연구보고서
- 저자
- 정유란 박사
- 작성일
- 2016.03.14
- 조회
- 268
- 요약
- 목차
There are three steps to conduct an impact assessment on agricultural productivity and vulnerability to climate change. First, the analysis of climate resources in the region should be prioritized in order to understand the plant responses to extreme weather events. Second, the response of crops to climate resources and climate change should be reflected in the crop simulation model. Third, the impact crop responses to future climate change should be evaluated by combining future climate scenarios and crop models, which simulate response results such as genetic parameters or soil parameters during extreme climate events. In this study, we analyzed the changes in heading times and yield components for previous winter barley growing seasons; calculated the duration and frequency of barley’s growth limit temperature during overwintering events within the observed period; and calculated the historical and future periods of future climate scenarios for individual GCMs (Global Climate Models). The resulting frequency and duration information was coupled with a map presenting the areas that are able to safely cultivate barley. Then, we evaluated the changes of heading time and yield potential of barley simulated by multi-model ensemble approach of future climate scenarios. Changes in flowering time and uncertainty of climate change were evaluated in major fruit crop growing areas by simulating fruit crop flowering days through the prediction model.
The research results showed that in Daegu, the daily minimum temperatures had a higher impact than the daily maximum temperature on the heading time during the first half period of barley’s growing season. High temperature during overwintering had larger impacts on the development of growth than minimum temperature. We anticipated that this would be the case because the daily maximum temperature influenced a change in heading time during the early growing season in Jinju and Naju. In the case of changes in yield, the daily minimum temperature had a larger effect than the daily maximum temperature during the second half of growing season in Daegu, Jinju, and Naju. On the other hand, in Suwon, the daily maximum temperature affected changed on the winter barley yield during the second half of the growing season. Iksan presented different results. In four regions, with the exception of Iksan, yield decreased when daily temperature increased. In Iksan, yield increased when daily temperature increased during the second half of growing season. Overall, the range of responses of the heading time to the daily maximum and minimum temperature during the first half of the growing season was changed in 4°C range. During the second half of the growing season, there was a 2°C temperature range of response to change in yield during the second half of the growing season. It is worthy to note that the cold exposure duration decreased due to the effects of climate change in the areas that grow the most barley.
Crop Environment Resource Synthesis-Barley (CERES—Barley) was simulated under the observed climate, and the historical and future periods of GCM’s future climate scenarios. In the crop model’s simulation results, the anthesis date has been shortened under future climate scenarios of Representative Concentration Pathway (RCP) 4.5 and RCP8.5 on CO2 emissions, despite the condition of an unchanged sowing date. Increasing effects of winter barley yield in the RCP8.5 scenario were more present than in the RCP4.5 scenario in the areas that grow the most winter barley. However, in Jangheung and Haenam, there was a projected decrease in winter barley yields in both the RCP4.5 and RCP8.5 scenarios.
The assessment results indicated that the chill-dormancy clock model produced more reliable flowering day forecasts than the growth development model. Under the RCP4.5 CO2 scenario, the results of the ratio of change on flowering time were as follows: grape > peach > pear > apple, in that order. The grape’s ratio of change on flowering time was expected to be the highest amongst the four fruit crops while apple’s ratio of change was expected to be low. Under the RCP8.5 CO2 scenario, the results of the ratio of change on flowering time were as follows: apple > pear > grape > peach, in that order. The apple’s ratio of change on flowering time increased sharply while the peach’s ratio of change was expected to be low. This was the opposite of RCP4.5’s results. In conclusion, the apple is expected to have the greatest change in flowering time between the four fruit crops, due to climate change impacts.