• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.111-121
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• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

• Korean Journal of Soil Science and Fertilizer
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• v.22 no.4
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• pp.301-306
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• 1989

For the agricultural utilization of Korean forest land resources, which constitutes most of country, the distribution of environment and soil physico-chemical properties of establishable grass lands were clarified. The surveyed data were analized for the reasonable utilization and management of establishable grass land. The results were as follows ; 1. About 50.2% of the grass lands to be established were located under the 200m in altitude. The higher the altitude was, the more the organic matter content. 2. Tall type grass species such as Miscanthus purpurascens, Purple eulalia, and Themeda Japonica covered 71.3% of the natural vegetation in the soils of grass land to be established. 3. The extent of sandy and clayey soils which might be limited in the establishment of grassland was only 3.3%, meanwhile majority of the soils were in the favourable condition for grassland that is about 94% have more than 20cm in available soil depth and about 60.5% of the soils have less than 10% of gravels and stones in the soil profiles. 4. The chemical properties of the prearranged grassland soils were worse than the established grasslands, especially in the content of available $P_2O_5$. 5. The amount of fertilizer recommended for meadow were 286kg of nitrogen per hectare, 271kg of phosphorus, 224kg of potassium and 2040kg of calcium per hectare, but for grazing land were 201, 204, 136 and 1920kg/ha respectively.