RESUMEN
Joint standard-exceeding risk and its spatial uncertainty of soil available nitrogen (AN) and available phosphorus (AP) under the specific constraints are essential for guiding the joint regulation of pollutants but were rarely considered by previous studies. Moreover, traditionally-used spatial simulation models are not only non-robust but also ignoring valuable categorical information (e.g., land-use types), which may hinder the acquisition of high-precision spatial simulation results. This study first established optimally robust semi-variogram estimators to identify the spatial outliers of soil AN and AP in Jintan County, China. Then, robust sequential Gaussian simulation (RSGS) with land-use types (RSGS-LU) was proposed and further compared with RSGS, SGS-LU, and SGS in the spatial simulation accuracy. Last, a joint standard-exceeding probability model under the specific constraints was proposed, and the corresponding high-risk areas were delineated for the joint regulation of soil AN and AP. Results showed that: (i) 23 and 17 spatial outliers were identified for soil AN and AP, respectively; (ii) removing outliers or combining land-use types could improve the spatial simulation accuracy of soil AN and AP; (iii) RSGS-LU generated the highest spatial simulation accuracy for both soil AN and AP; (iv) the area with the joint standard-exceeding (AP > 30 mg kg-1⪠AN > 130 mg kg-1) probability >75% accounted for 9.98% of the county's area; (iv) the area with the joint standard-exceeding (AP > 30 mg kg-1⩠AN > 130 mg kg-1) probability >75% accounted for 2.29% of the county's area. It is concluded that RSGS-LU and joint standard-exceeding probability model under the specific constraints could provide more accurate and flexible spatial decision support for the joint regulation of soil AN and AP at a regional scale. Moreover, the methods recommended in this study also provide valuable tools for the joint standard-exceeding risk assessment of other multiple soil pollutants.