Data

The FEWSION Database™ is a spatially- and temporally- detailed input-output database describing the FEW system of communities in the United States along with other commodity flows, their resource footprints, and resource dependencies. The FEWSION Database™ Version 1.0 Dataset Documentation and Guide is intended for use in conjunction with the FEWSION Database™ and other associated data products. The FEWSION Database™ Version 1.0 Dataset Documentation and Guide describes the coverage, methods, processing techniques, statistical methods, schemas, source material, file structure, and file formats for the FEWSION™ Database v. 1.0.

The goal of the FEWSION Project is to produce FEW data for researchers, decision-makers, and the public. Extracts from the FEWSION Database™ are available to the public through an online visualization system called FEW-View™ where users can visualize U.S. state- and county-level FEW system connections.

Download the FEWSION Database™ Version 1.0 Dataset Documentation (updated March 4, 2020) and Guide HERE.

The FEWSION Database™ Glossary is adapted from Rushforth & Ruddell (2018). Included are terms from the FEWSION Database™ v. 1.0, v. 1.1, and v. 1.2. See the FEW-VIEW™ GLOSSARY PAGE HERE.

Agricultural Sector: Economic sector comprised of farm-based activities to grow crops for food or industrial purposes. Irrigation is the primary water using activity in the agricultural sector (Maupin et al., 2014).

Attraction Factor: A fraction used to disaggregate commodity flows on the consumption side. In the FEWSION Database™ v.1.0, population is used as an attraction factor. Each county within a FAF zone is assigned a fraction equivalent to its percent of the total population.

Circularity: The Circularity metric is a specific way of looking at the Dependence data layer for a specific physical unit like tons, dollars, barrels of oil, or GWh, among others. Rather than looking at all of the areas a state or county/county equivalent may depend on, the Circularity metric shows how much a state or county/county equivalent depends on itself. For example, a State purchases 100,000 gallons of gasoline from itself and consumes 200,000 gallons of gasoline overall. Using the Circularity metric, the State’s circularity fraction is 0.5.

County: A county or county equivalent (parish, borough, Washington D.C., or an independent city) is a sub-state geographic scale that is roughly equivalent to the mesoscale.

Dependence: The Dependence metric is a different way of looking at the flow of goods into an area. Instead of measuring flow between an origin and destination in a physical unit like tons, dollars, barrels of oil, of GWh, the Dependence metric is a relative measure of how large a supplier is in a supply chain as a percent from 0 -100%. For example, a State purchases 100,000 gallons of gasoline from another state and consumes 200,000 gallons of gasoline overall. Using the Dependence metric, the State depends on the other state for 50% of its gasoline supply.

Destination: The geographic location where a commodity flow terminates.

Freight Analysis Zone (FAF Zone): A group of counties that represents a metropolitan statistical area, census statistical area, or the remainder of the state (Southworth et al., 2010; Hwang et al., 2016)

Industrial Sector: Economic sector that produces industrial goods. Water use in the industrial sector includes, “fabricating, processing, washing, diluting, cooling, or transporting a product; incorporating water into a product; or for sanitation needs within the manufacturing facility,” (Maupin et al., 2014).

Inflow Rank: The numeric rank of how much of a specific commodity flows into a geographic area (county, state, metropolitan area) compared to all other geographic areas of that type for a specific unit.

Leverage: The Leverage metric is a different way of looking at the flow of goods out of an area. Instead of measuring flow between an origin and destination in a physical unit like tons, dollars, barrels of oil, of GWh, the Leverage metric is a relative measure of how large a supplier is in a supply chain as a percent from 0 -100%. For example, a State sells 100,000 gallons of gasoline to another state and sells 500,000 gallons of gasoline overall. Using the Leverage metric, the state consuming gasoline has leverage over 20% the producing state’s its gasoline supply.

Livestock Sector: Economic sector comprised of the raising of animals for animal products in addition to aquaculture activities. Water use in the livestock sector only includes direct water use at livestock, and related facilities (Maupin et al., 2014).

Mining Sector: Economic sector comprised of mineral producing activities, including metallic and non-metallic ore, in addition to sand and gravel, crude petroleum and natural gas. Water using activities in the mining sector include, “Mining water use is water used for the extraction of minerals that may be in the form of solids, such as coal, iron, sand, and gravel; liquids, such as crude petroleum; and gases, such as natural gas,” (Maupin et al., 2014).

Origin: The geographic location where a commodity flow originates.

Outflow Rank: The numeric rank of how much of a specific commodity flows out of a geographic area (county, state, metropolitan area) compared to all other geographic areas of that type for a specific unit.

Production Factor: A fraction used to disaggregate commodity flows on the production side. In the FEWSION Database™ v.1.0, multiple production factors are used specific to the economic sector. Each county within a FAF zone is assigned a fraction equivalent to its percent of the total population.

Power Sector: In the FEWSION Database™ v.1.0, the power sector is comprised of electric generating stations, which includes thermoelectric and non-thermoelectric facilities (renewable energy sources). Water is used at thermoelectric generation stations in addition to hydroelectric facilities.

Resilience: Resilience is a measure of the potential for disruptions in a commodity supply chain. The potential for disruption is estimated by determining if a supply chain is overly reliant on a handful of sources, rather than relying on a diverse set of sources. Resilience is measured from 0 to 1. A score of 0 indicates that a supply chain is heavily reliant on one supplier, and if that supplier is disrupted, it may cause disruptions in supply. A score of 1 indicates that a supply chain relies on a diverse set of suppliers equally.

Total Inflows: The total amount of a specific commodity flowing into a geographic area (county, state, metropolitan area) for a specific unit.

Total Outflows: The total amount of a specific commodity flowing out of a geographic area (county, state, metropolitan area) for a specific unit.

Virtual Water: Also known as indirect water or embodied water, has been studied as a strategic resource for two decades as it allows geographic areas (country, state, province, city) to access more water than is physically available (Allan, 1998; Allan, 2003; Suweis et al., 2011; Dalin et al., 2012; Dang et al., 2015; Zhao et al., 2015; Marston et al., 2015).

Virtual Water Inflows into a Geographic Area (VWIn): The volume of water indirectly consumed to produce goods or services produced outside a geographic boundary of interest for consumption within that geographic boundary of interest.

Virtual Water Outflows from a Geographic Area (VWOut): The volume of water used to produce goods or services that are consumed outside of the geographic boundary of interest.

Virtual Water Balance of a Geographic Area (VWNet): Virtual water Inflows minus virtual water outflows for a geographic boundary of interest.

Water Footprint: The volume of surface water and groundwater consumed during the production of a good or service and is also called the virtual water content of a good or service (Mekonnen and Hoekstra, 2011a).

Water Footprint of Consumption: Water consumption for local use in addition to virtual water import (Mekonnen and Hoekstra, 2011b)

Water Footprint of a Geographic Area (F): The volume of water representing direct water consumption plus virtual water inflows minus virtual water outflows for a geographic boundary of interest. A per-capita water footprint (F`) is F divided by the population within the geographic boundary of interest.

Water Footprint of Production: the total volume of water consumed with a geographic boundary, including water consumption for local use less virtual water export (Mekonnen and Hoekstra, 2011b).

Water Consumption (C): The total volume of water consumed from a water source, when consumption is withdrawals minus return flows. A water source is either surface water or groundwater. The FEWSION Database™ v.1.0 utilizes four consumptive use scenarios based on a withdrawal-based scenario, and minimum, median, and maximum consumptive use scenario. Consumptive use scenarios are based on reports published by the United States Geological Survey (Shaffer and Runkle, 2007).

Vulnerability: In FEW-View, vulnerability is a measure of exposure to drought in a supply chain. Vulnerability is measured from 0 to 1. A score of 1 indicates that a supply chain is heavily reliant suppliers with stressed water supplies. A score of 0 indicates that a supply chain is not heavily reliant suppliers with stressed water supplies. Vulnerability can be visualized as a total for each area (IWSI) and compared to other areas or visualized to show the most vulnerable sources for a single area (IWSIc).

Water Withdrawal (W): The total volume of water withdrawn from a water source. A water source is either surface water or groundwater.


Glossary References

Allan, J. A. (1998). Virtual Water: A Strategic Resource Global Solutions to Regional Deficits, Ground Water, 36, 545-546, 10.1111/j.1745-6584.1998.tb02825.x.

Allan, J. A (2003). Virtual water-the water, food, and trade nexus. Useful concept or misleading metaphor?, Water international, 28, 106-113.

Dang, Q., Lin, X., and Konar, M.: Agricultural virtual water flows within the United States, Water Resources Research, 51, 973-986, 10.1002/2014WR015919, 2015.

Dalin, C., Konar, M., Hanasaki, N., Rinaldo, A., and Rodriguez-Iturbe, I (2012). Evolution of the global virtual water trade network, Proceedings of the National Academy of Sciences, 109, 5989-5994.

Hwang, H.-L., Hargrove, S., Chin, S.-M., Wilson, D., Lim, H., Chen, J., Taylor, R., Peterson, B., and Davidson, D (2016). Building the FAF4 Regional Database: Data Sources and Estimation Methodologies, in, edited by: Laboratory, O. R. N., Oak Ridge, TN.

Marston, L., Konar, M., Cai, X., and Troy, T. J (2015). Virtual groundwater transfers from overexploited aquifers in the United States, Proceedings of the National Academy of Sciences, 112, 8561-8566, 10.1073/pnas.1500457112.

Maupin, M. A., Kenny, J. F., Hutson, S. S., Lovelace, J. K., Barber, N. L., and Linsey, K. S (2014). Estimated use of water in the United States in 2010, U.S. Geological Survey2330-5703.

Mekonnen, M. M., and Hoekstra, A. Y (2011a). National water footprint accounts: the green, blue and grey water footprint of production and consumption, UNESCO-IHE.

Mekonnen, M. M., and Hoekstra, A. Y (2011b). The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15, 1577.

Rushforth, R. R., & Ruddell, B. L. (2018). A spatially detailed and economically complete blue water footprint of the United States. Hydrology and Earth System Science. https://doi. org/10.5194/hess-2017-650.

Shaffer, K., and Runkle, D. L (2007). Consumptive Water, Use Coefficients for the Great Lakes Basin and Climatically Similar Areas, U.S. Geological Survey Reston, VA.

Southworth, F., Davidson, D., Hwang, H., Peterson, B. E., and Chin, S (2010). The freight analysis framework, version 3: Overview of the FAF3 National Freight Flow Tables, Prepared for Federal highway administration Office of freight management and operations Federal highway administration U.S. Department of Transportation, Washington, DC.

Suweis, S., Konar, M., Dalin, C., Hanasaki, N., Rinaldo, A., and Rodriguez‐Iturbe, I (2011). Structure and controls of the global virtual water trade network, Geophysical Research Letters, 38.

Zhao, X., Liu, J., Liu, Q., Tillotson, M. R., Guan, D., and Hubacek, K (2015). Physical and virtual water transfers for regional water stress alleviation in China, Proceedings of the National Academy of Sciences, 112, 1031-1035, 10.1073/pnas.1404130112.

FEW-VIEW™ LICENSE TEXT

FEW-View(TM) and limited extracts from the FEWSION Database™ visualized by FEW-View™ are licensed to the user under the Creative Commons License “Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)”, Accessible at https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may not use the material for commercial purposes. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. FEW-View(TM) and the FEWSION Database™ are the property of the Arizona Board of Regents.

PUBLIC ACCESS FEWSION DATABASE™ EXTRACTS LICENSE TEXT

Publicly accessible extracts from the FEWSION Database™ are licensed to the user under the Creative Commons License “Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)”, Accessible at https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may not use the material for commercial purposes. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. The FEWSION Database™ is the property of Northern Arizona University and the Arizona Board of Regents.

PRIVATE ACCESS FEWSION DATABASE LICENSE TEXT

User has been provided with access to the FEWSION Database™. The FEWSION Database™ is the property of Northern Arizona University and the Arizona Board of Regents. The FEWSION Database™ may not be duplicated, reproduced, distributed to third parties, used to create derivative works, displayed publicly, or used for any purpose without express written consent of Northern Arizona University. Your access agreement serves as this express written consent and specifies the allowable uses.