인공신경망모형을 이용한 기온기반 기준증발산량 산정
Estimating Reference Crop Evapotranspiration Using Artificial Neural Network and Temperature-based Climatic Data
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초록
Evapotranpiration (ET) is one of the important factor in Hydrological cycle and irrigation planning. In this study, temperature-based artificial neuralnetwork (ANN) model for daily reference crop ET estimation was developed and compared with reference crop evapotranpiration ( ) from FAO-56Penman-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 (Tmax), minimum temperature (Tmin), and extraterrestrialradiation (RA) were used for training and validation of temperature-based ANN model. Monthly reference ET by the ANN model also compared withparameter regionalized Hargreaves method for ANN model applicability evaluation. The ANN model evapotranspiration demonstrated more accordanceto FAO-56 PM evapotranspiration than the from parameter regionalized Hargreaves method(R-Hargreaves). The results of this study proposed thatdaily reference crop ET estimated by the ANN model could be used in the condition of no sufficient climate data.
Abstract
Evapotranpiration (ET) is one of the important factor in Hydrological cycle and irrigation planning. In this study, temperature-based artificial neuralnetwork (ANN) model for daily reference crop ET estimation was developed and compared with reference crop evapotranpiration ( ) from FAO-56Penman-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 (Tmax), minimum temperature (Tmin), and extraterrestrialradiation (RA) were used for training and validation of temperature-based ANN model. Monthly reference ET by the ANN model also compared withparameter regionalized Hargreaves method for ANN model applicability evaluation. The ANN model evapotranspiration demonstrated more accordanceto FAO-56 PM evapotranspiration than the from parameter regionalized Hargreaves method(R-Hargreaves). The results of this study proposed thatdaily reference crop ET estimated by the ANN model could be used in the condition of no sufficient climate data.
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