Evaluation of nitrogen balance in a direct-seeded-rice field experiment using Hydrus-1D
- Author(s): Li, Y
- Šimůnek, J
- Zhang, Z
- Jing, L
- Ni, L
- et al.
Published Web Locationhttps://doi.org/10.1016/j.agwat.2014.10.010
© 2014 Elsevier B.V.. Nitrogen (N) pollution is a global environmental problem that has greatly increased the risks of both the eutrophication of surface waters and contamination of ground waters. The majority of N pollution mainly comes from agricultural fields, in particular during rice growing seasons. In recent years, a gradual shift from the transplanting rice cultivation method to the direct seeding method has occurred, which results in different water and N losses from paddy fields and leads to distinct impacts on water environments. The N transport and transformations in an experimental direct-seeded-rice (DSR) field in the Taihu Lake Basin of east China were observed during two consecutive seasons, and simulated using Hydrus-1D model. The observed crop N uptake, ammonia volatilization (AV), N concentrations in soil, and N leaching were used to calibrate and validate the model parameters. The two most important inputs of N, i.e., fertilization and mineralization, were considered in the simulations with 220 and 145.5kgha-1 in 2008 and 220 and 147.8kgha-1 in 2009, respectively. Ammonia volatilization and nitrate denitrification were the two dominant pathways of N loss, accounting for about 16.0% and 38.8% of the total N input (TNI), respectively. Both nitrification and denitrification processes mainly occurred in the root zone. N leaching at 60 and 120cm depths accounted for about 6.8% and 2.7% of TNI, respectively. The crop N uptake was 32.1% and 30.8% of TNI during the 2008 and 2009 seasons, respectively, and ammonium was the predominant form (74% of the total N uptake on average). Simulated N concentrations and fluxes in soil matched well with the corresponding observed data. Hydrus-1D could simulate the N transport and transformations in the DSR field, and could thus be a good tool for designing optimal fertilizer management practices in the future.