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Assessing explanatory factors for variation in on-farm irrigation in US maize-soybean systems

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  • Gibson, Katherine E.B.
  • Yang, Haishun S.
  • Franz, Trenton
  • Eisenhauer, Dean
  • Gates, John B.
  • Nasta, Paolo
  • Farmaha, Bhupinder S.
  • Grassini, Patricio

Abstract

Irrigation exhibits large variation across producer fields, even within same region and year. A knowledge gap exists relative to factors that explain this variation, in part due to lack of availability of high-quality irrigation data from multiple field-years. This study assessed sources of variation in irrigation using a large database collected during 9 years (2005–2013) from ca. 1400 maize and soybean producer fields in Nebraska, central USA (total of 12,750 field-year observations). The study area is representative of ca. 4.5 million ha of irrigated land sown with maize and soybean. Influence of biophysical (weather, soil, and crop type) and behavioral (producer skills, risk aversion) factors on irrigation was investigated. Field irrigation distributions showed a substantial number of fields received irrigation amounts that were well above average irrigation for same region-year. Variation in irrigation across fields, within the same region, was as large as year-to-year variation. Seasonal water deficit (defined as total reference evapotranspiration minus precipitation), soil available water holding capacity, and crop type explained about half of observed variation in field irrigation, indicating that producers adjusted irrigation depending upon site-year variation in these parameters. However, half of the variation in irrigation remained unexplained, indicating that producer behavior and skills play also an important role. There was evidence of a “neighbor” effect as fields that received large irrigation were surrounded by other fields with similarly large irrigation. Likewise, fields with above- or below-average irrigation in one year remained consistently above and below regional average irrigation, respectively, in other years despite similarity in weather and soil among fields. These findings indicate that irrigation decisions are influenced by both biophysical and behavioral factors, making predictions of field and regional irrigation extremely difficult. This study highlights the value of collecting on-farm irrigation data to understand producer decision-making and find opportunities to improve current water management in irrigated crop systems.

Suggested Citation

  • Gibson, Katherine E.B. & Yang, Haishun S. & Franz, Trenton & Eisenhauer, Dean & Gates, John B. & Nasta, Paolo & Farmaha, Bhupinder S. & Grassini, Patricio, 2018. "Assessing explanatory factors for variation in on-farm irrigation in US maize-soybean systems," Agricultural Water Management, Elsevier, vol. 197(C), pages 34-40.
    • Handle: RePEc:eee:agiwat:v:197:y:2018:i:c:p:34-40
    DOI: 10.1016/j.agwat.2017.11.008
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    References listed on IDEAS

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    1. Droogers, P. & Immerzeel, W.W. & Lorite, I.J., 2010. "Estimating actual irrigation application by remotely sensed evapotranspiration observations," Agricultural Water Management, Elsevier, vol. 97(9), pages 1351-1359, September.
    2. Mullen, Jeffrey D. & Yu, Yingzhuo & Hoogenboom, Gerrit, 2009. "Estimating the demand for irrigation water in a humid climate: A case study from the southeastern United States," Agricultural Water Management, Elsevier, vol. 96(10), pages 1421-1428, October.
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    1. Gonçalves, Ivo Zution & Mekonnen, Mesfin M. & Neale, Christopher M.U. & Campos, Isidro & Neale, Michael R., 2020. "Temporal and spatial variations of irrigation water use for commercial corn fields in Central Nebraska," Agricultural Water Management, Elsevier, vol. 228(C).
    2. Salgado, Ramiro & Mateos, Luciano, 2021. "Evaluation of different methods of estimating ET for the performance assessment of irrigation schemes," Agricultural Water Management, Elsevier, vol. 243(C).
    3. Ruchie Pathak & Nicholas R. Magliocca, 2022. "Assessing the Representativeness of Irrigation Adoption Studies: A Meta-Study of Global Research," Agriculture, MDPI, vol. 12(12), pages 1-31, December.
    4. Gao, Zitian & Guo, Danlu & Ryu, Dongryeol & Western, Andrew W., 2024. "Exploring key factors driving farm-level seasonal irrigation water usage with Bayesian hierarchical modelling," Agricultural Water Management, Elsevier, vol. 294(C).
    5. Wilian Rodrigues Ribeiro & Morgana Scaramussa Gonçalves & Daniel Soares Ferreira & Dalila Costa Gonçalves & Samira Luns Hatum Almeida & Ramon Amaro Sales & Felipe Cunha Siman & Luan Peroni Venancio & , 2022. "Water demand of central pivot-irrigated areas in Bahia, Brazil: management of water resources applied to sustainable production," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(10), pages 12340-12366, October.
    6. dos Santos Almeida, Alexsandro Claudio & Mamédio, Mário Roberto & Goelzer, Ademar & Rodrigues, Lucas Araujo & Mateos, Luciano, 2023. "Shared centre pivot. An experience of smallholder irrigation in Midwest Brazil," Agricultural Water Management, Elsevier, vol. 275(C).

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