Evaluation and Modeling of the Impact of Environmentally Friendly
7
Shaviv (1996) demonstrated the importance of matching the temporal pattern
of release from coated urea granules with plant demand. CRNs with a sigmoidal
release pattern closest to that ofN demand induced the highest yield and N uptake
of ryegrass and smallest leaching losses of nitrate in a pot experiment with
different CRNs. The results obtained in pot experiments in which the bed volume
is confined and the leaching from the pot makes the process nonreversible are far
from properly representing field conditions, and can serve only for first evaluation
of the agronomic and environmental performance of CRFs under real field
conditions. The incorporation of N release into N dynamics models enables the
analysis of CRN effectiveness and prediction of nitrogen fate under field
conditions.
3 Modeling Nitrogen Dynamics
Mathematical models of N dynamics can indeed provide a means for testing the
effectiveness of EFFPs in reducing N losses and increasing N-use efficiency
(NUE), resulting in savings in part of the labor-intensive and time-consuming
efforts required for performing proper field experiments. Existing N dynamics
models are not geared to this purpose, since several important factors or effects
that control N transport and transformations in the soil under conditions of the
application of EFFPs have not been well accounted for in these models. Among
these are nitrification inhibition, pH changes due to nitrification, N release from
CRNs, and multidimensional N transport. Soil water content, temperature, O2,
NH3, and CO2 concentrations, and pH are highly dynamic under field conditions.
The spatial distribution of these variables strongly depends on the fertilizer
application method (banding, nesting, or broadcasting), the irrigation method, and
the root distribution that may be affected by the planting or seeding method (e.g.,
row vs. random distribution). The incorporation of the effects in N dynamics
models is essential for a realistic evaluation ofN losses and NUE.
In this chapter, the influences of various EFFPs on N losses and N uptake are
analyzed by a comprehensive N dynamics model described by Bear et al. (1998)
and Wang et al. (1998b). The model consists of three main components: (1) mass
balance (continuity) equations that describe the transport of water, air, proton,
carbon, and nitrogen species (ammonium, nitrate, urea) via partial differential
equations (PDEs); (2) submodels that describe the transformations related to
water, heat, and chemical components, appearing as time-dependent source-sink
terms in the PDEs; and (3) submodels that describe the chemical equilibrium
among ammoniacl and carbonate species in soil solution.
Equation (7) shows the typical formulation of the continuity equations for the
components (y) dealt with in the model:
7
Shaviv (1996) demonstrated the importance of matching the temporal pattern
of release from coated urea granules with plant demand. CRNs with a sigmoidal
release pattern closest to that ofN demand induced the highest yield and N uptake
of ryegrass and smallest leaching losses of nitrate in a pot experiment with
different CRNs. The results obtained in pot experiments in which the bed volume
is confined and the leaching from the pot makes the process nonreversible are far
from properly representing field conditions, and can serve only for first evaluation
of the agronomic and environmental performance of CRFs under real field
conditions. The incorporation of N release into N dynamics models enables the
analysis of CRN effectiveness and prediction of nitrogen fate under field
conditions.
3 Modeling Nitrogen Dynamics
Mathematical models of N dynamics can indeed provide a means for testing the
effectiveness of EFFPs in reducing N losses and increasing N-use efficiency
(NUE), resulting in savings in part of the labor-intensive and time-consuming
efforts required for performing proper field experiments. Existing N dynamics
models are not geared to this purpose, since several important factors or effects
that control N transport and transformations in the soil under conditions of the
application of EFFPs have not been well accounted for in these models. Among
these are nitrification inhibition, pH changes due to nitrification, N release from
CRNs, and multidimensional N transport. Soil water content, temperature, O2,
NH3, and CO2 concentrations, and pH are highly dynamic under field conditions.
The spatial distribution of these variables strongly depends on the fertilizer
application method (banding, nesting, or broadcasting), the irrigation method, and
the root distribution that may be affected by the planting or seeding method (e.g.,
row vs. random distribution). The incorporation of the effects in N dynamics
models is essential for a realistic evaluation ofN losses and NUE.
In this chapter, the influences of various EFFPs on N losses and N uptake are
analyzed by a comprehensive N dynamics model described by Bear et al. (1998)
and Wang et al. (1998b). The model consists of three main components: (1) mass
balance (continuity) equations that describe the transport of water, air, proton,
carbon, and nitrogen species (ammonium, nitrate, urea) via partial differential
equations (PDEs); (2) submodels that describe the transformations related to
water, heat, and chemical components, appearing as time-dependent source-sink
terms in the PDEs; and (3) submodels that describe the chemical equilibrium
among ammoniacl and carbonate species in soil solution.
Equation (7) shows the typical formulation of the continuity equations for the
components (y) dealt with in the model: