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Modelling agricultural nitrogen losses to enhance the environmental sustainability under Mediterranean conditions

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  • Malik, Wafa
  • Dechmi, Farida

Abstract

In intensive agricultural systems, irrigation and nitrogen (N) fertilizer are the most important factors that influence crop production and N losses. This work aimed to evaluate the N best management practices using the calibrated and validated Decision Support System for Agro-technology Transfer (DSSAT) model for maize (short and long season), wheat, barley, sunflower and alfalfa in the Violada Irrigation District (VID, Northeast Spain) to reduce the impact of N losses on irrigation return flows quality. In total, 59 farmers’ field plots were investigated from 2014 to 2017 crop seasons distributed in the different soil types in the VID in order to assess the current and optimum N fertilization and the combined irrigation and N fertilization management practices. Considering the whole cultivated crop area in each soil type of the VID and comparing with the current N fertilization, results showed that the optimum N management could reduce the NO3–N leaching below root zone by 51 % and residual NO3–N in soil by 58 %. These reductions could be improved further by 35 % and 3 %, respectively, under the combined N fertilization and irrigation optimum management. The more vulnerable soils for NO3–N leaching (shallow and/or very permeable soils) were also identified. As for the impact of individual crops, the model identified that both long and short season maize were the most polluting crops (84 % of total N leached) due to the heavy fertilization applied by the local farmers that exceed crop requirements by more than 50 %. Moreover, the recommended irrigation and N fertilization could reduce N2O–N emissions by 60 %, the triple than under the recommended N fertilization alone. This study supports the potential of the DSSAT model to incentivize farmers to adjust their N fertilizer and irrigation practices to crop requirement and soil properties to ensure production while improving environmental sustainability.

Suggested Citation

  • Malik, Wafa & Dechmi, Farida, 2020. "Modelling agricultural nitrogen losses to enhance the environmental sustainability under Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:agiwat:v:230:y:2020:i:c:s0378377419304688
    DOI: 10.1016/j.agwat.2019.105966
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    References listed on IDEAS

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    1. Asadi, Mohammad Esmaeil & Clemente, Roberto S. & Gupta, Ashim Das & Loof, Rainer & Hansen, Gunner K., 2002. "Impacts of fertigation via sprinkler irrigation on nitrate leaching and corn yield in an acid-sulphate soil in Thailand," Agricultural Water Management, Elsevier, vol. 52(3), pages 197-213, January.
    2. Malik, Wafa & Dechmi, Farida, 2019. "DSSAT modelling for best irrigation management practices assessment under Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 216(C), pages 27-43.
    3. Jiménez-Aguirre, M.T. & Isidoro, D., 2018. "Hydrosaline Balance in and Nitrogen Loads from an irrigation district before and after modernization," Agricultural Water Management, Elsevier, vol. 208(C), pages 163-175.
    4. He, Jianqiang & Dukes, Michael D. & Hochmuth, George J. & Jones, James W. & Graham, Wendy D., 2012. "Identifying irrigation and nitrogen best management practices for sweet corn production on sandy soils using CERES-Maize model," Agricultural Water Management, Elsevier, vol. 109(C), pages 61-70.
    5. Attia, Ahmed & Rajan, Nithya & Xue, Qingwu & Nair, Shyam & Ibrahim, Amir & Hays, Dirk, 2016. "Application of DSSAT-CERES-Wheat model to simulate winter wheat response to irrigation management in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 165(C), pages 50-60.
    6. Jeong, Hanseok & Jang, Taeil & Seong, Chounghyun & Park, Seungwoo, 2014. "Assessing nitrogen fertilizer rates and split applications using the DSSAT model for rice irrigated with urban wastewater," Agricultural Water Management, Elsevier, vol. 141(C), pages 1-9.
    7. Shang, Songhao & Mao, Xiaomin, 2006. "Application of a simulation based optimization model for winter wheat irrigation scheduling in North China," Agricultural Water Management, Elsevier, vol. 85(3), pages 314-322, October.
    8. Ismail, Saleh M. & Ozawa, Kiyoshi & Khondaker, Nur A., 2008. "Influence of single and multiple water application timings on yield and water use efficiency in tomato (var. First power)," Agricultural Water Management, Elsevier, vol. 95(2), pages 116-122, February.
    9. 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.
    10. 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.
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