USING TOTAL WATER FOOTPRINT OF NATIONAL CONSUMPTION AS SUSTAINABLE DEVELOPMENT INDICATOR – A CRITICAL REVIEW

In highly competitive and modern economies, water represents a determinant productive resource and using the water footprint (WF) as a possible indicator in assessing sustainable development is integrated in the overall framework of macroeconomic efficiency analysis. The main aim of this paper is to argue that water footprint could represent a proper indicator in analyzing the sustainable economic development. In this context the territorial distribution of water footprint across the 28 EU countries is analyzed in order to substantiate decisions and achieve sustainable economic development forecasts and strategies at European level. The results have led to the conclusion that, overall, the total water footprint of national consumption in the 28 EU Member States has a very low degree of concentration, therefore, tends towards uniformity. With regard to the three types of water footprint, the main characteristic outcome of the research is the low degree of concentration for gray and green water footprint, while blue water footprint proves a moderate degree of concentration. © 2018 EA. All rights reserved.


A B S T R A C T
In highly competitive and modern economies, water represents a determinant productive resource and using the water footprint (WF) as a possible indicator in assessing sustainable development is integrated in the overall framework of macroeconomic efficiency analysis. The main aim of this paper is to argue that water footprint could represent a proper indicator in analyzing the sustainable economic development. In this context the territorial distribution of water footprint across the 28 EU countries is analyzed in order to substantiate decisions and achieve sustainable economic development forecasts and strategies at European level. The results have led to the conclusion that, overall, the total water footprint of national consumption in the 28 EU Member States has a very low degree of concentration, therefore, tends towards uniformity. With regard to the three types of water footprint, the main characteristic outcome of the research is the low degree of concentration for gray and green water footprint, while blue water footprint proves a moderate degree of concentration.

Introduction
The human being, as a beneficiary of the environment, provokes and generates malfunctions which in time have had a significant impact on the economic and human development. Meeting the growing needs of large human communities, consuming environmental services and territorial resources, have led to less favorable environmental effects. Water represents an essential component of the environment, with a complex use (Galli et al., 2012;Gallopin and Rijsberman, 2000;Hoekstra and Mekonnen, 2012). Monitoring the quality and quantity of water is very important in preventing several problems related to the deficit or the loss manifested in various sectors of the economic activity (Kaplowitz and Witter, 2008).
Moreover, water denotes a limited economic resource that directly and irremediably affects the level of competitiveness of the European economy. The intensity of climate change, and especially the frequency of occurrence and manifestation of phenomena such as drought, but also the growing needs of the population, calls for a complex approach to water issues. Water availability and access to sources of supply are major challenges for EU Member States, given the growing share of economic sectors with a high degree of water dependency. The growing need for securing water resources also requires the optimization of consumption and of the geographical distribution of these resources across the EU.
Integrated and efficient water resource management involves a complex process of measures that include, besides water savings, the reuse of waste water, water transfers and desalination. Extending the life cycle of water must in this context be a fundamental objective for achieving sustainable economic development, not only from a sectoral perspective but also as an integrated management tool. At the same time, the transformations of the paradigm of the European economy imposed the necessity of identifying and promoting alternative and reliable sources for ensuring a sustainable water supply in full compliance with the objectives of encouraging the circular economy at European level. Thus, the following figures present sources of drinking water in the European Union (   Figure 1 shows that drinking water at EU level is ensured from a wide range of supply sources in which groundwater provides about half of the required amount, while surface water cover only 36% of the necessary drinking water. This distribution of supply sources requires the promotion and application of a dynamic water management, from the perspective of security of supply and diversity of sources. However, if we consider the distribution of sources for drinking water in the Member States for the same period (Figure 2), one can notice a non-uniform spread of drinking water sources. Thus, some countries such as Austria and Germany secure their needs from the exploitation of underground water resources, while countries such as Romania and Bulgaria through a mix of exploitation composed both from surface and underground sources. The evolution of water importance and usage in economy has transformed this resource in a potential indicator for understanding sustainable development. In this context, the need for developing a representative indicator has imposed water as a significant candidate in achieveing this goal. Also, given the great importance of water resources in the economy and the multiple roles they play in the everyday life of both people and companies, understanding and promoting an indicator such as water footprint as an  Mekonnen, and Hoekstra (2009) in the case of Netherlands and Sima and Gheorghe (2015) in the case of Romania.
Water footprint represents the indicator that highlights the quantity of water consumed by people in order to produce goods and services, under the impact of direct factors of consumption such as: climatic conditions, agricultural practice, consumption volume of Gross National Income and the consumption model specific to each country (Hoekstra and Chapagain, 2007). As emphasized by available literature (Vanham and Bidoglio, 2013), despite the fact that the water footprint is presented as one aggregate number, it represents a multidimensional indicator of water usage, by combining different types of water consumption and highlighting pollution as a function of space and time.
Furthermore, the water footprint has been analyzed as possible sustainable development indicator in several studies (Lamastra, Suciu, Novelli, and Trevisan, 2014; Varela-Ortega et al., 2009) which may represent important steps in understanding the role and influence of this indicator in shaping the environmental economic behavior.
In adjacent connection with the phenomenon of sustainable development at global level, world organizations have put forward the quantification of the water footprint. The concept of water footprint, closely linked to virtual water is used in analogy with the ecological footprint (Ridoutt and Pfister, 2013; Zhao, Chen, and Yang, 2009).
In this context, the purpose of this research is to analyze the territorial distribution of water footprint across the 28 EU countries in order to substantiate decisions and achieve sustainable economic development forecasts and strategies at European level (Vanham and Bidoglio, 2013). The analysis of territorial distribution was conducted both by measuring the degree of territorial concentration of the water footprint on the 28 EU countries, by graphical and numerical methods, and also by cluster grouping. At the same time, the study was developed taking into consideration the three fundamental components of water footprint: green, blue and gray water footprint of national consumption per capita for the 28 EU countries.
The EU countries are targeting water consumption both in relation to national requirements and to certain consumption related to outsourcing process. Thus, there are countries which, involved in the outsourcing process, considered that the products they import are in direct interdependence with the process of water exhaustion or pollution for the countries that produce them.
The current study is structured into five sections as follows: a brief introduction on the importance of the analysis of territorial distribution of water footprint across the 28 EU countries; the second section includes the methodology and datasets used for research; the third section contains the results of the analysis of the territorial footprint

Research methodology
The basis of the study consisted of the series of statistical data on water footprint of national consumption per capita, (m 3 /yr/cap) available in Hoekstra (2011a, 2011b), synthesized from the time range 1996-2005 and structured as: In (1), n=28 represents the EU-28 Member States, and m=4 stands for the three types of water under analysis (green, blue and gray) and total water.
Taking into account the method of calculating the water footprint, the study envisaged the application of methods by which to examine and measure the distribution of the water footprint of national consumption per capita. Thus, the assessment of the concentration of water footprint of the national consumption per capita (m 3 /yr/cap) shown by major consumption category and by internal and external component in the EU countries is highlighted by applying both graphical procedures (concentration curve) and numerical procedures (Kaplowitz and Witter (2008) Zaiontz (2017) and (Wessa, 2018) The graphical procedure used in the analysis of territorial concentration of the water footprint of national consumption per capita shown by major consumption category and by internal and external component is represented by the concentration curve.
Depending on the method of determining the Gini Coefficient, as an expression of the level of concentration, the concentration curve of the water footprint of national consumption per capita was completed in two variants. The first variant reflects 6 variation ranges in which the EU countries have grouped, as a result of applying the trapezoid method, and the second is in relation to all EU countries (Lorenz curve).
The degree of concentration is represented by the deviation of the concentration curve ( Figure 3) from the diagonal of the square, specifically by the size of the concentration surface. The larger the concentration area, hence the disparity between countries in terms of the water footprint of national consumption per capita is more accentuated, more pronounced the concentration is.
http://ea.bg.ac.rs The main numerical indicator used for water footprint analysis of national consumption per capita is Gini Coefficient (Săvoiu, Crăciuneanu, & Ţaicu, 2010) given by (2): In (2) xi designates water footprint analysis of national consumption per capita at country level and gi represents the water footprint of national consumption per capita corresponding to that country. In this case 2 8 , 1 , Additionally, for analyzing the level of concentration, the following indicators were used: Entropy, Maximum Entropy, Normalized Entropy, Herfindahl, Normalized Herfindahl, Gini Coefficient, and Concentration Coefficient.
To highlight the groups of Member States in which the concentration phenomenon identified by the application of the presented methods appears, the Hierarchical Cluster methodology was used, starting from the data series (1) to which the following transformation was applied (Mooi and Sarstedt, 2011): Subsequently, in order to generate the Proximity Matrix, the Euclidian distance was used, while for determining the distance between clusters the Average Linkage method was employed.
For testing the statistical significance of the mean values of the variables used for generating the clusters, the Welch's Test and F test were employed (Keselman, Othman, Wilcox, and Fradette, 2004). The results indicate the location of each country at European level and the role it has in relation to the other countries regarding the changes over time concerning the water footprint of national consumption per capita. This aspect envisages the development and implementation of policies and strategies aimed at sustainable economic development for the European area.

Results and discussion
Since the water footprint refers to the amount needed to support the population of EU countries, the study started with the identification of the level of concentration of the total water footprint of national consumption per capita for the EU28 countries.
At aggregate level, the direct factors of consumption that determine the water footprint of national consumption per capita (volume of consumption related to Gross National Income, consumption pattern, climatic conditions, agricultural practice) have fluctuated through compensation, hence the 28 countries, as a whole, present a fairly low concentration.
The reduced concentration of 12.68% of the total water footprint of national consumption per capita determined at the cumulative level of EU countries is evidenced both by the calculation of the concentration indicators (Table 1) and by the graphic representation as a result of the application of the trapezoid method.
The Entropy indicator with a value of 3.307, close to the value of Maximum Entropy of 3.33 and Normalized Entropy with a high value of 0.9925 pointing to the upper limit 1, indicates a low concentration of total water footprint of national consumption per EU country. This statement is also confirmed by the results of the indicators Herfindahl (0.0375) and Normalized Herfindahl (0.0019), since they tend towards 0.0357, respectively 0. The concentration curve of EU countries, distributed into groups by total water footprint of national consumption per capita (Figure 4), is rather close to the diagonal of the square, confirming the low concentration of EU countries regarding the water footprint of national consumption per capita.
http://ea.bg.ac.rs In the Gini form, applying the trapezoid method led to the division of EU countries into 6 groups regarding water footprint of national consumption per capita ( Figure 5). In national governmental plans, EU countries have been targeting water consumption to be set both in relation to national requirements and in relation to that consumption leveling the outsourcing process. Water dependence and the results of the algorithm for calculating the trapezoids have led to the conclusion that the UK, Ireland, Slovakia, Poland, Finland, Germany, Sweden, and the Netherlands have the lowest consumption (between 1,258.1 and 1,467.43 m 3 /yr/cap) as it was shown in Mekonnen and Hoekstra (2011a, 2011b). They account for 23.32% of all countries that account for 28.57% of the total water footprint of national consumption per capita.
If we also include Lithuania, Austria, Denmark and the Czech Republic, members of the second group with a slightly higher consumption, then 33.62% of all countries will account for 42.86% of the total water footprint of national consumption per capita. With more water consumed than previous groups, another 5 countries (Croatia, Romania, Estonia, France and Latvia) are added to the 12 countries previously mentioned, so that more than half of all countries (51.03%) make up 60.71% of the total water footprint of national consumption per capita. At the level of the fourth group, the 17 countries together with Belgium and Slovenia will represent 58.82% of their total, accounting for 67.86% of the total water footprint of national consumption per capita.
The fifth group indicates a distribution of 78.57% of the total water footprint of national consumption per capita which belongs to 71.78% of the total EU countries (Malta, Bulgaria and Italy were added to the 19 countries). The countries of the last group, Greece, Hungary, Cyprus, Spain, Portugal and Luxembourg are the largest consumers of water (consumption between 2,304.93-2,514.30 m 3 /yr/cap), as main consumers of agricultural products, especially of meat. This complements the distribution of the water footprint of national consumption per capita across all European Union's countries.
For a clearer picture of the place occupied by each country in distributing the water footprint of national consumption per capita at European level, completing the study with a more detailed analysis of the territorial distribution of the three types of watergreen, blue and gray -proved extremely useful.  (2011a, 2011b). These nine countries, differing from one country to another, have climate and landscapes that are not very favorable, show a high consumption of agricultural products (especially meat, a large agricultural consumer of water), and have farming practices that do not offer the possibility of important water savings. However, across all EU countries, as shown in Figure 6, the particularity of the high level of the total green water footprint of national consumption per capita of the 9 countries did not greatly affect the degree of territorial concentration. The high value of the Entropy indicator, close to Maximum Entropy, and the one of Normalized Entropy, which tends to the upper limit of value 1 (Table 2), show low concentration of the EU countries regarding total green water footprint of national consumption per capita. This concentration tendency is also confirmed by the values of the other concentration indicators that point towards 0357 . 0 1 = n or towards 0.
The Lorenz concentration curve of EU countries by total green water footprint of national consumption per capita (Figure 7(a)) also indicates a fairly uniform territorial distribution of the countries, being very close to the diagonal of the square. The particularity of a significant gap is also encountered when analyzing the concentration of countries for the total blue water footprint of national consumption per capita. The territorial concentration degree of 34% of the total blue water footprint of national consumption per capita by country at EU level is quite low, but higher than in the case of the total green water footprint of national consumption per capita, which requires special attention to the issues deriving from blue water footprint of national consumption per capita. This is evidenced by the values of the concentration indicators determined in Table 2 that are higher than the ones of total green water footprint of national consumption per capita, although they tend towards the upper limits for Entropy and Normalized Entropy and towards the lower limits for Herfindahl, Normalized Herfindahl, and Gini Coefficient.
At the same time, the graphical representation (Figure 7(b)), with the traced curve built at a higher distance than the diagonal, reveals a more marked disparity among countries concerning the total blue water footprint of national consumption per capita compared to the total green water footprint of national consumption per capita.
Started form the consideration that water footprint is a major component of the environmental footprint, the gray water footprint (Figure 9) component represents a proper indictor in highlighting the human pressure on the environment. In this context analyzing the gray water footprint as a component in total water footprint of national consumption per capita could be considered justified in revealing the sustainable development. Starting from the main assumption that gray water footprint has the lowest degree of concentration among the analyzed countries; it could be considered as a basic indicator in understanding the economic impact on the environment pressure. Moreover, the analysis shows that the gray water footprint distribution is very close to the uniform one.
Belgium and Slovenia are the countries with the highest total gray water footprint of national consumption per capita as it was measured in ( The concentration curve (Figure 7(c)), traced through the six groups of countries formed, confirms the almost uniform distribution of countries in terms of total gray water footprint of national consumption per capita. By comparing the three graphs of the three types of water footprint, it is noted that the latter has the closest curve to the square's diagonal, highlighting the approximation of the uniform distribution; this tendency is supported by the results of the concentration indicators ( The analysis of the degree of concentration of the total water footprint of national consumption per capita for the 28 EU countries is deepened by grouping them into clusters. Considering the statistical data series, synthesized from 1996-2005, referring to the water footprint of national consumption per capita, on the three types (green, blue and gray), a dendrogram ( Figure 10) suggesting several clustering solutions (between 3 and 10 clusters) was constructed.
http://ea.bg.ac.rs Subsequently, the methodology determined the number of clusters; the choice is based on both the significant reduction of Total Sum of Squared Error (Peeples, 2011) and better readability of the results. The applied methodology allowed the formation of four significant clusters synthesized by country in Table 3. These clusters were afterwards used in the analysis of water footprint of national consumption per capita. Testing the statistical validity of the chosen solution (the formation of the four clusters) involves testing the hypothesis that cluster membership of each analyzed variable is not statistically significant (Table 4). The results obtained as an outcome of applying relationship (8) ( Table 4) show that the analyzed variables are statistically significant from the point of view of cluster membership because the values of F are higher than the critical value F 0.05,3,24 =3.01. Fulfilling the conditions of statistical significance for the four clusters allows the analysis of the variables green, blue and gray water footprint of national consumption per capita to be further carried out in relation to the mean values determined and presented in Table 5. The detailed analysis of the results comprised in Table 5 covers all the countries in the clusters, for which the evolution of the three variables green, blue, respectively gray water footprint of national consumption per capita is being studied and compared.
Depending on the mean value at cluster level, corresponding to the three variables taken into analysis, it can be stated that most countries (  Taking into account the mean values of the total water footprint of national consumption per capita, a graphical representation ( Figure 11) was made in relation to GDP per capita, in order to clearly show their evolution within clusters.
The data included in the analysis determined the concentration of the countries according to the results obtained by the clustering methodology (Table 3) and the graphical representation ( Figure 11) into the four clusters presented, which leads to the conclusion that the GDP significantly influences the distribution of the water footprint. The obtained results and the graphical representations reflect the low and moderate concentration of the three types of water footprint of national consumption per country.

Conclusions
The paper presents certain aspects related to the degree of territorial concentration of water footprint of national consumption across the 28 EU Member States, considering the three known components: green, blue and gray water footprint. The analysis of the territorial concentration was completed by applying the trapezoid method and the concentration indicators: Entropy, Maximum Entropy, Normalized Entropy, Herfindahl, Normalized Herfindahl, Gini Coefficient, and Concentration Coefficient, and graphical representation through the Concentration Curve namely the Lorenz Curve. At the same time, this analysis was supplemented by the application of the clustering method for the water footprint of national consumption, in the context of highlighting the impact of GDP on water consumption.
The results have led to the conclusion that, overall, the total water footprint of national consumption in the 28 EU countries has a very low degree of concentration, therefore, tends towards uniformity. With regard to the three types of water footprint, there is a low level of concentration in the case of gray and green water footprint, while the blue water footprint provides a distribution with a moderate degree of concentration.
Taking into account the results, the composition of each type of water footprint and the direct factors mentioned in the introduction that act upon it, clearly explain that the water footprint distribution places the following six countries as water-consuming: Greece, Hungary, Cyprus, Spain, Portugal, and Luxembourg; the lowest water consumption is recorded in the UK, Ireland, Slovakia, Poland, Finland, Germany, Sweden, Netherlands.
The eight countries presented as low water-consuming hold their position also for green water footprint due to climate conditions and excessive consumption of meat and agricultural products. At the opposite pole Hungary, Bulgaria, Spain, Portugal and Luxembourg are situated, which, according to the ranking of the territorial distribution of the green water footprint, register the largest quantities of water consumed.
Four of the six water-consuming countries (Spain, Greece, Cyprus, and Portugal) find themselves in the distribution of blue water footprint. Depending on the way it is formed, the climate and the landscape of each country, the low water footprint consumption is justified and listed for: Croatia, Lithuania, Poland, Latvia, Hungary, Slovakia, Romania, Finland, Czech Republic, Bulgaria and Germany. Belgium and Slovenia are the countries with high gray water footprint consumption, while Lithuania, Slovakia, Estonia, UK, and Ireland occupy the last places in the hierarchy of countries consuming this type of water.
The results of clustering highlight the same aspects of territorial concentration of water types by country, but the four clusters complete the analysis of the mean values obtained and the link with the GDP, stressing the place and role of the water footprint in the EU as a whole, but also in the economy of each country. These results, employing concentration methods, lead to a hierarchy that emphasizes to a certain extent the level of each Member State, proving useful for the national policy adopted by each country. At the same time, as they represent a firm starting point, the perspectives of analyses of the water footprint distribution can be continued both on the three types of water and on the various categories of activities (agriculture, industry, domestic), while considering the internal and external dimensions.