• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.219-231
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• 2010

The Reference Evapotranspiration Calculator Software (REF-ET) supports computational guidelines for the reference evapotranspiration using seventeen FAO Penman-Monteith (PM) equations simultaneously such as the ASCE and FAO standardized forms. The REF-ET can conveniently consider missing data predictions and regional site characterizations, when reference ET is computed on monthly, daily, and hourly time steps. The applicability of the REF-ET was estimated to simulate the reference ET using hourly weather data from Seoul weather station for 29 years. The result found that the FAO24-Rd and 1957-Makk equations closely concerned with solar radiation parameter which were the most highly correlated to reference ET computed by pan coefficient. In addition, the 1957-Makk equation was identified as the most correct computational method for reference ET by analysis of bias and root mean square error. The 1957-Makk equation could predict the reference ET within the error of less than 1.06 mm/day, though all the other equations tended toward overestimation of predicting the reference ET in comparison with refecence ET of pan. The results of this study suggest that the REF-ET will be applicable to support reference ET estimation for a variety of field condition and time-scale.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.295-295
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• 2023

물수지 분석은 우리가 사용하는 물의 순환과정을 파악하여 우리 생활에 필요한 물을 안정적으로 공급하고 관리하기 위한 기초 자료이다. 물관리 기본법 제11조에도 유역 간의 물관리는 조화와 균형을 이루고 있는 기본원칙으로 설명되고 있으며 지속가능한 개발, 이용과 보전을 도모하고 물로인해 발생하는 재해를 예방하기 위해서는 유역단위로 관리되어야 함을 원칙으로 두고 있다. 최근 들어 국내에서는 강수량과 유량에 대한 조사가 급격히 발전함에 따라 정확도 높은 관측이 수행되고 있는 반면에 증발산량 같은 경우에는 경험식에 의존하여 측정자료를 산정하고 있는 실정이다. 증발산량은 눈에 보이지 않아 비교적 중요성을 인지하고 있지 못하나 강수량의 약 30~40%를 차지함으로 오차를 무시하기 어려우며 보다 정확한 관측이 필요하다. 실측으로는 증발접시가 있지만 물이 항상 차 있어야 하며, 팬의 가열, 강수 등 관측값 보정이 필요하다. 최근 기술의 발전으로 에디공분산 방법이 장비로 구현할 수 있게 되었으며 이러한 방법은 기존의 장비에서 발생되는 근본적인 문제점을 해결하였다. 특히 증발과 증산을 모두 측정이 가능하며 실제 증발산량 측정이 가능하다. 환경부에서는 에디공분산을 활용한 증발산량 관측소 13개소를 운영하고 있으며 관측소 인근 실제 유량측정하고 있는 지역과 연계하여 실측 기반의 물수지 검토를 수행해보고자 한다.

• Journal of Korea Water Resources Association
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• v.40 no.1 s.174
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• pp.89-99
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• 2007

Uncertainty analysis is used to eliminate the climatic variables of input nodes and construct the model of an optimal type from COMBINE-GRNNM-GA(Type-1), which have been developed in this issue(2007). The input variable which has the lowest smoothing factor during the training performance, is eliminated from the original COMBINE-GRNNM-GA (Type-1). And, the modified COMBINE-GRNNM-GA(Type-1) is retrained to find the new and lowest smoothing factor of the each climatic variable. The input variable which has the lowest smoothing factor, implies the least useful climatic variable for the model output. Furthermore, The sensitive and insensitive climatic variables are chosen from the uncertainty analysis of the input nodes. The optimal COMBINE-GRNNM-GA(Type-1) is developed to estimate and calculate the PE which is missed or ungaged and the $ET_r$ which is not measured with the least cost and endeavor Finally, the PE and $ET_r$. maps can be constructed to give the reference data for drought and irrigation and drainage networks system analysis using the optimal COMBINE-GRNNM-GA(Type-1) in South Korea.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.6-6
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• 2016

최근 전 지구적인 기후 변화에 따라 수문 순환을 이루고 있는 다양한 수문 기상 인자들의 변동성에 영향을 미치고 있다. 특히, 증발산은 수문순환을 구성하는 중요한 인자로서 대기와 지표간의 상호 작용을 파악하기 위해서는 이에 대한 정확한 이해 및 산정이 필수적이다. 일반적으로 증발산량을 산정하기 위해서 증발 접시 및 에디 공분산 기반 플럭스 타워에서 관측된 지점 자료만을 이용하여 증발산량의 변동성을 파악하는 연구들이 수행되어왔다. 그러나 지점 자료만을 이용하여 증발산량을 산출하게 되면 공간적인 변동성을 파악하는데 있어서 한계점이 발생하게 된다. 이러한 제약 사항을 해결하기 위해서, 인공위성 기반의 수문 기상인자를 물리식 기반 증발산량 산정식의 입력 자료로 구축하여 증발산량을 산정하고 이에 대한 시 간적인 변동성을 파악하는 연구들이 활발히 이루어지고 있다. 인공위성 기반 증발산량 산정 알고리즘의 대표적인 예로 공기동역학적 항과 에너지 수지 항들을 동시에 고려할 수 있는 Penman-Monteith 방법을 근간으로 수정하여 만들어낸 Remote Sensing based Penman-Monteith (RS-PM) 알고리즘이 있다. 그러나 RS-PM 기반의 증발산량 경우 태양복사열, 풍속, 온도, 습도와 같은 많은 수문기상인자들이 입력 자료를 요구한다. 이에 따라, 본 연구에서는 기존의 방법에 비해 상대적으로 적은 입력 자료를 사용하는 Modified Satellite-Based Priestley-Taylor (MS-PT) algorithm의 적용성을 평가하기 위해 MODerate-Resolution Imaging Spectroradiometer (MODIS) 자료를 이용하여 한반도에서 순복사에너지 (Net radiation) 및 실제 증발산량 (Actual evapotranspiration)을 산정하였다. 또한, 이에 대한 검증을 위해 청미천 유역에 설치되어있는 에디 공분산 기반 플럭스 타워에서 관측된 순복사 에너지 및 실제 증발산량에 대한 통계적 검증을 실시하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1147-1150
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• 2008

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of the support vector machines neural networks model (SVM-NNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The SVM-NNM in time series modeling is relatively new and it is more problematic in comparison with classifications. In this study, The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training, cross validation, and testing data, respectively. From this research, we evaluate the impact of the SVM-NNM and the MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1596-1599
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• 2010

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using GMDH-NNM.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1560-1563
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of support vector machine neural networks model (SVM-NNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of SVM-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.165-175
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• 2016

In order to examine the applicability, the evaporation estimation approaches based on solar radiation are classified into 3 different model groups (Model groups A, B, and C) in this study. Each group is tested in the 6 study stations (Seoul, Daejeon, Jeonju, Busan, Mokpo, and Jeju). The model parameters of each model group are estimated and verified with measured pan evaporation data. The applicability of verified model groups are compared with results of Penman (1948) combination approach. Nash-Sutcliffe (N-S) efficiency coefficients greater than 0.663 in all study stations indicate satisfactory estimates of evaporation. On the other hand, in the model verification process, N-S efficiency coefficients greater than 0.526 in all study stations indicate also satisfactory estimates of evaporation. However, N-S efficiency coefficients in all study cases except Model groups B and C in Busan are less than those of Penman (1948) combination approach. Therefore, it is concluded in this study that the evaporation estimation approaches based on solar radiation have capability to replace Penman (1948) combination approach for the estimation of evaporation in case that some meteorological data (wind speed, relative humidity) are missing or not measured.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.435-448
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• 2012

Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a sensitive hydrological factor with outer circumstances. Though both direct measurements with an evaporation pan and a lysimeter, and empirical methods using eddy covariance technique and the Bowen ratio have been widely used to observe ET accurately, they have a limitation that the observation can stand for the exact site, not for an area. In this study, remote sensing technique is adopted to compensate the limitation of ground observation using the Moderate Resolution Imaging Spectroradiometer (MODIS) multispectral sensor mounted on Terra satellite. We improved to evapotranspiration model based on remote sensing (Mu et al., 2007) and estimated Penman-Monteith evapotranspiration considering regional characteristics of Korea that was using only MODIS product. We validated evapotranspiration of Sulma (SMK)/Cheongmi (CFK) flux tower observation and calculation. The results showed high correlation coefficient as 0.69 and 0.74.