Seminar for the external evaluation of the preliminary results Madrid, October 27, 2008 OBSERVATORIO DEL AGUA FUNDACIÓN MARCELINO BOTÍN

WATER FOOTPRINT AND VIRTUAL WATER TRADE: POLICY IMPLICATIONS (Guadina Water Footprint) Alberto Garrido*, M. Ramón Llamas§ Consuelo Varela-Ortega*, Paula Novo*, Roberto Rodríguez Casado*, Maite M. Aldaya+ § Universidad

Complutense, Spain

*Universidad Politécnica de Madrid, Spain + Twente

Project Funded by

University, The Netherlands

Contents

Background and the Spanish context Motivation and objectives Conceptual framework M th d and Method dd data t sources Results Conclusions and discussion

Background • ‘Virtual water’ coined by Allan (1997, 1999) ‰Conceptually powerful and appealing ‰Empirically untested • Earlier studies by Chapagain and Hoekstra (2004) and Hoekstra and Hung (2005) ‰Very general quant evaluations ‰Very specific ones (coffee, tomatoes,…)

Background The Case for an application to Spain and the Guadiana

• Spatial and temporal diversity within the Spanish territory • Very active in farm trade (large importer and exporter) • Ministry Mi i t mandates d t th thatt WF calculations l l ti b be made d ffor River Basin Management Plans

⇒An ideal case study for an in-depth analysis of VW and WF

The Spanish Context Population change 1993-2001

Annual average Runoff

Objectives

1. Evaluate WF and VW, considering: ‰ Green-blue water components ‰ Time and spatial dimensions

2. Add the economic dimension to previous studies of WF and VW 3. Evaluate water scarcity in light of the evaluations of WF and VW 4. Draw water and agricultural policies lessons based on the WF and VW analysis

Conceptual framework (I) WFD EU Policies CAP National water policy

Cropping patterns

Livestock

Physical Land Temporal

Water uses Water Footprint (x,y, t) WTO

Water use

VWTrade ‘trade’

Drought cycles l

Technology Economic

Productivity

Climate change

Adaptation

Conceptual framework (II)

• Virtual water (embedded water, embodied water or hidden water) • The colours of water: green and blue (% vary significantly across time, province and species) • Virtual water ‘flows’ • Water footprint: Internal and external WF

Method (I)

• WF assessed from a top-down approach WF = (WU − VWE ) + (VWI − VWRE )

• Agricultural water use (WUa) n

[

]

WU a = ∑ CWU g*S t + CWU b*S iirr + LWU c =1

lgp

ETg = min (CWR,Peff )

CWR = ETo*K c

ETb = max ( 0 ,CWR-ET g )

Peff

CWU g = 10* ∑ ETg

Vg =

m =1 lgp

Y CWU b Vb = Y

CWU b = 10* ∑ ETb m =1

Agronomic and climatic parameters

Green and blue water evapotranspiration

Green and blue crop water use

CWU g

Green and blue virtual water content

Peformed for 93 crops 50 provinces and 10 years

Method (II)

• Virtual Water ‘Flow’ VW [ne , ni , j ] = V [ne , j ]× T [ne , ni , j ]

• Water and Land Apparent Productivity, economic value of farm output per m3 and per ha cultivated, lti t d respectively ti l

• Economic Value of Water • Only blue water is evaluated • Shadow price (scarcity value) refers to the marginal value of water (€ per m3, evaluated at basin level and for each year)

Method (III)

• Econometric approach • Hypothesis: water productivity’s dependent on water scarcity and blue-green water % • Model (panel / time series data) BWPit = α + β1SVit + β 2GB% it + ε it BWPit

SVit GB% it

inverse of blue water productivity 1000 m3/€ water scarcity value in €/m3 ratio: green crop water use/total crop water use

Method (IV) • Exchange terms of virtual water ‘trade’

VW t exp (€ / m 3 ) ETerms _ VWt = VW t imp (€ / m 3 ) • Macro-economy water dependence

VFt (m3 ) Dep _ ratiot = GNPt (€)

Data sources Data

Spatial dimension

Time dimension

Source

Climatic

Provincial

1997-2006

Meteorological Agency

Crop area and yield

Provincial

1997-2006

Ministry of Agriculture

Crop parameters

National

-----

Allen et al., 1998

Crop products

Provincial

1997-2006

Ministry of Agriculture

Livestock water use

River basin

2001

Ministryy of Environment

Industrial water withdrawal

National

1997-2004

National Statistics Institute

Urban water withdrawal

National

1997-2006

National Statistics Instit.

Trade

Provincial

1997-2006

DataComex

Crop market prices

National

1997-2006

Ministry of Agriculture

Industrial production

Autonomous Community

1997-2006

National Statistics Institute

Results 1. Water footprint and virtual water of Spain: hydrologic and economic perspectives 2. Water apparent productivity 3 Economic implications for water allocation: inter3. inter basin and intra-basin transfers 4. Does agricultural footprint depend on water scarcity? 5. Water exchange rates 6. Economic growth and the water footprint

Million m 3

1. Water footprint of Spain (Mm3/yr) 1,000 m3/year and person

50,000 45,000 40,000 35,000 30,000 25,000 20,000

Total Water footprint

Water footprint urban sector

Water footprint agricultural sector

Water footprint industrial sector

15,000 10,000 5,000 0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006 Year

Million m 3

1. WF agriculture and agricultural sector (Mm3/yr)

50,000

Water footprint agriculture

Virtual water imports agriculture

Water footprint agricultural sector

Virtual water exports agriculture

45,000 40,000 35,000 30,000 25,000

Net Imports

20,000 15,000 10,000 5,000 0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Year

Million m 3

1. Livestock water footprint (Mm3/yr)

50,000

Smaller footprint

45,000 40,000 35,000 30,000 25,000 20,000

Water footprint agriculture

Virtual water exports livestock

Water footrpint agricultural sector

Virtual water imports livestock

15,000 10,000

Net Exports

5,000 0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Year

2. Water apparent productivity in agriculture (€/m3)

Crop blue water use Crop green water use Water apparent productivity

12,000 10,000

4.5 4.0 3.5 3.0

8,000

25 2.5

6,000

2.0 1.5

4,000

1.0 2,000

0.5

Fo dd er Tu be Ve r ge ta bl es Vi ne ya rd

fru it

Fr es h

O liv es

fr u it s

Dr y

Ci tri cs

0.0

Ce re al s Pu lse s

ria lc

ro ps

0

In du st

Crop water use ((Million m 3)

14,000

Water apparent pro oductivity (€/m 3)

Year 2006

4,000

4.0

3,000

3.0

Vineyard

2,000

2.0

5,000

4,000

2.0

Crop blue water use

Olives

Crop green water use

1.8

Water Apparent Productivity

1.6 1.4 1.2

3,000

1.0 0.8

2,000

0.6 1,000

1.0

0

00 0.0

0.4

1,000

0.2 1999 2000 2001

2002 2003

0

2004 2005 2006

0.0 1997

1998

1999

2000

Industrial crops Crop blue water use 5,000

1.0

Crop green water use

0.9

Water Apparent Productivity

0.8

4,000

0.7 0.6

3,000

0.5 0.4

2,000

0.3 0.2

1,000

0.1 0

0.0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Water Apparent Productivity (€/m3)

1997 1998

2001

2002

2003

2004

2005

2006

Water Apparent Productivity (€/m3)

Water Apparent Productivity

Crop water use (Mm3)

Crop water use (Mm3)

5.0

Crop green water use

Crop water use (Mm3)

Crop blue water use

5,000

Water Apparent Productivity (€/m3)

2. Water apparent productivity in agriculture (€/m3)

3. Economic scarcity value of blue water use (M€/yr) Year

Blue water use (%)

1997 51,04% 1998 57,67%

64 32% 1999 64,32% 2000 59,94% 2001 59,86% 2002 57,47% 2003 59,49% 2004 58,84% 2005 75,67% 2006 63,37%

Green water use (%)

48,96% 42,33% 35 68% 35,68% 40,06% 40,14% 42,53% 40,51% 41,16% 24,33% 36,63%

Total water use (Mm3)

Rainfall (mm)

Scarcity value blue water (M€)

27,616

767

925

26,427

676

895

23 455 23,455

570

1759

27,046

558

2515

27,743

760

949

26,675

569

2283

27,761

650

1153

29,114

713

911

23,585

452

1956

25,529

632

3216

Virtual water "flo ows" (Mm 3/ yr)

4- Virtual water 'trade' in agriculture (Mm3/yr)

45000

Virtual water "imports"

40000

Virtual water "exports"

35000

Net virtual water "imports"

30000

Tendency (Net virtual water "imports")

25000 20000 15000 10000 5000 0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

4. Major crop-related virtual water ‘imports’ (Mm3/yr) 35000

30000

France

Brazil

USA

Ukraine

Argentina

Portugal

Germany

U.K

Tunisia

Uganda

Indonesia

TOTAL

Millio on m3

25000

20000

15000

10000

5000

0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

4. Virtual water ‘exports’ (Mm3/yr and M€/yr) Scarcity value of blue virtual water ‘exports’

9000 8000

8000 7000

Others

Aragón

C-La Mancha

4000

Andalucía

Million m3

Million m3

3500

5000

900

Cataluña C-León

R. de Murcia Aragón

6000

1000

Economic value of blue virtual water exports

4500

C-La Mancha

6000 7000

Million m3

Blue virtual water exports

5000

Others

9000

Aragón

3000

Extremadura

500

Andalucía 2000

3000

C. Valenciana

4000

C-La Mancha

1500

2000

C-León

Extremadura

1000

Cataluña

2000 0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

1997

1998

1999

2000

2001

2002

2003

2004

Cataluña C-León

Aragón

C-La Mancha

C. Valenciana

Extremadura Andalucía

Murcia

2005

2006

300 200

500

Cataluña

0

400

C. Valenciana C-León

1000

C. Valenciana

Extremadura

1000

3000

700 600

R. de Murcia 2500

4000

5000

800

100

0 1997

1998

1999

Andalucía 2000

2001

Murcia 2002

2003

2004

0 2005

2006

Million €

By Autonomous Community

4.Livestock virtual water 'trade' (Mm3/yr) Virtual water 'exports'

Virtual water 'imports' Bovine

5,000

5,000

Swine

4,500

4,500

4,000

Other animals

3,000

3,500 3

3,000

4,000

2,500 Milk and dairy products Eggs

2,000 1,500 1,000

Sheep and goats

500 0

Milliion m

Milllion m

3

3,500

Others edible products Poultry

2,500 , 2,000 1,500 1,000 500 0

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

4- Livestock virtual water ‘trade’ and economic value

Virtual Water Imports

Virtual Water Exports

Economic Value of Imports

Economic Value of Exports

12,000

4,000 3,500

10,000 3,000 2,500 6,000

2,000 1,500

4,000 1,000 2,000 500 0

0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Millio on €

Million m 3

8,000

5. Bringing the analysis to the policy context -- the spatial and time dimensions--

1

2

3

1

2

Jaén

Córdoba

Sevilla

Jaén

Almería

1

2

Albacete

Valencia

1 2 1

3

2

Ciudad Real

1

5

Guadalajara

3

1

1

2

1

4

Badajoz

3 Huelva

2

3

4

Madrid

Toledo

Murcia

3

4

2 1

2

Navarra

2 La Rioja

Zaragoza

Lleida

5 Tarragona

1 1 2 4

3 2

3

WATER TRANSFERS

Norte

Negratín – Alzamora (2002)

Tajo – Júcar – Segura (1979)

Duero

Ebro

C.I. Cataluña

Ebro – Tarragona (1989)

Tajo Source: Own elaboration

Júcar Guadiana Segura Guadalquivir Sur Canarias

Baleares

5. The spatial and time dimensions River basin analysis

Norte C.I. Cataluña Duero

Ebro

Tajo Jú Júcar Guadiana Segura Guadalquivir Sur

Canarias

B l Baleares

5. The spatial and time dimensions Case A: Ebro river basin

Norte Ebro Ebro Ebro

Duero

C.I. Cataluña

Tajo Júcar

Baleares

Guadiana S Segura Guadalquivir Sur Canarias

Upper Ebro

Lower Ebro

Álava Navarra

Huesca

Lleida

La Rioja Zaragoza Tarragona

Upper Ebro: Changes in land apparent productivity 1996-2006 (real € of 2000) Lower Ebro

8

8

Upper Ebro 2006

2004

Irrig-land prod 1000 €/ha 3 4 5 6 7

Irrig-land prod 1000 €/ha 3 4 5 6 7

2005 2006 2004 2000

2005 1996 2000

2000 1996 2006 2006 2004 2006 2004 2000 2000 2005 2005 2004 1996 1996

2005

2000

2005 1996

.5

1

1.5 2 Dry-land prod 1000 €/ha Alava Navarra

2.5

3

0

La Rioja

.5 1 Dry-land prod 1000 €/ha Huesca Tarragona

Source: Ministry of Agriculture Real euros of year 2000

Source: Ministry of Agriculture Real euros of year 2000

Álava

Navarra

EBRO Huesca Lleida

La Rioja Zaragoza

Tarragona

2006

2004

2

2

1996 2006 2005 2004 2000 1996

Lleida Zaragoza

1.5

Ebro basin: changes in water apparent productivity

Blue crop water use EBRO 1600 1400

Million n m3

1200

Zaragoza

Lleida

Navarra

Tarragona

La Rioja

1000 2006 1997 2006

800

1997

600 2004 400

2005

2006 1999

200

1997

2002

2001 2000

0 0

Navarra La Rioja Zaragoza

Lleida

Tarragona

0.5

1 1.5 2 Blue water apparent productivity (€/m 3)

2.5

3

Case B: Júcar river basin

Norte Duero

Ebro

C.I. Cataluña

Tajo Júcar Júcar Guadiana S Segura Guadalquivir Sur Canarias

Júcar Castellón Valencia Albacete Alicante

Baleares

Júcar: Changes in land apparent productivity

Castellón

Jucar Alicante

2006 2005 2004 2004 2006

2006

2000

2000 2005 1996 1996

2000

2004

2006

2005

1996

2005 2004 2000 1996

2

Albacete

Irrig-land prod 1000 €/ha 3 4 5 6

Valencia

.5

1

1.5 Dry-land prod 1000 €/ha Albacete Valencia

Source: Ministry of Agriculture Real euros of year 2000

2

Alicante Castellon

2.5

Júcar: changes in water apparent productivity Blue crop water use Blue crop water use (Million m 3) B

1400 1200 1000

1998 2006

1999

800 600

Albacete

400

Valencia

2002 1997

2006 2004

200 0 0

Valencia Albacete

0.2

0.4 0.6 0.8 Blue water apparent productivity (€/m3)

1

1.2

5. Blue water apparent productivity (1000 m3/€) against water scarcity Mainland regions

.003

.003

.004

.004

Mediterranean regions

.002

R-squared = 0.001

0

0

.001

.001

.002

R-squared = 0.3382

0

.1

.2

.3

.4

.5

Scarcity value (€/m3) Fitted values

Blue water productivity 1000 m3/€

0

.1

.2

.3

.4

.5

Scarcity value (€/m3) Fitted values Blue water productivity 1000 m3/€

5. Blue water apparent productivity in light of water scarcity BWPit = α + β1 SVit + β 2GB % it + ε it

Mediterranean regions Scarcity Value ( β1 )

Green-blue Water ( β 2 ) Constant α Number of obs Number of groups Time periods p