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Basic Soil Data Requirements for Process-Based Crop Models as a Basis for Crop Diversification

Author

Listed:
  • Eranga M. Wimalasiri

    (Crops for the Future UK, Chelmsford, Essex CM2 7PJ, England, UK)

  • Ebrahim Jahanshiri

    (Crops for the Future UK, Chelmsford, Essex CM2 7PJ, England, UK)

  • Tengku Adhwa Syaherah Tengku Mohd Suhairi

    (Crops for the Future UK, Chelmsford, Essex CM2 7PJ, England, UK)

  • Hasika Udayangani

    (Department of Export Agriculture, Faculty of Agricultural Sciences, Sabaragamuwa University of Sri Lanka, Belihuloya 70140, Sri Lanka)

  • Ranjith B. Mapa

    (Department of Soil Science, Faculty of Agriculture, University of Peradeniya, Peradeniya 20400, Sri Lanka)

  • Asha S. Karunaratne

    (Department of Export Agriculture, Faculty of Agricultural Sciences, Sabaragamuwa University of Sri Lanka, Belihuloya 70140, Sri Lanka)

  • Lal P. Vidhanarachchi

    (Department of Export Agriculture, Faculty of Agricultural Sciences, Sabaragamuwa University of Sri Lanka, Belihuloya 70140, Sri Lanka)

  • Sayed N. Azam-Ali

    (Crops for the Future UK, Chelmsford, Essex CM2 7PJ, England, UK)

Abstract

Data from global soil databases are increasingly used for crop modelling, but the impact of such data on simulated crop yield has not been not extensively studied. Accurate yield estimation is particularly useful for yield mapping and crop diversification planning. In this article, available soil profile data across Sri Lanka were harmonised and compared with the data from two global soil databases (Soilgrids and Openlandmap). Their impact on simulated crop (rice) yield was studied using a pre-calibrated Agricultural Production Systems Simulator (APSIM) as an exemplar model. To identify the most sensitive soil parameters, a global sensitivity analysis was performed for all parameters across three datasets. Different soil parameters in both global datasets showed significantly ( p < 0.05) lower and higher values than observed values. However, simulated rice yields using global data were significantly ( p < 0.05) higher than from observed soil. Due to the relatively lower sensitivity to the yield, all parameters except soil texture and bulk density can still be supplied from global databases when observed data are not available. To facilitate the wider application of digital soil data for yield simulations, particularly for neglected and underutilised crops, nation-wide soil maps for 9 parameters up to 100 cm depth were generated and made available online.

Suggested Citation

  • Eranga M. Wimalasiri & Ebrahim Jahanshiri & Tengku Adhwa Syaherah Tengku Mohd Suhairi & Hasika Udayangani & Ranjith B. Mapa & Asha S. Karunaratne & Lal P. Vidhanarachchi & Sayed N. Azam-Ali, 2020. "Basic Soil Data Requirements for Process-Based Crop Models as a Basis for Crop Diversification," Sustainability, MDPI, vol. 12(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7781-:d:416619
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    References listed on IDEAS

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    Cited by:

    1. Ebrahim Jahanshiri & Sayed Azam-Ali & Peter J. Gregory & Eranga M. Wimalasiri, 2023. "A Shortlisting Framework for Crop Diversification in the United Kingdom," Agriculture, MDPI, vol. 13(4), pages 1-29, March.
    2. Dorijan Radočaj & Mladen Jurišić & Irena Rapčan & Fran Domazetović & Rina Milošević & Ivan Plaščak, 2023. "An Independent Validation of SoilGrids Accuracy for Soil Texture Components in Croatia," Land, MDPI, vol. 12(5), pages 1-16, May.

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