


































Energy and Earth Science 
Vol. 3, No. 2, 2020 

www.scholink.org/ojs/index.php/ees 

ISSN 2578-1359 (Print)   ISSN 2578-1367 (Online) 

1 
 

Original Paper 

After the Sun: Energy Use in Blue v. Green Water for 

Agriculture 

Jenny R. Kehl
1
 

1
 Global Water Security Scholar for the University of Wisconsin, Office of the Provost, Global Studies, 

and School of Freshwater Sciences, Milwaukee, Wisconsin, USA 

 

Received: May 29, 2020          Accepted: June 8, 2020         Online Published: July 6, 2020 

doi:10.22158/ees.v3n2p1             URL: http://dx.doi.org/10.22158/ees.v3n2p1 

 

Abstract  

The purpose of this article is to highlight the difference in energy consumption between using blue 

water versus green water for agriculture in areas where water-intensive crops are grown in 

water-scarce regions. It focuses on water and energy consumption for greening the desert in United 

States, the world’s largest grain producer. The analysis is limited to the three largest crops by volume 

and value; corn, cotton, and wheat, which generate billions of dollars for the economy and use billions 

of gallons of water each day. The primary methodology is to use Geographic Information Systems (GIS) 

to visually represent the comparative amounts of blue water and green water used to grow 

water-intensive crops in water-scarce regions, by statistically mapping levels of water stress overlaid 

with the amounts of blue water versus green water used. It exposes where energy-intensive water 

practices are occurring due to a high dependence on blue water for irrigation in agriculture. The 

article concludes by discussing strategies to improve energy efficiency and reduce the vulnerabilities 

associated with overdependence on blue water such as high energy costs, low energy security, and 

susceptibility to aquifer reduction and ground water depletion. 

Keywords 

energy security, water use efficiency, agriculture, sustainable development 

 

1. Introduction 

Energy is an integral part of providing water for food security. After the sun, which is the greatest 

source of energy for growing plants for food, substantial amounts of additional energy are needed to 

irrigate, produce, harvest, process and transport agricultural crops to support a burgeoning population. 

Most of the additional energy used in agriculture is for irrigation, which requires large amounts of 

energy to pump vast amounts of water from long distances or great depths.  



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Agriculture is the largest water-user and second largest energy-user in the United States. 

Approximately 300 billion gallons of freshwater are withdrawn daily, requiring energy for pumping 

and transporting, from surface and ground water sources for agricultural irrigation in the United States 

(US Geological Survey 2019). With such a high amount of all energy flowing to one sector, we cannot 

advance sustainable development without addressing the inefficiencies and interdependencies between 

water and energy in the agricultural sector.   

One of the hidden realities in this energy-water-food nexus is that there is a significant difference in the 

amount of energy used between blue water and green water in agriculture. Blue water is the volume of 

freshwater used from surface and groundwater sources, green water is the volume of freshwater in the 

form of precipitation or stored in the soil. The difference is important because agricultural areas that 

use blue water are highly dependent on irrigation, which requires a tremendous amount of energy to 

pump, transport, deliver and disperse water.  

The purpose of this research is to examine the amount of energy use in blue water versus green water 

for agriculture. It examines two problems: 1) Water-intensive crops are grown in water-scarce areas, 2) 

these crops require a lot of blue water, which is energy-intensive. The use of blue water for irrigating 

crops is energy-intensive because it involves pumping, treating, diverting, delivering and moving large 

volumes from great depths and across vast distances. The conclusion provides empirical evidence of 

where the is an imbalance in blue water versus green water consumption in the largest parts of our 

agricultural sector, emphasizing that blue water is highly energy-intensive, and discusses the 

vulnerabilities associated with overdependence on blue water such as energy insecurity and 

susceptibility to aquifer depletion. 

 

2. Method 

The methodological objectives of this research are to: 1) provide empirical evidence of the comparative 

amount of blue water and green water used to grow our three mega crops -corn, cotton, wheat- in 

water-scarce regions, and, 2) to identify and provide empirical evidence of any imbalances or 

inefficiencies in energy consumption between blue and green water in the nexus of energy-water-food 

security. 

This research uses the three largest crops in the U.S. economy, meaning the crops with the highest 

production volume and highest monetary value. The largest crops by volume and value are corn, cotton, 

and wheat. These three major crops are all water-intensive and energy-intensive. The data sources for 

agricultural production are the Agriculture and Food Statistics: Charting Essentials, a collection of key 

statistics on food security, food prices, natural resources, and other information; and the Agricultural 

Baseline Database, a database, report and projection of major field crops including corn, wheat, cotton, 

and others, from the United States Department of Agriculture (USDA 2020). To indicate the level of 

water-stress in each region, we use a ratio of water use to water availability. The primary data source 

for the statistical mapping of water stress is the U.S. Geological Survey National Water Information 



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System and it is verified and constitutes no data inconsistency (Tinker, 2019) with Aquastat and the 

U.S. Drought Monitor (USGS NWIS 2020, Aquastat 2020, USDM 2020).   

Spatial, production, and economic data are used to locate areas where the three major crops are grown 

in large quantities in water stressed regions. Geographic Information Systems (GIS) maps are used to 

represent the data. The graduated levels of water stress are statistically mapped and then overlaid with 

the quantity of the commodities produced in that region. The overlay illustrates the amount of blue 

water and green water used.  

 

3. Result 

This research distinguishes between the use of blue water and green water in the analysis in order to 

statistically map the water footprint and indicate the difference in energy consumption. Prominent 

water scholars Hoekstra and Hung note “The distinction between the blue and green water footprint is 

important because the hydrological, environmental, and social impacts, as well as the economic 

opportunity costs, of surface and groundwater use for production differ distinctively from the impacts 

and costs of rainwater use” (Hoekstra et al., 2011, p. 45). Blue water is the volume of freshwater 

consumed from surface and groundwater sources. Green water is the volume of freshwater consumed 

as precipitation or stored in the soil. The difference is important to understand because areas that are 

dependent on blue water are more dependent on irrigation and thus highly dependent on energy for 

pumping and transporting water. Areas dependent on blue water are also more susceptible to aquifer 

depletion, whereas areas that are dependent on green water are less dependent on energy consumption 

but more vulnerable to factors such as precipitation. 

The baseline water stress of the United States is mapped in Figure 1, which uses Geographic 

Information Systems (GIS) to statistically represent water stress using water data from USGS, USDM, 

and USDA. The indicator is a ratio; it measures water stress as the difference between water 

availability and water consumption. The baseline water stress map is the current level of water stress 

across the U.S. 

 



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Figure 1. Baseline Water Stress Map of the United States  

Source: USGS https://waterdata.usgs.gov/nwis, GIS Kehl and Olshfski. 

 

The baseline water stress map exposes one of the most consequential realities of the water-energy-food 

nexus: many of our largest food producing regions are growing water-intensive crops in water-scarce 

areas, such as the Great Plains, Midwest, Southwest, Texas, and California. This reality is highly 

energy-intensive. These areas rely on blue water and depend on irrigation, which is energy-intensive 

for pumping from increasing depths and transporting from increasing distances. We can expect this 

reality to worsen with increasing consumptive demands and increasing environmental variability. 

Mighty rivers such as the Colorado and expansive aquifers such as the Ogallala are being depleted and 

our dependence on blue water from these sources places heavy, expensive, and unsustainable demands 

on energy. 

The results of this analysis demonstrate that several regions have a double dilemma of growing 

water-intensive crops in water-scarce regions and adding the complication of a blue-green water 

imbalance, which greatly increases the amount of energy required to grow crops.  



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Figure 2. Blue and Green Water for Corn 

Source: USGS https://waterdata.usgs.gov/nwis, GIS Kehl and Olshfski. 

 

The primary result is illustrated in the case of double water inefficiency, meaning that a water-intensive 

crops is grown in a water-scarce region and it is grown using a blue water-green water imbalance. 

Colorado, Wyoming, Utah, Arizona, New Mexico, and California have a double inefficiency in water 

use in their corn production: They grow a lot of corn in a water-stressed region and they use a lot of 

blue water to do it. See Figure 2. There is extreme water stress and a high volume of water-intensive 

corn grown in Nebraska and Colorado. There is high water stress and large quantities of corn grown in 

Illinois, Minnesota, Wisconsin, and Kansas. In areas with relatively high levels of precipitation and 

green water, namely Iowa, Mississippi, Indiana, Ohio, and Kentucky, water efficiency and energy 

efficiency in corn production are most balanced. These areas do not require a huge amount of 

additional energy (or inefficient energy consumption) as they do not have a large blue-green water 

imbalance. In contrast, the areas that have the double inefficiency, water scarcity and blue-green water 

imbalance, require a tremendous amount of additional energy to “green the desert” through pumping 

depleted aquifers and diverting over-extracted rivers across great distances.  

 



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Figure 3. Blue and Green Water for Cotton 

Source: USGS https://waterdata.usgs.gov/nwis, GIS Kehl and Olshfski. 

 

There is also an extreme blue-green water imbalance with extreme blue water inefficiency in growing 

cotton in California, Texas, New Mexico, Arkansas and Arizona. See Figure 3. Cotton is one of the 

most water-intensive crops in modern production. It is also highly energy intensive if it is grown in 

water scarce regions. There is extreme water stress and a high volume of cotton grown in California, 

Arizona and Texas, and high water stress and a high volume of cotton in Arkansas and Georgia. 

 

 

Figure 4. Blue and Green Water for Wheat 

Source: USGS https://waterdata.usgs.gov/nwis, GIS Kehl and Olshfski. 

 



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California and Arizona show extreme water inefficiency in the use of blue water to grow wheat in the 

desert. There is also blue-green water inefficiency in Idaho, Nevada, and New Mexico. See Figure 4. 

There is extreme water stress and a high volume of wheat produced in Colorado, Montana, Kansas, 

Nebraska, and Oklahoma. There is high to moderate water stress and high wheat production in Illinois, 

Minnesota, and Indiana.  

The greatest problem in water inefficiency and energy inefficiency in wheat production in the U.S. is in 

the states that are dependent on the Ogallala Aquifer for water security; Colorado, Montana, Kansas, 

Nebraska, and Oklahoma. As the Ogallala Aquifer gets depleted due to over-extraction, the feasibility 

of agricultural production will decrease due to the dependence on pumping scarce water from the 

rapidly depleting source, as we know, and the more hidden reality of the high cost of large amounts of 

energy required to pump it from greatening depths. The loss of the capacity to produce a high volume, 

high value mega cash crop will jeopardize the economic viability of the agricultural sector in the 

multi-state Ogallala region, not only due to the water inefficiency but due to the interdependent and 

expensive energy inefficiency that is not cost effective for relatively cheap cash crops. 

 

4. Discussion 

It is often overlooked that agricultural practices in water-scarce regions are highly energy-intensive. 

The use of blue water irrigation requires immense amounts of energy to pump water from extreme 

depths and move water across great distances. Greening the desert is a deleterious distortion that is not 

environmentally or economically sustainable.  

This research provides empirical evidence of energy inefficiency in areas where there is an imbalance 

in blue water versus green water use for large agricultural production, as the use of blue water is highly 

energy intensive. The research has provided empirical evidence that wheat, corn, and cotton, all high 

volume, high value, and water-intensive crops grown in water stressed areas in the U.S., demonstrate 

the most sever water imbalances and energy inefficiencies in the American West, Southwest and Great 

Plains, The results indicate that the water imbalance and consequent energy inefficiency is particularly 

extreme for corn in Colorado, Wyoming, Utah, Arizona, New Mexico, and California; cotton in 

California, Texas, New Mexico, Arkansas and Arizona; and wheat in Californian and Arizona, which 

arguably should not be growing these crops and should expedite a transition to crops better suited to the 

urgency of environmental sustainability and economic durability in the region. Water and energy 

intensive crops should be grown in areas that have a comparative advantage in water availability and 

energy efficiency, and a sustainable balance of blue-green water consumption, which seems intuitive 

but is actually the opposite of the empirical reality that our most water-intensive crops are grown in our 

most water scarce regions. These water scarce regions are highly dependent on energy-intensive blue 

water, which makes them vulnerable to worsening water stress, energy costs, energy insecurity, and the 

depletion of the aquifers and ground water resources upon which they depend. 

 



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As these areas suffer more frequent and severe droughts, which exacerbate the problems of dependence 

on energy-intensive blue water and rapidly depleting aquifers, this study portends a large transition of 

intensive agriculture to the Great Lakes region, the largest source of surface freshwater on the planet. 

Great Lakes regional governments, development corporations, producers and consumers are 

commercially advertising and marketing Great Lakes water to large-scale growers as an abundant and 

free source of freshwater to attract business. The Great Lakes might consider putting policies in place 

to manage this anticipated growth with water-efficiency in the interest of sustainable development.  

This study introduces the empirical reality and environmental risk, and, arguably, the emerging 

depravity of continuing to grow water-intensive and energy-intensive crops in highly water-stressed 

regions. The research has been conducted in the interest of introducing difference in the amount of blue 

water versus green water in large-scale agriculture in the U.S. and to expose the energy inefficiency of 

the high dependency on large quantities of blue water to produce water-intensive crops in water 

stressed regions. Although this work is introductory, it can be expanded and used to prompt additional 

research on the difference in energy consumption of blue water and green water in agriculture. It can 

also be used as part of a larger initiative to restructure agriculture in the U.S. from the perspective of 

joint water efficiency and energy efficiency, or at least be used as justification to pursue energy 

efficiency and sustainable sources of energy for water-intensive agriculture. 

 

References 

Antonelli, M., Rosen, R., & Sartori, M. (2012). Systemic Input-Output Computation of Green and Blue 

Virtual Water “Flows”. Water Resources Management, 26, 4133-4146. 

https://doi.org/10.1007/s11269-012-0135-9 

Boelens, R., & Vos, J. (2012). The danger of naturalizing water policy concepts: Water productivity 

and efficiency discourses from field irrigation to virtual water trade. Agricultural Water 

Management, 108, 16-26. https://doi.org/10.1016/j.agwat.2011.06.013 

Copeland, C., & Carter, N. (2017). Energy-Water Nexus: The Water Sector’s Energy Use, 

Congressional Research Service, CRS Report 7-5700 R43200. Retrieved March 14, 2020, from 

https://www.crs.gov R43200 

Dabrowski, J. M., Masekoameng, E., & Ashton, P. J. (2009). Analysis of virtual water flows associated 

with the trade of maize in the SADC region: Importance of scale. Hydrology and Earth System 

Sciences, 13, 1967-1977. https://doi.org/10.5194/hess-13-1967-2009 

Daugherty, K. (2019). U.S. Agricultural Trade Data Update. Economic Research Service, 2(7).  

Fader, M., Gerten, D., Thammer, M., Heinke, J., Lotze-Campen, H., Lucht, W., & Cramer, W. (2011). 

Internal and external green-blue agricultural water footprints of nations, and related water and land 

savings through trade. Hydrology and Earth System Sciences, 15, 1641-1660. 

https://doi.org/10.5194/hess-15-1641-2011 

 

https://doi.org/10.1016/j.agwat.2011.06.013


www.scholink.org/ojs/index.php/ees                    Energy and Earth Science                     Vol. 3, No. 2, 2020 

9 
Published by SCHOLINK INC. 

Hoekstra, A. Y. (2013). Sustainable, efficient, and equitable water use: The three pillars under wise 

freshwater allocation. WIREs Water. https://doi.org/10.1002/wat2.1000 

Hoekstra, A. Y., & Hung, P. Q. (2004). Globalisation of water resources: International virtual water 

flows in relation to crop trade. Global Environmental Change, 15, 45-56. 

https://doi.org/10.1016/j.gloenvcha.2004.06.004 

Hoekstra, A. Y., & Hung, P. Q. (2005). UNESCO-IHE, Globalisation of water resources: International 

virtual water flows in relation to crop trade. Global Environmental Change, 15, 45-56. 

https://doi.org/10.1016/j.gloenvcha.2004.06.004 

Hoekstra, A. Y., & Mekonnen, M. M. (2012). The water footprint of humanity. PNAS, 109(9), 

3232-3237. https://doi.org/10.1073/pnas.1109936109 

Hoekstra, A. Y., Chapagain, A. K., Aldaya, M. M., & Mekonnen, M. M. (2011). The Water Footprint 

Assessment Manual: Setting the Global Standard. London: Earthscan.  

Islam, M. S., Oki, T., Kanae, S., Hanasaki, N., Agata, Y., & Yoshimura, K. (2007). A grid-based 

assessment of global water scarcity including virtual water trading. Water Resources Management, 

21, 19-33. https://doi.org/10.1007/s11269-006-9038-y 

Kehl, J. R., & Olshfski, E. (2015). GIS Mapping of Water Stress in Kehl and McGuire, Greening the 

Desert. Common Ground and Center for Water Policy, University of Wisconsin-Milwaukee. 

Retrieved from https://AH2srMO3MB4 

Lopez-Gunn, E., & Llamas, M. R. (2008). Re-thinking water scarcity: Can science and technology 

solve the global water crisis? Natural Resources Forum, 32, 228-238. 

https://doi.org/10.1111/j.1477-8947.2008.00200.x 

Mekonnen, M. M., & AY Hoekstra, A. Y. (2011). National Water Footprint Accounts: The Green, Blue 

and Grey Water Footprint of Production and Consumption. Value of Water Research Report 

Series, 50.  

Mubako, S. T., & Lant, C. L. (2013). Agricultural Virtual Water Trade and Water Footprint of U.S. 

States. Annals of the Association of American Geographers, 103(2), 385-396. 

https://doi.org/10.1080/00045608.2013.756267 

Rost, S., Gerten, D., Bondeau, A., Lucht, W., Rohwer, J., & Schaphoff, S. (2008). Agricultural green 

and blue water consumption and its influence on the global water system. Water Resources 

Research, 44, W09405. https://doi.org/10.1029/2007WR006331 

Tinker, R. (2019). Drought Summary, Classification, and Impact. Climate Prediction Center, 

NCEP/NWS/NOAA, College Park, MD, USA. 

U. S. Geological Survey (USGS). (2020). Total Water Use in the United States, US Department of the 

Interior. Retrieved March 2, 2020, from https://water.usgs.gov/edu/wateruse-total.html  

U.S. Drought Monitor (USDM). (2019). University of Nebraska-Lincoln. Retrieved February 12, 2019, 

from https://droughtmonitor.unl.edu 

 

https://doi.org/10.1016/j.gloenvcha.2004.06.004
https://doi.org/10.1073/pnas.1109936109
https://ah2srmo3mb4/
https://doi.org/10.1111/j.1477-8947.2008.00200.x
https://doi.org/10.1080/00045608.2013.756267
https://doi.org/10.1029/2007WR006331
https://droughtmonitor.unl.edu/


www.scholink.org/ojs/index.php/ees                    Energy and Earth Science                     Vol. 3, No. 2, 2020 

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Published by SCHOLINK INC. 

U.S. Geological Survey (USGS). (2020). National Water Information System, US Department of the 

Interior. Retrieved February 12, 2020, from https://waterdata.usgs.gov/nwis 

United States Department of Agriculture (USDA). (2019). Agriculture and Food Statistics: Charting 

Essentials. Retrieved February 12, 2019, from https://www.ers.usda.gov/data-products/ 

United States Department of Agriculture (USDA). (2019). Agricultural Baseline Database. Retrieved 

February 12, 2019, from https://www.ers.usda.gov/data-products/ 

 

 

https://www.ers.usda.gov/data-products/
https://www.ers.usda.gov/data-products/

