Change on the Agricultural Sector 4
3. Analysis of the Impacts of Adaptation Measures on Agricultural Production 14on Agricultural Production14
14 The simulation analysis using ORYZA2000 is an abstract of main results of the research commissioned to Dr. C. G. Lee (National Institute of Crop Science, RDA).
3.1. Background of Analysis of the Impacts of Adaptation Measures
Increases in CO2 concentration and the subsequent global warming can have both positive and negative impacts on crop growth. In order to mitigate negative impacts of climate change, the farm households will have to utilize adaptation measures. For this reason, and in order to understand how adaptation measures affect crop growth, a simulation analysis is required.
In this section, the impacts of adaptation measures on the rice yield are analyzed including the changes in rice growth, the nitrogenous content of each unit of farm household, irrigation, and cultivation time by temperature and CO2 concentration. For this, the change in annual potential productivity of each rice ecotype and the growth model in each year caused by climate change (temperature and CO2) is analyzed.
Following this the annual rice productivity, taking into consideration the adaptation measures (control of the nitrogenous fertilizer level and the amount of irrigation) in each year is estimated.
This crop growth simulation provides basic data for analyzing the expected economic utility used when measuring the extent of individual farm household’s application of climate change adaptation measures and the effectiveness of those measures.
3.2. Analysis Models
To analyze the impacts of climate change adaptation measures,
“ORYZA2000” is used, which is the rice growth model developed jointly by International Rice Research Institute (IRRI) and by International Rice Research Institute and Wageningen University of Netherlands in 2000. The environment for the rice growth model in ORYZA2000 is characterized by the following three conditions: First is the potential
productivity condition: meteorological data such as light, temperature and CO2 and the variety characteristics (cultivars) for growth type and physiological process determine the growth of crop. Second is the accessible productivity condition. Accessible growth is determined by limiting factors on potential productivity, such as moisture and nutrient availability. Third is the actual productivity condition, for in reality growth is further reduced by additional restraining factors such as weeds and pests. At present, ORYZA2000 simulates the growth model under the potential productivity condition or the accessible productivity condition in which nitrogenous fertilizer level and moisture are limited, on the assumption that the additional restraining factors such as weeds and pests are completely controlled.
The rice growth simulation in ORYZA2000 requires meteorological data such as sunlight, the lowest and the highest temperatures, and precipitation as well as cultivar parameters such as development rate, rate of distribution of assimilation product to each organ, the speed of assimilation product’s travelling during the ripening period, and the specific leaf area (SLA). In this study, the cultivar parameters of the early-maturing variety Odaebyeo, the medium-maturing variety Hwaseongbyeo, and the medium/late-maturing variety Ilpoombyeo, are applied for simulating the growth model of each rice ecotype.
3.3. Analysis Data
For simulating the rice growth model according to the climate change scenario, 56 areas were selected from those where a meteorological station or observatory was located and whose average annual data had been built up over the past 30 years. Island areas and the areas where rice cultivation was impossible were excluded. All the areas selected for simulating the potential productivity according to the climate change scenario were used, of which 17 areas were used for the growth
modeling taking into consideration adaptation measures (nitrogenous fertilizer level and irrigation control) under the climate change conditions.
The 17 areas were Cheolwon, Chuncheon, Gangneung, Suwon, Cheongju, Daejon, Andong, Daegu, Jeonju, Gwangju, Jinju, Jecheon, Cheonan, Imsil, Haenam, Yeongnam, and Milyang, which represented the agricultural zones (Central, Honam, Yeongnam, etc.) of the different altitudes in Korea.
For simulating the rice growth model according to the climate change scenario, meteorological data was produced. The growth model was simulated using the meteorological data for the average annual yield over several 30 year periods: 1971~2000 (base years), 2011~2040, 2041~2070, and 2071~2100. As for climate change scenario itself, A1B scenario of IPCC was applied. From the climate change scenario data provided by KMA, data on the highest and lowest temperatures and precipitation applicable to the growth model was created. In addition the carbon dioxide concentration for the years of the growth model was decided using the data from the IPCC climate change scenario.
The distribution of average annual temperature and precipitation (average of 56 areas) over the years simulated by the growth model shows that the highest and lowest temperature, precipitation, and CO2
concentration are all increasing as global warming progresses, in comparison to the base years (1971~2000). According to A1B climate change scenario, the planet-wide global temperature rise for the coming 100 years is 2.8℃. In this study, however, the highest temperature and the lowest temperature are estimated to rise by 4.0% and 4.4℃
respectively. Therefore, global warming in Korea is expected to be much more severe than the planet-wide global warming <Table 4-8>.
CO2 concentration in 2071~2100 is estimated to be 661ppm, which is twice the concentration (345ppm) in the base years <Table 4-9>.
Table 4-8. Average annual temperature and precipitation for the years in the growth model
Meteorological factors
Year of growth model Deviation from 1971-2000 1971~2000 2011~2040 2041~2070 2071~2100 2011~2040 2041~2070 2071~2100 Highest temp.
(℃) 17.9 19.0 20.4 22.0 1.1 2.5 4.0
Lowest temp.
(℃) 7.3 8.5 10.1 11.7 1.2 2.8 4.4
Precipitation
(mm) 1,286 1,367 1,518 1,557 82 232 271
Note: Average annual temperature and precipitation is the average value of 56 areas.
Table 4-9. CO2 concentration according to the climate change scenario (A1B)
Unit: ppm
Years ISAMS BERN Average
1971-2000 346 345 345
2011-2040 438 434 436
2041-2070 552 542 547
2041-2100 666 655 661
Note: ISAMS and BERN are types of Carbon Cycle Model (CCM).
3.4. Analysis Results
3.4.1. Change in the productivity of each rice ecotype and growth model, for each model period
To analyze the change in productivity of each rice ecotype and growth model by temperature for each model period (30 years), the temperature of each period of the growth model for the climate change scenario and the CO2 concentration of the base year were applied. The result shows that the productivities of early-maturing, medium-maturing,
and medium/late-maturing varieties were all reduced as global warming progresses, relatively worse in the northern areas and for medium/late- maturing variety. <Table 4-10 and Appendix Table A4>.
To analyze the change in productivity of each rice ecotype and growth model by CO2 concentration for each model period (30 years), the temperature of the base year and the CO2 concentration of each period of the growth model for the climate change scenario were applied. The result shows that the productivity increased regardless of rice ecotypes, with much more increase in medium/late-maturing variety than in early-maturing and medium-maturing varieties <Appendix Table A5>.
A temperature rise results in a decrease in rice productivity, while a rise in CO2 concentration results in an increase in rice productivity.
For each temperature rise of 1℃, the rice productivity per ha is estimated to decrease by an average of 292kg: 178kg for early-maturing variety, 304kg for medium- maturing variety, and 395kg for medium/late- maturing variety. For CO2 concentration increase of each 100ppm, the rice productivity per ha is to increase by an average of 231kg: 201kg for early-maturing variety, 254kg for medium- maturing variety, and 238kg for medium/late-maturing variety.
When temperature and CO2 concentration from the climate change scenario for each period (30 years) of the growth model are applied simultaneously, the productivity of early-maturing variety appears to increase slightly; that of medium-maturing variety decreases a little;
and that of medium/late-maturing variety decreases significantly. In general, the southern areas experience a greater decrease in the productivity due to global warming than the northern areas do. This is because the southern regions are not suitable for cultivating the early- maturing variety, its productivity at the base year is relatively low and thus the decrease is relatively large. In addition, as the growth period of medium/ late-maturing variety is relatively long and most regions in Korea are suitable for its cultivation, the decrease in productivity by
Table 4-10. Change in the productivity of each rice ecotype and
Average temperature (℃) 1.1 2.6 4.2 2.7 2.7
CO2 concentration (ppm) 91 202 316 203 203
Rice
ng variety -556 -1,012 -1,222 -930 Temperature fixed,
variety 312 486 570 456 415
Temperature fixed, CO2 change
Medium/late-maturing variety 321 435 457 404 Temperature &
CO2 change
Early-maturing
variety 31 13 88 44
Temperature &
CO2 change
Medium-maturing
variety -53 -124 -144 -107 -183
Temperature &
CO2 change
Medium/late-maturing variety -219 -513 -729 -487
Change in rice productivity by the change in unit temperature
(kg/ha/1℃)
Early-maturing
variety -211 -179 -143 -178
Medium-maturing
variety -382 -299 -231 -304 -292
Medium/late-maturing variety -506 -389 -291 -395
Change in rice productivity by the change in unit CO2 concentration
(kg/ha/100CO2 ppm)
Early-maturing
variety 238 184 179 201
Medium-maturing
variety 342 241 180 254 231
Medium/late-maturing variety 353 216 145 238
Note: For the period of 1971∼2000, average temperature was 12.6℃; CO2 con-centration 345ppm; the productivity of each ecotype 4,752kg/ha for early- maturing variety, 4,777 kg/ha for medium-maturing variety, and 5,180kg/
ha for medium/late-maturing variety.
global warming is greater than early-maturing and medium-maturing varieties.
3.4.2. Estimation of the rice productivity in consideration of adaptation measures
For growth modeling in consideration of adaptation measures against climate change (nitrogenous fertilizer level and irrigation control), 17 representative areas were selected. For adaptation measures, nitrogenous fertilizer levels (0, 30, 60, 90, 120, 150, 180, 210kg/ha) and irrigation days (0, 3, 6, 9, 12, 15, 30, 200 days) were set. The number of irrigation days referred to the number of days when dried rice field was irrigated, and the amount of irrigation each time was 75mm.
When the cultivation period was fixed regardless of rice ecotype, nitrogenous fertilizer level and irrigation control, the rice productivity appeared to rather increase in the order of early-maturing, medium- maturing, and medium/late- maturing varieties <Appendix Table A6>.
For each ecotype, the early-maturing variety did not show a significant decrease in rice productivity by the fixed cultivation period but showed a large increase by the shifted cultivation period for each period of the growth model. For the medium/late-maturing variety, the rice productivity decreased significantly by the fixed cultivation period, but in comparison to other ecotypes, it decreased less by the shifted cultivation period for each period of the growth model. The medium-maturing variety showed an in-between trend of early-maturing and medium/late-maturing varieties. It appeared that when the cultivation period was fixed, the ripening period temperature rose significantly along with global warming.
This will cause the rice to ripen poorly and thus result in reduced productivity, when compared to the model in which the cultivation period is altered, for each period of the ORYZA2000 growth model
<Appendix Table A7 and Table A8>.
Analysis of the impacts of nitrogenous fertilizer level and irrigation
control on the rice productivity shows that the nitrogenous absorption by plants and the rice productivity tended to increase as the nitrogenous fertilizer level went up, regardless of rice ecotype and period of the growth model but conversely it decreased when the nitrogenous fertilizer level exceeded 180kg per ha. In fact, most rice varieties cultivated in Korea still produce less when the nitrogenous fertilizer level was 150~
180kg because of pests and mutual shading. In order to reflect this phenomenon, the rice productivity in our model was set using the nitrogenous nutrient index, to decrease when the nitrogenous fertilizer level reaches a certain limit (180kg/ha) or beyond. It appeared that regardless of rice ecotype and period of the growth model, irrigation requirements increased and the rice productivity also increased as the period of irrigation to the dried rice field shortened.
In comparison to the days or the amount of irrigation, the nitrogenous fertilizer level appeared to have more impact on rice productivity. As Korea experience substantial precipitation during the rice cultivation period and most farm households in Korea have good irrigation facilities, the impact of irrigation does not seem to be large.