• KOREAN JOURNAL OF CROP SCIENCE
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• v.45 no.4
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• pp.241-244
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• 2000

This experiment was conducted to evaluate the effect on evapotranspiration and yield of soybean according to different soil water conditions, and to find the optimum time and amount for irrigation in soybean cultivation. The difference between potential evapotranspiration (PET) and maximum evapotranspiration (MET) during growing season of soybean planted in lysimeter was higher during reproductive stage than during vegetative one. The maximum crop coefficient was obtained at beginning seed stage of soybean. Soil water coefficient of irrigation treatment was higher than that of non-irrigation treatment during soybean growth stage in field experiment. Grain yield was highest in lysimeter due to its high water use efficiency and evapotranspiration rate.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.6
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• pp.103-112
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• 2001

The development of infrared thermometry has led many researchers to use plant temperatures, and specifically the temperature of the crop canopy in the field, for estimating the water stress of a crop. The purpose of this study was to evaluate the role of leaf temperature in irrigation scheduling. An experiment was carried out in a greenhouse with chinese cabbage. Leaf temperature was measured with infrared thermometry and evapotranspiration of the crop was measured by lysimeters. Influence of the difference between leaf temperature and air temperature on crop evapotranspiration was evaluated under varying water stress condition. A further objective was to evaluate the effect of other climatic variables on the relationship between evapotranspiration and temperature difference between leaf and air. A statistical model for estimating evapotranspiration using the temperature difference, relative humidity. and radiation was developed and tested. Crop water stress index was calculated using vapour pressure deficit and the temperature difference. Relations between the crop water stress index and crop evapotranspiration was tested. The index was closely related with evapotranspiration.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.4
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• pp.50-56
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• 2001

In order to provide basic information for the estimation of reference crop evapotranspiration in the greenhouse on experiment was performed. Daily evapotranspiration of the reference crop wear measured using lysimeters. kentucky Blue Grass was used as a reference crop. Climatic elements I the greenhouse such as air temperature relative humidity and radiation were measured. The influence of each climatic element on the evapotranspiration were analyzed. A multi-regression model for the estimation of reference crop evapotranspiration in the greenhouse was developed and tested simulated evapotranspiration by the model were in good agreement with measured evapotransiration.

• 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.

• 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.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.151-156
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• 2000

This study was to evaluate the effect of leaf temperature on daily evapotranspiration of crop. A transpiring crop will be cooled by the vaporization of water to a temperature below that of the surrounding air. Leaf temperature was measured a infrared thermometer. Crop evapotranspiration was measured by the method of lysimeter. A statistical model for estimating evapotranspiration was developed and tested. It was showed that the model was applicable.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1273-1281
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• 1993

Estimation of daily and seasonal evaportranspiration is essential for water resource planning irrigation feasibility study, and real-time irrigation water management . This paper is to evaluate the applicability of neural networks to the estimation of evapotranspiration . A neural network was developed to forecast daily evapotranspiration of the rice crop. It is a three-layer network with input, hidden , and output layers. Back-propagation algorithm with delta learning rule was used to train the neural network. Training neural network wasconducted usign daily actural evapotranspiration of rice crop and daily climatic data such as mean temperature, sunshine hours, solar radiation, relative humidity , and pan evaporation . During the training, neural network parameters were calibrated. The trained network was applied to a set of field data not used in the training . The created response of the neural network was in good agreement with desired values. Evaluating the neural networ performance indicates that neural network may be applied to the estimation of evapotranspiration of the rice crop.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.88-95
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• 1994

This paper is to evaluate the applicability of neural networks to the estimation of evapotranspiration. Two neural networks were developed to forecast daily evapotranspiration of the rice crop with back-propagation and counter-propagation algorithm. The neural network trained by back-propagation algorithm with delta learning rule is a three-layer network with input, hidden, and output layers. The other network with counter-propagation algorithm is a four-layer network with input, normalizing, competitive, and output layers. Training neural networks was conducted using daily actual evapotranspiration of rice crop and daily climatic data such as mean temperature, sunshine hours, solar radiation, relative humidity, and pan evaporation. During the training, neural network parameters were calibrated. The trained networks were applied to a set of field data not used in the training. The created response of the back-propagation network was in good agreement with desired values and showed better performances than the counter-propagation network did. Evaluating the neural network performance indicates that the back-propagation neural network may be applied to the estimation of evapotranspiration of the rice crop. This study does not provide with a conclusive statement as to the ability of a neural network to evapotranspiration estimating. More detailed study is required for better understanding and evaluating the behavior of neural networks.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.32-37
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• 2005

Crop evapotranspiration rates of the garlic, potato and carrot were measured in a lysimeter at the National Institute of Subtropical Agriculture. The crop coefficients were calculated using the values of the actually measured evapotranspiration(ETcrop) and the reference crop evapotranspiration (ETo) estimated by the Penman-Monteith equation. The maximum crop coefficients of the garlic, potato, carrot and cabbage were 1.07, 1.07, 0.73 and 0.92 respectively. For the Citrus Aoshima Unshiu and Hallabong in the plastic house, the maximum crop coefficients were 1.38 and 1.29 respectively. Computer program using EXCEL was also developed to estimate the crop water use.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.247-250
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• 2003

Crop evapotranspiration rates of the garlic and potato were measured in a lysimeter at National Jeju Agricultural Experiment Station, Rural Development Administration, Korea. The crop coefficients were calculated using the values of the actually measured evapotranspiration(ETcrop) and the reference crop evapotranspiration (ETo) estimated by the Penman-Monteith equation. The maximum crop coefficients of the potato and garlic were 1.07 and 1.31 respectively. A water requirement model using the moisture accounting method is presented. The moisture accounting method is illustrated by the example (Table 2). As soon as the accumulated deficit exceeds 22 mm, a further irrigation is supplied.