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Modeling irrigation management for water conservation by DSSAT-maize model in arid northwestern China

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  • Jiang, Yiwen
  • Zhang, Lanhui
  • Zhang, Baoqing
  • He, Chansheng
  • Jin, Xin
  • Bai, Xiao

Abstract

Water shortage is a chronic problem in arid Northwest China, where agriculture cannot exist without irrigation. Efficient irrigation and water uses are important to sustainable development and management of water resources in the region. This paper applied DSSAT-maize v4.5 to the Yingke Irrigation District in the middle reach oasis of the Heihe River Watershed in Northwest China to explore the optimal irrigation strategies under different climatic conditions, and to improve the beneficial water consumption and reduce non-beneficial water consumption while maintaining yields at the same time. The model was first calibrated based on the crop yield, phenological phases and soil water content data, and good agreements were achieved between the simulated and observed data in both the calibration and validation periods. In the calibration period, the simulated maize phenological phases differed by two days of the observed phases, and nRMSE (normalized root mean square errors) for grain yield was 6%. In the validation period, the values of nRMSE of yield were 4.95% in 2006 and 2.96% in 2008, respectively, while the RMSE for soil water content ranged from 0.118 to 0.046. Subsequently the calibrated model was used to simulate the effects of planting dates and different irrigation treatments on maize yield and the potentially reduced water amount was calculated. Results show that in the Yingke Irrigation District, the best planting dates range from early April to mid-April, and the best irrigation periods are the jointing and tassel phases. The optimal irrigation amounts vary under different climatic conditions, ranging from about 1000m3/ha, to 4200m3/ha, and to 4800m3/ha in wet, normal and dry years respectively. Nearly half of the irrigation amount could be reduced under the simulated irrigation schedule for the district. Once validated by field tests, the simulated irrigation scenarios would provide partial basis for effective water resources management in the study area.

Suggested Citation

  • Jiang, Yiwen & Zhang, Lanhui & Zhang, Baoqing & He, Chansheng & Jin, Xin & Bai, Xiao, 2016. "Modeling irrigation management for water conservation by DSSAT-maize model in arid northwestern China," Agricultural Water Management, Elsevier, vol. 177(C), pages 37-45.
    • Handle: RePEc:eee:agiwat:v:177:y:2016:i:c:p:37-45
    DOI: 10.1016/j.agwat.2016.06.014
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    1. Molden, D., 1997. "Accounting for water use and productivity," IWMI Books, Reports H021374, International Water Management Institute.
    2. Panda, R. K. & Behera, S. K. & Kashyap, P. S., 2003. "Effective management of irrigation water for wheat under stressed conditions," Agricultural Water Management, Elsevier, vol. 63(1), pages 37-56, November.
    3. Seckler, David & Amarasinghe, Upali A. & Molden, David J. & de Silva, Radhika & Barker, Randolph, 1998. "World water demand and supply, 1990 to 2025: scenarios and issues," IWMI Research Reports 61108, International Water Management Institute.
    4. Stockle, Claudio O. & Williams, Jimmy R. & Rosenberg, Norman J. & Jones, C. Allan, 1992. "A method for estimating the direct and climatic effects of rising atmospheric carbon dioxide on growth and yield of crops: Part I--Modification of the EPIC model for climate change analysis," Agricultural Systems, Elsevier, vol. 38(3), pages 225-238.
    5. Liu, S. & Yang, J.Y. & Zhang, X.Y. & Drury, C.F. & Reynolds, W.D. & Hoogenboom, G., 2013. "Modelling crop yield, soil water content and soil temperature for a soybean–maize rotation under conventional and conservation tillage systems in Northeast China," Agricultural Water Management, Elsevier, vol. 123(C), pages 32-44.
    6. McCown, R.L. & Hammer, G.L. & Hargreaves, J.N.G. & Holzworth, D. & Huth, N.I., 1995. "APSIM: an agricultural production system simulation model for operational research," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 225-231.
    7. Deng, Xi-Ping & Shan, Lun & Zhang, Heping & Turner, Neil C., 2006. "Improving agricultural water use efficiency in arid and semiarid areas of China," Agricultural Water Management, Elsevier, vol. 80(1-3), pages 23-40, February.
    8. Rinaldi, Michele, 2001. "Application of EPIC model for irrigation scheduling of sunflower in Southern Italy," Agricultural Water Management, Elsevier, vol. 49(3), pages 185-196, August.
    9. G. Kapetanaki & C. Rosenzweig, 1997. "Impact of climate change on maize yield in central and northern Greece: A simulation study with CERES-Maize," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 1(3), pages 251-271, September.
    10. Molden, David J., 1997. "Accounting for water use and productivity," IWMI Books, International Water Management Institute, number 113623.
    11. Yang, J. & Greenwood, D. J. & Rowell, D. L. & Wadsworth, G. A. & Burns, I. G., 2000. "Statistical methods for evaluating a crop nitrogen simulation model, N_ABLE," Agricultural Systems, Elsevier, vol. 64(1), pages 37-53, April.
    12. Ko, Jonghan & Piccinni, Giovanni & Steglich, Evelyn, 2009. "Using EPIC model to manage irrigated cotton and maize," Agricultural Water Management, Elsevier, vol. 96(9), pages 1323-1331, September.
    13. Yang, Yonghui & Watanabe, Masataka & Zhang, Xiying & Zhang, Jiqun & Wang, Qinxue & Hayashi, Seiji, 2006. "Optimizing irrigation management for wheat to reduce groundwater depletion in the piedmont region of the Taihang Mountains in the North China Plain," Agricultural Water Management, Elsevier, vol. 82(1-2), pages 25-44, April.
    14. Nelson, Gerald C. & Rosegrant, Mark W. & Koo, Jawoo & Robertson, Richard & Sulser, Timothy & Zhu, Tingju & Ringler, Claudia & Msangi, Siwa & Palazzo, Amanda & Batka, Miroslav & Magalhaes, Marilia & Va, 2009. "Climate change: Impact on agriculture and costs of adaptation," Food policy reports 21, International Food Policy Research Institute (IFPRI).
    15. Chen, Chao & Wang, Enli & Yu, Qiang, 2010. "Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain," Agricultural Water Management, Elsevier, vol. 97(8), pages 1175-1184, August.
    16. Panda, R. K. & Behera, S. K. & Kashyap, P. S., 2004. "Effective management of irrigation water for maize under stressed conditions," Agricultural Water Management, Elsevier, vol. 66(3), pages 181-203, May.
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    7. Zhong, Honglin & Sun, Laixiang & Fischer, Günther & Tian, Zhan & Liang, Zhuoran, 2019. "Optimizing regional cropping systems with a dynamic adaptation strategy for water sustainable agriculture in the Hebei Plain," Agricultural Systems, Elsevier, vol. 173(C), pages 94-106.
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    12. Pereira, L.S. & Paredes, P. & Jovanovic, N., 2020. "Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach," Agricultural Water Management, Elsevier, vol. 241(C).
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