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Requirement Analysis of a System to Predict Crop Yield under Climate Change

기후변화에 따른 작물의 수량 예측을 위한 시스템 요구도 분석

  • Kim, Junhwan (Rice Research Division, National Institute of Crop Science, Rural Development Administration) ;
  • Lee, Chung Kuen (Planning and Coordination Division, National Institute of Crop Science, Rural Development Administration) ;
  • Kim, Hyunae (Department of Plant Science, College of Agriculture and Life Science, Seoul National University) ;
  • Lee, Byun Woo (Department of Plant Science, College of Agriculture and Life Science, Seoul National University) ;
  • Kim, Kwang Soo (Department of Plant Science, College of Agriculture and Life Science, Seoul National University)
  • 김준환 (농촌진흥청 국립식량과학원 답작과) ;
  • 이충근 (농촌진흥청 국립식량과학원 기획조정과) ;
  • 김현애 (서울대학교 농업생명과학대학 식물생산과학부) ;
  • 이변우 (서울대학교 농업생명과학대학 식물생산과학부) ;
  • 김광수 (서울대학교 농업생명과학대학 식물생산과학부)
  • Received : 2014.09.11
  • Accepted : 2014.11.25
  • Published : 2015.03.30

Abstract

Climate change caused by elevated greenhouse gases would affect crop production through different pathways in agricultural ecosystems. Because an agricultural ecosystem has complex interactions between societal and economical environment as well as organisms, climate, and soil, adaptation measures in response to climate change on a specific sector could cause undesirable impacts on other sectors inadvertently. An integrated system, which links individual models for components of agricultural ecosystems, would allow to take into account complex interactions existing in a given agricultural ecosystem under climate change and to derive proper adaptation measures in order to improve crop productivity. Most of models for agricultural ecosystems have been used in a separate sector, e.g., prediction of water resources or crop growth. Few of those models have been desiged to be connected to other models as a module of an integrated system. Threfore, it would be crucial to redesign and to refine individual models that have been used for simulation of individual sectors. To improve models for each sector in terms of accuracy and algorithm, it would also be needed to obtain crop growth data through construction of super-sites and satellite sites for long-term monitoring of agricultural ecosystems. It would be advantageous to design a model in a sector from abstraction and inheritance of a simple model, which would facilitate development of modules compatible to the integrated prediction system. Because agricultural production is influenced by social and economical sectors considerably, construction of an integreated system that simulates agricultural production as well as economical activities including trade and demand is merited for prediction of crop production under climate change.

온실가스 증가로 인한 기후변화는 농업 생태계에 다양한 경로로 영향을 미쳐 작물 생산에 영향을 미칠 수 있다. 또한, 농업 생태계는 생물, 기후, 토양 및 경제 환경이 서로 복잡하게 연결되어 있어 개별 분야에 초점을 맞춘 적응 대책들은 농업 부문 내 다른 영역에 의도하지 않은 파급 효과를 초래할 수 있다. 기후변화 조건에서 복잡한 농업 생태계의 상호작용을 고려하면서 최적의 작물 생산성을 유지하기 위해 개별분야별 모델을 연계한 통합 예측 시스템 구축이 요구된다. 이러한 통합시스템을 구축하기 위해서는 단계적 접근이 필요하다. 국내에서 사용되고 있는 모델들은 통합시스템에 적합하도록 설계된 것이 아니기 때문에, 이를 위한 모델의 재개발이 필요하다. 농업생태계 감시를 위한 수퍼사이트와 위성사이트의 구축을 통해 장기간 작물 생육 자료를 확보하고 이를 개별 분야 모델의 개선에 활용할 수 있다. 모델 대상의 추상화와 상속과정을 통해 보다 유연한 형태의 통합 모델의 모듈 개발이 가능할 것이다. 마지막으로, 농업분야는 사회경제적인 요인에 지대한 영향을 받기 때문에, 농업생산과 경제분야가 연계될 수 있는 통합 시스템 구축이 바람직 할 것 이다.

Keywords

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