• 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 The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.95-105
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• 2019

Evapotranpiration (ET) is one of the important factor in Hydrological cycle and irrigation planning. In this study, temperature-based artificial neural network (ANN) model for daily reference crop ET estimation was developed and compared with reference crop evapotranpiration ($ET_0$) from FAO-56 Penman-Monteith method (FAO-56 PM) and parameter regionalized Hargreaves method. The ANN model was trained and tested for 10 weather stations (5 inland stations and 5 costal stations) and two input climate factors, maximum temperature ($T_{max}$), minimum temperature ($T_{min}$), and extraterrestrial radiation (RA) were used for training and validation of temperature-based ANN model. Monthly reference ET by the ANN model also compared with parameter regionalized Hargreaves method for ANN model applicability evaluation. The ANN model evapotranspiration demonstrated more accordance to FAO-56 PM evapotranspiration than the $ET_0$ from parameter regionalized Hargreaves method(R-Hargreaves). The results of this study proposed that daily reference crop ET estimated by the ANN model could be used in the condition of no sufficient climate data.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.5
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• pp.1-9
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• 2010

Evapotranspiration (ET) is one of the basic components of the hydrologic cycle and is essential for estimating irrigation water requirements. In this study, artificial neural network (ANN) models for reference crop evapotranspiration ($ET_0$) estimation were developed on a monthly basis (May~October). The models were trained and tested for Suwon, Korea. Four climate factors, daily maximum temperature ($T_{max}$), daily minimum temperature ($T_{min}$), rainfall (R), and solar radiation (S) were used as the input parameters of the models. The target values of the models were calculated using Food and Agriculture Organization (FAO) Penman-Monteith equation. Future climate data were generated using LARS-WG (Long Ashton Research Station-Weather Generator), stochastic weather generator, based on HadCM3 (Hadley Centre Coupled Model, ver.3) A1B scenario. The evapotranspirations were 549.7 mm/yr in baseline period (1973-2008), 558.1 mm/yr in 2011-2030, 593.0 mm/yr in 2046-2065, and 641.1 mm/yr in 2080-2099. The results showed that the ANN models achieved good performances in estimating future reference crop evapotranspiration.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.473-473
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• 2011

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily reference evapotranspiration (ETo) 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 consists 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 ETo 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 ETo modeling can be generalized using GMDH-NNM.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.193-193
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• 2017

Trend analysis can enhance our knowledge of the dominant processes in the area and contribute to the analysis of future climate projections. The results of previous studies in South Korea showed that southeast regions of Korea had the highest value of evapotranspiration. Thereby, it is of interest to determine the trend analysis in hydrological variables in this area. In this study, the recent 35 year trends of precipitation, reference evapotranspiration, and aridity index in monthly and annual time scale will be analyzed over three stations (Pohang, Daegu, and Pusan) of southeast Korea. After removing the significant Lag-1 serial correlation effect by pre-whitening, non-parametric statistical Mann-Kendall test was used to detect the trends. Also, the slope of trend of the Mann-Kendall test was determined by using Theil-Sen's estimator. The results of the trend analysis of reference evapotranspiration on the annual scale showed the increasing trend for the three mentioned stations, with significant increasing trend for Pusan station. The results obtained from this research can guide development if water management practices and cropping systems in the area that rely on this weather stations. The approaches use and the models fitted in this study can serve as a demonstration of how a time series trend can be analyzed.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.1
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• pp.89-99
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• 2018

This study analyzed the change of the dam inflow and evapotranspiration in the Soyanggang dam basin using the results of 26 CMIP5 GCMs based on AR5 RCP 4.5 and RCP 8.5 scenarios. The SWAT model was used to simulate the dam inflow and evapotranspiration in the target watershed. The simulation was performed during 2010~2016 as the reference year and during 2010~2099 as the analysis period. Bias correction of input data such as precipitation and air temperature were conducted for the reference period of 2006~2016. Results were analyzed for 3 different periods, 2025s (2010~2040), 2055s (2041~2070), and 2085s (2071~2099). It demonstrated that the change of dam inflow gradually increases 9.5~15.9 % for RCP 4.5 and 13.3~29.8 % for RCP 8.5. The change of evapotranspiration gradually increases 1.6~8.6 % for RCP 4.5 and 1.5~8.5 % for RCP8.5.

• KCID journal
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• v.6 no.2
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• pp.37-46
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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 and compare reference crop evapotranspiration at 13 stations by REF-ET model. The three smallest 10-year return period 7-month(Apri

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.137-149
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• 2019

Accurate estimation of reference evapotranspiration (RET) is important to quantify crop evapotranspiration for sustainable water resource management in hydrological, agricultural, and environmental fields. It is estimated by different methods from direct measurements with lysimeters, or by many empirical equations suggested by numerous modeling using local climatic variables. The potential to use some such equations depends on the availability of the necessary meteorological parameters for calculating the RET in specific climatic conditions. The objective of this study was to determine the proper RET equations using limited climatic data and to analyze the temporal and spatial trends of the RET in South Korea. We evaluated the FAO-56 Penman-Monteith equation (FAO-56 PM) by comparing several simple RET equations and observed small fan evaporation. In this study, the modified Penman equation, Hargreaves equation, and FAO Penman-Monteith equation with missing solar radiation (PM-Rs) data were tested to estimate the RET. Nine weather stations were considered with limited climatic data across South Korea from 1973 - 2017, and the RET equations were calculated for each weather station as well as the analysis of the mean error (ME), mean absolute error (MAE), and root mean square error (RMSE). The FAO-56 PM recommended by the Food Agriculture Organization (FAO) showed good performance even though missing solar radiation, relative humidity, and wind speed data and could still be adapted to the limited data conditions. As a result, the RET was increased, and the evapotranspiration rate was increased more in coastal areas than inland.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.3
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• pp.25-35
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• 2009

Climate change due to global warming possibly effects the agricultural water use in terms of evapotranspiration. Thus, to estimate rice evapotranspiration under the climate change, future climate data including precipitation, minimum and maximum temperatures for 90 years ($2011{\sim}2100$), were forecasted using LARS-WG. Observed 30 years ($1971{\sim}2000$) climate data and climate change scenario based on SRES A2 were prepared to operate the LARS-WG model. Using these data and FAO Blaney-Criddle method, reference evapotranspiration and rice evapotranspiration were estimated for 9 different regions in South Korea and rice evapotranspiration of 10 year return period was estimated using frequency analysis. As the results of this study, rice evapotranspiration of 10 year return period increased 1.56%, 5.99% and 10.68% for each 30 years during $2011{\sim}2100$ (2025s; $2011{\sim}2040$, 2055s; $2041{\sim}2070$, 2085s; $2071{\sim}2100$) demonstrating that the increased temperature from the climate change increases the consumptive use of crops and agricultural water use.