38-8 Evaluation of Water and Nitrogen Balance in a Direct-Seeded-Rice Field Experiment Using Hydrus-1D.
See more from this Division: SSSA Division: Soil Physics and Hydrology
See more from this Session: Symposium--Grand Challenges in Modeling Soil Processes: I
Monday, November 16, 2015: 10:00 AM
Minneapolis Convention Center, 103 DE
Abstract:
A gradual shift of the rice cultivation method from transplanting to direct seeding occurred in recent years and this could result in different water and N losses from paddy fields and lead to distinct impacts on the environment. Water fluxes, as well as nitrogen transport and transformations, were observed in an experimental direct-seeded-rice (DSR) field in the Taihu Lake Basin of east China during two consecutive seasons, one significantly wetter than the other. The experimental data were analyzed using Hydrus-1D, which was calibrated using data from the first year and validated using data from the second year. For that purpose, the Hydrus-1D model was modified so that it could handle the rice growing season in its entirety with its distinct irrigation/fertilization periods. Observed pressure heads at different soil depths were used to calibrate soil hydraulic parameters, and the observed crop N uptake, ammonia volatilization (AV), N concentrations in soil, and N leaching were used to calibrate and validate the N model parameters. The two most important inputs of N were fertilization and mineralization, while AV and nitrate denitrification were the two dominant pathways of N loss. Simulated pressure heads and vertical water fluxes, as well as N concentrations and N fluxes in the soil matched measured data well. The Hydrus-1D can be used to simulate water flow and water balance, as well as the N transport and transformations, in the DSR fields, and could thus be a good tool for designing optimal irrigation/fertilizer management practices in the future.
See more from this Division: SSSA Division: Soil Physics and Hydrology
See more from this Session: Symposium--Grand Challenges in Modeling Soil Processes: I