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Optimizing preplant irrigation for maize under limited water in the High Plains

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  • Kisekka, I.
  • Schlegel, A.
  • Ma, L.
  • Gowda, P.H.
  • Prasad, P.V.V.

Abstract

Due to inadequate irrigation capacity, some farmers in the United States High Plains apply preplant irrigation to buffer the crop between irrigation events during the cropping season. The purpose of the study was to determine preplant irrigation amount and irrigation capacity combinations that optimize yield, water productivity, and precipitation use efficiency (PUE) and minimize soil water evaporation losses prior to planting. The CERES-Maize model embedded in the RZWQM2 model in combination with long-term climatic data from 1986 to 2014 for southwest Kansas were used for this research.

Suggested Citation

  • Kisekka, I. & Schlegel, A. & Ma, L. & Gowda, P.H. & Prasad, P.V.V., 2017. "Optimizing preplant irrigation for maize under limited water in the High Plains," Agricultural Water Management, Elsevier, vol. 187(C), pages 154-163.
    • Handle: RePEc:eee:agiwat:v:187:y:2017:i:c:p:154-163
    DOI: 10.1016/j.agwat.2017.03.023
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    1. Ma, L. & Hoogenboom, G. & Ahuja, L.R. & Ascough II, J.C. & Saseendran, S.A., 2006. "Evaluation of the RZWQM-CERES-Maize hybrid model for maize production," Agricultural Systems, Elsevier, vol. 87(3), pages 274-295, March.
    2. Muñoz-Carpena, R. & Ritter, A. & Bosch, D.D. & Schaffer, B. & Potter, T.L., 2008. "Summer cover crop impacts on soil percolation and nitrogen leaching from a winter corn field," Agricultural Water Management, Elsevier, vol. 95(6), pages 633-644, June.
    3. DeJonge, K.C. & Ascough, J.C. & Andales, A.A. & Hansen, N.C. & Garcia, L.A. & Arabi, M., 2012. "Improving evapotranspiration simulations in the CERES-Maize model under limited irrigation," Agricultural Water Management, Elsevier, vol. 115(C), pages 92-103.
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    Cited by:

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    2. Zhou, Shiwei & Hu, Xiaotao & Ran, Hui & Wang, Wenè & Hansen, Neil & Cui, Ningbo, 2020. "Optimization of irrigation and nitrogen fertilizer management for spring maize in northwestern China using RZWQM2," Agricultural Water Management, Elsevier, vol. 240(C).
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    4. Mao, Wei & Zhu, Yan & Wu, Jingwei & Ye, Ming & Yang, Jinzhong, 2022. "Evaluation of effects of limited irrigation on regional-scale water movement and salt accumulation in arid agricultural areas," Agricultural Water Management, Elsevier, vol. 262(C).
    5. Haomiao Cheng & Shu Ji & Hengjun Ge & Mohmed A. M. Abdalhi & Tengyi Zhu & Xiaoping Chen & Wei Ding & Shaoyuan Feng, 2022. "Optimizing Deficit Irrigation Management to Improve Water Productivity of Greenhouse Tomato under Plastic Film Mulching Using the RZ-SHAW Model," Agriculture, MDPI, vol. 12(8), pages 1-13, August.
    6. Kevser Cetin & Wolfram Mauser, 2023. "The Role of Recent Climate Change in Explaining the Statistical Yield Increase of Maize in Northern Bavaria—A Model Study," Agriculture, MDPI, vol. 13(7), pages 1-19, July.
    7. Foster, T. & Brozović, N., 2018. "Simulating Crop-Water Production Functions Using Crop Growth Models to Support Water Policy Assessments," Ecological Economics, Elsevier, vol. 152(C), pages 9-21.
    8. Liu, Xiao & Li, Mo & Guo, Ping & Zhang, Zhongxue, 2019. "Optimization of water and fertilizer coupling system based on rice grain quality," Agricultural Water Management, Elsevier, vol. 221(C), pages 34-46.

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