WATER FOOTPRINT AND VIRTUAL WATER TRADE: POLICY IMPLICATIONS (Guadina Water Footprint)

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1 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 University, The Netherlands Project Funded by

2 Contents Background and the Spanish context Motivation and objectives Conceptual framework Method and data sources Results Conclusions and discussion

3 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, )

4 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 i mandates that t WF calculations l be made for River Basin Management Plans An ideal case study for an in-depth analysis of VW and WF

5 The Spanish Context Population change Annual average Runoff

6 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

7 Conceptual framework (I) WFD CAP EU Policies National water policy Cropping patterns Physical Water use Land Livestock Water Water Footprint uses (x,y, t) Temporal Technology Drought cycles Economic Productivity WTO VW Trade trade Climate change Adaptation

8 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

9 Method (I) WF assessed from a top-down approach WF = (WU VW ) + (VW VW Agricultural water use (WU a ) CWR = ET o *K c Peff WU Agronomic and climatic parameters E I RE n = [ CWU *S + CWU *S ] LWU a g t b irr + c= 1 ET g = min (CWR,P eff ETb = max ( 0,CWR-ET Green and blue water evapotranspiration ) g ) CWU CWU ) = 10* lgp g ET g m= 1 lgp = 10* b ET b m= 1 Green and blue crop water use V V g = b = CWU Y CWU Y Green and blue virtual water content b g Peformed for 93 crops 50 provinces and 10 years

10 Virtual Water Flow VW [ n, n, j] = V [ n, j] T[ n, n j] e i e e i, Method (II) Water and Land Apparent Productivity, economic value of farm output per m 3 and per ha cultivated, t respectively 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)

11 Method (III) Econometric approach Hypothesis: water productivity s dependent on water scarcity and blue-green water % Model (panel / time series data) BWP it = α + β1 SVit + β 2 GB % it + ε it BWPit inverse of blue water productivity 1000 m 3 / SV water scarcity value in /m 3 it ratio: green crop water use/total crop water use GB% it

12 Method (IV) Exchange terms of virtual water trade ETerms VW VW ( / m ( / m t 3 exp _ VWt = t 3 imp ) ) Macro-economy water dependence Dep _ ratio = t 3 VFt ( m ) GNP ( ) t

13 Data sources Data Spatial dimension Time dimension Source Climatic Provincial Meteorological Agency Crop area and yield Provincial Ministry of Agriculture Crop parameters National Allen et al., 1998 Crop products Provincial Ministry of Agriculture Livestock water use River basin 2001 Ministry of Environment Industrial water withdrawal National National Statistics Institute Urban water withdrawal National National Statistics Instit. Trade Provincial DataComex Crop market prices National Ministry of Agriculture Industrial production Autonomous Community National Statistics Institute

14 Results 1. Water footprint and virtual water of Spain: hydrologic and economic perspectives 2. Water apparent productivity 3. Economic implications for water allocation: 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

15 1. Water footprint of Spain (Mm 3 /yr) Million m 3 50,000 45,000 40,000 35,000 30,000 1,000 m3/year and person 25,000 20,000 15,000 10,000 5,000 Total Water footprint Water footprint agricultural sector Water footprint urban sector Water footprint industrial sector Year

16 1. WF agriculture and agricultural sector (Mm 3 /yr) Water footprint agriculture Virtual water imports agriculture Million m 3 50,000 45,000 40,000 Water footprint agricultural sector Virtual water exports agriculture 35,000 30,000 25,000 20,000 15,000 Net Imports 10,000 5, Year

17 1. Livestock water footprint (Mm 3 /yr) Million m 3 50,000 45,000 40,000 35,000 30,000 Smaller footprint 25,000 20,000 15,000 10,000 5,000 Water footprint agriculture Water footrpint agricultural sector Virtual water exports livestock Virtual water imports livestock Net Exports Year

18 Industrial crops Cereals Pulses Citrics Dry fruits Olives Fresh fruit Fodder Tuber Vegetables Vineyard Crop water use (Million m 3 ) 2. Water apparent productivity in agriculture ( /m 3 ) Year ,000 12,000 10,000 8,000 6,000 4,000 2,000 0 Crop blue water use Crop green water use Water apparent productivity Water apparent productivity ( /m 3 )

19 2. Water apparent productivity in agriculture ( /m 3 ) Crop water use (Mm3) 5,000 4,000 3,000 2,000 1,000 Vineyard Crop blue water use Crop green water use Water Apparent Productivity Water Apparent Productivity ( /m3) Crop water use (Mm3) 5,000 4,000 3,000 2,000 1,000 Olives Crop blue water use Crop green water use Water Apparent Productivity Water Apparent Productivity ( /m3) Industrial crops Crop water use (Mm3) 5,000 4,000 3,000 2,000 Crop blue water use Crop green water use Water Apparent Productivity Water Apparent Productivity ( /m3) 0.3 1,

20 3. Economic scarcity value of blue water use (M /yr) Year Blue water use (%) Green water use (%) Total water use (Mm 3 ) Rainfall (mm) Scarcity value blue water (M ) ,04% 48,96% 27, ,67% 42,33% 26, ,32% 35,68% 23, ,94% 40,06% 27, ,86% 40,14% 27, ,47% 42,53% 26, ,49% 40,51% 27, ,84% 41,16% 29, ,67% 24,33% 23, ,37% 36,63% 25,

21 4- Virtual water 'trade' in agriculture (Mm 3 /yr) Virtual water "imports" Virtual water "exports" Virtual water "flo ows" (Mm 3 / yr) Net virtual water "imports" Tendency (Net virtual water "imports")

22 4. Major crop-related virtual water imports (Mm 3 /yr) France Brazil USA Ukraine Argentina Portugal Germany U.K Tunisia Uganda Indonesia TOTAL Millio on m

23 4. Virtual water exports (Mm 3 /yr and M /yr) By Autonomous Community Scarcity value of blue virtual water exports Million m Million m Others Others 4500 C-La Mancha 4000 Aragón C-La Mancha 3500 R. de Murcia Aragón 3000 Andalucía R. de Murcia 2500 Extremadura Andalucía 2000 C. Valenciana 1500 Extremadura C-León 1000 Cataluña C. Valenciana 500 Million m 3 C-León 0 Cataluña Blue virtual water exports Economic value of blue virtual water exports Cataluña C-León Aragón C. Valenciana C-La Mancha Extremadura Andalucía Murcia Million C-León Aragón Cataluña C. Valenciana C-La Mancha Extremadura Andalucía Murcia

24 4.Livestock virtual water 'trade' (Mm 3 /yr) Virtual water 'exports' Virtual water 'imports' Bovine llion m 3 Mil 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 Swine Others edible products Poultry Other animals Milk and dairy products Eggs ion m 3 Milli 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, Sheep and goats 1,

25 4- Livestock virtual water trade and economic value Virtual Water Imports Virtual Water Exports 12,000 Economic Value of Imports Economic Value of Exports 4,000 10,000 3,500 3,000 m 3 Million 8,000 6,000 4,000 2,500 2,000 1,500 Millio on 1,000 2,

26 5. Bringing the analysis to the policy context -- the spatial and time dimensions Jaén 1 Ciudad Real Córdoba 2 Badajoz Sevilla 3 Huelva Jaén 1 Almería 2 Albacete Valencia Guadalajara 2 Madrid 3 Toledo 4 Murcia WATER TRANSFERS 1 Navarra 2 La Rioja 3 4 Zaragoza Lleida 5 Tarragona Negratín Alzamora (2002) Tajo Júcar Segura (1979) Ebro Tarragona (1989) Norte Duero Ebro C.I. Cataluña Tajo Source: Own elaboration Guadiana Júcar Baleares Guadalquivir Sur Segura Canarias

27 5. The spatial and time dimensions River basin analysis Norte Duero Ebro C.I. Cataluña Tajo Guadiana Júcar Bl Baleares Guadalquivir Sur Segura Canarias

28 5. The spatial and time dimensions Case A: Ebro river basin Norte Duero Ebro C.I. Cataluña Guadiana Tajo Guadalquivir Júcar Segura Sur Baleares Canarias Upper Ebro Lower Ebro Álava La Rioja Navarra Huesca Zaragoza Lleida Tarragona

29 Upper Ebro: Changes in land apparent productivity (real of 2000) Upper Ebro Lower Ebro Irrig-land prod 1000 /ha Irrig-land prod 1000 /ha Dry-land prod 1000 /ha Dry-land prod 1000 /ha Alava Navarra La Rioja Huesca Tarragona Lleida Zaragoza Source: Ministry of Agriculture Real euros of year 2000 Source: Ministry of Agriculture Real euros of year 2000 Álava La Rioja Navarra Huesca Lleida EBRO Zaragoza Tarragona

30 Ebro basin: changes in water apparent productivity EBRO Blue crop water use Zaragoza Navarra La Rioja Lleida Tarragona La Rioja Navarra Zaragoza Lleida Tarragona Million m Blue water apparent productivity ( /m 3 )

31 Case B: Júcar river basin Norte Duero Ebro C.I. Cataluña Guadiana Tajo Guadalquivir Júcar Júcar Segura Sur Baleares Canarias Júcar Castellón Albacete Valencia Alicante

32 Júcar: Changes in land apparent productivity Castellón Valencia Albacete Alicante d prod 1000 /ha Irrig-lan Jucar Dry-land prod 1000 /ha Albacete Valencia Alicante Castellon Source: Ministry of Agriculture Real euros of year 2000

33 Júcar: changes in water apparent productivity Blue crop water use 1400 Blue crop water use (Million m 3 ) Albacete Valencia Valencia Blue water apparent productivity ( /m 3 ) Albacete

34 5. Blue water apparent productivity (1000 m3/ ) against water scarcity Mediterranean regions R-squared = Mainland regions R-squared = Scarcity value ( /m3) Scarcity value ( /m3) Fitted values Blue water productivity 1000 m3/ Fitted values Blue water productivity 1000 m3/

35 5. Blue water apparent productivity in light of water scarcity BWP = α + β SV + β GB% + ε Mediterranean regions it 1 it 2 it Coef. Std. Err. Elasticity ey/ex Scarcity Value ( β 1 ) ** Green-blue Water ( β 2 ) * Constant α ** Number of obs 190 Number of groups 19 Time periods 10 p<0.05*, p<0.01** Inland regions Coef. Std. Err. Elasticity ey/ex Scarcity Value ( β 1 ) * Green-blue Water ( β 2 ) ** Constant α ** Number of obs 220 Number of groups 22 Time periods 10 p<0.05*, p<0.01** it

36 6. Can economic growth be decoupled from water use? Water footprint and virtual water trade per of Gross Domestic Product Water footprint Total water use Net virtual water imports Virtual water exports Virtual water imports m 3 / cent Year

37 6. Can economic growth be decoupled from water use? Water Exchange Terms 3.00 Water apparent produ uctivity ( /m 3 ) Ratio Exp / Imp /m3 Exp /m3 Imp ETerms VW VW ( / m ( / m t 3 exp _ VWt = t 3 imp ) )

38 7. Conclusions 1. VW & WF are valuable indicators for the analysis of water, trade & agricultural policies 2. VW trade contributes to alleviate and mitigate the effects of drought cycles 3. Green vs. Blue water accounting is essential to evaluate VW+WF (proportion varies with years and regions). 4. The water scarcity paradigm should be revisited in light of VW trade

39 Conclusions 5. The Spanish economy is increasingly decoupled from its water footprint, but relies on international trade and thus on virtual water imports/exports 6. Virtual water exports and imports are only slightly dependent on water scarcity 7. Mediterranean provinces are more responsive to water scarcity and, possibly, to market signals 8. Mediterranean regions export more valuable water 9. Water productivity changes within Spain explain regional attitudes towards water markets and questions the upstreamdownstream value gradient

40 Questions for discussion 1. To what extent can VW and WF analyses at basins and provincial levels contribute to the implementation of the WFD one single RBMP and marked provincial differences 2. Can inter-basin water transfers be more accurately supported in light of the VW flows? (from water abundant lower value- added productions to water scarce high-value added productions) 3. Can VW and WF analyses throw some light on the environmental effects of the intensive Mediterranean agriculture? 4. Farm trade and agricultural policy are main drivers of the changes seen in Spain in the last 10 years; are they helping

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