• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.274-274
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• 2020

환경부 홍수통제소의 경우는 전국단위의 강수량(지상, 레이더), 하천수위, 유사량 관측과 국부적으로 증발산량과 토양수분 관측이 이루어지고 있는 상황이며, 기상청 및 다른 공공기관도 각 목적에 맞게 수문기상관측이 이루어지나 유역(또는 지역) 단위의 물순환 과정(강우량, 유출량, 증발산량, 지하수함양량, 토양수분량 등 포함)을 규명하는 조사·연구는 매우 미비한 실정이다. 개별적인 물순환 성분별 수문조사에서 벗어난 전체적인 관점을 고려한 유역단위의 물순환 과정을 규명하는 것은 매우 중요하다. 즉 물순환 성분별 명확한 수문량 산정 결과는 수자원 개발과 물환경 보전에 중요한 정보를 제공할 수 있다. 따라서 물순환 성분별 명확한 분석을 위해서는 중·소규모 유역 단위를 대상으로 지속적이고 신뢰성 있는 자료의 획득과 축적이 중요하므로 중·소규모 유역 단위의 대표성 있는 시험유역의 운영은 매우 의미가 있다고 볼 수 있다. 본 논문에서는 한국건설기술연구원에서 운영하는 설마천 유역(유역면적 8.48㎢, 유로경사 2.15%, 경기도 파주시 적성면 소재)의 신뢰성 높은 2019년 관측자료를 이용하여 물순환 성분인 강우량, 하천유출량, 증발산량과 지하수 함양량의 자료를 산정하였으며, 물순환 성분별 균형을 이루는 자료를 생성하였다. 기본 관측자료인 강우량은 각 지점강우량의 관측자료의 비교·검토 등 품질관리를 통해 자료를 확정하고 유역평균강우량을 산정하였다. 하천수위는 기준수위표와의 검토를 통해 자료를 확정하였으며, 하천유출량은 유량측정성과와 단면검토를 통해 수위-유량관계곡선식을 개발하고, 확정된 수위자료를 적용하여 산정하였다. 그리고 증발산량은 유역내의 기상관측자료를 활용하여 잠재증발산량을 산정하였으며, 지하수함양량은 유역내에 관측된 지하수위자료를 이용하여 지하수 함양량을 산정하였다. 각 물순환 성분별로 산정된 자료는 과거년 자료와 비교·평가를 통해 균형성을 판단하였다. 각 성분별 최대치와 최소범위, 평균값을 고려하고, 강우일수, 강우의 강우강도와 지속기간, 기상자료(기온, 일조시간, 습도, 풍속 등)를 충분히 고려하였다. 각 물순환 성분별로 생성된 2019년의 설마천 유역의 총강우량은 1,024.1mm이며, 하천유출량은 608.6mm(총강우량 대비 59.4%), 실제증발산량은 385.1mm(37.6%), 지하수함양량은 30.4mm(3.0%)이다. 여기서, 실제증발산량과 지하수 함양량은 1개 지점에서 산정값이나, 물순환의 폐합 조건을 고려하여 산정된 결과이다. 향후 유역 전체를 대표하는 기법의 개발은 필요한 실정이다. 이와 같이 산정된 물순환 성분별 자료는 유역의 물순환 과정 규명을 위한 기초자료로 매우 유용하게 활용될 수 있으며, 유역 물관리를 위한 의사결정 과정에 중요한 역할을 할 수 있을 것으로 기대된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.3
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• pp.111-117
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• 2009

Food and Agricultural Organization (FAO) Penman-Monteith (PM) equation is one of the most widely used equations for predicting evapotranspiration (ET) of crops. The ET rate and the base crop coefficients ($K_{cb}$) of the two different grape vines (i.e., Campbell Early and Kyoho) cultivated in Suwon were calculated by using the FAO PM equation. The ET rate of Campbell Early was $2.41\;mm\;day^{-1}$ and that of Kyoho was $2.22\;mm\;day^{-1}$ in August when the leaf area index was 2.2. During this period, the $K_{cb}$ of Campbell Early based on the FAO PM equation was on average 0.49 with the maximum value of 0.72. On the other hand, the $K_{cb}$ of Kyoho was averaged to be 0.45 with the maximum value of 0.64. The seasonal leaf area index for two grape cultivars was measured as 0.15 in April, 0.5 in May, 1.4 in June, 2.2 in July-September, and 1.5 in October. The $K_{cb}$ of Campbell Early showed a seasonal variation, changing from 0.03 in April to 0.11 in May, 0.31 in June, 0.49 in July-September, and 0.33 in October. The magnitudes and the seasonality of $K_{cb}$ of Kyoho were similar to those of Campbell Early.

• Journal of Korea Water Resources Association
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• v.41 no.4
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• pp.413-422
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• 2008

It is essential to locally adjust the Hargreaves parameter for estimating reference evapotranspiration with short data as a substitute of Penman-Monteith equation. In this study, evaluation of daily-based reference evapotranspiration is computed with Hargreaves equation. in Gyeonggi bay area including Ganghwa, Incheon, Suwon, Seosan, and Cheonan station for the time period of 1997-2004. Hargreaves coefficient is adjusted to give the best fit with Penman-Monteith evapotranspiration, being regarded as a reference. Then, the preferred parameters are validated for the same stations for the time period of 2005-2006. The optimization-based correction in calibration for 1997-2004 shows improved performance of the Hargreaves equation, giving 0.68-0.77 to 0.92-0.98 in Nash-Sutcliffe coefficient of efficiency (NSC) and 14.63-23.30 to 5.23-11.75 in RMSE. The validation for 2005-2006 shows improved performance of the Hargreaves equation, giving 0.43-0.85 to 0.93-0.97 in NSC and 14.43-26.81 to 6.48-9.09 in RMSE.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1141-1180
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• 2022

The application of satellite imageries has increased in the field of hydrology and water resources in recent years. However, challenges have been encountered on obtaining accurate evapotranspiration and soil moisture. Therefore, present researches have emphasized the necessity to obtain estimations of satellite-based evapotranspiration and soil moisture with related development researches. In this study, we presented the research status in Korea by investigating the current trends and methodologies for evapotranspiration and soil moisture. As a result of examining the detailed methodologies, we have ascertained that, in general, evapotranspiration is estimated using Energy balance models, such as Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration (METRIC). In addition, Penman-Monteith and Priestley-Taylor equations are also used to estimate evapotranspiration. In the case of soil moisture, in general, active (AMSR-E, AMSR2, MIRAS, and SMAP) and passive (ASCAT and SAR)sensors are used for estimation. In terms of statistics, deep learning, as well as linear regression equations and artificial neural networks, are used for estimating these parameters. There were a number of research cases in which various indices were calculated using satellite-based data and applied to the characterization of drought. In some cases, hydrological cycle factors of evapotranspiration and soil moisture were calculated based on the Land Surface Model (LSM). Through this process, by comparing, reviewing, and presenting major detailed methodologies, we intend to use these references in related research, and lay the foundation for the advancement of researches on the calculation of satellite-based hydrological cycle data in the future.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1243-1254
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• 2021

For water resources operation or agricultural water management, it is important to accurately predict evapotranspiration for a long-term future over a seasonal or monthly basis. In this study, reference evapotranspiration forecast (up to 12 months in advance) was performed using statistically predicted monthly temperatures and temperature-based Hamon method for the Han River basin. First, the daily maximum and minimum temperature data for 15 meterological stations in the basin were derived by spatial-temporal downscaling the monthly temperature forecasts. The results of goodness-of-fit test for the downscaled temperature data at each site showed that the percent bias (PBIAS) ranged from 1.3 to 6.9%, the ratio of the root mean square error to the standard deviation of the observations (RSR) ranged from 0.22 to 0.27, the Nash-Sutcliffe efficiency (NSE) ranged from 0.93 to 0.95, and the Pearson correlation coefficient (r) ranged from 0.97 to 0.98 for the monthly average daily maximum temperature. And for the monthly average daily minimum temperature, PBIAS was 7.8 to 44.7%, RSR was 0.21 to 0.25, NSE was 0.94 to 0.96, and r was 0.98 to 0.99. The difference by site was not large, and the downscaled results were similar to the observations. In the results of comparing the forecasted reference evapotranspiration calculated using the downscaled data with the observed values for the entire region, PBIAS was 2.2 to 5.4%, RSR was 0.21 to 0.28, NSE was 0.92 to 0.96, and r was 0.96 to 0.98, indicating a very high fit. Due to the characteristics of the statistical models and uncertainty in the downscaling process, the predicted reference evapotranspiration may slightly deviate from the observed value in some periods when temperatures completely different from the past are observed. However, considering that it is a forecast result for the future period, it will be sufficiently useful as information for the evaluation or operation of water resources in the future.

• Current Research on Agriculture and Life Sciences
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• v.3
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• pp.28-35
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• 1985

This work Was carried out to obtain the most suitable crop coefficient for the paddy rice growing in Taegu area. The result was due to the comparative measurements of evapotranspiration formula in terms of Blaney & Criddle and eight other formulas with those produced by experiment particularly in this area. The crop coefficient, evapotranspiration and transpiration ratio produced by this research are hopefully expected to be of service in the future calculation of evapotranspiration without repeating experiment respectively, whenever the water requirement of paddy rice is planned in Taegu and its vicinity. The accomplished results could be summarized as follows : The maximum amount of evapotranspiration was recorded in the early and middle parts of August. The average reading of evapotranspiration was 6.33mm/day throughout the growth. The evapotranspiration had a highly significant correlation with pan evaporation, solar radiation, sunshine hours and relative humidity of meteorological elements. K and Kc by the use of Blaney & Criddle formula calculated at 0.76 to 1.45 and 0.82 to 1.27, respectively. Its peak value appeared commonly in early August. The ratio of transpiration was 269.03.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.111-121
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• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

• Journal of Korea Water Resources Association
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• v.41 no.2
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• pp.212-228
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• 2008

Five representative reference evapotranspiration(RET) equations were selected, and these equations were compared with pan evaporation by correlation analysis. Pan coefficients were also estimated. Furthermore, five selected RET equations were compared to find the similarity among those at the 21 meteorological stations located in South Korea. Five RET equations selected from 4 different category were Penman(combination approach), FAO Penman-Monteith(FAO P-M) (single source approach), Makkink and Priestley-Taylor (radiation approach) and Hargreaves(temperature approach) equations. In this study, the geographical and topographical conditions were considered for the selection of study stations. The daily meteorological data measured from 1970 at an interval of 5 years were applied in this study. The evapotranspiration estimates obtained by applying evapotranspiration equations were evaluated with numerical and graphical methods. The correlation coefficients between pan evaporation and RET in study stations were above 0.9 indicating very high correlation; however, the slopes of the individual regression lines show the values greater or less than 1.0. Hargreaves equation(temperature approach) shows the most similar evapotranspiration estimates to those of FAO P-M equation from 12 study stations, which are located near to seashore except Daegu station. On the other hand, Priestley-Taylor equation(radiation approach) shows the most similar evapotranspiration estimates to those of FAO P-M equation from 8 study stations, which are located in inland.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.285-299
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• 2023

Estimating the evapotranspiration is very important factor for effective water resources management, and FAO Penman-Monteith (FAO P-M) model has been applied for reference evapotranspiration estimation by many researchers. However, because various input data are required for the application of FAO P-M model, understanding the effect of each input data on FAO P-M model is necessary. Therefore, in this study, for 56 study stations located in South Korea, the effects of 8 meteorological factors (maximum and minimum temperature, wind speed, relative humidity, solar radiation, vapor pressure deficit, net radiation, ground heat flux), energy and aerodynamic terms of FAO P-M model, and elevation on FAO P-M reference evapotranspiration (RET) estimation were analyzed. The relative sensitivity analysis was performed to determine how 10% increment of each specific independent variable affects a reference evapotranspiration under given set of condition that other independent variables are unchanged. Furthermore, to select the 5 representative stations and perform the monthly relative sensitivity analysis for those stations, 56 study stations were classified into 5 clusters using cluster analysis. The study results showed that net radiation was turned out to be the most sensitive factor in 8 meteorological factors for 56 study stations. The next most sensitive factor was relative humidity, solar radiation, maximum temperature, vapor pressure deficit and wind speed, followed by minimum temperature in order. Ground heat flux was the least sensitive factor. In case of ground surface condition, elevation showed very low positive relative sensitivity. Relativity sensitivities of energy and aerodynamic terms of FAO P-M model were 0.707 for energy term and 0.293 for aerodynamic term respectively, indicating that energy term was more contributable than aerodynamic term for reference evapotranspiration. The monthly relative sensitivities of meteorological factors showed the seasonal effects, and also the relative sensitivity of elevation showed different pattern each other among study stations. Therefore, for the application of FAO P-M model, the seasonal and regional sensitivity differences of each input variable should be considered.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.123-129
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• 1999

Evapotranspiration is one of the important water budget components . An experiment was conducted to measure evapotranspiration. Three lysimeters were used to measure daily evapotranspiration. Lysimetrically measured values were compared with estimated values of various methods in REF-ET model , and then crop coefficient was computed.