Spatially Explicit Analysis of Water Footprints in the UK

Abstract

Abstract:The Water Footprint, as an indicator of water consumption has become increasingly popular for analyzing environmental issues associated with the use of water resources in the global supply chain of consumer goods. This is particularly relevant for countries like the UK, which increasingly rely on products produced elsewhere in the world and thus impose pressures on foreign water resources. Existing studies calculating water footprints are mostly based on process analysis, and results are mainly available at the national level. The current paper assesses the domestic and foreign water requirements OPEN ACCESSWater 2011, 3 48 for UK final consumption by applying an environmentally extended multi-regional input-output model in combination with geo-demographic consumer segmentation data. This approach allows us to calculate water footprints (both direct and indirect) for different products as well as different geographies within the UK. We distinguished between production and consumption footprints where the former is the total water consumed from the UK domestic water resources by the production activities in the UK and the latter is the total water consumed from both domestic and global water resources to satisfy the UK domestic final consumption. The results show that the production water footprint is 439 m 3 /cap/year, 85% of which is for the final consumption in the UK itself. The average consumption water footprint of the UK is more than three times bigger than the UK production water footprint in 2006. About half of the UK consumption water footprints were associated with imports from Non-OECD countries (many of which are waterscarce), while around 19% were from EU-OECD countries, and only 3% from Non-EU-OECD countries. We find that the water footprint differs considerably across sub-national geographies in the UK, and the differences are as big as 273 m 3 /cap/year for the internal water footprint and 802 m 3 /cap/year for the external water footprint. Our results suggest that this is mainly explained by differences in the average income level across the UK. We argue that the information provided by our model at different spatial scales can be very useful for informing integrated water supply and demand side management.

Water Footprint of Cities: A Review and Suggestions for Future Research

“…For example, Feng et al [125] found that the consumption WF per person for London, UK, was 58% higher for direct water use and 79% higher for virtual water use than the national average. Feng et al [128] also found this for urban household's in the Yellow River basin identifying a 50% higher WF than rural households.…”

“…The urban WF studies have been performed for Beijing, China [66,97,[121][122][123]; Milan [124]; London, UK [125]; as well as Berlin, Delhi, and Lagos in Germany, India, and Nigeria, respectively [69]. Hoff et al [69] found that Berlin imported more than 60% of its virtual water from abroad whereas the virtual water for the developing cities of Delhi and Lagos primarily came from domestic sources.…”

“…For instance, together with assumptions for the local redistribution of production surpluses and deficits, Hoff et al [69] downscaled national WF estimates based on gridded population, while Feng et al [125] combined national (e.g., IO tables) and local (e.g., income, demographic, and consumption estimates) data when determining the WF at the local authority level in the UK. The need to relate and employ datasets from different scales (e.g., national, subnational, and local) in urban WF studies can be an important source of WF variability and uncertainty that needs to be further understood and quantified.…”

Review of Methodologies of Water Footprint.

“…They used a method based on bottom-up approach which combines water use in detailed descriptions of individual production process and in consumption. Since energy comes from domestic and external sources, both sources are factored into the computation (Okadero et al, 2014;Feng et al, 2011). Energy sector by its very nature is water intensive and this can be used by countries whose water resources are poor to decide on the energy production method to adopt which will not severely affect water availability for other economic and domestic uses.…”

Combination of Assessment Indicators for Policy Support on Water Scarcity and Pollution Mitigation

“…Conversely, the top-down approach moves from the highest level to the lower level according to the boundaries of a defined system and subsystem [7]. The I-O model initially developed by Leontief [19], a top-down technique, has been extensively applied to assess VW and WF, as well as sectoral water use on a regional or national scale [20][21][22][23][24][25][26][27][28][29]. Due to the high level of aggregation, the I-O technique is not adept at providing detailed calculation of a specific technique or product [13].…”