Crop Modeling Team


Ken Boote, University of Florida
Peter Thorburn, Commonwealth Scientific and Industrial Research Organisation


The Crop Modeling Team has the responsibility of coordinating the evaluation, intercomparison and improvement of crop models prior to using the crop models for climate change assessment and adaptation to climate change. They are coordinating team efforts to calibrate crop models at both site-specific and regional levels, so the models will give more reliable predictions under baseline and future climate scenarios. These model predictions will be input into economic models to study and meet the AgMIP goal of enhancing world food security and adaptation capacity in both developing and developed countries. Crop modelers, plant scientists, and soil scientists are invited to participate in these activities.

The goals of Crop Modelers in AgMIP include:
1. Intercomparing multiple crop models to each other, for their variability (uncertainty) of response to climate factors of temperature, CO2, and rainfall, as well as management inputs,
2. Testing multiple crop models against observed response data on temperature, CO2, water availability, and management inputs,
3. Improving code and relationships of crop models at process-level to give more accurate responses to climatic, management, and genetic factors,
4. Calibrating and using crop models with climate and economic modelers to assess impact of climate scenarios on crop production and food security for regions,
5. Developing methodologies for simulating climate impacts on agriculture for regions with low soil fertility, low inputs, and low water availability,
6. Developing and using methodologies for scaling up and aggregating crop model outputs for regions,
7. Applying crop models to evaluate adaptations to minimize impacts and take advantage of climate change scenarios.

Toward the first three objectives, there are teams of crop modelers for specific crops, starting with wheat, maize, rice, and sugarcane, and following with new teams for potato, sorghum-millet, peanut (groundnut), and soybean. A maize model improvement group has been formed. These teams are initially working as crop-specific teams to intercompare their models for hypothetical response to CO2, temperature, rainfall, and management factors at four sentinel sites representing variation in productivity. Most of the crop teams will make a transition from uncertainty analyses to model testing and improvement, and will collaborate with experimentalists to test the models against experimental data on response to temperature, CO2, and water deficit.

Please click on the appropriate crop pilot to learn more about the leaders, team members, crop models used, and activities. Click here for a pdf of the full crop modeling protocols.

For additional information and preliminary intercomparisons, see the crop modeling highlights pdf (Applying multiple crop models for assessing climate change impact). Preliminary tests of model sensitivity to temperature are available for three maize models in Brazil and three rice models in India. Those were test cases conducted at various Workshops and show that the models vary in response to rising temperature, although the general conclusion is for shorter life cycles and yield decline with temperature rise at those sites. Crop model predictions for regions will require aggregation in various ways: See the pdf prediction of district-level groundnut yields for Anantapur,

Calibration of crop models for sites and for regions will be conducted in the regions, by modelers working very closely with regional data specialists (agronomists, soil scientists, plant scientists, etc.) who know the management and growth environment for those regions. Regional data inputs include weather, soils, management, and cultivar characterization. Issues at this step range from site-specific calibration at relatively limited sites, to calibration against regional yields, which will require consideration for aggregation methodology as well as yield-gap factors.

Crop model simulations for baseline and future climate scenarios for given regions are conducted by crop modelers in collaboration with climate scientists. Issues of aggregation are important.

Crop modeling teams develop and evaluate adaptation and mitigation strategies under future climate. Adaptations include crop management as well as genetic improvement.

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