Korean Journal of Agricultural and Forest Meteorology (한국농림기상학회지)

Korean Society of Agricultural and Forest Meteorology (한국농림기상학회)
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A Comparison between Simulation Results of DSSAT CROPGRO-SOYBEAN at US Cornbelt using Different Gridded Weather Forecast Data

격자기상예보자료 종류에 따른 미국 콘벨트 지역 DSSAT CROPGRO-SOYBEAN 모형 구동 결과 비교

  • Yoo, Byoung Hyun (Department of Agriculture, Forestry and Bioresources, Seoul National University) ;
  • Kim, Kwang Soo (Department of Agriculture, Forestry and Bioresources, Seoul National University) ;
  • Hur, Jina (National institute of Agricultural sciences, RDA) ;
  • Song, Chan-Yeong (Division of Earth Environment, Pusan National University) ;
  • Ahn, Joong-Bae (Division of Earth Environment, Pusan National University)
  • 유병현 (서울대학교 농림생물자원학부) ;
  • 김광수 (서울대학교 농림생물자원학부) ;
  • 허지나 (국립농업과학원) ;
  • 송찬영 (부산대학교 지구환경시스템학부) ;
  • 안중배 (부산대학교 지구환경시스템학부)
  • Received : 2022.03.17
  • Accepted : 2022.09.27
  • Published : 2022.09.30
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Abstract

Uncertainties in weather forecasts would affect the reliability of yield prediction using crop models. The objective of this study was to compare uncertainty in crop yield prediction caused by the use of the weather forecast data. Daily weather data were produced at 10 km spatial resolution using W eather Research and Forecasting (W RF) model. The nearest neighbor method was used to downscale these data at the resolution of 5 km (W RF5K). Parameter-elevation Regressions on Independent Slopes Model (PRISM) was also applied to the WRF data to produce the weather data at the same resolution. W RF5K and PRISM data were used as inputs to the CROPGRO-SOYBEAN model to predict crop yield. The uncertainties of the gridded data were analyzed using cumulative growing degree days (CGDD) and cumulative solar radiation (CSRAD) during the soybean growing seasons for the crop of interest. The degree of agreement (DOA) statistics including structural similarity index were determined for the crop model outputs. Our results indicated that the DOA statistics for CGDD were correlated with that for the maturity dates predicted using WRF5K and PRISM data. Yield forecasts had small values of the DOA statistics when large spatial disagreement occured between maturity dates predicted using WRF5K and PRISM. These results suggest that the spatial uncertainties in temperature data would affect the reliability of the phenology and, as a result, yield predictions at a greater degree than those in solar radiation data. This merits further studies to assess the uncertainties of crop yield forecasts using a wide range of crop calendars.

주요 곡물 생산 지역에 대한 작황 계절 예측을 위해 작물모형과 기상 예보자료들이 활용되고 있다. 이 때, 작물모형의 입력자료로 활용되는 기상자료의 불확실성이 작황 예측 결과에 영향을 줄 수 있다. 본 연구에서는 기상 예보자료에 따른 작물모형 결과에 미치는 영향을 알아보고자 하였다. 주요 곡물 생산 지역인 미국의 콘벨트 지역을 대상으로 중규모 수치예보 모형인 Weather Research and Forecasting (WRF)로 10km 해상도의 계절 예측 자료를 생산하였다. 보다 상세한 기상 예보자료 생산을 가정하기 위해 통계적 기법인 Parameter-elevation Regressions on Independent Slopes Model (PRISM) 기법을 활용하여 WRF 자료를 기반으로 5km 해상도로 예측 자료를 생산하였다. WRF와 PRISM 계절 예측 자료로 CROPGRO-SOYBEAN 모형을 구동하여 두 기상 예보자료에 따른 작물 생육 모의 결과를 얻었다. 2011~2018 기간에 대하여 4월 10일부터 8일 간격으로 11개의 파종일을 설정하였으며, 3개의 콩 성숙군에 대한 품종 모수가 사용되었다. 기상 자료의 불확실성을 파악하기 위해 작물 재배기간 동안의 누적 생육도일과 누적 일사량을 비교하였다. 예측된 수량 및 성숙일 등의 주요 변수들을 비교하였다. 두 기상 자료로부터 얻어진 변수들 사이의 일치도 통계량 계산을 위해 root mean square error (RMSE), normalized root mean square error (NRMSE) 및 structural similarity(SSIM) index가 사용되었다. WRF와 PRISM에서 계산된 누적 생육도일 사이의 일치도가 낮았던 연도에 콩 성숙일 모의 값에 대한 오차가 크게 나타났다. 콩 모의 수량 또한 성숙일 및 온도의 오차가 크게 나타났던 연도에 상대적으로 낮은 일치도를 가졌다. 또한 파종일이 수량 및 성숙일 예측의 일치도에 상당한 영향을 미치는 것으로 나타났다. 이러한 결과는 WRF와 PRISM 자료 사이에 온도 자료의 불확실성이 작황 예측의 불확실성에 영향을 주었으며, 재배 시기에 따라 그 불확도의 크기가 상이할 수 있음을 암시하였다. 따라서 신뢰도 높은 작황 예측 자료 생산을 위해 작물별 재배기간을 고려한 불확실성 평가 등의 추가적인 연구가 진행되어야 할 것으로 보인다.

Keywords

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