FINAL REPORT

1 October 2004 

European Outlook on Water Use 

Martina Flörke and Joseph Alcamo 

Center for Environmental Systems Research 

University of Kassel
European 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 contribution by sending national data on water uses. 

The authors wish to thank their colleagues at the 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 also thankful to Barbara Lübkert for her editorial 

assistance. 
European Outlook on Water Use Final Report 

CONTENTS 

1. INTRODUCTION......................................................................................................................1

1.1 OBJECTIVES...........................................................................................................................1 

1.2 SCOPE....................................................................................................................................1 

2. DRIVING FORCES AND OTHER FACTORS OF WATER USE ......................................4

2.1 DOMESTIC SECTOR................................................................................................................4 

2.2 ELECTRICITY PRODUCTION SECTOR......................................................................................5 

2.3 MANUFACTURING SECTOR....................................................................................................5 

2.4 AGRICULTURE SECTOR..........................................................................................................6 

2.5 DRIVING FORCES INCLUDED IN THIS STUDY..........................................................................7 

3. METHODOLOGY.....................................................................................................................9

3.1 THE SCENARIO APPROACH....................................................................................................9 

3.2 MODELING APPROACH ..........................................................................................................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 IMPROVED ESTIMATES ACHIEVED IN THIS STUDY ...............................................................22 

4. ASSUMPTIONS OF THE BASELINE SCENARIO (LREM-E).........................................23

4.1 THE WORLD OF THE BASELINE SCENARIO – A QUALITATIVE DESCRIPTION .......................23 

4.2 DRIVING FORCE ASSUMPTIONS ...........................................................................................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 electricity 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 THE WORLD OF THE CLIMATE POLICY SCENARIO – A QUALITATIVE DESCRIPTION............34 

5.2 DRIVING FORCE ASSUMPTIONS ...........................................................................................34 

6. SCENARIO RESULTS............................................................................................................39

6.1 WATER USE.........................................................................................................................39 

6.2 WATER AVAILABILITY AND WATER STRESS .......................................................................48 

6.2.1 Water Availability.......................................................................................................48

6.2.2 Water Stress................................................................................................................49

6.3 CONTRIBUTION TO THE WATER FRAMEWORK DIRECTIVE...................................................51 

7. UNCERTAINTY AND SENSITIVITY OF RESULTS........................................................53
European Outlook on Water Use Final Report 

7.1 UNCERTAINTY OF DOMESTIC WATER USE TRENDS.............................................................53 

7.2 SENSITIVITY TO LOWER PER CAPITA INCOME......................................................................54 

7.3 SENSITIVITY TO UNCERTAIN FUTURE IRRIGATED AREA......................................................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

HISTORICAL TECHNOLOGICAL CHANGES OF WATER INTENSITY: ELECTRICITY PRODUCTION 

SECTOR............................................................................................................................................74 

HISTORICAL TECHNOLOGICAL CHANGES OF WATER INTENSITY: MANUFACTURING 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 .....................................................................................................................83
European Outlook on Water Use Final Report 

FIGURES 

Figure 1. ‘Europe-30’ region covered 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 necessarily irrigated every year. Source: FAO 

(2004). ..........................................................................................................................................6 

Figure 5. Area equipped for irrigation versus total arable land by country as used in the 

WaterGAP model. Source: Döll and Siebert (2000). ...................................................................7 

Figure 6. Conceptual model of structural change in the domestic 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 higher water use efficiency in the domestic 

use sector. Source: V-ZUG AG (2004)......................................................................................15 

Figure 10. Impact of technological change 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 water use in the electricity production sector 

and model efficiency. 25 European countries are taken into account........................................18 

Figure 13. Validation of the irrigation model: calculated irrigation water withdrawals versus 

published data.............................................................................................................................21 

Figure 14. Atmospheric GHG concentration (CO2 equivalents) for the baseline (LREM-E, 

upper line) and the climate policy (SEP, lower 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 compared to today’s level..............................................................37 

Figure 17. Difference between the baseline (LREM-E) and climate policy (SEP) scenarios. 

Differences in long-term average annual temperature (top) and precipitation (bottom). ..........38 

Figure 18. Profile of sector-specific water withdrawals in the Northern Europe in 2000. 

Sources: EUROSTAT and national Statistical Offices. .............................................................39 

Figure 19. Computed water withdrawals for the baseline (LREM-E) scenario for Northern 

Europe. .......................................................................................................................................40 

Figure 20. Profile of sector-specific water withdrawals in Southern Europe in 2000. Sources: 

EUROSTAT and national Statistical Offices.............................................................................41 
European Outlook on Water Use Final Report 

Figure 21. Computed water withdrawals for the baseline (LREM-E) scenario for Southern 

Europe. .......................................................................................................................................41 

Figure 22. Profile of sector-specific water withdrawals in the New EU Member States in 2000. 

Sources: EUROSTAT and national Statistical Offices. .............................................................42 

Figure 23. Computed water withdrawals for the baseline (LREM-E) scenario for the New EU 

Member States............................................................................................................................42 

Figure 24. Profile of sectoral-specific water withdrawals in the EU Candidate States in 2000. 

Sources: EUROSTAT and national Statistical Offices. .............................................................43 

Figure 25. Computed water withdrawals for the baseline (LREM-E) scenario for the EU 

Candidate Countries. ..................................................................................................................44 

Figure 26. Computed water withdrawals for irrigation in the base year 2000 and in 2030 for the 

baseline (LREM-E) and climate policy (SEP) scenarios. ..........................................................45 

Figure 27. Computed water withdrawals for the electricity production in the base year 2000 and 

in 2030 for the baseline (LREM-E) and climate policy (SEP) scenarios...................................46 

Figure 28. Comparison of water use scenarios. (See text for explanation of numbers).....................47 

Figure 29. Change in average annual water availability for European river basins under the 

baseline (LREM-E) scenario compared 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 scenario. 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 agricultural 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 intensity (baseline curve) for Belgium. Source: 

EUROSTAT and national Statistical Office. .............................................................................68 

Figure 38. Domestic structural water use intensity (baseline curve) for Denmark. Source: 

EUROSTAT and national Statistical Office. .............................................................................68 

Figure 39. Domestic structural water use intensity (baseline curve) for Finland. Source: 

EUROSTAT and national Statistical Office. .............................................................................68 

Figure 40. Domestic structural water use intensity (baseline curve) for Germany. Source: 

EUROSTAT and national Statistical Office. .............................................................................68 

Figure 41. Domestic structural water use intensity (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 intensity (baseline curve) for The Netherlands. 

Source: EUROSTAT and national Statistical Office. ................................................................69 
European Outlook on Water Use Final Report 

Figure 44. Domestic structural water use intensity (baseline curve) for Sweden. Source: 

EUROSTAT and national Statistical Office. .............................................................................69 

Figure 45. Domestic structural water use intensity (baseline curve) for United Kingdom. 

Source: EUROSTAT and national Statistical Office. ................................................................69 

Figure 46. Domestic structural water use intensity (baseline curve) for Norway. Source: 

EUROSTAT and national Statistical Office. .............................................................................69 

Figure 47. Domestic structural water use intensity (baseline curve) for Switzerland. Source: 

EUROSTAT and national Statistical Office. .............................................................................69 

Figure 48. Domestic structural water use intensity (baseline curve) for France. Source: 

EUROSTAT and national Statistical Office. .............................................................................70 

Figure 49. Domestic structural water use intensity (baseline curve) for Greece. Source: 

EUROSTAT and national Statistical Office. .............................................................................70 

Figure 50. Domestic structural water use intensity (baseline curve) for Italy. Source: 

EUROSTAT and national Statistical Office. .............................................................................70 

Figure 51. Domestic structural water use intensity (baseline curve) for Portugal. Source: 

EUROSTAT and national Statistical Office. .............................................................................70 

Figure 52. Domestic structural water use intensity (baseline curve) for Spain. Source: 

EUROSTAT and national Statistical Office. .............................................................................70 

Figure 53. Domestic structural water use intensity (baseline curve) for Cyprus. Source: 

EUROSTAT and national Statistical Office. .............................................................................71 

Figure 54. Domestic water use intensity (baseline curve) for the Czech Republic. Source: 

EUROSTAT and national Statistical Office. .............................................................................71 

Figure 55. Domestic water use intensity (baseline curve) for Estonia. Source: EUROSTAT and 

national Statistical Office. ..........................................................................................................71 

Figure 56. Domestic water use intensity (baseline curve) for Hungary. Source: EUROSTAT 

and national Statistical Office. ...................................................................................................71 

Figure 57. Domestic water use intensity (baseline curve) for Latvia. Source: EUROSTAT and 

national Statistical Office. ..........................................................................................................71 

Figure 58. Domestic water use intensity (baseline curve) for Lithuania. Source: EUROSTAT 

and national Statistical Office. ...................................................................................................71 

Figure 59. Domestic structural water use intensity (baseline curve) for Malta. Source: 

EUROSTAT and national Statistical Office. .............................................................................72 

Figure 60. Domestic water use intensity (baseline curve) for Poland. Source: EUROSTAT and 

national Statistical Office. ..........................................................................................................72 

Figure 61. Domestic water use intensity (baseline curve) for the Slovak Republic. Source: 

EUROSTAT and national Statistical Office. .............................................................................72 

Figure 62. Domestic structural water use intensity (baseline curve) for Slovenia. Source: 

EUROSTAT and national Statistical Office. .............................................................................72 

Figure 63. Domestic structural water use intensity (baseline curve) for Bulgaria. Source: 

EUROSTAT and national Statistical Office. .............................................................................73 

Figure 64. Domestic structural water use intensity (baseline curve) for Romania. Source: 

EUROSTAT and national Statistical Office. .............................................................................73 
European Outlook on Water Use Final Report 

Figure 65. Domestic water use intensity (baseline curve) for Turkey. Source: EUROSTAT and 

national Statistical Office. ..........................................................................................................73 

Figure 66. Historical technological change of water intensity 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 and 1997-2002). Source: Vattenfall (2002). ...........75 

Figure 68. Determination of the historical technological change in water intensity of the 

manufacturing of food products, beverages, and tobacco, considering two time periods 

(1953-1983 and 1983-1998). Source: DESTATIS.....................................................................76 

Figure 69. Determination of the historical technological change of water intensity of the 

manufacturing of textiles, considering two time periods (1957-1979 and 1979-1998). 

Source: DESTATIS....................................................................................................................76 

Figure 70. Determination of the historical technological 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 technological change of water intensity for the 

manufacturing of basic metals and fabrication of metal products, considering one time 

period (1952-1991). Source: DESTATIS...................................................................................78 
European Outlook on Water Use Final Report 

TABLES 

Table 1. European countries and reporting regions included in this report. ........................................2 

Table 2. Index of agreement for structural change 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 are defined in Table 1. ..........................................................26 

Table 6. Gross value added separated by sectors in the Northern Europe economy. Source: 

EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in 

Table 1........................................................................................................................................27 

Table 7. ‘Area equipped for irrigation’ and the ‘percentage of equipped area exploited for 

irrigation’ (base year 2000). .......................................................................................................29 

Table 8. Baseline (LREM-E) scenario assumptions for the change in extent 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 are defined in Table 1. ..........................................................35 

Table 10. Difference in thermal electricity production for the baseline (LREM-E) and climate 

policy (SEP) scenarios. Source: EUROSTAT, PRIMES. Regions are defined in Table 1........35 

Table 11. Per capita GDP in the Europe-30 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 sectors in the Southern Europe economy. Source: 

EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in 

Table 1........................................................................................................................................79 

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....................................................................................................................................79 

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....................................................................................................................................80 

Table 15. Water use in 2030 (in million m3). Overview of the model outputs (domestic and 

agricultural sector)......................................................................................................................81 

Table 16. Water use in 2030 (in million m3). Overview of the model outputs (manufacturing 

and electricity sector). ................................................................................................................82 

Table 17. Gross value added separated by sectors in the Northern Europe economy (low 

economic growth variant). Source: EUROSTAT, Economic and Financial Affairs DG, 

PRIMES, PROMETHEUS. Regions are defined in Table 1......................................................83 
European Outlook on Water Use Final Report 

Table 18. Gross value added separated by sectors in the Southern Europe economy (low 

economic growth variant). Source: EUROSTAT, 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, Economic 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, Economic 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 are defined in Table 1. ..........................................................85 

Table 22. Difference in thermal electricity production for the baseline scenario and low 

economic growth variant. Source: EUROSTAT, PRIMES. Regions are defined in Table 1. ...86 
European Outlook on Water Use Final Report 

EXECUTIVE SUMMARY 

This report presents quantitative scenarios 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 were developed – a baseline scenario reflecting a continuation of 

current trends and a climate policy scenario assuming drastic 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 cooling, structural changes in domestic water use, extent and 

exploitation of irrigated areas, and climate change. 

The WaterGAP model was the tool used to compute the scenarios. After calibration, model 

estimates compared well to historical trends or base year data on the country level. Nevertheless, 

scenario estimates have major uncertainties such as the trend in per capita water use in some of the 

countries undergoing a major economic transition, the emergence of new water-intensive industries, 

the useful lifetime of different power stations requiring water withdrawals, and the future extent of 

irrigated areas. Future water outlooks should try to reduce these and other uncertainties. 

In a number of ways this study advanced the state-of-the-art of European water 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 electricity production sector. Third, for the first time detailed calculations of water 

use in several manufacturing sectors were performed. Finally, calculations 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 decreasing trend. These results are intermediate 

compared to previously published estimates. 

• The profile of water use in Europe is changing. In Northern Europe the most important waterusing sector is now the electricity production sector but in the future 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 sector 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 water conservation efforts in Europe 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 countries to address different 

water use sectors that are dominant in these countries. 

• A river basin approach is also needed. For administrative and technical reasons it makes sense 

to carry out water conservation programs on the country-scale. However, the river basin 

approach required by the Water Framework 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. 

 

1

 This and other certainty statements presented 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 states, an intervention now to encourage water 

conservation could avoid large increases in the domestic 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 sectors 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 withdrawals for agriculture in the South (low to 

medium uncertainty). However, this increasing 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 runoff to surface 

and groundwater. Countries will have to take this into account 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 and thereby on the volume of water 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 Environment 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 Outlook’ report published every five years. It is 

obvious that such a comprehensive assessment of Europe’s environment should also assess the state 

of Europe’s freshwater resources. Of particular concern to society is the use of these water 

resources. Besides satisfying basic needs for drinking water and sanitation, water in the household 

also supports other needs such as housecleaning, dishwashing, clothes washing, and landscaping, 

Water plays a vital role in Europe’s economy. It is needed to produce steam and to cool turbines in 

thermal power stations, and is a necessary input for the manufacturing industry where it is used to 

produce power, as input to various industrial processes, or as a basic raw material. Much of 

Europe’s agricultural production comes from irrigated fields, and irrigation requires extensive 

withdrawals of freshwater. Not only is water use critical from the standpoint of society, but the use 

of water is also an important determinant of water 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 next 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 Directive. 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 – Global Assessment and Prognosis) 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 water 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 changing 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 future water use on water availability and water 

stress. 

(d) Contribute to the development of a medium-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 cover 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 scenario results into four regions (Table 1). These 

regions are based on a pragmatic combination of geographic and political factors. Due to lack of 

data Iceland and Liechtenstein are not included in the study. 

Table 1. European countries and reporting 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 the 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 facilities 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 irrigation 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 river 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 amount of pressure put on water resources and aquatic 

ecosystems by the users of these resources, including municipalities, industries, power plants and 

agricultural users (see, for example, Alcamo et al., 2000; Vörösmarty et al., 2000; Cosgrove and 

Rijsberman, 2000). Here we use a conventional measure of water stress, the withdrawal-toavailability ratio. This is the ratio of total annual 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. Instead 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 influence 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 sectoral-specific water use in the Europe-30 region for the year 2000. 

Sources: EUROSTAT2

 and national Statistical Offices. 

2.1 Domestic Sector 

The domestic sector accounts for about 24 percent of total water withdrawn in the Europe-30 in 

2000 (Figure 2). This sector usually includes households and businesses but not manufacturing or 

electrical production facilities. 

The intensity of water use in households [m3

/(cap⋅year)] depends on many factors including the 

amount of household income which is related to the amount of water-using appliances in a 

household (Höglund, 1999; Dalhuisen et al., 2003). Another factor is the size of the household since 

it is usually observed that there are economies of scale in water usage per person in larger 

households (Björnsen, 1993; Höglund, 1999). Other 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 others. There is also an observed difference between 

water consumption patterns in urban versus rural areas. 

Higher water prices are also known to dampen the demand for water 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 relationship between prices and demand are highly variable 

because household and business outlays for water are normally only a very small fraction of their 

total income, and because prices and price structures vary tremendously across Europe. Figure 3 

vividly illustrates the wide variability between average domestic water prices and water use across 

Europe. Currently countries with roughly the same per capita water 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 relationship of price and 

demand for all of Europe. Of course a decisive factor in the domestic sector is not only how much 

water is used per capita but the size of the population using water. The amount of water withdrawn 

for domestic water supply will also depend on the amount of losses in the water 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 thermal power plants account for most of the water 

withdrawn while the amount of water required by wind, solar, and hydroelectric power stations is 

relatively small. (Sometimes the water evaporated in reservoirs of hydroelectric power stations are 

reckoned as water requirements of electricity production, but we do not take this into account in our 

study). In this context, a thermal power plant is a power-generating plant which 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 the 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 being replaced by tower cooled plants. Obviously, 

another crucial driving force is the magnitude of electricity produced at thermal power plants and 

how this will change in the future. 

2.3 Manufacturing Sector 

Manufacturing activity accounts for about 13 percent of the total water withdrawn in the Europe-30 

in 2000 (Figure 2). The intensity of water use [m3

/(1000 € gross value added)] varies tremendously 

from industry to industry. For example it is around 138 m3

/(1000 € gross value added) in the paper 

industry and only 1 m3

/(1000 € gross value added) in the textile industry (values with respect to 

Turkey Sweden

Germany Belgium

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 industry, the chemical industry 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 price and water usage in the entire 

manufacturing sector of Europe. 

The main driving force of water use in the manufacturing sector is the change 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 the 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-intensive industries such as electronics, will affect 

overall water use by manufacturing. 

2.4 Agriculture Sector 

Agriculture accounts for about 32 percent of the total 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 accounts for most of the water 

used in this sector, followed by livestock water use. 

The amount of water required for irrigating 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 estimate the country scale water withdrawn 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 changes in the extent of irrigated land and in the 

improvement of irrigation efficiency will also drive 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 increased three-fold between the 

1960s and the end of the century. In general the expansion of irrigated area in Europe shows a clear 

upward trend between 1960 and 1990 (Baldock et al. 2000) and declined or stabilized 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 particularly high in southeast Romania 

and northern Italy. High concentrations 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

year

area equipped for irrigation [1000 ha]

Figure 4. Extent of irrigated land 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 arable 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 particular 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 account 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 not feasible here for three reasons. First of all, 

while some Europe-30 countries have detailed data on driving forces, most do not. Second, the short 

time available for this study (11 months) made it infeasible to identify and 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 relationship between all driving forces and 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 obviously determine the magnitude of water 

use in the domestic sector. Population assumptions 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 taken into account as an indirect driving force of water use in 
European 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 future population estimates among other factors. 

Likewise, changing population is indirectly 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 water use in Europe it has been 

observed that water use tends to increase as a country becomes wealthier and then it levels off 

and in some cases declines. Hence changing income is an important driving force of future 

water use. Per capita income is used in the WaterGAP model to compute per capita water use in 

the domestic sector. (Other variables are also important as described in Section 3.2.3). Income 

is an indirect driver of water use in the electricity production sector because assumptions for 

future electricity use (used to compute future 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 facilities. The WaterGAP model uses 

assumptions about future thermal electricity production (and other variables as explained in 

Section 3.2.4) to drive calculations of water use in the electricity 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-through or tower) is an important determinant 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 manufacturing output in a particular industry is an 

important determinant of water use by the manufacturing industry. The WaterGAP model uses 

assumptions of future manufacturing output (in the form of gross 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 assumptions about the future coverage of irrigated 

area (and other data, as described in Section 3.2.6) to compute water use for irrigation. 

(g) Climate change: Not only the extent of irrigated land, but also climate is an important driver of 

irrigation water requirements. The WaterGAP model takes into account local climate (see 

Section 3.2.6) in calculating irrigation water requirements. 

(h) Number of livestock: Water use by livestock in a country is obviously driven, among other 

factors, by the number of livestock. This driving 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 technological change on improving 

water use efficiency is taken into account 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 scenario approach and a modeling 

approach. The scenario approach was chosen to combine 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 alternative scenarios. The modeling approach was selected 

to quantify the current and future European water 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 more driving forces that have an influence on 

future water use. We further used newly available European data to improve previous Europeanscale estimates of future water use in the domestic, manufacturing, and 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 environmental problems, particularly those 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 trends 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 simulation. In order to be meaningful to science and 

policy, scenarios must be based on a set of assumptions and/or theories of the key relationships and 

driving forces of change that are coherent, internally consistent, reproducible 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 depends on the goals of the scenario exercise. In this study, the EEA 

needs numerical estimates of future water use indicators for its regular environmental 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 circumstances 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 European 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 water situation in Europe and 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 services 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 Europe 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 availability in Europe and the world up to 2025 

(WBGU, 1999). 

WaterGAP is used to compute both water use and availability on different scales within Europe. It 

consists of two main components: a Global Hydrology Model to simulate 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 determine both the water withdrawals and water 

consumption in the household, electricity, manufacturing, irrigation, and livestock sector. In this 

context, water withdrawals depict the total amount of water used in each sector while the 

consumptive water use indicates the part of withdrawn 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 environment for subsequent use. 

3.2.2 WaterGAP: Water Availability 

The aim of the Global Hydrology Model is to simulate the characteristic 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° (geographical longitude and latitude, respectively) 

which covers the entire global land area except Antarctica (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 cells is defined by a global drainage direction 

map (DDM30) which indicates the drainage direction of surface water (Döll 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 areas is described by a 

canopy water balance (representing interception) and a soil water 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 balances incoming precipitation with actual 
European Outlook on Water Use Final Report 11

evapotranspiration and total runoff. Then, the total runoff from land area is divided into surface 

runoff and groundwater recharge, using information on cell-specific slope characteristics, soil 

texture, hydrogeology, and the existence 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 freshwater bodies is defined 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 freshwater bodies. In the model, it is distinguished 

between ‘local’ and ‘global’ open freshwater bodies. In contrast to the local lakes and wetlands, 

which only consider flow-through processes within a cell, global open freshwater bodies are 

additionally flowed through from neighboring cells. The runoff produced within the cell and the 

volume of water coming from upstream cells is transported 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 precipitation, potential evapotranspiration, and 

temperature for each grid cell. As climate input, the data by New et al. (2000) provide observed 

monthly values of precipitation, temperature, number of wet days, average daily sunshine hours, 

cloudiness, and global radiation, interpolated onto a 0.5° by 0.5° grid and for each of the years 1901 

to 1995. In the Global Hydrology Model, the calculations are performed on a daily resolution. 

Synthetic daily precipitation values 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 precipitation, 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 climate projections from general circulation models 

(GCMs). 

The Global Hydrology Model is calibrated against long-term average annual discharges measured at 

724 gauging stations world-wide, the drainage areas of which cover half the global land 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 annual withdrawals and consumption of water by 

households and small businesses. The basic approach 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 the approach described in Alcamo et al. (2000, 2003a, 

b). Changes in water use intensity 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-wide values are allocated to grid cells within the country based on 

population density which, in turn, is aggregated from the CIESIN world 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, water consumers tend at first towards a more waterintensive lifestyle (washing machines, dishwashers, more bathrooms, more car-washing). Finally a 

maximum level is reached after which 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) changes with income (GDP/cap). (See Figure 6). 
European Outlook on Water Use Final Report 12

Figure 6. Conceptual model of structural change in the domestic sector. 

The relationship between water intensity and income is derived for each country by fitting a 

sigmoid curve to historical data from each country: 

( ) 



 





⋅ = + ⋅ − − ⋅

cap year

m DSWI DWSI e GDP

3

min

2

1 γ α (1) 

where: 

DSWI = Domestic structural water use intensity 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] 

DWSImin = 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 states covering up to forty years in the past. Figure 7 gives an 

example of the fitted curve for Germany. (Note that the water intensities shown in Figure 7 are not 

the observed water intensities. These are adjusted data from which the estimated effect of 

technological improvements in water use efficiency on past water intensities have been subtracted. 

Hence the water intensities in these graphs are somewhat higher than the observed per capita water 

use.) 

Historical/Current Trends 

domestic structural water use intensity 

[(m3/(cap ⋅ year)] 

Scenarios 

? 

Today 

GDP/cap 

sigmoid curve 
European Outlook on Water Use Final Report 13

Figure 7. Structural change in water intensity in the domestic sector in Germany. Source: 

DESTATIS3

. 

To evaluate the fit of the curves, we use the index of agreement of Willmott (1984) which is 

suitable for evaluating sigmoid curves. The resulting index of agreement for each country is given 

in Table 2. The index of agreement varies between 0.0 and 1.0, where a value 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 study, the index of agreement is higher than 0.80, for 

50% the index is higher than 0.90. (See Table 2 and Appendix A). The calibrated curves were used 

for almost all European countries to compute future 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 data 

domestic 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 Republic, 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 drastically changed after 1990. For all 

countries but Turkey, this could be explained by the transition from a socialist to a market 

economy; in the case of Turkey, historical data show the same trend. 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 insight into the direction 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. 

Two extreme assumptions are shown in Figure 8 for the example of the Czech Republic. The 

bottom flat curve assumes that domestic 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 assumption 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 water 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 assume 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 scenario 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 the domestic sector and in other sectors to account 

for the important effect that improving technology tends to improve water use efficiency. 

Continuous improvements in technology make appliances and industrial processes more water 

efficient and hence, contribute to reductions in water use. (See Figure 9). 

Czech Republik

0

20

40

60

80

100

120

140

1960 1980 2000 2020 2040

year

domestic water use 

intensity [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 convergence 
European Outlook on Water Use Final Report 15

Figure 9. Technological improvements leading to higher 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 use intensity (See Figure 

10). Technological improvements are included in calculations of water use by specifying the rate at 

which new water using devices become more efficient over time. For every scenario, this rate of 

efficiency improvement (technological change) is specified in Equation (2): 





 





⋅ = ⋅ cap year

m DWI DWSI TchD

3

(2) 

where: 

DWI = Domestic water use intensity for each country [m3/(cap ⋅ year)] 

DWSI = Domestic structural water use intensity for each country [m3/(cap ⋅ year)] 

TchD = 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)] 

Time 
European Outlook on Water Use Final Report 16

3.2.4 WaterGAP: Water Use for Electricity Production 

The objective of this submodel is to compute water use for producing electricity. Here, the model 

simulates the amount of water withdrawn and consumed for cooling purposes in the electricity 

sector. (Some of the water is converted to the steam which drives the generator producing the 

electricity). Since thermal power plants4 use freshwater for cooling we calculate location-specific 

annual values for water withdrawals as well as water consumption. The allocation of the water used 

for cooling purposes to the global grid with a spatial resolution 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/MWh). The total annual thermal 

power plant water withdrawal (TPWW) in each grid cell is then calculated as the sum of the 

withdrawals of all power plants within the cell (Vassolo and Döll, 2004): 





 



 = ∑ ⋅ ⋅ = year

m TPWW EP WI CS TchTPi i

n

i

i

3 ( )

1

(3) 

where: 

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

WIi = Station-specific water withdrawal intensity [m3/MWh]. This figure depends on the 

cooling system of the plant, CSi

TchPi = Technological change for water cooling 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 consumption 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 EPi (Equation (3)). 

The technological change that will lead to a higher water use efficiency is taken into account as the 

factor TchPi. Further, TPWW depends on the water use intensity which is solely impacted by the 

cooling system of the power station. In this approach, two types of cooling systems are 

distinguished: i) the ‘once-through flow’ system and ii) the ‘tower cooling’ system. In contrast to 

the once-through flow system, where the cooling water is returned to the river after it has cooled 

down the condenser, the water in a tower cooling system flows in a closed circuit. As a result, the 

water use intensity of a once-through flow cooling system is much 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 evaporation 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 produce the necessary thermal energy. 
European Outlook on Water Use Final Report 17

- 180 m3/MWh for power plants with once-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 systems 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 information on the name of the station, 

installed capacity, year of connection to the net, fuel type, and cooling type. All these values are 

based on statistical data from 1995. Unfortunately, the exact geographical locations of the power 

stations are not included. To determine the geographic coordinates of the stations, the database of 

foreign geographic features (NIMA – National Imagery and Mapping Agency, 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 taken into account in this study. Sources: UDI (2000) 

and NIMA (2000). 

To validate the estimated water withdrawals for electricity 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

published i published i

n

i

calculated i published i

PWW PWW

PWW PWW

ME (4)

where: 

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

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

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

n = Number of countries 

The overall model results show a ME of 0.99. It is, thus, concluded that the applied methodology 

leads to an adequate evaluation of the spatially distributed water withdrawals for power plants. 

Figure 12. Comparison of simulated and published water use in the electricity production sector and 

model efficiency. 25 European countries are taken into account5

. 

3.2.5 WaterGAP: Water Use in the Manufacturing Industry 

The objective of this submodel is to compute water used by the manufacturing industry. To take 

into account the great diversity of industrial processes and the variety of input and output 

specifications, the manufacturing water use model distinguishes between 6 manufacturing 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 line
European 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 sectoral 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 total manufacturing water withdrawal. 

For each of these sectors the model simulates the amount of water withdrawn and consumed in 

production processes, except for cooling for power generation. For most of the countries, water 

withdrawal per sector is available 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 the sector-specific water use intensity SMWI. The 

model then takes SMWI and multiplies it with the future sector-specific GVA. Technological 

improvements are taken into account by a sector-specific technological change factor (as specified 

in the scenarios). To obtain the total manufacturing water withdrawal at national level, the sum over 

the six sectors is computed according to Equation (5): 





 



 = ∑ ⋅ ⋅ = year

m MWW SMWI TchM GVAi

i

i i

3 6

1

(5)

where: 

MWW = Manufacturing water withdrawal per country [m3/year] 

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

TchMi = 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, the 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 assumed to be distributed among the grid cells of a 

country proportional to its urban population. 

Base year data (year 2000) for water withdrawals are taken from EUROSTAT and other national 

statistical agencies. About one-half of the Europe-30 countries have sector-specific water 

withdrawals for the base year. For the remaining countries, total manufacturing water withdrawals 

are distributed to the different sectors 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 extrapolated based on historical data (see Appendix B). 

3.2.6 WaterGAP: Irrigation Water Use 

The objective of this submodel is to compute net and gross irrigation requirements which reflect an 

optimal supply of water to irrigated crops. In this context, ‘net irrigation requirement’ refers to the 

part of the irrigation water that is evapotranspirated by plants, while ‘gross irrigation requirement’ 
European Outlook on Water Use Final Report 20

refers to the total volume of water that is withdrawn from its source (Döll and Siebert, 2002; 

Alcamo et al., 2003a). The ratio of net to gross irrigation requirement is called ‘irrigation water use 

efficiency’. This concept is similar to the water use efficiency of the previous sectors described. 

In contrast to the other water use models, the irrigation model computes monthly rather than annual 

results. The model calculation is based on a global map of irrigated areas (Döll and Siebert, 2000) 

with a spatial resolution of 0.5° by 0.5° (geographical longitude and 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 per unit irrigated land is a function of climate, 

cropping intensity, and crop type (distinguishing rice and other crops). First, the cropping patterns 

for each grid cell with irrigated land are modeled using a rule-based system, among other things 

considering data on total irrigated area, long-term average temperature and cropping intensity. In 

general, cropping intensity refers to the average number of crops that are consecutively grown 

within a year, and set to 1 for European countries. The cropping pattern describes whether rice or 

other crops or both are irrigated and whether there 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 two initial steps, the net irrigation requirement is 

computed for each day of the growing season similar to the CROPWAT (Smith, 1992) approach: 





 



 = ⋅ − d

mm IRnet kc Epot Pavail if kcEpot > Pavail (6)

IRnet = 0 if kcEpot ≤ Pavail

where: 

IRnet = Net irrigation requirement [mm/d] 

Epot = Potential evapotranspiration [mm/d] 

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

kc = Crop coefficient, depends on the growing stage of the crop [-] (Doorenbos and 

Kassam, 1979) 

Equation (6) indicates that the net irrigation water intensities are calculated as the difference 

between crop-specific potential evapotranspiration and the precipitation available to the plant. The 

crop-specific potential evapotranspiration is described by the product of kc and Epot, in which a daily 

potential evapotranspiration is computed according to the Priestley-Taylor formulation as a function 

of net radiation and temperature. Finally, gross irrigation requirement is calculated by dividing the 

net irrigation requirement by the efficiency of irrigation water use, a value that depends on 

irrigation technology and management (see Equation (7)). 





 



 = d

mm

eff

IR

IR

IR

net

gross (7)

where: 

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

IRnet = Net irrigation requirement [mm/d] 

effIR = Irrigation field efficiency [-] 

The irrigation field efficiencies vary regionally between 0.5 and 0.65 in the Europe-30 region. Here, 

higher efficiencies are estimated for southern countries because these countries make use of water 

saving systems (e.g. drip systems instead of sprinklers). With respect to climate as a main driving 

force on the irrigation water requirement, monthly temperature and precipitation values are taken 

into account on a 0.5° by 0.5° global grid (geographical longitude and latitude, respectively). 

Today’s climate is depicted by a 30-year time series (climate normal, 1961-90) of observed monthly 

data by New et al. (2000). To derive appropriate future scenarios, today’s climate is scaled by 

applying changes projected by GCMs. Next to the climate input, the rate 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, irrigated areas and gross irrigation requirements were 

compared with independent data of the year 2000. Data regarding irrigation 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 irrigation 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, industrial 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-specific water use intensity 

[m3/(head⋅year)]. 

To quantify livestock-specific water use intensities, 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 water use (UNEP, 2002; Henrichs et al., 2002; Alcamo 

et al., 2000): 

1. The reliability of estimating domestic water use has been improved by calibrating the model to 

newly available data on historical trends of domestic water use on a country scale in Europe. 

Model calculations have been shown 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 time 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 with independent country scale estimates. (See Section 3.2.4). 

3. Estimates of future water use in the manufacturing 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 European agriculture has been tested by comparing 

WaterGAP calculations to data from several European 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 when interpreting and using scenario results. (See 

Chapter 7). These uncertainties should be addressed in follow-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) and 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 current 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 the Long Range Energy Modelling scenario project 

(LREM-E), commissioned by the Directorate-General 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 development of this outlook in the 

context of the LREM contract with the Directorate-General for Energy and Transport. The PRIMES 

Energy System Model was used to develop the scenarios. 

4.1 The World of the Baseline Scenario – 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 between the old and new EU countries, and markets in these countries 

expand. Exports to other world regions from Europe-30 also increase. Mobility of workers to 

booming industrial areas reduces unemployment and increases the consumer spending of workers. 

Following these and other factors, the economy in the Europe-30 grows at a rate of 2.3% per year 

between 2000 and 2030 as compared to 1.5% per year in the 1990s. Economic growth is 

particularly strong in the ‘new’ (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 population 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 example, 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 decline. 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 expansion 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 and pulp, chemicals, food products), water use in the 

manufacturing sector grows. Additionally, the higher standard of living and increased 

manufacturing output requires more electricity production at all power facilities, including thermal 

power stations. The increased electricity 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, many older power stations are also phased out and all new power 

stations in Europe have tower cooling which drastically lowers water withdrawals compared to the 

older stations that had once-through cooling. As a result almost all countries have declining water 

use in the electricity production sector in the 2010s and 2020s. 

The economic expansion also affects the agricultural sector. Increasing income raises food 

consumption and this leads to a greater demand for food grown on irrigated land. This larger 
European Outlook on Water Use Final Report 24

domestic food demand, combined with growing food exports from Europe lead to a vast expansion 

of irrigated cropland in many Europe-30 countries. 

Higher overall industrial activity is accompanied by an acceleration of investments in new 

technologies and improved management of businesses, industrial processes and agricultural activity. 

A spinoff of this ‘technological improvement’ is improved efficiency of water use in all sectors. For 

example, fewer raw materials are used for manufacturing chemicals and this is accompanied by a 

reduction in water requirements for chemical manufacturing processes. Another example is that 

water-intensive traditional flood irrigation is replaced on many farms by water-saving sprinkler 

irrigation. As a result of these changes, water use becomes more efficient at a faster rate than in the 

last decades of the 20th 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 increase even faster than anticipated back in the 

1990s. However, not all air pollution policies are abandoned in Europe so some renewable energy 

continues to penetrate the energy market as a tactic 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 21st century. 

Continuing climate change leads to a somewhat drier climate in Southern Europe and wetter climate 

over the northern Europe-30 countries. Mean annual 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 data. The trends in population 

are driven by on-going economic growth. Table 3 shows the population levels and growth rates of 

the Europe-30 countries, aggregated 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. Regions 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 differences in the growing rates and contrary trends 
European Outlook on Water Use Final Report 25

occur among the different regions. After 2000 the Northern 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 assumed up to 2010. Between 2010 and 2020 

the development in population almost stagnates and declines thereafter by 0.11% per year. The New 

EU Member States face a considerable reduction in population. The population decreases by 5.6 

million inhabitants between 2000 and 2030. A further increase of the EU Candidate States’ 

population by some 19 million people is projected between 2000 and 2030, 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 sectoral projections from 

different sources, including the European Commission’s Directorate-General for Economic and 

Financial Affairs (Economic and Financial Affairs DG), Member States’ stability programs and 

long-term projections, macroeconomic forecasts from WEFA (now integrated into DRI-WEFA6

), 

and results from the GEM-E37

 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 slowdown 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 region, 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 Europe 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. Much 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 integration of these countries into the EU. 

Nevertheless per capita income in these regions in 2030 remains considerably lower than in other 

EU regions (Table 4). 

 

6

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

7

 GEM-E3. General Equilibrium Model for 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) first rises as income increases, then stabilizes and 

in some countries drops. This relationship is confirmed by historical data 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 depicts the change in water intensity as income 

changes in a particular country. (See Figure 6 and Figure 7). For the baseline scenario we use the 

sigmoid curves to estimate future water intensities corresponding to future income in a particular 

country. 

In the case of the Czech Republic, Estonia, Hungary, Latvia, Lithuania, 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 with 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 electricity 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 environmental areas. Regarding climate policy, it assumes that the 

Kyoto Protocol will not be implemented and that greenhouse gas emissions will not otherwise be 

controlled. Thermal electricity production increases by 54% between 2000 and 2030 in the Europe30 countries. During the same period thermal electricity production increases by 36% in the 

Northern Europe countries, by 55% in the Southern Europe countries, 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 Member States and the EU Candidate States is 

attributed to higher economic activity over the scenario period, leading to increased use of electrical 

appliances in households and service industries (EU, 2003). 

Table 5. Projected thermal electricity 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

Northern 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 

New 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 electricity 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-cooling is an important 
European 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 age 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 production is a major driving force of water use in 

manufacturing. The assumptions for the economic growth of the industry sector for the EU15 

countries reflect the trend of structural changes in developed economies as well as aspects of 

international trade and dematerialization (EU, 2003). 

To give an overview of the projected GVA, the values for Northern Europe countries are given in 

Table 6. The GVA projection for the other three European regions are presented 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 sectors in the Northern Europe economy. Source: 

EUROSTAT, Economic and Financial Affairs DG, PRIMES. Regions are defined in Table 1. 

GVA [109 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 paragraphs 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 the 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 increased GVA in the manufacturing sector. In 

the Northern Europe countries, the chemical industry is one of the fastest growing industrial sectors 
European Outlook on Water Use Final Report 28

with an annual increase of 2.4% between 2000 and 2030. By 2030, the chemical industry continues 

to account for 12% of the total manufacturing GVA as in 2000. 

The non-metallic minerals sector accounts for a relatively small share 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 decade (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 for 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 largest 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 explicitly 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 withdrawals 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 extent of irrigated land, detailed European-specific projections are not 

available. Here, we use a variety of sources for deriving assumptions of future irrigated land. 

Two major variables concerning irrigated area must be specified. The first is the area equipped for 

irrigation which is the area which is set up for irrigation but not necessarily irrigated. The second 

important variable is the percentage of equipped area exploited for irrigation. This is important 

because a variety of sources confirm 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 equipped irrigated area was actually used 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 land we adapt assumptions from a 

global study presented in the ‘Global Environment 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 European countries contained in Baldock et al. (2000) and Magat and 

Vallée (2000). For example, the change in irrigated area is of the same direction (increasing or 

decreasing) for two-thirds of the countries considered by all three references. 
European Outlook on Water Use Final Report 29

Table 7. ‘Area equipped for irrigation’ and the ‘percentage of equipped area exploited for irrigation’ 

(base year 2000). Sources: (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). 

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 

Norway 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 70 
European Outlook on Water Use Final Report 30

Table 8. Baseline (LREM-E) scenario assumptions for 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 

Norway 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 irrigation (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 data were provided by IIASA. The 

projection does not include the effects of the ‘Common Agricultural Policy’ (CAP8

) 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 historical data reported by the United Nations Food and 

Agriculture Organization (FAO, 2000) and the International Fertilizer Industry Association (IFA, 

1998). In general, on the one hand, the future projections assume a decrease in the number of dairy 

(-15%) and non-diary cattles (-21%) in the Europe-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 projected to increase (12%) in the New EU Member 

States but decreases in Northern and Souterhn Europe. 

4.2.9 Technological change – Improvements in water use efficiency 

Also important for determining future water are the future rates of technological change that lead to 

technological improvements and an increase in water use efficiency. Continuous improvements in 

technology make water-using appliances 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 only in a reduction in water use (See Figure 9). 

Technological improvements are included in calculations of water use by specifying the rate at 

which new water using devices become more efficient over time. For every scenario, this rate of 

efficiency improvement (technological change) is specified for every sector (domestic, electricity, 

manufacturing, and agriculture) and region. 

For the domestic sector of Northern and Southern Europe, technological changes continue at 1% 

per year over the entire scenario period. In the New EU Member States, a higher rate (1.5% per 

year) is assumed for the decade 2000 to 2010, reflecting the acceleration of economic growth during 

this decade. After this time period, when economic 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 rates are based on available 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 Masannek, 1990). According to this reference, a rate 

of efficiency improvement of 2% per year between 1980 and 2000 is used for the domestic sector 

and applied to Northern and Southern Europe. To take into account a lower development in 

technical improvement of water saving appliances, a smaller rate of 1% per year is used for the New 

EU Member States as well as for the EU Candidate 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 Europe, 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 replaced by more water-saving irrigation systems. 

Estimates of future water use efficiency rates for irrigation are derived from the GEO-3 ‘Market 

Forces’ scenario and specified 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 for calculating climate change. Climate change 

projections used in this study were calculated by the IMAGE 2.2 model 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). The concentration of the 

greenhouse gases increases up to nearly 1000 ppm CO2 equivalents under the baseline scenario 

(‘CO2 equivalents’ takes into account all greenhouse gases addressed by the Kyoto Protocol), and 

stabilizes at about 550 ppm under the climate policy scenario. However, 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 2100

concentration (ppm)

LREM-E

SEP

Figure 14. Atmospheric GHG concentration (CO2 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 (temperature and precipitation) are derived from the IMAGE 

2.2 model in combination with results from the general circulation model (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 future and present-day precipitation. An exception 

to this rule occurs when present-day precipitation is close to zero (< 1mm); in this case the 

respective value is added. Following this method, monthly 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 calculated for the baseline (LREM-E) scenario; 2030 

projections compared to today’s level. 

The map on the top of Figure 15 shows the increase 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 average annual temperature will increase between 

1°C and 1.25°C in 2030. Temperature 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 (LREM-E) scenario for 2030. The changes 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 average 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 scenario (SEP) is to investigate the impact 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 Change (ETC/ACC, 2004). The climate policy scenario 

assumes the same basic driving forces as the baseline scenario except that dastic climate policies are 

assumed (in terms of GHG emissions limits) which have direct effects on the fuel profile of the 

electricity sector and on the intensity of climate change. 

5.1 The World of the Climate Policy Scenario – A Qualitative Description 

This world resembles that of the baseline scenario in that the expansion of the EU and integration of 

Europe has turned out to be a stimulus for successful 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 effects. 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 electricity is produced by low or nocarbon fuels – natural gas, wind, solar and biomass. Producing electricity with wind or solar power 

has very low water requirements, and this also tends 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 slightly higher costs than current technologies and 

therefore the shift to renewable energy does not appreciably increase the operating costs of 

manufacturing nor the household expenses 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 use are achieved. As a result, water use efficiency 

improves rather rapidly and tends to lower water use. 

The implementation of stronger climate policies in Europe-30 and elsewhere in the world leads to a 

significant reduction in greenhouse gas 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 system. 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 domestic 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 scenario leads to a mix of fuels different from the 

baseline scenario. In particular renewable energies (solar, wind, biofuels) are introduced in order to 

reduce greenhouse gas emissions. Since much of this new renewable energy capacity is non-thermal 

solar and wind energy, the total thermal electricity generation is lower in this scenario than in the 

baseline scenario. (Table 9, Table 10). 

Table 9. Projected thermal electricity 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 thermal electricity productions expected for the 

climate policy (SEP) and the baseline scenarios (LREM-E) between 2000 and 2030. Although the 

thermal electricity production declines in all the regions, the largest reduction occurs in the 

Northern Europe countries (-16%). In Southern Europe the generation 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 production for the baseline (LREM-E) and climate policy 

(SEP) scenarios. Source: EUROSTAT, PRIMES. 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

Northern 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

New 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 density are the same as in the baseline scenario. 

Technological change – Improvements in water use efficiency 

Because this is a more environmentally-oriented scenario, we assume that society invests more 

heavily in improving technology so that greater efficiencies in energy, materials and water use can 

be achieved. Technological changes are assumed to improve water use efficiency at a faster 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 and Southern Europe and EU Candidate States) the 

assumptions for the SEP scenario are the same as for the baseline scenario. 

Assumptions for the technological development of water-saving appliances for the electricity sector, 

manufacturing sector, and agricultural 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 region 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 Europe-30 region, larger 

differences only occur in Southern Spain. 

The changes in long-term average precipitation vary between –17.8% and 14.2%. with a wetter 

climate in Northern Europe (> 5%) and a drier climate (< -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 calculated 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 difference in long-term average annual temperature (top map) and 

precipitation (bottom map) between the baseline (LREM-E) and the climate policy (SEP) scenario 

for the year 2030. The slightly higher atmospheric concentrations of greenhouse gases in the 

baseline scenario results in somewhat larger climate changes. Nevertheless, 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 distribution of the differences indicates a wetter 

climate in Northern Europe and a drier climate 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). Similarly, those regions with less precipitation in the 

future are drier in the baseline scenario than in the climate policy scenario (red colour in right map). 

But the difference in average annual precipitation between the LREM-E and SEP scenarios varies 

only from –7 mm to 8 mm per year. 

Figure 17. Difference between the baseline (LREM-E) and climate policy (SEP) scenarios. 

Differences in long-term average annual temperature (top) and precipitation (bottom). 
European Outlook on Water Use Final Report 39

6. SCENARIO RESULTS 

The scenario input data described in the previous chapters were taken as input into the WaterGAP 

model to compute future water use, water availability, and water stress in 5-year intervals until 

2030. Since the focus of the study was on water use, we first give the quantitative results for the 

baseline scenario, discuss the results of the climate policy scenario, and compare our scenario results with other published European studies. Subsequently, we present quantitative results of our 

scenarios for water availability and water stress. At the end, we discuss the policy relevance of our 

results with regard to the European Water Framework Directive. 

6.1 Water Use 

Country-by-country results for water use are presented 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 describing 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 Baseline and Climate Policy Scenarios’. 

Northern Europe 

The profile of water withdrawals in 2000 in Northern Europe region 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 future 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 withdrawals 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 2030

Water withdrawals [mio. m3/yr]

Domestic Manufacturing Electricity Agriculture

Figure 19. Computed water withdrawals for the baseline (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, and 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 increases and this tends to increase water use, but improving efficiency of 

water use in this sector tends to dampen the increase 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 sectoral changes. Water withdrawals sharply decrease 

as older power stations with once-through cooling are replaced by new ones with tower cooling 

which requires much smaller water withdrawals. (See Figure 19). Therefore, in the electricity 

sector, the expected water uses for 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 small 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 electricity 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 dominates water withdrawals (44 %), followed by the electrical production 

sector (23%), the domestic sector (22%) and manufacturing (11%). (See Figure 20). In Figure 21 

the computed water withdrawals per sector are presented 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-specific water withdrawals in Southern 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 2030

Water withdrawals [mio. m3/yr]

Domestic Manufacturing Electricity Agriculture

Figure 21. Computed water withdrawals for the baseline (LREM-E) scenario for Southern Europe. 

Changes in water use are similar to those in Northern Europe in that the most dynamically-changing 

sector is electricity production where older plants are replaced, especially 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 than in 2000 in the baseline scenario. 

Water withdrawals increase slightly, but continuously, in the manufacturing sector by 24% between 

2000 and 2030. In the domestic sector, water withdrawals increase slightly, and then stabilize for 

the same reasons as in Northern Europe. 

A variety of compensating changes go on in the agricultural sector. On the one hand, gross 

irrigation water requirements increase by 14% because 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, this 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% (including the expansion of irrigated areas) in 2030 compared to 2000. If 

we keep the irrigated area constant, a net increase of 5% in irrigation water 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 because the decrease in the electricity sector is 

compensated by an increase in water withdrawals in the agricultural sector. 

New EU Member States 

The profile of water withdrawals in 2000 in the New EU Member States is different from the 

previous two regions. Electrical production is the largest water-using sector as in Northern Europe, 

but it claims a higher percentage of total withdrawals (61%) than in Northern 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 claims 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 sector-specific water withdrawals in the New EU Member States in 2000. 

Sources: EUROSTAT and national Statistical Offices. 

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

0

5000

10000

15000

20000

25000

2000 2005 2010 2015 2020 2025 2030

Water withdrawals [mio. m3/yr]

Domestic Manufacturing Electricity Agriculture

Figure 23. Computed water withdrawals 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 and Southern Europe, water withdrawals decline in 
European 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 water withdrawal used for cooling puposes in the 

electricity production is 75% lower in the baseline projection (2030) than in the year 2000. 

Water withdrawals in the domestic sector steadily increase up to 2025 as per capita water use 

converges with the higher water use of Northern and Southern Europe by 2030 (see Sections 3.2.3 

and 4.2.3, Figure 23). In the case of convergence, the domestic water withdrawals 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 Section 7.2 we analyse the 

result of an alternative assumption, namely that per capita water use in this region remains at its 

current level. The increase in domestic water withdrawals is dampened somewhat by a continuous 

decrease in population which is the main driving force in this sector. Water withdrawals stabilize in 

the domestic sector by 2025 as the convergence to higher per capita water use is balanced by the 

decline in population growth. 

Water withdrawals strongly increase in the manufacturing 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 expansion of manufacturing production. 

Agricultural water use remains about the same because of compensating changes in this sector. – 

Higher temperatures tend to increase water requirements of irrigation, while increasing precipitation 

and improving water use efficiency tend to decrease these requirements. 

The temporal trend of total withdrawals is uneven over the scenario period as water withdrawals 

strongly decline in the electrical production sector while they sharply 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 resembles that of the Southern region since they are 

in similar climate zones. The profile is dominated 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 withdrawals per sector for the projected time period 

between 2000 and 2030. 

Water withdrawals by sector [%] in the EU Candidate 

Countries (2000)

16% 60%

9%

15% Agriculture

Domestic

Manufacturing

Electricity

Figure 24. Profile of sectoral-specific water withdrawals in the EU Candidate States in 2000. 

Sources: EUROSTAT and national 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 2030

Water withdrawals [mio. m3/yr]

Domestic Manufacturing Electricity Agriculture

Figure 25. Computed water withdrawals for the baseline (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 reasons as in the other regions (Figure 25). 

The manufacturing sector has the next biggest changes 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 agricultural sector have a small net increase (by 10% between 2000 and 

2030) for the same combination of factors as in Southern Europe. Water withdrawals tend to 

increase because a drier and warmer climate increases the per hectare water requirements of 

irrigation while the area of irrigation increases by 20% between 2000 and 2030. Withdrawals tend 

to decrease because of efficiency improvements in irrigation water use. 

Total water withdrawals slightly 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 baseline and climate policy scenarios 

Climate policy, as represented in the climate policy scenario, affects water use in two major ways. 

The first effect is obvious – the lower greenhouse gases in Europe and elsewhere slow down the 

rate of climate change and lead to more moderate changes in precipitation and temperature. These 

more moderate climate changes lead to more moderate changes in the amount 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 temperature would be a few tenths of a degree warmer 
European Outlook on Water Use Final Report 45

throughout Europe. The North would receive a few percent more millimeters of precipitation and 

the South a few percent less. That is, under the stronger climate change of the baseline scenario the 

North would become a bit wetter and the South a bit drier. We explained earlier that the difference 

is not big because there is enormous inertia built into the global climate system which means that 

that climate responds slowly to changes in greenhouse gas emissions. 

Figure 26 gives an overview of the amount of water used for irrigation in the base year (2000) and 

for the projected time horizon 2030 for both scenarios. 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 agriculture 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

region

water withdrawals [mio. m3/yr]

2000 LREM-E (2030) SEP (2030)

Figure 26. Computed water withdrawals for irrigation in the base year 2000 and in 2030 for the 

baseline (LREM-E) and climate policy (SEP) scenarios. 

Regarding the country scale, water withdrawals for irrigation, for example, in Spain are 23106 

million m3

 in 2030 under the baseline scenario, and slightly smaller 23007 million m3 in the same 

year (-0.4%) under the climate policy scenario because 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 all possible impacts of climate change on irrigation were evaluated 

(for example, the impacts of possible changes 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. The 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 directly or indirectly. Consequently the amount of 

water used for electricity production by power plants is smaller in the climate policy scenario than 

in the baseline scenario, and this reduces water withdrawals in the electrical production sector as 

shown in Figure 27. Hence, Europe-30 water withdrawals 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 Member 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

region

water withdrawals [mio. m3/yr]

2000 LREM-E (2030) SEP (2030)

Figure 27. Computed water withdrawals for the electricity 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 climate policy (SEP) scenarios are 

compared to other scenarios of European water withdrawals. 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 explorative 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 ‘Dialogue 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 to, 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 looks 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 first the global level and then at the regional level, 

e.g. Europe. In GEO-3 a set of four scenarios has been developed: (1) ‘Market 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 intermediate rates of technological 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-conserving 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 population growth similar to the first two scenarios, 

an intermediate economic growth rate, a much higher use of sustainable energy, and a high level of 

water-saving behavior. 

An Integrated Analysis of Changes in Water Stress in Europe (Scenario 5 in Figure 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 combination of both, changes in future water withdrawals and future water availability, pressure on European river basins was estimated. With the focus on three time slices, model calculations were done for 1995 (as base year), 

the 2020s, and the 2070s. Figure 28 shows the ‘Baseline A’ scenario from this study (labeled Sce-
European Outlook on Water Use Final Report 47

nario 5). This scenario has socio-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 withdrawals 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 Planck 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 scenario has higher population growth and lower economic growth in Europe than 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 scenario

change in total water withdrawals to 

base 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 results 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 and economic growth and less attention is given 

to water conservation. 

Results in this report also fall mid-way between a set of scenarios developed by the Dialogue on 

Water and Climate (Scenarios 6 to 9). These scenarios are less extreme than the GEO-3 scenarios 

because they have less extreme assumptions 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 this is an important factor in this report, other 

factors are also important, for example the transition from once-through cooling 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 check country-scale calculations of 

domestic water use in Europe. Therefore it is likely that estimates of future domestic water use in 

the Baseline A scenario were much 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 compared the results of the baseline 

and climate policy scenarios with forecasts obtained by Shiklomanov and Rodda (2003). To obtain 

future values of water withdrawals 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 Monetary Fund (IMF, 1994) trends for the GDP/cap. The growth in 

industrial water use was derived for the year 2025 from data relative to 1990 (Strzepek and Bowling, 1995). Data on irrigated areas based on information given in Zonn and Nosenko (1981) and 

FAO (1995) and the extent of future irrigated areas was calculated for the European countries taking into account economic and population growth. These data were used to extrapolate future irrigated areas and future irrigation water withdrawals. As a result, the dynamics of water withdrawals 

and water consumption are given by sector and by continent up to 2025. Based on these assumptions, Shiklomanov and Rodda (2003) calculate that, in Europe, total water withdrawal will continuously increase and will be 21% higher in 2025 compared to 1995. 

However, it should be noted that the main goal of the 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 based on extrapolation of actual trends 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, which 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 availability for European river basins under the baseline 

(LREM-E) scenario compared to today’s level. 

Under the baseline scenario water availability declines in parts 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 throughout the rest of Europe despite increasing temperatures because 

precipitation also increases significantly. The increase 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 climate 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 available 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 differences should lead to a higher water availability 

in the climate policy scenario, but these are not observed because they are so small. Over the rest of 

Europe, water availability should 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 baseline (LREM-E) and climate policy (SEP) scenarios. Differences 

in changes in average annual water availability for European river basins. 

6.2.2 Water Stress 

Water stress is a measure of the amount of pressure put on water resources and aquatic ecosystems 

by the users of these resources, including municipalities, industries, power stations and agricultural 

users (see, for example, Alcamo et al., 2000; Vorösmarty et al., 2000; Cosgrove and Rijsberman, 

2000). To estimate stress we use a conventional indicator, 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 depleted, therefore limiting further use of these water 

drainage resources to downstream users. This indicator has the advantage of being transparent and 

computable for all river basins. 

Figure 31 (left map) depicts current water stress conditions for the different drainage basins of 

Europe. (Current conditions are defined as water use for the year 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 area (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 areas that earlier had low water stress in eastern 

Turkey, now have medium stress because of increasing 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 south 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 baseline scenario, and is therefore not shown. 

Figure 31. Water stress under current conditions and under the baseline scenario. Top: Current conditions. Bottom: Baseline scenario, 2030. 
European Outlook on Water Use Final Report 51

6.3 Contribution to the Water Framework Directive 

The Water Framework Directive 

The Water Framework Directive (WFD) entered into force in October 2000, breaking a new ground 

in the European water policy. The WFD establishes 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 and 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 discharges, emissions and losses of priority substances and the cessation or phasing-out of discharges, emissions and losses of the priority hazardous substances; 

(d) To ensure the progressive reduction of pollution of groundwater and 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 each 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 consequence, administrative or political boundaries become less important 

in their respective countries compared to natural geographical 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 objective by calculating water stress in all river basins 

of the Europe-30 region, thereby addressing the question of good ecological 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 water availability and use. In the following, we list the contribution 

of this study to the individual 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) To promote sustainable water use based on long-term protection of water resources. Water use 

has been calculated under current conditions and two different scenario assumptions for four 

distinct economic sectors per country and been attributed to all river basins within Europe-30 

regions. Together with the water stress of the river basin and the scenario information, sectorspecific policy measures can be designed to promote sustainable water use. 

(c) To aim at enhancing protection and improvement of the aquatic environment through specific 

measures for the progressive reduction of discharges, emissions and losses of priority substances and the cessation or phasing-out of discharges, emissions and losses of the priority 

hazardous substances. The scenarios compute increases (or decreases) in water availability and 
European 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 improving the aquatic environment. 

(d) To ensure the progressive reduction of pollution of groundwater and to prevent its further pollution. Although this study does not explicitly address water quality, water use and discharge to 

surface water bodies and groundwater from the agricultural sector is calculated for current and 

alternative future climatic conditions. Based on the extent of irrigated areas and amount of water withdrawn, the agricultural return flow (water withdrawal minus consumption) carries a 

specific pollution load of agrochemicals. The larger the extent of irrigated 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 agricultural policies. 
European Outlook on Water Use Final Report 53

7. UNCERTAINTY AND SENSITIVITY OF RESULTS 

The scenario approach used in this report addresses 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 pathways are more feasible, or more uncertain, than 

others. Here is a list of some of the factors determining water use that are particularly uncertain. In 

principle, reducing the uncertainties of these factors will increase the reliability of the scenarios and 

lead to better estimates of future water use. 

Domestic – In most European countries the relationship 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 possible to define a relationship between income and 

water use. For these countries more detailed studies are needed to identify the factors that help 

explain historical and future trends 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 (m3 per gross value added) is a major 

uncertainty in most countries. But perhaps more important is the water use of industries that are not 

now important but will become important over the next 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 tower versus once-through cooling, and their future 

geographic location. Also important is the uncertainty of future thermal electricity production. 

Agriculture – Major unknowns in the 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 the historical trend of per capita water use in the Czech Republic, 

Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Republic, and Turkey shows an important 

break after the 1980s. This obviously has to do with 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 direction 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 that per capita water use in these countries would 

converge with the average value of the other Europe-30 countries by 2030. Here we compare this 

assumption with the assumption that per capita water use in these countries remains constant at its 

year 2000 level. This would correspond 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 because 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 average. Hence assuming that per capita water use 

remains at its current level (the middle bar in Figure 32) leads to much lower water use than the 
European Outlook on Water Use Final Report 54

baseline scenario (left bar) which assumes that per capita water use will rise to the EU average in 

2030 (See Section 4.2). In the New EU Member States, 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 investigated in future water outlooks. 

New EU Member States: water use in the domestic sector

0

2000

4000

6000

8000

10000

2010 2030

Water 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 Lower 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 impact 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 climate policy scenarios (Section 4.2). These projections were produced by the PROMETHEUS model (Section 4.2). In the low economic growth variant, the annual average growth rate of GDP per capita in the Europe-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 distributed between the four Europe-30 regions. 

Greater reductions in economic growth rate are 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 the Europe-30 region under the low economic growth assumptions, 

1990 to 2030. Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES, PROMETHEUS9

. 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 

Northern 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

New 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 driving forces of different 

water-using sectors. 

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

• Electricity production sector: Along with slower economic growth, the production of electricity 

will also be lower than in the baseline and climate policy scenarios (See Appendix E). 

• Manufacturing sector: Consistent with the lower economic growth rate is a lower industrial 

output in terms of gross value added (See Appendix E). 

The difference between the baseline scenario and the low economic growth variant is very small 

(Figure 32) because for most countries 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, respectively. Figure 33 shows that water withdrawals are 

8% lower under the low economic growth 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 (population, 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 growth rates in the ‘low growth 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 2030

Water withdrawals [mio. m3/yr]

baseline low economic growth

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

EU Candidate Countries: water use in the manufacturing sector

0

2000

4000

6000

8000

10000

12000

2010 2030

Water withdrawals [mio. m3/yr]

baseline low economic growth

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

7.3 Sensitivity to Uncertain Future Irrigated Area 

The main driving force of changes in water withdrawals 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. 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 around the baseline scenario (which is the ‘reference’ variant): 

Lower variant: The ‘area equipped for irrigation’ (the total area of irrigation) and ‘percentage of 

equipped area exploited for irrigation’ (the small part that is actually 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 baseline 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 actually exploited remains constant). 

Higher variant: It is assumed that the area equipped for irrigation expands in several countries as in 

the baseline scenario, and that the percentage of exploited area also increases step-wise up to 100% 

from 2000 to 2030. This gives higher water withdrawals (in countries with 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 variant (right bar) leads to large differences with the baseline scenario (left bar). Only results for the New Member States 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 water 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 agricultural sector will decrease by 3% in 2010 and 9% in 2030 compared to 

the baseline scenario. But taking into account that the whole area equipped for irrigation will be irrigated (Higher variant), the amount of water used in this sector will increase by 49% in the year 

2030 (respective 15% in 2010). 

We have mentioned earlier that the future extent of irrigated area is an obviously important driving 

force, and this sensitivity analysis confirms this point. It is urgent in future water outlooks to improve projections of irrigated area, both the area equipped for irrigation 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 2030

Water withdrawals [mio. m3/yr]

baseline low variant high variant

Figure 35. Sensitivity analysis of the agricultural 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 Environment 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 availability 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), only two alternative scenarios 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 most 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 should be noted, however, that a much wider and more refined range 

of scenarios is possible, and that additional driving forces may also have a considerable influence. 

In the following, we summarize our main recommendations for such future studies. 

• Build multiple baselines. The terms of reference for this study called for the development of 

only one baseline. Unfortunately it is difficult to argue that one particular baseline scenario is 

more probable than another. Therefore it is common in international scenario exercises (e.g. the 

greenhouse gas emission scenarios of IPCC, 2000) to generate multiple baseline scenarios that 

indicate a range of plausible future developments. It is strongly 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 the New EU Member States is very uncertain. The 

EEA should give special attention to understanding trends in per capita water use in these 

countries in order to reduce these uncertainties and 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 about 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 difficult at this time to include 

price effects in estimates of future water use in Europe. The EEA should support the collection 

of European-wide data documenting the relationship 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 emerging 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 recommend that the EEA support detailed studies of 

the future importance of existing and emerging water-intensive industries. Information from 

these studies will improve estimations of the 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 available pan-European projections of this land. We 

recommend that the EEA support the development of detailed projections of future irrigated 

land that take into account economic, geographic and other factors. 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 technological 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 provides examples of changes in water use efficiency in all sectors 

over time. These data will afford a more solid basis 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 scenarios 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 were developed – a baseline scenario reflecting a continuation of 

current trends and a climate policy scenario assuming drastic 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 cooling, structural changes in domestic 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 considerable policy relevance. Due to the inherent uncertainties of such 

scenario studies covering 30 years into the future, we will attempt to qualify our conclusions by 

adding estimates of certainty based on expert judgement. 

• The trend of total European water withdrawals is downward. Under the two scenarios 

developed in this study, total water withdrawals in the Europe-30 countries decrease by 

approximately 11% between 2000 and 2030. These results are intermediate compared to 

previously published estimates. This will allow 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 Europe 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 expect (with low to medium certainty) that 

water use in the manufacturing and domestic 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 expect (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 conservation efforts in Europe on any individual sector. A panEuropean strategy to reduce water use should concentrate on different sectors in different 

countries, that is, it should take a multi-sector approach. Here, the implementation of the Water 

Framework Directive by individual countries becomes important and offers a good policy 

instrument to further water conservation efforts. 

• A river basin approach is also needed.. For administrative and technical reasons it makes sense 

to carry out water conservation programs on the country-scale. However, the river basin 

approach required by the Water Framework 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 rises 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 domestic water use stays at its current level 

in New EU Member States, then total water withdrawals in the domestic sector in 2030 will be 

about the same as those of the electricity production and manufacturing sectors taken together. 

One conclusion from these results is that intervening 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 their 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 stations will have tower cooling rather than once-through 

cooling. Tower cooling requires much lower withdrawals than once-through cooling. 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. Although water 

withdrawals decline, water consumption per unit electricity generated is much higher with tower 

cooling. This has to be taken into account when 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 sectors 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 decrease 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 technological improvements in these sectors, their water 

use would be from 34% to 56% higher. Therefore countries should support technological 

improvements in the water use sector in order to make use of these important 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 increasing tendency will be dampened somewhat by 

continuing improvements in the water use efficiency of irrigation. Countries may have to take 

this into account when formulating their agricultural 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 irrigated areas and amount of 

water withdrawn, the agricultural return flow (water 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 will have to take this into account when implementing the Water Framework Directive in order to maintain or improve the 

ecological and chemical status 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 climate 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 electricity production sector (medium to high 

certainty). Greenhouse gas emissions are reduced under this scenario by replacing fossil fuels 

with renewable energy. The introduction of renewable energy implies that some thermal power 

stations will be phased out or replaced by low water-using technologies, and this reduces overall 

water withdrawals (medium to high certainty). 
European Outlook on Water Use Final Report 62

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European Outlook on Water Use Final Report 67

 APPENDIX A: DOMESTIC WATER USE MODEL – CONCEPT 

OF STRUCTURAL CHANGE 

In the domestic water use model, changes in water use intensity are expressed by structural and 

technological changes. The concept of structural change is represented in the baseline scenario by a 

sigmoid curve which indicates how water use intensity (water 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 improvements in water use efficiency have been subtracted. This approach, using a sigmoid curve to describe the baseline scenario, has been used for 22 countries within the Europe-30 region. To evaluate the fit of the curves, 

we use the index of agreement of Willmott (1984) which is defined as follows: 

PE

n RMSE d

2

1 ⋅ = − (8)

2 2 2 RMSE = RMSEs + RMSEu (9)

where 

d = Index of agreement [-] 

n = Number of cases 

RMSE = Root mean square error 

RMSEs = Average systematic portion of RMSE 

RMSEu = 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, Lithuania, 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 described in Section 3.2.3. 

The following Figure 36 to Figure 65 show the baseline curves representing the domestic (structural) water use intensities for each country within 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 water 

use 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 water 

use 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 water 

use 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 water 

use intensity [m3/cap.year]

adjusted data baseline

index of agreement=0.908

Figure 39. Domestic structural water use intensity (baseline curve) for 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 water 

use 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 water 

use 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 water 

use 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 water 

use 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 national Statistical Office. 

Sweden

0

50

100

150

200

0 5000 10000 15000 20000 25000 30000 35000

GDP/cap. [Euro2000]

domestic structural water 

use 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 water 

use 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 national Statistical Office. 

Norway

0

50

100

150

200

250

300

350

0 10000 20000 30000 40000 50000

GDP/cap. [Euro2000]

domestic structural water 

use 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 water 

use 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 water 

use 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 water 

use 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 water 

use 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 water 

use 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 water 

use 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 water 

use 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

year

domestic water use 

intensity [m3/cap.year]

historical data non-convergence convergence

Figure 54. Domestic water use intensity (baseline 

curve) 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

year

domestic water use 

intensity [m3/cap.year]

historical data non-convergence convergence

Figure 55. Domestic water use intensity (baseline 

curve) 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

year

domestic water use 

intensity [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

year

domestic water use 

intensity [m3/cap.year]

historical data non-convergence convergence

Figure 57. Domestic water use intensity (baseline 

curve) for Latvia. Source: EUROSTAT and national Statistical Office. 

Lithuania

0

20

40

60

80

100

120

140

1985 1995 2005 2015 2025 2035

year

domestic water use 

intensity [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 water 

use 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

year

domestic water use 

intensity [m3/cap.year]

historical data non-convergence convergence

Figure 60. Domestic water use intensity (baseline 

curve) 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

year

domestic water use 

intensity [m3/cap.year]

historical data non-convergence convergence

Figure 61. Domestic water use intensity (baseline 

curve) 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 water 

use 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 water 

use 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 water 

use 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

year

domestic water use 

intensity [m3/cap.year]

historical data non-convergence convergence

Figure 65. Domestic water use intensity (baseline 

curve) 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 effect of improving technologies tend to improve water use efficiency. In this Section, the calculation of the historical technological changes in water use efficiency in the electricity and manufacturing sectors are described. 

All information about former technological changes were derived from data collected for Germany. 

 Historical technological changes of water intensity: Electricity production 

sector 

In the water use model of the electricity production sector, two water intensities are distinguished: 

the water use intensity for once-through flow cooling 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 electricity production because water is 

mainly used by thermal power stations. 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 technological changes for once-through flow cooling systems are not 

available. Figure 66 shows the water use intensities of thermal power stations 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 use intensity slows down since 1997. As a result, two 

time periods for the basic approach of technological changes are used: A first time period from 

1989 to 1997 and a second from 1997 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 compared 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 future 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

year

water use intensity [m3/MWh]

data

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

Figure 66. Historical technological change of water intensity 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

year

water 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 change of water intensity of tower 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 are determined for different manufacturing sectors (see Figure 68 

to Figure 73). The sectoral-specific water use intensities are calculated for each year as the quotient 

of the sectoral-specific production and the sectoral-specific water use. Time series for the time period between 1965 and 1995 (from DESTATIS and several statistical yearbooks of Germany) are 

taken into account. The historical technological changes are derived 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

year

water 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 technological change in water intensity of the manufacturing of food products, beverages, and tobacco, considering two time 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

year

water 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 historical technological change of water intensity of the manufacturing of textiles, considering 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

year

water 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 historical technological change of water intensity of the manufacturing of pulp, paper, publishing 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

year

water use intensity [m3/t]

water use intensity

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

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. 
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 year

water 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 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. 

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

year

water intensity [m3/t]

water use intensity

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

Figure 73. Determination of historical technological change of water intensity for the manufacturing 

of basic metals and fabrication of metal products, 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 force of water use in the 

manufacturing industry. The assumptions for the economic growth of the industry by sector for the 

baseline and climate policy scenarios are listed in Table 12 to Table 14 for 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 [109 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 [109 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 3.27
European 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 [109 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
European 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 regions. The water withdrawals are subdivided into 

four sectors: domestic, agriculture, manufacturing, and electricity. Table 15 shows the results for 

the domestic and agricultural sectors, Table 16 those for the manufacturing and electricity sectors. 

Table 15. Water use in 2030 (in million m3). Overview 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 1500 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 154189
European Outlook on Water Use Final Report 82

Table 16. Water use in 2030 (in million m3). Overview of the model 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 26186 
European Outlook on Water Use Final Report 83

 APPENDIX E: DRIVING FORCE 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 climate policy scenario. These projections were produced by the PROMETHEUS model. Table 17 to Table 20 present the gross value added for the 

low economic growth variant separated by manufacturing 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 separated by sectors in the Northern Europe economy (low economic 

growth variant). Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1. 

GVA [109 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 1.69
European Outlook on Water Use Final Report 84

Table 18. Gross value added separated by sectors in the Southern Europe economy (low economic 

growth variant). Source: EUROSTAT, Economic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1. 

GVA [109 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, Economic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1. 

GVA [109 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 2.98
European 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, Economic and Financial Affairs DG, PRIMES, PROMETHEUS. Regions are defined in Table 1. 

GVA [109 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 growth 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 production for the baseline scenario and low economic 

growth variant. Source: EUROSTAT, PRIMES. 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.