4.6 Article

A global soil data set for earth system modeling

Journal

JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
Volume 6, Issue 1, Pages 249-263

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2013MS000293

Keywords

global soil data set; soil linkage method; earth system modeling; legacy soil data; soil mapping

Funding

  1. Natural Science Foundation of China [41205037, 40875062, 40225013]
  2. MOST [2010CB951802]
  3. R&D Special Fund for Nonprofit Industry (Meteorology) [GYHY201206013, GYHY200706025]
  4. R&D Special Fund for GRAPES of CMA
  5. Fundamental Research Funds for the Central Universities

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We developed a comprehensive, gridded Global Soil Dataset for use in Earth System Models (GSDE) and other applications. The GSDE provides soil information, such as soil particle-size distribution, organic carbon, and nutrients, and quality control information in terms of confidence level at 30 '' x 30 '' horizontal resolution and for eight vertical layers to a depth of 2.3 m. The GSDE is based on the Soil Map of the World and various regional and national soil databases, including soil attribute data and soil maps. We used a standardized data structure and data processing procedures to harmonize the data collected from various sources. We then used a soil type linkage method (i.e., taxotransfer rules) and a polygon linkage method to derive the spatial distribution of the soil properties. To aggregate the attributes of different compositions of a mapping unit, we used three mapping approaches: the area-weighting method, the dominant soil type method, and the dominant binned soil attribute method. The data set can also be aggregated to a lower resolution. In this paper, we only show the vertical and horizontal variations of sand, silt and clay contents, bulk density, and soil organic carbon as examples of the GSDE. The GSDE estimates of global soil organic carbon stock to the depths of 2.3, 1, and 0.3 m are 1922.7, 1455.4, and 720.1 Gt, respectively. This newly developed data set provides more accurate soil information and represents a step forward to advance earth system modeling.

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