• Title/Summary/Keyword: Water estimation models

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Evaluation of Meteorological Elements Used for Reference Evapotranspiration Calculation of FAO Penman-Monteith Model (FAO Penman-Monteith 모형의 증발산량 산정에 이용되는 기상요소의 평가)

  • Hur, Seung-Oh;Jung, Kang-Ho;Ha, Sang-Keun;Kim, Jeong-Gyu
    • Korean Journal of Soil Science and Fertilizer
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    • v.39 no.5
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    • pp.274-279
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    • 2006
  • The exact estimation of crop evapotranspiration containing reference or potential evapotranspiration is necessary for decision of crop water requirements. This study was carried out for the evaluation and application of various meteorological elements used for the calculation of reference evapotranspiration (RET) by FAO Penman-Monteith (PM) model. Meteorological elements including temperature, net radiation, soil heat flux, albedo, relative humidity, wind speed measured by meteorological instruments are required for RET calculation by FAO PM model. The average of albedo measured for crop growing period was 0.20, ranging from 0.12 to 0.23, and was slightly lower than 0.23. Determinant coefficients by measured albedo and green grass albedo were 0.97, 0.95 and standard errors were 0.74, 0.80 respectively. Usefulness of deductive regression models was admitted. To assess an influence of soil heat flux (G) on FAO PM, RET with G=0 was compared with RETs using G at 5cm soil depth ($G_{5cm}$) and G at surface ($G_{0cm}$). As the results, RET estimated by G=0 was well agreed with RET calculated by measured G. Therefore, estimated net radiation, G=0 and albedo of green grass could be used for RET calculation by FAO PM.

Comparative Analysis of Nitrogen Concentration of Rainfall in South Korea for Nonpoint Source Pollution Model Application (비점오염모델 적용을 위한 우리나라 행정구역별 강수 중 질소농도 비교분석)

  • Choi, Dong Ho;Kim, Min-Kyeong;Hur, Seung-Oh;Hong, Sung-Chang;Choi, Soon-Kun
    • Korean Journal of Environmental Agriculture
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    • v.37 no.3
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    • pp.189-196
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    • 2018
  • BACKGROUND: Water quality management of river requires quantification of pollutant loads and implementation of measures through monitoring study, but it requires labour and costs. Therefore, many researchers are performing nonpoint source pollution analysis using computer models. However, calibration of model parameters needs observed data. Nitrogen concentration in rainfall is one of the factors to be considered when estimating the pollutant loads through application of the nonpoint source pollution model, but the default value provided by the model is used when there are no observed data. Therefore, this study aims to provide the representative nitrogen concentration of the rainfall for the administrative district ensuring rational modeling and reliable results. METHODS AND RESULTS: In this study, rainfall monitoring data from June 2015 to December 2017 were used to determine the nitrogen concentration in rainfall for each administrative district. Range of the $NO_3{^-}$ and $NH_4{^+}$ concentrations were 0.41~6.05 mg/L, 0.39~2.27 mg/L, respectively, and T-N concentration was 0.80~7.71 mg/L. Furthermore, the national average of T-N concentration in this study was $2.84{\pm}1.42mg/L$, which was similar to the national average of T-N 3.03 mg/L presented by the Ministry of Environment in 2015. Therefore, the nitrogen concentrations suggested in this study can be considered to be resonable values. CONCLUSION: The nitrogen concentrations estimated in this study showed regional differences. Therefore, when estimating the pollutant loads through application of the nonpoint source pollution model, resonable parameter estimation of nitrogen concentration in rainfall is possible by reflecting the regional characteristics.