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Sep 12, 2013 - ABSTRACT: We construct a multiregional input−output model for. Spain, in order to evaluate the pressures on the water resources, virt...
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Multiregional Input−Output Model for the Evaluation of Spanish Water Flows Ignacio Cazcarro,*,† Rosa Duarte,‡ and Julio Sánchez Chóliz‡ †

Department of Economics, School of Humanities and Social Sciences, Rensselaer Polytechnic Institute (RPI), Sage Laboratories Room 3407, Troy, New York 12180, United States ‡ Department of Economic Analysis, Faculty of Economics and Business, University of Zaragoza, Gran Vía 2, 50005, Zaragoza, Spain S Supporting Information *

ABSTRACT: We construct a multiregional input−output model for Spain, in order to evaluate the pressures on the water resources, virtual water flows, and water footprints of the regions, and the water impact of trade relationships within Spain and abroad. The study is framed with those interregional input−output models constructed to study water flows and impacts of regions in China, Australia, Mexico, or the UK. To build our database, we reconcile regional IO tables, national and regional accountancy of Spain, trade and water data. Results show an important imbalance between origin of water resources and final destination, with significant water pressures in the South, Mediterranean, and some central regions. The most populated and dynamic regions of Madrid and Barcelona are important drivers of water consumption in Spain. Main virtual water exporters are the South and Central agrarian regions: Andalusia, Castile-La Mancha, Castile-Leon, Aragon, and Extremadura, while the main virtual water importers are the industrialized regions of Madrid, Basque country, and the Mediterranean coast. The paper shows the different location of direct and indirect consumers of water in Spain and how the economic trade and consumption pattern of certain areas has significant impacts on the availability of water resources in other different and often drier regions.



INTRODUCTION Water scarcity, the temporal or spatial imbalance between water endowments and demands, and their relationship with overexploitation, environmental degradation and climate change is a serious global concern, which has attracted increasing public and research attention.1 This problem is particularly relevant in Mediterranean countries such as Spain, whose geographical characteristics, especially the extension, topography, and location between temperate and warmer latitudes, generate large climatic differences both in terms of temperature and precipitation. Natural and regional characteristics have coexisted, historically, with increasing demands of water, linked to the development of the Spanish economy. Agriculture has been a central economic sector in Spain for centuries, and despite its reduction in GDP and employment share (from almost 50% and 66% at the beginning of the century to the current 3% and 9% respectively2), irrigated areas have increased notably during the 20th century. Since the 1950s, the extension of irrigation, orientation toward more profitable but water intensive crops (citrus, feed), boom of tourism development in coastal Spain, and urban population growth have led to significant increasing water demands and pressures. Halfway through the first decade of the 21st century water withdrawals in Spain have been slightly less than 40 km3 per year (own estimations from ref 2), being around 60% abstracted by agriculture, 14.5% by the water © 2013 American Chemical Society

distribution sector (distributed to industries and households), 16% by the energy and gas sectors, and 4% by industries. In this context, we develop the first full multiregional input− output (MRIO) model for Spain (considering all 17 Spanish regions, plus the European Union and the Rest of the World) extended for computing water flows and water footprints (WFs). Without losing the international perspective (i.e., maintaining two regions in the model for the rest of the world), we infer an important implication: the importance of the interregional flows and the different role of the Spanish regions (autonomous communities (ACs)) as net importers or exporters. We also relate these water flows and demands with the regional water availability, in order to offer insights on the Spanish water stress, defined as volume of water consumed/availability per capita. As we will see, trade flows between regions explain, to a great extent, pressures (impacts) on water resources in some Spanish areas where regional water availability is low. Embodied water flows associated to trade are often expressed making use of the virtual water (VW) concept, which has been defined as the volume of water that has been necessary to Received: Revised: Accepted: Published: 12275

May 10, 2013 July 29, 2013 September 12, 2013 September 12, 2013 dx.doi.org/10.1021/es4019964 | Environ. Sci. Technol. 2013, 47, 12275−12283

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a description of the general (both natural and potential) water availability in Spain, the importance of agrarian sectors, and their relationship with water withdrawals and consumption in origin (relatively high in some relatively low water endowed areas of the south and southeast), which contributes to better contextualize the results obtained (the main section) and the final discussion.

produce a good or service. Closely linked to this concept, the WF is used to measure the necessary water volumes for human consumption.3,4 For Spain, where water scarcity is a concern, some pioneering water related input−output (IO) studies5 have been applied. It has been argued that WF reduction should be enhanced since it has been ranked as one of the countries with highest WF in the world.6 For example, it has been studied that, by changing the diets, water consumption and household health and budget could improve.7 Several international studies of the WF have been carried out relating Spain with other countries,3,6 which approximated the WFs of production (water associated to a region or nation for the production of goods and services within its boundaries) and of consumption (associated to the goods and services, domestic or imported, consumed by a citizen or population) based on the examination of international trade, and mostly with a methodology of process analysis. To study water flows, a few works used multidirectional data and models;8−17 these last articles are the closest references for our work in terms of methodology. In our study, we follow those works on MRIOs and other works with a regional focus18,19 trying to capture better the regional agricultural and water particularities. The regional detail allows a better distinction of water uses, of the interregional trade (which is the main component for most Spanish regions), and of the WF of consumption, by making use of the regional information of final demand expenditures. There is an interesting precedent in Spain to build an interregional IO model.20−22 The first interregional IO model was built for the year 1995, but the initial information was not homogeneous to the SEC-95 criteria, and there were only five regional IO tables for that year. If some of the main disadvantages of those tables had to do with the needs of updating and the absence of survey data, the positive side had to do with the effort of the authors of compiling (apart from the 1995 Spanish IO, the most recent at that time) regional and interregional trade information and the use of nonsurvey techniques. In the analysis we deal with blue and green water (both separately and in combination) looking both for environmental effects and policy implications. Green water is defined as the moisture stored in soil strata, and blue water is defined as the fresh surface and groundwater (in freshwater lakes, rivers, and aquifers).6 This latter one has a higher relevance in the economic analysis due to the possibilities of multiple or competitive uses and political debate on its water management. We consider that the relevance of the analysis goes beyond the specific case studied. First, it is shown the capacity of water extended MRIO models to assess footprints from the producer and consumer perspectives and to capture the full map of water flows embodied in interregional and international trade among regions. Second, lessons from the imbalance between origin of water resources and final destination are derived, and more specifically, the chained relationship between some populated, industrialized, and highly water-demanding regions and other areas that act as suppliers, which ultimately represents significant impacts on regional water resources. The rest of the article is structured as follows. In the next section the Methodology and data are described. After this, we analyze the results of regional water flows and WFs extending the insights and discussion in that one and the final section. The Supporting Information (SI) contains further description of data sources and uncertainties of the analysis. It also includes



METHODOLOGY Basic MRIO Model. The model used is based on the nonfull survey model, multiregional input−output (trade matrices based on trade coefficients).23−26 Our MRIO for the year 2005 for Spain has 40 economic sectors (aggregated into 13 in Table 3) and 19 regions corresponding to the 17 Spanish ACs and 2 other regions: the European Union (EU) and the Rest of the World (RW). The key elements are the multiregional matrix of technical coefficients A⊕ and its Leontief inverse L⊕, the output matrix X⊕, and the final demands matrix Y⊕. These matrices verify the following equilibrium equation: X ⊕ = A⊕X ⊕ + Y ⊕ ⇔ X ⊕ = (I − A⊕)−1Y ⊕ ⇔ X ⊕ = L⊕Y ⊕

(1)



In A , each 40 × 40 matrix Arr indicates the domestic technical coefficients in the region r. The 40 × 40 off-diagonal matrices Ars indicate the coefficients of the region s of imported inputs from r. Associated to this matrix, each characteristic element of L⊕, lijrs expresses the total quantity of output of sector i produced in r and directly or indirectly (through the full supply chain, which explicitly considers all the sectors and regions participating in some stage of production) incorporated in the final demand of sector j of region s. Matrix Y⊕ is formed of 19 column vectors ys with vector yss (40 × 1) representing the domestic final demand of s, and with the other yrs being the final demands of goods from r to s not consumed as productive inputs, i.e., the imports of finished products from r to s. Matrix X⊕ is formed of 19 column vectors xs which each of them represents, according to 1, the production needed to obtain final demand ys. This production can be broken down into xss (a 40 × 1 vector), which is the production of s used to fulfill the final demand ys, and vectors xrs which quantify the additional production needed from the other regions r. One of the main contributions of this paper is the construction of Z⊕ = A⊕X⊕, the matrix of intermediate economic flows across sectors and regions, which contain in the diagonal the different Zrr, which are the domestic IO tables of each region. The matrices of imports of intermediates to region s, Zrs, and the matrices of imports to region s of finished goods and services yrs have been constructed from each of the s regional tables of imports Ms and additional information from regional statistical institutes. A detailed explanation of the process followed to obtain these matrices can be found in the SI (subsection 3.3). We define wr (19 × 1) as the vector of coefficients of water consumption per output of region r, whose characteristic element wir indicates the quantity of water per unit of output of sector i in region r ( ̂ indicates diagonalization). Matrix W⊕ is formed by the diagonalized wr vector. Water associated with production, and embodied in final demand products is obtained as follows: H = W ⊕(I − A⊕)−1Y ⊕ 12276

(2)

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Hr,s is a 40 × 40 matrix whose elements Hijrs represent the direct and indirect water necessary in sectors i of region r to meet the demands of sector j in region s. Hs,s is the matrix of the amounts of water that are used in production activities in region s to support region s final demand, while ∑ r Hr,s is the matrix of water used in other regions

imports is somewhat different than in Madrid, since it imports less agrarian and food related goods and is more oriented toward exports of goods, receiving a net amount of 2774 hm3 from the rest of Spain (RS) and 4102 hm3 from the EU and RW. Total WF to GDP ratio (SI Table SI2) is on average higher for Spain than for EU and lower than for the RW (the opposite for the last ratios of WF per capita). It stands out that the total WF to Population ratio is 15% higher for Madrid than for Catalonia (1837 and 1602 hm3/capita respectively). Apart from different final demands by sector/goods further studied below, the local context is also important, since there are different historical trends, water policies implemented, and water cultures at stake, as explained in the article devoted to the history of the urban environmental imprint of Barcelona, main city in Catalonia,28 which can be compared with the sociometabolic study of the autonomous community of Madrid.29 SI Table SI2 also shows that Catalonia has high industrial WF per capita, while Madrid has higher agricultural and total WF per capita. A very different pattern is observed in Murcia, which on overall is a net importer of 2720 hm3 of water, being a big net importer from the RS (2483 hm3) and with smaller volumes from abroad (237 hm3). This last small figure is a result of the compensation of imports with its high exports of agricultural production. The case of Andalusia is relevant. Andalusia has a high WF and the highest volume of direct consumption of water (due to production), being its total net exports 8663 hm3. From that the VW export to RS is 3444 hm3 (mainly to Murcia, Madrid, and Catalonia), the rest being essentially VW export to the EU. Although when speaking of exporting water the case of Andalusia is usually highlighted, data show that three other Spanish regions have similar situations, although biased to interior trade, the Castiles and Aragon, with net exports of 11 408 and 2797 hm3, respectively. Their interior situation and climatic characteristics (drought and high thermal variability) impose significant pressures on the environment, especially in some critique summers. Finally, Spain as a whole is a net importer of water with 6680 hm3 (see Table 1), which is essentially green water import (97%). More specifically, Spain is a net exporter toward the EU, but net importer from the RW. The image of the water is clearly influenced by the level of development and the weight of agricultural production, which largely determine water flows and their final destination. This picture, although maintaining the general characteristics described, is even more polarized when one looks specifically at the blue water. The most industrialized and most populated regions (Catalonia, Madrid, Andalusia, and Valencia to a lesser extent; see data in Table 1) are the areas with the highest blue WF (2627, 2294, 1639, and 1445 hm3, respectively). Madrid and Catalonia are net importers of blue water, while Andalusia and Valencia are net exporters. Thus, Madrid and Catalonia avoid a significant part of their direct consumption of blue water through their interregional and international trade. As shown in Table 1, the blue WF for Madrid is 2294 hm3, while blue direct consumption is 494 hm3 and the blue water associated to its domestic demand is 307 hm3. As further detailed in SI Table SI2, the blue water demands that Madrid directly and indirectly generates are satisfied to a great extent by the RS (1063 hm3), especially the Castiles and Aragon, and by the EU and RW (925 hm3). Similarly, two-thirds of the Catalonian blue WF are satisfied by the RS (mainly Andalusia and Aragon) and by the EU and RW.

r≠s

production to support region s final demand (VW imports of region s) and ∑ s Hr,s the matrix of water used in r to support s≠r

the final demands of other regions. Then, being e a column vector of ones, e′Hs,se is the volume of water used in region s to support its own final demand, i.e., the domestic component of the WF of region s. Similarly, ∑ r e′Hr,se is the total VW import r≠s

of region s, and ∑

s e′Hr,se s≠r

the total VW export of region r.

Moreover, ∑r e′Hr,se = e′Hs,se + ∑ s and ∑s e′Hr,se = e′Hr,re + ∑

r e′Hr,se r≠s

s e′Hr,se s≠r

is the WF of region

the water embodied in

production of region r. As a consequence, ∑ ∑

r e′Hr,se r≠s

s e′Hr,se s≠r



is the net trade in water from r to s, which can be

positive (net export) or negative (net import).



RESULTS WFs of the Spanish Regions and VW Flows. One of the main advantages of the MRIO model built is the possibility of obtaining the volumes of regional WFs (water embodied in the economic activity of the Spanish regions) and of identifying the main drivers for them, both geographically (regions) and economically (sectors). The main results appear in Table 1 together with other economic magnitudes and more information is synthesized in Figure (map) 1 (detailed flows in SI Map SI4 and Map SI5). Results for total, green and blue WFs and interregional flows, and regional economic shares are presented in detail in SI Tables SI2 and SI3. In Table 1 the largest total (green plus blue water) WFs of production correspond to Andalusia the “Castiles”, Aragon, and Extremadura. The map somehow contrasts with the WFs of consumption, being the highest for Catalonia, Madrid, Andalusia, Valencia, and Basque country, followed by Murcia and Castile-Leon. These seven regions together account both for 63% of the WF of Spain and of its population and 66% of its GDP, implying that they alone are very representative of the whole country. The net balances of interregional flows of water, characterized by the net exports, confirm the important opening of the regional economies in Spain, their economic interdependence, and the noncorrelation between regional availability and water destinations. Three of the four regions with higher WF (Madrid, Catalonia, and Valencia) are significant net importers of water; however, the fourth (Andalusia) has the highest water export volumes. Madrid presents net imports of 10 131 hm3 (see Table 1), indicative of net water balances of embodied products into the region, i.e. the water that the region prevents from using through purchases from the rest of Spain (5645 hm3, more than half) and through purchases from the EU and RW (641 and 3948 hm3). For Catalonia, the net imports are “only” of 6876 hm3 although the share on Spanish GDP is similar in both regions (Madrid 17.7% and Catalonia 18.7%). Catalonia has higher relative availability of water, receiving downstream the rainfall in the Catalan Pyrenees, but notably, the origin of net 12277

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regions

12278

1784

649

88

1917

5616

1639

59

924

47 153 571 2433

83 316 1826 7254

149 43 29 4 48 6

172 112 12 29 44 10

33 1

8 4 1 4 108

20 28 12 11 282

204 22

105 1014 107

3245 145 682

1373

86

464

2138

38 81 474 2603

28 7

24 19 5 12 10 2

3 1 0 2 139

129 55 1572

713

39

190

578

4 48 221 768

7 0

27 87 7 5 9 3

183 1 0 5 94

34 14 20

1354

60

331

1001

30 100 317 1331

8 1

95 15 3 3 23 3

8 415 1 2 21

232 34 20

1097

60

597

1561

31 177 1066 2159

19 2

85 38 4 16 17 3

3 16 312 2 85

168 53 62

1153

56

174

474

6 21 191 648

15 0

24 29 4 4 13 7

12 0 0 82 139

22 21 57

1306

68

656

2623

11 96 433 3279

56 2

29 63 31 9 22 13

9 1 0 35 2266

78 46 80

1602

67

2627

8578

135 874 4720 11205

110 11

1446 125 48 18 184 22

26 32 7 29 642

931 1288 554

340 42

214 247 48 560 118 20

16 27 16 23 1486

943 540 1600

6 5

54 36 41 2 184 13

1 1 0 4 160

77 156 69

102

119

518

1837

69

2294

8659

1963

77

285

878

1 125 10 38 641 76 305 3948 269 637 10953 1164

3 0

7 3 147 1 30 3

1 0 0 1 44

7 38 8

1103 2115

67

577

2469

17 248 1239 3046

17 1

57 809 11 9 14 7

50 2 1 8 276

146 43 92

2061

79

902

3477

36 314 1589 4379

23 1

103 109 130 6 162 379

19 2 1 40 1004

233 131 97

1842

139

360

1629

11 64 531 1989

174 1

30 25 3 18 19 1

5 2 1 3 319

447 26 309

2331

213

720

2963

131 134 864 3683

35 79

109 47 5 10 32 6

9 28 3 5 187

995 145 860

1358

73

1445

4927

643 372 2726 6371

57 27

210 78 14 12 33 9

24 53 12 13 383

765 278 662

530 472

590 187 52 49 139 66

58 43 18 44 513

2152 499 905

RW

1516

79

660

88

33962 594544

584544 3321037

484 517 191429 111375 539964 3833221 742918 3951431

1643 289

902 288 74 54 208 89

64 46 39 49 685

5209 702 702

EU

2359 306554 4394475

3309 964

4329 2359 669 822 1308 660

517 703 425 362 8833

15917 5230 8457

503 688 730

3064 610

619 854 2223 138 2206 311

480 715 216 644 3518

2028 4122 4463

−26 −144 −340 12 737

−251 −225 −628 −484 −1734 −1395 −286 −298 5554 4817

486 −175 −4012 −4025 12 −436364−374751 −61614 443044 381205 61839

1320 834 −2720 −2544

−6876 −5915 −962 −688 −327 −360 32 55 −23 −10131 −8330 −1800 144 −32 176 −3719 −3151 −568

939 1153 658

7723 1644 5196

8663 2797 5854

net net green net blue water of water of production production/ water water water (direct water population export exports exports consumption) (m3/person) (hm3) (hm3) (hm3)

a Note: The total of the column s shows the water embodied in the goods consumed in region s, i.e., its WF. Looking by rows, the row r represents the water embodied in the total final demand de r, both by domestic demand and by exports, including the export of imported water. In the last three columns, we obtain the water net exports for each region r as difference between water of production of r and the water footprint of r.

Andalusia Aragon Castile−La Mancha Asturias Baleares Canarias Cantabria Castile and Leon Catalonia Galicia La Rioja Madrid Navarre Basque Country Extremadura Murcia C and M Valencian C. EU RW water embodied in Y green WF (hm3) blue WF (hm3) WF (m3)/ GDP (million €) WF/population

Castile Murcia Castile−La and La Basque C and Valencian Andalusia Aragon Mancha Asturias Baleares Canarias Cantabria Leon Catalonia Galicia Rioja Madrid Navarre country Extremadura M C.

Table 1. Total, Green, and Blue Regional Water Use and Footprints (hm3) for the Year 2005a

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Figure 1. Map 1. Virtual water (blue plus green) net exports of the year 2005. Note: The size of the spheres shows proportionally the size of VW contents in regional final demand while their color ranges from green to blue depending on the representativeness of the agrarian goods with respect to industrial and services goods in the regional final demand (greener implies a higher ratio of VW from agrarian goods with respect to industrial). Regions are colored according to their net export (positive values) or net import (negative) character. The arrows show the main (higher than 100 hm3) net blue and green VW flows across Spanish regions and with the EU and RW (see detailed flows in the SI in Map SI2 and Map SI3). 1. Galicia. 2. Asturias. 3. Cantabria. 4. Basque country. 5. Navarre. 6. La Rioja. 7. Aragon. 8. Madrid. 9. Castile and Leon. 10. Castile−La Mancha. 11. Extremadura. 12. Catalonia. 13. Valencian Community, 14. Balearic islands (Baleares). 15. Andalusia. 16. Murcia. 17. Autonomous cities of Ceuta and Melilla (neglible values). 18. Canary islands (Canarias).

We highlight the exporter character of Andalusia in blue water, especially oriented toward the foreign trade. More than a third of its blue water of production is embodied in goods exported to EU or RW. Again Aragon and the Castiles are net exporters of blue water, mainly due to interregional trade inside Spain. All in all, Figure 1 shows these interregional VW flows across Spanish regions are characterized by agriculturally specialized regions to industrial ones, with particular areas of influence such as Andalusia to the Mediterranean regions, the Castiles to Madrid, and the northern (Castile−Leon, Aragon, Navarre, or La Rioja) to the Basque country. We look now at the relationship between water flows and regional water availabilities, to identify regional pressures on the water resources, similarly to the works on ecological footprinting, overshooting, and deficit.30 We can get a first approach to water stress from the description given by Map 1 and from the total domestic water uses in each region (blue and green), which have been shown in Tables 1 and SI1. According to this, in the ranking of regions with the greatest uses of water for production, all the first regions but the Basque country and Galicia are located in arid areas predominantly. In general then, most Spanish regions are in a situation of high pressure on water resources, which as we have seen is strongly linked to production and income generation. The picture is quite similar if we focus on blue water and can be completed in Table 2 with three ratios (the

higher their values, the higher the pressure), derived from our MRIO estimations. The first (column) is the ratio between WF of consumption and the domestic uses given by the main diagonal of Table 1. The second is the ratio between WF of production (direct use of water) and WF of consumption. The third is per capita WF. The first measures the pressure exerted on water from other regions or countries to fill domestic needs. The second informs about how foreign trade influences the use of water, measuring therefore the external pressure. The third measures water impact derived from population lifestyles and can be understood as a proxy of the moral responsibility of a society on the uses of water. The highest values (above 10) for the first ratio appear in Murcia, Madrid, Basque country, and Extremadura. They all suffer water stress either because of lacking resources (as shown in Map 1) or high level of economic activity. For the second ratio, the region with the lowest value is Madrid (0.08), followed at a high distance by the Basque country (0.15), Canarias, Murcia, Valencia, and Catalonia. Clearly the agribusiness and the industrial component is very strong in those with high coefficients, also indicating that often is production for exports (to other regions or abroad) what generates water stress in many regions. Finally, the highest per capita WFs are found in the southeastern region of Murcia and the northern regions of La Rioja, the Basque country, Navarre, and Aragon, followed by 12279

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through the restaurants in La Rioja, as clearly appreciated when looking at the relative (per capita) figures. These results highlight the idea that Spain exerts important indirect water impact through many different economic activities, far beyond agricultural and food production by irrigation or hydroelectric production. Without doubt, to assume this fact is essential to carry out adequate water management in Spain. It must not only address the efficiency of irrigation and its environmental impacts, but rather also accounts for the use of (green and blue) water, which depends on the rain but also on the arable land and moisture-retaining capacity of the soil and other actions on the territory. Other interesting relationship that arises from our results is the relationship between regional use of water and the local production of goods in which the region is relatively specialized. We often find the highest volumes of VW in sectors in which the regions in question are strong in (e.g., Galicia in textiles or the Canary islands in hotels), and the social role of water may be quite different across regions. In this sense, on one hand the fact that VW volumes are high in (finalist) services sectors important in a region (such as hotels and restaurants, in the cases of Andalusia and Madrid, through the arts, entertainment, and recreation sector, or, in Aragon, through public administration and related activities) is somehow logical since production and consumption occurs mostly in the same place. However, the fact that also there are high volumes in final demand for regions such as Galicia in especially relevant sectors such as textiles and other manufacturing industries (mostly from the sectors of construction and vehicles and transport material) has to do both with the interesting facts that domestic demands in Spain are often strong in the products the region is specialized in and that the role of water intensive productions are reflected through their the supply chains. This latter aspect relates to a relevant recent discussion,27,31−33 regarding the importance of VW flows and the determinants of trade (comparative advantage, public policies, market structures, etc.).

Table 2. Indicators on the Pressure Exerted on Water Resources by Each Region WF cons/total uses WF production/ of domestic water WF consumption Andalusia Aragon Castile−La Mancha Asturias Baleares Canarias Cantabria Castile and Leon Catalonia Galicia La Rioja Madrid Navarre Basque country Extremadura Murcia C and M Valencian C.

per capita total WF (m3 per citizen)

2.24 2.40 1.66

2.19 2.15 3.25

924 1917 1373

4.21 3.21 6.93 7.87 1.45

0.67 0.53 0.20 0.56 2.69

713 1354 1097 1153 1306

7.75 3.76 4.32 19.54 6.34 11.55

0.39 0.77 1.05 0.08 1.12 0.15

1602 1103 2115 1837 1963 2061

11.41 46.86

1.66 0.17

1842 2331

9.91

0.37

1358

the middle-west region of Extremadura, most of them being important in the agro-food sectors except for the (industrial) economy of the Basque country. Then the highest is for the strong economies of Madrid and Catalonia, i.e., highly populated regions, typically highly industrialized, and now also specialized in services as Madrid, Catalonia, and the Basque country, which show important absolute and relative WFs. Other important local impacts appear in other Mediterranean regions such as Murcia, with the high relative water demands of low populated interior regions also being significant. This impact is mainly due to the generation of inputs to satisfy final demands of other Spanish regions. Once the regional flows are analyzed, we look now at the WFs through sectors. The per capita results are shown in Table 3, and the absolute water volumes in SI Table SI4. The highest embodied green water volumes appear generally in the agrarian, food (meat) industry and restaurants sector, followed by others such as textile. The embodied water contents through restaurants represent the highest share in the WFs for Andalusia, Aragon, Baleares, La Rioja (where is even superior to the water from the agrarian sector), Galicia, and the Valencian community. In the case of these two last regions, but also for some others, the second sector through which more water is consumed is the group of other food industries. Particular cases of embodied water through less common sectors are those for Aragon in the sectors of (wholesale, retail, and automotive fuel) trade and public administration or, for the cases of Andalusia and Madrid, through the recreation sector. Regarding blue water, apart from the importance of the agrarian sector, the restaurants sector appears even stronger, and for some regions such as Asturias and Galicia the manufacturing industries (e.g., textiles) are the second sector in importance. High relative (to their other sectors) VW contents through construction appear for Aragon, Andalusia, Asturias, and Cantabria, through hotels in Canarias and various services in Cantabria and Aragon, and notably (green water)



DISCUSSION The MRIO built has shown the imbalances between natural water availability and water demands, mainly located in widely populated areas, coastal Mediterranean (Murcia, Andalusia), and generally dry regions. This reveals strong differences between use, trade orientation, and availability. Agricultural production and food processing, which satisfy important national and foreign demands, generate strong water impacts in regions. Industrial demand from regions such as Madrid, Catalonia, and the Basque country generates water requirements that exceed physical availability. Madrid (and to a lesser extent, other high populated regions) also play a significant role in the intermediate processes of transformation and distribution of goods and hence on water embodiment. The results show that the consumption of water in a territory is dependent on its economic structure, trade patterns, and income. As similar studies for other countries have shown, there is often high economic interdependence among regions in a country, while existing relevant differences in wealth, economic structure, and resources that drive imbalances in interregional trade and the embodiments in trade.34 The Spanish economy is an importer of water, much of which is used to meet domestic demands, but is also exporting water, especially through the agricultural products sold to the European Union. Both trends are strong (especially relative to their population or GDP) in most of the regions. 12280

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a Sectors are grouped due to expositive reasons. bThe absence of representation in the table used for Madrid of the sectors of production and distribution of electricity and gas and collection, purification, and distribution of water impede us from deriving results on this.

Table 3. Embodied Green and Blue Water in Final Demand (m3 per citizen) by Spanish Autonomous Community (Region)

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Lifestyles, population, water savings, and demands have important effects on the use of resources far beyond where they occur. In this respect, policies such as the incorporation into products of traceability indicators of water would be an interesting tool for improving water policy and reduce environmental impacts. Significant impacts, both locally and globally, can be captured with multiregional models, as the one used. Such studies inform on indicators and impacts for regions with similar climates (with arid or semiarid areas), while water management and political decisions are certainly different for humid areas such as the UK or The Netherlands. Relevant results are also expected from the implementation of international projects of IO data compilation,35−38 whose results and link to subnational models, may help in moving toward consistent information requirements of traceability indicators. How this knowledge is put into policy and behavioral changes is a wider story, since governments have taken decisions ranging from the so-called example of Israel discouraging the export of oranges or avocados (water intense products) to the opposite viewpoint of promoting exports for profit despite the depletion on domestic water resources. Such a policy has to do with the reallocation of agrarian production and water, but the incentives/disincentives can vary from subsidies/taxes and other modifications on the price of water, quantitative constraints, or a highly defended solution by the Spanish institutions: subsidizing and strengthening improvements in irrigation technologies. A question to assess is whether physical transfers of water between regions (building channels, pumping, etc.) can be more costly than promoting (or even paying) reductions of water uses and increases of water intense imports in water scarce regions. The models built and the figures obtained are a first step to advance in this line of research. Further policies based on direct and indirect consumption are suggestive but difficult to implement. The determinants of trade probably relate mostly to microdecisions on profits and the complete set of factors of production. For example the fact that regions such as Andalusia, Extremadura, or Murcia with relative (both per area and per capita) low availability have water intense productions, notably irrigated fruits and vegetables, could be explained theoretically by the abundance of another “factor”, sunlight/heat (specialization in such production requiring this factor intensely). However, incorporating information about the real impact on domestic and foreign water resources embodied in demands could help policy makers to anticipate potential impacts and bottlenecks associated to different productions and lifestyles, such as intensifications of irrigation, construction, tourism or textiles, chemicals, and paper utilization.



ACKNOWLEDGMENTS

The authors acknowledge the very useful comments received from the (four) anonymous reviewers and the participants at the 20th International Input−Output Conference (Bratislava, June 2012) and thank the project ECO2010-14 929 of the Spanish Ministry of Education and Science. I.C. also acknowledges the help from the directorate and the organizers of the course on Multi-Regional Input−Output Analysis at the 19th International Input−Output Conference (Alexandria, June 2011). He also is grateful to the NSF grant project, 10-612, CNH: Impacts of Global Change Scenarios on Ecosystem Services from the World’s Rivers (Award ID: 1115025), to support his post-doctoral position at Rensselaer Polytechnic Institute. All errors and shortcomings are the authors’ sole responsibility.



ABBREVIATIONS MRIO multiregional input−output IO input−output VW virtual water WF water footprint RS rest of Spain EU European Union RW rest of the world GDP gross domestic product



REFERENCES

(1) Fleskens, L.; Nainggolan, D.; Termansen, M.; Hubacek, K.; Reed, M. Regional consequences of the way land users respond to future water availability in Murcia, Spain. Reg. Environ. Change. 2012, 1−18. (2) National Statistics Institute (NSI = INE). Historical statistics. National and regional accounts. Satellite Accounts of water, Surveys of water supply and treatment, on water use in agriculture and in industry; Madrid, 2011. (3) Hoekstra, A. Y.; Hung, P. Q. Virtual Water Trade: A Quantification of Virtual Water Flows Between Nations in Relation to International Crop Trade; IHE Delft: Delft, The Netherlands, 2002. (4) Hoekstra, A. Y. Human appropriation of natural capital: A comparison of ecological footprint and water footprint analysis. Ecol. Econ. 2009, 68 (7), 1963−74. (5) Duarte, R.; Sánchez-Chóliz, J.; Bielsa, J. Water use in the Spanish economy: An input-output approach. Ecol. Econ. 2002, 43 (1), 71−85. (6) Chapagain, A. K.; Hoekstra, A. Y. Water Footprints of Nations; Value of Water Research Report Series 16; UNESCO-IHE Delft: Delft, The Netherlands, 2004. (7) Cazcarro, I.; Duarte, R.; Sánchez-Chóliz, J. Water Flows in the Spanish Economy: Agri-Food Sectors, Trade and Households Diets in an Input-Output Framework. Environ. Sci. Technol. 2012, 46 (12), 6530−8. (8) Peters, G. P. Opportunities and challenges for environmental MRIO modeling: illustrations with the GTAP database. 16th International Input−Output Conference of the International Input− Output Association (IIOA), Istanbul, Turkey, July 2−6, 2007. (9) Berrittella, M.; Hoekstra, A. Y.; Rehdanz, K.; Roson, R.; Tol, R. S. J. The economic impact of restricted water supply: a computable general equilibrium analysis. Water Res. 2007, 41, 1799−813. (10) Okadera, T.; Watanabe, M.; Xu, K. Analysis of water demand and water pollutant discharge using a regional input−output table: An application to the City of Chongqing, upstream of the Three Gorges Dam in China. Ecol. Econ. 2006, 58 (2), 221−37. (11) Guan, D.; Hubacek, K. Assessment of regional trade and virtual water flows in China. Ecol. Econ. 2007, 61 (1), 159−70. (12) Guan, D.; Hubacek, K. A new and integrated hydro-economic accounting and analytical framework for water resources: A case study for North China. Environ. Manage. 2008, 88 (4), 1300−13.

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(13) Feng, K.; Siu, Y. L.; Guan, D.; Hubacek, K. Assessing regional virtual water flows and water footprints in the Yellow River Basin, China: A consumption based approach. Appl. Geography 2011, 32, 691−701. (14) Lenzen, M. Understanding virtual water flows: A multiregion input-output case study of Victoria. Water Resour. Res. 2009, 45. (15) López-Morales, C.; Duchin, F. Policies and technologies for a sustainable use of water in Mexico: a scenario analysis. Econ. Sys. Res. 2011, 23 (4), 387−407. (16) Wiedmann, T. A review of recent multi-region input-output models used for consumption-based emission and resource accounting. Ecol. Econ. 2009, 69 (2), 211−22. (17) Daniels, P. L.; Lenzen, M.; Kenway, S. J. The ins and outs of water use − a review of multi-region input−output analysis and water footprints for regional sustainability analysis and policy. Econ. Sys. Res. 2011, 23 (4), 353−70. (18) Dietzenbacher, E.; Velazquez, E. Analysing Andalusian virtual water trade in an input−output framework. Region. Stud. 2007, 41 (2), 185−96. (19) Cazcarro, I.; Duarte, R.; Sánchez-Chóliz, J. Water Consumption Based on a Disaggregated Social Accounting Matrix of Huesca (Spain). J. Ind. Ecol. 2010, 14 (3), 496−511. (20) Llano, C. Economiá espacial y sectorial: el comercio interregional en el contexto de un modelo Multirregional para la economiá española. In Colección Investigaciones 1; Instituto de Estudios Fiscales. Ministerio de Economiá y Hacienda: Madrid, 2004. (21) Pérez, J.; Dones, M.; Llano, C. An interregional impact analysis of the EU structural funds in Spain (1995−1999). Pap. Region. Sci. 2009, 88, 509−29. (22) Llano, C. Efectos de desbordamiento interregional en España: Una estimación a través del modelo input-output interregional. Invest. Region. 2009, 16, 181−8. (23) Chenery, H. B. In The Structure and Growth of the Italian Economy; U.S. Mutual Security Agency: Rome, 1953; pp 98−139. (24) Moses, L. N. The Stability of Interregional Trading Patterns and Input−Output Analysis. Am. Econ. Rev. 1955, 45, 803−32. (25) Miller, R. E.; Blair, P. D. Input−Output Analysis: Foundations and Extensions; Cambridge University Press: Cambridge, U.K., 2009. (26) Isard, W. Interregional and regional input−output analysis: A model of a space economy. Rev. Econ. Stat. 1951, 33 (4), 318−28. (27) López-Morales, C.; Duchin, F. Do water-rich regions have a comparative advantage in food production? Improving the representation of water for agriculture in economic models. Econ. Sys. Res. 2012, 24 (4), 371−89. (28) Tello, E.; Ostos, J. R. Water consumption in Barcelona and its regional environmental imprint: a long-term history (1717−2008). Reg. Environ. Change 2012, 12 (2), 347−361. (29) Naredo, J. M.; Frías, J. El metabolismo económico de la conurbación madrileña: 1984−2001. Econ. Ind. 2003, 351. (30) Wackernagel, M.; Schulz, N. B.; Deumling, D.; Linares, A. C.; Jenkins, M.; Kapos, V.; et al. Tracking the ecological overshoot of the human economy. Proc. Natl. Acad. Sci. 2002, 99 (14), 9266−71. (31) Wichelns, D. Virtual Water: A Helpful Perspective, but not a Sufficient Policy Criterion. Water Resources Manag. 2010, 24 (10), 2203−19. (32) Horlemann, L.; Neubert, S. Virtual water tradeA realistic concept for developing countries?; German Development Institute Deutsches Institut für Entwicklungspolitik: Bonn, Germany, 2006. (33) Verma, S.; Kampman, D. A.; Zaag, P. Vd; Hoekstra, A. Y. Addressing India’s Water Challenge 2050: The Virtual Water Trade Option. Proceedings of the Second National Workshop on Strategic Issues in Indian Irrigation, New Delhi, India, April 8−9; International Water Management Institute, 2009; Paper 13. (34) Feng, K.; Davis, S. J.; Sun, L.; Li, X.; Guan, D.; Liu, W.; Hubacek, K. Outsourcing CO2 within China. Proc. Natl. Acad. Sci. 2013, 110 (28), 11654−9. (35) Narayanan, B.; Aguiar, A.; McDougall, R. Global Trade, Assistance, and Production: The GTAP 8 Data Base, Center for Global Trade Analysis; Purdue University: West Lafayette, IN, 2012.

(36) Dietzenbacher, E.; Los, B.; Stehrer, R.; Timmer, M.; de Vries, G. The construction of world input−output tables in the WIOD project. Econ. Sys. Res. 2013, 25 (1), 71−98. (37) Tukker, A.; Poliakov, E.; Heijungs, R.; Hawkins, T.; Neuwahl, F.; Rueda-Cantuche, J. M.M.; Giljum, S.; Moll, S.; Oosterhaven, J.; Bouwmeester, M. Towards a global multi-regional environmentally extended input-output database. Ecol. Econ. 2009, 68 (7), 1928−37. (38) Lenzen, M.; Moran, D.; Kanemoto, K. Building EORA: A global multi- region input − output database at high country and sector resolution. Econ. Sys. Res. 2013, 25, 37−4.

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