Crop Modeling and Impacts on Rice
Agro-meteorology Institute, Chinese Academy of Agricultural Sciences, Beijing 100081
Good afternoon, Ladies and gentlemen. Welcome to our institute and attend the workshop.
My presentation’s title is the crop modeling and impacts on rice
It constitutes of three parts:1. Introduction
2. Materials and Method
3. Results and discussion.
Why do we choose rice as our main research item? Because there are such reasons, that is
1. Rice is the second most important crop in China after wheat, is the main item of the diet, however, to meet the demands of rapidly expanding population, a notable increase in rice production is required over the coming decades.
2. The yields in some places are already approaching the ceiling, in some of the more productive farmers’ fields, especially in the south and southeast China, the yields are already approaching the ceiling of average yields obtained on experimental stations. There are very difficult to increase the yields through optimizing the planting management.
3. The likely impacts of climate change on rice production, in former research, we get the conclusion that the climate change will go against the rice production, this conclusion is drawn based on the assumption that CO2 haven’t effect on rice yield. With the development of the simulation technology, we added the CO2 effect into the simulation, then got the new conclusion that climate change will benefit the rice production, especially in southwest China.
So we chose rice as our considered item for assessment research.
For this project, except the formal results will be got, such as the yield change map of whole China, the relevant interpret of the yield change, and so on. The following items will be fulfilled as well, these items will reflect the advance of the research and improve the research capacity.
1. To provide climate change scenarios for China, based on selected IPCC SRES emission scenarios for the 2020s, 2050s and 2080s.
2. To provide socioeconomic scenarios for China relevant to agriculture, for the 2020s and 2050s.
4. To provide an overview of the overall effects of climate change on agriculture in China, including economic costs of damages and /or adaptation.
Materials and Method
The materials in this research included Climate Change Scenarios, China digital map, land use map of present and future, FAO soil data, Crop Variety and Planting details database and so on. The most important materials that can embody the progress of assessment are the new Climate Change Scenarios, the regional crop model and using the GIS technology in simulation.
1. Climate Change Scenarios:
In total, the impact of 7 different climate change scenarios were evaluated, which are baseline, 2025, 2050 and 2080 under two emission scenarios (typically A2 and B2 SRES). All the scenarios are predicted by the Hadley Centre RCM-PRECIS (Providing Regional Climates for Impacts Studies). The resolution of the Regional GCMs is 50*50KM. Simulation period: 1961-1990, 2071-2100. For the period of 2011-2040, 2041-2071, can be get from pattern scaling. For climate scenarios over China, Hadley Centre RCM system: PRECIS is to be set up over China region, which has horizontal resolution of 50KM with 19 levels in the atmosphere (from surface to 30km in the stratosphere). The climate simulation for baseline and climate scenarios under different emission scenarios would be performed for climate scenarios.
2. China Digital Map:
The scale of China boundary map is 1:100million. Which will be used as the background for the later use.
3. Grid Polygon:
The resolution of the grid is 50km*50km, which divide whole China into 3000 to 4000 cells, each cell will be regard as a unit, for each cell the simulation will be run one time for per year.
4. Land Use Map:
The land use of current and future, the land use map will reflect the development of the agriculture, it will be act as a mask to delete the cells which can not be use as a rice filed, which can decrease the quantity of the simulation and increase the work effciency.
5. FAO Soil Map:
As the soil data, we will use our own soil data that retrieved from the soil survey books. And we use the FAO soil data the adjust the soil attributes in each cell. The soil attributes is for the crop model running, it is the weighted average of map unit and soil unit in the FAO soil. Based on the FAO soil data, we will use the soil model to adjust the soil organic carbon. That is to say the simulation will take the soil change under the climate change into account.
6. Crop Variety and Planting Details database
According to each cell, we will distribute its regional crop variety and planting details. We have established the crop variety database which can be used for the selection. The planting details include sowing date, transplanting date, and fertilizer application, and so on. The planting detail will embody the socioeconomic development.
Regional Crop Model:
Aim at this project, which the help of cranfield university, we developed a regional crop model, which can dispose the polygon file and run regional simulation. In fact, it is based on the CERES-rice, For the CERES-Rice’s widespread use and validation, we chose it as the model core, above the CERES we built a shell over it, the shell is for reading polygon input files, writing output files, running CERES model repeatedly based on the polygon definition.
First , we input the input files, which include soil polygon file, crop variety polygon file and socioeconomic polygon, all the input files will be tabular or excel format, which is the output format of ARCGIS, and input the climate scenarios files. As soon as prepare all the input files, just press the run button, the model will run repeatedly. The result of every cell will be got into the output file, biomass output file, water output file and growth output file. Use the output files, a series of map will be retrieved.
Firstly: using the grid polygon mask, we get the cell partition of whole China,
Secondly: using the land use map, the arable cells will be extracted. The criteria for extraction is percentage of arable area in cell is great than 10% or something else.
Thirdly: using FAO soil data, get the soil attribute for each cell, at the moment, the soil data also can be used as a mask to delete the no-arable cells, the criteria is percentage of area of arable soil unit is greater 5% or something else.
Furthermore: using the climate scenarios, soil attributes and variety and planting details as the input, running the crop model. Get the results of yield change.
The Flowchart of the Process.
Of course, in order getting the fine results, a validation will be useful, we will use the field experiments data to feedback the results
Because of the schedule, we can not get the regional climate change scenarios at this moment, so we use the GCMs model scenarios as the climate change scenarios for this workshop, for the GCMs’ low resolution, it has only 51 sites all over China boundary, as for rice planting, it only has about 20 sites, so using it we got the coarse results for rice yield change.
The upper map is the site yield change map, it is just for single rice, the yield change is a little bit complicated all over china, but there is a sign that the yield will increase in north China if the irrigation is available.
The bottom map is the upscaling result, we use the province as a unit, so got the weighted average yield change map.
The conclusion can be summarize to:
1. If not take the CO2 effect into the account, the yield in most of places will decrease, especially in north China.
2. If take the CO2 effect into the account, the yield in most of places will increase, especially in southwest China.
3. Irrigation will be the most effective way to compensate the cost of climate change, additionally, the adjustment of planting location will be beneficial under the climate change.
For the anticipated results, this map will be the eventual results. But this one is only used a same climate change file for each cell, it only can embodies the soil attributes.
Progress of work
The works we have finished and carrying out now are:
The regional crop model for rice, wheat and maize.
FAO Soil data; Got thve weighted average of soil attribute for each cell.
Crop variety and planting details database; Distributing each cell its crop variety and planting details that can embody the socioeconomic scenarios.
The works we will carry out in coming future are:
The 7 climate scenarios for China
Compiling and interpreting the results.
This is just a blueprint of the work, it should have some complements in the process of research, any advices will be appreciated, I thank in advance.
Watching Slides: http://www.ami.ac.cn/Sino_UK/workshop/Xiong_presentation.ppt