Evaluation of nitrogen balance in a direct-seeded-rice field experiment using Hydrus-1D

Abstract

a b s t r a c tNitrogen (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 145.5 kg ha −1 in 2008 and 220 and 147.8 kg ha −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 120 cm 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.

Nitrogen Transportation and Transformation Under Different Soil Water and Salinity Conditions

“…Therefore, soil salinity has been shown to reduce the µ w1 value under irrigation. Compared with µ w1 , the µ w2 value in our study ranged from 0.04 to 0.12 day -1 among the different soil salinity levels, and this result was similar to that of the studies by Li et al [31] and Tan et al [32]. Therefore, under irrigation, the effects of soil salinity on µ w2 could not be directly compared to the effects of irrigation water levels.…”

“…1 ranged from 0.0024 to 0.1992 day -1 , which was reduced from 99.63% to 73.08% compared with that of the studies of Li et al [31] and Tan et al [32], respectively. The µ w1 value in Tan et al [32] ranged from 0.65 to 0.7 day -1 and the value in Li et al [31] was even larger at 0.74 day -1 , and these phenomena may have been caused by soil salinity because the study sites of Li et al [31] and Tan et al [32] are usually regarded as non-saline soils. Therefore, soil salinity has been shown to reduce the µ w1 value under irrigation.…”

“…HYDRUS-1D is a useful tool that can indirectly obtain the nitrogen transformation rate through calibrations based on experimental data. Li et al [31] applied the HYDRUS-1D model to evaluate the nitrogen balance in an experimental direct-seeded rice field in the Taihu Lake Basin of east China. Tan et al [32] also used the HYDRUS-1D model to analyse the water and nitrogen dynamics of lowland paddy fields under alternating wet and dry irrigation in the Tuanlin experimental paddy fields of Hubei, China.…”

Simulating the Fate and Transport of Coal Seam Gas Chemicals in Variably-Saturated Soils Using HYDRUS

“…When these constants are nonzero, then Equation (2) for i = 1 is used to simulate the transport of a parent compound and for i > 1 the transport of daughter products. The above formulation has proved useful in modelling a broad range of chemicals, including radionuclides (e.g., [15,42]), mineral nitrogen species (e.g., [16,43,44]), pesticides (e.g., [17]), chlorinated aliphatic hydrocarbons (e.g., [18,45]), hormones (e.g., [19,[46][47][48][49]), antibiotics (e.g., [20,50]), and explosives [51,52]. HYDRUS-1D at present considers up to ten solutes (five for the dual-permeability model), which either can be coupled in a unidirectional chain or are allowed to move independently of each other.…”

“…Typical examples of the latter include heavy metals [13], radionuclides [14,15]), mineral nitrogen species [16], pesticides (e.g., [17]), chlorinated aliphatic hydrocarbons (e.g., [18]), hormones [19], antibiotics [20], and explosives [21]. While this approach has proved to be suitable for many chemicals, important environmental problems often require analyses of the coupled transport of multiple chemical species that may mutually interact, create complexed species, precipitate, dissolve, and/or could compete with each other for sorption sites.…”