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United States Department of Agriculture

Agricultural Research Service

Title: Environmental Management of Soil Phosphorus: Modeling Spatial Variability in Small Fields

Authors
item Needleman, Brian
item Gburek, William
item Sharpley, Andrew
item Petersen, Gary - PENN STATE UNIVERSITY

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 13, 2000
Publication Date: September 2, 2001
Citation: NEEDLEMAN, B.A., GBUREK, W.J., SHARPLEY, A.N., PETERSEN, G.W. ENVIRONMENTAL MANAGEMENT OF SOIL PHOSPHORUS: MODELING SPATIAL VARIABILITY IN SMALL FIELDS. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL. 2001. V. 65(5) P. 1516-1522.

Interpretive Summary: Excess phosphorus (P) inputs can increase the biological productivity of fresh waters by accelerating eutrophication. State and Federal authorities are moving towards stricter P management and increased pollution prevention support. A site vulnerability assessment tool, the P index, has been developed to target P management in agricultural fields. In order to implement the P index, the P contents of a field need to be mapped. This mapping can simply be the use of a bulk sample or average of several samples as an estimate of P content across that field. However, there may be areas of the field with greater or lesser P contents. Ideally, we should manage these areas differently. In order to do so, a distributed sampling design is necessary. Further, we need to interpolate the sampling points in order to generate an accurate map of the P contents across that field. This approach would increase sampling and analysis costs, which may ynot be economically feasible in areas with relatively small agricultural fields, such as the Northeast. In this study, we compared the effectiveness of two interpolation strategies for the mapping of P contents within a field. These strategies were then compared to the simple bulking approach. The interpolation strategies did perform slightly better than the bulking approach. However, the difference was fairly minor. When applied to the P index, the resulting field management strategies would be identical. Therefore, we concluded that although soil P contents do vary substantially within fields, the added expense of more complicated mapping strategies is not warranted for the application of the P index.

Technical Abstract: The mapping of soil phosphorus (P) contents is necessary to assess the risk of P loss in runoff. We modeled the distribution of Mehlich-3 extractable soil P (M3P) in an east-central Pennsylvania 39.5-ha watershed (FD-36) with an average field size of 1.0 ha using three interpolation methods. Soils were sampled on a 30-m grid, resulting in an average of 14 samples per field. The three interpolation models used were: 1) the field classification model - using field means as the estimator across a field, 2) the global model - using ordinary kriging across the watershed, and 3) the within-field model - using ordinary kriging within fields with a pooled within-stratum variogram. Multiple validation runs were used to compare the models. Overall, the mean absolute errors of the models were 76, 71, and 66 mg kg-1 for the field classification, global, and within-field models, respectively. The field classification model performed substantially worse than did the kriging methods in five fields; these fields exhibited strong spatial autocorrelation. The within-field model performed substantially better than did the global model in three fields where autocorrelation was confined by the field boundary. However, no differences in P index classification were observed between the three prediction surfaces. The field classification model is simpler and less expensive to implement than the kriging models and should be adequate for applications that are not sensitive to small errors in soil P content estimates.

Last Modified: 7/24/2014
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