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Modeling spatial distribution patterns to delineate irrigation and nutrient management zones for high-density olive orchards

Author

Listed:
  • Samira Vahedi

    (Urmia University)

  • Sina Besharat

    (Urmia University)

  • Naser Davatgar

    (Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO))

  • Mehdi Taheri

    (Soil and Water Research Department, Zanjan Agriculture and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO))

Abstract

Delineation of multivariate management zones is an effective approach to implement sustainable agriculture. Super-high density (SHD) is an effective growth strategy that is widely used in all olive-producing countries, particularly in Iran. The present field-scale study was carried out in the 120 hectare SHD planting system of ‘Arbequina’ olive orchards to provide a full picture of the management zones model automated in the GIS model builder. Geostatistical techniques were used to characterize the spatial variability patterns and distribution maps of three different groups of soil physical and chemical parameters and leaf nutrient contents. Principal component analysis (PCA) and weighted overlay analysis revealed a homogeneous management class for the above three groups. Finally, irrigation and nutrient management zones were determined by a fuzzy K-means (FKM) algorithm. Results showed that soil and leaf properties had a moderate to strong degree of spatial correlation; the spherical model, with a lower mean RSS and a higher R2, offered a good fit; also, Co-Kriging (CoK) produced better estimates than other methods. The variables showing the highest variances in the PCA were used as inputs for the FKM algorithm. The optimum number of irrigation and nutrient management zones was 4 and 5, respectively. The study area, in terms of percentage, was divided into MZ3 > MZ2 > MZ4 > MZ1 for irrigation management and MZ2 > MZ3 > MZ1 > MZ4 > MZ5 for the nutrient management zones. GIS model builder acted successfully under a large number of input layers. These findings, thus, suggest developing this workflow of the GIS model builder by the desired modifications in similar studies on the regional scale for other orchards or crops.

Suggested Citation

  • Samira Vahedi & Sina Besharat & Naser Davatgar & Mehdi Taheri, 2024. "Modeling spatial distribution patterns to delineate irrigation and nutrient management zones for high-density olive orchards," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(3), pages 6051-6083, March.
  • Handle: RePEc:spr:endesu:v:26:y:2024:i:3:d:10.1007_s10668-023-02950-6
    DOI: 10.1007/s10668-023-02950-6
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    References listed on IDEAS

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    1. Fernández, J.E. & Alcon, F. & Diaz-Espejo, A. & Hernandez-Santana, V. & Cuevas, M.V., 2020. "Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high density olive tree orchard," Agricultural Water Management, Elsevier, vol. 237(C).
    2. Manuel Peragón, Juan & Delgado, Antonio & Antonio Rodríguez Díaz, Juan & Pérez-Latorre, Francisco J., 2016. "A GIS-based decision tool for reducing salinization risks in olive orchards," Agricultural Water Management, Elsevier, vol. 166(C), pages 33-41.
    3. Chartzoulakis, K.S., 2005. "Salinity and olive: Growth, salt tolerance, photosynthesis and yield," Agricultural Water Management, Elsevier, vol. 78(1-2), pages 108-121, September.
    4. Chen, Shichao & Du, Taisheng & Wang, Sufen & Parsons, David & Wu, Di & Guo, Xiuwei & Li, Donghao, 2021. "Quantifying the effects of spatial-temporal variability of soil properties on crop growth in management zones within an irrigated maize field in Northwest China," Agricultural Water Management, Elsevier, vol. 244(C).
    5. Mojtaba Zeraatpisheh & Esmaeil Bakhshandeh & Mostafa Emadi & Tengfei Li & Ming Xu, 2020. "Integration of PCA and Fuzzy Clustering for Delineation of Soil Management Zones and Cost-Efficiency Analysis in a Citrus Plantation," Sustainability, MDPI, vol. 12(14), pages 1-17, July.
    6. Hasan Zabihi & Mohsen Alizadeh & Philip Kibet Langat & Mohammadreza Karami & Himan Shahabi & Anuar Ahmad & Mohamad Nor Said & Saro Lee, 2019. "GIS Multi-Criteria Analysis by Ordered Weighted Averaging (OWA): Toward an Integrated Citrus Management Strategy," Sustainability, MDPI, vol. 11(4), pages 1-17, February.
    7. Antonis Papadopoulos & Dionissios Kalivas & Thomas Hatzichristos, 2015. "GIS Modelling for Site-Specific Nitrogen Fertilization towards Soil Sustainability," Sustainability, MDPI, vol. 7(6), pages 1-22, May.
    8. Ramos, Tiago B. & Darouich, Hanaa & Šimůnek, Jiří & Gonçalves, Maria C. & Martins, José C., 2019. "Soil salinization in very high-density olive orchards grown in southern Portugal: Current risks and possible trends," Agricultural Water Management, Elsevier, vol. 217(C), pages 265-281.
    9. Isaac Zipori & Ran Erel & Uri Yermiyahu & Alon Ben-Gal & Arnon Dag, 2020. "Sustainable Management of Olive Orchard Nutrition: A Review," Agriculture, MDPI, vol. 10(1), pages 1-21, January.
    10. Melgar, J.C. & Mohamed, Y. & Serrano, N. & García-Galavís, P.A. & Navarro, C. & Parra, M.A. & Benlloch, M. & Fernández-Escobar, R., 2009. "Long term responses of olive trees to salinity," Agricultural Water Management, Elsevier, vol. 96(7), pages 1105-1113, July.
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