A simulation model of cereal-legume intercropping systems for semi-arid regions I. Model development

Cereal-legume intercropping plays an important role in subsistence food production in developing countries, especially in situations of limited water resources. Crop simulation can be used to assess risk for intercrop productivity over time and space. In this study, a simple model for intercropping was developed for cereal and legume growth and yield, under semi-arid conditions. The model is based on radiation interception and use, and incorporates a water stress factor. Total dry matter and yield are functions of photosynthetically active radiation (PAR), the fraction of radiation intercepted and radiation use efficiency (RUE). One of two PAR sub-models was used to estimate PAR from solar radiation; either PAR is 50% of solar radiation or the ratio of PAR to solar radiation (PAR/SR) is a function of the clearness index (K-T). The fraction of radiation intercepted was calculated either based on Beer's Law with crop extinction coefficients (K) from field experiments or from previous reports. RUE was calculated as a function of available soil water to a depth of 900 mm (ASW). Either the soil water balance method or the decay curve approach was used to determine ASW. Thus, two alternatives for each of three factors, i.e., PAR/SR, K and ASW, were considered, giving eight possible models (2 methods x 3 factors). The model calibration and validation were carried out with maize-bean intercropping systems using data collected in a semi-arid region (Bloemfontein, Free State, South Africa) during seven growing seasons (1996/1997-2002/2003). The combination of PAR estimated from the clearness index, a crop extinction coefficient from the field experiment and the decay curve model gave the most reasonable and acceptable result. The intercrop model developed in this study is simple, so this modelling approach can be employed to develop other cereal-legume intercrop models for semi-arid regions. (c) 2004 Elsevier B.V. All rights reserved.

Simulation study of ammonia adsorption on graphitized carbon black

GCMC simulations are applied to the adsorption of sub-critical ammonia on graphitized carbon black at 240 K. The carbon black was modelled both with and without carbonyl functional groups. Large differences are seen between the amount adsorbed for different carbonyl configurations at low pressure (P < 10kPa). Once a single layer is formed on the carbon black, the adsorption behaviour is similar between the model surfaces with and without functional groups. Simulation isotherms are qualitatively similar to the few experimental isotherms available in the literature for ammonia on highly graphitized carbon black. The mode of adsorption up to monolayer coverage is exhaustively shown to be two-dimensional clustering using various techniques. A comparison between experiment and simulation isosteric heats shows that a surface without functional groups cannot reproduce the experimental isosteric heats of adsorption, even comparing with the experimental results of carbon black heat treated at 3373 K. The addition of carbonyls produces isosteric heats with similar features to those in the literature if the separation between the carbonyls is small.

Occurrence and simulation of nitrification in two contrasting sugarcane soils from the Australian wet tropics

The concentration of ammonium-nitrogen (NH4+-N) frequently exceeds that of nitrate-N (NO3--N) in Australian wet tropical sugarcane soils. The amount of mineral N in soil is the net result of complex processes in the field, so the objective of this experiment was to investigate nitrification and ammonification in these soils under laboratory conditions. Aerobic and saturated incubations were performed for 1 week on 2 wet tropical soils. Net NO3--N increased significantly in both soils during both types of incubation. A second series of aerobic incubations of these soils treated with NH4+-N and inoculated with subtropical nitrifying soils was conducted for 48 days. Nitrification in the wet tropical soils was not significantly affected by inoculation, and virtually all added N was nitrified during the incubation period. Mineral N behaviour of the 48-day incubations was captured with the APSIM-SoilN model. As nitrification proceeded under laboratory conditions and was able to be captured by the model, it was concluded that nitrification processes in the wet tropical soils studied were not different from those in the subtropical soils. Processes that remove NO3- from the soil, such as leaching and denitrification, may therefore be important factors affecting the proportions of NH4+-N and NO3--N measured under field conditions.

Simulation of air traffic controllers' behaviour using the operator choice model

The Operator Choice Model (OCM) was developed to model the behaviour of operators attending to complex tasks involving interdependent concurrent activities, such as in Air Traffic Control (ATC). The purpose of the OCM is to provide a flexible framework for modelling and simulation that can be used for quantitative analyses in human reliability assessment, comparison between human computer interaction (HCI) designs, and analysis of operator workload. The OCM virtual operator is essentially a cycle of four processes: Scan Classify Decide Action Perform Action. Once a cycle is complete, the operator will return to the Scan process. It is also possible to truncate a cycle and return to Scan after each of the processes. These processes are described using Continuous Time Probabilistic Automata (CTPA). The details of the probability and timing models are specific to the domain of application, and need to be specified using domain experts. We are building an application of the OCM for use in ATC. In order to develop a realistic model we are calibrating the probability and timing models that comprise each process using experimental data from a series of experiments conducted with student subjects. These experiments have identified the factors that influence perception and decision making in simplified conflict detection and resolution tasks. This paper presents an application of the OCM approach to a simple ATC conflict detection experiment. The aim is to calibrate the OCM so that its behaviour resembles that of the experimental subjects when it is challenged with the same task. Its behaviour should also interpolate when challenged with scenarios similar to those used to calibrate it. The approach illustrated here uses logistic regression to model the classifications made by the subjects. This model is fitted to the calibration data, and provides an extrapolation to classifications in scenarios outside of the calibration data. A simple strategy is used to calibrate the timing component of the model, and the results for reaction times are compared between the OCM and the student subjects. While this approach to timing does not capture the full complexity of the reaction time distribution seen in the data from the student subjects, the mean and the tail of the distributions are similar.