• Title/Summary/Keyword: Spatio-temporal data

Search Result 511, Processing Time 0.024 seconds

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 (토양유효수분율 공간분포와 기상인자와의 상관관계 분석을 통한 콩 재배기간 밭가뭄 특성 및 변동성 평가)

  • Se-In Lee;Jung-hun Ok;Seung-oh Hur;Bu-yeong Oh;Jeong-woo Son;Seon-ah Hwang
    • Korean Journal of Agricultural and Forest Meteorology
    • /
    • v.26 no.2
    • /
    • pp.127-139
    • /
    • 2024
  • 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.