Global Water Footprint Research Articles

Spatiotemporal dynamics of the water footprint and virtual water trade in global cotton production and trade

Cotton, the world's most widely cultivated fiber crop, is associated with a multitude of environmental impacts, particularly the intensive use of water resources. While previous studies have assessed cotton's water usage through the water footprint concept, they largely focused on spatial variability, leaving temporal dynamics and the issue of unsustainable water use underexplored. This global study addressed these gaps by examining both the spatial and temporal variability of cotton's water footprint and assessing the unsustainable water footprint over time. Additionally, it explored the potential of flax as a water-efficient alternative for fiber production. Using a global gridded crop model, the study simulated yield and water use of flax and cotton from 1972 to 2018 at 30 arcmin resolution. The results showed that the global average blue, green, and total water footprint of cotton decreased by 37%, 48%, and 43%, respectively, due to yield improvements driven by improved crop cultivars, fertilizers, and better water management practices, with climate playing a minor role in these reductions. Despite this, the total water footprint of cotton production increased by 5%, with the blue water footprint rising by 17%. Additionally, unsustainable blue water usage in cotton cultivation increased from 59.3 km³/y to 70.9 km³/y between 1972-1976 and 2014–2018, with 71.1% of the unsustainable water traded virtually. USA, Pakistan, and India accounted for over 60% of this unsustainable virtual water trade. Flax, with its substantially lower water footprint, emerged as a promising alternative to reduce water consumption in fiber production. These findings offer critical insights for formulating strategies to mitigate unsustainable water use in global fiber production.

Evolution of global water footprints of crop production in 1990–2019

Abstract Crop production has the largest water footprint (WF) of all economic sectors and ranks as a leading cause of water scarcity. Despite this, our understanding of historical changes in global WFs of crops remains limited. In this study, we analyse the recently published dataset on green and blue WFs of 175 individual crops in 1990–2019. We explore the main changes in unit WFs (expressed in m3t−1 yr−1) and WFs of production (m3 yr−1) and connect the observed changes to various physical and socio-economic drivers. We find that nearly 80% of crops reduced global average unit WFs (required less water per tonne) as crop yields improved and cultivation centred around more productive areas. However, the total WF of crop production increased by 30% as these productivity gains were insufficient to compensate for cropland expansion of mostly water-intensive crops. Close to 90% of the increase occurred between 2000–2019 likely driven by accelerated economic growth, globalisation, changing diets, and production of first-generation biofuels. Among crops, we observe the largest increases for oil palm fruit, soya beans, and maize as they became the main providers of crop-based nutrients, animal feed, and biofuels for the modern economy. Among regions, most of the increase occurred across the tropics, mainly in Indonesia, Brazil, and Nigeria. However, India, China, and the USA had the largest WFs of production over the study period. Humanity consumed 6.8 trillion m3 of water (87.1% green) to produce crops in 2019. This number is likely to increase in the future which may exacerbate already existing environmental and socio-economic issues. Thus, it is important to transition to more water-sustainable agrifood systems. Much potential still exists in increasing crop water productivity, shifting production to less water-scarce geographies, and rethinking our dietary and industrial consumption patterns.

A Water Scarcity Treaty for the Future

Water scarcity is an increasing global problem, but an international agreement on this issue does not exist. The UN Summit of the Future in September 2024 focuses on achieving existing international goals. The Water Convention and the Watercourses Convention however do not provide sufficient legal basis for mitigating global water scarcity. Since international trade is an important cause, water footprint experts suggest measures from a geographic, a production and a consumption perspective. Obligations to set maximum water footprint caps on river basin level and to formulate international reference values for water efficiency (geographical and production measures) can be inserted in the existing conventions. A consumption-oriented target does not fit in their scope. A separate Water Scarcity Treaty, introducing a reduction target of the global average water footprint per capita per year, is needed. The next UN Water Conferences, in 2026 and 2028, offer new opportunities for proposals towards such a treaty.

Water Footprint of Animal Breeding Industry and Driving Forces at Provincial Level in China

Agriculture significantly contributes to the global water footprint (WF) with the animal breeding industry accounting for over 33% of agricultural water consumption. Since 2000, rapid development in animal breeding has intensified the pressure on water resources. Forecasts indicate a projected 70% increase in freshwater usage in the meat industry by 2025 compared to 2000, particularly in developing countries, such as China, yet comprehensive studies regarding China’s animal breeding industry WF remain limited. This study aimed to assess the variations in the green, blue, and gray WF of pork, beef, milk, eggs, and chicken meat across 31 provinces in China from 2000 to 2017. Additionally, a driving force analysis using the Kaya equation and LMDI method was conducted. Findings revealed that the total WF of animal products increased from 1049.67 Gm3 (in 2000) to 1385.05 Gm3 (in 2017) in China, and pork exhibited a significantly higher WF compared to other animal products, contributing 64.49% to China’s total animal product WF. The sharp rise in the green WF demonstrated regional disparities in water consumption efficiency within the animal breeding industry. The increase in the blue WF was associated with rising livestock numbers and China’s efforts to conserve water. The increase in the gray WF indicated that increased consumption of animal products heightened wastewater treatment pressures, particularly in economically developed provinces. The augmentation in China’s animal product WF was primarily influenced by policy and economic effects, with increased agricultural equipment funding and enhanced production efficiency identified as effective strategies for WF reduction. This study suggests that the promotion of technology, combined with scientific policies, can alleviate the pressure on water resources in the animal breeding industry in developing countries.

Case Study on the Impact of Water Resources in Beef Production: Corn vs. Triticale Silage in the Diet of Limousine × Podolian Young Bulls.

In this study, we have included the water footprint (WF) in the process of optimizing animal feed rations. The global footprint of cattle production accounts for the largest share (33%) of the global water footprint of livestock production. Using two homogeneous groups of Limousine × Podolian young bulls, two different diets were compared: corn silage feeding (CSF), with a corn silage-based diet; and triticale silage feeding (TSF), with a triticale silage-based diet. Silage constituted about 41% and 46% of the feed composition (for CSF and TSF, respectively). Diets were characterised by the same energy and protein content. Despite the lower WF in the TSF group than in the CSF group (7726 vs. 8571 L/day/calf respectively), no significant differences were found in animal performances (i.e., daily weight gain and final weight), feed conversion or income over feed costs. These results show that simple production decisions can have a significant impact on water resource. Therefore, the use of triticale silage should be further promoted, especially in world regions with limited water resources where low WF feed formulation is more strategic than elsewhere.

The Environmental Footprint of Bitcoin Mining Across the Globe: Call for Urgent Action

AbstractBased on a multi‐attribute assessment of the environmental impacts and challenges associated with global Bitcoin (BTC) mining activities around the globe, we call for urgent action by the scientific, policy, and advocacy communities. The worldwide BTC mining network consumed 173.42 TWh of electricity during the 2020–2021 period, bigger than the electricity consumption of most nations. The mining process emitted over 85.89 Mt of CO2eq in the same timeframe, equivalent to the emission caused by burning 84 billion pounds of coal or running 190 natural gas‐fired power plants. The environmental footprint of BTC mining is not limited to greenhouse gas emissions. In 2020–2021, the global water footprint of BTC mining was about 1.65 km3, more than the domestic water use of 300 million people in rural Sub‐Saharan Africa. The land footprint of the global BTC mining network during this period was more than 1,870 square kilometers, 1.4 times the area of Los Angeles. These striking numbers highlight the heavy reliance of the BTC network on fossil fuels and natural resource‐intensive energy sources, resulting in major but unmonitored and unregulated environmental footprints. To mitigate the environmental costs of BTC mining, immediate policy interventions, technological advancements, and scientific research are crucial. Proposed measures include enhanced transparency, economic and regulatory tools, developing energy‐efficient alternative coins, and the adoption of greener blockchain validation protocols.

Are advertising campaigns for water conservation in Latin America persuasive? A mixed-method approach

The United Nations 2030 Agenda for Sustainable Development calls for an urgent reduction of global water footprint. Communication is crucial to respond to this call. However, most water conservation communication campaigns use the knowledge deficit model and overlook persuasive techniques. This paper presents a mixed-method approach consisting of exploratory sequential qualitative (content) analysis followed by a quantitative (cluster) analysis. This approach was used to explore the communication strategies of 95 advertisements promoting water conservation in Latin America. Four widely used persuasion frameworks were analyzed: (1) the elaboration likelihood model (ELM), (2) prospect theory (gains vs. losses), (3) the action framework (i.e., do more vs. take less), and (4) the temporal distance frame. Regarding persuasive characteristics (ELM model), most ads excluded behavioral beneficiaries (58%) and included explicit (60%) and active (52%) messages. Virtually all ads (87%) had a denotative message. Surprisingly, only 3% and 43% of ads used social norms and an authority source, respectively. Regarding the communication strategy, 44% of ads used a loss frame, and 59% focused on the current generation. Cluster analysis was used to classify the sample of ads into homogeneous groups. This analysis leads to a better understanding of the profile of campaigns promoting water conservation. Four advertising profiles were identified: (1) Persuade to act (29%), (2) Motivate without scaring (35%), (3) Raise awareness of water problems (19%), and (4) Warn of water problems (17%). The paper offers a discussion of the implications for social marketers and directions for future research on how to design effective communication campaigns.

Multi-model assessment identifies livestock grazing as a major contributor to variation in European Union land and water footprints

Food systems are the largest users of land and water resources worldwide. Using a multi-model approach to track food through the global trade network, we calculated the land footprint (LF) and water footprint (WF) of food consumption in the European Union (EU). We estimated the EU LF as 140–222 Mha yr−1 and WF as 569–918 km3 yr−1. These amounts are 5–7% of the global LF and 6–10% of the global WF of agriculture, with the EU representing 6% of the global population. We also calculated the global LF of livestock grazing, accounting only for grass eaten, to be 1,411–1,657 Mha yr−1, and the global LF of agriculture to be 2,809–3,014 Mha yr−1, which is about two-thirds of what the Food and Agriculture Organization Statistics (FAOSTAT) database reports. We discuss here the different methods for calculating the LF for livestock grazing, underscoring the need for a consistent methodology when monitoring the food LF and WF reduction goals set by the EU’s Farm To Fork Strategy.

Water Footprint Assessment of Major Crops in Henan Province and Reduction Suggestions

Henan Province, located in the North China Plain, as one of the most important grain production bases in China, is facing severe challenges of water pressure and sustainable development caused by agricultural production. In this study, water footprint (WF) estimation and sustainability assessment of crop production were carried out for wheat and maize, two major crops in the Henan Province. Based on a set of global WF benchmark values for various crops which were established by previous studies, we calculated a set of benchmark values of blue water footprint (BWF, surface water, and groundwater) for major crops in Henan Province. Four benchmark values were calculated for each crop, and we selected two of them as the optimal and sub-optimal benchmark levels. Additionally, potential blue water savings were estimated by reducing the crop-specific BWF to different benchmark levels. According to our simulations with CROPWAT 8.0, the average annual blue water footprint of wheat production in Henan Province from 2006 to 2016 was 7914 Million m3, of which about 77% is unsustainable, and that of maize production is 703 Million m3, of which about 70% is unsustainable. When reducing the water footprint of wheat production to optimal or sub-optimal benchmark levels, approximately 2742 Million m3 or 375 Million m3 blue water can be saved, and reducing that of maize production to optimal or sub-optimal benchmark levels could save approximately 214 Million m3 or 44 Million m3 blue water.

Global warming potential, water footprint, and energy demand of shared autonomous electric vehicles incorporating circular economy practices

With the emergence of research on Shared autonomous electric vehicles (SAEVs) as a futuristic transportation option, it becomes important to explore the environmental implications of these types of vehicles before being implemented on a large scale. This work aims to investigate some of the environmental implications of SAEVs compared to privately owned electric vehicles (EVs) through a set of assessment criteria consisting of their life cycle global warming potential (GWP), water footprint and energy demand. In addition, this work examines how different circular economy (CE) practices and energy mixes influence the SAEV's environmental implications. The analysis conducted shows that SAEVs have higher negative environmental effects than private conventional EVs. However, circularity practices were found to decrease these effects. CE practices reduced the GWP, water footprint, and energy demands of SAEVs by 21.4 %, 18.2 %, and 17.3 % respectively. Results have also shown that utilizing the projected 2050 U.S. energy mix and incorporating CE practices throughout the life cycle of an SAEV will decrease the GWP, water footprint, and energy demand by 46 %, 36.2 %, and 39.3 % respectively. In contrast, by utilizing an energy mix that only consists of the clean energy sources of the 2050 U.S. energy mix in the same proportions but forming 100 % of the mix, the GWP, water footprint and energy demand decrease by 73.2 %, 51.2 %, and 29.1 % respectively. The analysis shows that an SAEV will always have higher GWP, water footprint, and energy demand compared to an EV utilizing the same battery due to deadheading and the increased power consumption caused by the additional automation enabling components.

Environmental impacts and diet quality of popular diet models compared to Turkey's national nutrition guidelines.

This study aimed to compare the environmental impacts and diet qualities of popular diet models with the recommendations of the Turkish national dietary guidelines. Seven-day isocaloric (8368 kJ) diet models were created taking into account the Mediterranean, Atkins (20/40/100), Ornish, Zone diets, and Turkey Dietary Guidelines-2015 recommendations with different food and nutrient contents. Water footprints were evaluated using the global water footprint standards. Greenhouse gas emissions were evaluated using carbon footprint factors compiled as a result of meta-analyses of life cycle analysis studies in the literature. In addition, the quality of diets was evaluated with the Diet Quality Index-International. Atkins20 diet model had the most harmful environmental impact (greenhouse gas emissions 8.74 kg CO2 -eq/per/day and total water footprint 7731 L/per/day), whereas Ornish and Mediterranean diet models (greenhouse gas emissions 2.2/3.07 kg CO2 -eq/per/day and total water footprints 3184/3675 L/per/day, respectively) had less harmful environmental impact. The highest Diet Quality Index-International score was in the Ornish diet model while the lowest Diet Quality Index-International was in the Atkins20 diet model. Ornish and Mediterranean diet models had less harmful environmental impacts, which contributed to sustainable nutrition. The importance of diet quality and environmental impacts should be kept in mind when evaluating diet models to ensure sustainable nutrition.

Global and regional models for identification of cooling technology in thermal power generation for water demand estimations in water-energy nexus studies

Water-energy nexus studies aim to connect the process of power generation with the corresponding water demand. The lack of information on the currently installed cooling systems at individual power plants is a challenge for the assessment of the water use on the power plant-level, which complicates decision-making in water management, especially in water-stressed regions. In this study, we investigate the spatial and temporal trends in cooling technology installations globally. Based on that, we propose a machine learning model for cooling technology identification on a regional and global level, which uses a combination of feature selection and classification algorithms. The global model demonstrates an average test set accuracy of 85.42%, which corresponds to only a minor underestimation of the actual global water footprint of 1.78% when the cooling technology and water footprint of individual power plant units is unknown. Apart from that, a special emphasis was placed on regions characterized by high and extremely high water stress, where mistakes in water policy planning and water management may lead to an unsustainable water use or even to an overexploitation of water resources. In these regions, the calculated test set accuracy was 80.83%, which is significantly larger than the average accuracy of a majority class model. The results and the method proposed in this study enable cooling system identification in individual power units using information available from other sources, such as the water stress score or seasonal freshwater availability in the region.

Exploring the sustainability challenges facing digitalization and internet data centers

Internet data centers have received significant scientific, public, and media attention due to the challenges associated with their greenhouse gas, water, and land footprint. This resource greedy data services sector continues to rapidly grow driven by data storage, data mining, and file sharing activities by a wide range of end-users. A fundamentally important question then arises; what impact does data storage have on the environment and is it sustainable? Water is used extensively in data centers, both directly for liquid cooling and indirectly to generate electricity. Data centers house a huge number of servers, which consume a vast amount of energy to respond to information requests and store files and large amounts of resulting data. Here we examine the environmental footprint of global data storage utilizing extensive datasets from the latest global electricity generation mix to throw light on this data sustainability issue. The analysis also provides a broad perspective of carbon, water, and land footprints due to worldwide data storage to through some light on the real impact of data centers globally. The findings indicate that if not properly handled, the annual global carbon, water and land footprints resulting from storing dark data might approach 5.26 million tons, 41.65 Gigaliters, and 59.45 square kilometers, respectively.

Peranan Penilaian Daur Hidup (Life Cycle Assessment) Dalam Menunjang Perolehan Program Penilaian Peringkat Kinerja Perusahaan (Proper) Pada Industri Mineral Timah

The Ministry of Environment and Forestry added a new criteria, Life Cycle Assessment (LCA) on PROPER assessment 2021. This assessment aims to identify, calculate the sustainable usage of natural resources, discharge of pollution to environment as well as evaluate and implement possible environmental improvements. In the tin mining industry that has negative impact on the environment due to their activities, has to conducted life cycle assessment to support the acquisition of green PROPER. Asociation exporter tin Indonesia proposes scope of LCA from cradle to gate, this scope divided into an upstream process & tin smelterwhich consists of several processing units, namely preparing, smelting, refining, water treatment etc. Functional units are set as input and output references and have been normalized per 1 tonne of tin with impact categories as follows: Global warming, Ozone depletion, acidification potential, eutrophication, photochemical oxidant, abiotic depletion, human toxicity, land use, water footprint and carcinogenic

The Water Footprint of Biodiesel Produced from Sunflower in South Africa

The use of feedstock crops for the production of biodiesel suggests that biodiesel production may have a major impact on the scarce freshwater resource in South Africa. This paper aimed to assess the green plus blue water footprints (WFgreen+blue) of biodiesel produced from sunflower in South Africa using the Global Water Footprint Standard approach. The green (WFgreen) and blue water footprint (WFblue) at the farm level were assessed for sunflower grown under the rain-fed and irrigation production system respectively. The results show that 2617 m3 and 2477 m3 are required to produce 1 ton of rain-fed and irrigated sunflower respectively. At the processing level, about 7.12 L of blue water is required to produce 1 L of biodiesel from sunflower. The WFblue at the processing stage of biodiesel produced from irrigated sunflower was 1.01 m3/GJ, compared to 1.15 m3 m3/GJ from rain-fed sunflower. The WFgreen+blue of biodiesel produced from irrigated and rainfed sunflower was 2477 and 2617 m3/ton, respectively. WFgreen was the largest, accounting for about 59% and 99% for biodiesel produced from irrigated and rain-fed sunflower, respectively. It was further found that water consumption at the farm level accounted for about 99% of the WFgreen+blue of biodiesel in both production systems. Management practices that improve water use efficiency at the farm level may help to lower the WFgreen+blue of biodiesel. Interestingly, the WFgreen+blue is lower for biodiesel produced from irrigated sunflower than for rainfed sunflower. The blue water scarcity assessment showed that blue water scarcity is low during the period when sunflower requires water. As such, purely from a water use perspective, irrigated sunflower production in the Orange Riet Irrigation Scheme may be considered sustainable.

Thermoresponsive Polymers for Water Treatment and Collection

To overcome the current scarcity of fresh water sustainably, new technologies will be required that produce potable water from a range of sources, including seawater and moisture from the atmosphere. Moreover, we must recover and reuse water from wastewater streams to reduce our global water footprint. To date, there remain significant concerns about the environmental/ecological impact, high energy consumption, and extensive maintenance costs of current technologies that might prevent their transition to more sustainable routes of potable water generation. One class of material that can enable low-energy water production is thermoresponsive polymers. Due to their unique phase behavior, production flexibility, and biocompatibility, these materials may allow for sustainable routes to fresh water in current and new technologies. In this Perspective, we specifically summarize the design and application of poly(N-isopropylacrylamide)- (PNIPAm-) based thermoresponsive microgels and hydrogels. In particular, we show how these materials have been used for water purification, including wastewater treatment, seawater desalination, and moisture harvesting from the atmosphere. Finally, we discuss the opportunities and challenges of transforming current thermoresponsive materials into practical water-related technologies.

Historical simulation of maize water footprints with a new global gridded crop model ACEA

Abstract. Crop water productivity is a key element of water and food security in the world and can be quantified by the water footprint (WF). Previous studies have looked at the spatially explicit distribution of crop WFs, but little is known about their temporal dynamics. Here, we present AquaCrop-Earth@lternatives (ACEA), a new process-based global gridded crop model that can simulate three consumptive WF components: green (WFg), blue from irrigation (WFbi), and blue from capillary rise (WFbc). The model is applied to analyse global maize production in 1986–2016 at 5×5 arcmin spatial resolution. Our results show that over the 2012–2016 period, the global average unit WF of maize is 728.0 m3 t−1 yr−1 (91.2 % WFg, 7.6 % WFbi, and 1.2 % WFbc), with values varying greatly around the world. Regions with high-input agriculture (e.g. Western Europe and Northern America) show small unit WFs and low interannual variability, while low-input regions show opposite outcomes (e.g. Middle and Eastern Africa). From 1986 to 2016, the global average unit WF reduced by a third, mainly due to the historical increase in maize yields. However, due to the rapid expansion of rainfed and irrigated areas, the global WF of maize production increased by half, peaking at 768.3×109 m3 yr−1 in 2016. As many regions still have a high potential in closing yield gaps, unit WFs are likely to reduce further. Simultaneously, humanity's rising demand for food and biofuels may further expand maize areas and hence increase WFs of production. Thus, it is important to address the sustainability and purpose of maize production, especially in those regions where it might endanger ecosystems and human livelihoods.

Compliance with EAT-Lancet dietary guidelines would reduce global water footprint but increase it for 40% of the world population.

The EAT-Lancet Commission has proposed a global benchmark diet to guide the shift towards healthy and sustainable dietary patterns. Yet it is unclear whether consumers' choices are convergent with those guidelines. Applying an advanced statistical analysis, we mapped the diet gap of 15 essential foods in 172 countries from 1961 to 2018. We found that countries at the highest level of development have an above-optimal consumption of animal products, fats and sugars but a sub-optimal consumption of legumes, nuts and fruits. Countries suffering from limited socio-economic progress primarily rely on carbohydrates and starchy roots. Globally, a gradual change towards healthy and sustainable dietary targets can be observed for seafood, milk products, poultry and vegetable oils. We show that if all countries adopted the EAT-Lancet diet, the water footprint would fall by 12% at a global level but increase for nearly 40% of the world's population.

Compliance with EAT-Lancet dietary guidelines would reduce global water footprint but increase it for 40% of the world population

Compliance with EAT-Lancet dietary guidelines would reduce global water footprint but increase it for 40% of the world population

Does plastic mulching reduce water footprint in field crops in China? A meta-analysis

Excessive use of water resources is threatening agriculture, other business and populations in China, India and USA, and crop production is expected to play a critical role in the sustainable use of water. In China, plastic mulching is widely employed in crop production, but its impact on agricultural water footprint has not been properly described. A meta-analysis was performed to examine how plastic mulching influences volumetric water availability (VWA), global stress-weighted water footprint per unit of output energy (WFo), and per unit of net economic return in crop production (WFe). Data extracted from 394 published studies in maize (Zea mays L.), wheat (Triticum aestivum L.), and potato (Solanum tuberosum L.) were used in the meta-analysis on crop production at the regional scale and across a range of N fertilization gradients in China. Plastic mulching reduced VWA by 15.3%, 14.1%, and 16.3% in maize, wheat, and potato, respectively, when compared to non-mulching practice, with corresponding reductions of WFo by 33.3%, 28.1%, and 32.1% and of WFe by 14.8%, 31.1%, and 31.0% in maize, wheat, and potato, respectively. Water footprint for crop production increased first and then decreased over the past four decades in China, and was greater in northwest and north central regions of China than in other regions. Under moderate and high N fertilization (>100 kg N ha−1) in dry regions, plastic mulching increased the impact on VWA, thereby reducing WFo and WFe. Water footprint for the production in potato and maize was lower than that in wheat. The meta-analysis demonstrated that plastic mulching practices reduced water footprint while lowering VWA. Therefore, plastic mulching has potential for saving water resource when appropriate growing region and N fertilizer applications are considered.