The field of WFA is rooted in four basic thoughts. The first is the idea that freshwater is a global resource (Hoekstra and Chapagain 2008), because people in one place can and do make indirect use of freshwater resources elsewhere through VWT (Allan 2001), and because local water allocations and patterns of unsustainable water consumption are increasingly driven by the global economy which lacks incentives for sustainable water use (Hoekstra 2013). The second idea is that freshwater renewal rates are limited, so we must study the development of consumption, production and trade patterns in relation to these limitations. In broader sense, when analysing the environmental sustainability of economies, it is necessary to study the ‘footprint’ of human consumption in relation to planetary boundaries. When creating the WF concept, I was inspired by the ‘ecological footprint’ that had been developed by Wackernagel and Rees (1996). The third idea is that for understanding natural resources use and impacts of consumption, we have to think in terms of supply chains and product life cycles. The fourth idea is that in a comprehensive approach towards freshwater use and scarcity, we must consider both green and blue water consumption (Falkenmark 2000) as well as water pollution (Postel et al. 1996). The field of WFA is thus fundamentally interdisciplinary and integrative, with papers published in both ‘environmental sciences’ and ‘water resources’ journals. Broadly spoken, WFA bridges the two interdisciplinary communities by bringing environmental thinking (footprint and supply chain thinking) into the water resources community and by bringing water resources thinking (water allocation, water productivity, water scarcity) into the environmental sciences community.
Distinguishing Green, Blue and Grey WFs
The WF is a measure of consumptive and degradative freshwater use. The consumptive WF includes a green component referring to the consumption of rainwater, and a blue component referring to the consumption of surface water or groundwater. The degradative WF, the so-called grey WF, measures the volume of water required to assimilate pollutants entering freshwater bodies (Hoekstra et al. 2011). In early WF studies, the focus was just consumptive water use. From the start, water consumption was understood to include both green and blue water consumption, but they were presented as a total, because the models applied did not allow to make explicit distinction between the two components (Hoekstra and Hung 2002). The inclusion of green water consumption in the WF metric was an important and deliberate decision, inspired by the work of Falkenmark (2000), who had introduced the green-blue water terminology in order to broaden the perspective of water management beyond the historical focus on blue water. The first paper to assess a crop’s green and blue WF separately was by Chapagain et al. (2006b). That same paper introduced the grey WF, albeit not yet under that name, but presented as a ‘dilution water volume’ necessary to assimilate a pollutant load. This appeared to be an unfortunate term, because some took it in a normative sense as if it was proposed to solve pollution through dilution. That was of course not the intention; the idea was to express water pollution in terms of the claim it puts on scarce freshwater resources by expressing pollution in terms of the amount of water it takes to assimilate it. Water pollution in that sense competes with water consumption. Hoekstra and Chapagain (2008) presented the green, blue and grey WF for the first time in one coherent framework. Hoekstra et al. (2011) made a slight improvement in the definition of the grey WF by accounting for natural concentrations of substances in water bodies, thus decreasing the capacity to take up additional loads from anthropogenic origin given maximum allowable concentrations. Whereas the first grey WF studies were limited to just pollution through nitrogen, today, grey WF studies have been carried out for a variety of water quality parameters, including nutrients, dissolved solids, metals, and pesticides. Whereas a few studies have already distinguished between different types of blue WF, depending on the source of the water (surface water, renewable groundwater, fossil groundwater, or capillary rise), it may be expected that this will increasingly be done, when data allow, since the potential implications of these different shades of blue WF may be different.
From Concept to Field of Analysis
The initial stage of development was centred around the quantification of WFs of crops, VWT related to crop trade and WFs of national consumption (Hoekstra and Hung 2002). The basis for the national WF estimation was the accounting scheme shown in Fig. 1. Hoekstra and Chapagain (2007, 2008) improved the national WF accounts by considering all forms of consumption and trade, including animal and industrial products and municipal water use as well. Until 2008, the focus remained on national WFs in relation to consumption and on accounting. Afterwards, the scope broadened, whereby also the production perspective received increasing attention, driven by the growing interest from companies, which started to discover the use of the WF concept in 2007. Another driver was the interest to analyse aggregate WFs of production within certain geographic areas in order to put them in the context of the limited water availability per area. These advances resulted in the development of a larger conceptual framework, as shown in Fig. 2, allowing the quantification of WFs at the most basic level of a single process or activity, the WFs of products, the WF of consumption at individual or community level, the WF of production in a certain area, and the operational and supply-chain WFs of companies. With the broadening of scope, terminology regarding water consumption per unit of product changed from ‘specific water demand’ (Hoekstra and Hung 2002) or ‘virtual water content’ (Hoekstra 2003) to ‘water footprint of a product’ in order to have consistency when aggregating WFs of products to the WF of a basket of products or further to the WF of a consumption pattern or diet (Hoekstra et al. 2011).
Around 2008, there was a broadly felt need to move beyond a concept and work on a more elaborate assessment method, recognizing that a quantification of WFs yields interesting figures but does not address the ‘so what’ question and policy implications. The full WFA method was developed in consultation with stakeholders from the private and public sector over the years 2008–2011, which resulted in the Global WFA Standard of the Water Footprint Network (Hoekstra et al. 2011). The method includes four steps: setting scope of analysis, accounting, sustainability assessment, and response formulation. The sustainability assessment step addresses the ‘so what’ question by putting WFs in the context of sustainability, efficiency and fairness, recognizing that WF figures in themselves tell little if not compared to reference levels. In this stage, new concepts were developed, like the idea of the ‘maximum sustainable WF’, to be translated into ‘WF caps’ per river basin, the idea of ‘WF benchmarks’ for processes and products as a reference for what WF level could be achieved based on the use of certain good or best technology or practice, the idea of ‘blue and grey WF permits’ as opposed to water abstraction and wastewater discharge permits, the idea of ‘fair WF shares’ as a tool to discuss WFs of communities, and the concepts of ‘supply-chain water risk’ for companies and ‘imported water risk’ for countries (Hoekstra 2013).
Relation to Other Research Fields
The maturing of the research field has led to an increasing exchange with other fields of investigation. While initial WFA studies were little integrated within the broader field of integrated water resources management (IWRM), we see a growing integration of WF and VWT notions in regular water management studies. In addition, we see that WFA is integrated into broader environmental and economic research. First of all, the research community working on environmentally extended input-output modelling started to incorporate WFs into their tools (Ewing et al. 2012), allowing for the full tracing of virtual water flows across economic sectors and regions. The life cycle assessment (LCA) community has started to incorporate the WF into LCA (Boulay et al. 2013) and scholars working on corporate environmental indicators, corporate social responsibility and corporate water stewardship started to integrate the WF in their frameworks as well (Herva et al. 2011; Sarni 2011). Furthermore, an increasing number of scholars is working on integrating different footprints in more holistic environmental footprint studies (Hoekstra 2009; Galli et al. 2012) and linking footprint work to the concept of planetary boundaries (Hoekstra and Wiedmann 2014; Fang et al. 2015). With the transition from a fossil to biobased economy, carbon footprint studies will gradually make place for land and water footprint studies, because biobased essentially means based on scarce land and water resources. Finally, the idea of ‘zero WF’ as the ultimate target for industrial processes fits within studies on the circular economy.
The Emergence of WF Studies at Different Geographic Scales
A series of global WFAs has been carried out over the years. The first WF study estimated the WFs of national consumption for most countries of the world (Hoekstra and Hung 2002). In a second global assessment, improvements were made by including a larger range of products (Hoekstra and Chapagain 2007, 2008). Whereas both assessments were done at the country level, a third global assessment was based on a high spatial resolution (Hoekstra and Mekonnen 2012). Another global WFA around the same time was carried out by Fader et al. (2011). Chen and Chen (2013) were the first to make a global WFA using a multi-region input-output model as opposed to static trade databases to estimate international VWT. Ercin and Hoekstra (2014) were the first to develop future global WF and VWT scenarios.
Country-specific studies emerged since 2006 (Ma et al. 2006), river-basin studies since 2008 (Aldaya and Llamas 2008), urban studies since 2009 and site-specific studies (for specific crop fields and factories) since around 2010 (see Supporting Material). Whereas the country and urban studies generally consider primarily the internal and external WF of consumption of citizens, the river basin studies tend to focus on the WF of production within the basin. Most site-specific studies focus on the WF from a local production perspective as well, without considering supply chains. Many of the more local studies are fed by results from the global studies, since local studies can be more specific in terms of spatial detail within the area studied, but as for data on WFs of imported products and on the sustainability of those WFs elsewhere, one has to rely on other studies.
The Emergence of Product, Sector and Corporate WF Studies
Hoekstra and Hung (2002) estimated the WFs of 38 crops, per country. Hoekstra and Chapagain (2007, 2008) estimated, again per country, WFs of all primary crops (and various derived crop products), WFs of eight types of animal (and animal products like meat, milk, butter, cheese, leather) and WFs of the industrial and municipal sectors. Mekonnen and Hoekstra (2011, 2012a) made improvements and applied a high spatial resolution, thus accounting for spatial variability in climate, soils and other production conditions. More specific product studies started to appear in 2006 with a study on cotton (Chapagain et al. 2006b). WF studies have been published now on a wide variety of products, including food and beverage products (Ercin et al. 2011, 2012), fibre products like textiles (Chico et al. 2013) and paper (Van Oel and Hoekstra 2012), cut flowers (Mekonnen et al. 2012), packages, minerals, construction materials and manufactured products like cars and computers (see Supporting Material). Sector studies were published for instance for beverages, electricity, transport, tourism, and food aid. WF studies from specific companies started to appear after a first study from SABMiller and WWF-UK (2009). A great problem in most of these applications is the tracing of supply chains and obtaining specific data rather than crude global estimates. This is particularly true for products with long and complex supply chains like animal and manufactured products. For animal products, for instance, the diet of the animal and feed origin is crucial, but in many cases it is difficult to trace the precise composition and origin of feed concentrates.
The WF of Dietary Choices – the Water-Food Nexus
The impact of diet on the WF of consumption has been studied since 2010. Hoekstra (2010) estimated a potential overall WF reduction of 36% in the industrialised world and 15% in the developing world if people would replace meat by nutritionally equivalent crop products. Mekonnen and Hoekstra (2012a) showed that for any animal product there are crop products with equivalent nutritional value that have a substantially smaller WF. The average WF per calorie for beef was found to be 20 times larger than for cereals and starchy roots. The WF per gram of protein for milk, eggs and chicken meat was estimated to be 1.5 times larger than for pulses. For beef, the WF per gram of protein is six times larger than for pulses. Ercin et al. (2012) found the WF of 1 l of cow milk to be three times larger than for 1 l of soy milk, and the WF of a beef burger 15 times larger than for a similar soy burger. Vanham et al. (2013) estimate that a shift from current to vegetarian diets, would result in a WF reduction of 41% for Southern and Western Europe and reductions of 27% and 32% for Eastern and Northern Europe, respectively. Jalava et al. (2014) estimate that a global shift from current diets to recommended diets (following the dietary guidelines of the World Health Organization) plus a replacement of animal products by nutritionally equivalent local crop products would reduce the food-related global green WF by 23% and the global blue WF by 16%.
The innovation of these studies on the relation between diet and water consumption lies in the fact that efforts to mitigate water scarcity through water demand management have traditionally focussed on the question how to increase water productivity in crop production and raising livestock, while a more fundamental question remained unaddressed: how water efficient is the food production system as a whole? WF studies open up the possibility to study the ‘nutritional water productivity’ of the global agricultural sector, i.e., how many kilocalories or grams of protein are produced per drop of water. Another focus of research has become the WF of food waste; it has been estimated that the blue WF for the production of total food wastage is about 250 billion m3, which is 3.6 times the blue WF of total USA consumption (FAO 2013).
The WF of the Energy Mix – the Water-Energy Nexus
Research on the WF of energy started with studies for bio-energy (Gerbens-Leenes et al. 2009; Dominguez-Faus et al. 2009), followed by research on the WF of hydro-electricity (Mekonnen and Hoekstra 2012b). Currently, we have a reasonable understanding of the WF of all different forms of energy, covering both the fossil and renewable sources (Mekonnen et al. 2015). Per unit of energy, the WF of bioenergy and hydroelectricity is two to three orders of magnitude larger than for fossil fuels and nuclear. The variation for bio-energy is large, since the precise form (e.g., first or second generation bio-energy, which crops or other organic material, and which production circumstances) hugely matters. The variation for hydropower is large as well, depending on the location and characteristics of the reservoir. Electricity from concentrated solar power (CSP) has a similar WF to fossil fuels, while geothermal can be an order of magnitude smaller or even less. The WF of photovoltaic (PV) and wind energy is one to two orders of magnitude smaller than for fossil fuels.
WF studies have been instrumental in showing the water implications of the energy transition from fossil to renewable. The ‘greenest’ of the existing energy scenarios (with quickest and largest CF reduction) will greatly enlarge the WF of global energy production, because of the large fractions of bio-energy and hydro-electricity in the mix. The only way to reduce both carbon and water footprint of energy production appears to be if all investments are aimed towards wind and solar energy (Mekonnen et al. 2016). Future research will undoubtedly focus on how the energy transition will change interregional energy dependencies and thus power relations, because future energy supply will depend on the availability of land, wind and water resources to produce the renewable energy. If only 10% of fossil fuels in today’s global transport sector were replaced by bioethanol from relatively efficient crops, global water consumption would increase by 7% (Gerbens-Leenes and Hoekstra 2011). Future energy scarcity will essentially be land and water scarcity, so the land and water footprints of energy will be at the core of future energy research.
An additional concern is that the energy return on investment (the EROI factor) for renewables is much lower than for fossils; the energy demand for generating energy will thus become substantial, putting additional claims on land and water (Mekonnen et al. 2015). With current energy-intensive agricultural practices, net energy output is far lower than gross energy production, sometimes even near zero.
PV panels and CSP systems are more efficient in capturing incoming solar radiation than photosynthesis, thus generating more energy per square metre. Since substantial growth of bioenergy – beyond using rest streams of organic material – is impossible, our economies will increasingly depend on wind and solar power, which will drive the electrification of the transport sector, but also electric heating, at least where surplus heat from industrial processes or geothermal energy does not offer a solution. Further on, we will need to find ways to store energy and design electrical grids that can handle the large variability of both electricity demand and supply.
Putting WFs and VWT in Context
Since 2009, an increasing number of papers put WFs of production and consumption and VWT in the context of what is sustainable, fair and efficient (Hoekstra 2013). In a case study for the Netherlands, Van Oel et al. (2009) were the first to put the external WF of national consumption in the context of local scarcity in the regions of production, thus identifying critical hotspots. The approach was refined by Ercin et al. (2013) in a case study for France and further by Hoekstra and Mekonnen (2016) for the UK. The latter study also shows the level of water-use efficiency in all the locations of UK’s external WF. Lenzen et al. (2013) showed to which extent international virtual water flows in the world originate from water-scarce places.
Based on estimates of WFs at a high temporal and spatial resolution level and high-resolution data on freshwater renewal rates, it has become possible to assess water scarcity at a greater level of detail than ever before, showing where precisely WFs exceed maximum sustainable levels and which types of water use (e.g., which crops) are responsible for that. It has been shown that blue WFs exceed maximum sustainable levels by a factor two for at least one month per year in half of the four hundred largest river basins in the world (Hoekstra et al. 2012) and that about 4 billion people in the world live in areas that experience severe water scarcity at least one month per year (Mekonnen and Hoekstra 2016). It has also become possible to relate WFs and virtual water trade to the overexploitation of specific aquifers, as shown for example by Marston et al. (2015) for the United States. Grey WFs can be put in the context of a river basin’s assimilation capacity. For nitrogen and phosphorus pollution, it has been shown that grey WFs exceed maximum sustainable levels in many catchments in the world (Liu et al. 2012; Mekonnen and Hoekstra 2015).
It has become possible to discuss fairness of water use by comparing the WFs related to the consumption levels and patterns of different communities (Hoekstra 2013). Given that WFs have passed levels of what is maximally sustainable in half of the world’s major river basins, one may conservatively assume that the WF of humanity as a whole – currently averaging at 1400 m3/y per capita – should at least not increase in the future. Future population growth implies that the maximum sustainable level per capita will decline. In the hypothetical case that fairness would be interpreted as an equal water share for every world citizen, this would imply an enormous WF reduction challenge for countries with current WFs beyond the average, like the US (Fig. 3). Future research is needed to better understand the complexities involved here, including questions on what are precise sustainability levels, what is fair given human rights for water and food, what reductions can be achieved through greater water-use efficiencies and to what degree consumption patterns would need to be adapted. One question is also what is the potential VWT may offer. Seekell et al. (2011) and Suweis et al. (2011) find that current VWT is primarily driven by gross domestic product and social development status of countries rather than spatial patterns of water scarcity and solidarity toward water-stressed populations. Studies have shown that VWT results in modest global water saving (Chapagain et al. 2006a) and that global VWT leads to a slightly more equal global distribution of water resources (Seekell 2011), but it comes with adverse environmental impacts and the risk of long-term water dependency for water-scarce nations. This leads to the need of further inquiry in what Suweis et al. (2013) call the water-controlled wealth of nations.
WF research has resulted in discussions around water-use efficiency from three different perspectives: the production perspective (local water-use efficiency), the trade perspective (global water-use efficiency) and the consumption perspective (consumer water-use efficiency). Local water-use efficiency can be assessed by comparing the WF of a specific process or product to a WF benchmark for that process or product, which can be based for instance on best available technology and practice (Hoekstra 2013; Mekonnen and Hoekstra 2014; Chukalla et al. 2015). Further research is needed on the effectiveness of regulations or economic instruments to motivate water users to reduce WFs to benchmark levels. Global water-use efficiency depends on whether water-intensive commodities are dominantly produced in relatively water-abundant regions with high water productivity and traded to places characterized by the opposite (Hoekstra 2013). Questions remain on how water scarcity can be better factored into the world economy. Water-use efficiency from the consumer point of view refers to the fact that consumers can seek to fulfil certain demands (e.g., certain amount of kcal and protein per day) in alternative ways, some of which will have a much smaller WF than others. It is quite a new field of research to see how consumers can be incentivized to account for indirect environmental impacts in their shopping choices.
Future WFA research will likely concentrate more on questions around the sustainability, equity and efficiency of WFs than more narrowly on quantification of WFs as in the past. In addition, WFs will increasingly be put in the context of associated risks. Water dependency and security can be assessed by analysing the extent to which companies or communities depend on unsustainable water use in their supply chain. Where companies have supply-chain water risks (Sarni 2011), countries have an ‘imported water risk’ (Hoekstra and Mekonnen 2016).
Data Sources, Models, Spatial and Temporal Resolution, Scenarios and Uncertainties
The first WF studies were done based on FAO’s CropWat model, national production statistics and international trade data (Hoekstra and Hung 2002). The first global grid-based assessment, at 5 × 5 arc minute resolution, was published in 2011, again using the CropWat model for estimating WFs in crop production (Mekonnen and Hoekstra 2011). More recently, FAO’s AquaCrop soil-water-balance and crop-growth model has been employed in several studies, with an added module to partition ET into green and blue ET (Chukalla et al. 2015; Zhuo et al. 2016a). Other models applied to estimate WFs of crop production include EPIC (Liu et al. 2007) and LPJmL (Fader et al. 2011). Next to modelling, the usefulness of remote sensing in assessing WFs has been explored (Romaguera et al. 2010), with the long-term potential of real-time monitoring. Modelling in combination with national statistics, field measurements and remote sensing products will likely improve the quality of the assessments. The field has to mature still in terms of calibrating model results against field data, adding uncertainties to estimates and inter-model comparisons as done in the field of climate studies. Furthermore, past studies mostly focused on average WFs over multi-year periods, although since 2010 an increasing number of studies show historical times series, with data year by year, enabling the analysis of variability and trends (Dalin et al. 2012; Zhuo et al. 2016a). A few WF and VWT scenario studies – considering the future implications of population and economic growth, diet changes, technological advances, the energy transition and climate change – have been published (Ercin and Hoekstra 2014, 2016; Orlowsky et al. 2014), but this branch of study is in its infancy.
Standards and Guidelines
The first WF standard was developed by Water Footprint Network (WFN) in consultation with a broad array of stakeholders over the period 2008–2011, a process that resulted in the 2009 draft and 2011 final Global WFA Standard (Hoekstra et al. 2011). The beverage industry published a guideline largely consistent with this standard (BIER 2011). In the years 2012–2013, WFN hosted an international expert group to develop grey WF guidelines, providing additional practical help in assessing the grey WF for a variety of chemicals (Franke et al. 2013). In 2014, ISO published an assessment and reporting standard related to the WF of products, processes and organizations based on LCA (ISO 2014). Unfortunately, this standard is inconsistent with WFN’s standard; the difference partly lies in method, which is understandable, because ISO focusses on product LCAs and environmental impact, while the WFN standard offers a broader framework, in which WFs can be studied with different focus (product, producer, consumer or geographic focus) and from different perspectives (environmental sustainability, social equity, resource efficiency or water risk). However, ISO also confusingly deviates in terminology. A key difference is that ISO requires water consumption to be multiplied with a ‘characterization factor’, whereby in practice it has been proposed to multiply water consumption by local water scarcity (Ridoutt and Pfister 2010), which has been criticized for being inconsistent with the way other environmental footprints are defined (Hoekstra 2016).