• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.93-101
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• 2019

This study aims to analyze the influences of applications of two different evapotranspiration (ET) estimation methods on the irrigation water requirements (IWR) for paddy rice and water supply reliability of agricultural reservoirs. The modified Penman (MP), traditional method, and the Penman-Monteith (PM), the new adopted method, were applied on 149 reservoirs located in Honam province for this study. The weather date was used from 1987 to 2016, and analysed the trends of temperature and rainfall during rice growing season between past and current 10 years respectively. The increased average temperature and rainfall were observed from the current 10 years compared to the past years. This phenomena impacts on the results of ET and IWR estimations with decreased IWR obtained from high rainfall regions and increased ET obtained high temperature regions. For the comparisons of application results of two ET approaches, the PM method showed lower ET and IWR, and hence more reliable storage capacity of the reservoirs respect to water supply to paddy fields. The results also showed that the influences of different ET methods applications on the water supply reliability of reservoirs are negligible for the cases of over 3.7 watershed ratio and 670 mm unit reservoir storage, while significant variations of the results obtain from the applications between two ET approaches for the opposite cases. Further studies are necessary to consider various field conditions for practical applications of the PM method estimating ET in the fields of paddy farming.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.341-341
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• 2019

물 순환과정의 구성요소 중 증발산(Evapotranspiration)은 수자원개발을 위한 계획의 수립과 수자원 시스템 운영적 측면에서 대단히 중요한 부분이다. 증발산량을 산정하기 위해서는 온도, 바람, 상대습도, 대기압, 수질 및 수표면의 성질과 형상 등을 산정하여야 하는데 이러한 기상자료들을 확보하기란 매우 어려운 실정이다. 본 연구에서는 기온자료만을 이용하여 기준증발산량을 산정할 수 있는 Hargreaves 공식의 경험적 매개변수 및 온도 매개변수를 수정하여 경안천유역의 기준증발산량을 산정하였다. 수정된 공식의 성능평가를 위해 현재 널리 사용되고 있는 Penman-Monteith 방법을 이용하여 산정된 기준증발산량을 정해로 가정하여 Root Mean Square Error와 Nash Sutcliffe Model Efficiency Coefficient분석을 수행하여 검증하였다. 또한 기온 및 Hargreaves 경험적 매개변수와의 상관관계를 이용한 회귀식에 대한 검증을 수행함으로써 본 연구에서 제안한 수정된 공식의 적용가능성을 확인하였으며, 향후 수자원 시스템 운영 측면에 도움이 될 것으로 판단된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.199-213
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• 2008

The goal of this research is to develop and apply the integrational operation method (IOM) for the modeling of the monthly pan evaporation (PE) and the alfalfa reference evapotranspiration ($ET_r$). Since the observed data of the alfalfa $ET_r$ using lysimeter have not been measured for a long time in Republic of Korea, Penman-Monteith (PM) method is used to estimate the observed alfalfa $ET_r$. The IOM consists of the application of the stochastic and neural networks models, respectively. The stochastic model is applied to generate the training dataset for the monthly PE and the alfalfa $ET_r$, and the neural networks models are applied to calculate the observed test dataset reasonably. Among the considered six training patterns, 1,000/PARMA(1,1)/GRNNM-GA training pattern can evaluate the suggested climatic variables very well and also construct the reliable data for the monthly PE and the alfalfa $ET_r$. Uncertainty analysis is used to eliminate the climatic variables of input nodes from 1,000/PARMA(1,1)/GRNNM-GA training pattern. The sensitive and insensitive climatic variables are chosen from the uncertainty analysis of the input nodes. Finally, it can be to model the monthly PE and the alfalfa $ET_r$ simultaneously with the least cost and endeavor using the IOM.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.225-225
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• 2016

잠재증발량에 대한 많은 경험식들이 제시되어 있지만 각각의 방식에 대한 국내의 적용성에 대하여 구체적으로 비교검토된 사례는 매우 제한적이다. 널리사용되고 있는 Hargreaves식은 비교적 단순한 형태를 지니고 있으나 대기수분량을 계산에 반영치 못하는 한계를 지니고 있다. 본 연구에서는 남한 내 다목적 댐 유역의 1973-2014년 기상자료를 바탕으로 Penman-Monteith (P-M) 식과 Hargreaves식을 통해 계산한 잠재증발산량($ET_{PM}$, $ET_{Harg}$)의 비교를 통해, Bouchet (1963)의 보완 관계 관점에서 $ET_{Harg}$가 $ET_{PM}$에 비해 과다 산정되는 경향이 있음을 확인하였다. 이에, 1973-2004년에 대한 각 댐 유역의 기상관측소 단위별로 산정된 $ET_{PM}$을 상대적인 정해로 간주하여 Hargreaves식의 매개변수를 추정하였다. 추정된 매개변수는 동일 관측소의 2005-2014년 기상자료와 함께 Hargreaves식에 적용 후, 다목적 댐 유역별 $ET_{PM}$과 $ET_{Harg}$을 산정하여 검정을 수행하였다. 수행 결과, Hargreaves 식의 매개변수 조정 전 $ET_{PM}$과의 Nash-Sutcliffe 일치계수는 0.47-0.79 (1973-2004), 0.28-0.76 (2005-2014)이었고, RMS 오차는 17.79-25.85 (1973-2004), 18.24-27.40 (2005년-2014년)이었으나, 매개변수 조정 후 Nash-Sutcliffe 일치계수는 0.96-0.98 (1973-2004), 0.95-0.98 (2005-2014)로, RMS 오차는 5.78-7.11 (1973-2004), 4.97-6.95 (2005-2014)로 조정 전 보다 향상된 결과를 보였다.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.93-98
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• 1999

This study is performed to select irrigation design year from 10-year return period 7-month(April to October) precipitation amount and compare reference crop evapotranspiration at 13 regions by REF-ET model. 1. Seven-month growing season average reference crop evapotranspiration values showed low values of 4.1 ∼4.2mm /day by FAO-24 Corrected Penman method, and 3.6 ∼3.7mm/day by FAP-24 Blaney Criddle method in Chinjin and Ulsan, high values of 4.9mm/day by FAO-24 Corrected Penman method , 4.1mm/day by FAO -24 Blaney Criddle method in Mokpo and Pohang. 2. Estimated seven-month growing season average reference crop evapotranspirations are 4.6mm/day by FAO-24 Corrected Penman method, 3.9,mm/day by FAO-24 Balney Criddle method, 4.0mm/day 1985 Hargreaves method, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.459-469
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• 2010

This study is to develop a grid-based daily runoff model considering seasonal vegetation canopy condition. The model simulates the temporal and spatial variation of runoff components (surface, interflow, and baseflow), evapotranspiration (ET) and soil moisture contents of each grid element. The model is composed of three main modules of runoff, ET, and soil moisture. The total runoff was simulated by using soil water storage capacity of the day, and was allocated by introducing recession curves of each runoff component. The ET was calculated by Penman-Monteith method considering MODIS leaf area index (LAI). The daily soil moisture was routed by soil water balance equation. The model was evaluated for 930 $km^2$ Yongdam watershed. The model uses 1 km spatial data on landuse, soil, boundary, MODIS LAI. The daily weather data was built using IDW method (2000-2008). Model calibration was carried out to compare with the observed streamflow at the watershed outlet. The Nash-Sutcliffe model efficiency was 0.78~0.93. The watershed soil moisture was sensitive to precipitation and soil texture, consequently affected the streamflow, and the evapotranspiration responded to landuse type.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1067-1071
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• 2008

장기적인 수자원정책을 수립하기 위해서는 강수, 증발산, 유출 등의 물수지의 변동성을 평가하는 것이 중요하다. 특히 기후변화로 인한 기온 증가는 증발산량에 영향을 미칠 것이다. 따라서 기후변화에 따른 수자원의 영향을 신뢰성 있게 평가하기 위해서는 증발산량의 산정방법에 대한 불확실성을 평가하는 것이 필요하다. 본 연구에서는 다섯 가지의 증발산량 산정방법에 대해 기온 및 강수변화에 따라 증발산량 계산과 유출량산정에 미치는 영향을 평가하였다. 안동댐 유역에 대해 준분포형 수문모형인 SLURP를 이용하여 기온과 강수변화에 따른 5가지 증발산량 산정방법의 민감도를 분석하였다. SLURP 모형에서는 Penman-Monteith method, Morton CRAE method, Spittlehouse/Black method, Granger method, Linacre method의 다섯 가지방법을 제시하고 있고, 관측 자료에 대해 검 보정을 수행한 결과 5개의 증발산량 산정법 모두 안동댐 유역에 대해 잘 모의하는 것으로 나타났다. 기온과 온도를 변화시킨 합성시나리오에서 Linacre 방법이 다른 방법들과 비교하여 높은 민감도를 나타내었는데 증발산량 산정법별 구조적 차이가 원인 것으로 판단되어 추가적인 연구가 진행 중이다. 결과적으로 각 증발산량 산정방법에 따른 민감도 차이는 기후변화 영향평가 결과의 불확실성을 제시하는 척도가 될 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.184-184
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• 2020

수자원 계획 및 관리 시 증발산량의 정량적 분석은 필수적으로 고려되는 사항 중 하나이다. 일단위 이하의 잠재증발산량 산정은 세계식량기구(FAO)가 Penman-Monteith 방법을 기반으로 개발한 FAO56 PM 방법을 주로 활용하며, 이는 다른 방법에 비하여 높은 정확성과 적용성이 뛰어나다. 그러나 FAO56 PM 방법의 입력 매개변수는 다양한 기상자료이며, 장기간의 신뢰성 높은 자료를 구축하는 것은 어려운 실정이다. 이에 본 연구에서는 증발산량 공식인 Hargreaves 공식을 활용하여 FAO56 PM 방법으로 산정된 잠재증발산량과 기온차 사이의 시계열 관계를 재구성한 회귀분석 기법을 개발하였다. 개발된 모형에 유역면적을 적용하여 유역면적별 잠재증발산량을 산정하였으며, 이를 기존의 잠재증발산량과의 비교를 통해 모형의 적합성을 평가하였다. 결과적으로, 복잡한 잠재증발산량식을 단순한 대체모형(surrogate model)으로 제시함으로써 효율적인 증발산량 정량적 평가와 제한적인 기상자료 조건에 보편적 활용이 가능하다. 향후 연구에서는 회귀분석방법에 Bayesian 추론기법을 활용하여 구성함으로 잠재증발산량의 불확실성을 정량적으로 표현하고자 한다.