3. METHODOLOGY
3.8 Model input data requirements
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sites limited chances to calibrate and validate the model at specific sites. However, since the model has been calibrated and validated for South African conditions, the model was applied at all sites.
Abraha and Savage (2008) calibrated and validated the CropSyst prior to investigating impacts of climate change on the maize crop in Cedara, KwaZulu-Natal. They calibrated and validated various parameters in the model but in this study, concern was given to aspects within the model involved in simulating maize crop yield, i.e. crop phenology (thermal time, photoperiod) and crop growth (water and radiation dependent growth). Their findings showed that the model performed well in simulating fallow and cropped plots (maize). They found that the soil water was slightly under-estimated in maize-planted plots and advised that soil water parameters should be updated using field observations especially following high rainfall events. They also found that the models ability to model maize phenological stages was good(Abraha and Savage, 2008). In this study, version 4.14.04 (19 January 2013) of the CropSyst model was used.
3.8 Model input data requirements
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Soil attributes such as soil horizon thickness, texture, bulk density, cation exchange, pH and volumetric soil water content were obtained for each area of study from the land type maps.
The volumetric water content was also assumed to be the initial soil water content at the beginning of each season. All soil parameters used as input in the model are shown in APPENDIX C.
3.8.3 Crop file
Typical crop input parameters for maize are available in the model but if field measured data is available, relevant adjustments should be made.This file is structured in four general sections: phenology (thermal time requirements to reach specific growth stages, modulated by photoperiod and vernalization requirements if needed), morphology (Maximum LAI, root depth, specific leaf area and other parameters defining canopy and root characteristics), Growth (transpiration-use efficiency normalized by VPD, light-use efficiency, stress response parameters, etc.) and harvest component. Due to lack of phenological and morphological data, default maize crop parameters required in the crop file were used (shown in APPENDIX D).
3.8.4 Management file
The CropSyst management file includes automatic and scheduled management events.
Automatic events (irrigation and nitrogen fertilization) are generally specified to provide optimum management for maximum growth (Stockle and Nelson, 2000). Management events can be scheduled using actual date or relative date. Scheduled events include irrigation (application date, amount, chemical or salinity content), nitrogen fertilization (application date, amount, source- organic and inorganic, and application mode- broadcast, incorporated, injected), tillage operations (primary and secondary tillage operations), and residue management (such as grazing, burning and chopping) (Stockle and Nelson, 2000).
In this study, management input parameters that were used included only fertilization and harvesting. Tillage, irrigation and residue application were not utilized since most commercial farmers practice conservation farming (minimal or no till) with crops entirely dependent on rainfall. Also, since one of aims of the study is to determine the effect of increased rainfall amounts on maize yields, thus water supply by irrigation should not be considered in order to
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obtain precise results. Nitrogen (N) application was considered to occur five days before and at planting. In South Africa, N application ranges from 20 – 30 kg ha-1 depending on the soil conditions (Maine et al., 2009). In this study, 30 kg ha-1 of inorganic N fertilizer was used for each location. Ideally, N supplements should be applied during the growing season in order to replenish lost N. A plant density of 3 plants per meter was assumed for each location (adopted from Walker, (2005)). Fixed planting dates are generally not used in South Africa. It depends on spring/early summer rainfall having been received at a specified window. However, in this study, planting dates for the eastern parts of the Highveld were assumed to be on the 1st of November and on the 15st of November for the western parts. The reason for this was that the eastern parts are wetter and also receive rainfall earlier than the western parts (under normal circumstances) (Walker, 2005). The model executes harvesting 5 days after at maturity.
3.8.5 Simulation control file
The CropSyst simulation control file allows the user to build simulation conditions from an existing database i.e. location, soil, crop and management files. The file determines the start and ending day of simulations, defines the crop rotation to be simulated and set the values of all parameters requiring initialization. Within the simulation control file wizard are options to input initial values and parameters that influence different sub-models (Stockle and Nelson, 2000). Figure 7.1 in APPENDIX E shows the simulation control file.
Once the simulation control file has been defined, the user can then choose the desired output variables. The variables can either be daily, annual (annual summery of variables accumulated throughout the calendar year) or harvest variables (provide harvest yield and relevant crop conditions at harvest time accumulated throughout the growing season) (Stockle and Nelson, 2000). The output files or reports are formatted as excel spreadsheets or notepad.
In this study, a few output variables were chosen with the harvest variables being the most important. Figure 7.2 in APPENDIX E shows the model’s output report format editor and Figure 7.3 shows an example of the harvest output report.
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