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Evaluation of water-limited cropping systems in a semi-arid climate using DSSAT-CSM

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  • Araya, A.
  • Kisekka, Isaya
  • Gowda, Prasanna H.
  • Prasad, P.V. Vara

Abstract

Water is the major factor limiting crop production in western Kansas due to declining groundwater levels in the Ogallala aquifer resulting from withdrawals for irrigation exceeding recharge rates coupled with erratic semi-arid rainfall. Study objectives were to assess yield and water productivity of water limited cropping systems in western Kansas using DSSAT-CSM (Decision Support System for Agrotechnology Transfer Cropping Systems Model). The cropping systems evaluated included continuous (corn, wheat, and grain sorghum) and rotation (corn-wheat, corn-wheat-grain sorghum, and corn-wheat-grain sorghum-corn). Results showed that the model adequately reproduced measured days to flowering and maturity as well as yield and aboveground biomass of all three crops. Crop rotation improved water productivity of corn. Under deficit irrigation, corn in rotation produced higher yields, crop water productivity, and irrigation water use efficiency compared to continuous corn, implying that crop rotation is a better option under limited well capacities. Under full irrigation, yield and water productivity of continuous wheat were lower than wheat in rotation. In contrast, continuous wheat yields under deficit irrigation were better than under crop rotation. Deficit irrigation substantially improved irrigation water use efficiency of grain sorghum under both continuous and crop rotations. Long–term average grain sorghum yields under rotation were higher than those of continuous grain sorghum. Indicating grain sorghum should be grown in rotation under deficit irrigation. This research did not simulate the impacts of pests, weeds and diseases, hail and freeze damage on crop yield. However, the study identifies cropping systems that are more likely to produce highest water productivity under semi-arid climate similar to that in western Kansas.

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  • Araya, A. & Kisekka, Isaya & Gowda, Prasanna H. & Prasad, P.V. Vara, 2017. "Evaluation of water-limited cropping systems in a semi-arid climate using DSSAT-CSM," Agricultural Systems, Elsevier, vol. 150(C), pages 86-98.
    • Handle: RePEc:eee:agisys:v:150:y:2017:i:c:p:86-98
    DOI: 10.1016/j.agsy.2016.10.007
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    7. Araya, A. & Kisekka, I. & Gowda, P.H. & Prasad, P.V.V., 2018. "Grain sorghum production functions under different irrigation capacities," Agricultural Water Management, Elsevier, vol. 203(C), pages 261-271.
    8. Jha, P.K. & Araya, A. & Stewart, Z.P. & Faye, A. & Traore, H. & Middendorf, B.J. & Prasad, P.V.V., 2021. "Projecting potential impact of COVID-19 on major cereal crops in Senegal and Burkina Faso using crop simulation models," Agricultural Systems, Elsevier, vol. 190(C).
    9. A. Mukherjee & A. K. S. Huda, 2018. "Assessment of climate variability and trend on wheat productivity in West Bengal, India: crop growth simulation approach," Climatic Change, Springer, vol. 147(1), pages 235-252, March.
    10. Araya, A. & Gowda, P.H. & Golden, B. & Foster, A.J. & Aguilar, J. & Currie, R. & Ciampitti, I.A. & Prasad, P.V.V., 2019. "Economic value and water productivity of major irrigated crops in the Ogallala aquifer region," Agricultural Water Management, Elsevier, vol. 214(C), pages 55-63.
    11. Araya, A. & Prasad, P.V.V. & Gowda, P.H. & Sharda, V. & Rice, C.W. & Ciampitti, I.A., 2021. "Evaluating optimal irrigation strategies for maize in Western Kansas," Agricultural Water Management, Elsevier, vol. 246(C).
    12. Amiri, E. & Irmak, S. & Araji, H. Ahmadzadeh, 2022. "Assessment of CERES-Maize model in simulating maize growth, yield and soil water content under rainfed, limited and full irrigation," Agricultural Water Management, Elsevier, vol. 259(C).
    13. Araya, A. & Gowda, P.H. & Rad, M. Rouhi & Ariyaratne, C.B. & Ciampitti, I.A. & Rice, C.W. & Prasad, P.V.V., 2021. "Evaluating optimal irrigation for potential yield and economic performance of major crops in southwestern Kansas," Agricultural Water Management, Elsevier, vol. 244(C).
    14. Khadim, Fahad Khan & Dokou, Zoi & Bagtzoglou, Amvrossios C. & Yang, Meijian & Lijalem, Girmachew Addisu & Anagnostou, Emmanouil, 2021. "A numerical framework to advance agricultural water management under hydrological stress conditions in a data scarce environment," Agricultural Water Management, Elsevier, vol. 254(C).
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