IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v127y2014icp28-40.html
   My bibliography  Save this article

Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture

Author

Listed:
  • Brown, Jesslyn F.
  • Pervez, Md Shahriar

Abstract

Over 22 million hectares (ha) of U.S. croplands are irrigated. Irrigation is an intensified agricultural land use that increases crop yields and the practice affects water and energy cycles at, above, and below the land surface. Until recently, there has been a scarcity of geospatially detailed information about irrigation that is comprehensive, consistent, and timely to support studies tying agricultural land use change to aquifer water use and other factors. This study shows evidence for a recent overall net expansion of 522 thousand ha across the U.S. (2.33%) and 519 thousand ha (8.7%) in irrigated cropped area across the High Plains Aquifer (HPA) from 2002 to 2007. In fact, over 97% of the net national expansion in irrigated agriculture overlays the HPA. We employed a modeling approach implemented at two time intervals (2002 and 2007) for mapping irrigated agriculture across the conterminous U.S. (CONUS). We utilized U.S. Department of Agriculture (USDA) county statistics, satellite imagery, and a national land cover map in the model. The model output, called the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the U.S. (MIrAD-US), was then used to reveal relatively detailed spatial patterns of irrigation change across the nation and the HPA. Causes for the irrigation increase in the HPA are complex, but factors include crop commodity price increases, the corn ethanol industry, and government policies related to water use. Impacts of more irrigation may include shifts in local and regional climate, further groundwater depletion, and increasing crop yields and farm income.

Suggested Citation

  • Brown, Jesslyn F. & Pervez, Md Shahriar, 2014. "Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture," Agricultural Systems, Elsevier, vol. 127(C), pages 28-40.
    • Handle: RePEc:eee:agisys:v:127:y:2014:i:c:p:28-40
    DOI: 10.1016/j.agsy.2014.01.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X14000134
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2014.01.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jacinto F. Fabiosa & John C. Beghin & Fengxia Dong & JAmani Elobeid & Simla Tokgoz & Tun-Hsiang Yu, 2010. "Land Allocation Effects of the Global Ethanol Surge: Predictions from the International FAPRI Model," Land Economics, University of Wisconsin Press, vol. 86(4), pages 687-706.
    2. Swinton, Scott M. & Babcock, Bruce A. & James, Laura K. & Bandaru, Varaprasad, 2011. "Higher US crop prices trigger little area expansion so marginal land for biofuel crops is limited," Energy Policy, Elsevier, vol. 39(9), pages 5254-5258, September.
    3. Ruben N. Lubowski & Andrew J. Plantinga & Robert N. Stavins, 2008. "What Drives Land-Use Change in the United States? A National Analysis of Landowner Decisions," Land Economics, University of Wisconsin Press, vol. 84(4), pages 529-550.
    4. Swinton, Scott & Babcock, Bruce A. & James, Laura K. & Bandaru, Varaprasad, 2011. "Higher U.S. Crop Prices Trigger Little Area Expansion So Marginal Land for Biofuels is Limited," Staff General Research Papers Archive 34897, Iowa State University, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Chen & Di, Liping & Lin, Li & Li, Hui & Guo, Liying & Yang, Zhengwei & Yu, Eugene G. & Di, Yahui & Yang, Anna, 2022. "Towards automation of in-season crop type mapping using spatiotemporal crop information and remote sensing data," Agricultural Systems, Elsevier, vol. 201(C).
    2. Kliment, T. & Bordogna, G. & Frigerio, L. & Stroppiana, D. & Crema, A. & Boschetti, M. & Sterlacchini, S. & Brivio, P. A., 2014. "Supporting a Regional Agricultural Sector with Geo & Mainstream ICT – the Case Study of Space4Agri Project," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 6(4), pages 1-12, December.
    3. Hamze, Mohamad & Cheviron, Bruno & Baghdadi, Nicolas & Lo, Madiop & Courault, Dominique & Zribi, Mehrez, 2023. "Detection of irrigation dates and amounts on maize plots from the integration of Sentinel-2 derived Leaf Area Index values in the Optirrig crop model," Agricultural Water Management, Elsevier, vol. 283(C).
    4. Minghao Bai & Shenbei Zhou & Ting Tang, 2022. "A Reconstruction of Irrigated Cropland Extent in China from 2000 to 2019 Using the Synergy of Statistics and Satellite-Based Datasets," Land, MDPI, vol. 11(10), pages 1-27, September.
    5. Haqiqi, Iman & Bowling, Laura C. & Jame, Sadia & Hertel, Thomas W. & Baldos, Uris Lantz C. & Liu, Jing, 2019. "Global Drivers of Land and Water Sustainability Stresses at Mid-Century," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291101, Agricultural and Applied Economics Association.
    6. Hussain, Mir Zaman & Hamilton, Stephen K. & Bhardwaj, Ajay K. & Basso, Bruno & Thelen, Kurt D. & Robertson, G.P., 2019. "Evapotranspiration and water use efficiency of continuous maize and maize and soybean in rotation in the upper Midwest U.S," Agricultural Water Management, Elsevier, vol. 221(C), pages 92-98.
    7. Kayla A. Cotterman & Anthony D. Kendall & Bruno Basso & David W. Hyndman, 2018. "Groundwater depletion and climate change: future prospects of crop production in the Central High Plains Aquifer," Climatic Change, Springer, vol. 146(1), pages 187-200, January.
    8. Zhang, Chao & Dong, Jinwei & Zuo, Lijun & Ge, Quansheng, 2022. "Tracking spatiotemporal dynamics of irrigated croplands in China from 2000 to 2019 through the synergy of remote sensing, statistics, and historical irrigation datasets," Agricultural Water Management, Elsevier, vol. 263(C).
    9. Roger F. Auch & Danika F. Wellington & Janis L. Taylor & Stephen V. Stehman & Heather J. Tollerud & Jesslyn F. Brown & Thomas R. Loveland & Bruce W. Pengra & Josephine A. Horton & Zhe Zhu & Alemayehu , 2022. "Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series," Land, MDPI, vol. 11(2), pages 1-20, February.
    10. Hsing-Hsiang Huang & Michael R. Moore, 2018. "Farming under Weather Risk: Adaptation, Moral Hazard, and Selection on Moral Hazard," NBER Chapters, in: Agricultural Productivity and Producer Behavior, pages 77-124, National Bureau of Economic Research, Inc.
    11. Nicholas J. Pates & Nathan P. Hendricks, 2021. "Fields from Afar: Evidence of Heterogeneity in United States Corn Rotational Response from Remote Sensing Data," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1759-1782, October.
    12. Lee, Juhee & Hendricks, Nathan P., 2022. "Crop Choice Decisions in Response to Soil Salinization on Irrigated Land in California," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322602, Agricultural and Applied Economics Association.
    13. Su, Shiliang & Hu, Yi’na & Luo, Fanghan & Mai, Gengchen & Wang, Yaping, 2014. "Farmland fragmentation due to anthropogenic activity in rapidly developing region," Agricultural Systems, Elsevier, vol. 131(C), pages 87-93.
    14. Dinesh Shrestha & Jesslyn F. Brown & Trenton D. Benedict & Daniel M. Howard, 2021. "Exploring the Regional Dynamics of U.S. Irrigated Agriculture from 2002 to 2017," Land, MDPI, vol. 10(4), pages 1-16, April.
    15. Ferin, Kelsie M. & Kucharik, Christopher J., 2024. "Irrigation expansion shows potential for increased maize yield and reduced nitrogen leaching in the Midwest US," Agricultural Systems, Elsevier, vol. 219(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. P. A. Turner & C. B. Field & D. B. Lobell & D. L. Sanchez & K. J. Mach, 2018. "Unprecedented rates of land-use transformation in modelled climate change mitigation pathways," Nature Sustainability, Nature, vol. 1(5), pages 240-245, May.
    2. Ribeiro, Barbara E. & Quintanilla, Miguel A., 2015. "Transitions in biofuel technologies: An appraisal of the social impacts of cellulosic ethanol using the Delphi method," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 53-68.
    3. Piroli, Giuseppe & Ciaian, Pavel & Kancs, d'Artis, 2012. "Land use change impacts of biofuels: Near-VAR evidence from the US," Ecological Economics, Elsevier, vol. 84(C), pages 98-109.
    4. Chamberlain, Jim F. & Miller, Shelie A., 2012. "Policy incentives for switchgrass production using valuation of non-market ecosystem services," Energy Policy, Elsevier, vol. 48(C), pages 526-536.
    5. Miroslava Rajcaniova & d'Artis Kancs & Pavel Ciaian, 2014. "Bioenergy and global land-use change," Applied Economics, Taylor & Francis Journals, vol. 46(26), pages 3163-3179, September.
    6. Miroslava Rajcaniova & d'Artis Kancs & Pavel Ciaian, 2014. "Bioenergy and global land-use change," Applied Economics, Taylor & Francis Journals, vol. 46(26), pages 3163-3179, September.
    7. Dumortier, Jerome, 2015. "Impact of agronomic uncertainty in biomass production and endogenous commodity prices on cellulosic biofuel feedstock composition," IU SPEA AgEcon Papers 198707, Indiana University, IU School of Public and Environmental Affairs.
    8. Wilson, P. & Glithero, N.J. & Ramsden, S.J., 2014. "Prospects for dedicated energy crop production and attitudes towards agricultural straw use: The case of livestock farmers," Energy Policy, Elsevier, vol. 74(C), pages 101-110.
    9. Burli, Pralhad & Lal, Pankaj & Wolde, Bernabas & Jose, Shibu & Bardhan, Sougata, 2021. "Perceptions about switchgrass and land allocation decisions: Evidence from a farmer survey in Missouri," Land Use Policy, Elsevier, vol. 109(C).
    10. Mellor, P. & Lord, R.A. & João, E. & Thomas, R. & Hursthouse, A., 2021. "Identifying non-agricultural marginal lands as a route to sustainable bioenergy provision - A review and holistic definition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    11. Van Deynze, B., 2018. "The Effects of Experience on Landowner Preferences over Bioenergy Feedstocks," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277001, International Association of Agricultural Economists.
    12. Kauffman, Nathan S. & Hayes, Dermot J., 2013. "The trade-off between bioenergy and emissions with land constraints," Energy Policy, Elsevier, vol. 54(C), pages 300-310.
    13. De Laporte, Aaron V. & Ripplinger, David G., 2019. "The effects of site selection, opportunity costs and transportation costs on bioethanol production," Renewable Energy, Elsevier, vol. 131(C), pages 73-82.
    14. repec:lic:licosd:33613 is not listed on IDEAS
    15. Jennifer Ifft & Deepak Rajagopal & Ryan Weldzuis, 2019. "Ethanol Plant Location and Land Use: A Case Study of CRP and the Ethanol Mandate," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(1), pages 37-55, March.
    16. Sharp, Benjamin E. & Miller, Shelie A., 2014. "Estimating maximum land use change potential from a regional biofuel industry," Energy Policy, Elsevier, vol. 65(C), pages 261-269.
    17. Ifft, Jennifer & Rajagopal, Deepak & Ryan, Weldzius, 2016. "The effect of the ethanol mandate on the Conservation Reserve Program," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236178, Agricultural and Applied Economics Association.
    18. Chen, Xiaoguang & Khanna, Madhu, 2018. "Effect of corn ethanol production on Conservation Reserve Program acres in the US," Applied Energy, Elsevier, vol. 225(C), pages 124-134.
    19. Ren, Jie & Campbell, James B. & Shao, Yang, 2016. "Spatial and temporal dimensions of agricultural land use changes, 2001–2012, East-Central Iowa," Agricultural Systems, Elsevier, vol. 148(C), pages 149-158.
    20. Changchun Feng & Hao Zhang & Liang Xiao & Yongpei Guo, 2022. "Land Use Change and Its Driving Factors in the Rural–Urban Fringe of Beijing: A Production–Living–Ecological Perspective," Land, MDPI, vol. 11(2), pages 1-18, February.
    21. Carrión-Flores, Carmen E. & Flores-Lagunes, Alfonso & Guci, Ledia, 2018. "An estimator for discrete-choice models with spatial lag dependence using large samples, with an application to land-use conversions," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 77-93.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:127:y:2014:i:c:p:28-40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.