• Title/Summary/Keyword: 농업기상

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Suggestions for improving data quality assurance and spatial representativeness of Cheorwon AAOS data (철원 자동농업기상관측자료의 품질보증 및 대표성 향상을 위한 제언)

  • Park, Juhan;Lee, Seung-Jae;Kang, Minseok;Kim, Joon;Yang, Ilkyu;Kim, Byeong-Guk;You, Keun-Gi
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.20 no.1
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    • pp.47-56
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    • 2018

  • Providing high-quality meteorological observation data at sites that represent actual farming environments is essential for useful agrometeorological services. The Automated Agricultural Observing System (AAOS) of the Korean Meteorological Administration, however, has been deployed on lawns rather than actual farm land. In this study, we show the inaccuracies that arise in AAOS data by analyzing temporal and vertical variation and by comparing them with data recorded by the National Center for AgroMeteorology (NCAM) tower that is located at an actual farming site near the AAOS tower. The analyzed data were gathered in August and October (before and after harvest time, respectively). Observed air temperature and water vapor pressure were lower at AAOS than at NCAM tower before and after harvest time. Observed reflected shortwave radiation tended to be higher at AAOS than at NCAM tower. Soil variables showed bigger differences than meteorological observation variables. In August, observed soil temperature was lower at NCAM tower than at AAOS with smaller diurnal changes due to irrigation. The soil moisture observed at NCAM tower continuously maintained its saturation state, while the one at AAOS showed a decreasing trend, following an increase after rainfall. The trend changed in October. Observed soil temperature at NCAM showed similar daily means with higher diurnal changes than at AAOS. The soil moisture observed at NCAM was continuously higher, but both AAOS and NCAM showed similar trends. The above results indicate that the data gathered at the AAOS are inaccurate, and that ground surface cover and farming activities evoke considerable differences within the respective meteorological and soil environments. We propose to shift the equipment from lawn areas to actual farming sites such as rice paddies, farms and orchards, so that the gathered data are representative of the actual agrometeorological observations.

  • https://doi.org/10.5532/KJAFM.2018.20.1.47 인용 PDF KSCI

Spatiotemporal Agricultural Drought Damage and Its Relationship with Hydrometeorological Characteristics of Historical Drought Events for Recent 40 Years (최근 40년간 가뭄사상의 수문기상학적 특성 및 시공간적 변화와 농업가뭄피해)

  • Woo, Seung-Beom;Nam, Won-Ho;Kim, Taegon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.392-392
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    • 2020

  • 최근 기후변화로 인해 가뭄의 규모 및 발생 빈도가 증가하고 있으며, 1994-1995년, 2000-2001년 전국적으로 발생했던 가뭄 상황과 달리 2010년 이후의 가뭄은 지역별로 편중되어 내리는 강수때문에 국소적으로 발생하고 있다. 특히, 2011년부터 2018년까지 연속적으로 국지적인 가뭄이 발생하였고, 2017년에는 경기, 충남, 전남지역을 중심으로 극심한 가뭄이 발생하였다. 우리나라의 경우 강수부족으로 기상, 수문학적 가뭄이 발생한다고 하더라도 농업용 수리시설물에 의한 농업용수 공급이 가능하고, 양수장, 관정 등 농업용수 공급의 형태가 다양하기 때문에 실제로 농업현장에서 체감하는 농업가뭄피해는 시공간적으로 상이하다. 따라서, 강수 부족으로 인한 가뭄사상의 발생에 따른 수문기상학적 특성 및 시공간적인 분포 특성과 농업가뭄피해의 발생 현황, 농업용 저수지의 저수율 변화 및 농업용수 이용과의 관계는 향후 농업가뭄의 지역별 가뭄대책 수립에 중요한 기초자료로 활용할 수 있다. 본 연구에서는 농업가뭄에 대하여 정량적인 가뭄피해를 분석하기 위하여 지역별 가뭄발생면적 및 쌀 생산량과 가뭄사상의 수문기상학적 특성간의 상관성을 분석하고자 한다. 최근 40년간 강수량, 표준강수지수 (Standard Precipitation Index, SPI), 표준강수증발산지수(Standardized Precipitation Evapotranspiration Index, SPEI) 등의 가뭄지표인자와 쌀 생산량, 농업용 저수지 저수율 자료 등 관련 인자들을 수집하여, 농업가뭄발생 및 피해면적과의 정량적인 상관관계를 분석하고자 한다.

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Study on Improvement of Frost Occurrence Prediction Accuracy (서리발생 예측 정확도 향상을 위한 방법 연구)

  • Kim, Yongseok;Choi, Wonjun;Shim, Kyo-moon;Hur, Jina;Kang, Mingu;Jo, Sera
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.295-305
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    • 2021

  • In this study, we constructed using Random Forest(RF) by selecting the meteorological factors related to the occurrence of frost. As a result, when constructing a classification model for frost occurrence, even if the amount of data set is large, the imbalance in the data set for development of model has been analyzed to have a bad effect on the predictive power of the model. It was found that building a single integrated model by grouping meteorological factors related to frost occurrence by region is more efficient than building each model reflecting high-importance meteorological factors. Based on our results, it is expected that a high-accuracy frost occurrence prediction model will be able to be constructed as further studies meteorological factors for frost prediction.

  • https://doi.org/10.5532/KJAFM.2021.23.4.295 인용 PDF KSCI