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|Title:||Optimising Agronomic Options At The Farm Scale|
|Series/Report no.:||Program 1|
|Abstract:||Strategic planning and policy development for environmentally sustainable and economically viable management options for the rice based farming systems require the assessment of management options using mathematical models which integrate our understanding of water and salt movement with economic considerations at both the farm and regional scales. This project also had strong links with LWRRDC/MIL/CSIRO project on optimising irrigation intensities in the Murray Valley. During this project a standalone farm scale hydrological economic model SWAGMAN Farm (Salt Water and Groundwater MANagement) was developed and customised for situations in the Coleambally and Murray Irrigation Areas. The model processes were developed and refined by using feed back from irrigation managers, regulators and community groups. The following major achievements have been made: · Collection of crop, soil, irrigation, climatic and economic data sets for fourteen farms in the Murray Irrigation Districts · Rigorous validation of model processes by applying the model to fourteen farms with a range of enterprise, soil and groundwater conditions. · Development of simulation and optimisation modes in SWAGMAN Farm to assess environmental and economic impacts of existing and optimal cropping patterns · Various improvements of water and salt balance processes to suit conditions in the Murray Districts and the Coleambally Irrigation Area · Incorporation of soil water content accounting which provides flexibility in the representation of various starting soil profile water content conditions, water availability to crops and rational computation of recharge and watertable rise during the cropping and fallow periods · Development of a Windows based GAMS independent version of SWAGMAN Farm. GAMS (General Algebraic Modelling System) was an expensive software platform for the previous version with inflexible licence requirements. The new version written in C++ language uses Microsoft Access databases and will be linked with a GIS interface in near future. These sensitivity runs and model developments gained the confidence of members of the steering committee who provided vital inputs throughout this project. While considerable progress was made, they see the need for the work to continue to the stage where it can be applied to assist strategic planning and policy development, taking into account local regional conditions. Parallel to the modelling project an intensive paddock water monitoring project titled “Rigorously determined water balance benchmarks for irrigated crops and pasture’ was also initiated by the steering committee with the assistance of CSIRO, MIL, NSW Agriculture and LWRRDC. The purpose of the monitoring project was to further customise SWAGMAN Farm to local conditions and to validate the model results with the field data. Since monitoring projects take significant time in setting up and calibrating equipment, data analysis has only recently started, however initial comparisons of model results with the field results suggest that the improved SWAGMAN Farm can reasonably simulate field situations. However this work needs to continue to maximise the benefits of the paddock water balance monitoring. However, due to the wide range of groundwater, enterprise and soil conditions in the irrigation areas, SWAGMAN Farm needs to be applied to every farm to develop soundly based policy options. The need for application to individual farms is further driven by the complex regional groundwater interactions causing reversal (downward to upward and local discharge zones) of leakage rates in parts of the irrigation areas e.g. Murray Valley. This project has demonstrated that it is possible to develop methodology which helps assess optimal irrigation intensity within a multitude of biophysical and socio-economic constraints. The methods developed have scientific validity in capturing and representing key processes, and have community acceptance as a way of examining options that are important to them.|
|Appears in Collections:||Research Papers|
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