Biophysical models are commonly used in ecosystem impact assessment studies at different temporal and spatial scales, and their results implicate decisions on the overall system at multiple levels—from micro-scale natural resource management to country- or regional-scale policy decisions. In agricultural systems, soil data is often key for understanding the current status of the ecosystem and its constraints, and strategizing proper interventions to sustainably improve its productivity.
Increased demand for comprehensive, large-scale assessments of ecosystems increase, especially in the context of enhancing food security and improving resilience to the climate change impacts, leads to a corresponding increase in global/regional-scale soil databases. However, it is difficult to find extensive, quantitative, and geo-referenced soil property databases that are readily available for the areas (or regions) of interest, especially in developing countries.
The International Soil Reference and Information Centre (ISRIC) developed a detailed geo-referenced global soil profile database, entitled World Inventory of Soil Emission Potentials (WISE). It is designed to provide scientists and ecosystem modelers with a homogenized set of soil property data that is useful for multiple purposes, from assessing soil vulnerability to determining crop production (Batjes, 2002). However, the WISE database does not provide all the information required by simulation models; the raw database is not immediately usable in all ecosystems models. Using the DSSAT (Decision Support Systems for Agrotechnology Transfer) Crop Systems Model (Hoogenboom et al., 2009; Jones et al., 2003) as an example, Figure 1 shows which variables are directly provided by WISE (solid arrows) and which ones can be estimated from other variables using pedotransfer functions (dotted arrows).
In 2007, using the 1.0 version of WISE, Gijsman et al corrected and converted 836 out of 1,125 soil profiles to a format suitable for the DSSAT. A new, improved methodology implementing a rigorous quality control to detect and estimate errors and missing values was developed by Romero et al (2010), who successfully converted 3,404 out of 4,382 soil profiles into the same format (Figure 2). In this new version of the database, about 38% of original soil profiles were improved by correcting erroneous values and estimating key missing values. By utilizing this large sample of soil profiles, it would be possible to extend crop modeling studies to the areas where no soil profile data was previously available, by, for example, finding the closest matching soil profile from the database based on key soil parameters (e.g., texture, organic carbon, rooting depth, nitrogen).
- Click the soil profile cluster (number indicates the number of soil profiles in each cluster) and zoom into it until the locations of individual soil profiles is shown.
- Some soil profiles are reported on the same location; their profile information will be shown together.
The latest version (1.1) of WISE Soil Database for Crop Simulation Models data and maps can be downloaded from Google Drive. (NOTE: The WI.SOL file contains soil profiles data formatted specifically for the DSSAT Crop Systems Models. The original WISE database can be downloaded from the World Soil Information (ISRIC) website.)
- Batjes, N.H. 2002. A Homogenized Soil Profile Data Set for Global and Regional Environmental Research (WISE, version 1.1) 2002/01. International Soil Reference and Information Centre, Wageningen, The Netherlands.
- Gijsman, A.J., P.K. Thornton, and G. Hoogenboom. 2007. Using the WISE database to parameterize soil inputs for crop simulation models. Computers and Electronics in Agriculture 56:85-100.
- Hoogenboom, G., J.W. Jones, P.W. Wilkens, C.H. Porter, K.J. Boote, L.A. Hunt, U. Singh, J.L. Lizaso, J.W. White, O. Uryasev, F.S. Royce, R. Ogoshi, A.J. Gijsman, and G.Y. Tsuji. 2009. Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 [CD-ROM]. University of Hawaii, Honolulu, Hawaii.
- Jones, J.W., G. Hoogenboom, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, and J.T. Ritchie. 2003. The DSSAT cropping system model. European Journal of Agronomy 18:235-265.
- Romero, C.C., G. Hoogenboom, G.A. Baigorria, J. Koo, A.J. Gijsman, and S. Wood. 2012. Reanalysis of a global soil database for crop and environmental modeling. Environmental Modelling & Software (Accepted).