• Journal of Korea Water Resources Association
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• v.53 no.7
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• pp.557-567
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• 2020

The six current models for estimating pan coefficient were applied to test the applicability of models in Seoul, South Korea. The models are Cuenca's model, Snyder's model, Pereira et al.'s model, Allen et al.'s model, Orang's model, and Raghuwanshi and Wallender's model. The estimated pan coefficients were compared with measured one. The measured pan coefficient was obtained by using measured pan evaporation and FAO Penman-Monteith reference evapotranspiration. Estimated evaporation by using estimated pan coefficients was compared with measured one. Furthermore, model for estimating pan coefficient in Seoul was developed. When applying 6 current models for 10 m, 15 m and 20 m fetch distances, pan coefficient estimates from Snyder's model were most similar to measured pan coefficients for all fetch distances. On the other hand, pan coefficient estimates from Pereira et al.'s model were most different from measured one. Therefore, model for estimating pan coefficient in Seoul was developed by modifying Snyder's model. When applying developed model, estimated monthly average evaporation was 92.1 mm for 10 m, 15 m and 20 m fetch distances and measured one was 91.9 mm, indicating that evaporation estimate from developed model is closest to measured one, compared with those of current models.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.37-53
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• 2017

Pan evaporation has been used as an indirect method for the estimation of reservoir evaporation. Therefore, in this study, pan evaporation estimation equations using only temperature data were suggested in the case that available meteorological data is limited. A formula for estimating the pan evaporation were suggested by comparing estimated pan evaporation with measured pan evaporation in 12 study areas in Korea. The suggested pan evaporation equations were verified in 44 study areas by comparing not only with temperature-based equations but also with equations using other meteorological data (temperature, wind speed, relative humidity, and sunshine duration). The study results indicate that the suggested equations in this study provide much better pan evaporation estimates, compared with other temperature-based equations. Overall, the suggested equations provide appropriate pan evaporation estimates in most of 56 study areas. Therefore, the suggested equations using only temperature data in this study are considered appropriate for the estimation of pan evaporation in Korea especially in the case that available meteorological data is limited. In the future, using the air temperature and pan evaporation data measured at the reservoir, further research is needed to examine the applicability of suggested equations for the estimation of reservoir evaporation.

• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.229-243
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• 2022

The effects of monthly meteorological data measured at 11 stations in South Korea on pan coefficient were analyzed to develop the four types of multiple linear regression models for estimating pan coefficients. To evaluate the applicability of developed models, the models were compared with six previous models. Pan coefficients were most affected by air temperature for January, February, March, July, November and December, and by solar radiation for other months. On the whole, for 12 months of the year, the effects of wind speed and relative humidity on pan coefficient were less significant, compared with those of air temperature and solar radiation. For all meteorological stations and months, the model developed by applying 5 independent variables (wind speed, relative humidity, air temperature, ratio of sunshine duration and daylight duration, and solar radiation) for each station was the most effective for evaporation estimation. The model validation results indicate that the multiple linear regression models can be applied to some particular stations and months.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.291-291
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• 2023

증발량을 산정하는 방법 중 증발접시를 활용한 방법은 하천의 증발량을 직접적으로 측정할 수 있는 장점이 있는 반면, 장기간의 증발접시를 활용한 증발량 추정은 현실적으로 쉽지 않다. 대표적인 증발량 산정식으로는 에너지 수지 및 공기동역학적 원리의 혼합적용 방법(PCE, Penman combination equation)과 경험적 바람공식(PWF, Penman wind function)이 있다. PCE로 산정된 증발량의 경우 하천 내 바닥열(bed heat flux)과 물기둥의 열저장 변화율이 장기간 규모의 순 복사량에 비해 작은 값을 가져 식에서 제외되므로 전반적으로 증발량이 과대 추정되는 문제가 발생한다. 반면, PWF로 산정한 증발량에서는 광범위한 매개변수 범위와 기상자료의 부족으로 모형의 불확실성을 증대시키는 요인으로 작용한다. 본 연구의 최종적인 목표는 하천 수로의 수면증발량을 추정하는 것이지만, 실제 하천 중심에서 증발량을 추정하기 위한 수문학적 자료는 매우 부족한 실정이다. 따라서, 본 연구에서는 유역단위에서의 증발량을 전이하는 방안을 모색하고자 하며, 구체적인 연구과정은 다음과 같다. 첫째, 유역단위 수문학적 자료를 수집하여(flux tower 자료 활용) 유역단위의 증발량을 산정한다. 둘째, PCE와 PWF으로 산정한 증발량과 관측된 증발량을 이용하여 각 식의 매개변수를 최적화한다. 마지막으로 최적화된 매개변수를 적용한 증발량과 관측값의 유사성을 분석한다. 본 연구에서는 하천단위의 증발량을 산정하기 위해 PWF을 적용하였으며 용담댐 내의 기상자료를 활용하여 산정한 증발량과 실제 용담댐 내의 수면증발량의 상관성을 분석한 결과 높은 상관성 확인할 수 있었다. 따라서 하천 주변에 증발량 추정을 위한 최소한의 기상정보가 존재하는 지역에서, 하천단위의 증발량을 산정할 수 있으며 장기간의 증발량도 산정할 수 있을 것으로 판단된다.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1033-1046
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• 2019

To evaluate the utilization suitability of solar radiation models, estimated solar radiation from 13 solar radiation models were verified by comparing with measured solar radiation at 5 study stations in South Korea. Furthermore, for the evaluation of evaporation estimates according to solar radiation models, 5 different evaporation estimation equations based on Penman's combination approach were applied, and evaporation estimates were compared with pan evaporation. Some solar radiation models require only meteorological data; however, some other models require not only meteorological data but also geographical data such as elevation. The study results showed that solar radiation model based on the ratio of the duration of sunshine to the possible duration of sunshine, maximum temperature, and minimum temperature provided the estimated solar radiation that most closely match measured solar radiation. Accuracy of estimated solar radiation also greatly improved when Angstrőm-Prescott model coefficients are adjusted to the study stations. Therefore, when choosing the solar radiation model for evaporation estimation, both data availability and model capability should be considered simultaneously. When applying measured solar radiation for estimating evaporation, evaporation estimates from Penman, FAO Penman-Monteith, and KNF equations are most close to pan evaporation rates in Jeonju and Jeju, Seoul and Mokpo, and Daejeon respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1746-1750
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• 2006

다양한 목적의 장기유출분석에 많이 적용되고 있는 4단 Tank 모형의 증발산관련 입력자료는 증발접시자료를 이용하거나 또는 장기간의 유량과 강수량의 차이로 정의되는 월별 손실량을 계산한 결과를 사용하고 있다. 증발접시자료는 자료 구득문제와 신뢰성 문제 등으로 인해 적용사례가 적고 통상 인근 관측지점의 손실량을 계산하고 이를 전이하여 적용하고 있다. 그러나 이러한 일증발산량 산정방법은 장기적인 유량 자료를 보유한 인근 관측지점이 있어야 적용할 수 있다는 점과 관측지점의 자료 신뢰성에 따라 유출결과에 큰 영향을 미칠수 있는 한계가 있다. 따라서 본 연구에서는 이러한 문제점을 개선하기 위하여 Hamon 방법과 Jensen-Haise 방법 및 FAO Penman-Monteith 방법을 검토하여 Tank 모형 계산에 필요한 실제증발산량을 산정할 수 있는 방안에 대해 모색하였다. 분석결과 유역별 실제손실량은 지형적인 영향을 받는 것으로 분석되었으며, 이를 통해 잠재증발산량을 실제증발산량으로 보정하는 월별보정계수를 지형인자로부터 추정하는 방법을 제안하였다.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.521-529
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• 2012

The evapotranspiration (ET) is one of the most important factor in the hydrological cycle. In this study, remote sensing based ET algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) was considered. Then, Priestley-Taylor algorithm was used for estimation of potential evapotranspiration in South Korea, and its spatial distribution was analyzed. Overall applicability between estimated potential evapotranspiration and weather station pan evaporation in Nakdong river basin was represented. The results using small pan showed that correlation coefficient in Pohang and Moonkyung Station was 0.70 and 0.55, respectively. However, the results using large pan showed correlation coefficient in Pohang and Moonkyung Station was 0.62 and 0.52, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4B
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• pp.399-412
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• 2010

The goal of this research is to apply the neural networks models for the temporal disaggregation of the yearly pan evaporation (PE) data, Republic of Korea. The neural networks models consist of multilayer perceptron neural networks model (MLP-NNM) and generalized regression neural networks model (GRNNM), respectively. And, for the performances evaluation of the neural networks models, they are composed of training and test performances, respectively. The three types of data such as the historic, the generated, and the mixed data are used for the training performance. The only historic data, however, is used for the testing performance. From this research, we evaluate the application of MLP-NNM and GRNNM for the temporal disaggregation of nonlinear time series data. We should, furthermore, construct the credible monthly PE data from the temporal disaggregation of the yearly PE data, and can suggest the available data for the evaluation of irrigation and drainage networks system.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.781-793
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• 2017

In this study, applicabilities of aerodynamic approaches for the estimation of pan evaporation were evaluated on 56 study stations in South Korea. To accomplish this study purpose, previous researchers' evaporation estimation equations based on aerodynamic approaches were grouped into seven generalized evaporation models. Furthermore, four multiple linear regression (MLR) models were developed and tested. The independent variables of MLR models are meteorological variables such as wind speed, vapor pressure deficit, air temperature, and atmospheric pressure. These meteorological variables are required for the application of aerodynamic approaches. In order to consider the effect of autocorrelation, MLR models were developed after differencing variables. The applicability of MLR models with differenced variables was compared with that of MLR models with undifferenced variables and the comparison results showed no significant difference between the two methods. The study results have indicated that there is strong correlation between estimated pan evaporation (using aerodynamic models and MLR models) and measured pan evaporation. However, pan evaporation are overestimated during August, September, October, November, and December. Most of meteorological variables that are used for MLR models show statistical significance in the estimation of pan evaporation. Vapor pressure deficit was turned out to be the most significant meteorological variable. The second most significant variable was air temperature; wind speed was the third most significant variable, followed by atmospheric pressure.

• Journal of Korea Water Resources Association
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• v.40 no.1 s.174
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• pp.73-88
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• 2007

The goal of this research is to develop and apply the generalized regression neural networks model(GRNNM) embedding genetic algorithm(GA) for the estimation and calculation of the pan evaporation(PE), which is missed or ungaged and of the alfalfa reference evapotranspiration ($ET_r$), which is not measured in South Korea. Since the observed data of the alfalfa 37. using Iysimeter have not been measured for a long time in South Korea, the Penman-Monteith(PM) method is used to estimate the observed alfalfa $ET_r$. In this research, we develop the COMBINE-GRNNM-GA(Type-1) model for the calculation of the optimal PE and the alfalfa $ET_r$. The suggested COMBINE-GRNNM-GA(Type-1) model is evaluated through training, testing, and reproduction processes. The COMBINE-GRNNM-GA(Type-1) model can evaluate the suggested climatic variables and also construct the reliable data for the PE and the alfalfa $ET_r$. We think that the constructive data could be used as the reference data for irrigation and drainage networks system in South Korea.