Comparison of DNDC and RZWQM2 for simulating hydrology and N dynamics in a corn-soybean system with a winter cover crop.


Smith, W., Qi, Z., Grant, B.,VanderZaag, A., Desjardins, R. 2017. Comparison of DNDC and RZWQM2 for simulating hydrology and N dynamics in a corn-soybean system with a winter cover crop. B53B Agricultural Systems: Links Between Hydrology and Biogeochemical Cycling III posters, AGU Fall meeting, December 15th 2017, New Orleans, United States.


It is crucial that they can accurately simulate soil hydrology and nutrient flows which strongly influence crop growth, biogeochemical processes and water quality. The purpose of this study was to compare the performance of the DeNitrification DeComposition model (DNDC),which includes relatively simple hydrologic processes, to a more comprehensive water flow model, the Root Zone Water Quality Model (RZWQM2), to determine which processes are sufficient for simulating crop yields, biomass and water quality and recommend improvements. Both models were calibrated and validated for simulating crop biomass, soil hydrology, and nitrogen loss to tile drains using detailed observations from a corn-soybean rotation in Iowa, with and without cover crops. Results indicated that soybean and maize yield, and maize biomass over the growing season were well simulated by both models (RMSE<25%). Soybean yields were also very well simulated by both models (RMSE<20%); however, soybean biomass was over-predicted by RZWQM2 in the validation treatments. The magnitude of winter rye biomass and N uptake was well simulated but the timing of growth initiation in the spring was sometimes off. The annual and monthly estimation of tile flow and nitrogen loss to tiles drains were well simulated by both models; however, RZWQM2 performed better for simulating soil water content, and the dynamics of daily water flow to tile drains (DNDC: NSE -0.32 to 0.24; RZWQM2: NSE 0.35 to 0.69). DNDC overestimated soil water content near the soil surface and underestimated it deeper in the profile which was presumably caused by the lack of a root distribution algorithm, the inability to simulate a heterogeneous profile and lack of a water table. We recommend these improvements along with the potential inclusion of enhanced water flow and a mechanistic tile drainage sub-model. The accurate temporal simulation of water and N strongly impacts several biogeochemical processes.