Evaluation of the DSSAT-CSM for simulating yield and soil organic C and N of a long-term maize and wheat rotation experiment in the Loess Plateau of Northwestern China

The aim of this study was to evaluate the potential of the Decision Support System for Agrotechnology Transfer - Cropping System Model (DSSAT-CSM) using the CENTURY-based soil module to simulate long-term trends of grain yield, soil organic C (SOC) and soil organic N (SON) based upon 14-year data from a spring maize (Zea mays L.) and winter wheat (Triticum aestivum L.) cropping system study conducted in the Loess Plateau of Northwestern China. There were four treatments including no fertilizer (N0), 90 kg N ha−1 from urea (N90), 30 kg N ha−1 from straw plus 90 kg N ha−1 from urea (SN90), and 40 kg N ha−1 from cattle manure plus 90 kg N ha−1 from urea (MN90) selected in this study. The DSSAT-CSM showed a good to excellent agreement for simulating maize yields with normalized root mean square error (nRMSE) ≤ 19%, index of agreement (d) > 0.91 and modeling efficiency (EF) ≥ 0.56, and a moderate to good agreement for wheat yields with nRMSE ≤ 22%, d > 0.89 and EF > 0.46 for N90, SN90 and MN90 treatments. The model simulated SOC in the 0-20 cm depth for both SN90 and MN90 very well with nRMSE < 13% and d > 0.63 and moderately for N90 and N0. The simulated topsoil SON matched the measured data for N90, SN90 and MN90 very well with nRMSE < 7%, d > 0.77 and EF > 0.15, whereas the simulation for N0 was poor. Both maize wheat yields were found to be more sensitive to the fertilizer N rates in humid than drought soil conditions. The sensitivity of grain yields for either maize or wheat to generated growing season precipitation was affected by fertilizer N rate. The simulated soil nitrate-N (NO3-N) in soil profile and the NO3-N leaching below 150 cm increased with the increased fertilizer N rates as expected. The periods occurring high NO3-N leaching were along with drainage events mainly in the next fallow periods. Therefore, this study found that the DSSAT-CSM has a large potential to assess the impacts of various agricultural practices on crop growth, soil C and N dynamics in the semi-arid to semi-humid region of the Loess Plateau, and could contribute to selecting the optimum management practices.