• 한국농공학회논문집
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• 제51권3호
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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.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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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.

• 한국농공학회지
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• 제36권2호
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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.

• 물과 미래
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• 제5권2호
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• pp.44-48
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• 1972

This article includes hydrometeorological analysis of evapotranspiration and precipitation, which are used available basic data for a certain basin water budget. Evapotranspiration on water surface, bare soil and rice fields is directly measured by Thornthwaite's type Lysimeter and on water surface and vegetables computed using the Penman's equation. Areal precipitation is analized through the Thiessen method and arithmatic mean method. It is interested fact that the correlation coefficient for Class A Pan's evaporation vs. the actual evapotranspiration is the highest value among the coefficients for different type evaporimeter and Penman equation, and evaporation ratio on rice field's evapotranspiration vs. Class A Pan's evaporation is 1. 5-2. 3.

• 한국농공학회지
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• 제25권2호
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• pp.86-95
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• 1983

Evapotranspiration is a major factor determining the water consumption in the rice fields. Therefore, realistic evapotranspiration estimates are important to the agricultural water resources planning. In Korea, however, the Blaney-Criddle formula, which was developed under the meteorological condition of western arid United States and the upland cultivation, has been widely used to estimate evapotranspiration from paddy fields. Hence, it has considered that the Blaney-Criddle formula would not be the proper method for the Korean paddy condition. The purpose of this study is to select the most appropriate and realistic method for estimating evapotranspiraion from paddy field in Korea and to derive crop coefficients using the chosen method. The results are summerized as follows. 1. Total seasonal-average evapotranspiration by the field observation was 660mm for Tongil and 621. Ornm for the Japonica variety of rice. The amount of evapotranspiration for Tongil variety was 6% larger than that of the Japonica variety. 2. There was no significant differences in the amount of evapotranspiration among early, middle and late mature varieties, that is, early 638mm, middle 627mm and late 630mm for the whole growing season. 3. The rate of peak evapotranspiration appeared at the beginning of August and was in the range of 7.7-8. Omm/day according to the different mature varieties. 4. The correlation between pan evaporation data and the calculated evapotranspiration using related meteorological data from various methods suggested such as Radiation (FAO), Hargreaves, Christiansen, Hargreaves-Christiansen, Jensen-Haise, showed high statistic significance. Therefore, it seemed to use those formulars in estimating evapotranspiration inste4 of using pan evaporation data. 5. It was concluded from the analysis of field data that the evapotranspiration estimate for Blaney-Criddle method might not be appropriate in Korea. On the other hand, Penman equation showed more accurate estimation at the flourishing stage of rice than the pan evaporation method. 6. The crop coefficients for the Penman and pan-evaporation method were obtained by graphical representation.

• 한국농공학회논문집
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• 제52권3호
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• pp.57-64
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• 2010

The impacts of climate change on yield and evapotranspiration of rice have been modeled using AquaCrop model developed by Food and Agriculture Organization (FAO). Climate change scenario downscaled by Mesoscale Model 5 (MM5) regional model from ECHO-G General Circulation Model (GCM) outputs by Korea Meteorological Research Institute (METRI) was used in this study. Monthly average climate data for baseline (1971-2000) and three time periods (2020s, 2050s and 2080s) were used as inputs to the AquaCrop model. The results showed that the evapotranspiration after transplanting was projected to increase by 4 % (2020s), 8 % (2050s) and 14 % (2080s), respectively, from the baseline value of 464 mm. The potential rice yield was 6.4 t/ha and water productivity was 1.4 kg/$m^3$ for the baseline. The potential rice yield was projected to increase by 23 % (2020s), 55 % (2050s), and 98 % (2080s), respectively, by the increased photosynthesis along with the $CO_2$ concentration increases. The water productivity was projected to increase by 19 % (2020s), 44 % (2050s), and 75 % (2080s), respectively.

• 한국기후변화학회지
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• 제9권2호
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• pp.143-156
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• 2018

Evapotranspiration is a key element in designing and operating agricultural hydraulic structures. The profound effect of climate change to local agro-hydrological systems makes it inevitable to study the potential variability in evapotranspiration rate in order to develop policies on future agricultural water management as well as to evaluate changes in agricultural environment. The APEX-Paddy model was used to simulate local evapotranspiration responses to climate change scenarios. Nine Global Climate Models(GCMs) downscaled using a non-parametric quantile mapping method and a Multi?Model Ensemble method(MME) were used for an uncertainty analysis in the climate scenarios. Results indicate that APEX-Paddy and the downscaled 9 GCMs reproduce evapotranspiration accurately for historical period(1976~2005). For future periods, simulated evapotranspiration rate under the RCP 4.5 scenario showed increasing trends by -1.31%, 2.21% and 4.32% for 2025s(2011~2040), 2055s(2041~2070) and 2085s(2071~2100), respectively, compared with historical(441.6 mm). Similar trends were found under the RCP 8.5 scenario with the rates of increase by 0.00%, 4.67%, and 7.41% for the near?term, mid?term, and long?term periods. Monthly evapotranspiration was predicted to be the highest in August, July was the month having a strong upward trend while. September and October were the months showing downward trends in evapotranspiration are mainly resulted from the shortening of the growth period of paddy rice due to temperature increase and stomatal closer as ambient $CO_2$ concentration increases in the future.

• 한국농공학회지
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• 제37권E호
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• pp.72-78
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• 1995

To support some knowledge in planning irrigation system, short or long-term irrigation scheduling or determining irrigation reservoir capacity, it is necessary to estimate peak irrigation requirements and seasonal distribution of water demands for various return periods. In this paper Dry Day Index and Probable Evapotranspiration were evaluated to decide seasonal consumptive use of paddy rice for a design year using several decades' daily rainfall data and 5 years'('82~'86) actual evapotranspiration data, respectively. To obtain Dry Day Index that is defined as the number of probable dry days for a given period, Slade unsymmetrical distribution function was adopted. Dry Day Index was analysed for 5 and 10-day intervals. Each of them was evaluated with return periods of 1, 3, 5, 10 and 20 year. Their singnificance was tested by X$^2$ method. Based on these values, the Probable Evaportanspiration, that is the average daily ET both in dry days and rainy days during a given period, was estimated. Crop coefficient was also determined by the modified Penman equation proposed by Doorenbos & Pruitt.

• 한국농공학회논문집
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• 제59권4호
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• pp.27-42
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• 2017

The global rise in atmospheric $CO_2$ concentration and its associated climate change have significant effects on agricultural productivity and hydrological cycle. For food security and agricultural water resources planning, it is critical to investigate the impact of climate change on changes in agricultural productivity and water consumption. APEX-Paddy model, which is the modified version of APEX (Agricultural Policy/Environmental eXtender) model for paddy ecosystem, was used to evaluate rice productivity and evapotranspiration based on climate change scenario. Two study areas (Gimjae, Icheon) were selected and the input dataset was obtained from the literature. RCP (Representitive Concentration Pathways) based climate change scenarios were provided by KMA (Korean Meteorological Administration). Rice yield data from 1997 to 2015 were used to validate APEX-Paddy model. The effects of climate change were evaluated at a 30-year interval, such as the 1990s (historical, 1976~2005), the 2025s (2011~2040), the 2055s (2041~2070), and the 2085s (2071~2100). Climate change scenarios showed that the overall evapotranspiration in the 2085s reduced from 10.5 % to 16.3 %. The evaporations were reduced from 15.6 % to 21.7 % due to shortend growth period, the transpirations were reduced from 0.0% to 24.2 % due to increased $CO_2$ concentration and shortend growth period. In case of rice yield, in the 2085s were reduced from 6.0% to 25.0 % compared with the ones in the 1990s. The findings of this study would play a significant role as the basics for evaluating the vulnerability of paddy rice productivity and water management plan against climate change.

• 한국농공학회논문집
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• 제48권1호
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• pp.13-23
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• 2006

In 1998, Food and Agriculture Organization addressed that FAO Modified Penman method possibly over-estimates consumptive use of water comparing to the measured reference crop evapotranspiration (PET) and Penman-Monteith method can be better choice for accurate PET estimation. Nevertheless it is still difficult to find research efforts about paddy rice crop coefficient for Penman-Monteith method. This study aims to estimate paddy rice crop coefficients for Penman-Monteith and FAO modified Penman methods in the manner of comparing two equations. To estimate the crop coefficients, measured evapotranspiration data during 1982-1986 and 1995-1997 were used. The average Penman-Monteith crop coefficients ranged from 0.78 to 1.58 for translated paddy rice and from 0.87 to 1.74 for flood-direct seeded paddy rice. The average FAO Modified Penman crop coefficients ranged from 0.65 to 1.35 for translated paddy rice and from 0.70 to 1.58 for flood-direct seeded paddy rice.