scholarly journals A Spatially Detailed and Economically Complete Blue Water Footprint of the United States

2017 ◽  
Author(s):  
Richard R. Rushforth ◽  
Benjamin L. Ruddell
Keyword(s):  
United States ◽  
Water Use ◽  
Water Footprint ◽  
The United States ◽  
Irrigated Agriculture ◽  
Energy Information Administration ◽  
United States Geological Survey ◽  
United States Department ◽  
Blue Water ◽  
The U.S

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 federal data resources from the United States Geological Survey (USGS), the United States Department of Agriculture (USDA), the U.S. Energy Information Administration (EIA), the U.S. Department of Transportation (USDOT), the U.S. Department of Energy (USDOE), and the U.S. 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 U.S. water footprint (F) and in the observed pattern of virtual water flows. The median water footprint (FCUMed) of the U.S. is 181 966 Mm3 (FWithdrawal: 400 844 Mm3; FCUMax: 222 144 Mm3; FCUMin: 61 117 Mm3) and the median per capita water footprint (F'CUMed) of the U.S. is 589 m3 capita−1 (F'Withdrawal: 1298 m3 capita−1; F'CUMax: 720 m3 capita−1; F'CUMin: 198 m3 capita−1). The U.S. hydro-economic network is centered on cities and is dominated by the local and regional scales. Approximately (58 %) of U.S. water consumption is for the direct and indirect use by cities. Further, the water footprint of agriculture and livestock is 93 % of the total U.S. water footprint, and is dominated by irrigated agriculture in the Western U.S. 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.

scholarly journals A spatially detailed blue water footprint of the United States economy

2018 ◽  
Vol 22 (5) ◽  
pp. 3007-3032 ◽  
Author(s):  
Richard R. Rushforth ◽  
Benjamin L. Ruddell
Keyword(s):  
United States ◽  
Water Use ◽  
Water Footprint ◽  
Virtual Water ◽  
The United States ◽  
Energy Information Administration ◽  
Blue Water ◽  
Consumptive Use ◽  
The Us ◽  
Per Capita

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.

scholarly journals Regional Multivariate Indices of Water Use Potential for the Continental United States

2019 ◽  
Vol 11 (8) ◽  
pp. 2292
Author(s):  
White ◽  
Mack ◽  
Harlan ◽  
Krayenhoff ◽  
Georgescu ◽  
...  
Keyword(s):  
United States ◽  
Water Use ◽  
Human Life ◽  
Regional Scale ◽  
The United States ◽  
Data Availability ◽  
Water Withdrawal ◽  
United States Geological Survey ◽  
Scarce Water ◽  
Small Set

The necessity of freshwater for sustaining human life has prompted the development of numerous estimation techniques and metrics for understanding where, when, and why water is used. While estimates are valuable, techniques for estimating water use vary, and may be difficult to replicate and/or unavailable on an annual basis or at the regional scale. To address these drawbacks, this paper proposes a series of regional indices for the continental United States that could serve as proxies for water use that are based on key variables associated with water use. Regional indices at the county level are computed, compared against each other, and compared to water withdrawal estimates from the United States Geological Survey (USGS). These comparisons highlight differences amongst the derived indices and the water withdrawal estimates. They also demonstrate promise for future development and implementation of related indices, given their similarities with water withdrawal estimates. Using only a small set of variables, these indices achieve some degree of similarity (~20%) to estimates of water withdrawals. The comparative data availability and ease of estimating these indices, as well as the ability to decompose the additive indices into their constituent use categories and constituent variables, renders them practically useful to water managers and other decision makers for identification of locally specific drivers of water use and implementation of more geographically-appropriate policies to manage scarce water resources.

Aphomia gularis (Zeller) (Lepidoptera, Pyralidae) at Baie d'Urfé, Quebec

1955 ◽  
Vol 87 (6) ◽  
pp. 239-240 ◽  
Author(s):  
P. H. H. Gray
Keyword(s):  
United States ◽  
The United States ◽  
United States Department ◽  
National Museum ◽  
San Jose ◽  
Department Of Agriculture ◽  
States Department ◽  
Lepidoptera Pyralidae ◽  
The U.S

This moth was first reported on this continent as a pest in a consignment of peanuts, received in California from China (de Ong, 1919). Mr. Hahn W. Capps, of the United States Department of Agriculture, informs me, in litt., that 6 adults from that infestation, together with 2 from “near prunes” in 1930, and 8 from a prune warehouse in 1931, at San José, are in the U.S. National Museum.

scholarly journals A content review of precision agriculture courses across the United States

2017 ◽  
Author(s):  
◽  
Danielle Skouby
Keyword(s):  
United States ◽  
Precision Agriculture ◽  
The United States ◽  
United States Department ◽  
Differential Gps ◽  
Department Of Agriculture ◽  
University Of Missouri ◽  
Four Year Institutions ◽  
Content Review ◽  
The U.S

Knowledge of what Precision Agriculture (PA) content is currently taught across the U.S. will help build a better understanding for what PA instructors should incorporate into their classes in the future. For this assessment, the University of Missouri (MU) partnered with several universities throughout the nation on a United States Department of Agriculture (USDA) challenge grant. A survey was conducted with PA instructors from 44 institutions from across the U.S. participating. Each institution was assessed to determine amount of time they spent teaching on 59 different PA topics in their PA-related courses. Results were obtained from 56 PA courses. Scope of PA, Global Positioning System (GPS), Differential GPS, Yield Monitoring, and Yield Map were all topics that were frequently discussed in PA courses, whether they were entryor advanced-level or two-year or four-year institutions. Review of the content showed a need for a more standardized curriculum.

scholarly journals Opportunities to improve the accuracy of the United States Department of Agriculture beef yield grade equation through precision agriculture1

2020 ◽  
Vol 4 (2) ◽  
pp. 1216-1223
Author(s):  
Jerad R Jaborek ◽  
Alejandro E Relling ◽  
Francis L Fluharty ◽  
Steven J Moeller ◽  
Henry N Zerby
Keyword(s):  
United States ◽  
Precision Agriculture ◽  
The United States ◽  
Carcass Composition ◽  
United States Department ◽  
Department Of Agriculture ◽  
Additional Information ◽  
Animal Identification ◽  
The U.S ◽  
Beef Carcass

Abstract The U.S. Department of Agriculture (USDA) yield grade (YG) equation is used to predict the retail yield of beef carcasses, which facilitates a more accurate payment for cattle when they are sold on a grid pricing system that considers carcass composition instead of body weight alone. The current USDA YG equation was developed over 50 yr ago. Arguably, the population of cattle used to develop the YG equation is different than the current diverse U.S. beef cattle supply today. The objectives of this manuscript are to promote the adoption and use of precision agriculture technologies (i.e., camera grading and electronic animal identification) throughout the U.S. beef supply chain as a means to enhance the ability of the USDA YG equation to more accurately predict the retail yield across the population of cattle that contributes to the current U.S. beef supply. Camera grading has improved the accuracy of determining beef carcass retail yield; however, the use of electronic animal identification would allow for additional information to be passed back and forth between the packer, cattle feeder, and producer. Information, such as sex, genetics, medical treatment history, diets consumed, and growth promotant administration, as well as other information could be used to create additional variables for a new augmented USDA YG equation. Herein, fabrication yields demonstrated a 5.6 USDA YG and 12.8% boneless closely trimmed retail cut difference between actual cutout measurements and calculated values from the USDA YG equation for Jersey-influenced cattle. Evidence of such disparities between calculated and actual values warrants a reevaluation of the USDA YG system and consideration for implementing advancements in precision agriculture to improve the prediction of beef carcass retail yield to more accurately account for the large amount of variation in beef carcass retail yield from the cattle in the United States.

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