[Abstract]Grain harvest represents a period of high risk and is also a bottleneck in a grain production. This study develops a climate-based systems simulation model toinvestigate the economics of high moisture grain harvesting in Australia. The optimum harvesting and drying strategies were determined. The role of grain aeration cooling was also examined. The model software was developed in MATLAB. This model was run on an hourly basis using 15 years of historical weather data (1991-2005) for three main wheat production areas in Australia, represented by Goondiwindi (QLD), Tamworth (NSW) and Scaddan (WA).The Wheat Harvest System Simulation Model (WHSSM) consists of four submodels of weather data, machinery performance, crop loss and economic calculations. Each submodel is represented by mathematical functions and supportedby available theoretical and field data. The weather submodel is used to predict dynamic grain moisture contents for a standing crop in the field. Machinerysubmodel was developed to calculate machinery performance and its operating costs at different grain and weather conditions. The main machinery involved are combineharvester, cooling aerator, and four categories of grain driers. Crop loss submodel is used to quantify grain losses involved during harvest and storage periods, including shedding (yield) losses, header losses, threshing losses, crop quality downgrading losses (due to rainfalls), and storage spoilage losses.The model has been used to predict and compare the possible return for different harvesting and postharvest management strategies. For the reference case (a 1000 ha farm with a high-capacity harvester and medium-capacity drier in Goondiwindi), it is found that the optimum harvest moisture content for using continuous flow drier and batch drier is 14 and 13% (wet basis) respectively. Foraeration simulation, it is found that the use of an aeration cooling system would slightly increase grower’s return when the drier capacity is inadequate. No positiveimpact can be achieved on return if growers use either high or medium capacity driers. Generally, high capacity harvester travelling at lower speed is preferred.It is also demonstrated that local weather conditions/rainfall patterns can have a very significant influence on grower returns. Growers in dry and warmlocation (e.g. Goondiwindi) will gain better return. It is predicted that at the given model control values, the long-term optimum harvest moisture contents for Goondiwindi, Scaddan and Tamworth are 14, 15 and 17% respectively.

This PhD thesis evaluated the applicability of Climate-Based Daylight Modelling (CBDM) as it is presently done. The objectives stated in this thesis aimed at broadly assessing applicability by looking at multiple aspects: (i) the way CBDM is used by expert researchers and practitioners; (ii) how state-of-the-art simulation techniques compare to each other and how they are affected by uncertainty in input factors; (iii) how the simulated results compare with data measured in real occupied spaces. The answers obtained from a web-based questionnaire portrayed a variety of workflows used by different people to perform similar, if not the same, evaluations. At the same time, the inter-model comparison performed to compare the existing simulation techniques revealed significant differences in the way the sky and the sun are recreated by each technique. The results also demonstrated that some of the annual daylight metrics commonly required in building guidelines are sensitive to the choice of simulation tool, as well as other input parameters, such as climate data, orientation and material optical properties. All the analyses were carried out on four case study spaces, remodelled from existing classrooms that were the subject of a concurrent research study that monitored their interior luminous conditions. A large database of High Dynamic Range images was collected for that study, and the luminance data derived from these images could be used in this work to explore a new methodology to calibrate climate-based daylight models. The results collected and presented in this dissertation illustrate how, at the time of writing, there is not a single established common framework to follow when performing CBDM evaluations. Several different techniques coexist but each of them is characterised by a specific domain of applicability.