• Water for future
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• v.6 no.2
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• pp.6-11
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• 1973

This paper include the hydrometeorological analyses of evapotranspiration which is import factor concerning the estimate of water budgest over a certain basin. Evapotranspiration model mode by the multiple regression analysis between the evapotranspiration measured on various kinds of ground cover (water, bare soil and lawn) and the other meteorological elements affecting the evapotranspiration process, and the simple regression analysis between the evapo transpiration measured on each ground cover and the evapotranspiration on water and vegetables calculated from the Penman equation. It is expected that the evapotranspiration models are a very useful formulae estimating ten days amounts or a month's amounts.

• Journal of Korea Water Resources Association
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• v.51 no.3
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• pp.273-280
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• 2018

Accurate estimation of evapotranspiration is mightily important for understanding and analyzing the hydrological cycle. There are various methods for estimating evapotranspiration and each method has its own advantages and limitations. Therefore, it is necessary to develop an optimal evapotranspiration product by combing different evapotranspiration products. In this study, we developed an optimal evapotranspiration by fusing two satellite- and model-based evapotranspiration estimates, including revised remote sensing-based Penman-Monteith (RS-PM) and Modified Satellite-Based Priestley-Taylor (MS-PT) methods, Global Land Data Assimilation System (GLDAS), and Global Land Evaporation Amsterdam Model (GLEAM). The statistical analysis (i.e., correlation coefficients, index of agreement, MAE, and RMSE) of combined evapotranspiration product showed to be improved compared to the individual model results. After confirming the overall results, in future studies, advanced data fusion techniques will be used to obtained improved results.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.4
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• pp.50-56
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• 2001

In order to provide basic information for the estimation of reference crop evapotranspiration in the greenhouse on experiment was performed. Daily evapotranspiration of the reference crop wear measured using lysimeters. kentucky Blue Grass was used as a reference crop. Climatic elements I the greenhouse such as air temperature relative humidity and radiation were measured. The influence of each climatic element on the evapotranspiration were analyzed. A multi-regression model for the estimation of reference crop evapotranspiration in the greenhouse was developed and tested simulated evapotranspiration by the model were in good agreement with measured evapotransiration.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.178-183
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• 2004

Hydrological models simulate the land phase component of the water cycle and provide a mechanism for evaluating the effects of climatic variation and change on water resources. Evapotranspiration(ET) is a critical process within hydrological models. This study evaluates five different methods for estimating ET in the SLURP(Semi-distrubuted Land Use Runoff Process)model, in the Yongdam basin. The five ET methods were the FAO Penman-Monteith, Motorn CRAE(Complementary Relationship Area Evapotranspiration), the Spittlehouse-Black, the Granger, the Linarce model. We evaluated the five ET models, based on the ability of SLURP model to simulate daily streamflow. and How the five ET methods influence the sensitivity of simulated streamflow to changes in key model parameters and validation SLURP independently for each ET methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1423-1426
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• 2007

The goal of this research is to develop and apply the integrational model for the pan evaporation and the alfalfa reference evapotranspiration in Republic of Korea. Since the observed data of the alfalfa reference evapotranspiration using lysimeter have not been measured for a long time in Republic of Korea, PM method is used to assume and estimate the observed alfalfa reference evapotranspiration. The integrational model consists of staochastics and neural networks processes respectively. The stochastics process is applied to extend for the short-term monthly pan evaporation and alfalfa reference evapotranspiration. The extended data of the monthly pan evaporation and alfalfa reference evapotranspiration is used to evaluate for the training performance. For the neural networks process, the generalized regression neural networks model(GRNNM) is applied to evaluate for the testing performance using the observed data respectively. From this research, we evaluate the impact of the limited climatical variables on the accuracy of the integrational operation of stochastics and neural networks processes. We should, furthermore, construct the credible data of the pan evaporation and the alfalfa reference evapotranspiration, and suggest the reference data for irrigation and drainage networks system in Republic of Korea.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.151-156
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• 2000

This study was to evaluate the effect of leaf temperature on daily evapotranspiration of crop. A transpiring crop will be cooled by the vaporization of water to a temperature below that of the surrounding air. Leaf temperature was measured a infrared thermometer. Crop evapotranspiration was measured by the method of lysimeter. A statistical model for estimating evapotranspiration was developed and tested. It was showed that the model was applicable.

• 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.

• Journal of Korea Water Resources Association
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• v.37 no.9
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• pp.745-758
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• 2004

Hydrological models simulate the land phase components of the water cycle and provide a mechanism for evaluating the effects of climatic variation and change on water resources. Evapotranspiration(ET) is a critical process within hydrological models. This study evaluates five different methods for estimating ET in the SLURP(Semi-distributed Land Use Runoff Process)model, in the Yongdam basin. The five ET methods were the FAO Penman-Monteith, Morton CRAE (Complementary Relationship Area Evapotranspiration), the Spittlehouse-Black, the Granger, the Linacre model. We evaluated the five ET models, based on the ability of SLURP model to simulate daily streamflow, and How the five ET methods influence the sensitivity of simulated streamflow to changes in key model parameters and validation SLURP independently for each ET methods. The results showed that the Merton CRAE model had more physical significance and gave better agreement simulated stream flow and recorded flows. It noted that the Morton CRAE model might be more appropriate for the simulation of the actual evapotranspiration in SLURP hydrologic model.

• Journal of Climate Change Research
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• v.9 no.2
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• pp.143-156
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• 2018

Evapotranspiration is a key element in designing and operating agricultural hydraulic structures. The profound effect of climate change to local agro-hydrological systems makes it inevitable to study the potential variability in evapotranspiration rate in order to develop policies on future agricultural water management as well as to evaluate changes in agricultural environment. The APEX-Paddy model was used to simulate local evapotranspiration responses to climate change scenarios. Nine Global Climate Models(GCMs) downscaled using a non-parametric quantile mapping method and a Multi?Model Ensemble method(MME) were used for an uncertainty analysis in the climate scenarios. Results indicate that APEX-Paddy and the downscaled 9 GCMs reproduce evapotranspiration accurately for historical period(1976~2005). For future periods, simulated evapotranspiration rate under the RCP 4.5 scenario showed increasing trends by -1.31%, 2.21% and 4.32% for 2025s(2011~2040), 2055s(2041~2070) and 2085s(2071~2100), respectively, compared with historical(441.6 mm). Similar trends were found under the RCP 8.5 scenario with the rates of increase by 0.00%, 4.67%, and 7.41% for the near?term, mid?term, and long?term periods. Monthly evapotranspiration was predicted to be the highest in August, July was the month having a strong upward trend while. September and October were the months showing downward trends in evapotranspiration are mainly resulted from the shortening of the growth period of paddy rice due to temperature increase and stomatal closer as ambient $CO_2$ concentration increases in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.115-119
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• 2006

The goal of this research is to develop and apply the generalized regression neural networks model (GRNNM) embedding genetic algorithm (GA) for pan evaporation, which is missed or ungaged and for the alfalfa reference evapotranspiration, which is not measured in South Korea. The GRNNM-GA is evaluated using the training, the testing, and reproduction performance respectively for the estimation of the PE and the alfalfa reference evapotranspiration. Since the observed data of the alfalfa reference evapotranspiration using lysimeter have not been measured for a long time in South Korea, the PM method is used to assume and estimate the observed alfalfa reference evapotranspiration. From this research, we evaluate the impact of the limited climatical variables on the accuracy of the GRNNM-GA. We should, furthermore, construct the credible data of the PE and the alfalfa reference evapotranspiration and suggest the reference data for irrigation and drainage networks system in South Korea.