Why Generic Soil Profiles
Map of the distribution of 27 generic soils in sub-Saharan Africa at 5 arc-minute grid cells. Each cell shows the predominant soil.
Ecosystems models are used in various types of impact assessment studies at different temporal and spatial scales, and their results often implicate policy and management decisions at multiple levels (e.g., from micro-level farm management to macro-level natural resource management). Soil information is often a key input to the models, yet it is difficult to obtain extensive, quantitative, and geo-referenced soil property data for the areas (or regions) of interest. Global soil databases do exist (e.g., Harmonized World Soil Database (HWSD) by IIASA/FAO/ISSCAS/ISRIC/JRC, 2009), but they do not provide all the required information for the models at a specific site. Whereas existing global soil profile databases (e.g., WISE by ISRIC, 2002) do not extensively cover large areas in the developing world.
To overcome the limitation of location-specific soil profile data for crop modeling applications, we generated a set of generic soil profiles based on three criteria that crop models are most responsive to: texture, rooting depth, and organic carbon content. By classifying three levels for each category and setting their boundary conditions, 27 soil profiles, HC27, were generated in formats compatible with DSSAT and APSIM. The boundary conditions were defined based on soil profiles recorded in Sub-Saharan Africa (SSA) and are thus subject to further adjustments in other regions where extensive soil profiles are available.
How to Use the 27 Soil Profiles
There are multiple ways to utilize HC27 in crop modeling applications. First, for a given site, users can choose which one best matches the soils found in the area. It would be difficult to estimate values of all soil properties that crop models need, but selecting one out of 27 by answering three multiple-choice questions would be relatively straightforward to users with some level of agronomic knowledge. Secondly, a model can be run with all 27 soil profiles for a given site to create a set of simulation results, then narrowed down to the most relevant one later as more site-specific information becomes available. Finally, based on additional information from other databases, a new kind of soil map that locates 27 soils can be generated and used in large-scale applications.
For example, Figure 1 is an example of a soil map indicating which one of 27 soils is predominantly distributed where. This data layer was generated by 1) overlaying 10-km grids on HWSD v1.1; 2) computing zonal statistics of soils on grids; 3) determining the predominant soil in each grid cell; and 4) matching the soil with one of 27 soils based on the predominant soil’s texture, organic carbon content of top soil, and available water content classification (as the proxy of rooting depth) from the HWSD.
Is HC27 the Ultimate Soil Database?
The HC27 does not replace existing high-resolution soil mapping efforts nor duplicate site-specific soil measurements. Instead, this approach tries to address the need for a reasonably representative meso-scale soil profile database to be used in certain types of spatial crop systems modeling applications. For example, in 2009, HC27 was used in regional/global scale climate change impact assessment studies by IFPRI. However, due to the nature of “generic” characteristics, there will be applications for which the use of HC27 is not desirable, namely where detailed soil property dynamics beyond the three criteria are emphasized.
Download
The latest version of HC27 can be downloaded at IFPRI’s Dataverse.
Download HC27How to Cite
Koo, Jawoo; Dimes, John, 2010-07, “HC27 Generic Soil Profile Database”, http://hdl.handle.net/1902.1/20299 International Food Policy Research Institute [Distributor] V1 [Version]
References
- FAO/IIASA/ISRIC/ISSCAS/JRC, 2009. Harmonized World Soil Database (version 1.1) http://bit.ly/cDZLyq
- ADB, 2009. Building Climate Resilience in the Agricultural Sector of Asia and the Pacific. http://bit.ly/bV6JtV
- IFPRI, 2009. Climate Change Impact on Agriculture and Costs of Adaptation. http://bit.ly/aAL4tI
