Vertical and horizontal distribution of soil parameters in intensive agricultural zone and effect on diffuse nitrogen pollution

Abstract

Understanding the spatial relationships of diffuse agricultural pollution with soil properties at a sub-basin scale is an innovative way to characterize the pollution yield. The objectives of this study was to identify the interaction of soil parameters with diffuse nitrogen (N) loading at spatial-vertical directions, which provide an optional method to assess the diffuse N pollution. The diffuse N loading of a sub-basin was simulated with the Soil and Water Assessment Tool with the consideration of land use (upland and paddy rice). Soil properties were analyzed in terms of eight parameters by employing a 1.5km-grid soil sampling process at two depths across multiple sub-basins. The spatial soil properties were interpolated for each sub-basin. The spatial distributions of total nitrogen (TN), iron (Fe), manganese (Mn), and cadmium (Cd) exhibited the same pattern at two soil depths, but the vertical patterns of available nitrogen (AN), soil organic carbon (SOC), sulfur (S) and lead (Pb) varied. Overlaying the diffuse N loading and land use distribution, it was found that the sub-basins of upland and paddy rice were primary contributors. The diffuse N discharged from upland sub-basins was about 50% lower than that from paddy rice. The correlation analysis of soil variables with diffuse N indicated that the top layer had a stronger relationship with the diffuse N than the subsurface, which had more direct impact on the pollution. A partial least squares (PLS) regression analysis was employed to identify the key soil variables in surface layer. The analysis indicated that the metal parameters (Fe, Mn, Cd, and Pb) were the important factors for diffuse N loading. However, the TN in the paddy rice was the principal predictor. With the soil property information, the diffuse N yield from the two types of farmlands can be assessed in a simplified way. The developed method in this paper is flexible and efficient, which also is compatible with results of the SWAT model.