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Soil Data For Crop - Soil Models

J. Bouma, M. Wopereis, J. Wösten, A. Stein
Published 1992 · Environmental Science

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Systems approaches for agricultural development can be realized at different levels of detail which are associated with different data needs. For soils five levels were defined, ranging from farmer’s knowledge and expert systems to use of complex simulation models. Any problem to be studied should be analyzed thoroughly beforehand and the most appropriate level of study should be established for each discipline. Field monitoring of soil physical conditions, which is crucial for model calibration and validation, becomes increasingly important at higher levels of detail. Monitoring should be increased, paying due attention to soil profile characteristics during installation of equipment. Measurements of physical parameters needed for simulation should preferably be made in situ, using methods that are relatively simple, accurate and low-cost, such as the crust-test infiltrometer. Pedotransfer functions, which relate available soil data to parameters needed for simulation, are a potentially important source of basic soil data and should be further developed. One type of pedotransfer function uses pedogenic soil horizons from soil surveys as ‘carriers’ of data. This approach is illustrated for both a small scale and a large scale soil survey carried out in the Philippines. Field work is needed to better characterize ‘non-ideal’ soil behaviour due to soil heterogeneity, which is quite common and is as yet not covered by existing models which assume soils to be homogeneous. Soil input is not only relevant for obtaining point data but also to assist in obtaining results that are representative for areas of land. Geostatistics can make contributions towards developing efficient sampling schemes which base the number of observations on spatial heterogeneity and not on the scale of the map to be made. Geostatistics was used successfully to interpolate point data to areas of land, including estimates of accuracies, as is illustrated for a case study at the International Rice Research Institute.
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