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Representative soil profiles for the Harmonized World Soil Database at different spatial resolutions for agricultural modelling applications

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  • Jones, Peter G.
  • Thornton, Philip K.

Abstract

Agricultural modellers often need detailed soil profile data with which to run their models. We combine an extensive soil profile database with the Harmonized World Soil Database, a 30arcsecond raster database of soil information worldwide, and describe a statistical process to identify representative soil profiles for each of its 188 distinct soil types at different spatial resolutions. We then outline a method to cluster the soils in the Harmonized World Soil Database to produce soil maps at coarser resolution, and we describe derived global soil maps at spatial resolutions of 5 and 10arcmin, which may be more practical for some large-scale modelling studies. The derived data files allow a user to select any point or area on land and then to access the set of soil profiles pertaining to the mapping unit selected, which are available in a format suitable for use in modelling applications. In situations where the user has little or no other information about the soils in the region of study, the methods described can be used to produce plausible soil profile information based on the most up-to-date global soil map currently available.

Suggested Citation

  • Jones, Peter G. & Thornton, Philip K., 2015. "Representative soil profiles for the Harmonized World Soil Database at different spatial resolutions for agricultural modelling applications," Agricultural Systems, Elsevier, vol. 139(C), pages 93-99.
    • Handle: RePEc:eee:agisys:v:139:y:2015:i:c:p:93-99
    DOI: 10.1016/j.agsy.2015.07.003
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    References listed on IDEAS

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    1. Hertel, Thomas W. & Lobell, David B., 2014. "Agricultural adaptation to climate change in rich and poor countries: Current modeling practice and potential for empirical contributions," Energy Economics, Elsevier, vol. 46(C), pages 562-575.
    2. Jones, Peter G. & Thornton, Philip K., 2013. "Generating downscaled weather data from a suite of climate models for agricultural modelling applications," Agricultural Systems, Elsevier, vol. 114(C), pages 1-5.
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    5. Global Commission on Adaptation, 2019. "Adapt Now," World Bank Publications - Books, The World Bank Group, number 32362.
    6. Yang, Chenyao & Fraga, Helder & Ieperen, Wim Van & Santos, João Andrade, 2017. "Assessment of irrigated maize yield response to climate change scenarios in Portugal," Agricultural Water Management, Elsevier, vol. 184(C), pages 178-190.
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    12. Amit Kumar Basukala & Livia Rasche, 2022. "Model-Based Yield Gap Assessment in Nepal’s Diverse Agricultural Landscape," Land, MDPI, vol. 11(8), pages 1-25, August.

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    More about this item

    Keywords

    WISE 3.1; Soil profile; DSSAT; Cluster; MarkSimGCM; CMIP5;
    All these keywords.

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