Threshold Based Footprints (for Water)

Agriculture accounts for ~90% of India's fresh water use, and there are concerns that future food production will be threatened by insufficient water supply of adequate quality. This study aimed to quantify the water required in the production of diets in India using the water footprint (WF) assessment method. The socio-demographic associations of dietary WFs were explored using mixed effects regression models with a particular focus on blue (irrigation) WF given the importance for Indian agriculture. Dietary data from ~7000 adults living in India were matched to India-specific WF data for food groups to quantify the blue and green (rainfall) WF of typical diets. The mean blue and green WF of diets was 737l/capita/day and 2531l/capita/day, respectively. Vegetables had the lowest WFs per unit mass of product, while roots/tubers had the lowest WFs per unit dietary energy. Poultry products had the greatest blue WFs. Wheat and rice contributed 31% and 19% of the dietary blue WF respectively. Vegetable oils were the highest contributor to dietary green WF. Regional variation in dietary choices meant large differences in dietary blue WFs, whereby northern diets had nearly 1.5 times greater blue WFs than southern diets. Urban diets had a higher blue WF than rural diets, and a higher standard of living was associated with larger dietary blue WFs. This study provides a novel perspective on the WF of diets in India using individual-level dietary data, and demonstrates important variability in WFs due to different food consumption patterns and socio-demographic characteristics. Future dietary shifts towards patterns currently consumed by individuals in higher income groups, would likely increase irrigation requirements putting substantial pressure on India's water resources.

Inter- and intra-annual variation of water footprint of crops and blue water scarcity in the Yellow River basin (1961–2009)

Since the development of Water Footprint environmental indicator, significant research on blue and green crop water use and the respective water footprint estimations has been published. Such research is commonly approached using different methodologies that leverage tabulated values for crop development characterisation, while studies based on remote sensing data are less abundant, despite crop monitoring using remote sensing-based vegetation indices having demonstrated great capabilities and operability. To help fill this gap, we present a methodology that uses a remote sensing vegetation index time series from Sentinel-2 satellite near infra-red and red spectral bands data to derive basal crop coefficient time series to subsequently be used under the Remote Sensing-based Soil Water Balance approach that follows the globally operative FAO56 procedure. It provides pixel-based temporal and spatially distributed estimations of net irrigation requirements and adjusted crop evapotranspiration, with the aim being to divide up the latter and estimate the remote sensing-based green and blue crop water use and the subsequent green and blue water footprint. This is all done under the Agricultural Water Footprint Assessment framework for a growing crop or tree. This methodology was applied over a large, crop-diverse Spanish river basin district (Júcar) and across two different climatological years (humid vs. dry). Its feasibility was demonstrated by the acceptable behaviour of the remote sensing-based blue crop water use estimation for different herbaceous and woody crops, against the official dataset for irrigation water accounting at two water management scales (of a relative mean absolute error of 15.4 % in the case of the largest water user association and of 17.1 % in the case of the river basin water authorities’ own estimations). The proposed approach, which we call Remote Sensing-based Agricultural Water Accounting and Footprint, aims to provide reliable and accurate spatially and temporally distributed thematic cartography about the remote sensing-based blue and green crop water use and water footprint. This information is essential for water managers with the goal of generating transparent and complementary information to incorporate into their own working scales.

China's dietary changes would increase agricultural blue and green water footprint

Agriculture is the largest consumer of freshwater and plays a critical role in addressing global water scarcity. While numerous studies have focused on the water footprint (WF) of various agricultural products, little attention has been paid to changing cropping patterns and their impact on WF. Here, we investigate the impact of conversion from hazelnut fields to kiwi orchards on green, blue, and gray WF between 2010 and 2021 in Ordu, Turkey. Our results show a total increase of 803,901 tons WF for all green, blue, and gray WF. Compared to the previous situation, changing the agricultural product and growing kiwifruit on previously established hazelnut fields increases green WF by 372,106 tons and blue WF by 334,167 tons. Thus, the change of cultivation pattern could significantly contribute to the water scarcity in the area, and at the same time, the increase in WF. Although kiwi cultivation might be advantageous economically, this economic benefit might be an ecological disadvantage as kiwi production is highly dependent on limited blue water resources. Therefore, it is suggested to further promote the rain-fed product, the hazelnut.

The water footprint (WF) concept is a generally accepted tool introduced in 2002. Many studies applied water footprinting, indicating impacts of human consumption on freshwater, especially from agriculture. Although the WF includes supply chains, presently it excludes irrigation supply chains and non-beneficial evapotranspiration, and calculations for agriculture start from crop water requirements. We present a conceptual framework distinguishing between traditional (net) WFs and proposed gross WFs, defined as the sum of net WFs and irrigation supply chain related blue WFs and as the sum of green WFs and green WFs of weeds. Many water management studies focused on blue water supply efficiency, assessing water losses in supply chain links. The WF concept, however, excludes water flows to stocks where water remains available and recoverable, e.g. to usable groundwater, in contrast to many water management approaches. Also, many studies focused on irrigation technology improvement to save water. We argue that not only irrigation technology should be considered, but whole water supply chains, also distinguishing between surface and groundwater, to improve efficient blue water use in agriculture. This framework is applied to the Pakistani part of the Indus basin that includes the largest man-made irrigation network in the world. The gross blue WF is 1.6 times the net blue WF leading to a K value (ratio of gross and net blue WF) of 0.6. Surface water losses vary between 45 and 49 %, groundwater losses between 18 and 21 %. Presently, efficient irrigation receives much attention. However, it is important to take irrigation supply chains into account to improve irrigation efficiency. Earlier WF studies showing water scarcity in many regions underestimate agricultural water consumption if supply chains are neglected. More water efficient agriculture should take supply chain losses into account probably requiring water management adaptations, which is more a policy than an agriculture task.

Abstract. This paper quantifies and maps a spatially detailed and economically complete blue water footprint for the United States, utilizing the National Water Economy Database version 1.1 (NWED). NWED utilizes multiple mesoscale (county-level) federal data resources from the United States Geological Survey (USGS), the United States Department of Agriculture (USDA), the US Energy Information Administration (EIA), the US Department of Transportation (USDOT), the US Department of Energy (USDOE), and the US Bureau of Labor Statistics (BLS) to quantify water use, economic trade, and commodity flows to construct this water footprint. Results corroborate previous studies in both the magnitude of the US water footprint (F) and in the observed pattern of virtual water flows. Four virtual water accounting scenarios were developed with minimum (Min), median (Med), and maximum (Max) consumptive use scenarios and a withdrawal-based scenario. The median water footprint (FCUMed) of the US is 181 966 Mm3 (FWithdrawal: 400 844 Mm3; FCUMax: 222 144 Mm3; FCUMin: 61 117 Mm3) and the median per capita water footprint (FCUMed′) of the US is 589 m3 per capita (FWithdrawal′: 1298 m3 per capita; FCUMax′: 720 m3 per capita; FCUMin′: 198 m3 per capita). The US hydroeconomic network is centered on cities. Approximately 58 % of US water consumption is for direct and indirect use by cities. Further, the water footprint of agriculture and livestock is 93 % of the total US blue water footprint, and is dominated by irrigated agriculture in the western US. The water footprint of the industrial, domestic, and power economic sectors is centered on population centers, while the water footprint of the mining sector is highly dependent on the location of mineral resources. Owing to uncertainty in consumptive use coefficients alone, the mesoscale blue water footprint uncertainty ranges from 63 to over 99 % depending on location. Harmonized region-specific, economic-sector-specific consumption coefficients are necessary to reduce water footprint uncertainties and to better understand the human economy's water use impact on the hydrosphere.

Explaining water security indicators using hydrologic and agricultural systems models

Water resources are a key constraint on sustainable development in arid regions, especially for agricultural production where water use is intensive. To assess the sustainability of agricultural water use in such environments, this study utilizes 2010–2020 agricultural data from the Turpan–Hami Basin and is among the first to integrate the water footprint (WF) theory with the DPSIR (driver–pressure–state–impact–response) model into a comprehensive framework for evaluating water resource sustainability in arid agricultural systems. The agricultural blue, green, and grey WF in the Turpan–Hami Basin were quantified for 2010–2020, followed by a sustainability assessment under the DPSIR framework using a comprehensive weighting method. The results showed a continuous increase in the WF, dominated by the blue WF (>60%), largely due to crops like cotton and grapes, intensifying regional water stress. Turpan experienced prolonged resource overload, while Hami exhibited slightly higher sustainability. DPSIR analysis revealed stronger policy responses in Turpan and significant ecological investments in Hami. Key influencing factors included the crop yield, WF modulus, per capita WF, and water quality shortage index. Overall, sustainability in the basin fluctuated between “Basically Sustainable (Level III)” and “Insufficiently Sustainable (Level IV)”, with slight improvement in 2020. The findings highlight the need for region-specific agricultural optimization, strengthened ecological governance, and improved water-saving strategies to enhance water use efficiency and sustainability in arid regions.

The global water requirements of economic activities have been studied through the concept of the water footprint, which can be captured in multinational Input–Output (IO) frameworks. While useful for looking at aggregate requirements, this paper links the UK’s blue and green water footprint with a country-level water stress index. We show that more than half of the UK’s blue water footprint was in areas of high water stress, while its green water footprint is more concentrated in areas of lower water stress. These findings show how water stress can be incorporated alongside measures of water footprint. This can be critical in evaluating the success of policies aimed to improve national and international water security and reduce water stress.

The current water scarcity situation in South Africa is a threat to sustainable development. The present paper has assessed the water footprint of milk produced and processed in South Africa using the procedures outlined in the water footprint assessment manual. The results show that 1352 m3 of water is required to produce one tonne of milk with 4% fat and 3.3% protein in South Africa. The water used in producing feed for lactating cows alone accounts for 86.35% of the total water footprint of milk. The water footprint of feed ration for lactating cows is about 85% higher than that of non-lactating cows. Green water footprint accounts for more than 86% of the total water footprint of feed ration for lactating cows. Green and blue water footprints are the highest contributors to the total water footprint milk production in South Africa. Water used for feed production for both lactating and non-lactating cows accounts for about 99% of the total water footprint of milk production in South Africa. Particular attention should be given to feed crops with low water footprints and high contribution to dry matter to provide balanced ration with low water footprint. Water users, managers and livestock producers should pay attention to green and blue water consumption activities along the milk value chain and design strategies to minimize them. Corn, sorghum and lucerne production under irrigation in the greater Orange River basin is sustainable, whereas oats production for silage in the same catchment area is not sustainable. Our findings provide the rationale for dairy producers and water users in the dairy industry to get an understanding of the degree of sustainability of their input and output combinations, production choices, and policy interventions, in terms of water use.

Agricultural activities account for a significant portion of global water consumption, emphasizing the need to improve water productivity in this sector. This can be achieved through the implementation of effective agricultural management practices, such as optimizing crop patterns, adjusting irrigation methods, and improving fertilization practices. The Water Footprint (WF) concept offers a comprehensive approach to assessing water consumption in agriculture, considering different types of water use. By integrating the WF methodology with hydrological modeling programs, a more detailed analysis of water consumption patterns can be achieved, overcoming previous limitations in understanding agricultural water use. This study aims to assess the water consumption patterns of maize under different spatio-temporal dynamics. The WF of maize, including blue, green, and grey components, was calculated using the Soil and Water Assessment Tool (SWAT) model in the Ceyhan Basin (Turkey) between 2011-2020. The study outputs indicated considerable spatial and temporal variations, with a total WF ranging from 350 to 1320 m3/t. Green WF (61-385 m3/t) is found to be less dominant in maize production across the basin, while blue water emerges as the primary component (25 to 870 m3/t). In this study, the utilization of the SWAT model provided detailed spatio-temporal results, allowing for adjustments in agricultural patterns. We obtained that, optimizing the cultivation regions of maize within the Ceyhan Basin has the potential to reduce the total WF by approximately 26% and the blue WF by 47%. This optimization could result in an annual saving of around 135 million m3 of irrigation water. Furthermore, the study also analyzed temporal water consumption patterns. The findings highlight the significant potential for water conservation in agricultural activities through the spatio-temporal optimization of blue and green water, taking into account hydrological characteristics.

Remote sensing (RS) has long been a useful tool in global and regional applications. The Water Footprint (WF) of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage. RS provides new tools for global WF assessment and represents an innovative approach to regional and global irrigation mapping, enabling the estimation of green and blue water use. This paper presents an overview of the EU COST Action ES 1106 Assessment of European agriculture water use and trade under climate change (EURO-AGRIWAT), regarding the evaluation of the potential of remote sensing to improve the WF and Virtual Water Trade (VWT) assessment. The main objective is the analysis of the role of satellite data in the suitable models and indices concerned with the analysis of WF and VWT. The main tasks include: an inventory of the existing and near future satellite data records for several European regions that could be used for the WF and VWT assessment; the study of satellite data resolution requirements, in time and space; the analysis of the assimilation of satellite data into models for the determination of green and blue water use; conclusions and recommendations concerning the possibility to integrate remote sensing into WF and VWT accounting. The combination of RS data to assess the volume of irrigation applied, and the green and blue WF faces several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which will be studied.

Forest residue has been proposed as a feasible candidate for cellulosic biofuels. However, the number of studies assessing its water use remains limited. This work aims to analyze the impacts of forest-based biofuel on water resources and quality by using a water footprint approach. A method established here is tailored to the production system, which includes softwood, hardwood, and short-rotation woody crops. The method is then applied to selected areas in the southeastern region of the United States to quantify the county-level water footprint of the biofuel produced via a mixed alcohol gasification process, under several logistic systems, and at various refinery scales. The results indicate that the blue water sourced from surface or groundwater is minimal, at 2.4 liters per liter of biofuel (l/l). The regional-average green water (rainfall) footprint falls between 400 and 443 l/l. The biofuel pathway appears to have a low nitrogen grey water footprint averaging 25 l/l at the regional level, indicating minimal impacts on water quality. Feedstock mix plays a key role in determining the magnitude and the spatial distribution of the water footprint in these regions. Compared with other potential feedstock, forest wood residue shows promise with its low blue and grey water footprint.

In the context of intensive water consumption patterns emanating from urbanization and accelerated economic growth, water footprint (WF) has been recognized as comprehensive measure to promote efficient, equitable and sustainable use of water resources. In the present study, the WF of a river basin was assessed and blue, green and grey water footprints of major water-consuming sectors of agriculture, domestic and industry within the Betwa river basin were quantified. Sustainability of the blue and grey WFs were analysed to identify temporal hotspots wherein water consumption and pollution infringed upon environment flow requirements. Total annual WF of the Betwa river basin was estimated as 9186 Mm3 . Agricultural sector was the largest water consumer accounting for 96.4 % of the total WF, followed by the industrial and domestic sectors (2.2 %). The WF of rainfed and irrigated agriculture was 3868 and 4986 Mm3 , respectively. The comparable proportions of blue (45.5 %) and green (43.6 %) WFs in total WF highlighted equal dependence on rainfall, surface water and groundwater resources. The study demonstrated that consumption-based approach of WF provided more realistic estimates of the water uses at river basin scale. Higher values of sustainability indicators like Blue Water Scarcity Index (>400 during December, January and February) and Water Pollution Index (>135 during January and February) indicated that the pattern of human consumption of blue water and resultant pollution was encroaching into environmental flows within the Betwa river basin.