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DSSAT modelling for best irrigation management practices assessment under Mediterranean conditions

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  • Malik, Wafa
  • Dechmi, Farida

Abstract

Water is considered the most critical resource for sustainable development in Spain. Crop models can enhance water efficiency, which provides an economic advantage while also reducing environmental burdens. The aim of this study was to calibrate and evaluate the Decision Support System for Agro-technology Transfer (DSSAT) model for the major crops grown in the fields of the La Violada Irrigation District (VID), Spain; additionally, this research sought to evaluate the current practices and to determine the best irrigation management practices under different soil types in the VID for each crop. Crop and soil type data from 54 plots of farmers’ fields were used for model calibration and evaluation during the 2015 and 2016 irrigation seasons. Two irrigation scenarios were applied in eight soil types in the VID based on the current irrigation applied by farmers and the optimum irrigation adjusted to crop requirement. The DSSAT model demonstrated good performance among maize, wheat, barley and sunflower crops. The evaluation of the current irrigation system showed that farmers were not managing their irrigation systems properly. The adjusted irrigation management application showed a potential reduction in the seasonal irrigation depth for maize-SS (short-season maize) (27%), maize-LS (long season maize) (18%) and sunflower (16%). In a broader context, optimum irrigation practices can reduce the amount of leached N and deep percolation losses by 31% (4.48 T) and 34% (1.2 hm3), respectively, considering the cultivated crop area in each soil type in the entire VID.

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  • 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.
    • Handle: RePEc:eee:agiwat:v:216:y:2019:i:c:p:27-43
    DOI: 10.1016/j.agwat.2019.01.017
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    1. 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).
    2. Dechmi, Farida & Skhiri, Ahmed & Isidoro, Daniel, 2021. "Modeling environmental impact in a semi-arid intensive irrigated watershed," Agricultural Water Management, Elsevier, vol. 256(C).
    3. Zhang, Jing & Zhang, Huihui & Sima, Matthew W. & Trout, Thomas J. & Malone, Rob W. & Wang, Li, 2021. "Simulated deficit irrigation and climate change effects on sunflower production in Eastern Colorado with CSM-CROPGRO-Sunflower in RZWQM2," Agricultural Water Management, Elsevier, vol. 246(C).
    4. Kheir, Ahmed M.S. & Alrajhi, Abdullah A. & Ghoneim, Adel M. & Ali, Esmat F. & Magrashi, Ali & Zoghdan, Medhat G. & Abdelkhalik, Sedhom A.M. & Fahmy, Ahmed E. & Elnashar, Abdelrazek, 2021. "Modeling deficit irrigation-based evapotranspiration optimizes wheat yield and water productivity in arid regions," Agricultural Water Management, Elsevier, vol. 256(C).
    5. Malik, Wafa & Dechmi, Farida, 2020. "Modelling agricultural nitrogen losses to enhance the environmental sustainability under Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 230(C).

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