Water Footprint of Cities: A Review and Suggestions for Future Research
Abstract
:“Water flows uphill to money”—Western U.S. Folklore
1. Introduction
2. Methodologies for Water Footprint Analysis
Blue Water | Green Water | Grey Water |
---|---|---|
Volume of water sourced from surface water or groundwater/baseflow. Determined by modeling evapotranspiration for irrigated water or a consumptive water coefficient is applied for water withdrawals. | Volume of water that is determined by the moisture in the soil-water evapotranspired through plants and soils. Evaluated for agricultural processes. | Volume of water necessary to assimilate waste flows. Primarily evaluated for nitrogen and phosphorous content in return flows. Determined by dividing pollutant load by the difference in the maximum acceptable concentration and the natural concentration of the receiving water body. |
WF Method | Scale | Advantages | Disadvantages |
---|---|---|---|
Water Footprint Assessment (WFA) | Product level (bottom-up) | WaterStat database. Detailed analysis of agricultural products to give specific estimates of foods grown in certain regions. Dietary WF may be an easier communication tool. Partial supply chain assessment. Takes a systems approach to evaluate sustainability. Evaluates blue, green, and grey water. | Primarily uses national or state/province level averages that do not show unique consumption patterns of the city. |
Environmentally extended input–output (EEIO) | Sector level (top-down) | Full supply chain assessment. Can identify hot spot sectors as key water users, assess the water inter-dependency and efficiency of sectors, and identify the “water multiplier” indicating the degree of virtual water recycling between sectors within the city. Can easily compare changes across time using IO tables. | Aggregation errors within each sector and disaggregation errors as IO tables are often not created at the urban scale. Primarily considers blue water. |
Life cycle assessment (LCA) | Product level (bottom-up) | Full supply chain assessment. Explicit consideration of human and environmental impacts. Accounts for opportunity costs of water use. Assists businesses in evaluating supply chain water use and impacts. | Focus is on individual products. Difficult to account for all products within the city. Rely on databases that might be limited by the regional or product detail that is available. Inventory stage considers blue water. |
2.1. Water Footprint Assessment (WFA)
2.2. Environmentally Extended Input–Output (EEIO)
2.3. Life Cycle Assessment (LCA)
3. Water Footprint Studies at Different Spatial Scales
3.1. National Scale
3.2. Subnational Scale
3.3. Urban Scale
* | City/Region | Study by | Water Footprint | Methodology ** |
---|---|---|---|---|
C | Berlin, Delhi, and Lagos | Hoff et al., 2013 [69] | Green and blue † | WFA |
C | Milan, Italy | Vanham, 2014 [124] | Green, blue, grey | WFA |
R | California | Fulton et al., 2014 [129] | Green, blue, grey | WFA |
B | Heihe River basin, China | Zeng et al., 2012 [131] | Green and blue † | WFA |
B | Yellow River basin, China | Zhuo et al., 2014 [130] | Green and blue | WFA |
B | European River basins | Vanham, 2013 [132] | Net virtual water | WFA |
S | Interstate transfers in the U.S. | Mubako and Lant, 2013 [65] | Green and blue | WFA |
S | Interstate transfers in the U.S. | Dang et al., 2015 [72] | Green and blue | WFA |
S | Interstate transfers in India | Verma et al., 2009 [120] | Green and blue | WFA |
S | North and south China | Ma et al., 2006 [66] | Green and blue (surface and groundwater) | WFA |
S | Interprovincial transfers in China | Dalin et al., 2014 [71] | Green and blue | WFA |
S | Interprovincial transfers in Indonesia | Bulsink et al., 2010 [133] | Green, blue, grey | WFA |
S | Western U.S. states | Ruddell et al., 2014 [73] | Blue | WFA/MRIO/ERA |
C | Beijing and China | Hubacek et al., 2009 [134] | Blue | SRIO |
C | Beijing | Wang and Wang, 2009 [121] | Blue | SRIO |
C | Beijing | Zhang et al., 2011 [122] | Blue | MRIO |
C | Beijing | Wang et al., 2013 [123] | Blue and grey | SRIO |
B | Haihe River basin, China | White et al., 2015 [135] | Blue † | MRIO |
B | Haihe River basin, China | Zhi et al., 2014 [136] | Blue | SRIO |
B | Haihe River basin, China | Zhao et al., 2010 [137] | Blue | SRIO |
B | Yellow River basin, China | Feng et al., 2012 [128] | Green and blue (rural/urban WF) | MRIO |
S | Liaoning Province, China | Dong et al., 2013 [138] | Blue | SRIO |
S | Shandan County China | Deng et al., 2014 [139] | Blue | SRIO |
S | North and south China | Guan and Hubacek, 2007 [80] | Blue (considers wastewater) † | IRIO |
S | Interprovincial trade in China | Feng et al., 2014 [127] | Blue † | MRIO |
S | Interprovincial trade in China | Jiang et al., 2014 [126] | Blue | MRIO |
S | The southeast and northeast UK | Yu et al., 2010 [119] | Green and blue | MRIO |
S | Domestic UK | Feng et al., 2011 [125] | Green and blue | MRIO |
C | Sydney and Melbourne, Australia | Lenzen and Peters, 2010 [140] | Indirect impacts of blue water use | MRIO |
S | Victoria, Australia | Lenzen, 2009 [82] | Blue | MRIO |
S | Andalusia, Spain | Velázquez, 2006 [80] | Blue | SRIO |
S | California and Illinois | Mubako et al., 2013 [82] | Green and blue (also saline water) | IRIO |
C | Beijing | Huang et al., 2014 [98] | Blue and grey † | LCA |
4. Discussion
4.1. A General Approach for Urban Water Footprint Analysis
4.2. Spatial Scale or Boundary for Urban Water Footprint Analysis
4.3. Required Datasets for Urban Water Footprint Analysis
Source | Type of Data | Spatial Scale | Temporal Scale (Most Recent) |
---|---|---|---|
Bureau of Labor Statistics | Consumer Expenditure Survey (CES)-Complete information on consumers’ expenditures and incomes-Section 20A collects expense estimates for food and beverages per household. | National, regional, state, and MSA | Quarterly and yearly (2013) |
Bureau of Economic Analysis (BEA) | National input–output datasets. Also provides regional input–output modeling system (RIMS) multipliers, GDP analysis, and details on imports and exports at national level. | National | Every 5 years (2007–years with 2 and 7) |
IMPLAN | Economic databases and methodologies to construct input–output tables. | National, state, county, MSA, and zip code | Yearly |
US Census | Population and socioeconomic statistics, including employment, income, and GDP. | National, state, county, MSA, city, and town | Every 10 years (2010) |
US Census Agricultural Imports and Exports | Agricultural exports and imports. Volume by principal commodities and by value. Also provides consumer expenditures for farm foods. | National | Yearly (2010) |
USDA Census of Agriculture | Farm and Ranch Irrigation Survey for blue water calculations. Harvested cropland by size of farm and acres harvested. Inventory and sales of livestock. | State, county, and zip code | Every 5 years (2012) |
Bureau of Transportation Statistics-Commodity Flow Survey (CFS) | Primary source on domestic freight shipments by American establishments in 42 sectors. Provides a modal picture of national freight flows, and represents the only publicly available source of commodity flow data for the highway mode. Used to track commodity to source region. | National, state, and MSA | Every 5 years (bilateral only in 2007, 2012) |
Federal Highway Administration and Bureau of Transportation Statistics- FAF3 | Integrates data from the most recent CFS and a variety of sources to create a more comprehensive picture of freight movement among states and major metropolitan areas. Provides estimates for tonnage, value, and domestic ton-miles by region of origin and destination, commodity type, and mode. | National, state, and MSA | Every 5 years. Last finalized data were 2007, interim data for 2012 and projected to 2040 |
USGS | Water withdrawal data for 8 sectors: public supply, domestic, irrigation, livestock, aquaculture, industrial, thermo-electric-power generation, and mining. | National, state, and county | Every 5 years (2010) |
USGS MRDS | Mineral resources data for production of all minerals, including sand and gravel, and locations of mining operations worldwide. | GPS coordinates of each mining site in the world | (2011) |
FAOSTAT | Food and agricultural commodity production data for every country. Food balance sheets created to determine a country’s food supply. | National | Yearly (2012) |
4.4. Urban Metabolism and Water Footprint Analysis
4.5. Applications of Urban Water Footprint Analysis
5. Summary
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Paterson, W.; Rushforth, R.; Ruddell, B.L.; Konar, M.; Ahams, I.C.; Gironás, J.; Mijic, A.; Mejia, A. Water Footprint of Cities: A Review and Suggestions for Future Research. Sustainability 2015, 7, 8461-8490. https://doi.org/10.3390/su7078461
Paterson W, Rushforth R, Ruddell BL, Konar M, Ahams IC, Gironás J, Mijic A, Mejia A. Water Footprint of Cities: A Review and Suggestions for Future Research. Sustainability. 2015; 7(7):8461-8490. https://doi.org/10.3390/su7078461
Chicago/Turabian StylePaterson, Willa, Richard Rushforth, Benjamin L. Ruddell, Megan Konar, Ikechukwu C. Ahams, Jorge Gironás, Ana Mijic, and Alfonso Mejia. 2015. "Water Footprint of Cities: A Review and Suggestions for Future Research" Sustainability 7, no. 7: 8461-8490. https://doi.org/10.3390/su7078461