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Simulation of cotton growth and soil water content under film-mulched drip irrigation using modified CSM-CROPGRO-cotton model

Author

Listed:
  • Li, Meng
  • Du, Yingji
  • Zhang, Fucang
  • Bai, Yungang
  • Fan, Junliang
  • Zhang, Jianghui
  • Chen, Shaoming

Abstract

Cotton is one of the major cash crops in Xinjiang, an arid region in northwestern China. Most cotton fields in this region are drip irrigated with plastic film mulch. However, few studies have tested the performance of the DSSAT (Decision Support System for Agrotechnology Transfer) model on cotton under film-mulched drip irrigation. The objective of this study is to evaluate the performance of the modified CSM-CROPGRO-Cotton model and determine the genetic coefficients of cotton using data from different irrigation treatments conducted at the irrigation experiment station in Bayingol Mongolian Autonomous Prefecture, Korla, China. Based on the selected genetic coefficients, the model was calibrated using field experiment datasets in 2016 and validated using datasets in 2015. The simulation results of soil water content, leaf area index, phenological period and cotton yield were compared with their corresponding measurements. Absolute relative error (ARE) of seeding emergence date, flowing date, maturity date and cotton yield simulated by the original model were 5.8%, 7.3%, 5.0% and 70.6%, respectively, while those of the modified model were 1.7%, 1.1%, 1.1% and 0.1%, respectively. Simulated leaf area index agreed well with the field observations with the coefficient of determination (R2) > 0.739, the index of agreement (d) > 0.910 and the root mean square error (RMSE) < 0.965. Simulated soil water content in the 20–40 cm soil layer were generally consistent with the measured values with R2 = 0.724, d = 0.639 and RMSE = 0.087 cm3/cm3, while the simulated soil water content in the 40–60 cm was slightly worse than the observations with R2 = 0.708, d = 0.519 and RMSE = 0.109 cm3/cm3. Overall, the modified CSM-CROPGRO-Cotton model can be used as a practical tool to simulate the cotton growth under film-mulched drip irrigation in this region. Potential opportunities for the model improvement in cotton growth include the influence of various scenarios such as soil types, climates and irrigation strategies.

Suggested Citation

  • Li, Meng & Du, Yingji & Zhang, Fucang & Bai, Yungang & Fan, Junliang & Zhang, Jianghui & Chen, Shaoming, 2019. "Simulation of cotton growth and soil water content under film-mulched drip irrigation using modified CSM-CROPGRO-cotton model," Agricultural Water Management, Elsevier, vol. 218(C), pages 124-138.
    • Handle: RePEc:eee:agiwat:v:218:y:2019:i:c:p:124-138
    DOI: 10.1016/j.agwat.2019.03.041
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    15. Himanshu, Sushil Kumar & Fan, Yubing & Ale, Srinivasulu & Bordovsky, James, 2021. "Simulated efficient growth-stage-based deficit irrigation strategies for maximizing cotton yield, crop water productivity and net returns," Agricultural Water Management, Elsevier, vol. 250(C).
    16. Desheng Wang & Chengkun Wang & Lichao Xu & Tiecheng Bai & Guozheng Yang, 2022. "Simulating Growth and Evaluating the Regional Adaptability of Cotton Fields with Non-Film Mulching in Xinjiang," Agriculture, MDPI, vol. 12(7), pages 1-20, June.
    17. Guo, Jinjin & Fan, Junliang & Xiang, Youzhen & Zhang, Fucang & Yan, Shicheng & Zhang, Xueyan & Zheng, Jing & Li, Yuepeng & Tang, Zijun & Li, Zhijun, 2022. "Coupling effects of irrigation amount and nitrogen fertilizer type on grain yield, water productivity and nitrogen use efficiency of drip-irrigated maize," Agricultural Water Management, Elsevier, vol. 261(C).
    18. Yu, Qihua & Kang, Shaozhong & Zhang, Lu & Hu, Shunjun & Li, Yunfeng & Parsons, David, 2023. "Incorporating new functions into the WAVES model, to better simulate cotton production under film mulching and severe salinity," Agricultural Water Management, Elsevier, vol. 288(C).
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