Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
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Statistical Analysis of Determining Optimal Monitoring Time Schedule for Crop Water Stress Index (CWSI)

작물 수분 스트레스 지수 산정을 위한 최적의 관측 간격과 시간에 대한 통계적 분석

  • Choi, Yonghun (Department of Agricultural Engineering, National Institute of Agricultural Sciences (NAS), Rural Development Administration (RDA)) ;
  • Kim, Minyoung (Department of Agricultural Engineering, National Institute of Agricultural Sciences (NAS), Rural Development Administration (RDA)) ;
  • Oh, Woohyun (Department of Agricultural Engineering, National Institute of Agricultural Sciences (NAS), Rural Development Administration (RDA)) ;
  • Cho, Junggun (Department of Horticultural Crop Research, National Institute of Horticultural and Herbal Sciences (NIHHS), Rural Development Administration (RDA)) ;
  • Yun, Seokkyu (Department of Horticultural Crop Research, National Institute of Horticultural and Herbal Sciences (NIHHS), Rural Development Administration (RDA)) ;
  • Lee, Sangbong (Department of Agricultural Engineering, National Institute of Agricultural Sciences (NAS), Rural Development Administration (RDA)) ;
  • Kim, Youngjin (Department of Agricultural Engineering, National Institute of Agricultural Sciences (NAS), Rural Development Administration (RDA)) ;
  • Jeon, Jonggil (Department of Agricultural Engineering, National Institute of Agricultural Sciences (NAS), Rural Development Administration (RDA))
  • Received : 2019.09.19
  • Accepted : 2019.10.28
  • Published : 2019.11.30
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Abstract

Continuous and tremendous data (canopy temperature and meteorological variables) are necessary to determine Crop Water Stress Index (CWSI). This study investigated the optimal monitoring time and interval of canopy temperature and meteorological variables (air temperature, relative humidity, solar radiation and wind speed) to determine CWSIs. The Nash-Sutcliffe model efficiency coefficient (NSE) was used to quantitatively describe the accuracy of sampling method depending upon various time intervals (t=5, 10, 15, 20, 30 and 60 minutes) and CWSIs per every minute were used as a reference. The NSE coefficient of wind speed was 0.516 at the sampling time of 60 minutes, while the ones of other meteorological variables and canopy temperature were greater than 0.8. The pattern of daily CWSIs increased from 8:00 am, reached the maximum value at 12:00 pm, then decreased after 2:00 pm. The statistical analysis showed that the data collection at 11:40 am produced the closest CWSI value to the daily average of CWSI, which indicates that just one time of measurement could be representative throughout the day. Overall, the findings of this study contributes to the economical and convenient method of quantifying CWSIs and irrigation management.

Keywords

References

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