 120 140

0 0.5 1 1.5 2 2.5 3 3.5 Water prices [US$/m3] (1994-98)household water use [m3/cap×year]European Outlook on Water Use Final Report 6

Finland). Indeed some industries are clearly much more water-intensive than others. These include not only the paper industry, but also the food indus try, the chemical industr y and the production of mineral products. As in the domestic sector, the price of water is known to influence water use in industry. But normally only a small fraction of the operating costs of a firm goes to water costs. Moreover, data are inadequate to generalize about the relationship between water pric e and water usage in the entire manufacturing sector of Europe. The main driving force of water use in the manufact uring sector is the cha nge in the output of water-intensive industries (measured, for example, in units of the gross value added of products generated in a particular industry) . Hence structural changes in th e profile of industrial production – what will be produced and how much – will profoundly affect the total water use in this sector. For example, the increasing influence of water-intensi ve industries such as electronics, will affect overall water use by manufacturing.


### 2.4 Agriculture Sector Agriculture accounts for about 32 percent of the to tal water withdrawn in the Europe-30 in 2000 whereas 1 percent accounts for livestock water use and 31 percent account for irrigation (Figure 2). The two main needs for water use in this sector are irrigation, which account s for most of the water used in this sector, followed by livestock water use. The amount of water required for irri gating a hectare of a particular crop depends especially on the water retention characteristics of crops and soil, and local precipitation, temperature, wind, and other climatic conditions. To es timate the country scale water wi thdrawn for irrigation, we must multiply the per hectare crop requirements for water by the actual area irrigated and then divide this by the irrigation ‘field’ efficiency. Hence change s in the extent of irrigated land and in the improvement of irrigation efficiency will also dr ive changes in the amount of water withdrawn for irrigation. Figure 4 presents the increase of area equipped for irrigation in Turkey, an example of rapidly expanding irrigated land. Here the extent of irrigated land in creased three-fold between the 1960s and the end of the century. In general the expansion of irriga ted area in Europe shows a clear upward trend between 1960 and 1990 (Baldock et al. 2000 ) and declined or stab ilized in the 1990s. The ‘area equipped for irrigation’ as a percent of local arable land is depicted on a European grid (base year 1995) in Figure 5. The density of irrigated land is partic ularly high in southeast Romania and northern Italy. High concentratio ns of irrigated land are also found in Turkey, Bulgaria, Greece, and Spain.

Turkey

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000

1955 1965 1975 1985 1995 2005

yeararea equipped for irrigation [1000 ha]

Figure 4. Extent of irrigated la nd in Turkey between 1961 and 2001. These data depict the surface area equipped for irrigation but not necessarily irrigated every year. Source: FAO (2004).European Outlook on Water Use Final Report 7

Figure 5. Area equipped for irrigation versus total ar able land by country as used in the WaterGAP model. Source: Döll and Siebert (2000).
Livestock also are major users of water in many countries and in Northern Europe the amount of water used for livestock is almost as high as the amount of water used for irrigation. The main driving forces of water use by livestock in a particul ar area are the type and number of livestock in a given area.


### 2.5 Driving Forces Included in this Study While Sections 2.1 to 2.4 give an overview of most of the important factors that drive changes in water use, here we review the driving forces that are taken into ac count in this report. Although it would be desirable to include all of the driving forces described in Sections 2.1 through 2.4 in a study of future European water use, it is no t feasible here for three reasons. First of all, while some Europe-30 countries ha ve detailed data on driving forces, most do not. Second, the short time available for this study (11 months) made it in feasible to identify an d analyse large amounts of new data (although some new data were used as we describe in Section 3.3) In Chapter 8 we recommend specific data that should be collected to improved future water use outlooks. Third, even if more driving force data were available for estimating future water use, current models do not reliably describe the relations hip between all driving forces a nd water use. For example, it is currently not possible to model the relationship between future household age structure and future water use on the European scale. More fundamental work is needed in developing comprehensive and realistic water use models that apply to all European countries. Although not all important driving forces could be taken into account, this study does take into account a very wide range of important driving forces. These driving forces are incorporated in the calculations of the WaterGAP model which is used here to compute quantitative scenarios. The WaterGAP model is described in Section 3.2. Here, we list some of the more important driving forces incorporated into WaterGAP: (a) Population: The number of future water users will obvi ously determine the magnitude of water use in the domestic sector. Population assump tions are used in the WaterGAP model to compute water use in the domestic sector. (Other variables are also important as explained in Section 3.2.3). Population is also ta ken into account as an indirect driving fo rce of water use inEuropean Outlook on Water Use Final Report 8

other sectors. For example, the assumptions for future electricity use (used to compute future water use by power plants) are based on futu re population estimates among other factors. Likewise, changing population is in directly included in estimates of future irrigated land and emissions of greenhouse gases (which drives future climate change). (b) Per Capita Income (GDP/cap): From historical trends of wa ter use in Europe it has been observed that water use tends to increase as a c ountry becomes wealthier and then it levels off and in some cases declines. Hence changing inco me is an important driving force of future water use. Per capita income is used in the Wate rGAP model to compute pe r capita water use in the domestic sector. (Other variables are also im portant as described in Section 3.2.3). Income is an indirect driver of water use in the el ectricity production sector because assumptions for future electricity use (used to compute fu ture water use by power plants) are based on assumptions about future income, population, and other factors. (c) Thermal electricity production: The volume of water needed at thermal power plants is driven by the production of electricity at these faciliti es. The WaterGAP model uses assumptions about future thermal electricity pr oduction (and other variables as explained in Section 3.2.4) to drive calculations of water use in the electrici ty production sector. In this context, thermal power plants may burn fossil fuels, biomass or use nuclear energy to produce the necessary thermal energy. (d) Type of cooling system: Previously we have mentioned that the type of cooling system in a power station (once-thro ugh or tower) is an important determ inant of the station’s water use. This driving force (and others as explained in Section 3.2.4) is taken into account by the WaterGAP model to compute water use in the electricity production sector. (e) Gross value added: The magnitude of manuf acturing output in a particular industry is an important determinant of water use by the manu facturing industry. The WaterGAP model uses assumptions of future manufactur ing output (in the form of gro ss value added of products) to compute water use in the manufacturing industry sector. (See Section 3.2.5). (f) Irrigated areas: An obviously important driving force of irrigation water use is the extent of irrigated land. The WaterGAP model uses assump tions about the future coverage of irrigated area (and other data, as descri bed in Section 3.2.6) to com pute water use for irrigation. (g) Climate change: Not only the extent of irrigated land, but al so climate is an important driver of irrigation water requirements. The WaterGAP model takes into account local climate (see Section 3.2.6) in calculating ir rigation water requirements. (h) Number of livestock: Water use by livestock in a count ry is obviously driven, among other factors, by the number of livestock. This drivin g force is taken into account by WaterGAP to compute livestock water use. (See Section 3.2.7). (i) Technological changes leading to improvements in water use efficiency: This driving force is particularly important because it tends to reduce water use whereas the preceding driving forces in most cases increase water use. The impact of tec hnological change on improving water use efficiency is taken into acc ount in all sectors. (See Section 3.2.4).European Outlook on Water Use Final Report 9



## 3. METHODOLOGY

In order to attain the goals of this study (estimating future water use and availability for 30 separate European countries), we decided to combine two approaches: a sc enario approach and a modeling approach. The scenario approach was chosen to co mbine qualitative images of possible futures with quantitative data of water use in Europe. However, due to the very short time available (11 months) for the study, we could only develop two alternativ e scenarios. The modeling approach was selected to quantify the current and future European wate r use in a consistent way and thus support the scenarios. Here, we selected the existing WaterGAP model and focused on the most critical driving forces although we recognize that there are many mo re driving forces that have an influence on future water use. We further us ed newly available European datato improve previous Europeanscale estimates of future water use in the do mestic, manufacturing, a nd electricity production sectors.


### 3.1 The Scenario Approach The basic methodology of this study is ‘scenario analysis’ which has become a common tool for assessing future trends of envir onmental problems, particularly th ose that are complex and poorly described. The aim of scenario analysis is not to predict the future but rather to support the understanding of complex systems, to examine the interactions of tr ends within a given domain and time frame, and to identify critical issues. In this sense, scenarios provide images of possible futures and complement conventional forecasting and simulati on. In order to be meaningful to science and policy, scenarios must be based on a set of assumpti ons and/or theories of the key relationships and driving forces of change that are coherent, intern ally consistent, reproduci ble and plausible (IPCC, 2000). If these requirements are fulfilled, scenarios can provide useful results for decision making. The scenario approach is used in this study to produce two main scenarios of water use – a baseline scenario and a climate policy scenario . Variants of these scenarios are also produced for analysing the importance of the various driving forces. There are different types of scenarios that can be built to describe the future of water use in Europe. One way of classifying scenarios is into qualitative and quantitative categories. Qualitative scenarios describe in words or other non-numerical form the trends of future water use, whereas quantitative scenarios provide numerical information about future changes in water use. The appropriate type of scenario de pends on the goals of the scenario exercise. In this study, the EEA needs numerical estimates of future water use indi cators for its regular envi ronmental reporting and assessment so that the quantititive trends of water use indicators can be compared to the trends of other environmental indicators. Hence, our scenario approach here is to develop quantitative scenarios that provide the numerical data needed for the EEA assessments. It is important to note, however, that under other circumst ances and objectives it might be equally useful to develop qualitative scenarios or combined qualitative-quantitative scenarios.


### 3.2 Modeling Approach

3.2.1 Introduction In order to build quantitative scenarios of future water use, it is necessary to use a suitable instrument for quantifying current and future water use. The instrument used in this study is the WaterGAP model (Alcamo et al., 2003a, b; Döll et al., 2003). It has been applied in several international assessments of Eur opean and world water resources:European Outlook on Water Use Final Report 10

- EuroWasser : first assessment of the impacts of climate change on both the frequency of droughts and occurrence of flooding in Europe (Lehner et al., 2001).

- UNEP Global Environmental Outlook 3 : assessment of the impact of climate change and socioeconomic changes on water resources in Europe and the world for the time horizon between 2002 and 2032 (UNEP, 2002).

- Water for People – Water for Life. The United Nations World Water Development Report: analyses of the current wa ter situation in Europe a nd the world (UNESCO, 2003).

- International Dialogue on Water and Climate : assessment of the impact of climate change and variability on water resources in Europe and the world (Kabat and van Schaik, 2002).

- Millennium Ecosystem Assessment : assessment of ecosystem serv ices provided by the world’s freshwater system.

- World Water Vision Exercise of the World Water Commission : assessment of the impact of different economic and population pathways on water use in Eur ope and the world (Alcamo et al., 2000).

- World in Transition: Ways towards sustainable management of freshwater resources: assessment of the future water use and water av ailability in Europe and the world up to 2025 (WBGU, 1999).

WaterGAP is used to compute both water use and av ailability on different sc ales within Europe. It consists of two main components: a Global Hydrology Model to simula te the terrestrial water cycle and a Global Water Use Model to estimate water withdrawals and consumption. The Global Water Use Model consists of five submodels to de termine both the water withdrawals and water consumption in the household, electricity, manufactur ing, irrigation, and lives tock sector. In this context, water withdrawals depi ct the total amount of water us ed in each sector while the consumptive water use indicates the part of withdr awn water that is lost to evapotranspiration, consumed by industrial products or humans. For most water use sectors, only a small amount of water is actually consumed, whereas most of the water withdrawn is returned, probably with reduced quality, to the envir onment for subsequent use.

3.2.2 WaterGAP: Water Availability The aim of the Global Hydrology Mode l is to simulate the characteri stic macro-scale behavior of the terrestrial water cycle in order to estimate water availability. Herein, water availability is defined as the total river discharge, which is the sum of surface runoff and groundwater recharge.
The model covers most of the terrestrial surface of the earth with a geographic grid containing 66896 grid cells with a size of 0.5° by 0.5° (geogr aphical longitude and la titude, respectively) which covers the entire global la nd area except Antarcti ca (IMAGE 2.2 land mask). For each grid cell, information on the fraction of land area and of freshwater area (lakes, reservoirs , and wetlands) is available. Land cover is assumed to be homogeneous within each grid cell. The upstream/downstream relationship among the grid cel ls is defined by a globa l drainage direction map (DDM30) which indicates the drainage dir ection of surface water (D öll and Lehner, 2001). Thus, each individual grid cell is assigned to a drainage basin. The model calculates a daily vertical water balance for each grid cell, separately for the fraction of land area and for the freshwater area. The vertical water balance of land ar eas is described by a canopy water balance (representing interception) and a soil wate r balance. The canopy water balance determines which part of the precipitation is intercepted (evaporates) by the canopy, and which part reaches the soil. The model ba lances incoming precipitation with actualEuropean Outlook on Water Use Final Report 11

evapotranspiration and total runoff. Then, the tota l runoff from land area is divided into surface runoff and groundwater recharge, using informati on on cell-specific slope characteristics, soil texture, hydrogeology, and the existe nce of permafrost and glaciers. Aside from calculating the land area water balance, a vertical water balance for the freshwater areas (lakes, reservoirs, and wetlands) is calculated. The runoff from open fr eshwater bodies is defi ned as the difference between effective precipitation and potential evaporation. Finally, the total runoff of a grid cell is the sum of the runoff from land and from open freshw ater bodies. In the mode l, it is distinguished between ‘local’ and ‘global’ open freshwater bodies . In contrast to the local lakes and wetlands, which only consider flow-through processes with in a cell, global open freshwater bodies are additionally flowed through from neighboring cells. The runoff pr oduced within th e cell and the volume of water coming from upstream cells is trans ported through a series of storages representing the groundwater, lakes, reservoirs , wetlands, and rivers. Then, the total cell discharge is routed along the drainage direction map (DDM30) to the next downstream cell. The hydrological model requires data about pr ecipitation, potential ev apotranspiration, and temperature for each grid cell. As climate input, the data by New et al. (2000) provide observed monthly values of precipitation, te mperature, number of wet days, average daily sunshine hours, cloudiness, and global radiation, inte rpolated onto a 0.5° by 0.5° grid and for each of the years 1901 to 1995. In the Global Hydrology Model, the calcu lations are performed on a daily resolution. Synthetic daily precipitation valu es are generated using monthly precipitation values and the number of wet days per month, the monthly precipitation is distributed equally to all rainy days. In order to take into account the effect of snow, effective preci pitation, which is the sum of precipitation as rainfall and snowmelt, is calculated using a degree-day algorithm. Future climate is simulated by changing the monthly temperature and precipitation observed in the so-called climate normal period (1961-1990) according to future climat e projections from gene ral circulation models (GCMs). The Global Hydrology Model is calib rated against long-term average annual discharges measured at 724 gauging stations world-wide, the drainage areas of which cover ha lf the global la nd area except Greenland and Antarctica. In Europe, the model has been calibrated in 126 drainage basins, covering 65% of Europe’s land area (Lehner et al., 2001).

3.2.3 WaterGAP: Domestic Water Use
The domestic water use model calculates the annua l withdrawals and cons umption of water by households and small businesses. The basic appro ach of this submodel is to first compute the domestic water use intensity [m3/(cap

⋅ year)] and then to multiply this by the population of water users. The main concept of the model follows th e approach described in Alcamo et al. (2000, 2003a, b). Changes in water use in tensity can be expressed by structural changes and technological changes.
To calculate total water withdrawals in the domestic sector, the net water use intensity is multiplied by country population. Country-w ide values are allocated to grid cells within the country based on population density which, in turn, is aggregated from the CIESIN worl d population density map 2000 (Global Population Density Map, 2.5’ x 2.5’ resolution) (CIESIN, 2001). Structural Change The concept of structural change, as it is used to estimate domestic water use, is based on the observation that as average income increases, wa ter consumers tend at first towards a more waterintensive lifestyle (washing machines, dishwashers, more bathrooms, more car-washing). Finally a maximum level is reached after wh ich per capita water use is either stable or declines. This structural change is represented in the baseline scenario by a sigmoid curve which indicates how water use intensity (per capita water use) chan ges with income (GDP/cap). (See Figure 6).European Outlook on Water Use Final Report 12

Figure 6. Conceptual model of structur al change in the domestic sector.
The relationship between water intensity and in come is derived for each country by fitting a sigmoid curve to historical data from each country: 

# ( )      

⋅ − ⋅ + = ⋅ − year cap m e DWSI DSWI GDP 3

min 2 1 γ α (1)

where:

DSWI = Domestic structural water use in tensity for each country [m3/(cap

⋅ year)]

GDP = Annual gross domestic product in [Euro/(cap

⋅ year)]

γ = Fitting parameter for each country, fitted using historical data [1/Euro2]

DWSI min = Minimum water use intensity for human activities [m3/(cap

⋅ year)]. Set to 18 m3/(cap

⋅ year) for each country, corresponding to Gleick (1996)

α = Water use intensity parameter for each country, fitted using historical data [m3/(cap

⋅ year)]

Data for these curves were provided by the EEA, EUROSTAT, and other national statistical agencies of the EEA member stat es covering up to forty years in the past. Figure 7 gives an example of the fitted curve for Germany. (Note that the water intens ities shown in Figure 7 are not the observed water intensities. These are adjust ed data from which th e estimated effect of technological improvements in wate r use efficiency on past water in tensities have been subtracted. Hence the water intensities in these graphs are so mewhat higher than the obs erved per capita water use.) Historical/Current Trendsdomestic structural water use intensity[(m3/(cap⋅year)] Scenarios



# ? Today

GDP/cap sigmoid curveEuropean Outlook on Water Use Final Report 13

Figure 7. Structural change in water intensity in the domes tic sector in Germany. Source: DESTATIS 3

. To evaluate the fit of the curv es, we use the index of agreement of Will mott (1984) which is suitable for evaluating sigmoid curves. The resulti ng index of agreement for each country is given in Table 2. The index of agreement varies be tween 0.0 and 1.0, where a va lue of 1.0 expresses a perfect agreement between the observed and calculated values, and 0 describes a complete disagreement. The index ranges from 0.47 for Romania to 0.99 for the United Kingdom and Italy. For 70% of the countries considered in this stud y, the index of agreement is higher than 0.80, for 50% the index is higher than 0.90. (See Table 2 and Appendix A). Th e calibrated curves were used for almost all European countries to compute fu ture water use intensity and water withdrawals according to Equation (1).
Table 2. Index of agreement for structural change model of domestic water intensity.

country Index of agreement country Index of agreement
Austria 0.96 Lithuania — Belgium 0.91 Luxembourg 0.68 Bulgaria 0.66 Malta 0.82 Cyprus 0.90 The Netherlands 0.97 Czech Republic — Norway 0.83 Denmark 0.91 Poland — Estonia — Portugal 0.73 Finland 0.91 Romania 0.47 France 0.83 Slovak Republic — Germany 0.94 Slovenia 0.86 Greece 0.70 Spain 0.78 Hungary — Sweden 0.85 Ireland 0.96 Switzerland 0.69 Italy 0.99 Turkey — Latvia — United Kingdom 0.99

3 DESTATIS. Federal Statistical Office, Germany. Germany

0 20 40 60 80 100 120

0 5000 10000 15000 20000 25000 30000 35000 GDP/cap. [Euro2000]dom. water intensity [m3/a/cap.] today

baseline scenario adjusted datadomestic structural water use intensity[m3/(cap⋅year)]

GDP/cap. [Euro2000]European Outlook on Water Use Final Report 14

The curves could not be used for the Czech Repub lic, Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Republic, and Turkey whose historical data could not be fitted to a sigmoid curve because the trend of their data shows a sharp break after 1990. Therefore, we used the following alternative approach. Water use patterns in these countries dras tically changed after 1990. For all countries but Turkey, this coul d be explained by the transition from a socialist to a market economy; in the case of Turkey, hi storical data show the same tr end. This break in the temporal trend means that there is no clear relationship between per capita water use and GDP/cap. Hence historical data do not provide insi ght into the direction of per cap ita water use under future changes in the economy. We must ther efore assume a trend in future per capita water use a priori

. Two extreme assumptions are shown in Figure 8 for the example of the Czech Republic. The bottom flat curve assumes that dom estic water use will remain at its year 2000 level despite strong economic growth projected up to 2030. This might be achieved if water conservation programs can keep pace with the pressure to use more water because of wealthier lifestyles. The upper steep curve in Figure 8 assumes that per capita water use in the Czech Republic will converge by 2030 with the average value of other Europe- 30 countries. Under this assumpti on per capita water use in the Czech Republic will regain eventually its high level of 1990. These two assumptions ‘bracket’ a plausible range of possibilities for changing per capita wa ter use. For the baseline scenario we assume that the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Republic, and Turkey follow the upper curve in Figure 8 (adjusted for the historical data trends in each of these countries.). That is, we assu me that water intensity in the domestic sector (per capita water use) converges with the pan-European average in 2030. In Chapter 7, we use the lower curve in Figure 8 to compute water use and compare it with the baseline scenar io as a sensitivity analysis.

Figure 8. Temporal trend of per capita water use in the domestic sector in the Czech Republic. Source: EUROSTAT.
Technological Change The concept of technological change is used in th e domestic sector and in other sectors to account for the important effect that improving technology tends to im prove water use efficiency. Continuous improvements in technology make app liances and industrial processes more water efficient and hence, contribute to redu ctions in water use. (See Figure 9). Czech Republik

0 20 40 60 80 100 120 140

1960 1980 2000 2020 2040

yeardomestic water useintensity [m3/cap.year]

historical data low er bound upper bound Czech Republic

historical data remains at the year 2000 level converges to EU average

non-convergence conver g enceEuropean Outlook on Water Use Final Report 15

Figure 9. Technological improvements leading to hi gher water use efficiency in the domestic use sector. Source: V-ZUG AG (2004).
While structural changes can lead to both, an increase or a decrease of water use intensity, technological changes are assumed to result only in a reduction in water us e intensity (See Figure 10). Technological improvements are included in cal culations of water use by specifying the rate at which new water using devices beco me more efficient over time. For every scenario, this rate of efficiency improvement (technological ch ange) is specified in Equation (2):

     

⋅ ⋅ = year cap m Tch DWSI DWI D 3 (2)

where:

DWI = Domestic water use intensity for each country [m3/(cap

⋅ year)]

DWSI = Domestic structural water use in tensity for each country [m3/(cap

⋅ year)]

Tch D = Technological change for the domestic sector for each country [-]

Figure 10. Impact of technological change on water use intensity.Water use intensity[m3/(cap⋅yr)]

TimeEuropean Outlook on Water Use Final Report 16

3.2.4 WaterGAP: Water Use for Electricity Production The objective of this submodel is to compute wa ter use for producing electricity. Here, the model simulates the amount of water withdrawn and cons umed for cooling purposes in the electricity sector. (Some of the water is converted to the steam which dr ives the generator producing the electricity). Since thermal power plants 4 use freshwater for cooling we calculate location-specific annual values for water withdrawal s as well as water consumption. The allocation of the water used for cooling purposes to the globa l grid with a spatial resolutio n of 0.5° by 0.5° (geographical longitude and latitude) was possible because all power stations are given by their geographical coordinates. The amount of water withdrawn by each power plant using freshwater for cooling is computed by multiplying the annual electricity production [MWh/year ] with the water use intensity of the power station (water withdrawal per unit electricity production, in m3/M Wh). The total annual thermal power plant water withdrawal (TPWW) in each grid cell is then calculat ed as the sum of the withdrawals of all power plants with in the cell (Vassolo and Döll, 2004):

     

⋅ ⋅ = 

## ∑

= year m Tch CS WI EP TPWW

i TP i n

i i 3 ) (

1 (3)

where:

EP i = Electricity produced by a thermal power plant i within the cell [MWh/year]

WI i = Station-specific water withdrawal inte nsity [m3/MWh]. This figure depends on the cooling system of the plant, CS i
Tch Pi = Technological change for water cool ing in a thermal power plant i [-]

n = Number of stations in the cell
The consumption of water by each power plant is computed by substituting in Equation (3) the water withdrawal intensity with the water consum ption intensity. The main driving force of water use in the electricity sector is the amount of electricity produced by thermal power plants which is represented by EP i (Equation (3)). The technological change that will lead to a higher water use efficiency is taken into account as the factor Tch Pi . Further, TPWW depends on the water use in tensity which is solely impacted by the cooling system of the power station. In this approach, two types of cooling systems are distinguished: i) the ‘on ce-through flow’ system and ii) the ‘tower cooling’ system. In contrast to the once-through flow system, where the cooling water is re turned to the river after it has cooled down the condenser, the water in a to wer cooling system flows in a cl osed circuit. As a result, the water use intensity of a once-th rough flow cooling system is mu ch higher compared to a tower cooling system. On the other hand, the fraction of water consumed is very small compared to the tower cooling system. In the once-through flow system, only 0.36% of the water withdrawn is consumed and the rest is returned to the source , whereas in the tower cooling system, almost 30% of the water withdrawn leaves the station by ev aporation in the tower. The water withdrawal intensities for each cooling system are derived from various power station operators and related data. The values obtained are:

4 Thermal power plant: A power-generating plant which uses heat to produce energy. Such plants may burn fossil fuels, biomass or use nuclear energy to pr oduce the necessary thermal energy.European Outlook on Water Use Final Report 17

- 180 m3/MWh for power plants with on ce-through flow cooling system and - 4.5 m3/MWh for power plants with tower cooling systems. The water consumption intensities for each of the two cooling sy stems are taken from data of Unipede (1999): - 0.65 m3/MWh for power plants with once-through flow cooling and - 1.33 m3/MWh for power plants with cooling tower systems. Input data on location, type and size of power station are based on the World Electric Power Plants Data Set of the Utility Data Institute (UDI, 2000) . This database contains comprehensive global data on all types of electric power stations including informa tion on the name of the station, installed capacity, year of connection to the net, fuel type, and cooling t ype. All these values are based on statistical data from 1995. Unfortunately, the exact geograp hical locations of the power stations are not included. To determine the geogra phic coordinates of the st ations, the database of foreign geographic features (NIMA – National Imagery and Mapping Agen cy, 2000) was used. For Europe, 10469 power stations are taken into account, 97% are fossil- fueled, 2% nuclear-fueled, and another 1% are geothermal. Figure 11 shows the distribution of all European power plants taking into account in this study. The different symbols separate power plants according to the cooling system. In Europe, 66% of the power plants are cooled by once-through flow cooling system, while 34% used tower cooling.

Figure 11. Location of European power plants take n into account in this study. Sources: UDI (2000) and NIMA (2000).

To validate the estimated water withdrawals for el ectricity production, the values computed for the year 2000 are compared to data from EUROSTAT and other national Statistical Agencies for almost all countries considered in this study (Europe-30 region). Figure 12 shows a scatter-diagram for the model efficiency indicating the goodness-to -fit with respect to the 1:1 line. The model efficiency is calculated according to Equation (4):European Outlook on Water Use Final Report 18

)2 ( )2 ( 1

1 , , 1 , , 

## ∑ ∑

= =

− −

− = n

i i published i published n

i i published i calculated

PWW PWW PWW PWW ME (4)

where:
ME = Model efficiency, where ME = 1 indicates a perfect fit [-]

PWW = Water withdrawal for electric ity production per country [m3/year]

PWW Mean water withdrawal electr icity production per country [m3/year]

n = Number of countries

The overall model result s show a ME of 0.99. It is, thus, co ncluded that the applied methodology leads to an adequate evaluation of the spatially distributed water withdr awals for power plants.

Figure 12. Comparison of simulated and published wate r use in the electricity production sector and model efficiency. 25 European c ountries are taken into account 5

.
3.2.5 WaterGAP: Water Use in the Manufacturing Industry The objective of this submodel is to compute wa ter used by the manufacturing industry. To take into account the great diversity of industrial processes and th e variety of input and output specifications, the manufacturing water use model di stinguishes between 6 ma nufacturing sectors: - Food products; beverages and tobacco; - Textiles and textile products; - Pulp, paper; publishing and printing; - Chemicals, man-made fibres;

5 No published references were available for Luxembourg, Malta, Norway, and Slovak Republic. In Cyprus, only saltwater is used for cooling purposes. Water use for electrical power production in 2000

1 10 100 1000 10000 100000

1 10 100 1000 10000 100000 published values [mio. m3/year]simulated values [mio. m3/year] model efficiency = 0.99 1:1 lineEuropean Outlook on Water Use Final Report 19

- Non-metallic, mineral products; and - Basic metals and fabrication of metal products.
These six sectors are classified in the NACE se ctoral code system of the EU (Nomenclature générale des Activités dans les Communautés Européenes). This system is a standard system for classifying economic activities. Based on EUROSTAT (Pau Vall, 2001) these six sectors together account for more than 80% of the to tal manufacturing water withdrawal.
For each of these sectors the model simulates th e amount of water withdrawn and consumed in production processes, except for co oling for power generation. For most of the countries, water withdrawal per sector is availa ble from national statistics for the base year 2000. Since we are however interested in water withdrawals in the future, a water use intensity has to be derived that can then be multiplied with the driving force for water use in the respective sector. Sector-specific gross value added is used as this driving force. Thus the sector-specific water use of the base year is devided by the GVA of the base year to obtain th e sector-specific water use intensity SMWI. The model then takes SMWI and multip lies it with the future sect or-specific GVA. Technological improvements are taken into account by a sector-sp ecific technological change factor (as specified in the scenarios). To obtain the total manufacturi ng water withdrawal at national level, the sum over the six sectors is computed according to Equation (5):

     

⋅ ⋅ = 

## ∑

= year m GVA Tch SMWI MWW i M i i i 3 6

1 (5)

where:
MWW = Manufacturing water withdr awal per country [m3/year]

SMWI i = Sectoral manufacturing water intensity per country [m3/1000€ GVA]

Tch Mi = Technological change for the manufacturing sector i [-]
GVA = Gross value added per country [Euro/year]
The water consumption for each sector is obtained as the difference between the water withdrawal and the waste water. For countries where no data are available, th e fraction of consumptive water use is derived from neighboring or economically comparable countries. With respect to manufacturing water use, there is no information on the specific locations of water users. Therefore, manufacturing water use is assu med to be distributed among the grid cells of a country proportional to its urban population. Base year data (year 2000) fo r water withdrawals are taken fr om EUROSTAT and other national statistical agencies. About one-half of the Eu rope-30 countries have sector-specific water withdrawals for the base year. For the remaini ng countries, total manufac turing water withdrawals are distributed to the different se ctors according to the ratio of the sectoral gross value added to the total industrial gross value added. The improvement in water use efficiency due to technological changes is derived for each sector and extrapolat ed based on historical data (see Appendix B).

3.2.6 WaterGAP: Irrigation Water Use The objective of this submodel is to compute net a nd gross irrigation requirements which reflect an optimal supply of water to irrigated crops. In this context, ‘net irrigation re quirement’ refers to the part of the irrigation water that is evapotranspi rated by plants, while ‘gro ss irrigation requirement’European Outlook on Water Use Final Report 20

refers to the total volume of water that is wi thdrawn from its source (Döll and Siebert, 2002; Alcamo et al., 2003a). The ratio of net to gross irri gation requirement is calle d ‘irrigation water use efficiency’. This concept is similar to the water use efficiency of the pr evious sectors described. In contrast to the other water use models, the irri gation model computes monthly rather than annual results. The model calculation is based on a global map of irrigate d areas (Döll and Siebert, 2000) with a spatial resolution of 0.5° by 0.5° (geographical longitude a nd latitude). This map shows the fraction of agricultural area of each grid cell that is equipped for irrigation. The computation of the net irrigation requirement pe r unit irrigated land is a function of climate, cropping intensity, and crop type (distinguishing rice and other cr ops). First, th e cropping patterns for each grid cell with irrigated land are modeled using a rule-based system, among other things considering data on total irrigate d area, long-term average temper ature and cropping intensity. In general, cropping intensity refers to the averag e number of crops that are consecutively grown within a year, and set to 1 for European countries . The cropping pattern desc ribes whether rice or other crops or both are irrigated and whether th ere are one or two cropping seasons. Then, in a second step, the start day of the growing season is determined, assuming a growing period of 150 days for all crops. The start date of a growing season within a year is ranked according to a temperature and precipitation criteria. After these tw o initial steps, the net irrigation requirement is computed for each day of the growing season si milar to the CROPWAT (Smith, 1992) approach:

     

− ⋅ = d mm P E k IR avail pot c net if k c E pot > P avail (6)

IR net

= 0 if k c E pot ≤ P avail
where:

IR net

= Net irrigation requirement [mm/d]

E pot = Potential evapotranspiration [mm/d]

P avail = Precipitation that is available to the crop [mm/d]

k c = Crop coefficient, depends on the grow ing stage of the crop [-] (Doorenbos and Kassam, 1979)
Equation (6) indicates that the ne t irrigation water intensities ar e calculated as the difference between crop-specific potential evapotranspiration and the precipitation available to the plant. The crop-specific potential evapotranspira tion is described by the product of k c and E pot , in which a daily potential evapotranspiration is comp uted according to the Priestley-Ta ylor formulation as a function of net radiation and temperature. Finally, gross ir rigation requirement is ca lculated by dividing the net irrigation requirement by the efficiency of irrigation water use, a value that depends on irrigation technology and mana gement (see Equation (7)).

     

= d mm eff IR IR

IR net gross (7)

where:

IR gross = Gross irrigation requirement [mm/d]European Outlook on Water Use Final Report 21

IR net

= Net irrigation requirement [mm/d]

eff IR = Irrigation field efficiency [-]
The irrigation field efficiencies vary regionally between 0.5 and 0.65 in the Eur ope-30 region. Here, higher efficiencies are estimated for southern count ries because these countries make use of water saving systems (e.g. drip systems in stead of sprinklers). With respec t to climate as a main driving force on the irrigation water requi rement, monthly temperature and precipitation values are taken into account on a 0.5° by 0.5° global grid (geogra phical longitude and latitude, respectively). Today’s climate is depicted by a 30-year time seri es (climate normal, 1961-90) of observed monthly data by New et al. (2000). To de rive appropriate future scenarios, today’s climate is scaled by applying changes projected by GCMs. Next to the climate input, the ra te of expansion of irrigated areas or change in area exploited for irrigation is an additional driving force in water use scenarios. As a validation of the global irrigation model, irri gated areas and gross irri gation requirements were compared with independent data of the year 200 0. Data regarding irrigati on water withdrawals are obtained from EUROSTAT or other national Statistical Offices. In most cases, model calculations reflect adequately published data as can be seen from Figure 13.

Irrigation water withdrawals

1 10 100 1000 10000 100000

1 10 100 1000 10000 100000 published values [mio. m3/year]simulated values [mio. m3/year] model efficiency = 0.97 1:1 line

Figure 13. Validation of the irrigation model: calculated ir rigation water withdrawals versus published data.

3.2.7 WaterGAP: Livestock Water Use The aim of this submodel is to compute the amount of water used by animals which is in most countries very small compared to domestic, industri al or irrigation water use. However, if irrigation water use is low the livestock water use may play a considerable role. We therefore distinguish between ten different varieties of livestock (Alcamo et al., 2003a). It is assumed that the water withdrawals for livestock are equal to their consumptive water use. In WaterGAP the water withdrawals for livestock are computed annually on a global grid (0.5° by 0.5°) by multiplying the number of animals per grid cell (GlobalARC, 1996) by the livestock-speci fic water use intensity [m3/(head

⋅ year)]. To quantify livestock-specific water use intensiti es, a wide range of estimates exist. For the WaterGAP livestock water use model, several literature sources were considered (Kirchgeßner, 1997; Mc Nitt, 1983; Jeroch, 1986; van der Leeden, 1990).European Outlook on Water Use Final Report 22


### 3.3 Improved Estimates Achieved in this Study The methodology used in this report represents a significant advance to the methodology used in previous studies to compute European-scale wate r use (UNEP, 2002; Henrichs et al., 2002; Alcamo et al., 2000): 1. The reliability of estimating domestic water us e has been improved by calibrating the model to newly available data on histori cal trends of domestic water us e on a country scale in Europe. Model calculations have been show n to fit very well to historical data in most countries (see Table 2 and Appendix A). 2. A newly available data base on power stations and their cooling characteristics (Vassolo and Döll, 2004) has been used for the first time, in order to greatly improve the estimation of future water use in the electricity sector. For the first ti me important structural changes in the type of power station cooling were taken into account in a large scale water scenario study. WaterGAP estimates compare very well w ith independent country scale estimates. (See Section 3.2.4).
3. Estimates of future water use in the manufact uring sector have been greatly improved over previous estimates by performing separate estimates of water use for each of 6 water-intensive industrial sectors. This is the first time that water use scenarios were systematically developed for manufacturing on the European scale. (See Section 3.2.5). 4. The reliablility of estimates of water use in Eu ropean agriculture has been tested by comparing WaterGAP calculations to data from several Eu ropean countries. Model estimates were found to closely agree with independent estimates. (See Section 3.2.6). Despite these improvements in methodology, many uncertainties remain in the procedure for calculating water use that should be kept in mind wh en interpreting and using scenario results. (See Chapter 7). These uncertainties should be addressed in follo w-up studies. (See Chapter 8).European Outlook on Water Use Final Report 23



## 4. ASSUMPTIONS OF THE BASELINE SCENARIO (LREM-E)

In this and the next chapter we describe the assumptions of the two scenarios developed in this study – the ‘baseline scenario’ (LREM-E) a nd the ‘climate policy scenario’ (SEP). The goal of the baseline scenario is to provide a reference scenario of future developments of water use (and availability) in Europe assuming that cu rrent environmental policies continue, but also supposing that specific policies are not implemented to curtail water use. Many of the assumptions in the baseline scenario are derived from th e Long Range Energy Modelling scenario project (LREM-E), commissioned by the Directorate-Ge neral for Energy and Transport (EU, 2003). The original LREM-E scenario was built as a benchmark for the assessment of future energy and transport options. A detailed analysis of the assumptions as well as the results for this scenario can be found in the ‘European Energy and Transport – Trends to 2030’ report (EU, 2003). The National Technical University of Athens (NTUA) was responsible for the de velopment of this outlook in the context of the LREM contract with the Director ate-General for Energy and Transport. The PRIMES Energy System Model was used to develop the scenarios.



### 4.1 The World of the Baseline Scenar io – A Qualitative Description The baseline scenario describes a world up to 2030 in which technological developments continue to be an important factor for economic growth and less attention is paid to ecological sustainability. In this world the expansion of the EU turns out to be a boom for the economies of most Europe-30 countries as trade flourishes be tween the old and new EU countries , and markets in these countries expand. Exports to other world re gions from Europe-30 also incr ease. Mobility of workers to booming industrial areas reduces unemployment and increases the consumer spending of workers. Following these and other factors, the economy in th e Europe-30 grows at a rate of 2.3% per year between 2000 and 2030 as compared to 1.5% pe r year in the 1990s. Economic growth is particularly strong in the ‘n ew’ (post 2004) and ‘candidate ’ (as of 2004) EU countries. The demographic transition continues in Europe-30, as population stabilizes in most countries and decreases in others. Overall, the populati on in these countries only grows by 24 million. In the domestic sector, higher overall incomes tend to cause much higher per capita water use in the new EU countries. This is manifested by, for exam ple, the installation of new washing machines, dishwashers, etc. However, in some of the richer countries domestic water use had already reached its highest level in the 1990s and continues its d ecline. But in the new EU countries, the building boom accompanying economic expansion in the first decades of this century leads to increasing water use in households. This increase is slowed by an increasing efficiency of appliances as described in Section 4.2.9. One of the pillars of the new economic expa nsion between 2000 and 2030 is increased production of manufactured products for expanding domestic and export markets. Since the output also increases of water-intensive industries (paper an d pulp, chemicals, food products), water use in the manufacturing sector grows. Additionally, th e higher standard of living and increased manufacturing output requires more electricity production at all pow er facilities, including thermal power stations. The increased elec tricity generation of thermal power stations tends to increase water used in the electricity sector. However, there is a very important offsetting tendency. – While electricity generation increases, ma ny older power stations are also phased out and all new power stations in Europe have tower cooling which dras tically lowers water withdrawals compared to the older stations that had once-through cooling. As a result almost al l countries have declining water use in the electricity producti on sector in the 2010s and 2020s. The economic expansion also affects the agricu ltural sector. Increasing income raises food consumption and this leads to a greater demand for food grown on irrigate d land. This largerEuropean Outlook on Water Use Final Report 24

domestic food demand, combined with growing food e xports from Europe lead to a vast expansion of irrigated cropland in many Europe-30 countries. Higher overall industrial activity is accompanied by an accelera tion of investments in new technologies and improved management of businesses, industrial processes a nd agricultural activity. A spinoff of this ‘technological im provement’ is improved efficiency of water use in all sectors. For example, fewer raw materials are used for manuf acturing chemicals and this is accompanied by a reduction in water requirements for chemical manu facturing processes. A nother example is that water-intensive traditional fl ood irrigation is replaced on many farms by water-saving sprinkler irrigation. As a result of these chan ges, water use becomes more efficien t at a faster rate than in the last decades of the 20 th century. While economic activity becomes very lively, many climate and environmental policies practically die-out. For example, the hard-fought-for Kyoto Protocol is abandoned by nearly all of its signatories so that emissions of greenhouse gases incr ease even faster than anticipated back in the 1990s. However, not all air pollution policies are ab andoned in Europe so some renewable energy continues to penetrate the energy market as a ta ctic for controlling local and regional air pollution. Some water conservation policies are also continued, especially in countries where domestic water use was already levelling off or declining in the 1990s. However, no new large water conservation initiatives were launched in the first decades of the 21 st century. Continuing climate change leads to a somewhat drie r climate in Southern Europe and wetter climate over the northern Europe-30 countries. Mean annua l temperature increases on average by 1 degree Celsius between 2000 and 2030. These changes lead to a small increase in water requirements for irrigated farming in Spain and Greece. The effect of climate is compensated somewhat by the continuing improvements in the efficiency of irrigation water use, noted above.


### 4.2 Driving Force Assumptions

4.2.1 Population Assumed population is based on EUROSTAT and UN-HABITAT da ta. The trends in population are driven by on-going economic growth. Table 3 shows the populatio n levels and growth rates of the Europe-30 countries, a ggregated into regions.
Table 3. Population trends in the Europe- 30 region, 1990 to 2030. Source: EUROSTAT, Global Urban Observatory and Statistics Unit of UN-HABITAT, PRIMES. Re gions are defined in Table 1.

Inhabitants [million] Annual growth rate [%]

1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30 Northern Europe 203.16 211.50 216.08 218.76 219.51 0.40 0.21 0.12 0.03 0.12 Southern Europe 173.80 178.85 183.56 183.68 181.68 0.29 0.26 0.01 -0.11 0.05
New EU Member States 75.12 74.73 73.40 71.67 69.14 -0.05 -0.18 -0.24 -0.36 -0.26
EU Candidate States 88.13 98.07 105.18 111.45 117.06 1.07 0.70 0.58 0.49 0.59 Europe -30 540.20 563.14 578.22 585.56 587.39 0.42 0.26 0.13 0.03 0.14

A further increase of the Europe-30 population by some 24 million people is projected between 2000 and 2030. However, there are significant differen ces in the growing rates and contrary trendsEuropean Outlook on Water Use Final Report 25

occur among the different regions. After 2000 the Nort hern Europe population continues to increase but with a declining growth rate. Beyond 2020 the population in Northern Europe is assumed to grow by only 0.03% per year and to reach 219 million in 2030. In the Southern Europe countries an increase in population by more than 0.25% per year is assume d up to 2010. Betw een 2010 and 2020 the development in population almost stagnates and declines therea fter by 0.11% per year. The New EU Member States face a considerable reduc tion in population. The population decreases by 5.6 million inhabitants between 2000 and 2030. A furthe r increase of the EU Candidate States’ population by some 19 million people is projected between 2000 and 20 30, with a maximum rate of 0.70% per year between 2000 and 2010.

4.2.2 Economic growth (GDP/cap

⋅ year) The economic growth assumptions are based on the macroeconomic and sector al projections from different sources, including the European Co mmission’s Directorate-Ge neral for Economic and Financial Affairs (Economic and Financial Affa irs DG), Member States’ stability programs and long-term projections, macroeconomic forecasts from WEFA (now integrated into DRI-WEFA 6 ), and results from the GEM-E3 7 model. The presented economic outlook uses the same underlying assumptions for the New EU Member States as for the pre-2004 EU states. Economic growth assumptions take into account the recent European economic slow down and the expected long-term positive economic climate. The projected outlook of per capita GDP for the Europe-30 is given in Table 4.
Table 4. Per capita GDP in the Europe-30 re gion, 1990 to 2030. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in Table 1.

GDP per cap [Euro2000] annual growth rate [%]

1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30 Northern Europe 22308 26354 32425 39863 48815 1.68 2.09 2.09 2.05 2.08 Southern Europe 16275 19169 24058 30636 38894 1.65 2.30 2.45 2.42 2.39
New EU Member States 4434 5277 7819 11455 15916 1.76 4.01 3.89 3.34 3.75
EU Candidate States 2187 2391 3214 5200 7838 0.90 3.00 4.93 4.19 4.04 Europe -30 14599 17102 21332 26894 33707 1.60 2.23 2.34 2.28 2.29

In the Europe-30 region, GDP per capita increases at a rate of 2.3% per year on average, thereby doubling between 2000 and 2030. In the Northern Eur ope countries, the GDP per capita increases continuously by almost 2.1% per year, while the economy of Southern Europe shows an average growth rate of 2.4% per year. Mu ch faster growth is experienced in the New EU Member States (3.8%) and the EU Candidate States (4%). The acceleration of economic growth in these two European regions results from the successful integr ation of these count ries into the EU. Nevertheless per capita income in these regions in 2030 remains c onsiderably lower than in other EU regions (Table 4).

6 DRI-WEFA. DRI-WEFA Mode l: Economic Dynamic Equilibrium Growth Model. A Global Insight Company.

7 GEM-E3. General Equilibrium Model fo r Energy-Economy-Environment Interactions. National Technical University of Athens (NTUA).European Outlook on Water Use Final Report 26

4.2.3 Structural change in the domestic sector The concept of structural changes in the domestic sector is explained in Section 3.2.3. Basically we assume that water intensity (per capita water use) fi rst rises as income increa ses, then stabilizes and in some countries drops. This relationship is c onfirmed by historical da ta from most European countries. In Section 3.2.3 we explained that historical data were used to derive a separate sigmoid curve for each European country. This curve depi cts the change in wate r intensity as income changes in a particular country. (See Figure 6 an d Figure 7). For the baseline scenario we use the sigmoid curves to estimate future water intensitie s corresponding to future income in a particular country. In the case of the Czech Repub lic, Estonia, Hungary, Latvia, L ithuania, Poland, the Slovak Republic, and Turkey, we assume for the baseline scenario that the domestic water use intensities follow the upper curve in Figure 8. Therefore, we assume that water intensity in the domestic sector (per capita water use) converges wi th the pan-European average in 2030.

4.2.4 Thermal electricity production
The amount of freshwater used for cooling in the electricity production sector is mainly affected by the electricity generated by thermal power plants. Since thermal power plants may be fossil-fueled or nuclear-fueled both thermal el ectricity production and nuclear electricity production are taken into account. As noted above, the baseline scenario assumes a continuation of current trends except in climate policy and other envi ronmental areas. Regarding clim ate policy, it assumes that the Kyoto Protocol will not be implemented and th at greenhouse gas emissions will not otherwise be controlled. Thermal electricity production increases by 54% betw een 2000 and 2030 in the Europe30 countries. During the same period thermal el ectricity production increases by 36% in the Northern Europe countries, by 55 % in the Southern Europe count ries, and by 58% in the New EU Member States, and almost triples (177%) in the EU Candidate States. The significant growth in thermal electricity production in the New EU Me mber States and the EU Candidate States is attributed to higher economic activity over the scenar io period, leading to in creased use of electrical appliances in households and service industries (EU, 2003).
Table 5. Projected thermal electri city production for the baseline (LREM-E) scenario. Source: EUROSTAT, PRIMES. Regions are defined in Table 1.

Thermal electricity production [TWh]* Annual growth rate [%]

1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30

N orthern Europe 1183 1297 1437 1615 1771 0.93 1.03 1.18 0.92 1.04 Southern Europe 722 963 1156 1341 1492 2.92 1.85 1.50 1.07 1.47

N ew EU Member States 304 308 362 452 488 0.14 1.62 2.24 0.78 1.55
EU Candidate States 121 169 213 306 469 3.40 2.33 3.69 4.36 3.46 Europe -30 2329 2737 3168 3714 4220 1.63 1.47 1.60 1.28 1.45

* Thermal electricity production (including biomass) and nuclear electricity production.

4.2.5 Structural change in the el ectricity production sector The rate of water withdrawals per unit electricity generated is much higher in power stations using traditional once-through cooling than in the more contemporary tower cooled plants. Hence the structural change by which once-through cooling is replaced by tower-coo ling is an importantEuropean Outlook on Water Use Final Report 27

driver of water use. Consistent with EU (2001) we assume that all new power stations in the baseline scenario will be tower-cooled. Hence, the rate of penetration of tower-cooling in the baseline scenario is just a matter of the current ag e of power stations – the shorter the lifetime, the faster the power stations will be replaced and the faster the penetration of tower cooling. In the baseline scenario we assume all power stations have a lifetime of 40 years (Markewitz and Vögele, 2001).

4.2.6 Manufacturing output (gross value added) The gross value added (GVA) of industrial producti on is a major driving fo rce of water use in manufacturing. The assumptions for the economic gr owth of the industry sector for the EU15 countries reflect the trend of st ructural changes in developed ec onomies as well as aspects of international trade and dema terialization (EU, 2003). To give an overview of the projected GVA, the va lues for Northern Europe countries are given in Table 6. The GVA projection for the other three European regions are presen ted in Appendix C. Overall, the development of the GVA corresponds closely to the projected development of the per capita GDP. Table 6. Gross value added separated by sector s in the Northern Europe economy. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in Table 1.

GVA [10 9 Euro 2000] Annual growth rate [%]

1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Iron and steel 36 30 29 29 29 -1.83 -0.24 0.13 0.01 -0.03
Non-ferrous metals 15 17 24 31 39 1.42 3.39 2.64 2.24 2.75
Chemicals 106 133 171 218 271 2.28 2.55 2.49 2.19 2.41
Non-metallic minerals 39 40 46 54 63 0.14 1.42 1.77 1.51 1.57 Paper and pulp 86 108 135 166 199 2.31 2.24 2.13 1.82 2.06 Food, drink, tobacco 104 128 157 195 237 2.12 2.05 2.21 1.99 2.08 Engineering 442 507 652 845 1083 1.39 2.55 2.62 2.51 2.56
Textiles 42 32 32 34 37 -2.74 -0.07 0.70 0.64 0.43
Other industries 87 98 119 144 173 1.17 1.96 1.94 1.87 1.92 Total industry 957 1092 1364 1717 2131 1.33 2.24 2.33 2.18 2.25

The GVA is given for nine sectors (see Table 6). The following pa ragraphs describe changes in particular manufacturing sectors.
While the iron and steel sector experienced an economic recession between 1990 and 2010 in the Northern Europe region, the GVA shows a net increase between 2000 and 2030. By 2030, the iron and steel sector accounts for only 1.3% of th e total Europe-30 GVA compared to 2.7% in 2000.
The non-ferrous metals sector shows the highest growth rates between 2000 and 2030, with an average growth rate of 2.75% per year. However, this sector accounts only for 1.8% of the total GVA in 2030.
The chemical sector is a one of the main drivers of incr eased GVA in the manufacturing sector. In the Northern Europe countries, the chemical industr y is one of the fastest growing industrial sectorsEuropean Outlook on Water Use Final Report 28

with an annual increase of 2.4% between 2000 a nd 2030. By 2030, the chemical industry continues to account for 12% of the tota l manufacturing GVA as in 2000.
The non-metallic minerals sector accounts for a relatively small shar e of the total Northern Europe manufacturing output (3.6% in 2000 and 3.0% in 2030). This sector is projected to expand at rates well above those observed in the last d ecade (1.6% per year between 2000 and 2030).
The paper and pulp sector is projected to have a growth rate of 2.1% per year for the scenario period 2000 to 2030. By 2030, the sector accounts fo r 9.3% of industrial economic activity in the EU which remains almost steady compared to 9.8% in 2000.
The food, drink, and tobacco sector is amongst the larg est industrial activities in the Northern Europe countries, accounting for 11.7% of GVA in 2000 and 11.1% in 2030. For this sector the GVA is projected to grow by 2.1% per year between 2000 and 2030.
The engineering sector shows a continuous increase in GVA at an average rate of 2.6% per year between 2000 and 2030. This sector is the main industrial sector in the Northern Europe region and accounts for 50% of the total GVA in 2030 (46% in 2000). In the Northern Europe countries, the textile sector accounts for 2.9% of the total GVA in 2000, but this share declines to 1.7% in 2030. The decline is due to a growth rate of only 0.4% per year between 2000 and 2030. Slow growth, in part, is due to the re-location of this labor-intensive activity outside the region. (EU, 2003).
Other industries are those sectors which are not explici tly listed in Table 6. These industries are expected to expand throughout the scenario period at an average rate of 1.9% per year between 2000 and 2030. These miscellaneous industries account for 9% of the regional GVA in 2000 and 8% in 2030.

4.2.7 Irrigated area The main driving force of changes in water withdraw als in the agricultural sector is the change in extent of irrigated area. The larger this area, the more water needed for irrigation, and the larger the water use in the agricultural sector. Despite the importance of the exte nt of irrigated land, detailed Eur opean-specific projections are not available. Here, we use a variety of sources fo r deriving assumptions of future irrigated land. Two major variables concerni ng irrigated area must be specified. The first is the area equipped for irrigation which is the area which is set up for irrigati on but not necessarily ir rigated. The second important variable is the percentage of equipped ar ea exploited for irrigation. This is important because a variety of sources confir m that in many countries a large percentage of the equipped area is not exploited for irrigation, for example, because adequate rain sometimes occurs during the growing season, or because it is uneconomic to irrigate. (Baldock, 2000; Penov, 2001; Hristova, 2001; Siemianowski, 2001; Petkov, 2001; Leonte, 2001; ICID, 2004; DSI, 1991; Bazzani et al., 2003; Manos, 2003; Morris, 2003; FAO, 2002). For example, these references indicate that only about 5.5% of Romania’s equippe d irrigated area was actually us ed for irrigation in 2000. The current percentage of area exploited for irrigation is given in Table 7. For specifying the future change in extent of exploited irrigated la nd we adapt assu mptions from a global study presented in th e ‘Global Environmen t Outlook 3 (GEO-3)’ report (UNEP, 2002). Specifically, we have adapted the ‘Market Forces ’ scenario which has basic assumptions that resemble the baseline scenario in this report (Table 8). The projection in Table 8 is fairly consistent with estimates for some other Eu ropean countries contained in Ba ldock et al. (2000) and Magat and Vallée (2000). For example, the ch ange in irrigated area is of th e same direction (increasing or decreasing) for two-thirds of the countri es considered by a ll three references.European Outlook on Water Use Final Report 29

Table 7. ‘Area equipped for irriga tion’ and the ‘percentage of equi pped area exploited for irrigation’ (base year 2000). Sources: (Baldock, 2000; Pe nov, 2001; Hristova, 2001; Siemianowski, 2001; Petkov, 2001; Leonte, 2001; ICID, 2004; DSI, 1991; Bazzani et al., 2003; Manos, 2003; Morris, 2003; FAO, 2002).

Country Area equipped for irrigation [km2] Percentage of equipped area exploited for irrigation in 2000 Austria 580 78 Belgium 400 11 Bulgaria 8000 5 Cyprus 397 53 Czech Republic 1412 26 Denmark 4604 15 Estonia 40 92 Finland 638 47
France 26337 37 Germany 6262 23 Greece 14500 70 Hungary 2100 42 Ireland — 0 Italy 38513 76 Latvia 171 100 Lithuania 136 100 Luxembourg 0.037 100 Malta 20 61 The Netherlands 4983 59
N orway 1240 100 Poland 1000 89 Portugal 7920 82 Romania 26700 6 Slovak Republic 1800 20 Slovenia 30 83 Spain 37000 59 Sweden 1188 100 Switzerland 172 100 Turkey 45000 60 United Kingdom 2674 70European Outlook on Water Use Final Report 30

Table 8. Baseline (LREM-E) scenario assumptions fo r the change in extent of irrigated land and change in irrigation water use efficiency.

Country % change in extent of irrigated area (2030 relative to 2000)* Improvement in irrigation water use efficiency [%/year] Austria 0.0 0.5 Belgium 0.0 0.5 Bulgaria +20.0 0.4 Cyprus +20.0 0.4 Czech Republic 0.0 0.5 Denmark 0.0 0.5 Estonia 0.0 0.4 Finland 0.0 0.5
France +27.0 0.5 Germany 0.0 0.5 Greece +20.0 0.4 Hungary +20.0 0.4 Ireland — — Italy +27.0 0.5 Latvia 0.0 0.5 Lithuania 0.0 0.5 Luxembourg 0.0 0.5 Malta +27.0 0.5 The Netherlands 0.0 0.5
N orway 0.0 0.5 Poland 0.0 0.5 Portugal +27.0 0.5 Romania +20.0 0.4 Slovak Republic 0.0 0.5 Slovenia 0.0 0.5 Spain +27.0 0.5 Sweden 0.0 0.5 Switzerland 0.0 0.5 Turkey +20.0 0.4 United Kingdom 0.0 0.5

* The change in extent of irrigated area can be achieved either by an expansion of area exploited for irrigation or by the expansion of area equipped for i rrigation (if the area exploited for irrigation will be larger than 100%). Both attain the goal of an increase in irrigated land.

4.2.8 Livestock density The number of livestock in a particular area drives the livestock water use in that area. For the baseline scenario, national projections for 2000 to 2030 da ta were provided by IIASA. The projection does not include the effects of the ‘Common Agricultural Policy’ (CAP 8 ) reform and was developed with the use of modeling results from the Directorate-General for Agriculture (EU, 2002), future projections given by Bruinsma (2003) and available national projections. The modeled

8 CAP reform. The reform will completely change the way the EU supports its farm sector. For example, in future, the vast majority of subsidies will be paid independently from the volume of production.European Outlook on Water Use Final Report 31

future projections are also based on historic al data reported by the United Nations Food and Agriculture Organization (FAO, 20 00) and the International Fertilizer Industry Association (IFA, 1998). In general, on the one hand, the future projecti ons assume a decrease in the number of dairy (-15%) and non-diary cattles (-21%) in the Eur ope-30 region between 2000 and 2030. On the other hand, an increase in the number of poultry (16%) and swines (12%) is estimated for the same time period. The number of sheep and goats is project ed to increase (12%) in the New EU Member States but decreases in No rthern and Souterhn Europe.

4.2.9 Technological change – Improve ments in water use efficiency Also important for determining future water are the future rates of technologica l change that lead to technological improvements and an increase in water use efficiency. Continuous improvements in technology make water-using applian ces more efficient and hence, contribute to reductions in water

use. While structural changes can lead to either, an increase or a decrease of water use intensity, technological changes are assumed to result on ly in a reduction in water use (See Figure 9). Technological improvements are included in calcula tions of water use by specifying the rate at which new water using devices beco me more efficient over time. For every scenario, this rate of efficiency improvement (technological change) is specified for every sector (domestic, electricity, manufacturing, and ag riculture) and region.
For the domestic sector of Northern and Southern Europe, t echnological changes continue at 1% per year over the entire scenario period. In the New EU Memb er States, a highe r rate (1.5% per year) is assumed for the decade 2000 to 2010, reflect ing the acceleration of economic growth during this decade. After this time period, when economi c growth slows down, the rate of efficiency declines to 1% per year and remains at this rate until 2030. The estimation of the future water use efficiency ra tes are based on availabl e data about historical improvements. For the domestic sector, information on efficiency rates for the last twenty years are available for Germany (Roth, 1995; Möhle and Masanne k, 1990). According to this reference, a rate of efficiency improvement of 2% per year betw een 1980 and 2000 is used fo r the domestic sector and applied to Northern and Southern Europe. To take into account a lower development in technical improvement of water savi ng appliances, a smaller rate of 1% per year is used for the New EU Member States as well as for the EU Ca ndidate States for the last twenty years.
For the electricity production sector and the manufacturing sector , improvements in water use efficiency are assumed to continue at about 1% per year, regardless of the region. For both the electricity and the manufacturing sector, former technological changes have been calculated based on data available for Germany (Vattenfall Eur ope, 2002; DESTATIS). Detailed information is given in Appendix B.
For the agricultural sector , improvements in the water use efficiency continue to reduce water withdrawals depending on the country by 0.4% to 0.5% per year up to 2030. This takes into account that water-intensive irrigation systems are re placed by more water-savi ng irrigation systems. Estimates of future water use efficiency rates for irrigation are derived from the GEO-3 ‘Market Forces’ scenario and specifie d per country (see Table 8).

4.2.10 Climate change Estimates of future climate change depend on many factors including the trend of greenhouse gas (GHG) emissions and the climate model used fo r calculating climate ch ange. Climate change projections used in this study we re calculated by the IMAGE 2.2 m odel in connection with earlier studies (van Vuuren et al., 2003).European Outlook on Water Use Final Report 32

Figure 14 shows the computed increase in greenhouse gas concentration in the atmosphere for the baseline scenario (LREM-E) and for the climate policy scenario (SEP). Th e concentration of the greenhouse gases increases up to nearly 1000 ppm CO 2 equivalents under the baseline scenario (‘CO 2 equivalents’ takes into account all greenhouse gases addressed by the Kyoto Protocol), and stabilizes at about 550 ppm under th e climate policy scenario. Howeve r, the differences between the scenarios are small up to 2030, the time horizon of this scenario study.

Total Greenhouse gas concentration

0 100 200 300 400 500 600 700 800 900 1000

2000 2020 2040 2060 2080 2100concentration (ppm) LREM-E SEP

Figure 14. Atmospheric GHG concentration (CO 2 equivalents) for the baseline (LREM-E, upper line) and the climate policy (SEP, lower line) scenarios. Source: EEA (2004).
With respect to climate we focus our analysis on altogether 7 time slices: Today’s climate (climate normal), future climate representatives for the years 2005 up to 2030 in 5-year intervals. For the WaterGAP model, future climate data (temperatu re and precipitation) are derived from the IMAGE 2.2 model in combination with results from the general circulation mode l (GCM) ‘HadCM2’ and the observed time series 1961-90 (New et al., 2000). For temperature, the observed time series are scaled by adding the respective difference between the future (IMAGE 2.2 values) and present-day temperature (HadCM2 values). For precipitation, observed precipitation time series are scaled by multiplication with the respective ratio between fu ture and present-day precipitation. An exception to this rule occurs when present-day precipita tion is close to zero (< 1mm); in this case the respective value is added. Following this method, mont hly values for 30-year climate time series are constructed for each time slice.European Outlook on Water Use Final Report 33

Figure 15. Differences in long-term average annual temperature (top) and percentage change in long-term average precipitation (bottom) as calcu lated for the baseline (LREM-E) scenario; 2030 projections compared to today’s level.
The map on the top of Figure 15 shows the increas e in temperature calculated for the baseline (LREM-E) scenario for the year 2030. The differences compared to today’s level vary between 0.53°C to 1.43°C. In most parts of Europe the av erage annual temperatur e will increase between 1°C and 1.25°C in 2030. Temperatur e increases of more than 1.25°C occur in Southern Spain and Central Europe as a band over the Alps up to Hungary and parts of Romania. The map on the bottom illustrates the changes in long-term average precipitation compared to today’s level for the baseline (L REM-E) scenario for 2030. The ch anges vary between -18.8% to 15.5% in the LREM-E scenario. The distribution of precipitation indicates a wetter climate in Northern Europe (> 5%) and a drier climate (< -5%) in the Southern parts of Europe, especially in Spain, Sicily, Greece, Romania, Bulgaria, and Turkey. In the Western and mid European countries only slight changes (+/- 5%) in aver age annual precipitation are computed.European Outlook on Water Use Final Report 34 

## 5. ASSUMPTIONS OF THE CLIMATE POLICY SCENARIO ( SEP)

The goal of the climate policy scenar io (SEP) is to investigate the im pact of drastic climate policies on water use (and availability) in Europe. The climate policy scenario is derived from the ‘sustainability emission pathway’ scenario (hence the abbreviation ‘SEP’) developed by the EEA’s European Topic Centre on Air and Climate Cha nge (ETC/ACC, 2004). The climate policy scenario assumes the same basic driving forces as the baseli ne scenario except that dastic climate policies are assumed (in terms of GHG emissions limits) which ha ve direct effects on th e fuel profile of the electricity sector and on the intensity of climate change.


### 5.1 The World of the Climate Policy S cenario – A Qualitative Description
This world resembles that of the baseline scenario in that the expansion of th e EU and integration of Europe has turned out to be a stimulus for succe ssful and sustained economic growth in Europe-30. The main difference is that decision makers implement strong policies to reduce greenhouse gas emissions. The emission reduction targets of these policies are much more rigorous than the Kyoto targets. Emissions are lowered mainly by reducing carbon dioxide emissions from combustion of fossil fuels in electricity production. This action has two e ffects. First, less overall electricity is needed as a result of successful energy conservation activities. This means that overall production of electricity at thermal power stations is lower here than in the baseline scenario, and this tends to reduce water use in the electrical sector. Second, much more elec tricity is produced by low or nocarbon fuels – natural gas, wind, solar and biomass. Producing electricity w ith wind or solar power has very low water requirements, and this also te nds to decrease overall water use in the electrical sector. Under this scenario, improvements in renewable energy technologies make it possible to produce electricity with renewable energy at only sli ghtly higher costs than current technologies and therefore the shift to renewabl e energy does not appreciably in crease the operating costs of manufacturing nor the household e xpenses of domestic consumers. However, since this is an environmentally-oriented scenario , society invests more heavily in improving technology so that greater efficiencies in energy, materials and water us e are achieved. As a resu lt, water use efficiency improves rather rapidly and tends to lower water use. The implementation of stronger clim ate policies in Europe-30 and else where in the world leads to a significant reduction in greenhouse ga s emissions, and this slows down the rate of climate change slightly as compared to the baseline scenario. However, the difference is not big because of the enormous inertia built into the global climate sy stem. Climate policies implemented in the period 2000 to 2030 might have their greatest effect on global climate only after 2030. Consequently, the impact of climate change on irrigation water use and on water stress in this scenario is nearly the same as in the baseline scenario.


### 5.2 Driving Force Assumptions

Socio-economic Assumptions for population, gross dome stic product per capita (GDP/cap

⋅ year), and gross value added of manufacturing are the same as for the baseline scenario.European Outlook on Water Use Final Report 35

Thermal electricity production The implementation of climate policies in this scen ario leads to a mix of fuels different from the baseline scenario. In particular renewable energies (solar, wind, biof uels) are introduced in order to reduce greenhouse gas emissions. Since much of th is new renewable energy capacity is non-thermal solar and wind energy, the total thermal electricity ge neration is lower in this scenario than in the baseline scenario. (Table 9, Table 10).
Table 9. Projected thermal electri city production for the climate policy (SEP) scenario. Source: EUROSTAT, PRIMES. Regions are defined in Table 1.

SEP [TWh]* Annual growth rate [%]

1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30 Northern Europe 1183 1297 1421 1510 1488 0.93 0.92 0.61 -0.15 0.46 Southern Europe 722 963 1143 1302 1404 2.92 1.73 1.31 0.75 1.27
New EU Member States 304 308 358 441 474 0.14 1.52 2.10 0.72 1.45
EU Candidate States 121 169 207 287 434 3.40 2.05 3.30 4.22 3.19 Europe -30 2329 2737 3130 3540 3799 1.63 1.35 1.24 0.71 1.10

* Thermal electricity production (including biomass) and nuclear electricity production.

Thermal electricity production grows by 39% in the EU-30 countries between 2000 and 2030, and by 15% in Northern Europe, by 46 % in Southern Europe, by 54% in the New EU Member States, and will more than double (157%) in the EU Candidate States. Table 10 below shows a comparison between the th ermal electricity productions expected for the climate policy (SEP) and the baseline scenar ios (LREM-E) between 2000 and 2030. Although the thermal electricity production declines in all th e regions, the largest reduction occurs in the Northern Europe countries (-16%). In Southern Europe the genera tion of electricity decreases by 6%, in the New EU Member States by 3%, and in the EU Candidate States by 7% between 2000 and 2030.
Table 10. Difference in thermal electricity produc tion for the baseline (LREM-E) and climate policy (SEP) scenarios. Source: EUROSTAT, PR IMES. Regions are defined in Table 1.

LREM-E [TWh]* SEP [TWh]* Difference between SEP and LREM-E [%]

2000 2010 2020 2030 2010 2020 2030 2010 2020 2030

N orthern Europe 1297 1437 1615 1771 1421 1510 1488 -1.08 -6.52 -15.98 Southern Europe 963 1156 1341 1492 1143 1302 1404 -1.15 -2.93 -5.91

N ew EU Member States 308 362 452 488 358 441 474 -1.04 -2.36 -2.92
EU Candidate States 169 213 306 469 207 287 434 -2.63 -6.20 -7.47 Europe-30 2737 3168 3714 4220 3130 3540 3799 -1.21 -4.69 -9.96

* Thermal electricity production (including biomass) and nuclear electricity production.European Outlook on Water Use Final Report 36

Irrigated area and livestock density The assumptions for irrigated area and livestock de nsity are the same as in the baseline scenario.

Technological change – Improveme nts in water use efficiency Because this is a more environmentally-oriented scenario, we assume that society invests more heavily in improving technology so th at greater efficiencies in en ergy, materials and water use can be achieved. Technological changes ar e assumed to improve water use e fficiency at a fa ster rate in some regions than in the baseline scenario. Technological changes for the domestic sector are assumed to reduce water use by about 1.5% per year over the entire time horizon in the New EU Member States. For the other regions (Northern a nd Southern Europe and EU Candidate States) the assumptions for the SEP scenario are th e same as for the baseline scenario. Assumptions for the technological development of wa ter-saving appliances for the electricity sector, manufacturing sector, and agri cultural sector are the same as for the baseline scenario.

Climate change Climate change estimates are derived from the same source as the baseline scenario. However greenhouse gas emissions in the climate policy scenario are substantially lower than in the baseline scenario. As we noted earlier, up to 2030 there is only a small difference between the scenarios. Figure 16 shows the change in long-term average temperature (top map) and precipitation (bottom map) for the climate policy scenario between the climate normal period (1961 to 1990) and climate normal periods representative for 2030. The temperature increases in the Europe-30 regi on vary between 0.54°C and 1.29°C. A temperature increase between 1°C and 1.25°C is computed in most parts of the Eu rope-30 region, larger differences only occur in Southern Spain. The changes in long-term aver age precipitation vary between –17.8% and 14.2%. with a wetter climate in Northern Europe (> 5%) and a drier clim ate (< -5%) in the sSouthern parts of Europe. In the Western and mid European countries only slight changes (+/- 5%) in the average annual precipitation are computed.European Outlook on Water Use Final Report 37

Figure 16. Differences in long-term average annual temperature (top) and percentage change in long-term average precipitation (bottom) as calcula ted for the climate policy (SEP) scenarios; 2030 projections compared to today’s level.European Outlook on Water Use Final Report 38

Figure 17 presents the differenc e in long-term average annua l temperature (top map) and precipitation (bottom map) between the baseline (LREM-E) and the climat e policy (SEP) scenario for the year 2030. The slightly higher atmospheri c concentrations of greenhouse gases in the baseline scenario results in some what larger climate changes. Ne vertheless, these differences are small. The temperature differences between the baseline and the climate policy scenario are at maximum 0.15°C. In the case of precipitation, the di stribution of the differences indicates a wetter climate in Northern Europe and a drier climat e in Southern Europe (see Section 4.2.10). Those regions with an increase in precipitation are wetter in the baseline scenario than in the climate policy scenario (green colours in right map). Sim ilarly, those regions with less precipitation in the future are drier in the baseline scenario than in th e climate policy scenario (red colour in right map). But the difference in average annual precipitati on between the LREM-E and SEP scenarios varies only from –7 mm to 8 mm per year.

Figure 17. Difference between the baseline (LRE M-E) and climate policy (SEP) scenarios. Differences in long-term average annual te mperature (top) and pr ecipitation (bottom).European Outlook on Water Use Final Report 39



## 6. SCENARIO RESULTS

The scenario input data described in the previous chapters were ta ken as input into the WaterGAP model to compute future water use, water availabi lity, and water stress in 5-year intervals until 2030. Since the focus of the study was on water use, we first give the quant itative results for the baseline scenario, discuss the results of the clim ate policy scenario, and compare our scenario results with other published European studies. Subse quently, we present quant itative results of our scenarios for water availability a nd water stress. At the end, we di scuss the policy relevance of our results with regard to the Eur opean Water Framework Directive.



### 6.1 Water Use Country-by-country results for water use are presente d in Appendix D. Here we present the scenario results aggregated into the four regions defined in Table 1. For most figures we only present results for the baseline scenario because of the small differences between baseline and climate policy scenario results. The following four sections descri bing the scenario results per region only describe the results of the baseline scenario; results of the climate policy scenario are discussed together for all four regions in the section ‘Comparing Water Use in the Baseli ne and Climate Policy Scenarios’.

Northern Europe The profile of water wit hdrawals in 2000 in Northern Europe re gion is dominated by water use in the electrical production sector (45%), followed by the domestic sector (32%), the manufacturing sector (20%) and agriculture sector (3%) (See Figure 18). Computed futu re projections between 2000 and 2030 are shown in Figure 19.

Water withdrawals by sector [%] in Northern Europe (2000)

3%

32%

20% 45%

Agriculture
Domestic Manufacturing Electricity

Figure 18. Profile of sector-specific water withdr awals in the Northern Europe in 2000. Sources: EUROSTAT and national Statistical Offices.European Outlook on Water Use Final Report 40

LREM-E: water use in Northern Europe

0 20000 40000 60000 80000 100000

2000 2005 2010 2015 2020 2025 2030Water withdrawals [mio. m3/yr]

Domestic Manufacturing Electricity Agriculture

Figure 19. Computed water withdrawals for the base line (LREM-E) scenario for Northern Europe.
Water withdrawals in Northern Europe have decreased steadily during the 1990s (EEA, 2003) and the baseline and climate policy scenarios show a continuation of this trend. In the domestic sector, water withdrawals stabilize and then slowly decline because per capita water use in households and businesses reaches its saturation point, a nd the efficiency of water use continues to improve (for example, municipal water distribution losses are reduced with new technology). The amount of water declines between 2000 and 2030 by 18% from 29045 million m3 to 23924 million m3. Manufacturing output in creases and this tends to increase wa ter use, but improving efficiency of water use in this sector tends to dampen the incr ease somewhat. A continuous increase in water use in the manufacturing industry of 30% between 2000 and 2030 is calculated. Water withdrawals from electricity production show the largest sector al changes. Water withdr awals sharply decrease as older power stations with once-through cool ing are replaced by new ones with tower cooling which requires much smaller water withdrawals. (S ee Figure 19). Therefore, in the electricity sector, the expected water uses fo r cooling will decrease by 73%. Agricultural water use in Northern Europe only constitutes a minor 3% of total water withdrawal in 2000. Due to the short time horizon covered by the scenarios, the effect on temperature and precipitation in 2030 is relatively sm all in Northern Europe. Because of slightly higher temperatures and precipitation, the amount of water withdrawal for irrigation declines by 11% between 2000 and 2030. Compared to other sectors (in particular elec tricity production), this however, only constitutes a relatively small overall change.

Southern Europe The profile of water withdrawals in Southern Europe is distinctly different from that of Northern Europe. Here agriculture domina tes water withdrawals (44 %), fo llowed by the electrical production sector (23%), the domestic sector (22%) and ma nufacturing (11%). (See Figure 20). In Figure 21 the computed water withdrawals per sector are pr esented for the future time slices between 2000 and 2030 in 5-year intervals.European Outlook on Water Use Final Report 41

Water withdrawals by sector [%] in Southern Europe (2000)

44%

22% 11% 23%

Agriculture
Domestic Manufacturing Electricity

Figure 20. Profile of sector-speci fic water withdrawals in Sout hern Europe in 2000. Sources: EUROSTAT and national Statistical Offices.

LREM-E: water use in Southern Europe

0 20000 40000 60000 80000 100000 120000 140000 160000

2000 2005 2010 2015 2020 2025 2030Water withdrawals [mio. m3/yr]

Domestic Manufacturing Electricity Agriculture

Figure 21. Computed water withdrawals for the base line (LREM-E) scenario for Southern Europe.
Changes in water use are similar to those in Nort hern Europe in that th e most dynamically-changing sector is electricity production where older plants are replaced, es pecially after 2020, and this leads to more plants with tower cooling (see Figure 21). The water withdrawals in the electricity production sector are 63% lower in 2030 th an in 2000 in the baseline scenario. Water withdrawals increase slight ly, but continuously, in the manu facturing sector by 24% between 2000 and 2030. In the domestic sector, water withdr awals increase slightly, and then stabilize for the same reasons as in Northern Europe. A variety of compensating change s go on in the agricultural sector. On the one hand, gross irrigation water requirements increase by 14% becau se of a somewhat warmer and drier climate. Irrigation water requirements also increase because the total area irrigated in this region increases by 27% between 2000 and 2030. On the other hand, th is region makes steady progress in improving the efficiency of irrigation water use. The net result of these changes is an increase in irrigation water withdrawals of 32% (includi ng the expansion of irrigated areas) in 2030 compared to 2000. If we keep the irrigated area cons tant, a net increase of 5% in irrigation wa ter withdrawals is computed for the year 2030 compared to 2000.European Outlook on Water Use Final Report 42

The decrease in total water withdrawals is smaller in Southern Europe than in Northern Europe because the electricity production sector does not account for as large a percentage of total withdrawals as it does in Northern Europe, and b ecause the decrease in the electricity sector is compensated by an increase in water w ithdrawals in the agricultural sector.

New EU Member States The profile of water withdrawal s in 2000 in the New EU Member States is different from the previous two regions. Electrical pr oduction is the largest water-using sector as in Northern Europe, but it claims a higher percentage of total withdraw als (61%) than in Northe rn Europe. The domestic water sector is in second place, as in the previous two regions, but has a smaller percentage of total withdrawals (22%). The manufacturing sector cl aims a slightly higher percentage than the agriculture sector (10% and 7 %). (See Figure 22). The copmuted future water withdrawals are shown in Figure 23 for the time horizon up to 2030.

Water withdrawals by sector [%] in the New EU Member States (2000)

7%
22%

10% 61% Agriculture Domestic Manufacturing Electricity

Figure 22. Profile of sect or-specific water withdr awals in the New EU Member States in 2000. Sources: EUROSTAT and nati onal Statistical Offices.

LREM-E: water use in the New EU Member States

0 5000 10000 15000 20000 25000

2000 2005 2010 2015 2020 2025 2030Water withdrawals [mio. m3/yr]

Domestic Manufacturing Electricity Agriculture

Figure 23. Computed water withdr awals for the baseline (LREM-E) scenario for the New EU Member States.
Two sectors are very dynamic in this region – the electrical production sector (as in the previous regions) and the domestic sector. As in Northern a nd Southern Europe, water withdrawals decline inEuropean Outlook on Water Use Final Report 43

the electrical production sector because of the replacement of power stations with once-through cooling with plants having tower cooling. The wa ter withdrawal used for cooling puposes in the electricity production is 75% lo wer in the baseline projection (2030) than in the year 2000.
Water withdrawals in the domestic sector stea dily increase up to 2025 as per capita water use converges with the higher water us e of Northern and Southern Eu rope by 2030 (see Sections 3.2.3 and 4.2.3, Figure 23). In the case of convergence, the domestic water wit hdrawals increase from 5025 million m3 to 8753 million m3 (+74%) between 2000 and 2030. As we explain in Sections 3.2.3 and 4.2.3, this assumption of convergence is very uncertain, and in Sec tion 7.2 we analyse the result of an alternativ e assumption, namely that per capita wate r use in this region remains at its current level. The increase in domestic water wi thdrawals is dampened somewhat by a continuous decrease in population which is the main driving for ce in this sector. Water withdrawals stabilize in the domestic sector by 2025 as the convergence to higher per capita water use is ba lanced by the decline in population growth. Water withdrawals strongly increase in the manufact uring sector as it does in other regions and almost doubles between 2000 and 2030. In the year 2000, 2236 million m3 are used by manufacturing industry whereas 4340 million m3 of freshwater will be used in 2030. The increase in water use is a result of the expa nsion of manufacturing production. Agricultural water use remains about the same b ecause of compensating changes in this sector. – Higher temperatures tend to increase water requir ements of irrigation, while increasing precipitation and improving water use efficiency tend to decrease these requirements. The temporal trend of total withdrawals is uneve n over the scenario peri od as water withdrawals strongly decline in the electrical pr oduction sector while they sharpl y increase and then stabilize in the domestic sector. The combination of these changes create a ‘wavy’ tendency for total withdrawals.

EU Candidate Countries The profile of water withdrawals in this region rese mbles that of the Southern region since they are in similar climate zones. The profile is domin ated by agriculture (60 %), followed by domestic sector (16%), the electrical production (15%), and the manufacturing (9%) sector. (See Figure 24). Figure 25 visualizes the calculated water withdr awals per sector for th e projected time period between 2000 and 2030.

Water withdrawals by sector [%] in the EU Candidate Countries (2000)

60% 16% 9% 15% Agriculture Domestic Manufacturing Electricity

Figure 24. Profile of s ectoral-specific water withdrawals in the EU Candidate States in 2000. Sources: EUROSTAT and nati onal Statistical Offices.European Outlook on Water Use Final Report 44

LREM-E: water use in the EU Candidate Countries

0 10000 20000 30000 40000 50000 60000 70000

2000 2005 2010 2015 2020 2025 2030Water withdrawals [mio. m3/yr]

Domestic Manufacturing Electricity Agriculture

Figure 25. Computed water withdrawals for the base line (LREM-E) scenario for the EU Candidate Countries.
Here, as in other regions, the biggest changes are occurring in the electricity production sector where withdrawals decrease for the same re asons as in the other regions (Figure 25). The manufacturing sector has the next biggest cha nges as withdrawals sharply increase because of expanded industrial production and more than doubles between 2000 and 2030. The total amount of water used in this sector of 4968 million m3 in the year 2000 will increase to 11143 million m3 in the year 2030.
Withdrawals in the domestic sector increase as higher incomes lead to higher per capita water use (Bulgaria and Romania). But also as per capita water use in Turkey converges with the higher water use of Northern and Southern Europe by 2030 and in Turkey, the population is projected to increase by 23.5 million inhabitants (+35%) between 2000 and 2030. Hence, in the case of convergence, the domestic water withdrawals increase from 9230 million m3 to 14728 million m3 (+60%) between 2000 and 2030. Water withdrawals in the agricu ltural sector have a small net increase (by 10% between 2000 and 2030) for the same combination of factors as in Southern Europe. Wate r withdrawals tend to increase because a drier and warmer climate in creases the per hectare water requirements of irrigation while the area of irrigation increa ses by 20% between 2000 and 2030. Withdrawals tend to decrease because of efficiency im provements in irrigation water use. Total water withdrawals sligh tly increase (by 19% in 2030 over 2000) as the decrease in withdrawals from electricity production is outweighed by the combined increases in the manufacturing and domestic sectors.

Comparing water use in the baseli ne and climate policy scenarios Climate policy, as represented in the climate polic y scenario, affects water use in two major ways. The first effect is obvious – th e lower greenhouse gase s in Europe and else where slow down the rate of climate change and lead to more moderate changes in prec ipitation and temperature. These more moderate climate changes lead to more m oderate changes in the am ount of irrigation water required.
How different is the climate between the baseline and climate change scenarios? Figure 17 shows that under the baseline scenario the temperatur e would be a few tenths of a degree warmerEuropean Outlook on Water Use Final Report 45

throughout Europe. The North would receive a few percent more milli meters of precipitation and the South a few percent less. That is, under the str onger climate change of the baseline scenario the North would become a bit wetter an d the South a bit drier. We expl ained earlier that the difference is not big because there is enormous inertia bui lt into the global climate system which means that that climate responds slowly to ch anges in greenhouse gas emissions. Figure 26 gives an overview of the amount of water us ed for irrigation in the base year (2000) and for the projected time horizon 2030 for both scenar ios. The water withdrawals are aggregated according to the four regions as listed in Table 1. The small differences in climate (between the baseline and the climate policy scenarios) lead to similarly small differences in water requirements of irrigation and in water withdrawals in the ag riculture sector. However, the differences between the baseline (LREM-E) and climate policy (SEP) scenarios are less than 1% within a region in 2030.

Water use for irrigation in 2000 and 2030

0 10000 20000 30000 40000 50000 60000 70000

Northern Europe Southern Europe New EU Member States EU Candidate Countries regionwater withdrawals [mio. m3/yr]

2000 LREM-E (2030) SEP (2030)

Figure 26. Computed water withdrawals for irriga tion in the base year 2000 and in 2030 for the baseline (LREM-E) and climate policy (SEP) scenarios.
Regarding the country scale, wa ter withdrawals for irrigation, fo r example, in Spain are 23106 million m 3 in 2030 under the baseline scenario, and slightly smaller 23007 million m 3 in the same year (-0.4%) under the climate policy scenario becau se Spain’s temperature does not increase quite as much and it does not become quite as dry as under the baseline scenario. These results, however, are highly uncertain because not al l possible impacts of climate cha nge on irrigation were evaluated (for example, the impacts of possible cha nges in wind velocity were not included).
The second and more noticeable effect of climate policies is that greenhouse emissions are reduced by replacing fossil fuels with renewable energy. Th e introduction of renewable energy implies that some thermal power stations will be replaced by wind generators and solar photovoltaic systems which use very small volumes of water both direc tly or indirectly. Consequently the amount of water used for electricity productio n by power plants is sm aller in the climate policy scenario than in the baseline scenario, and this reduces water w ithdrawals in the electrical production sector as shown in Figure 27. Hence, Europe-30 water w ithdrawals for power plants in 2030 under the climate policy scenario are 9% lower than under the baseline scenario. The decreases are 16% in Northern Europe, 5% in Southern Europe, 3% in the New EU Memb er States, and 7% in the EU Candidate Countries.European Outlook on Water Use Final Report 46

Water use for the electricity production in 2000 and 2030

0 5000 10000 15000 20000 25000 30000 35000 40000 45000

Northern Europe Southern Europe New EU Member States EU Candidate Countries regionwater withdrawals [mio. m3/yr]

2000 LREM-E (2030) SEP (2030)
Figure 27. Computed water withdrawals for the elec tricity production in the base year 2000 and in 2030 for the baseline (LREM-E) and climate policy (SEP) scenarios.

Comparing water use scenarios with other estimates In the framework of this study, the baseline (LREM-E) and clim ate policy (SEP) scenarios are compared to other scenarios of European water w ithdrawals. Since all of these scenarios were generated by the WaterGAP model, the differences in scenarios are due to differences in scenario assumptions. It should be noted that the baseline and climate policy scenarios are prescriptive as opposed to the others which are expl orative scenarios. Three different studies are taken into consideration: The ‘Global Environment Outlook 3’ (GEO-3) (UNEP, 2001), ‘An integrated Analysis of Changes in Water Stress in Europe’ (Henrichs et al., 2002), and the ‘Dia logue on Water and Climate’ (Kabat and van Schaik, 2002). Altogether, they describe nine possible futures for Europe (and the world). Since all of these studies look forward t o, at least, the year 2025, this time slice will be considered in the comparison. In the following text the studies and scenarios are briefly introduced.
Global Environment Outlook 3 (Scenarios 1 to 4 in Figure 28) is a study, which lo oks back thirty years and forward thirty years. A set of four scenarios was used to examine environmental and social goals. The thematic issues are analyzed from firs t the global level and then at the regional level, e.g. Europe. In GEO-3 a set of four scenarios has been developed: (1) ‘Mar ket First’ (2) ‘Policy First’, (3) ‘Security First’, and (4) ‘Sustainability First’. The Market First scenario assumes relatively low population growth for Europe, a strong economic growth rate, a relatively large expansion of irrigated area, and interm ediate rates of technol ogical improvement in the water sector. The Policy First scenario has similar assumptions to the Market First scenario except that irrigated areas expand more modestly and a high level of water-cons erving behavior is assumed. In the Security First scenario the population growth rate is higher than the first two scenarios and economic growth is lower. The Sustainability First scenario has a popul ation growth similar to the first two scenarios, an intermediate economic growth rate, a much hi gher use of sustainable en ergy, and a high level of water-saving behavior. An Integrated Analysis of C hanges in Water Stress in Europe (Scenario 5 in Figu re 28) presents an ‘integrated’ analysis of global change impacts on European river basins with regard to projected changes in water withdrawals and water availability. With the comb ination of both, changes in future water withdrawals and future water availab ility, pressure on European river basins was estimated. With the focus on three time slices, mode l calculations were done for 1995 (as base year), the 2020s, and the 2070s. Figure 28 s hows the ‘Baseline A’ scenario from this study (labeled Sce-European Outlook on Water Use Final Report 47

nario 5). This scenario has soci o-economic driving forces, largely consistent with the no-climate policy ‘IPCC-IS92a’ scenario of the Intergovernmental Panel on Climate Change (IPCC, 1992). Although the economic and demographic driving forces of this scenario were once considered ‘intermediate’, they are on the higher side of current scenarios. Dialogue on Water and Climate (Scenarios 6 to 9 in Figure 28) presents an integrated assessment of future water availability and water withdrawal s following the assumptions of the IPCC SRES scenarios A2 and B2. To take into account climate change, climate data from two different climate models were used (ECHAM4-OPYC3 of the Max Pl anck Institute for Meteorology and HadCM3 of the Hadley Center). Figure 28 shows results for the A2 scenario (6 and 7) using climate inputs from the Max Planck and Hadley models, respectively, and for the B2 scenario (8 and 9) also using inputs from the two climate models. The A2 scen ario has higher population growth and lower economic growth in Europe th an the B2 scenario. The B2 scenario assumes faster rates of improvement in water use efficiency.

Ratio of European water withdrawals in 2025 to 2000

LREM-E SEP 1

2

3 4 5

6 7

8 9

-60 -40 -20

0 20 40 60

study and scenariochange in total water withdrawals tobase year [%]

Figure 28. Comparison of water use scenarios. (See text for explanation of numbers).
We can observe the following from the comparison of different studies. The re sults in this report fall mid-way in the range of scenarios produced for the GEO-3 report of UNEP (Scenarios 1 to 4). The lower scenarios in the GEO-3 report compute a lower domestic water use because of assumed water-saving behavior, and lower industrial water use because of lower electricity production. The higher GEO-3 scenarios assume higher population a nd economic growth and less attention is given to water conservation. Results in this report also fall mid-way betwee n a set of scenarios developed by the Dialogue on Water and Climate (Scenarios 6 to 9). These scen arios are less extreme than the GEO-3 scenarios because they have less extreme assumpti ons for socio-economic driving forces. The lower scenarios in other studies (Scenarios 3, 4, 8, and 9) are caused by the assumption of water-saving behavior in the domestic sector. While th is is an important factor in this report, other factors are also important, for example the trans ition from once-through cooli ng to tower cooling in power stations.The baseline and climate policy scenarios in this report are much lower than the Baseline A scenario (Scenario 5). This is because the Baseline A scenario has much higher assumptions for population and economic growth. Also, data were not available to ch eck country-scale calculations of domestic water use in Europe. Therefore it is likel y that estimates of future domestic water use in the Baseline A scenario were mu ch higher than the present study.European Outlook on Water Use Final Report 48

To sum up, the scenarios presented in this report give intermediate estimates of future water use in Europe as compared to earlier studies. In addition to the comparison with other WaterGAP studies, we compar ed the results of the baseline and climate policy scenarios with forecasts obtained by Shiklomanov and Rodda (2003). To obtain future values of water withdr awals and water consumption for the time period up to 2025, Shiklomanov and Rodda (2003) considered the UN (1995) population development scenario as well as UN (1993) and International Mone tary Fund (IMF, 1994) trends fo r the GDP/cap. The growth in industrial water use was derived fo r the year 2025 from data rela tive to 1990 (Strzepek and Bowling, 1995). Data on irrigated areas based on info rmation given in Zonn and Nosenko (1981) and FAO (1995) and the extent of future irrigated ar eas was calculated for the European countries taking into account economic and population growth. Thes e data were used to ex trapolate future irrigated areas and future irrigation water withdrawals. As a result, the dynamics of water withdrawals and water consumption are given by sector an d by continent up to 2025. Based on these assumptions, Shiklomanov and Rodda (2003) calculate that , in Europe, total wate r withdrawal will continuously increase and will be 21% higher in 2025 compared to 1995. However, it should be noted that the main goal of th e present study is to evaluate the impact of climate change on the water withdrawal, which is not explicitly considered by Shiklomanov and Rodda (2003). Their results are base d on extrapolation of actual tren ds and are thus, not directly comparable to our results.


### 6.2 Water Availability and Water Stress

6.2.1 Water Availability We define water availability here as the total river discharge, wh ich is the combined surface runoff and groundwater recharge. Figure 29 shows the change in annual water availability in the baseline scenario.

Figure 29. Change in average annual water availabili ty for European river basins under the baseline (LREM-E) scenario compared to today’s level.

Under the baseline scenario wate r availability declines in part s of Southern and Southeastern Europe because of higher temperatures (causing higher evapotranspiration) and lower precipitation.European Outlook on Water Use Final Report 49

Water availability increases thr oughout the rest of Europe despit e increasing temperatures because precipitation also increases significantly. The incr ease in water availability ranges up to about 20 percent, although the magnitude of increase is very different in different parts of Europe. Under the climate policy scenario, the rate of climat e change is lower than in the baseline. We noted above that this slower rate of climate change will reduce the amount of water needed for irrigation in the South which also means that less availabl e water will be consumed. Temperatures are also not as high in parts of Southern and Southeastern Europe as they are under the baseline scenario, nor does precipitation decline as much. These differ ences should lead to a higher water availability in the climate policy scenario, but these are not observ ed because they are so small. Over the rest of Europe, water availability shoul d be somewhat lower than in the baseline scenario because temperature and precipitation are not as high. But this effect is barely visible in Figure 30. To sum up, differences in water use and climate between the climate policy and baseline scenarios do not cause significant differences in water availability.

Figure 30. Comparison of the baseli ne (LREM-E) and climate policy (SEP) scenarios. Differences in changes in average annual water ava ilability for European river basins.

6.2.2 Water Stress
Water stress is a measure of th e amount of pressure put on wate r resources and aquatic ecosystems by the users of these resources, including municipal ities, industries, power st ations and agricultural users (see, for example, Alcamo et al., 2000; Vorö smarty et al., 2000; Cosgrove and Rijsberman, 2000). To estimate stress we use a conventional indi cator, namely the ratio of withdrawals to availability (w.t.a.). Roughly speaking, the higher the w.t.a.-ratio, the more repeatedly the water in a basin is used and the more it is degraded or de pleted, therefore limiting further use of these water drainage resources to downstream users. This in dicator has the advantage of being transparent and computable for all river basins. Figure 31 (left map) depicts curren t water stress conditions for the different drainage basins of Europe. (Current conditions are defined as water use for the ye ar 2000, and water availability averaged over the climate normal period, 1961-90). Drainage basins are in the severe stress category where water use is very high per unit ar ea (Belgium, The Netherlands, Southeast England)European Outlook on Water Use Final Report 50

and in countries having arid climates and where water availability is low relative to water use (Greece, Southern Italy, Portugal, Spain, and Turkey). Figure 31 (right map) shows the same indicator for the baseline scenario in 2030. The Central European areas in the medium stress category in 2000 have disappeared because of lower water withdrawals and slightly wetter climate, while ar eas that earlier had low water stress in eastern Turkey, now have medium stress because of incr easing water use. Areas of central and western Turkey that were in the medium stress category in 2000 jump to the severe water stress category in 2030 because of both increasing water use and slightly decreasing water availability. Other areas of severe water stress in the sout h remain about the same because of compensating changes – both water use and water availability slightly decrease. Te pattern of water stress for the climate policy scenario is very close to that of the ba seline scenario, and is therefore not shown.

Figure 31. Water stress unde r current conditions and under the ba seline scenario. To p: Current conditions. Bottom: Base line scenario, 2030.European Outlook on Water Use Final Report 51



### 6.3 Contribution to the Wa ter Framework Directive

The Water Framework Directive The Water Framework Directive (WFD) entered in to force in October 200 0, breaking a new ground in the European water policy. The WFD establishe s a framework for the protection of all aquatic systems, including surface waters, groundwater, and coastal waters; land ecosystems depending on groundwater are also included. Its overall environmental objective is to achieve a good status for all water bodies in the Community by 2015 in terms of good ecological status and good chemical status (Article 4). Article 1 further details the specific purposes of the Directive: (a) To prevent further deterioration, protect a nd enhance the status of water resources; (b) To promote sustainable water use based on long-term protection of water resources; (c) To aim at enhancing protection and improvement of the aquatic environment through specific measures for the progressive reduction of disc harges, emissions and losses of priority substances and the cessation or phasi ng-out of discharges, emissions and losses of the priority hazardous substances; (d) To ensure the progressive reduc tion of pollution of groundwater a nd to prevent its further pollution; and (e) To contribute mitigating the effects of floods and droughts. In order to attain the Directive’s goals, all waters are to be characterized according to their biological, chemical, and hydro-morphological characteristics. Therefore, Member States shall ensure that a River Basin Management Plan is produced for ea ch river basin. But many of the river basins are international and this requires that all partners in a given river basin manage their waters together in close cooperation. As a consequenc e, administrative or political boundaries become less important in their respective countries comp ared to natural geog raphical and hydrological units. The concept of river basins brings together upstream and downstream interests.

Contribution of this study With this study we contribute to the overall objectiv e by calculating water stress in all river basins of the Europe-30 region, thereby addressing the question of good ecol ogical status of all European water bodies. So far, we do not address the question of good chemical status because the focus of this study is on the quantitative wa ter availability and use. In the following, we list the contribution of this study to the indivi dual purposes identified above. (a) To prevent further deterioration, protect and enhance the status of water resources . Water stress under current conditions and two different scenario assumptions has been calculated for all river basins within Europe-30 regions. Based on the future projections, countries can decide on their future pathways as to how to enhance the status of water resources. (b) T o promote sustainable water use based on long-term protection of water resources . Water use has been calculated under current conditions an d two different scenario assumptions for four distinct economic sectors per coun try and been attributed to all river basins within Europe-30 regions. Together with the water stress of the ri ver basin and the scenario information, sectorspecific policy measures can be designe d to promote sustainable water use. (c) To aim at enhancing protection and improvemen t of the aquatic environment through specific measures for the progressive reduction of disc harges, emissions and losses of priority substances and the cessation or phasing-out of disc harges, emissions and losses of the priority hazardous substances . The scenarios compute increases (or d ecreases) in water availability andEuropean Outlook on Water Use Final Report 52

potential sector-specific reductions (or increases) in water use. This again allows the countries to focus on the water use reduction potentials to formulate their policies in order to minimize discharges and thereby improvi ng the aquatic environment. (d) To ensure the progressive reduction of polluti on of groundwater and to prevent its further pollution . Although this study does not expl icitly address water quality, water use and discharge to surface water bodies and groundwater from the agricu ltural sector is calculated for current and alternative future climatic conditions. Based on th e extent of irrigated areas and amount of water withdrawn, the agricultural re turn flow (water withdrawal minus consumption) carries a specific pollution load of agrochemicals. The larg er the extent of irriga ted areas and the higher the amount of water withdrawal, the higher is the potential pollution load. Based on this information, countries can formulate their future agri cultural policies.European Outlook on Water Use Final Report 53



## 7. UNCERTAINTY AND SENSITIVITY OF RESULTS

The scenario approach used in this report addr esses uncertainty by showing different feasible pathways into the future based on different sets of input assumptions. But we also know intuitively that some input assumptions and some scenario path ways are more feasible, or more uncertain, than others. Here is a list of some of the factors determining water use th at are particularly uncertain. In principle, reducing the uncertainties of these factors will increase th e reliability of the scenarios and lead to better estimates of future water use.
Domestic – In most European countries the relationshi p between future income and water use seems to be well defined (see Table 2 and Appendix A). However, in a few countries undergoing a major economic transition (see Section 7.2) it is not possibl e to define a relationship between income and water use. For these countries more detailed studies are needed to identify the fact ors that help explain historical and future tre nds in water use. Another source of uncertainty in estimating future water use in the domestic sector is the future population of water users. Manufacturing – The water intensity of different industries (m 3 per gross value added) is a major uncertainty in most countries. But perhaps more impor tant is the water use of industries that are not now important but will become important over the ne xt 30 years. Key questions are, what will these industries be and how much water will they use? As an example, it is possible that the electronics industry will emerge as a major water user in Europe, although it is not considered now as important as the industries listed in Section 3.2.5 or 4.2.6. Electricity Production – Major uncertainties in this sector are the useful lifetime of power stations, the percentage of new power stations having towe r versus once-through c ooling, and their future geographic location. Also important is the uncerta inty of future thermal electricity production. Agriculture – Major unknowns in th e agriculture sector are the future extent of irrigated crops, the types of crops to be irrigated, and future climate. While the preceding factors are clearly uncertain, it is not necessarily true that they have a big impact on computed water use. To address this impact question we now present sensitivity analyses of selected driving forces. These analyses help identify the sensitivity of computed water outputs to key input assumptions.


### 7.1 Uncertainty of Domestic Water Use Trends
In Section 4.2.3 we noted that th e historical trend of per capita water use in the Czech Republic, Estonia, Hungary, Latvia, Lithua nia, Poland, the Slovak Republic, and Turkey shows an important break after the 1980s. This obviously has to do w ith the important economic transition going on in these countries. The break in this temporal trend also means that there is no clear relationship in these countries between per capita water use and GDP/cap. Hence historical data do not provide insight into the directio n of per capita water use under future changes in the economy. We must therefore assume a trend in future per capita water use a priori . We reported earlier that under the baseline and climate policy scenarios we assumed th at per capita water use in these countries would converge with the average value of the other Eu rope-30 countries by 2030. Here we compare this assumption with the assumption that pe r capita water use in these countries remains constant at its year 2000 level. This would correspo nd to the lower curve in Figure 8. As expected, computed domestic water use is very sensitive to this assumption. In Figure 32 we present results for the New EU Member States b ecause they are particularly affected by these uncertainties. Currently the per capita water use in the Czech Republic and other countries mentioned above are considerably below the EU aver age. Hence assuming that per capita water use remains at its current level (the middle bar in Fi gure 32) leads to much lower water use than theEuropean Outlook on Water Use Final Report 54

baseline scenario (left bar) which assumes that pe r capita water use will rise to the EU average in 2030 (See Section 4.2). In the New EU Member Stat es, the amout of water used in the domestic sector computed with the non-convergence approach is 48% lower than in the baseline scenario (including the convergence approach) in 2030 (15% in 2010). The conclusion of this analysis is that the trend of future per capita water use in many of the the New EU Member States is an important uncertainty that needs to be inves tigated in future water outlooks.

New EU Member States: water use in the domestic sector

0 2000 4000 6000 8000 10000

2010 2030Water withdrawals [mio. m3/yr]

baseline non-convergence low economic growth

Figure 32. Sensitivity analysis of the domestic sector , New EU Member States.


### 7.2 Sensitivity to Lowe r per Capita Income In this section we investigate the sensitivity of computed water use to assumptions of economic growth. The variant described here addresses the question of the im pact on economic growth on the water uses. Will a lower economic growth cause a more sustainable use of water in Europe? For this sensitivity analysis, we use a projection of income (GDP/cap

⋅ year) that has lower economic growth rates than assumed for the baseline and cl imate policy scenarios (Section 4.2). These projections were produced by the PROMETHEUS model (S ection 4.2). In the low economic growth variant, the annual average growth rate of GDP per capita in the Eu rope-30 region is approximately 1.7% between 2000 and 2030 as compared to the 2.3% per year of the baseline assumption. This decrease in economic growth rates is unequally di stributed between the f our Europe-30 regions. Greater reductions in economic growth rate ar e projected for Northern and Southern Europe whereas the economic growth rates decrease more moderately in the New EU Member States and EU Candidate Countries. (See Table 11).European Outlook on Water Use Final Report 55

Table 11. Per capita GDP in th e Europe-30 region under the low economic growth assumptions,1990 to 2030. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES, PROMETHEUS 9 . Regions are defined in Table 1.

GDP per cap. [Euro2000] Baseline and climate policy scenario Low economic growth variant Difference between low economic growth variant and baseline [%]

2000 2010 2020 2030 2010 2020 2030 2010 2020 2030

N orthern Europe 26354 32425 39863 48815 30256 35078 40347 -6.69 -12.00 -17.35 Southern Europe 19169 24058 30636 38894 22052 26417 31881 -8.34 -13.77 -18.03

N ew EU Member States 5277 7819 11455 15916 7470 10688 14531 -4.46 -6.70 -8.70
EU Candidate States 2391 3214 5200 7838 3278 5050 7360 1.98 -2.89 -6.10 Europe-30 17102 21332 26894 33707 19852 23661 28116 -6.94 -12.02 -16.59

The lower economic growth rates have a direct and indirect impact on the driv ing forces of different water-using sectors.

• Domestic sector: The new economic growth rates dire ctly affect per capita water use.

• Electricity production sector : Along with slower economic grow th, the production of electricity will also be lower than in the baseline a nd climate policy scenarios (See Appendix E).

• Manufacturing sector: Consistent with the lower economic growth rate is a lower industrial output in terms of gross va lue added (See Appendix E).
The difference between the baselin e scenario and the low economic growth variant is very small (Figure 32) because for most count ries within this region (New EU Member States) domestic water use is not computed on the approach described by the relationship between per capita water use and GDP/cap. However, the difference between the low economic growth variant and the baseline scenario is about 2% in 2010 and 2030, respectivel y. Figure 33 shows that water withdrawals are 8% lower under the low economic gr owth variant in the electricity production sector in 2030. In the same year, water withdrawals are 7% lower in the manufacturing sector under the low economic growth variant (Figure 34). Hence, calculations are not sensitive to the lower GDP/cap assumptions in Table 11. Results are only presented for the New EU Member States but were similar for other European regions. Apparently the combination of other factors (popul ation, transition to tower cooling, improvements in water use efficiency) is more important than income in determining water use in these sectors. On the other hand the economic grow th rates in the ‘low gr owth scenario’ were not extremely low compared to the baseline scenario. Hence, large differences in water use were not expected.

9 PROMETHEUS. A tool for the generation of Stochastic Information for Key Energy, Environment and Technology Variables. National Technical University of Athens (NTUA).European Outlook on Water Use Final Report 56

New EU Member States: water use in the electricity sector

0 2000 4000 6000 8000 10000 12000

2010 2030Water withdrawals [mio. m3/yr]

baseline low economic growth

Figure 33. Sensitivity analysis of the electricity production se ctor, New EU Member States.

EU Candidate Countries: water use in the manufacturing sector

0 2000 4000 6000 8000 10000 12000

2010 2030Water withdrawals [mio. m3/yr]

baseline low economic growth

Figure 34. Sensitivity analysis of the manufacturing sect or, New EU Member States.


### 7.3 Sensitivity to Uncertain Future Irrigated Area The main driving force of changes in water withdraw als in the agricultural sector is the change in extent of irrigated area. The larger this area, the more water needed for irrigation, and the larger the water use in the agricultural s ector. We pointed out in Section 4.2.7 that despite the importance of future projections of irrigated area, no detailed studies are available for Europe. Hence the projections used in this study are quite uncertain. Here we investigate the sensitivity of water use calculations to the uncertain extent of future irrigated area. We investigate two variants ar ound the baseline scenario (which is the ‘reference’ variant):
Lower variant: The ‘area equipped for irriga tion’ (the total area of irri gation) and ‘percentage of equipped area exploited for irrigation’ (the small part that is actua lly used for irrigation in some countries) both remain constant between 2000 and 2030. This gives lower estimates of water with-European Outlook on Water Use Final Report 57

drawals (in countries with irrigation) than the base line scenario because the baseline scenario assumes that the extent of area for irrigation grows in many countries up to 2030 (although the percentage of equipped area that is ac tually exploited remains constant). Higher variant: It is assumed that the area equipped for irrigation expa nds in several c ountries as in the baseline scenario, and that th e percentage of exploited area al so increases step-wise up to 100% from 2000 to 2030. This gives higher water withdrawals (in countries wi th irrigation) than the baseline scenario because the baseline scenario assumes that the percentage of equipped area exploited for irrigation remains constant between 2000 and 2030. Figure 35 shows that the Higher vari ant (right bar) leads to large differences with the baseline scenario (left bar). Only results for the New Member St ates are shown, but this region together with the EU Candidate Countries is most affected by these uncertainties. In the New EU Member States, 1689 million m3 of wa ter will be used in the agricultural sector in the year 2030 considering the baseline assumptions . This result differs only slightly from the amount of water used in the base year (2000). If we assume that the extent of irrigated areas and the percentage of exploited area are constant during the projected time period (Lower variant), the water withdrawals in the agricultura l sector will decrease by 3% in 2010 and 9% in 2030 compared to the baseline scenario. But taking in to account that the whole area equi pped for irrigation will be irrigated (Higher variant), the amount of water used in this sector wi ll increase by 49% in the year 2030 (respective 15% in 2010).
We have mentioned earlier that the future extent of irrigated area is an o bviously important driving force, and this sensitivity analysis confirms this point. It is urgentin future water outlooks to improve projections of irrigated area, both the area equipped for irrigatio n as well as the area anticipated to be exploited on a regular basis.

New EU Member States: water use in the agricultural sector

0 500 1000 1500 2000 2500

2010 2030Water withdrawals [mio. m3/yr]

baseline low variant high variant

Figure 35. Sensitivity analysis of the agricultu ral sector, New EU Member States.European Outlook on Water Use Final Report 58



## 8. RECOMMENDATIONS FOR IMPROVING WATER OUTLOOKS FOR EUROPE

This report has been prepared on behalf of the European Environment Agency (EEA) as a contribution to the next State of the E nvironment and Outlook Report 2005 (SoEOR2005). In particular, it provides background information for the outlook on water use in Europe up to 2030 by estimating future water use and ava ilability for 30 separate European countries. In order to attain this goal, we decided to combine two approaches : a scenario approach and a modeling approach. Due to the short time available (11 months), onl y two alternative scenar ios were developed – a baseline and a climate policy scenario. The WaterGAP model was used to compute future water availability and use estimates, and focused on the mo st critical driving forces. Due to the limited number of scenarios and driving forces considered, the results cover the main aspects of future water availability and use. It s hould be noted, however, that a mu ch wider and more refined range of scenarios is possible, and that additional drivi ng forces may also have a considerable influence. In the following, we summarize our main reco mmendations for such future studies.

• Build multiple baselines. The terms of reference for this st udy called for th e development of only one baseline. Unfortunately it is difficult to argue that one particular baseline scenario is more probable than another. Therefore it is comm on in international scenario exercises (e.g. the greenhouse gas emission scenarios of IPCC, 2000) to generate multiple ba seline scenarios that indicate a range of plausible fu ture developments. It is strong ly recommended that future EEA water outlooks (and other environmental outlooks) produce multiple rather than single baseline scenarios.

• Collect and analyse data on domestic water use. We have pointed out that the trends in domestic water use in some (but not all) of th e New EU Member States is very uncertain. The EEA should give special attention to understandi ng trends in per capita water use in these countries in order to reduce these uncertainties a nd improve esimates of future water use in the domestic sector. In particular, a consistent European-wide data set regarding domestic water use should be compiled, including information a bout the relationship between water use and household profile and size, types of residences, and location (e.g. rural vs. urban residences). These data will greatly improve the estimation of future water use in the domestic sector.

• Include the effects of water prices. The price of water, no doubt, has an effect on water use in all sectors. Yet the lack of data and appropriate models makes it di fficult at this time to include price effects in estimates of future water us e in Europe. The EEA should support the collection of European-wide data documenting the relati onship between price changes and water use and should also support the development of models based on these data. These developments will improve the estimation of future water use in the domestic, and other sectors.

• Analyse the importance of emer ging industries on water use. We noted in Section 7 that a major uncertainty in anticipating future water use in manufacturing is the uncertainty about the emergence of new water-intensive industries or the growing importance of existing waterintensive industries such as electronics. We reco mmend that the EEA suppor t detailed studies of the future importance of existing and emerging water-intensive industries. Information from these studies will improve estimations of th e water use in the manufacturing sector.

• Project the extent of irrigated land. Although irrigated land is a decisive driving force of future water use in agriculture, there are no availabl e pan-European projecti ons of this land. We recommend that the EEA support the development of detailed projections of future irrigated land that take into account ec onomic, geographic and other fact ors. These projections will greatly improve estimates of future water use in the agricultural sector.European Outlook on Water Use Final Report 59

• Collect and analyse data on tec hnological developments. The data used in this report to estimate rates of improvement of water use efficiency are very sketchy and by no means comprehensive. To improve estimates of future water use the EEA should support the compilation of a European-wide data set that provi des examples of changes in wate r use efficiency in all sectors over time. These data will afford a more solid ba sis for estimating future rates of technological improvements in water use efficiency.European Outlook on Water Use Final Report 60



## 9. CONCLUSIONS

This study explored quantitative sc enarios of future water use up to 2030 in 30 European countries (the EU plus 5 EEA member countries). Estimates are also presented for future water availability and water stress. Two scenarios we re developed – a baseline scenar io reflecting a continuation of current trends and a climate policy scenario assuming drasti c policies to limit greenhouse gas emissions. The scenarios account for a wide range of driving forces of water use including changing population, economic growth, technological changes, changes in electricity production, transition to new types of power station coo ling, structural changes in dom estic water use, extent and exploitation of irrigated areas, and climate change. From the results of the study, several conclusions can be drawn that constitute not only important scientific findings but carry consid erable policy relevance. Due to th e inherent uncertainties of such scenario studies covering 30 years into the futu re, we will attempt to qualify our conclusions by adding estimates of certainty based on expert judgement.

• The trend of total European wa ter withdrawals is downward. Under the two scenarios developed in this study, total water withdraw als in the Europe-30 c ountries decrease by approximately 11% between 2000 and 2030. These results are intermediate compared to previously published estimates. This will allo w policy makers to set relatively stringent goals with regard to water use management.

• The profile of water use is changing. The profile of water use in Eur ope is expected to change in important ways over the next few decades (medium to high certainty). Different water sectors dominate total water withdrawals in different parts of Europe, and the relative importance of these sectors is likely to change up to 2030 (with high certainty):
- Water withdrawals in Northern Europe are currently dominated by water use in the electricity production sector but, by 2030, we e xpect (with low to medium certainty) that water use in the manufacturing and dome stic sectors will be more important.
- Water withdrawals in Southern Europe and in the EU Candidate States are currently dominated by agricultural water use, and this will remain the same in 2030 (medium to high certainty).
- Water withdrawals in the New EU Member States are dominated by water use in the electricity production sector but, by 2030, we exp ect (with low certainty ) that the domestic sector will dominate water withdrawals. These projections should help countries focus in their water use management policies on the most important economic sectors.

• A multi-sector approach is needed . Since no single sector dominates water use in Europe, it is not advisable to focus water c onservation efforts in Europe on any individual sector. A panEuropean strategy to reduce water use should c oncentrate on different sectors in different countries, that is, it should take a multi-sector approach. Here, the implementation of the Water Framework Directive by indivi dual countries becomes important and offers a good policy instrument to further water conservation efforts.

• A river basin approach is also needed. . For administrative and tec hnical reasons it makes sense to carry out water conservation programs on the country-scale. However, the river basin approach required by the Water Fr amework Directive makes it also necessary to address water use issues (including the reduction of water use and treatment of runoff from water use) on the river basin scale.European Outlook on Water Use Final Report 61

• A major unknown is future domestic water use in New EU Member States . If per capita water use in New EU Member States ri ses to the level of other EU countries by 2030, then water use in the domestic sector here will substantially increase, and it will become the most important water-using sector by far in this region. If per capita dom estic water use stays at its current level in New EU Member States, then total water wit hdrawals in the domestic sector in 2030 will be about the same as those of the electricity pr oduction and manufacturing s ectors taken together. One conclusion from these results is that in tervening now to encourage water conservation could avoid large increases in the domestic sector of these states (with low to medium certainty) and could contribute to thei r attaining the goals of the Water Framework Directive.

• Water use in the electricity production sector is expected (with medium certainty) to significantly decrease during the scenario period. The reason for this decline is primarily the assumption that all new power st ations will have tower coo ling rather than once-through cooling. Tower cooling requires much lower w ithdrawals than once-through cooling. It is apparent (with medium certainty) that requirin g the use of tower cooling in all new power stations is an effective strategy for redu cing overall water wit hdrawals. Although water withdrawals decline, water consum ption per unit electricity genera ted is much higher with tower cooling. This has to be taken into account wh en implementing the Water Framework Directive and other national policies.

• Technological development lowers water use . We expect (with medium certainty) that technological improvements in water use sect ors will continue to lead to significant improvements in the efficiency of water use. Between 2000 and 2030, we estimate that technological improvements will tend to decrea se water use by 25% to 36% depending on the sector and scenario. Technological improvements will tend to dampen the increase of water use in those sectors and regions of Europe that still show an overall increase (medium to high certainty). We estimate that without technologi cal improvements in these sectors, their water use would be from 34% to 56% higher. Th erefore countries should support technological improvements in the water use sector in order to make use of these im portant potential savings.

• Irrigation water withdrawals may increase in the South. A combination of drier/warmer climate and expanding irrigated area may increase water withdrawals for agriculture in the South. (lower medium uncertainty). However, this in creasing tendency will be dampened somewhat by continuing improvements in the water use efficien cy of irrigation. Countries may have to take this into account when formula ting their agricult ural policies.

• Increase in irrigated areas and/ or irrigation water withdrawals may deteriorate the ecological and chemical status of freshwater bodies. Based on the extent of irri gated areas and amount of water withdrawn, the agricultural return flow (w ater withdrawal minus consumption) carries a specific pollution load. The larger the extent of irrigated areas and the higher the amount of water withdrawal, the higher is the potential pollution load. Countries w ill have to take this into account when implementing the Water Framework Dir ective in order to maintain or improve the ecological and chemical stat us of freshwater bodies.

• Climate policies will lead to lower water use in the electricity production sector. The emission reductions assumed in the climate policy scenario do not dampen climate change very much in the coming decades (because of inertia in the c limate system). However, these policies could have a more noticeable effect on the future magnitude and profile of energy production and thereby on the volume of water used in the el ectricity production sector (medium to high certainty). Greenhouse gas emissions are reduced under this scenario by replacing fossil fuels with renewable energy. The introdu ction of renewable energy implies that some thermal power stations will be phased out or replaced by low wa ter-using technologies, and this reduces overall water withdrawals (medium to high certainty).European Outlook on Water Use Final Report 62



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## APPENDIX A: DOMESTIC WATER USE MODEL – CONCEPT OF STRUCTURAL CHANGE

In the domestic water use model, changes in wate r use intensity are expr essed by structural and technological changes. The concept of structural ch ange is represented in the baseline scenario by a sigmoid curve which indicates how water use intensity (w ater use per capita) changes with income (GDP/cap). Here, the relationship between structural water use intensity and income is derived for each country by fitting a sigmoid curve to adjusted data from each country. These adjusted data are historical data from which the estimated effect of technological improveme nts in water use efficiency have been subtracted. Th is approach, using a sigmoid curv e to describe the baseline scenario, has been used for 22 countries within the Eu rope-30 region. To evaluate the fit of the curves, we use the index of agreement of Willmo tt (1984) which is defined as follows:

PE RMSE n d 2 1 ⋅

− = (8)

2 2 2

u s RMSE RMSE RMSE + = (9)

where
d = Index of agreement [-]

n = Number of cases
RMSE = Root mean square error

RMSE s = Average systematic portion of RMSE

RMSE u = Average unsystematic portion of RMSE

PE = Potential error variance

The approach of using a sigmoid curve to represent the baseline scenario could not be used for the Czech Republic, Estonia, Hungary, Latvia, Lit huania, Poland, the Slovak Republic, and Turkey whose historical data could not be fitted to a sigmoid curve. Therefore we used an alternative approach which is desc ribed in Section 3.2.3. The following Figure 36 to Figure 65 show the base line curves representing the domestic (structural) water use intensities for each country with in the Europe-30 region. The countries are allocated according to the four regions defined in Table 1.European Outlook on Water Use Final Report 68

Northern Europe

Austria

0 20 40 60 80 100 120 140

0 5000 10000 15000 20000 25000 30000 35000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.964

Figure 36. Domestic structural water use intensity (baseline curve) for Austria. Source: EUROSTAT and national Statistical Office. Belgium

0 20 40 60 80 100 120

0 5000 10000 15000 20000 25000 30000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.907

Figure 37. Domestic structural water use intensity (baseline curve) for Belgium. Source: EUROSTAT and national Statistical Office.

Denmark

0 20 40 60 80 100 120 140 160

0 10000 20000 30000 40000 50000 60000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.905

Figure 38. Domestic structural water use intensity (baseline curve) for Denmark. Source: EUROSTAT and national Statistical Office. Finland

0 20 40 60 80 100 120 140

0 5000 10000 15000 20000 25000 30000 35000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.908

Figure 39. Domestic structural water use intensity (baseline curve) fo r Finland. Source: EUROSTAT and national Statistical Office.

Germany

0 20 40 60 80 100 120

0 5000 10000 15000 20000 25000 30000 35000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.935

Figure 40. Domestic structural water use intensity (baseline curve) for Germany. Source: EUROSTAT and national Statistical Office. Ireland

0 50 100 150 200

0 5000 10000 15000 20000 25000 30000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.963

Figure 41. Domestic structural water use intensity (baseline curve) for Ireland. Source: EUROSTAT and national Statistical Office.European Outlook on Water Use Final Report 69

Luxembourg

0 20 40 60 80 100 120 140 160

0 10000 20000 30000 40000 50000 60000 70000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.679

Figure 42. Domestic structural water use intensity (baseline curve) for Luxembourg. Source: EUROSTAT and national Statistical Office. The Netherlands

0 20 40 60 80 100 120 140

0 5000 10000 15000 20000 25000 30000 35000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.967

Figure 43. Domestic structural water use intensity (baseline curve) for The Netherlands. Source: EUROSTAT and na tional Statistical Office.

Sweden

0 50 100 150 200

0 5000 10000 15000 20000 25000 30000 35000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.847

Figure 44. Domestic structural water use intensity (baseline curve) for Sweden. Source: EUROSTAT and national Statistical Office. United Kingdom

0 50 100 150 200 250

0 5000 10000 15000 20000 25000 30000 35000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.991

Figure 45. Domestic structural water use intensity (baseline curve) for United Kingdom. Source: EUROSTAT and na tional Statistical Office.

Norway

0 50 100 150 200 250 300 350

0 10000 20000 30000 40000 50000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.829

Figure 46. Domestic structural water use intensity (baseline curve) for Norway. Source: EUROSTAT and national Statistical Office. Switzerland

0 50 100 150 200 250

0 10000 20000 30000 40000 50000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.691

Figure 47. Domestic structural water use intensity (baseline curve) for Switzerland. Source: EUROSTAT and national Statistical Office.European Outlook on Water Use Final Report 70

Southern Europe

France

0 50 100 150 200

0 5000 10000 15000 20000 25000 30000 35000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.955

Figure 48. Domestic structural water use intensity (baseline curve) for France. Source: EUROSTAT and national Statistical Office. Greece

0 20 40 60 80 100 120 140 160

0 5000 10000 15000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.702

Figure 49. Domestic structural water use intensity (baseline curve) for Greece. Source: EUROSTAT and national Statistical Office.

Italy

0 50 100 150 200 250 300

0 5000 10000 15000 20000 25000 30000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.993

Figure 50. Domestic structural water use intensity (baseline curve) for Italy. Source: EUROSTAT and national Statistical Office. Portugal

0 20 40 60 80 100 120 140

0 2000 4000 6000 8000 10000 12000 14000 16000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.733

Figure 51. Domestic structural water use intensity (baseline curve) for Portugal. Source: EUROSTAT and national Statistical Office.

Spain

0 50 100 150 200 250

0 2000 4000 6000 8000 10000 12000 14000 16000 1800 0 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.779

Figure 52. Domestic structural water use intensity (baseline curve) for Spain. Source: EUROSTAT and national Statistical Office.European Outlook on Water Use Final Report 71

New EU Member States

Cyprus

0 50 100 150 200

0 3000 6000 9000 12000 15000 18000 21000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.897

Figure 53. Domestic structural water use intensity (baseline curve) for Cyprus. Source: EUROSTAT and national Statistical Office. Czech Republic

0 20 40 60 80 100 120 140

1955 1965 1975 1985 1995 2005 2015 2025 2035

yeardomestic water useintensity [m3/cap.year]

historical data non-convergence convergence
Figure 54. Domestic water use intensity (baselinecurve) for the Czech Republic. Source: EUROSTAT and national Statistical Office.

Estonia

0 20 40 60 80 100 120 140

1985 1995 2005 2015 2025 2035

yeardomestic water useintensity [m3/cap.year]

historical data non-convergence convergence
Figure 55. Domestic water use intensity (baselinecurve) for Estonia. Source: EUROSTAT and national Statistical Office. Hungary

0 20 40 60 80 100 120 140 160

1955 1965 1975 1985 1995 2005 2015 2025 2035

yeardomestic water useintensity [m3/cap.year]

historical data non-convergence convergence
Figure 56. Domestic water use intensity (baseline curve) for Hungary. Source: EUROSTAT and national Statistical Office.

Latvia

0 20 40 60 80 100 120 140

1985 1995 2005 2015 2025 2035

yeardomestic water useintensity [m3/cap.year]

historical data non-convergence convergence
Figure 57. Domestic water use intensity (baselinecurve) for Latvia. Source: EUROSTAT and national Statistical Office. Lithuania

0 20 40 60 80 100 120 140

1985 1995 2005 2015 2025 2035

yeardomestic water useintensity [m3/cap.year]

historical data non-convergence convergence
Figure 58. Domestic water use intensity (baseline curve) for Lithuania. Source: EUROSTAT and national Statistical Office.European Outlook on Water Use Final Report 72

Malta

0 10 20 30 40 50 60 70 80

0 5000 10000 15000 20000 25000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.819

Figure 59. Domestic structural water use intensity (baseline curve) for Malta. Source: EUROSTAT and national Statistical Office. Poland

0 20 40 60 80 100 120 140

1965 1975 1985 1995 2005 2015 2025 2035

yeardomestic water useintensity [m3/cap.year]

historical data non-convergence convergence
Figure 60. Domestic water use intensity (baselinecurve) for Poland. Source: EUROSTAT and national Statistical Office.

Slovak Republic

0 20 40 60 80 100 120 140

1975 1985 1995 2005 2015 2025 2035

yeardomestic water useintensity [m3/cap.year]

historical data non-convergence convergence
Figure 61. Domestic water use intensity (baselinecurve) for the Slovak Republic. Source: EUROSTAT and national Statistical Office. Slovenia

0 20 40 60 80 100 120 140 160 180

0 5000 10000 15000 20000 25000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.859

Figure 62. Domestic structural water use intensity (baseline curve) for Slovenia. Source: EUROSTAT and national Statistical Office.European Outlook on Water Use Final Report 73

EU Candidate Countries

Bulgaria

0 50 100 150 200 250

0 2000 4000 6000 8000 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.657

Figure 63. Domestic structural water use intensity (baseline curve) for Bulgaria. Source: EUROSTAT and national Statistical Office. Romania

0 50 100 150 200

0 500 1000 1500 2000 2500 3000 3500 GDP/cap. [Euro2000]domestic structural wateruse intensity [m3/cap.year]

adjusted data baseline index of agreement=0.465

Figure 64. Domestic structural water use intensity (baseline curve) for Romania. Source: EUROSTAT and national Statistical Office.

Turkey

0 20 40 60 80 100 120 140

1985 1995 2005 2015 2025 2035

yeardomestic water useintensity [m3/cap.year]

historical data non-convergence convergence
Figure 65. Domestic water use intensity (baselinecurve) for Turkey. Source: EUROSTAT and national Statistical Office.European Outlook on Water Use Final Report 74



## APPENDIX B: CALCULATION OF TECHNOLOGICAL CHANGES

The concept of technological change takes into account the important effe ct of improving technologies tend to improve water use effi ciency. In this Section, the calcu lation of the historical technological changes in water use efficiency in the el ectricity and manufacturi ng sectors are described. All information about former technological changes were derived from data collected for Germany.


### Historical technological changes of wa ter intensity: Electricity production sector
In the water use model of the el ectricity production sector, two wate r intensities are distinguished: the water use intensity for once-through flow coo ling systems and water use intensity for tower cooling systems. Existing time series on electricity production and water use are used for calculating water use intensities. It is possible to separate the thermal el ectricity production because water is mainly used by thermal power statio ns. But the problem that occurs is the lack of data concerning different cooling systems. Technological changes for tower cooling systems of thermal power stations are determined from data given by Vattenfall (2002), one of the leading European energy companies.
Data to determine historical t echnological changes for once-through flow cooling systems are not available. Figure 66 shows the water use intensitie s of thermal power stati ons using tower cooling systems recorded between 1989 and 2002. The decrease in water use intensity is attributed to improvements in multiple-shift usage of water and reduction of evaporating water. These improvements are described by technological changes. For the whole time period (1989 to 2002) an annual technological change of 4.3% can be estimated. But it can be seen that the decrease in water us e intensity slows down si nce 1997. As a result, two time periods for the basic approach of technologi cal changes are used: A first time period from 1989 to 1997 and a second from 19 97 up to 2002 (which describes the reduction in technological efficiency). The determination of the historical technological change taking into account two different time periods, is shown in Figure 67 For the first time period (1989 to 1997) a more rapid decrease in water use intensity can be seen comp ared to the second phase (1997 to 2002). The annual technological change calculated for time period one is 5.3% and 1.5% for the second period. Taking into account this consideration, a smooth technological change for fu ture estimates will be more realistic.European Outlook on Water Use Final Report 75

Technological change: tower cooling system

0 0.5

1 1.5

2 2.5

3 3.5

4

1985 1990 1995 2000 2005

yearwater use intensity [m3/MWh]

data tech. change = 4.3% per year (1989-2002)

Figure 66. Historical technological change of water in tensity of tower cooling systems, (time period 1989-2002). Source: Vattenfall (2002).

Technological change: tower cooling system

0 1 2 3 4

1985 1990 1995 2000 2005 yearwater use intensity[m3/MWh]

data tech. change = 5.3% per year (1989-1997) tech. change = 1.5% per year (1997-2002)

Figure 67. Historical technological ch ange of water intensity of towe r cooling systems, considering two time periods (1989-1997 and 1997- 2002). Source: Vattenfall (2002).


### Historical technological changes of water intensity: Manufacturing sector Different technological changes ar e determined for different manuf acturing sectors (see Figure 68 to Figure 73). The sectoral-specific water use inte nsities are calculated for each year as the quotient of the sectoral-specific production and the sectoral-s pecific water use. Time series for the time period between 1965 and 1995 (from DEST ATIS and several statistica l yearbooks of Germany) are taken into account. The historical technological changes are derive d concerning data about the following manufacturing sectors: food products, beverages, and tobacco; textiles; pulp, paper, publishing, and printing; chemicals and man-made fibres ; non-metallic and mineral products; basic metals and fabrication of metal products.European Outlook on Water Use Final Report 76

Technological change: food products, beverages, tobacco

0 0.02 0.04 0.06 0.08

0.1 0.12 0.14

1950 1960 1970 1980 1990 2000 yearwater use intensity [m3/t]

water use intensity tech. change = 5.6 % per year (1953-1983) tech. change = 2.2 % per year (1983-1998)

Figure 68. Determination of the historical technologi cal change in water in tensity of the manufacturing of food products, beverages, and tob acco, considering two tim e periods (1953-1983 and 1983-1998). Source: DESTATIS.

Technological change: textiles

0 0.5

1 1.5

2 2.5

1950 1960 1970 1980 1990 2000

yearwater use intensity [m3/t]

water use intensity tech. change = 6.4 % per year (1957-1979) tech. change = 1.5 % per year (1979-1998)

Figure 69. Determination of the hi storical technological change of water inte nsity of the manufacturing of textiles, c onsidering two time periods (1957- 1979 and 1979-1998). Source: DESTATIS.European Outlook on Water Use Final Report 77

Technological change: pulp, paper, publishing, printing

0 20 40 60 80 100 120 140 160 180

1950 1960 1970 1980 1990 2000 2010 yearwater use intensity [m3/t]

water use intensity tech. change = 4.2 % per year (1957-1983) tech. change = 2.3 % per year (1983-1998)

Figure 70. Determination of the hi storical technological change of water inte nsity of the manufacturing of pulp, paper, publis hing and printing, considering two time periods (1957-1983 and 1983- 1998). Source: DESTATIS.

Technological change: non-metallic minerals

0 0.05

0.1 0.15

0.2 0.25

0.3

1950 1960 1970 1980 1990 2000 2010

yearwater use intensity [m3/t]

water use intensity tech. change = 1.2 % per year (1979-2001)

Figure 71. Determination of the historical technol ogical change of water intensity for the manufacturing of, non-metallic, mineral products cons idering one time period (1979-2001). Source: DESTATIS.European Outlook on Water Use Final Report 78

Technological change: chemicals, man-made fibres

0 50 100 150 200 250

1950 1960 1970 1980 1990 2000 yearwater use intensity [m3/t]

water use intensity tech. change = 3.4 % per year (1957-1979) tech. change = 0.5 % per year (1979-1998)

Figure 72. Determination of the historical technol ogical change of water intensity for the manufacturing of chemicals and man-made fibres, considering two time periods (1957-1979 and 1979- 1998). Source: DESTATIS.

Technological change: basic metals and fabrication of metal products

0 2 4 6 8 10 12 14 16 18

1950 1960 1970 1980 1990 2000 yearwater intensity [m3/t]

water use intensity tech. change =1.1 % per year (1952-1991)

Figure 73. Determination of histor ical technological change of water intensity for the manufacturing of basic metals and fabrication of metal product s, considering one time period (1952-1991). Source: DESTATIS.European Outlook on Water Use Final Report 79



## APPENDIX C: GROSS VALUE ADDED FOR THE BASELINE (LREM-E) AND CLIMATE POLICY (SEP) SCENARIOS

The gross value added (GVA) of industrial production is the main driving forc e of water use in the manufacturing industry. The assumpti ons for the economic growth of the industry by sector for the baseline and climate policy scenarios are listed in Table 12 to Table 14 fo r Southern Europe, the New EU Member States, and the EU Candidate Countries.
Table 12. Gross value added separated by sectors in the Southern Europe economy. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in Table 1.

GVA [10 9 Euro2000] Annual growth rate [%]

Year 1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Iron and steel 20 21 22 23 23 0.50 0.68 0.38 0.21 0.42
Non-ferrous metals 7 9 12 15 18 2.45 2.90 2.40 2.06 2.45
Chemicals 55 70 93 120 150 2.48 2.81 2.61 2.28 2.57
Non-metallic minerals 30 34 41 49 58 1.00 2.00 1.88 1.60 1.83 Paper and pulp 38 46 59 75 90 1.81 2.52 2.44 1.89 2.29 Food, drink, tobacco 60 71 92 116 142 1.63 2.63 2.32 2.04 2.33 Engineering 209 262 355 474 623 2.27 3.08 2.93 2.78 2.93
Textiles 53 50 51 53 54 -0.75 0.31 0.35 0.16 0.27
Other industries 45 58 74 92 108 2.45 2.53 2.16 1.62 2.11 Total industry 518 619 798 1016 1266 1.79 2.57 2.44 2.23 2.41

Table 13. Gross value added separated by sectors in the New EU Member States economy. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in Table 1.

GVA [10 9 Euro2000] Annual growth rate [%]

Year 1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Iron and steel 4 3 4 4 5 -2.16 1.70 1.13 0.80 1.21
Non-ferrous metals 1 1 1 1 1 2.58 2.19 2.44 1.38 2.00
Chemicals 6 7 13 19 25 1.51 6.06 4.17 2.71 4.30
Non-metallic minerals 3 5 7 10 12 4.61 3.25 2.94 1.87 2.68 Paper and pulp 4 6 9 13 17 3.78 4.56 3.98 2.51 3.68 Food, drink, tobacco 12 17 26 34 41 3.58 4.01 2.85 1.87 2.91 Engineering 27 30 46 69 90 1.38 4.21 4.15 2.68 3.68
Textiles 9 6 8 9 9 -3.43 1.76 1.25 0.84 1.28
Other industries 12 12 18 25 32 -0.21 4.39 3.32 2.24 3.31 Total industry 78 88 131 185 232 1.22 4.06 3.47 2.29 3.27European Outlook on Water Use Final Report 80

Table 14. Gross value added separated by sectors in the EU Candidate Countries economy. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in Table 1.

GVA [10 9 Euro2000] Annual growth rate [%]

Year 1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Iron and steel 3 3 4 4 5 1.74 1.93 1.25 0.85 1.34
Non-ferrous metals 1 1 1 1 1 -3.44 1.98 3.17 2.49 2.54
Chemicals 4 5 8 13 21 2.66 4.29 5.91 4.53 4.91
Non-metallic minerals 3 4 6 10 16 2.33 3.95 5.92 4.34 4.73 Paper and pulp 1 2 3 6 10 5.57 4.26 6.18 5.47 5.30 Food, drink, tobacco 6 10 15 23 34 5.29 4.02 4.43 3.82 4.09 Engineering 9 11 19 40 68 1.76 5.56 7.57 5.51 6.21
Textiles 10 8 9 11 13 -1.79 0.53 2.11 2.34 1.65
Other industries 11 12 16 29 45 1.24 3.18 5.88 4.57 4.54 Total industry 47 56 80 137 212 1.71 3.64 5.52 4.48 4.54European Outlook on Water Use Final Report 81



## APPENDIX D: OVERVIEW OF MODEL OUTPUTS

In this Section, both, water withdrawals for the base year (2000) and 2030 are presented for each country and summed for the four Europe-30 regi ons. The water withdrawal s are subdivided into four sectors: domestic, agricultu re, manufacturing, and electricit y. Table 15 shows the results for the domestic and agricultural sect ors, Table 16 those for the manufact uring and electricity sectors.
Table 15. Water use in 2030 (in million m3). Overvi ew of the model outputs (domestic and agricultural sector).

Domestic Agriculture 2000 2030 2000 2030 Sensitivity run Country/Region Baseline(LREME) Climate policy (SEP) Nonconvergence Low economic growth variant Baseline(LREME) Climate policy (SEP) Lower variant Higher variant

Northern Europe 29045 23924 23924 23856 23856 3140 2783 2785 2783 3298
Austria 906 771 771 771 765 175 155 155 155 270 Belgium 1078 925 925 925 913 124 108 108 108 108 Denmark 626 491 491 491 491 216 190 190 190 190 Finland 612 481 481 481 481 92 72 71 72 125 Germany 8139 6168 6168 6168 6165 738 659 660 659 659 Ireland 700 637 637 637 637 149 124 124 124 124 Luxembourg 55 51 51 51 51 1 1 1 1 1 The Netherlands 1881 1690 1690 1690 1664 565 511 508 511 569 Sweden 1420 1107 1107 1107 1107 300 274 274 274 274 United Kingdom 10840 9301 9301 9301 9292 513 454 457 454 743 Norway 1233 1128 1128 1128 1117 225 198 198 198 198 Switzerland 1554 1174 1174 1174 1174 42 38 38 38 38

Southern Europe 29922 28211 28211 27436 27436 59995 68344 68081 54584 77799

France 9097 8356 8356 8356 8256 3554 4095 4071 3312 4820 Greece 1343 1500 1500 1 500 1495 11624 12714 12666 10601 13306 Italy 12098 12688 12688 12688 12018 19722 22769 22691 17966 29725 Portugal 1129 1013 1013 1013 1013 4791 5451 5435 4301 6632 Spain 6255 4655 4655 4655 4655 20304 23316 23217 18404 23316

New EU Member States 5025 8753 8725 4568 8611 1684 1689 1690 1530 2275 Cyprus 103 104 94 104 104 295 271 276 227 271 Czech Republic 808 1218 1218 748 1198 59 54 54 54 137 Estonia 71 126 126 51 123 13 12 12 12 13 Hungary 746 1099 1099 639 1081 620 702 698 591 1113 Latvia 104 253 253 87 249 39 36 36 36 36 Lithuania 128 406 406 116 399 72 67 67 67 67 Malta 22 17 15 17 17 7 15 15 12 26 Poland 2350 4690 4690 2227 4612 441 408 408 408 434 Slovak Republic 423 669 669 410 658 117 106 107 106 161 Slovenia 268 170 154 170 170 19 16 16 16 17

EU Candidate Countries 9230 14728 14432 8934 14533 34774 38104 38012 31824 70817 Bulgaria 1420 765 692 765 765 396 454 452 383 6843 Romania 3464 2307 2085 2307 2307 1343 1525 1519 1291 25104 Turkey 4346 11656 11656 5862 11461 33034 36125 36041 30150 38869
Europe-30 73222 75616 75292 64794 74436 99593 110920 110568 90721 154189European Outlook on Water Use Final Report 82

Table 16. Water use in 2030 (in m illion m3). Overview of the m odel outputs (manufacturing and electricity sector).

Manufacturing Electricity 2000 2030 2000 2030 Country/Region Baseline Low economic growth variant Baseline Climate policy Low economic growth variant
Northern Europe 17628 22918 19794 40215 10975 9182 9368 Austria 1786 2527 2235 1146 314 258 226 Belgium 1441 1719 1482 4712 1244 1084 1093 Denmark 112 136 124 104 85 65 73 Finland 1491 1414 1262 276 189 158 162 Germany 5995 7880 6683 23253 3259 2733 2777 Ireland 466 816 695 283 83 58 70 Luxembourg 14 22 18 1 17 15 10 The Netherlands 782 911 715 6069 1594 1313 1257 Sweden 1934 2571 2268 310 85 70 71 United Kingdom 1472 1925 1723 2197 2418 2035 2137 Norway 1679 2293 1986 120 1531 1224 1367 Switzerland 457 704 603 1744 157 170 126
Southern Europe 14905 18542 15807 31831 11736 11108 9641 France 3950 5191 4473 17170 6902 6787 5878 Greece 110 200 178 186 245 232 218 Italy 9217 10486 8821 6974 3540 3202 2633 Portugal 328 527 436 1077 413 292 319 Spain 1300 2138 1898 6424 637 595 593

New EU Member States 2236 4340 4056 14401 3658 3554 3359 Cyprus 14 24 21 0 0 0 0 Czech Republic 425 610 532 528 275 274 242 Estonia 27 47 45 990 66 60 63 Hungary 152 309 269 3294 899 902 763 Latvia 65 165 157 13 40 26 36 Lithuania 52 101 97 1724 1056 1013 989 Malta 2 4 3 0 0 0 0 Poland 748 1730 1647 6614 1159 1116 1114 Slovak Republic 649 1200 1147 698 123 123 116 Slovenia 103 151 138 540 41 41 36

EU Candidate Countries 4968 11143 10379 8526 4447 4143 3818 Bulgaria 516 883 787 3071 874 840 766 Romania 955 1800 1609 2672 2398 2223 2123 Turkey 3497 8460 7983 2784 1175 1081 928
Europe-30 39737 56943 50036 94973 30816 27987 26186European Outlook on Water Use Final Report 83



## APPENDIX E: DRIVING FO RCE ASSUMPTIONS FOR THE LOW ECONOMIC GROWTH VARIANT

For the sensitivity run we use a projection of GDP/cap that has considerably lower economic growth rates than assumed for the baseline and cl imate policy scenario. These projections were produced by the PROMETHEUS model. Table 17 to Ta ble 20 present the gross value added for the low economic growth variant separated by manufactur ing sectors for the four Europe-30 regions. Along with a slower economic growth, the production of electricity will also be lower than in the baseline and climate policy scenarios. The results of this sensitivity run are given in Table 21 and Table 22.
Table 17. Gross value added sepa rated by sectors in the Northern Europe economy (low economic growth variant). Source: EUROSTAT, Economi c and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1.

GVA [10 9 Euro2000] Annual growth rate [%]

Year 1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Iron and steel 36 30 28 27 27 -1.83 -0.60 -0.15 -0.24 -0.33
Non-ferrous metals 15 17 23 29 35 1.42 2.91 2.25 1.89 2.35
Chemicals 106 133 160 195 230 2.28 1.91 1.97 1.67 1.85
Non-metallic minerals 39 40 43 50 56 0.14 0.94 1.38 1.14 1.15 Paper and pulp 86 108 129 153 175 2.31 1.80 1.71 1.39 1.63 Food, drink, tobacco 104 128 148 175 202 2.12 1.50 1.69 1.43 1.54 Engineering 442 507 611 747 902 1.39 1.88 2.03 1.91 1.94
Textiles 42 32 31 32 33 -2.74 -0.37 0.43 0.34 0.13
Other industries 87 98 112 128 147 1.17 1.35 1.41 1.37 1.37 Total industry 957 1092 1286 1537 1808 1.33 1.65 1.80 1.64 1.69European Outlook on Water Use Final Report 84

Table 18. Gross value added sepa rated by sectors in the Southern Europe economy (low economic growth variant). Source: EUROSTAT, Economi c and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1.

GVA [10 9 Euro2000] Annual growth rate [%]

Year 1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Iron and steel 20 21 21 21 21 0.50 0.25 0.09 0.00 0.11
Non-ferrous metals 7 9 11 13 16 2.45 2.35 2.01 1.78 2.04
Chemicals 55 70 86 105 127 2.48 2.04 2.06 1.85 1.98
Non-metallic minerals 30 34 39 45 51 1.00 1.45 1.46 1.27 1.39 Paper and pulp 38 46 55 68 79 1.81 1.93 1.99 1.55 1.82 Food, drink, tobacco 60 71 86 102 119 1.63 1.89 1.76 1.59 1.75 Engineering 209 262 325 408 512 2.27 2.18 2.30 2.28 2.26
Textiles 53 50 49 49 48 -0.75 -0.19 0.02 -0.10 -0.09
Other industries 45 58 69 81 91 2.45 1.79 1.61 1.19 1.53 Total industry 518 619 741 892 1064 1.79 1.81 1.88 1.77 1.82

Table 19. Gross value added separated by sectors in the New EU Member States economy (low economic growth). Source: EUROSTAT, Economi c and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1.

GVA [10 9 Euro2000] Annual growth rate [%]

Year 1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Iron and steel 4 3 4 4 5 -2.16 1.45 1.04 0.67 1.05
Non-ferrous metals 1 1 1 1 1 2.58 1.79 2.31 1.19 1.76
Chemicals 6 7 12 18 23 1.51 5.59 3.98 2.46 4.00
Non-metallic minerals 3 5 7 9 11 4.61 2.85 2.83 1.68 2.45 Paper and pulp 4 6 9 13 16 3.78 4.23 3.84 2.32 3.46 Food, drink, tobacco 12 17 25 32 38 3.58 3.65 2.65 1.62 2.64 Engineering 27 30 43 64 81 1.38 3.57 4.02 2.42 3.33
Textiles 9 6 7 8 9 -3.43 1.51 1.14 0.70 1.12
Other industries 12 12 18 24 29 -0.21 3.88 3.17 2.00 3.01 Total industry 78 88 126 174 213 1.22 3.59 3.31 2.05 2.98European Outlook on Water Use Final Report 85

Table 20. Gross value added separated by sectors in the EU Candidate Countries economy (low economic growth). Source: EUROSTAT, Economi c and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1.

GVA [10 9 Euro2000] Annual growth rate [%]

Year 1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Iron and steel 3 3 4 4 5 1.74 1.93 1.25 0.85 1.34
Non-ferrous metals 1 1 1 1 1 -3.44 1.98 3.17 2.49 2.54
Chemicals 4 5 8 13 21 2.66 4.29 5.91 4.53 4.91
Non-metallic minerals 3 4 6 10 16 2.33 3.95 5.92 4.34 4.73 Paper and pulp 1 2 3 6 10 5.57 4.26 6.18 5.47 5.30 Food, drink, tobacco 6 10 15 23 34 5.29 4.02 4.43 3.82 4.09 Engineering 9 11 19 40 68 1.76 5.56 7.57 5.51 6.21
Textiles 10 8 9 11 13 -1.79 0.53 2.11 2.34 1.65
Other industries 11 12 16 29 45 1.24 3.18 5.88 4.57 4.54 Total industry 47 56 80 137 212 1.71 3.64 5.52 4.48 4.54

Table 21. Projected thermal electricity production for the low economic grow th variant. Source: EUROSTAT, PRIMES. Regions are defined in Table 1.

Sensitivity run [TWh]* Annual growth rate [%]

Year 1990 2000 2010 2020 2030 90/00 00/10 10/20 20/30 00/30
Northern EU15 + EFTA2 1183 1297 1363 1461 1502 0.93 0.49 0.69 0.28 0.49
Southern EU15 722 963 1071 1169 1255 2.92 1.07 0.88 0.72 0.89
New EU Member States 304 308 348 433 452 0.14 1.23 2.21 0.44 1.29
EU Candidate Countries 121 169 207 265 382 3.40 2.03 2.51 3.72 2.75 Europe -30 2329 2737 2989 3327 3591 1.63 0.88 1.08 0.76 0.91

* Thermal electricity production (including biomass) and nuclear electricity production.European Outlook on Water Use Final Report 86

Table 22. Difference in thermal electricity produc tion for the baseline scenario and low economic growth variant. Source: EUROSTAT, PR IMES. Regions are defined in Table 1.

LREM-E [TWh]* Sensitivity run [TWh]* Difference between Sensitivity run and LREM-E [%]

Year 2000 2010 2020 2030 2010 2020 2030 2010 2020 2030
Northern EU15 + EFTA2 1297 1437 1615 1771 1363 1461 1502 -5.15 -9.58 -15.20
Southern EU15 963 1156 1341 1492 1071 1169 1255 -7.35 -12.86 -15.86
New EU Member States 308 362 452 488 348 433 452 -3.83 -4.16 -7.38
EU Candidate States 169 213 306 469 207 265 382 -2.84 -13.31 -18.55 Europe-30 2737 3168 3714 4220 2989 3327 3591 -5.65 -10.41 -14.90

* Thermal electricity production (including biomass) and nuclear electricity production.