. The WOFOST simulation model is a tool for analysing the growth and production of field crops under a wide range of weather and soil conditions. Such an analysis is important first to assess to what extent crop production is limited by the factors of light, moisture and macro‐nutrients, and second to estimate what improvements are possible. The theoretical concept of a production situation, as modelled by WOFOST, is explained, as is the hierarchy of potential production and water‐limited and nutrient‐limited production situations in the analysis. The organization of the computer files in the model, the structure of the FORTRAN source program and the available standard sets of data are described briefly.

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Abstract. Methane dynamics in a water-saturated soil layel' with gas-transporting roots is modeled with a weighed set of single-root model systems. Each model system consists of a soil cylinder with a gas-transporting root along its axis or a soil sphere with a gas-transporting root at its centel'. The weights associated with a different cylinder or sphere radius were deduced from root architecture. Methane dynamics in each single-root model system are calculated using a single-root model fi'om the previous paper. From this full model a simplified model was deduced consisting of an oxygen-saturated and an oxygen-unsaturated model system. An even more simplified model was deduced, called the homogeneous model. In this model the concentrations are homogeneous in the whole soil layer. Simulation results of the simplified model are closer to th• simulation results of the full model than the simulation results of the homogeneous model. The overall effect of the simplifications on simulated methane emissions are small, though the underlying processes are affected more severely, depending on simulation time and parameters. At high root densities and at large times, under stationary conditions, root density is proportional to simulated methane tluxes, provided that carbon availability is proportional to root density. Sensitivity analysis shows that lack of knowledge on root gas-transport is an important limitation for the predictability of methane fluxes via the processes at the kinetic level.

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T he upper part of a living mire consists of a sponge-like layer of predominantly moss species, the acrotelm (1), with a porosity above 95%. The green and brownish plants near the surface ( Fig. 1) intercept light and fix CO 2 . Further down, the older plants turn yellow and start to decay. Aerobic decay in the acrotelm takes place relatively rapidly and makes nutrients available for recycling. Below the acrotelm, a denser layer, the catotelm, is present, where the hydraulic conductivity is much lower than in the acrotelm (2), and where the decay rate is several orders of magnitude smaller due to the anoxic conditions (3). It is the peat formation (4, 5) in the slowly growing catotelm that represents a sink of atmospheric CO 2 (5, 6).The production of organic matter at the surface largely depends on the recycling of nutrients originating from decomposing plant material. Because decomposition and photosynthesis take place at different depths, the transport of oxygen, carbon compounds, and nutrients forms an important element in the functioning of the mire ecosystem. This transport takes place both inside (7) and outside the plants by diffusion and fluid flow.In this paper, we investigate a mechanism for fluid flow in a water-saturated peat moss layer, which does not depend on capillarity or an external hydraulic pressure. During the night, the surface cools, leading to relatively cold water on top of warm water, and if the temperature drop is sufficiently large, the cold water sinks and the warm water rises. This type of flow is called buoyancy flow, and it implies convective transport of the heat and solutes carried with the water. Buoyancy flow often occurs as ''cells'' consisting of adjacent regions with upward and downward flow. We studied the phenomenon in a peat moss layer by means of a mathematical model, numerical simulation, and laboratory measurements. Model Equations and StabilityThe Mathematical Model. The model describes the heat flow in a water-saturated porous layer that undergoes periodic and sudden temperature changes at its surface.The imposed surface temperature involves the model parameters ⌬T, which is the temperature difference between ''day'' and ''night,'' and t 0 , which is the duration of each of the two periods. Four parameters describe geometrical and physical properties of the layer: the thickness H, the thermal expansion coefficient of the fluid ␣, the thermal diffusivity of the layer ‫ބ‬ eff , and the hydraulic conductivity K. Table 1 lists parameter values for the water-saturated peat moss layer used in the experiment.The equations for heat transport and fluid flow, together with the boundary conditions, are given in Appendix B. Here, we briefly discuss the physical content of the model equations in dimensionless form. Dimensionless temperatures T are expressed in units ⌬T and lie between 0 and ϩ1. Similarly, the time interval t 0 is used as the unit of time, and the distance ͌ ‫ބ‬ eff t 0 , as the unit of length. This length scale (Ϸ0.078 m) characterizes the distance over which a...

The diffusivity of oxygen in soil was measured by periodically changing the gas above a soil core from nitrogen to air and vice versa. The concentration wave was measured as a function of depth with an oxygen electrode. For different Fourier components in the signal, phase shifts were calculated. The diffusivity follows from the increase of the phase shift with depth. Phase shifts are more suitable than signal amplitudes for the derivation of diffusivity. They are also easier to measure and do not require electrode calibration.For a clay soil with an air-filled porosity of about 0.05 m3 m-3 a local diffusivity of 0.9 x lop9 m2 s-' was measured. This is several orders of magnitude smaller than macroscopic values for entire core samples of the same soil type. This low value can be explained by the presence of locally water-saturated clay.

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