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APSIM Initiative Strategic Plan

The APSIM Initiative Strategic Plan is now available.  The plan summarises the Mission and Vision of the APSIM Initiative whilst clearly outlining the purpose and objectives for APSIM. 

The APSIM Initiative welcomes feedback from our stakeholders.  It can be found at http://www.apsim.info/AboutUs/StrategicPlan.aspx

Wednesday, 5 September 2018/Author: Sarah Cleary/Number of views (32)/Comments (0)/
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APSIM Downloads for 17/18

 

For the 2017/18 year there were 2103 non-commercial licenced users registered (an 11% increase on the previous year). This resulted in some 3775 downloads of APSIM (all versions as some users download older versions or use multiple versions).

APSIM is being used in 116 countries around the world, around the same number as the previous year. In Australia there are 482 users (up from 462 the previous year), with 157 in Queensland, an increase of 51 users. In New Zealand there were 46 users.

Monday, 30 July 2018/Author: Sarah Cleary/Number of views (205)/Comments (0)/
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SILO Redevelopment

Are you aware that the SILO climate database has been redeveloped. The new system is now available for use. Some benefits of the new system:
• all datasets are now free of charge (supported by the Queensland Government’s Open Data initiative)
• data can now be distributed as they are licensed under the Creative Commons Attribution 4.0 licence
• users can now download gridded data (data are in NetCDF format). Please see the new web site for more information about accessing the gridded data.
• the new web interface is much easier to use than the old interface
• the new Application Programming Interface (API) enables users to query the amount of observed data available at each station
• patched point datasets are available at nearly all (18,700) stations (previously patched datasets were only available at a modest subset of the stations)

The APSIM SILO mirror based out of Toowoomba will stop working soon. You will need to switch the new SILO climate database as soon as possible.

You can find the SILO Getting Started Guide in the Technical documentation section of http://www.apsim.info/Documentation.aspx

Monday, 25 June 2018/Author: Sarah Cleary/Number of views (217)/Comments (0)/
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4th Annual ISU APSIM Training Course

Iowa State University Department of Agronomy is hosting the 4th Annual ISU APSIM Training Course - Evaluating Production and Environmental Performance of Cropping Systems with APSIM. There are 34 participants from 12 U.S. states with interest in soils, crops, and atmospheric sciences. Look for updates on Twitter with #ISUAPSIM2018.  

Tuesday, 12 June 2018/Author: Sarah Cleary/Number of views (315)/Comments (0)/
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APSIM Training

September 18-19, Brisbane

The next APSIM training course will be held at the Queensland Bioscience Precinct, St Lucia on the 18th and 19th of September.  Please send your EOI and/or any questions to apsim@csiro.au
Tuesday, 12 June 2018/Author: Sarah Cleary/Number of views (271)/Comments (0)/
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FEATURES

Predicting optimum crop designs using crop models and seasonal climate forecasts

Expected increases in food demand and the need to limit the incorporation of new lands into agriculture to curtail emissions, highlight the urgency to bridge productivity gaps, increase farmers profits and manage risks in dryland cropping. A way to bridge those gaps is to identify optimum combination of genetics (G), and agronomic managements (M) i.e. crop designs (GxM), for the prevailing and expected growing environment (E). Our understanding of crop stress physiology indicates that in hindsight, those optimum crop designs should be known, while the main problem is to predict relevant attributes of the E, at the time of sowing, so that optimum GxM combinations could be informed to farmers. In a recent article published in Nature’s Scientific Reports by UQ-QAAFI’s Farming Systems Research Group, A/Prof Daniel Rodriguez tested our capacity to inform that “hindsight”. The work involved linking the APSIM-sorghum model with a skilful seasonal climate forecasting system, to answer “What is the value of the skill in seasonal climate forecasting, to inform crop designs?” 

The article is open access and can be downloaded from http://rdcu.be/F7Yp.



Thursday, 22 February 2018/Author: Dean Holzworth/Number of views (615)/Comments (0)/
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Modelling forage yield and water productivity of continuous crop sequences in the Argentinian Pampas

The global area and farming systems to which APSIM can be applied with confidence to have recently expanded with a research article recently published in the European Journal of Agronomy. A validation analysis showed that APSIM was able to accurately simulate the forage yield and water productivity of a range of forage crops and also continuous forage crop rotations across the Argentinian Pampas. Forage crops that the model was tested for includes maize, soybean, wheat, oats, annual ryegrass and barley. Water productivity was simulated with a greater accuracy when considering the whole crop rotation rather than individual crops. Crop forage yield simulated with greater accuracy for crops harvest without regrown compared to crops harvested frequently and allowed to regrowth.

For further details see the new paper titled ‘Modelling forage yield and water productivity of continuous crop sequences in the Argentinian Pampas’ published in European Journal of Agronomy at https://doi.org/10.1016/j.eja.2017.10.004.

Monday, 5 February 2018/Author: Dean Holzworth/Number of views (1305)/Comments (0)/
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APSIM features in international intercomparison of simulation models for grassland and crop yield and N2O emissions

In a paper recently accepted for publication in Global Change Biology (published open access), APSIM has contributed to an assessment of the ability of simulation models to simultaneously predict yield and N2O emissions.  The study included five variants of APSIM (two in the crop part of the study and three in the grasslands part).  In this study the modellers started with little site information (soil properties, weather data, management information) as Stage 1 and incrementally more data was supplied until in Stage 5 modellers had all available data.  Crop model outputs improved at Stage 3 when phenology information was made available but grassland model outputs were little affected by the availability of additional information.  As with other intercomparisons, the ensemble median performed better than any one model when considering multiple sites.  It was found that a small ensemble of three models outperformed the full ensemble.  This is the first study which has examined the effect of data availability of the performance of an ensemble and also the first examining both yield and N2O emissions.

Thursday, 9 November 2017/Author: Dean Holzworth/Number of views (1798)/Comments (0)/
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