Mapping soil organic carbon and total nitrogen in croplands of the Corn Belt of Northeast China based on geographically weighted regression kriging model

Abstract

Understanding the spatial distributions of soil organic carbon (SOC) and total nitrogen (TN) in croplands is necessary for the sustainable management of soil resources. In this study, a geographically weighted regression kriging (GWRK) model was applied to investigate spatial variabilities of SOC and TN in croplands of the Corn Belt of Northeast China (CBNC). Based on this, a map of the ratio of SOC and TN (C:N) was obtained. Results of geostatistical analysis showed that the best-fit variogram models for SOC and TN were spherical and exponential, respectively; the spatial dependence structures of SOC and TN were strong. The variabilities of SOC and TN were explained by GWRK model having a relatively high R2, and low root mean square error (RMSE) and mean absolute error (MAE) indices. These indices showed the potential applications of GWRK model on a large scale when environmental variables are quite different and the global trend is weak. The area under the curve (AUC) –receiver operating characteristic (ROC) curve exhibited that the prediction of SOC has a general performance whereas that of TN exhibited a good performance. Annual mean temperature had the largest impact on the prediction of SOC and TN in the CBNC. Mediated by topographic and climatic variables, remote sensing-derived variables did not play prominent roles as other studies for the explanation of the distributions of SOC and TN. SOC and TN contents reduced from northeast to southeast of the CBNC, and the average predicted contents were 13.22 g kg−1 and 1.28 g kg−1, respectively. The total level of C:N ratio was relatively low, suggesting high rates of decomposition. Our study results indicated that the influence of human activities on croplands of the CBNC should not be ignored. It also recommended that the improvement of agricultural management was an approach to re-configure the spatial distributions of SOC and TN in the CBNC of China.