alexa Evaluation of Variation and Uncertainty in the Potential Yield of Soybeans in South Korea Using Multi-model Ensemble Climate Change Scenarios
ISSN: 2168-9881

Agrotechnology
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Research Article

Evaluation of Variation and Uncertainty in the Potential Yield of Soybeans in South Korea Using Multi-model Ensemble Climate Change Scenarios

Chung U1*, Kim YU2, Seo BS2 and Seo MC3

1Climate Application Department, APEC Climate Center, Busan 48059, Republic of Korea

2Department of Plant Science, College of Agriculture and Life Science, Seoul National University, Seoul 08826, Republic of Korea

3Crop Production and Physiology Research Division, National Institute of Crop Science, Rural Development Administration, Jeonju 55365, Republic of Korea

*Corresponding Author:
Chung U
Climate Application Department, APEC Climate Center
Busan 48059, Republic of Korea
Tel: +82-51-745-3971
E-mail: [email protected]

Received date: July 17, 2017; Accepted date: July 25, 2017; Published date: August 01, 2017

Citation: Chung U, Kim YU, Seo BS, Seo MC (2017) Evaluation of Variation and Uncertainty in the Potential Yield of Soybeans in South Korea Using Multi-model Ensemble Climate Change Scenarios. Agrotechnology 6:158. doi: 10.4172/2168-9881.1000158

Copyright: © 2017 Chung U, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Recently, information provided by various Global Climate Models (GCMs) has been applied to various research fields. A Multi-model Ensemble (MME) approach, which assesses the impact of climate change on agricultural crop production using one or more climate datasets from GCMs, has been widely used. We estimated the changes in soybean potential yield at 16 sites using the climate change scenarios, and then predicted the relative change in predicted potential yield for each single GCM, producing an observation climate-based simulated potential yield. Lastly, we assessed the degree of uncertainty for changes in potential yield predicted from MME approach.

In the results, although there were differences in the values themselves, the Standard Deviations (SD) of predicted soybean potential yield for each individual GCM were not significantly different from the SD of observation climate-based simulated potential yield, and there were no correlations between the predicted soybean potential yield for each individual GCMs and observation climate-based simulated potential yield in most sites. The estimation error decreased as the number of participating GCMs in the MME increased, but it did not decrease to zero. The means, but not the variance, of the MME of potential yield of soybean was similar to that of the observation climatebased simulated potential yield. The relative changes for predicted soybean potential yield for individual GCMs values of the Representative Concentration Pathways 4.5 and 8.5 scenarios increased in the northern regions of South Korea, such as Chuncheon and Hongcheon. In contrast, differences between them were not significant in most southwestern regions.

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