한국농림기상학회지 (Korean Journal of Agricultural and Forest Meteorology)

  • 제26권2호
  • /
  • Pages.127-139
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  • 2024
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  • 1229-5671(pISSN)
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  • 2288-1859(eISSN)
한국농림기상학회 (Korean Society of Agricultural and Forest Meteorology)
권호 표지
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토양유효수분율 공간분포와 기상인자와의 상관관계 분석을 통한 콩 재배기간 밭가뭄 특성 및 변동성 평가

Assessment for Characteristics and Variations of Upland Drought by Correlation Analysis in Soil Available Water Content with Meteorological Variables and Spatial Distribution during Soybean Cultivation Period

  • 이세인 (농촌진흥청 국립농업과학원 토양비료과) ;
  • 옥정훈 (농촌진흥청 국립농업과학원 토양비료과) ;
  • 허승오 (농촌진흥청 국립농업과학원 토양비료과) ;
  • 오부영 (농촌진흥청 국립농업과학원 토양비료과) ;
  • 손정우 (농촌진흥청 국립농업과학원 토양비료과) ;
  • 황선아 (농촌진흥청 국립농업과학원 토양비료과)
  • Se-In Lee (Division of Soil and Fertilizer, National Institute of Agricultural Sciences, RDA) ;
  • Jung-hun Ok (Division of Soil and Fertilizer, National Institute of Agricultural Sciences, RDA) ;
  • Seung-oh Hur (Division of Soil and Fertilizer, National Institute of Agricultural Sciences, RDA) ;
  • Bu-yeong Oh (Division of Soil and Fertilizer, National Institute of Agricultural Sciences, RDA) ;
  • Jeong-woo Son (Division of Soil and Fertilizer, National Institute of Agricultural Sciences, RDA) ;
  • Seon-ah Hwang (Division of Soil and Fertilizer, National Institute of Agricultural Sciences, RDA)
  • 투고 : 2024.05.17
  • 심사 : 2024.06.24
  • 발행 : 2024.06.30
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초록

기후변화에 따라 폭염, 폭우 및 가뭄을 포함하여 극단적인 기상 현상의 빈도가 증가하고 있다. 가뭄은 다른 자연재해와 달리 점진적으로 진행되고 장시간에 걸쳐 피해가 증가하는 특징을 갖고 있기 때문에 가뭄 발생의 특징을 이해하는 것이 매우 중요하다. 농업 가뭄, 특히 밭가뭄은 토양 수분의 부족으로 인해 농작물이 필요로 하는 물의 공급이 부족해짐으로써 발생한다. 이에 농업 가뭄에 영향을 미치는 주요 변수로 토양 수분을 활용하고 있다. 본 연구는 토양, 기상 및 작물 데이터를 통합한 모델을 활용하여 토양유효수분율을 산정함으로써 한반도 가뭄의 시공간적 분포와 경향성을 분석하였다. 또한, 기상인자와 토양유효수분율의 상관관계를 분석하여 기상 특성이 가뭄 발생 특성에 미치는 영향을 평가하였다. 콩 재배기간 동안의 평균 토양유효수분율은 2018년에 88.6%로 가장 낮았으며, 2021년에는 103.2%로 가장 높았다. 콩 생육단계별 토양유효수분율 공간 분포를 분석한 결과, 2018년 개화기(S3), 2019년 잎 경엽신장기(S2), 2020년 유묘기(S1), 2021년 개화기(S3)와 2022년 유묘기(S1)에 가장 낮았다. 콩 생육단계별 평균 토양유효수분율을 기준으로 밭가뭄 빈도수를 평가한 결과 2018년 개화기(S3)에 22회로 빈도수가 가장 높았다. 토양유효수분율이 가장 낮을 때는 강우량과 증발산량과의 가장 큰 부(-)의 상관관계를 나타낸 반면, 토양유효수분율이 가장 높을 때는 강우량과 상대습도와 가장 큰 정(+)의 상관관계를 보였으며, 기준증발산량과는 가장 큰 부(-)의 상관관계를 나타냈다.

Climate change has increased extreme weather events likewise heatwaves, heavy rain, and drought. Unlike other natural disaster, drought is a slowly developing phenomenon and thus drought damage increases as the drought continues. Therefore, it is necessary to understand the characteristics and mechanism of drought occurrence. Agricultural drought occurs when the water supply needed by crops becomes insufficient due to lack of soil water. Therefore, soil water is used as a key variable affecting agricultural drought. In this study, we examined the spatio-temporal distribution and trends of drought across the Korean Peninsula by determining the soil available water content (SAWC) through a model that integrated soil, meteorological, and crop data. Moreover, an investigation into the correlation between meteorological variables and the SAWC was conducted to assess how meteorological characteristics influence the nature of drought occurrences. During the soybean cultivation period, the average SAWC was lowest in 2018 at 88.6% and highest in 2021 at 103.2%. Analysis of the spatial distribution of SAWC by growth stage revealed that the lowest SAWC occurred during the flowering stage (S3) in 2018, during the leaf extension stage (S2) in 2019, during the seedling stage (S1) in 2020, again during the flowering stage (S3) in 2021, and during the seedling stage (S1) in 2022. Based on the average SAWC across different growth stages, the frequency of upland drought was the highest at 22 times during the S3 in 2018. The lowest SAWC was primarily influenced by a significant negative correlation with rainfall and evapotranspiration, whereas the highest SAWC showed a significant positive correlation with rainfall and relative humidity, and a significant negative correlation with reference evapotranspiration.

키워드

과제정보

본 연구는 2023년도부터 농촌진흥청 학·연협동연구과정 지원사업에 의해 이루어진 것임.

참고문헌

  1. Ahmed, A. M., R. C. Deo, N. Raj, A. Ghahramani, Q. Feng, Z. Yin, and L. Yang, 2021: Deep learning forecasts of soil moisture: Convolutional neural network and gated recurrent unit models coupled with satellite-derived MODIS, observations and synoptic-scale climate index data. Remote Sensing 13(4), 554.
  2. Allen R.G., L. S. Pereira, D. Raes, and M. Smith, 1998: Crop evapotranspiration - guidelines for computing crop water requirements -. FAO Irrigation and Drainage Paper No. 56, Food and Agricultural Organization (FAO) of the United Nations, Rome, Italy, 300pp.
  3. Apurv. T., M. Sivapalan, and X. Cai. 2017: Understanding the role of climate characteristics in drought propagation. Water Resources Research 53(11), 9304-9329.
  4. Campozano, L., D. Ballari, M. Montenegro, and A. Aviles, 2020: Future meteorological droughts in Ecuador: Decreasing trends and associated spatio-temporal features derived from CMIP5 models. Frontiers in Earth Science 8(17), 1-17.
  5. Cui, Y., S. Ning, J. Jin, S. Jiang, Y. Zhou, and C. Wu. 2020: Quantitative lasting effects of drought stress at a growth stage on soybean evapotranspiration and aboveground BIOMASS. Water 13(1), 18.
  6. Doorenbos, J., and W.O. Pruitt, 1977: (Rev.) Guidelines for predicting crop water requirements. FAO Irrigation and Drainage Paper No. 24, Food and Agricultural Organization of the United Nations, Rome, Italy, 154pp.
  7. Elsalahy, H., and M. Reckling, 2022: Soybean resilience to drought is supported by partial recovery of photosynthetic traits. Frontiers in Plant Science 13, 971893.
  8. Eom, K.C., K.C. Song, K.S. Ryu, Y.K. Sonn, and S.E. Lee, 1995: Model equations to estimate the soil water characteristics curve using scaling factor. Korean Journal of Soil Science and Fertilizer 28(3), 227-232. (in Korean with English abstract)
  9. Han, K. H., D. J. Kim, H. R. Cho, Y. S. Zhang, J. H. Ok, S. A. Hwang, K. S. Choi, J. S. Choi, S. S. Kim, J. H. Lee, M. S. Gong, E. J. Lee, H. I. Jung, G. B. Jung, Y. H. Kim, Y. J. Lee, J. K. Sung, S. B. Lee, D. B. Lee, and Y. M. Kim, 2019: Research report: Evaluation of soil water movement and nutrient availability with weighing lysimeter. National Institute of Agricultural Sciences, Rural Development Administration (RDA), Wanju, Republic of Korea, 144pp. (in Korean)
  10. Hargreaves, G. H., and Z. A. Samani, 1985: Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture 1(2), 96-99.
  11. Hong, E. M., W. H. Nam., and J. Y. Choi, 2015: Climate change impacts on agricultural drought for major upland crops using soil moisture model - Focused on the Jeollanam-do -. Journal of the Korean Society of Agricultural Engineers 57(3), 65-76. (in Korean with English abstract)
  12. IPCC. 2023: Climate Change 2023: Synthesis Report. IPCC (Intergovernmental Panel on Climate Change), Geneva, Switzerland, 184pp.
  13. Jeon, M. G., W. H. Nam, H. J. Lee, E. M. Hong, S. A. Hwang, and S.O. Hur, 2021: Drought risk assessment for upland crops using satellite-derived evapotranspiration and soil available water capacity. Journal of Korean Society of Hazard Mitigation 21(1), 25-33. (in Korean with English abstract)
  14. Jung K. H., S. O. Hur, S. G. Ha, C. W. Park, and H. H. Lee. 2007, Runoff pattern in upland soils with various soil texture and slope at torrential rainfall events. Korean Journal of Soil Science and Fertilizer 40(3), 208-213.
  15. Kim, J.P., and G. Kim, 2011: The impact of climate change on the trends of precipitation effectiveness ratio and runoff data in South Korea. Journal of Korea Water Resources Association 44(8), 683-694. (in Korean with English abstract)
  16. Lee, H. J., W. H. Nam, D. H. Yoon, D. S. Mark, and D. W. Brian, 2021: Detection of flash drought using evaporative stress index in South Korea. Journal of Korea Water Resources Association 54(8), 557-589. (in Korean with English abstract)
  17. Liu, X., X. Zhu, Y. Pan, S. Li, Y. Liu, and Y. Ma, 2016: Agricultural drought monitoring: Progress, challenges, and prospects. Journal of Geographical Sciences 26(6), 750-767.
  18. Martinez-Fernandez. J., A. Gonzalez-Zamora, N. Sanchez, and A. Gumuzzio, 2015: A soil water based index as a suitable agricultural drought indicator. Journal of Hydrology 522, 265-273.
  19. Multi-ministries Cooperative. 2020. National Drought Information Statistics (2018). Multi-ministries Cooperative, Sejong, Republic of Korea, 365pp. (in Korean)
  20. NDIC. 2016: Guidebooks for Drought Response. NDIC (National Drought Information-Analysis Center), Ministry of Environment, Daejeon, Republic of Korea, 567pp. (in Korean)
  21. NGII. 2016: Definition and Terms on Spatial information NGII (National Geographic Information Institute), Ministry of Land, Infrastructure and Transport, Suwon, Republic of Korea, 299pp. (in Korean)
  22. Open MET Data Portal, KMA (Korea Meteorological Administration). https://data.kma.go.kr.
  23. Panu, U. S., and T. C. Sharma. 2002: Challenges in drought research: some perspectives and future directions. Hydrological Sciences Journal 47(S), 19-30.
  24. Park, G. S., W. H. Nam, H. J. Lee, M. G. Jeon, and S. Yun. 2022: Assessment of the spatiotemporal variability and cycle for the extreme 2022 spring drought event. Proceedings of Annual Conference, The Korean Society of Agricultural Engineers, Daegu, Republic of Korea, 117-117. (in Korean)
  25. Rosadi, R. A. B., M. S. Afandi, M. Senge, K. Ito, and J. T. Adomako. 2005, Critical water content and water stress coefficient of soybean (Glycine max [L.] Merr.) under deficit irrigation. Paddy Water Environment 3, 219-223.
  26. Smith, M., R. Allen, J. L. Monteith, A. Perrier, L. Santos Pereira, and A. Sageren, 1992: Expert Consultation on Revision of FAO Methodologies for Crop Water Requirements. Food and Agricultural Organization (FAO) of the United Nations, Land and Water Development Division, Rome, Italy, 60pp.
  27. Smith, S. D., L. C. Bowling, K. M. Rainey, and K. A. Cherkauer, 2021: Quantifying effects of excess water stress at early soybean growth stages using unmanned aerial systems. Remote Sensing 13(15), 2911.
  28. Spinoni, J., G. Naumann, H. Carrao, P. Barbosa, and J. Vogt, 2014: World drought frequency, duration, and severity for 1951-2010. International Journal of Climatology 34, 2792-2804.
  29. Suleiman, A. A., C. M. T. Soler, and G. Hoogenboom, 2013: Determining FAO-56 crop coefficients for peanut under different water stress levels. Irrigation Science 31, 169-178.
  30. Wei, Y., J. Jin, S. Jiang, S. Ning, and L. Liu, 2018: Quantitative response of soybean development and yield to drought stress during different growth stages in the Huaibei Plain, China. Agronomy 8(97), 1-16.
  31. Wei, Y., J. Jin, H. Li, Y. Zhou, Y. Cui, N. A. Commey, Y. Zhang, and S. Jiang, 2023: Assessment of agricultural drought vulnerability based on crop growth stages: A case study of Huaibei Plain, China. International Journal of Disaster Risk Science 14(2), 209-222.
  32. Xing, Z., M. Ma, W. Yongqiang, X. Zhang, Z. Yu, and P. Yi, 2020: A new agricultural drought index considering the irrigation water demand and water supply availability. Natural Hazards 104(3), 2409-2429.
  33. Yoo, J. Y., M. Choi, and T. W. Kim, 2010: Spatial analysis of drought characteristics in Korea using cluster analysis. Journal of Korea Water Resources Association 57(1), 1-8. (in Korean with English abstract)
  34. Zhang, R., L. Li, Y. Zhang, F. Huang, J. Li, W. Liu, T. Mao, Z. Xiong, and W. Shangguan, 2021: Assessment of agricultural drought using soil water deficit index based on ERA5-Land soil moisture data in four southern provinces of China. Agriculture 11(5), 411.