• Current Research on Agriculture and Life Sciences
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• v.3
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• pp.28-35
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• 1985

This work Was carried out to obtain the most suitable crop coefficient for the paddy rice growing in Taegu area. The result was due to the comparative measurements of evapotranspiration formula in terms of Blaney & Criddle and eight other formulas with those produced by experiment particularly in this area. The crop coefficient, evapotranspiration and transpiration ratio produced by this research are hopefully expected to be of service in the future calculation of evapotranspiration without repeating experiment respectively, whenever the water requirement of paddy rice is planned in Taegu and its vicinity. The accomplished results could be summarized as follows : The maximum amount of evapotranspiration was recorded in the early and middle parts of August. The average reading of evapotranspiration was 6.33mm/day throughout the growth. The evapotranspiration had a highly significant correlation with pan evaporation, solar radiation, sunshine hours and relative humidity of meteorological elements. K and Kc by the use of Blaney & Criddle formula calculated at 0.76 to 1.45 and 0.82 to 1.27, respectively. Its peak value appeared commonly in early August. The ratio of transpiration was 269.03.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.193-199
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• 2000

In order to provide basic information for the estimation of reference crop evapotranspiration in the greenhouse, an lysimeter experiment was performed. Kenturky Blue Grass was used as a reference crop. Relationships between measured reference crop evapotranspiration and weather factors were analyzed. A multi-regression model was developed and tested.

• Journal of Korea Water Resources Association
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• v.41 no.2
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• pp.212-228
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• 2008

Five representative reference evapotranspiration(RET) equations were selected, and these equations were compared with pan evaporation by correlation analysis. Pan coefficients were also estimated. Furthermore, five selected RET equations were compared to find the similarity among those at the 21 meteorological stations located in South Korea. Five RET equations selected from 4 different category were Penman(combination approach), FAO Penman-Monteith(FAO P-M) (single source approach), Makkink and Priestley-Taylor (radiation approach) and Hargreaves(temperature approach) equations. In this study, the geographical and topographical conditions were considered for the selection of study stations. The daily meteorological data measured from 1970 at an interval of 5 years were applied in this study. The evapotranspiration estimates obtained by applying evapotranspiration equations were evaluated with numerical and graphical methods. The correlation coefficients between pan evaporation and RET in study stations were above 0.9 indicating very high correlation; however, the slopes of the individual regression lines show the values greater or less than 1.0. Hargreaves equation(temperature approach) shows the most similar evapotranspiration estimates to those of FAO P-M equation from 12 study stations, which are located near to seashore except Daegu station. On the other hand, Priestley-Taylor equation(radiation approach) shows the most similar evapotranspiration estimates to those of FAO P-M equation from 8 study stations, which are located in inland.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.363-363
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• 2018

본 연구에서는 제주도 지역을 대상으로 현재의 용수공급 보장량을 기준으로 미래 인위적 자연적 요인에 따른 수요량의 변화를 고려하여 농업용수 과부족을 분석하였다. 인위적인 요인으로서 작물재배면적의 변화를 고려하였으며, 자연적인 요인으로서는 기후변화 영향을 고려하였다. 제주도의 유출특성과 지질특성, 물이용 특성 등을 고려하여 유역 물수지 기반의 순물소모량 개념을 활용하여 수요량을 추정하였으며, 농업용수 보장량(공급량)은 "제주특별자치도 농업용수 관리계획(2013-2022)"에서 제시하는 값을 적용하였다. 순물소모량 산정에 필요한 실제증발산량 및 잠재증발산량 등은 유역모형인 SWAT (Soil and Water Assessment Tool)을 이용하여 산정하였다. 인위적인 변화로서 2020년 작물재배면적 추정치를 적용하여 용수 과부족을 분석한 결과, 구좌읍과 성산읍 2개 지역에서 수요량이 보장량을 초과하는 것으로 나타났다. 참고로 기존의 필요수량 개념의 수요량을 적용했을 때에는 제주시 동지역, 구좌읍, 조천읍, 서귀포시 동지역, 성산읍, 표선면, 남원읍, 안덕면, 대정읍 등 9개 지역에서 용수가 부족할 것으로 분석된 바 있다. 미래 기후변화 영향을 고려하기 위하여 IPCC (International Panel on Climate Chnage) CMIP5(the fifth phase of the Coupled Model Intercomparison Project)에서 제시하는 대순환모델 중 9개 모형의 결과를 활용하여 미래(2010~2099년)의 수요량을 산정하고, 앞서 적용한 2020년 재배면적 추정치와 보장량을 기준으로 지역별, 시기별로 농업용수 과부족을 분석하였다. 기후변화 시나리오는 RCP 4.5와 RCP 8.5 결과를 적용하였다. 인위적인 영향에 대한 분석과 마찬가지로 구좌읍과 성산읍을 제외하고는 수요량 대비 보장량이 충분한 것으로 분석되었다. 시나리오에 따른 영향은 RCP 8.5 보다는 RCP 4.5 시나리오에서의 보장률이 상대적으로 높게 나타났으며, 2개 시나리오 모두 미래 후반기로 갈수록 수요량의 증가에 따라 보장률이 점차 감소하는 것으로 나타났다. 다만, 이 분석은 재배면적의 변화가 없이 단순히 기상조건의 변화만을 적용한 전망으로서, 향후 실제 기상여건과 재배면적, 물이용, 용수공급체계, 물관리 정책방향 등의 변화에 따라 좌우될 수 있다.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.1
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• pp.47-55
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• 2011

기후변화는 피할 수 없으며 다음 세기에도 계속될 것이다. 이는 생태계와 토지와 물과 같은 자연자원의 이용에도 영향을 미칠 것이다. 연구 결과에 의하면 아프리카는 낮은 경제수준과 지역적 다양성으로 인하여 기후변화에 가장 취약한 지역 중의 하나이다. 짐바브웨는 한계농지가 황폐화가 되는 등 농업분야가 특히 기후변화에 취약하다. 본 논문에서는 짐바브웨의 주요 옥수수 재배지역에 대하여 기후변화가 옥수수의 필요수량에 미치는 영향을 공간적 및 시간적으로 분석하였다. 미래 기후예측은 HadCM3 전지구 모형 결과에 change factor를 곱하여 추정하였다. 배출가스 시나리오는 A2b 및 B2a를 선정하였고, 시간대는 2020s, 2050s 및 2080s 각각 30년간에 대하여 분석하였다. 기준작물 증발산량은 Penman-Monteith 공식으로, 순관개량은 CROPWAT 모형을 이용하여 구하였다. 순관개량의 공간적인 분석은 GIS를 이용하였다. 분석 결과 대상지역은 강우량이 감소하고 관개의 필요성이 크게 증가할 것으로 나타났다. 2080s의 필요수량은 기준년도 (1961-1990)에 비하여 93 내지 115 % 증가할 것으로 예측되었다. 이 증가는 기온의 증가와 강우량의 감소에 기인한다. 대상 지역에 대한 기후변화 대응 전략 수립과 영향 저감대책에 대한 추가적인 연구가 필요하다고 하겠다.

• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.11-20
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• 2007

Estimation of crop consumptive use is a key term of agricultural water resource systems design and operation. The 10-year return period drought has special aspects as a reference period in design process of irrigation systems in terms of agricultural water demand analysis so that crop evapotranspiration (ETc) about the return period also has to be analyzed to assist understanding of crop water requirement of paddy rice. In this study, The ETc of 10-year return period drought was computed using frequency analysis by 54 meteorological stations. To find an optimal probability distribution, 8 types of probability distribution function were tested by three the goodness of fit tests including ${\chi}^2$(Chi-Square), K-S (Kolmogorov-Smirnov) and PPCC (Probability Plot Correlation Coefficient). Optimal probability distribution function was selected the 2-parameter Log-Normal (LN2) distribution function among 8 distribution functions. Using the two selected distribution functions, the ETc of 10-year return period drought was estimated for 54 meteorological stations and compared with prior study results suggested by other researchers.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.3
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• pp.254-261
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• 1988

Lysimeter and field experiments were conducted in Sandy Loam to establish a simple estimation model for evapotranspiration (ET) of soybean for three years (l984-1986). Potential ET (PET) could be estimated by the eq.1 using Pan-evaporation (Eo) and was ranged from 1.1 to 4.6 mm/day during the experiments. PET (mm/day)=1.348＋0.573 Eo …(1) Crop coefficient (Kc=maximum ET/PET) could be estimated by the eq.2 using Growth degree (G=days after planting/total growing days) and was ranged from 0.2 to 1.1 and from 0.6 to 1.4 for monoculture cropping and double cropping followed by barley, respectively, during the experiments. Monoculture : Kc=0.016＋3.719 G-3.224 G$^2$…(2), Double cropping : Kc=0.609＋2.014 G-2.120 G$^2$…(2). However, the maximum Kc was shown when G was about 50% and 40% for the monoculture and the double cropping, respectively. Soil water coefficient (f=AET/maximum ET) could be estimated by the eq.3 using soil water tension (Ψ) in 15cm depth. and it was decleased to 0.2 when Ψ was 10 bar. f=0.755-0.537 log │Ψ│…(3) Consequentially, the model to estimate the Actual ET (AET) of soybean was determined as eq.4 with the correction coefficient of -0.380. AET(mm/day)=PETㆍKcㆍf -0.380 …(4) The estimated AET were compared with the measured AET to verify the model established above. The average deviation of the estimated ET(AET) was 0.5782$\pm$0.338 (mm/day), and it would be within reasonable confidence range.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.3
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• pp.15-25
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• 2018

Estimating the reference evapotranspiration is an important factor to consider in irrigation system design and agricultural water use. However, there is a limitation in using the FAO Penman-Monteith (FAO P-M) equation, which requires various meteorological data. The purpose of this study is to compare three reference evapotranspiration (ETo) equations in the case of meteorological data missing for 11 study weather stations. Firstly, the FAO P-M equation is used for reference potential evapotranspiration estimation with the actual solar radiation data $R_n$ and the actual vapor pressure $e_a$. Then, in the case of $R_n$, and $e_a$ are missed, the reference evapotranspirations applying FAO P-M, Priestley-Taylor (P-T), Hargreaves (HG) equation were calculated using other meteorological factors. Secondly, MAE, RMSE, $R^2$ were calculated to compare ETo relationship from the ETo equations. From the results, ETo with Hargreaves equation in coastal areas and the Priestley-Taylor equation in the inland areas showed relatively high correlation with FAO P-M when $e_a$ data is missed. In the case of $R_n$ data is missed or two weather data, $e_a$, and $R_n$ data are all missed, $R^2$ value in Priestley-Taylor equation was highest in coastal areas, and $R^2$ values in Hargreaves equation were the high values for 7 inland areas. The results of sensitivity analysis showed that net radiation was the most sensitive for P-T and HG equation, and for FAO P-M, the most sensitive factor was net radiation and relative humidity, air temperature and wind speed were follows. Therefore, in considering of the accessibility to the coast, the types of the missing wether data, and the correlation and the magnitude of error, the reference evapotranspiration equations would be selected in sense of different conditions.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.577-587
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• 2021

Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.