APSIM at Plant & Food Research Joanna Sharp

Generic Crop Template - History 26 released models use generic crop template (cereals, legumes, vines, trees, weeds, vegetables, pastures)

History Generic Crop Model problems Inflexible model structure Programming skills needed to make changes Solution Next generation generic crop model Exploits modern software systems (.Net) Allows flexible approaches to model structure Without needing to write code

Contributors Dean Holzworth - CSIRO Neil Huth - CSIRO Robert Zyskowski – Plant and Food Research Edmar Teixeira – Plant and Food Research John Hargreaves - CSIRO Derrick Moot – Lincoln University (New Zealand)

Plant Modeling Framework

Current status and future Applied to a number of crops Broccoli, Carrot, Field Pea, French Bean, Fodder Beet, Grapes, Kale, Lucerne, Oat, Oil Palm, Potato Ongoing APSIM plant model development Plant model for APSIMX Existing crop models to be implemented into PMF New crop models to be build in PMF Upcoming publication Brown et al (in press). Plant Modelling Framework: Software for building and running crop models on the APSIM platform. Environmental Modelling and Simulation

Grapevine modelling in APSIM Developing the model (new crop model in APSIM) Current focus on phenology Phenology: Dormancy Budding Shoot growth Flower development Berry Development Senescence Budburst Flowering Veraison Leaf fall

Define start of development clock Budburst Experimental and simulation approach to define Chill Units + Thermal time Define start of development clock Subsequent phenology based on thermal time

Irrigation Use Efficiency Testing SoilWat Variable rate irrigation & spatial management Hydrophobicity Residues & mulches

Testing and improving soil C & N mineralisation Here are the experimental and modelled results for carbon mineralisation at field capacity under the range of temperatures. APSIM greatly underestimates mineralisation at all temperatures. Highlighting the 35 degrees data and model outputs (red lines) – at DUL or field capacity and at 35 degrees this is maximum mineralisation, so regardless of whether the temperature and moisture response functions are correct or not, the model should approximate the experimental data. Carbon mineralisation in the data is over 3 times that simulated by APSIM. NOTE error bars are standard deviation, they are all present but some are too small to see NOTE value for DUL was determined experimentally for this soil

Spatial assessment of climate change impact & adaptation Total maize silage biomass Production system: - High WHC soil Irrigated Adaptation: Sowing dates Maize Hybrid kg/ha Running APSIM spatially using NIWA’s virtual weather for current climate and different climate scenarios Setting up different levels of autonomous adaptation “modeled” by APSIM (change sowing date and genotype in this case) Baseline (1970 -2000) Climate Change A2 (2070-2099)

Sensitivity analysis on crop rotations Impact on Nitrogen Leaching (Lincoln – preliminary only) Kale Winter Forage Field peas 3 4 5 1 2 Preliminary results to illustrate only (work under way now). Aim is to quantify the importance (% of total variation) of each cropping system component for different impact variables. Winter Wheat Winter Forage Barley

Using APSIM to test another model (OVERSEER®) Phase I Phase II Phase III APSIM evaluation Long –term simulations APSIM vs. OVERSEER® N balance: APSIM vs. 2-3 year rotation treatment data N balance: Phase I treatments with 30 years of weather data N balance: Compare models & identify areas for improvement in OVERSEER®

Team