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DSSAT-CERES-maize modelling to improve irrigation and nitrogen management practices under Mediterranean conditions

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  • Malik, Wafa
  • Isla, Ramon
  • Dechmi, Farida

Abstract

Maintain high agriculture production levels while reducing environmental impacts is of primordial importance in intensive irrigated areas. Adequate management of water and nitrogen are critical for a sustainable agriculture. The objectives of this work were to (i) calibrate and validate DSSAT model for maize under different nitrogen availability conditions and (ii) assess the effect of best management practices on irrigation water needs and nitrogen losses by leaching using different scenarios in an intensive irrigated area. For model calibration and validation, three field experiments were conducted with a total of 134 plots. Then, the model application was performed in three soil types in the ‘Del Reguero’ watershed (Spain) considering (i) real irrigation applied by farmers and DSSAT automatic irrigation and (ii) a recommended dose of N fertilizer (250 kg N ha−1) compared to a traditional dose of 390 kg N ha−1. Among all plots, the model simulated reasonably well grain yield with a Root Mean Square Error (RMSE) lower than 708 kg ha−1 and high Willmott agreement index (d statistic) (>0.9). Very similar trends were observed for total biomass and total N uptake with a RMSE of 2018 kg ha−1 and 36.6 kg N ha−1. The prediction of residual nitrate in soil was acceptable with a RMSE of 43 kg N ha−1.Modeling results showed that adjusted irrigation would reduce (on average for different soil types) the total amount of seasonal irrigation water by 31% and the nitrate leaching by 97% without a significant reduction in grain yield. Regarding to N fertilizer scenarios, results showed that farmers can reduce the N fertilizer currently applied leading to a significant decrease in the N leached between 33 and 53% depending on soil types.

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  • Malik, Wafa & Isla, Ramon & Dechmi, Farida, 2019. "DSSAT-CERES-maize modelling to improve irrigation and nitrogen management practices under Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 213(C), pages 298-308.
    • Handle: RePEc:eee:agiwat:v:213:y:2019:i:c:p:298-308
    DOI: 10.1016/j.agwat.2018.10.022
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    References listed on IDEAS

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    Cited by:

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    2. Kang, Jian & Hao, Xinmei & Zhou, Huiping & Ding, Risheng, 2021. "An integrated strategy for improving water use efficiency by understanding physiological mechanisms of crops responding to water deficit: Present and prospect," Agricultural Water Management, Elsevier, vol. 255(C).
    3. Liang, Hao & Lv, Haofeng & Batchelor, William D. & Lian, Xiaojuan & Wang, Zhengxiang & Lin, Shan & Hu, Kelin, 2020. "Simulating nitrate and DON leaching to optimize water and N management practices for greenhouse vegetable production systems," Agricultural Water Management, Elsevier, vol. 241(C).
    4. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    5. Nasta, Paolo & Bonanomi, Giuliano & Šimůnek, Jirka & Romano, Nunzio, 2021. "Assessing the nitrate vulnerability of shallow aquifers under Mediterranean climate conditions," Agricultural Water Management, Elsevier, vol. 258(C).
    6. Tsakmakis, I.D. & Gikas, G.D. & Sylaios, G.K., 2021. "Integration of Sentinel-derived NDVI to reduce uncertainties in the operational field monitoring of maize," Agricultural Water Management, Elsevier, vol. 255(C).
    7. Mohamadzade, Fahime & Gheysari, Mahdi & Eshghizadeh, Hamidreza & Tabatabaei, Mahsa Sadat & Hoogenboom, Gerrit, 2022. "The effect of water and nitrogen on drip tape irrigated silage maize grown under arid conditions: Experimental and simulations," Agricultural Water Management, Elsevier, vol. 271(C).
    8. Wang, Yongqiang & Huang, Donghua & Sun, Kexin & Shen, Hongzheng & Xing, Xuguang & Liu, Xiao & Ma, Xiaoyi, 2023. "Multiobjective optimization of regional irrigation and nitrogen schedules by using the CERES-Maize model with crop parameters determined from the remotely sensed leaf area index," Agricultural Water Management, Elsevier, vol. 286(C).
    9. Malik, Wafa & Dechmi, Farida, 2020. "Modelling agricultural nitrogen losses to enhance the environmental sustainability under Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 230(C).
    10. Serra-Wittling, Claire & Molle, Bruno & Cheviron, Bruno, 2019. "Plot level assessment of irrigation water savings due to the shift from sprinkler to localized irrigation systems or to the use of soil hydric status probes. Application in the French context," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.

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